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Organisationseinheit der BAM
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Laser Powder Bed Fusion (PBF-LB/M) of AISI 316L stainless steel has gained popularity due to its exceptional capacity to produce complex geometries and hierarchical microstructures, which can increase the yield strength while maintaining good ductility. Nevertheless, owing to high thermal gradients encountered during the process, the as printed 316L stainless steel often exhibit microstructural heterogeneities and residual stresses, which can limit its performance in demanding environments. Hence, employing heat treatments which balance the reduction of residual stresses while retaining improved static strength may be beneficial in various scenarios and applications. This study investigates the impact of post-processing heat treatments on the microstructure of 316L stainless steel manufactured via PBF-LB/M, along with its correlation with micro-hardness properties. To this end, 6 different heat treatments, i.e., 450 °C for 4h, 700 °C for 1h, 700 °C for 3h, 800 °C for 1h, 800 °C for 3h, and 900 °C for 1h, were applied to different specimens and Vickers hardness measurements (HV1) were performed in all states. At 800 °C, although the cellular structure appears to be retained, there is an observable increase in cellular size. However, while treatments exceeding 900 °C indicate no significant grain growth compared to other conditions, the cellular structure is entirely dissolved, which leads to a reduced Vickers hardness. The effect of the heat treatments on other microstructural features such as grain size and morphology, melt pool boundaries (MPB), crystallographic texture, chemical segregation, dispersoids and phase stability are also discussed in the present work
The general term additive manufacturing (AM) encompasses processes that enable the production of parts in a single manufacturing step. Among these, laser powder bed fusion (PBF-LB) is one of the most commonly used to produce metal components. In essence, a laser locally melts powder particles in a powder bed layer-by-layer to incrementally build a part. As a result, this process offers immense manufacturing flexibility and superior geometric design capabilities compared to conventional processes. However, these advantages come at a cost: the localized processing inevitably induces large thermal gradients, resulting in the formation of large thermal stress during manufacturing. In the best case, residual stress remains in the final parts produced as a footprint of this thermal stress. Since residual stress is well known to exacerbate the structural integrity of components, their assessment is important in two respects. First, to optimize process parameter to minimize residual stress magnitudes. Second, to study their effect on the structural integrity of components (e.g., validation of numerical models). Therefore, a reliable experimental assessment of residual stress is an important factor for the successful application of PBF-LB. In this context, diffraction-based techniques allow the non-destructive characterization of the residual stress. In essence, lattice strain is calculated from interplanar distances by application of Braggs law. From the known lattice strain, macroscopic stress can be determined using Hooke’s law. To allow the accurate assessment of the residual stress distribution by such methods, a couple of challenges in regard of the characteristic PBF-LB microstructures need to be overcome.
This presentation highlights some of the challenges regarding the accurate assessment of residual stress in PBF-LB on the example of the Nickel-based alloy Inconel 718. The most significant influencing factors are the use of the correct diffraction elastic constants, the choice of the stress-free reference, and the consideration of the crystallographic texture. Further, it is shown that laboratory X-ray diffraction methods characterizing residual stress at the surface are biased by the inherent surface roughness. Overall, the impact of the characteristic microstructure is most significant for the selection of the correct diffraction elastic constants. In view of the localized melting and solidification, no significant gradients of the stress-free reference are observed, even though the cell-like solidification sub-structure is known to be heterogeneous on the micro-scale.
The damage mechanisms of metallic components produced by process laser powder bed fusion differ significantly from those typically observed in conventionally manufactured variants of the same alloy. This is due to the unique microstructures of additively manufactured materials. Herein, the focus is on the study of the evolution of creep damage in stainless steel 316L specimens produced by laser powder bed fusion. X-ray computed tomography is used to unravel the influence of the process-specific microstructure from the influence of the initial void distribution on creep damage mechanisms. The void distribution of two specimens tested at 600 °C and 650 °C is analyzed before a creep test, after an interruption, and after fracture. The results indicate that the formation of damage is not connected to the initial void distribution. Instead, damage accumulation at grain boundaries resulting from intergranular cracking is observed.
Laser powder bed fusion (PBF-LB/M) of metallic alloys is a layer-wise additive manufacturing process that provides significant scope for more efficient designs of components, benefiting performance and weight, leading to efficiency improvements for various sectors of industry. However, to benefit from these design freedoms, knowledge of the high produced induced residual stress and mechanical property anisotropy associated with the unique microstructures is critical. X-ray and neutron diffraction are considered the benchmark for non-destructive characterization of surface and bulk internal residual stress. The latter, characterized by the high penetration power in most engineering alloys, allows for the use of a diffraction angle close to 90° enabling a near cubic sampling volume to be specified. However, the complex microstructures of columnar growth with inherent crystallographic texture typically produced during PBF-LB/M of metallics present significant challenges to the assumptions typically required for time efficient determination of residual stress. These challenges include the selection of an appropriate set of diffraction elastic constants and a representative lattice plane suitable for residual stress analysis. In this contribution, the selection of a suitable lattice plane family for residual stress analysis is explored. Furthermore, the determination of an appropriate set of diffraction and single-crystal elastic constants depending on the underlying microstructure is addressed.
In-situ loading experiments have been performed at the Swiss Spallation Neutron Source with the main scope to study the deformation behaviour of laser powder bed fused Inconel 718. Cylindrical tensile bars have been subjected to an increasing mechanical load. At pre-defined steps, neutron diffraction data has been collected. After reaching the yield limit, unloads have been performed to study the accumulation of intergranular strain among various lattice plane families.
Metallbasierte additive Fertigungsverfahren werden zunehmend industriell zur Anfertigung von komplex geformten Komponenten eingesetzt. In diesem Zusammenhang ist das Laser-Pulverbettschweißen von Metall (PBF-LB/M) ist ein weitläufig genutztes Verfahren. Im PBF-LB/M-Prozess werden lagenweise aufgetragene Metallpulverschichten selektiv mittels eines Lasers aufgeschmolzen. Die Entstehung von internen Fehlstellen (bspw. Porosität, Lunker oder Risse) während des Fertigungsvorgangs stellt ein ernstzunehmendes Risiko für die Bauteilsicherheit und somit für die weitere industrielle Etablierung des Verfahrens dar. Die Entstehung von Fehlstellen hängt eng mit lokalen Änderungen der thermischen Historie des Bauteils zusammen. Mit Hilfe von thermografischen Kameras zur Prozessüberwachung kann die thermische Historie bereits während der Fertigung erfasst werden. Damit eröffnet sich die Möglichkeit, die Entstehung von Fehlstellen anhand der thermografischen Daten vorherzusagen und somit potenziell Kosten für eine nachgelagerte Qualitätssicherung einzusparen.
In diesem Beitrag soll die Modellierung der Fehlstellenvorhersage anhand thermografischer Prozessdaten diskutiert werden. Hierbei liegt ein Schwerpunkt auf der Fragestellung, mit welcher Genauigkeit unterschiedliche Formen von Fehlstellen, im speziellen Anbindungsfehler und Keyhole-Porosität, auf lokaler Bauteilebene vorhergesagt werden können. Weiterhin werden verschiedenen Modelltypen aus dem Bereich des Maschinellen Lernens auf ihre Eignung für die Fehlstellenvorhersage verglichen. Ein weiterer zentraler Aspekt in diesem Zusammenhang ist die Untersuchung der Eingangsdaten des Modells auf ihre Relevanz für das Vorhersageergebnis.
Als Datengrundlage für die durchgeführten Untersuchungen dienen die Fertigungsprozesse von zwei identischen Haynes-282-Bauteilen (Nickel-Basislegierung), welche mit Hilfe einer im kurzwelligen Infrarotbereich arbeitenden Thermografiekamera überwacht wurden. Das Bauteildesign umfasste lokale Bereiche, in denen mit Hilfe einer Parametervariation die Entstehung von Fehlstellen forciert wurde. Um die Position und Größe der entstandenen Defekte zu quantifizieren, wurden beide Bauteile nach erfolgter Fertigung mittels Computertomografie (CT) geprüft. Im Rahmen der Datenvorbereitung für die Modellierung erfolgte eine Reduzierung der erhobenen Thermogramme zu physikalisch-interpretierbaren Merkmalen (bspw. Schmelzbadfläche oder Zeit-über-Schwellwert). Weiterhin erfolgte eine Registrierung der thermografischen Daten mit den Fehlstellen-Referenzdaten der CT, um eine exakte örtliche Überlagerung von thermischer Information und lokalem Fehlstellenbild zu erzielen. Zur Ermöglichung einer lokalen Fehlstellenvorhersage wurden die thermografischen Daten schichtweise in kleinteiligen Volumina angeordnet, welche als Eingangsgröße für die genutzten ML-Algorithmen dienten.
Die Ergebnisse der Untersuchungen zeigen, dass sich die Porosität auf Bauteilschichtebene mit einer hohen Genauigkeit vorhersagen lässt. Eine Vorhersage der Porosität auf lokaler Bauteilebene erweist sich noch als herausfordernd. Die erprobten ML-Algorithmen zeigen vergleichbare Ergebnisse, obwohl ihnen unterschiedliche Modellierungsannahmen zugrunde liegen und sie variierende Komplexität aufweisen. Mit Hilfe der erzielten Erkenntnisse eröffnet sich die Möglichkeit, Rückschlüsse auf die gewählte Prozessüberwachungshardware und Datenvorverarbeitung zu ziehen und somit langfristig die Leistungsfähigkeit von Modellen zur Fehlstellenvorhersage zu verbessern.
Development of representative test specimens by thermal history transfer in laser powder bed fusion
(2024)
The use of components manufactured by laser powder bed fusion (PBF LB/M) and subjected to fatigue loading is still hampered by the uncertainty about the homogeneity of the process results. Numerous influencing factors including the component’s geometry contribute to the risk of process instability and resulting inhomogeneity of properties. This drastically limits the comparability of different built parts and requires expensive full component testing. The thermal history as the spatiotemporal temperature distribution has been identified as a major cause for flaw formation. Therefore, it can be hypothesized that a similar thermal history between components and test specimens enhances their comparability. Following this assumption, a strategy is developed to transfer the intrinsic preheating temperature as a measure of comparability of thermal histories from a region of interest of a complex component to a simple test specimen. This transfer concept has been successfully proved by the use of FEM-based macroscale thermal simulations, validated by calibrated infrared thermography. An adoption of the specimen manufacturing process by the adjustment of the inter layer times was established to manufacture specimens which are representatives of a specific region of a large-scale component in terms of the thermal history similarity criterion. The concept is schematically illustrated in Figure 1 and was demonstrated using a pressure vessel geometry from the chemical industry.
Direct energy deposition additive manufacturing technologies that utilize an electric arc have great potential for generating large volume metal components. However, selecting process parameters that yield the desired near net shape design and requested mechanical component behavior is not a trivial task due to the complex relationship between all process parameters and material characteristics. This presentation exemplifies the application of a newly developed solid welding wire doped with TiB to enhance grain refinement in the deposited metal for additive manufacturing based on DED-Arc of high-strength precipitation hardening AlMgSi-aluminum alloys. It is worth noting that the solid wire is the result of our preliminary metallurgical studies on grain refinement in aluminum weld metal.
Consequently, research focuses on the correlation between process parameters and component quality to understand the underlying mechanisms. This is crucial for evaluating a robust process parameter space that yields component quality in line with corresponding standards which are mainly taken from welding technology.
Specifically, we examine component quality by analyzing pore size and distribution, as well as grain morphology. To enhance the mechanical properties of the deposited metal, a post-weld heat treatment was conducted, comprising of solution treatment, quenching, and artificial aging. The study also evaluates the effects of various heat treatment strategies on the final mechanical properties of the material.
To demonstrate the applicability of 3D metal printing of high-strength aluminium alloys, a more complex demonstrator was created. It has been shown that DED-Arc can produce high-volume aluminium parts with the same quality as the corresponding subtractive processing strategy.
Additionally, the entire additive manufacturing chain has been digitally integrated, enabling traceability of all relevant process steps, which is essential for reliable subsequent quality assessment.
Die metallische additive Fertigung hat in den letzten Jahren in der industriellen Fertigung zunehmend an Bedeutung gewonnen. Hierbei dominiert das Laser-Pulverbettschweißen von Metallen (PBF/LB-M) die Fertigung von kleinformatigen Bauteilen mit hoher Oberflächengüte. Die anspruchsvolle und kostspielige Qualitätssicherung stellt aber weiterhin ein Hindernis für eine breitere und kostengünstigere Anwendung der additiven Fertigung dar. Dies resultiert teilweise aus fehlenden zuverlässigen In-situ-Monitoringsystemen. Belastbarere Prozessüberwachungsdaten würden eine oft erforderliche teure nachgelagerte Prüfung mittels Computertomografie entbehrlich machen. Die Aufzeichnung der thermischen Signaturen des Aufbauprozess mittels Thermografie-Kameras zeigen hier vielversprechende Ergebnisse. Eine Korrelation zu auftretender Porosität, Delaminationen und Deformationen scheinen möglich. Die geringe räumliche Auflösung und die hohen Anschaffungskosten für thermografische Kamerasysteme stehen jedoch einer größeren industriellen Nutzung im Wege.
Ein bereits industriell angewendeter Ansatz zur in-Situ Überwachung des PBF-LB/M Prozesses ist die Optische Tomografie (OT). Hierbei wird die emittierte Prozessstrahlung jeder Bauteilschicht mittels einer hochauflösenden günstigen Kamera für den sichtbaren Wellenlängenbereich in einer Langzeitbelichtung dokumentiert. Die zeitliche Information der emittierten Strahlung geht hierbei verloren. Der gesamte Bauprozess kann jedoch in einem vergleichsweise kleinen Datensatz dokumentiert werden (ein Bild pro Schicht). Eine direkte Korrelation zu auftretenden Defekten gestaltet sich aufgrund der reduzierten thermischen Informationsdichte jedoch schwierig.
In diesem Beitrag soll deshalb das Prinzip der Multispektralen Optischen Tomografie (MOT) vorgestellt und erste Messergebnisse an der Forschungsanlage SAMMIE diskutiert werden. Bei der MOT handelt es sich um eine Übertragung des Prinzips der Quotientenpyrometrie auf das etablierte Verfahren der Optischen Tomografie. Die auftretende Prozessstrahlung wird in mehreren Wellenlängenbereichen ortsaufgelöst über die gesamte Bauplattform erfasst und zeitlich in einer Langzeitbelichtung integriert. Hierbei kommen günstige Kamerasysteme für den sichtbaren Wellenlängenbereich zum Einsatz.
Das erfasste Signal I jedes Bildpixels für jeden separat erfassten Wellenlängenbereich kann als Maß für das zeitliche Integral der spezifischen Ausstrahlung M des Schmelzbades in diesem Wellenlängenbereich gesehen werden. Nach dem Stefan-Boltzmann-Gesetz hängt die abgestrahlte thermische Leistung P eines idealen Schwarzen Körpers in der vierten Potenz von dessen absoluten Temperatur T ab. Wird nur, wie z.B. bei der klassischen OT angewendet, der nahinfrarote Wellenlängenbereich betrachtet, lässt sich mit dem Planck’schen Strahlungsgesetz sogar eine Proportionalität zur siebten Potenz der Temperatur zeigen. Deshalb liegt ein starker Einfluss der maximal auftretenden Oberflächentemperatur Tmax auf das erfasste Messsignal vor.
Das erfasste Signal I wird aber auch durch die spektrale Transmission τ der verwendeten optischen Komponenten des Kamera-Setups, z.B. Filter und Objektive, durch die spektrale Sensitivität S der verwendeten Kamera-Sensoren und den nur sehr schwer zu bestimmenden Emissionsgrad ε der emittierenden (flüssigen) Oberfläche beeinflusst.
In einer ersten Näherung wird das Schmelzbad hier als Graukörper, also ein Körper mit wellenlängenunabhängigem Emissionsgrad ε, betrachtet. Basierend auf dieser Annahme und vermessenen optischen Eigenschaften des verwendeten Systems ist es möglich, eine erste Schätzung der maximalen Oberflächentemperatur Tmax vorzunehmen, selbst ohne genaue Kenntnis des tatsächlichen Emissionsgrades ε. Dies wird durch die Anwendung des Planck‘schen Strahlungsgesetzes und die Quotienten Bildung aus den einzelnen erfassten Signalen I ermöglicht.
Auch bei diesem Verfahren geht die zeitliche Information einer Schicht, also das Aufwärm- und Abkühlverhalten des Schmelzbades, verloren. Zudem sind die Messergebnisse in Hinblick auf tatsächlich gemessene „maximal auftretende Oberflächentemperatur“ mit gebotener Zurückhaltung zu interpretieren. Trotzdem konnten erste Ergebnisse bereits zeigen, dass die MOT-Daten auch in Bereichen mit Doppelbelichtungen (das teilweise notwendige mehrfache Scannen eines Bereiches mittels des Fertigungslasers) im Gegensatz zur klassischen OT erwartbare Maximaltemperaturen liefern. Abbildung 1 zeigt das erfasste Messergebnis für drei aufeinanderfolgende Schichten eines Bauteils einmal mit MOT (links) und einmal mit einfacher OT (rechts). Deutlich zu erkennen ist das durch die doppelte Belichtung hohe Signal bei der OT. Die Daten der MOT zeigen hier keine erhöhten Werte.
Um die ermittelten Temperaturwerte mittels MOT besser einordnen zu können, sind u.a. vergleichende Messungen an Referenzmaterialien geplant. Um die Auswertung der gemessenen Daten zu verbessern, wird zudem der Zeitverlauf des Abkühlens und Aufheizens des Schmelzbades sowie die Einflüsse von Prozessbeiprodukten wie Schmauch und Spritzer näher untersucht. Auch werden Messungen zum Emissionsgrad ε an additiv gefertigten Proben und Metallschmelzen vorgenommen.
Im additiven Fertigungsprozess Laser-Pulverbettschweißen wird Metallpulver lagenweise mittels eines Lasers aufgeschmolzen, um Bauteile zu generieren. Hierbei werden die Eigenschaften der Bauteile zu einem großen Teil durch die im Verlauf des Prozesses vorliegenden Temperaturen bestimmt. Dies beinhaltet unter anderem Materialeigenschaften wie Mikrostruktur, Härte, thermische und elektrische Leitfähigkeiten sowie die Ausbildung von Defekten wie z.B. Anbindungsfehler, Keyhole-Porosität (Gaseinschlüsse) oder auch die Ausbildung von Rissen. Zur Überwachung bzw. Vorhersage dieser Eigenschaften sowie zum Abgleich von Simulationen ist eine orts- und zeitaufgelöste Messung der Temperaturverteilung im Prozess daher von herausragender Bedeutung. In der Industrie kommen optische Verfahren, die auf der Messung der thermischen Strahlung basieren, regelmäßig zum Einsatz. Allerdings dienen diese bislang nur der statistischen Auswertung und der Identifikation von Abweichungen vom Normalprozess. Der quantitativen Auswertung zur Temperaturbestimmung stehen aktuell noch eine Vielzahl von Herausforderungen entgegen. Einerseits stellt der Prozess an sich hohe Anforderungen an die Datenerfassung und -auswertung: der Emissionsgrad verändert sich dynamisch im Prozess und lokale Schmauchbildung sorgt für potenzielle Absorption oder Streuung der thermischen Strahlung oder auch des Fertigungslasers. Weiterhin stellt der hochdynamische Prozess hohe Anforderungen an Orts- und Zeitauflösung der eingesetzten Sensorik (z.B. Kameratechnik). Andererseits erschweren an üblichen kommerziell erhältlichen Fertigungsanlagen praktische Hindernisse wie eine eingeschränkte optische Zugänglichkeit und der fehlende Zugriff auf die Anlagensteuerung sowie fehlende Möglichkeiten der Synchronisation der Messtechnik mit dem Prozess eine eingehende Untersuchung dieser Effekte.
Um letztere Hindernisse zu umgehen, wurde an der BAM die Forschungsanlage SAMMIE (sensor-based additive manufacturing machine) entwickelt. Einerseits bietet das System alle Möglichkeiten, die auch übliche kommerzielle Systeme bieten. Dies beinhaltet die Fertigung ganzer Bauteile (maximale Größe ca. 65mm x 45 mm x 30 mm) und den Einsatz einer Inertgasatmosphäre inkl. gefiltertem Schutzgasstrom. Andererseits bietet es aber auch einen besonders kompakten Bauraum, um die Sensorik möglichst nah an den Prozess führen zu können, sechs optische Fenster zur Prozessbeobachtung aus unterschiedlichen Winkeln und die Möglichkeit der Prozessbeobachtung koaxial zum Fertigungslaser. Des Weiteren besteht eine einfache Austauschbarkeit aller Fenster, Spiegel und Strahlteiler, um den gesamten optischen Pfad der aktuellen Messaufgabe flexibel anzupassen. Die komplette Anlagensteuerung ist eine Eigenentwicklung und bietet daher auch völlige Anpassbarkeit. Eine synchrone und frei konfigurierbare Triggerung diverser Sensoriken und synchrone Datenerfassung bieten maximale Kontrolle über die Sensorsteuerung.
Dieser Beitrag gibt einen Überblick über die Fertigungsanlage SAMMIE. Wissenschaftliche Ergebnisse sowie laufende Arbeiten an der Anlage werden in weiteren Beiträgen vorgestellt.
Das Ausbreitungsverhalten geführter Ultraschallwellen ermöglicht die großflächige Prüfung von Platten und schalenförmigen Bauteilen wie Rohren und Laminaten auf Fehlstellen von wenigen Prüfpunkten aus. Während die beschränkte Divergenz der geführten Wellen die Ultraschallprüfung begünstigt, erschwert das dispersive und multimodale Verhalten der Lamb-Wellen die Auswertung der Ultraschallsignale. Die dispersive und multimodale Wellenausbreitung verkompliziert die Bestimmung der Fehlerposition bei der Auswertung der Geschwindigkeiten einzelner Wellenpakete. Zudem ist es herausfordernd, einen einfachen Zusammenhang zwischen den Reflexionen der Fehlstelle und deren Größe und Form herzustellen. Eine Möglichkeit zur genauen Bestimmung der Fehlerposition und -geometrie bietet der direkte Vergleich der Messsignale mit den Signalen aus einem Simulationsmodell. Die Nachbildung des Schadens im Simulationsmodell stellt ein inverses Problem dar, das iterativ gelöst werden kann, indem ein Vorwärtsmodell immer weiter optimiert wird. Klassische Ansätze wie die Finite Elemente Methode (FEM) sind für die Simulation von Ultraschallwellen aufgrund der kleinen Wellenlängen im Vergleich zur Bauteilgröße meist ineffizient. Aus diesem Grund basiert das vorgestellte Vorwärtsmodell auf der semi-analytischen Scaled Boundary Finite Element Method (SBFEM), die große Teile der Wellenausbreitung analytisch berechnet. In diesem Beitrag wird die Validierung des zweidimensionalen Modells an Platten mit einer rechteckigen Nut als Ersatzfehler präsentiert und es werden erste Schritte zur Validierung von 3D-Modellen vorgestellt.
Das Ausbreitungsverhalten geführter Ultraschallwellen ermöglicht die großflächige Prüfung von Platten und schalenförmigen Bauteilen wie Rohren und Laminaten auf Fehlstellen von wenigen Prüfpunkten aus. Während die beschränkte Divergenz der geführten Wellen die Ultraschallprüfung begünstigt, erschwert das dispersive und multimodale Verhalten der Lamb-Wellen die Auswertung der Ultraschallsignale. Die dispersive und multimodale Wellenausbreitung verkompliziert die Bestimmung der Fehlerposition bei der Auswertung der Geschwindigkeiten einzelner Wellenpakete. Zudem ist es herausfordernd, einen einfachen Zusammenhang zwischen den Reflexionen der Fehlstelle und deren Größe und Form herzustellen. Eine Möglichkeit zur genauen Bestimmung der Fehlerposition und -geometrie bietet der direkte Vergleich der Messsignale mit den Signalen aus einem Simulationsmodell. Die Nachbildung des Schadens im Simulationsmodell stellt ein inverses Problem dar, das iterativ gelöst werden kann, indem ein Vorwärtsmodell immer weiter optimiert wird. Klassische Ansätze wie die Finite Elemente Methode (FEM) sind für die Simulation von Ultraschallwellen aufgrund der kleinen Wellenlängen im Vergleich zur Bauteilgröße meist ineffizient. Aus diesem Grund basiert das vorgestellte Vorwärtsmodell auf der semi-analytischen Scaled Boundary Finite Element Method (SBFEM), die große Teile der Wellenausbreitung analytisch berechnet. In diesem Beitrag wird die Validierung des zweidimensionalen Modells an Platten mit einer rechteckigen Nut als Ersatzfehler präsentiert und es werden erste Schritte zur Validierung von 3D-Modellen vorgestellt.
Various software products for the simulation of industrial X-ray radiography have been developed in recent years (e.g., aRTist 2, CIVA CT, Scorpius XLab, SimCT, Wilcore) and their application potential has been shown in numerous works. However, full systematic approaches to characterise a specific CT system for these simulation software products to obtain a truthful digital twin are still missing. In this contribution, we want to present two approaches to obtain realistic grey values in X-ray projections in aRTist 2 simulations based on measured projections. In aRTist 2, the displayed grey value of a pixel is based on the energy density incident on that pixel.
The energy density is calculated based on the X-ray tube spectrum, the attenuation between source and detector as well as an energy-dependent sensitivity curve of the detector. The first approach presented in this contribution uses the sensitivity curve as a free modelling parameter. We measured the signal response at different thicknesses of Al EN-AW6082 at different tube voltages (i.e., different tube spectra). We then regarded the grey values displayed by these projections as a data regression respectively an optimisation problem and obtained the sensitivity curve that is best able to reproduce the measured behaviour in aRTist 2. The resulting sensitivity curve does not necessarily hold physical meaning but is able to simulate the real system behaviour in the simulation software.
The second approach presented in this contribution is to estimate the sensitivity curve based on assumptions about the characteristics of the scintillation detector (e.g., scintillator material, scintillator thickness and signal processing characteristics). For this approach, a linear response function (linear relationship between the deposited energy per pixel and the resulting grey value) is assumed. If the detector characteristics, which affect the simulated deposited energy, are properly modelled, the slope and offset of the response function to match the measured grey values should be the same for different tube spectra. As the offset is constant and given by the grey values measured at no incident radiation, the slope is the remaining parameter to evaluate the success of the detector modelling. We therefore adapted the detector characteristics by changing the detector setup until the slope was nearly the same for all measured tube spectra. We are aware that the resulting parameters of the scintillator material and thickness might not be the real ones, but with those modelling parameters we are able to simulate realistic grey values in aRTist 2. Both of those approaches could potentially be a step forward to a full systematic approach for a digital twin of a real CT system in aRTist 2.
Die additive Fertigung von Metallen hat inzwischen einen Reifegrad erreicht, der einen Einsatz in vielen Industriezweigen ermöglicht oder in greifbare Nähe rückt. Die Vorteile liegen vor allem in der Möglichkeit der Fertigung komplexer Bauteile, die sich konventionell nicht oder nur sehr aufwändig produzieren lassen, sowie in der Fertigung von hochindividualisierten Bauteilen in kleinen Stückzahlen. Allerdings ist der additive Fertigungsprozess hoch komplex und fehleranfällig. Um eine insbesondere für sicherheitsrelevante Bauteile notwendige Qualitätskontrolle zu gewährleisten, ist aktuell aufwändige nachgelagerte ZfP der einzelnen Bauteile notwendig. Alternativen könnten die In-situ-Prozessüberwachung und -prüfung bieten, die aktuell aber noch keinen ausreichenden Entwicklungsstand erreicht haben. Industrielle Fertigungsanlagen bieten keine oder nur geringe Flexibilität und Zugänglichkeit, um umfangreiche Untersuchungen auf diesem Gebiet zu ermöglichen. Daher haben wir an der BAM ein System für den Prozess des selektiven Laserschmelzens (PBF-LB/M) entwickelt, genannt SAMMIE. Es bietet eine komplett offene Systemarchitektur mit voller Kontrolle über den Prozess und flexiblem Zugang zur Baukammer, z.B. optisch sowohl direkt als auch koaxial zum Fertigungslaser. In diesem Beitrag stellen wir das System vor und zeigen erste experimentelle Ergebnisse der In-situ-Überwachung und -prüfung: Thermografische Schmelzbadüberwachung, optische Tomografie und In-situ-Laserthermografie. SAMMIE ermöglicht uns grundlegende Untersuchungen, die helfen werden, die In-situ-Prozessüberwachung und -prüfung weiterzuentwickeln, neue Erkenntnisse über die additive Fertigung zu gewinnen und die Sicherheit und Zuverlässigkeit des Prozesses zu verbessern.
For a deep process understanding of the laser powder bed fusion process (PBF-LB/M), recording of the occurring surface temperatures is of utmost interest and would help to pave the way for reliable process monitoring and quality assurance. A notable number of approaches for in-process monitoring of the PBF-LB/M process focus on the monitoring of thermal process signatures. However, due to the elaborate calibration effort and the lack of knowledge about the occurring spectral directional emissivity, only a few approaches attempt to measure real temperatures. In this study, to gain initial insights into occurring in the PBF-LB/M process, measurements on PBF-LB/M specimens and metal powder specimens were performed for higher temperatures up to T = 1290 °C by means of the emissivity measurement apparatus (EMMA) of the Center for Applied Energy Research (CAE, Wuerzburg, Germany). Also, measurements at ambient temperatures were performed with a suitable measurement setup. Two different materials—stainless steel 316L and aluminum AlSi10Mg—were examined. The investigated wavelength λ ranges from the visible range (λ-VIS = 0.40–0.75 µm) up to the infrared, λ = 20 µm. The influence of the following factors were investigated: azimuth angle φ, specimen temperature TS, surface texture as for PBF-LB/M surfaces with different scan angles α, and powder surfaces with different layer thicknesses t.
This paper explores combining a gimbal-mounted tunable diode laser absorption spectroscopy (TDLAS) sensor and a video camera to create a virtual gas camera for methane leak detection. This provides a low-to-zero-cost extension of typical TDLAS gas tomography systems. A prototype setup mounted on a ground robot is evaluated. Results acquired using a simulated methane leak show the feasibility of the virtual gas camera, accurately detecting methane leaks by overlaying concentrations onto a visual image. While the acquisition time is significantly longer than for traditional gas cameras, potential enhancements are discussed. The study concludes that the virtual gas camera is feasible and useful, despite its longer acquisition time. It serves as a valuable software-only addition to typical TDLAS gas tomography systems, offering quickly-available on-site data augmentation for visual leak assessment at low-to-zero cost.
This paper outlines significant advancements in our previously developed aerial gas tomography system, now optimized to reconstruct 2D tomographic slices of gas plumes with enhanced precision in outdoor environments. The core of our system is an aerial robot equipped with a custom-built 3-axis aerial gimbal, a Tunable Diode Laser Absorption Spectroscopy (TDLAS) sensor for CH4 measurements, a laser rangefinder, and a wide-angle camera, combined with a state-of-the-art gas tomography algorithm. In real-world experiments, we sent the aerial robot along gate-shaped flight patterns over a semi-controlled environment with a static-like gas plume, providing a welldefined ground truth for system evaluation. The reconstructed cross-sectional 2D images closely matched the known ground truth concentration, confirming the system’s high accuracy and reliability. The demonstrated system’s capabilities open doors for potential applications in environmental monitoring and industrial safety, though further testing is planned to ascertain the system’s operational boundaries fully.
Early detection of fatigue cracks and accurate measurements of the crack growth play an important role in the maintenance and repair strategies of steel structures exposed to cyclic loads during their service life. Observation of welded connections is especially of high relevance due to their higher susceptibility to fatigue damage. The aim of this contribution was to monitor fatigue crack growth in thick welded specimens during fatigue tests as holistically as possible, by implementing multiple NDT methods simultaneously in order to record the crack initiation and propagation until the final fracture. In addition to well-known methods such as strain gauges, thermography, and ultrasound, the crack luminescence method developed at the Bundesanstalt für Materialforschung und -prüfung (BAM), which makes cracks on the surface particularly visible, was also used. For data acquisition, a first data fusion concept was developed and applied in order to synchronize the data of the different methods and to evaluate them to a large extent automatically. The resulting database can ultimately also be used to access, view, and analyze the experimental data for various NDT methods. During the conducted fatigue tests, the simultaneous measurements of the same cracking process enabled a comprehensive comparison of the methods, highlighting their individual strengths and limitations. More importantly, they showed how a synergetic combination of different NDT methods can be beneficial for implementation in large-scale fatigue testing but also in monitoring and inspection programs of in-service structures - such as the support structures of offshore wind turbines.
Es wird eine Studie zur Charakterisierung eines anisotropen Stahls vorgestellt, bei der Ultraschalluntersuchungen mit Mikrostrukturanalysen verbunden werden. Das Material weist hohe Festigkeit und Korrosionsbeständigkeit auf, zugleich ist mit anisotropen Eigenschaften die mechanischen und betrieblichen Eigenschaften beeinflussen zu rechnen. Vorläufige Ergebnisse lassen vermuten, dass weitere Untersuchungen notwendig sind, um die Fähigkeiten und Grenzen des Materials genau zu bestimmen. Es wird ein systematischer Ansatz mit Array- Prüfköpfen, Time-of-Flight Diffraction (TOFD) Technik und mikrostrukturellen Untersuchungen angewendet, um die Wechselwirkung zwischen Anisotropie und Mikrostruktur des Stahls zu analysieren. Ultraschallprüfungen mit der TOFD-Technik und in Tauchtechnik liefern Einblicke in das anisotrope Verhalten des Werkstoffes, einschließlich entsprechenden Kornorientierung, Dämpfung und Schallgeschwindigkeitsvariation. Diese Messungen führen in Verbindung mit mikrostrukturellen Analysen zu einem tieferen Verständnis des Materialverhaltens. Unser Hauptziel ist es, ein Framework zu erstellen, welches die Ultraschallantwort anisotroper Materialien mit ihren mikroskopischen Struktureigenschaften verbindet. Die vorgestellte Methodik ermöglicht eine zerstörungsfreie und zügige Bewertung der Materialintegrität, was besonders bei der Anwendung von Hochleistungsmaterialien relevant ist. Durch diesen integrativen Ansatz werden verschiedener Charakterisierungsmethoden kombiniert, um ein umfassenderes Materialverständnis zu erreichen.
This study explores the acceleration of material design in the concrete industry, focusing on improving carbonation resistance, a key factor in the durability of concrete structures. Traditional tests for carbonation resistance are lengthy, but with the construction industry aiming for sustainable production, finding a balance between carbonation resistance and CO2 footprint is crucial. Our research employs two innovative methods: 1. Applying the Sequential Learning App for Materials Discovery (SLAMD), an AI materials design framework, to an extensive dataset of real-world concrete compositions to selectively test materials that meet market demands: maximum durability, optimal eco-durability, and the best cost-durability trade-off. 2. Investigating 1H Nuclear Magnetic Resonance (NMR) relaxometry as a quick alternative for characterizing carbonation behavior, as it saves time compared to traditional tests and assesses the complete material's pore space. Specific NMR features are then integrated into the material design model, with the model's performance compared against traditional approaches. The results of our study are compelling, demonstrating that materials can be precisely tailored to meet specific requirements with minimal data points. This marks a significant stride in the concrete industry, indicating that NMR-based, low-fidelity surrogate characterizations, combined with a focused, data-driven design approach, can substantially accelerate the development of durable, sustainable concrete mixtures.
The stress-induced tetragonal to monoclinic (t-m) zirconia phase transformation can provide a certain degree of plasticity to Ceria-stabilized (Ce-TZP) zirconia-based composites. Characterizing and monitoring this phase transition on a millimeter-size range, within the bulk and in-situ remains a challenge. In this work, the mechanical behavior of Ce-TZP based composite was studied in tension, combining microscopy and synchrotron Xray refraction techniques. In contrast with microscopy methods, which only provide surface information, X-ray refraction radiography (SXRR) allowed the visualization of all the transformation bands, over the entire length and thickness of tested specimens, opening up new avenues for in-situ stress-induced t-m transformation studies.
In this presentation, the results of the determination of the diffraction and single-crystal elastic constants of laser powder bed fused Inconel 718 are presented. The analysis is based on high-energy synchrotron diffraction experiments performed at the Deutsches Elektronen-Synchrotron. It is shown that the characteristic microstructure of laser powder bed fused Inconel 718 impacts the elastic anisotropy and therefore the diffraction and single-crystal elastic constants. Finally, the consequences on the diffraction-based residual stress determination of laser powder bed fused Inconel 718 are discussed.
Ziel des FuE-Vorhabens ist die Entwicklung, Aufbau und Validierung eines gasto-mographischen Messsystems basierend auf stationärer und mobiler Sensorik zum Emissionsmonitoring in kommunalen Kläranlagen. Die Gastomographie basiert hierbei im Wesentlichen auf, aus unterschiedlichen Sichtwinkeln aufgenommenen, integralen Konzentrationsmessungen, anhand derer eine Rekonstruktion der Gasverteilung erfolgt. Das FuE-Projekt kombiniert hierfür stationäre Sensornetzwerke mit luftgestützten und bodengebundenen Robotersystemen in einem System. Letztere werden mit Reflektoren und/oder Gasdetektoren ausgestattet. Hierfür werden Open-Path-Gasmesstechnik basierend auf Tunable Diode Laser Ab-sorption Spectroscopy (TDLAS, primär CH4 in ppm·m) und In-situ-Gassensorik (CH4, ppm) auf Basis von z.B. Infrarot eingesetzt. Dies sind zwei komplementäre Methoden der Gasmessung: Die In-situ-Gassensorik ermöglicht Punktmessungen, wohingegen TDLAS-Sensoren Gaskonzentrationen integral über offene Messstre-cken von bis zu 60 m gegen Oberflächen messen. Die In-situ-Gassensorik wird für Referenzmessungen und ggf. zur Erhöhung der Rekonstruktionsqualität zum Ein-satz kommen. Die wesentlichen Neuheiten des Projekts sind:
• 2D-Gastomographie auf Basis eines mit TDLAS-basierter Open-Path-Gasmesstechnik und Reflektoren ausgestatteten heterogenen Messsystems.
• CT-basierte Rekonstruktionsalgorithmen, adaptiert an die komplexen Rahmenbedingungen.
• Validierung des Messsystems anhand realer Messungen auf Kläranlagen.
Ultrasonic guided waves interacting with complex geometrical features are of high interest in the SHM field. For example, investigations into the extent to which a small change in defect geometry affects wave propagation have applications in Probability of Detection and defect reconstruction. These fields have to be supported by numerical tools aiming to retrieve accurate and reliable results and, thus, more realistic modeling.
Due to the short wavelengths of ultrasonic waves and the relatively large domains in which the waves propagate, fine grid resolution for the entire domain is usually not possible due to limited computational resources. One solution is to partition the domain into different subdomains and use a specific, efficient approach for each subdomain.
This contribution shows a combination of methods that aims to study these wave defect interactions in an elastic media. Firstly we introduce high-order 3D meshes that can resolve very fine geometrical details and are based on an Octree discretisation technique that employs special transition shape functions to resolve the hanging nodes that may appear due to the nature of the method. Afterward, the Octree mesh is embedded in a prismatic wave-guide based on the semi-analytical formulation of the SBFEM in 3D. To couple the different domains, we employ the mortar method, which enforces the continuity of the wave field across the internal boundaries of the domains. Examples show the power of the approach especially when it comes to parametric analysis.
For structural health monitoring systems or non-destructive testing, it is crucial to study the interactions of ultrasonic-guided waves with inhomogeneities or damage in structural components. Simulation of these interactions poses a challenge.
After the wave-damage interaction, the numerical model must reproduce features like mode conversion or wave scattering. Mathematically, damages are discontinuities in a computational domain, and each interacts diversely depending on its geometrical features. We propose a quadtree-based meshing in the current contribution to capture these geometrical
characteristics.
This kind of discretisation approach requires special techniques to couple cells of different sizes since, after a quadtree decomposition, the problem of so-called hanging nodes may arise. Transition elements based on high-order transfinite shape functions are used to solve this issue. The advantage is that these elements allow the correct coupling of the cells while retaining a high-order interpolation. Moreover, the reuse of the dynamic stiffness matrices can be exploited based on the similarity of the cells. This procedure renders the approach very efficient.
Examples show the scattering characteristics of different guided wave modes after interacting with inhomogeneities and discontinuities in a plate.
AbstractIn this study, we compare the residual stress state in a laser powder bed fusion (PBF‐LB/M) AlSi10Mg alloy in the as‐built (AB) condition with that after two different heat treatments (265 °C for 1 h, HT1; and 300 °C for 2 h, HT2). The bulk residual stress (RS) is determined using synchrotron X‐ray diffraction (SXRD), and near‐surface profiles are determined using laboratory energy‐dispersive X‐ray diffraction (EDXRD). The EDXRD results do not reveal any notable difference between the conditions at a depth of 350 μm, suggesting that the machining process yields a comparable residual stress state in the near‐surface regions. On the other hand, the SXRD results show that HT1 is more effective in relieving the bulk RS. It is observed that HT1 reduces the RS state in both the aluminium matrix and the silicon network. In addtion, HT2 does not have a significant impact on relaxing the RS as‐built state of the matrix, although it does induce a reduction in the RS magnitudes of the Si phase. It is concluded that the heat treatment stress relieving is effective as long as the Si‐network is not disaggregated.
A new titanium alloy improving the operation of implants additively manufactured and including laterally closed lattice structures is proposed. The new alloy possesses an increased affinity to the bone. The measured bone–interface implant (BII) of less than 10 mm and bone–implant contact (BIC) of 95% demonstrated an excellent osseointegration. Furthermore, since additive manufacturing naturally leads to a high-roughness surface finish, the wettability of the implant is increased. The combination of these factors is pushing ossification beyond its natural limits. In addition, the quality and speed of the ossification and osseointegration in/around laterally closed lattice implants open the possibility of bone spline key of prostheses. This enables the stabilization of the implant into the bone while keeping the possibility of punctual hooks allowing the implant to be removed more easily if required.
The overview of the activity of Federal Institute for Material Research and Testing (BAM, Belin, Germany) in the field material characterization by X-ray imaging is presented. The principle of X-ray Computed Tomography (XCT) is explained. The multiple examples of application of quantitative analysis by XCT are reported, such as additive manufacturing, Li-ion battery, concrete research.
Bei der zerstörungsfreien Prüfung verlegter Eisenbahnschienen werden die Rohdaten derzeit in proprietären Datenformaten gespeichert und auf Datenträgern zwischen den Prüfzügen und den auswertenden Stellen versendet. Die proprietären Datenformate sind in der Regel nur den Herstellern der Prüfsysteme bekannt und deren Dokumentation nicht allgemein zugänglich.
Das Forschungsprojekt „Artificial Intelligence for Rail Inspection“ (AIFRI) erfordert den Austausch von Prüfdaten in einem offenen Format sowohl zwischen den Projektpartnern als auch die Veröffentlichung anonymisierter Daten ausgewählter Strecken aus dem Offenen Digitalen Testfeld (ODT). Wir haben uns in dem Projekt für die Verwendung der „Standard Practice for Digital Imaging and Communication in Nondestructive Evaluation“ (DICONDE) entschieden. DICONDE basiert auf dem medizinischen Standard „Digital Imaging and Communication in Medicine“ (DICOM) und wurde von ASTM an die ZfP angepasst. DICOM bzw. DICONDE ist nicht nur ein Datenformat, sondern beinhaltet auch Kommunikationsschnittstellen für die Auftragsvergabe, Datenübertragung und Abfrage gespeicherter Datensätze aus einem Archiv.
In dem Vortrag werden DICOM und DICONDE vorgestellt, sowie die Verwendung von DICONDE für die Schienenprüfung im Projekt AIFRI näher erläutert. Es wird gezeigt, wie sich Prüfdaten, Prüfparameter, Streckeninformationen incl. Kilometertafeln und Geokoordinaten und Befunde in DICONDE kodieren lassen.
Die Wirbelstromprüfung ist ein bewährtes Verfahren zur zerstörungsfreien Prüfung elektrisch leitfähiger Objekte im oberflächennahen Bereich. Nach einer Einführung in die Wirkungsweise, Möglichkeiten und Grenzen des Wirbelstromprüfverfahrens wird am Beispiel des Schreins der Heiligen Drei Könige gezeigt, wie sich mit dem Wirbelstromprüfverfahren unterschiedliche Metalllegierungen unter einer Vergoldung zerstörungsfrei identifizieren lassen.
Der Schrein der Heiligen Drei Könige wurde um das Jahr 1200 von Nikolaus von Verdun erschaffen, ca. 1750 von Johann Rohr und 1807 von Wilhelm Pollack restauriert. Die Restaurierungsarbeiten wurden jedoch nur unvollständig dokumentiert. Es ist bekannt, dass zu den unterschiedlichen Zeiten unterschiedliche Metalllegierungen als Grundmaterial unter der Vergoldung verwendet wurden. Mit Hilfe von Vergleichsproben aus einer Sammlung der Kölner Dombauverwaltung ließen sich die Akanthus-Prägungen des Schreins den verschiedenen Restaurierungen zuordnen.
Currently, mandatory requirements and recommendations for the detection of irregularities in laser beam welded joints are based on classic micrographs as set out in the standard ISO 13919-1:2019. Compared to classic micrographs, computed tomography enables a non-destructive, three-dimensional and material-independent mode of operation, which delivers much more profound results. Even in building material testing, methods with limited informative value can be checked and supplemented by CT examinations.
Die Erzeugung rissschließfreier Anrisse in gekerbten bruchmechanischen Proben für anschließende Ermüdungsversuche kann durch eine zyklische Druckbelastung an der Kerbe erfolgen: Bei der Erstbelastung wird eine plastische Verformung an der Kerbspitze erzeugt, welche Zugeigenspannungen und damit eine risstreibende Kraft bei der folgenden zyklischen Druckbelastung hervorruft. Durch das Risswachstum kommt es zu einer Entspannung, bis der Riss schließlich arretiert, weil die effektive risstreibende Kraft auf den Schwellenwert abgesunken ist. Um Kurzrisswachstum in additiv, mittels pulverbettbasiertem Laserstrahlschmelzen (Laser Powder Bed Fusion - LPBF) gefertigtem AISI 316L Stahl und seinem konventionell erzeugten, warmgewalzten Pendant zu untersuchen, wurde dieses Verfahren im Rahmen der vorliegenden Arbeit genutzt. Im Falle des additiv gefertigten Materials kam es zu unerwartet langem Ermüdungsrisswachstum, bevor der Riss arretierte. Zur Ermittlung der Ursache erfolgte eine Messung der Eigenspannungsverteilungen mittels Neutronendiffraktion in der Kerbebene der additiv gefertigten Proben. Anschließend wurde ein Finite-Elemente-Modell zur Simulation des Ermüdungsrisswachstums in konventionellem und additiv gefertigtem Material implementiert. Im Rahmen dieses Vortrages wird insbesondere auf das Vorgehen bei der Simulation und auf die getroffenen Annahmen und Vereinfachungen eingegangen. Die Resultate werden mit den experimentellen Ergebnissen verglichen und das für die Simulation von Risswachstum genutzte Knoten-Freigabe-Verfahren (Node-Release), das Einbringen von Eigenspannungen als initiale Spannungen in der Simulation, und die Rechengrößen zur Quantifizierung der risstreibenden Kraft kritisch diskutiert.
Laser powder bed fusion of metallic components (PBF-LB/M) is gaining acceptance in industry. However, the high costs and lengthy qualification processes required for printed components create the need for more effective in-situ monitoring and testing methods. This article proposes multispectral Optical Tomography (OT) as a new approach for monitoring the PBF-LB/M process. Compared to other methods, OT is a low-cost process monitoring method that uses long-time exposure imaging to observe the build process. However, it lacks time resolution compared to expensive thermographic sensor systems. Monochromatic OT (1C-OT) is already commercially available and observes the building process layer-wise using a single wavelength window in the NIR range. Multispectral OT (nC-OT) utilizes a similar setup but can measure multiple wavelength ranges per location simultaneously. By comparing the classical 1C-OT and nC-OT approaches, this article examines the advantages of nC-OT (two channel OT and RGB-OT) in reducing the false positive rate for process deviations and approximating maximum temperatures for a better comparison between different build processes and materials. This could ultimately reduce costs and time for part qualification. The main goal of this contribution is to assess the advantages of nC-OT compared to 1C-OT for in-situ process monitoring of PBF-LB/M.
To evaluate the durability of new alternative cement compositions, it is important to examine the internal transport of moisture through these materials. For this purpose, mortars were prepared from different types of cement and capillary suction experiments were carried out. The moisture transport was studied with an NMR tomograph and compared with weight easurements. With the tomograph, the total moisture input could be determined, as well as the moisture content within the samples non-destructively and spatially resolved. This allows precise observation of the moisture fronts. The tomograph was also used to determine the capillary transport
coefficient.
The European Commission has identified Advanced Manufacturing and Advanced Materials as two of six Key Enabling Technologies (KETs). It is considered that Metrology is a key enabler for the advancement of these KETs. Consequently, EURAMET, the association of metrology institutes in Europe, has strengthened the role of Metrology for these KETs by enabling the creation of a European Metrology Network (EMN) for Advanced Manufacturing. The EMN is comprised of National Metrology Institutes (NMIs) and Designated Institutes (DIs) from across Europe and was formally established in October 2021. The aim of the EMN is to provide a high-level coordination of European metrology activities for the Advanced Manufacturing community.
The EMN itself is organized in three sections representing the major stages of the manufacturing chain: 1) Advanced Materials, 2) Smart Manufacturing Systems, and 3) Manufactured Components & Products. The EMN for Advanced Manufacturing is engaging with stakeholders in the field of Advanced Manufacturing (large companies & SMEs, industry organisations, existing networks, and academia), as well as the wider Metrology community, including Technical Committees, to provide input for the Strategic Research Agenda (SRA) on Metrology for Advanced Manufacturing.
This contribution will give an overview about the first version of the SRA prepared by the EMN for Advanced Manufacturing
Laser powder bed fusion is one of the most promising additive manufacturing techniques for printing complex-shaped metal components. However, the formation of subsurface porosity poses a significant risk to the service lifetime of the printed parts. In-situ monitoring offers the possibility to detect porosity already during manufacturing. Thereby, process feedback control or a manual process interruption to cut financial losses is enabled.
Short-wave infrared thermography can monitor the thermal history of manufactured parts which is closely connected to the probability of porosity formation. Artificial intelligence methods are increasingly used for porosity prediction from the obtained large amounts of complex monitoring data. In this study, we aim to identify the potential and the challenges of deep-learning-assisted porosity prediction based on thermographic in-situ monitoring.
Therefore, the porosity prediction task is studied in detail using an exemplary dataset from the manufacturing of two Haynes282 cuboid components. Our trained 1D convolutional neural network model shows high performance (R2 score of 0.90) for the prediction of local porosity in discrete sub-volumes with dimensions of (700 x 700 x 40) μm³.
It could be demonstrated that the regressor correctly predicts layer-wise porosity changes but presumably has limited capability to predict differences in local porosity. Furthermore, there is a need to study the significance of the used thermogram feature inputs to streamline the model and to adjust the monitoring hardware. Moreover, we identified multiple sources of data uncertainty resulting from the in-situ monitoring setup, the registration with the ground truth X-ray-computed tomography data and the used pre-processing workflow that might influence the model’s performance detrimentally.
Residual stresses Analysis in Additively Manufactured alloys using neutron diffraction (L-PBF)
(2023)
An overview of recent progress at BAM of residual stress analysis in additively manufactured, in particular Laser Powder Bed Fusion of metallics materials, using neutron diffraction will be presented. This will cover important topics of the stress-free reference, the diffraction elastic moduli and principal stress determination.
The European Commission has identified Advanced Manufacturing and Advanced Materials as two of six Key Enabling Technologies (KETs). It is considered that Metrology is a key enabler for the advancement of these KETs. Consequently, EURAMET, the association of metrology institutes in Europe, has strengthened the role of Metrology for these KETs by enabling the creation of a European Metrology Network (EMN) for Advanced Manufacturing. The EMN is comprised of National Metrology Institutes (NMIs) and Designated Institutes (DIs) from across Europe and was formally established in October 2021. The aim of the EMN is to provide a high-level coordination of European metrology activities for the Advanced Manufacturing community.
The EMN itself is organized in three sections representing the major stages of the manufacturing chain: 1) Advanced Materials, 2) Smart Manufacturing Systems, and 3) Manufactured Components & Products. The EMN for Advanced Manufacturing is engaging with stakeholders in the field of Advanced Manufacturing (large companies & SMEs, industry organisations, existing networks, and academia), as well as the wider Metrology community, including Technical Committees, to provide input for the Strategic Research Agenda (SRA) on Metrology for Advanced Manufacturing.
This contribution will give an overview about the first version of the SRA prepared by the EMN for Advanced Manufacturing.
Ziel der Untersuchung: Evaluation der Eignung der Refraktions-Tomographie zur Analyse von Alterungserscheinungen innerhalb von adhäsiv verankerten Materialien vor und nach künstlicher Probenalterung.
Material und Methode: Vier humane mittlere Oberkieferfrontzähne wurden wurzelkanalbehandelt und ausgedehnte Klasse IV Defekte der Krone mit einer Aufbaufüllung aus dualhärtendem Komposit (Rebilda DC, VOCO) und einem Glasfaserstift (Rebilda Post, VOCO) restauriert. Alle Proben wurden feucht gelagert und in einer Synchrotron-Einrichtung (BAMline, BESSY II, HZB) mit einer Pixelgröße von 4,08 µm gescannt. Für diese Synchrotron-Refraktions-Tomographie (SXRCT) muss zunächst der Analysatorkristall (AK) zu einer Bragg-Reflexion (Beugung) angeregt werden, um eine SXRCT durchzuführen. Die SXRCT wird mit einer Transmissions-Tomographie (ohne AK) verrechnet. Darauf folgte eine künstliche Probenalterung mit 400.000 Kau- und 3.000 Thermozyklen (50N, 5-55°C). Anschließend wurden die Proben ein weiteres Mal gescannt. Die Datensätze beider SXRCT wurden mittels des „filtered back projection“ Algorithmus rekonstruiert, mit einer Bildanalyse-Software aufeinander registriert und ausgewertet. Hierdurch konnten die Veränderungen initialer Schädigungen analysiert werden.
Ergebnisse: Alle 4 Proben zeigten in den Scans Veränderungen des inneren Gefüges und an Grenzflächen nach Belastung. Es zeigten sich Ansammlungen von Wasser innerhalb eingeschlossener Hohlräume, subkritisches Risswachstum, Ausdehnung des Komposit und Quellung des Glasfaserstiftes um 0,4%. In den SXRCT Aufnahmen waren außerdem Dentintubuli, die bei Auflösungen von 4,08 µm sonst nicht deutlich sichtbar sind darstellbar. Dadurch konnte Eindringen von Wasser in die Tubuli im Anschluss an die Alterung belegt werden.
Zusammenfassung: SXRCT bietet die Möglichkeit, trotz einer vergleichbar geringen Auflösung, kleinste Strukturen und Veränderungen abzubilden. Dies ermöglicht unter anderem die detaillierte Analyse relativ großer Proben, wie eines vollständigen Zahnes in einem Scanvorgang.
In recent decades, the number of components in concrete has grown, particularly in formulations aimed at reducing carbon footprints. Innovations include diverse binders, supplementary cementitious materials, activators, concrete admixtures, and recycled aggregates. These developments target not only the enhancement of material properties but also the mitigation of the ecological and economic impacts of concrete — the most extensively used material by humankind. However, these advancements also introduce a greater variability in the composition of raw materials. The material’s behavior is significantly influenced by its nanoscale properties, which can pose challenges in accurate characterization. Consequently, there’s an increasing need for experimental tuning of formulations. This is accompanied by a more inconsistent composition of raw materials, which makes an experimental tuning of formulations more and more necessary. However, the increased complexity in composition presents a challenge in finding the ideal formulation through trial and error. Inverse design (ID) techniques offer a solution to this challenge by allowing for a comprehensive search of the entire design space to create new and improved concrete formulations. In this publication, we introduce the concept of ID and demonstrate how our open-source app “SLAMD” provides all necessary steps of the workflow to adapt it in the laboratory, lowering the application barriers. The intelligent screening process, guided by a predictive model, leads to a more efficient and effective data-driven material design process resulting in reduced carbon footprint and improved material quality while considering socio-economic factors in the materials design.
Offshore-Windenergieanlagen erfordern Gründungskonzepte aus unterpulver-(UP-)geschweißten Dickblechen (bspw. der Güte S420ML). Während der Schweißfertigung kann eine zeitverzögerte wasserstoffunterstützte Kaltrissbildung auftreten, deren Bewertung aufgrund der Bauteilgröße von Offshore-Strukturen sehr komplex ist. Deswegen wurde eine bauteilähnliche Geometrie (Mock-Up) entwickelt, um reale Steifigkeitsverhältnisse auf den Labormaßstab zu übertragen. Zusätzliche Versteifungen simulieren die Wirkung einer Einspannung bzw. Schrumpfbehinderung der Schweißnaht. Über die Verwendung von Schweißpulvern mit definierter Feuchte wurden zudem ein Extremszenario der Wasserstoffaufnahme simuliert. Entsprechend der vorgegebenen Mindestwartezeit für die ZfP von bis zu 48 h wurde die Schweißnaht zerstörungsfrei mit Phased-Array-Ultraschall-Prüfung (PAUT) geprüft und die Eigenspannungen über Röntgendiffraktometrie (XRD) bestimmt. Zusätzlich wurde die Wasserstoffverteilung in der Schweißverbindung numerisch simuliert. Außer zulässigen Defekten (wie Poren), wurde keine verzögerte Kaltrissbildung in den Mock-Ups festgestellt, was auf hohe Rissbeständigkeit hindeutet.
Structural alloys are largely employed in key industrial sectors and their demand is predicted to rise rapidly for the next decades. Most of these materials require a large amount of energy for extraction and manufacturing, which causes the emission of greenhouse gases and other pollutants. Therefore, strategies for improving the sustainability of structural metallic alloys are urgently needed.
Additive Manufacturing (AM), in particular Laser Powder Bed Fusion (PBF-LB/M), aims to be a sustainable manufacturing process, as it allows the build-up of complex geometry in near net-shape from 3D models, while minimizing material waste and the energy required for the process and post-process treatments.
Nevertheless, the application of additively manufactured parts in structural safety-relevant applications is still hindered by the poor fatigue performance. The cause of this has been mainly attributed to the presence of manufacturing defects and surface roughness. Therefore, a huge effort has been made to optimize the process parameters and to introduce post-process treatments to minimize the defect content. However, material flaws cannot be fully eliminated, but these can be considered in a damage tolerance framework for the prediction of the fatigue performance of additively manufactured metallic materials, which is essential for part design and qualification.
This work aims at presenting different modelling strategies for the prediction of the fatigue limit of AM metals. Simple empirical models and more complex models based on fatigue short crack propagation are proposed. The investigated material is an AlSi10Mg alloy fabricated by PBF-LB/M and subjected to two different low-temperature heat-treatments (265°C for 1 h and 300°C for 2h). The results show that the models can provide good approximation of the fatigue limits and help in the interpretation of the scatter of fatigue data.
The overview of the activity of Federal Institute for Material Research and Testing (BAM, Belin, Germany) in the field of additively manufacturing material characterization will be presented. The research of our group is focused on the 3D imaging of AM materials by means of X-ray Computed Tomography at the lab and at synchrotron, and the residual stress characterization by diffraction (nondestructive technique). Also, two successful research project in collaboration with CAM2, Sweden are presented.
Offshore wind turbines (OWT) are a key factor of the sustainable energy generation of tomorrow. The continuously increasing installation depths and weight of the OWTs require suitable foundation concepts like monopiles or tripods. Typically, mild steels like the S420ML are used with plate thicknesses up to several hundreds of mm causing high restraints in the weld joints. Due to the large plate thickness, submerged arc welding (SAW) with multiple wires is the state-of-the-art welding procedure. As a result of the very high stiffness of the construction, a certain susceptibility for time-delayed hydrogen-assisted cracking (HAC) may occur. The evaluation of crack susceptibility is very complex due to the component size and stiffness of real offshore structures. For this purpose, a near-component test geometry was developed to transfer the real stiffness conditions to laboratory (i.e., workshop) scale. The investigated mock-up, weighing 350 kg, comprised heavy plates (thickness 50 mm, seam length 1,000 m) joined by a 22-pass submerged arc weld. Additional stiffeners simulated the effect of high restraint or shrinkage restraint of the weld. Extreme scenarios of hydrogen absorption during welding were simulated via the use of welding fluxes in dry (HD < 5 ml/100g Fe) and moisture condition (HD > 15 ml/100g Fe). The residual stresses were determined by a robot X-ray diffractometer. Areas of critical tensile residual stress (at the level of the yield strength) were found in the weld metal and heat affected zone. To identify possible delayed cracking, the welds were tested by phased array ultrasonic testing (PAUT) after 48 h. Summarized, no significant occurrence of HAC was detected, indicating the high crack resistance of the welded joint, i.e., a suitable combination of base material, welding consumable and welding parameters.
The capability to produce complexly and individually shaped metallic parts is one of the main advantages of the laser powder bed fusion (PBF LB/M) process. Development of material and machine specific process parameters is commonly based on results acquired from small cubic test coupons of about 10 mm edge length. Such cubes are usually used to conduct an optimization of process parameters to produce dense material. The parameters are then taken as the basis for the manufacturing of real part geometries. However, complex geometries go along with complex thermal histories during the manufacturing process, which can significantly differ from thermal conditions prevalent during the production of simply shaped test coupons. This may lead to unexpected and unpredicted local inhomogeneities of the microstructure and defect distribution in the final part and it is a root cause of reservations against the use of additive manufacturing for the production of safety relevant parts. In this study, the influence of changing thermal conditions on the resulting melt pool depth of 316L stainless steel specimens is demonstrated. A variation of thermo-graphically measured intrinsic preheating temperatures was triggered by an alteration of inter layer times and a variation of cross section areas of specimens for three distinct sets of process parameters. Correlations between the preheating temperature, the melt pool depth, and occurring defects were analyzed. The limited expressiveness of the results of small density cubes is revealed throughout the systematic investigation. Finally, a clear recommendation to consider thermal conditions in future process parameter optimizations is given.
Monitoring and maintenance of civil infrastructure are of great importance, as any undetected damage can cause high repair costs, unintended deadtime, or endanger structural integrity. The inspection of large concrete structures such as bridges and parking lots is particularly challenging and time-consuming. Traditional methods are mostly manual and involve mapping a grid of measurement lines to record the position of each measurement. Current semi-automated methods, on the other hand, use GPS or tachymeters for localization but still require trained personnel to operate. An entirely automated approach using mobile robots would be more cost- and time-efficient. While there have been developments in using GPS-enabled mobile robots for bridge inspection, the weak signal strength in indoor areas poses a challenge for the automated inspection of structures such as parking lots. This paper aims to develop a solution for the automated inspection of large indoor concrete structures by addressing the problem of robot localization in indoor spaces and the automated measurement of concrete cover and rebar detection.
This study was carried out to investigate the neutron transmission signal as a function of sample temperature during a welding process. A theoretical description that includes the Debye-Waller factor was used to describe the temperature influence on the neutron crosssections. Neutron imaging using a monochromatic beam helps to observe transmission variations related to the material temperature. In-situ neutron imaging of welding experiments show the distribution of the temperature in bulk steel samples. The performed finite element modelling of expected temperature distributions shows good agreement with the obtained experimental data.
In this paper, we demonstrate the value of 1H NMR
relaxometry for studying the hydration of clinker-reduced, more
climate-friendly cementitious binders. The results were obtained
on typical CEM I cements and samples containing two different
reactive agricultural ashes as well as non-reactive biochars as
supplementary cementitious materials. The findings prove that
time-resolved NMR measurements provide valuable additional
information when combined with classical heat flow calorimetry.
X-ray refraction is analogous to visible light deflection by matter; it occurs at boundaries between different media. The main difference between visible light and X-rays is that in the latter case deflection angles are very small, from a few seconds to a few minutes of arc (i.e., the refraction index n is near to 1). Importantly, deflection of X-rays is also sensitive to the orientation of the object boundaries. These features make X-ray refraction techniques extremely suitable to a) detect defects such as pores and microcracks and quantify their densities in bulk (not too heavy) materials, and b) evaluate porosity and particle properties such as orientation, size, and spatial distribution (by mapping). While X-ray refraction techniques cannot in general image single defects, they can detect objects with size above a few wavelengths of the radiation.
Such techniques, especially at the Synchrotron BESSY II, Berlin, Germany, can be used in-situ, i.e. when the specimen is subjected to temperatures or external loads.
The use of X-ray refraction analysis yields quantitative information, which can be directly input in kinetics, mechanical and damage models.
We hereby show the application of non-destructive X-ray refraction radiography (SXRR, 2D mapping also called topography) to problems in additive manufacturing:
1) Porosity analysis in PBF-LM-Ti64. Through the use of SXRR, we could not only map the (very sparse) porosity distribution between the layers and quantify it, but also classify, and thereby separate, the filled porosity (unmolten powder) from the keyhole and gas pores (Figure 1).
2) In-situ heat treatment of laser powder bed fusion PBF-LM-AlSi10Mg to monitor microstructure and porosity evolution as a function of temperature (Figure 2). By means of SXRR we indirectly observed the initial eutectic Si network break down into larger particles as a function of increasing temperature. We also could detect the thermally induced porosity (TIP). Such changes in the Si-phase morphology upon heating is currently only possible using scanning electron microscopy, but with a much smaller field-of-view. SXRR also allows observing the growth of some individual pores, usually studied via X-ray computed tomography, but again on much smaller fields-of-view.
Our results show the great potential of in-situ SXRR as a tool to gain in-depth knowledge of the defect distribution and the susceptibility of any material to thermally induced damage and/or microstructure evolution over statistically relevant volumes.
Hot Isostatic Pressing (HIP) is often introduced to tackle the porosity issue in additively manufactured (AM) materials. For instance, HIP post-processing is recommended to improve fatigue resistance of Laser powder bed fusion (PBF-LB) manufactured parts [1, 2]. Even though HIP cannot completely remove porosity, it significantly decreases the defect population and its average size below the critical threshold value leading to early crack initiation.
In the present study, in-situ investigation of HIP procedure of PBF-LB Ti-6Al-4V parts was carried out to gain further insights into the densification mechanism occurring during HIP. The in-situ observations at high pressure and high temperature are uniquely possible at the PSICHE beamline of the Soleil synchrotron (France), thanks to the Ultrafast Tomography on a Paris-Edinburgh Cell (UToPEC) and the combination of the fast phase-contrast tomography and energy-dispersive diffraction [3, 4]. A detailed methodology was developed to ensure that the correct pressure and temperature were maintained during the experiments.
The results allowed an estimation of the global dentification rate during HIP of PBF-LB Ti-Al-4V material, as well as a detailed quantitative characterization of the influence of pore size and shape on the densification process, thereby understanding the effectiveness of HIP process on different pore categories. After 20 mins, 75% of porosity can be considered as closed or has size below the resolution of the XCT reconstruction. We also observed that the smallest defects showed higher densification rate, while the defect shape did not have significant effect on such rate. The current development of in-situ HIP experiment allows experimental quantification and validation of the simulation work. Ultimately it paves the road to tailoring the HIP procedure for different materials depending on the porosity and microstructure.
For the wide acceptance of the use of additive manufacturing (AM), it is required to provide reliable testing methods to ensure the safety of the additively manufactured parts. A possible solution could be the deployment of in-situ monitoring during the build process. However, for laser powder bed fusion using metal powders (PBF-LB/M) only a few in-situ monitoring techniques are commercially available (optical tomography, melt pool monitoring), which have not been researched to an extent that allows to guarantee the adherence to strict quality and safety standards.
In this contribution, we present results of a study of PBF-LB/M printed parts made of the nickel-based superalloy Haynes 282. The formation of defects was provoked by local variations of the process parameters and monitored by thermography, optical tomography and melt pool monitoring. Afterwards, the defects were characterized by computed tomography (CT) to identify the detection limits of the used in-situ techniques.
Inconel 718 (IN718) is a traditional age-hardenable nickel-based alloy that has been increasingly processed by additive manufacturing (AM) in recent years. In the as-solidified condition, IN718 exhibits chemical segregation and the undesired Laves phase, requiring a solution annealing (SA) prior to aging. The material produced by AM does not respond to the established thermal routines in the same way as conventionally produced IN718, and there is still no consensus on which routine yields optimal results. This work aims to provide a fundamental understanding of the heat treatment (HT) response by continuously monitoring the microstructural evolution during SA via time-resolved synchrotron x-ray diffraction, complemented by ex-situ scanning electron microscopy (SEM). The samples were produced by laser powder bed fusion to a geometry of 10x20x90 mm³, from which Ø1x5 mm³ cylindric specimens were extracted. Two different scanning strategies – incremental 67° rotations, Rot, and alternating 0°/67° tracks, Alt – were used, leading to two different as-built conditions. 1-hour SAs were carried out in the beamline ID22 of the ESRF at 50 KeV. Two SA temperatures, SA1 = 1020 °C, and SA2 = 1080 °C were tested for each scanning strategy. Data were processed using the software PDIndexer. In the as-built state, all samples showed typical subgrain columnar cell structures with predominant Nb/Mo segregation and Laves phase at the cell walls, as seen by SEM. The Alt scan induced higher intensity on the Laves peaks than the Rot scan, suggesting a greater content of Laves. Chemical homogenization in the SA was largely achieved during the heating ramp (Fig. 1). SA2 eliminated the Laves peaks just before reaching 1080 °C, and mitigated differences between Rot and Alt samples. On the other hand, SA1 induced the precipitation of the generally detrimental δ phase, also observed by SEM. Furthermore, the Rot scan showed higher δ peak intensities than the Alt scan, indicating a higher content of δ in the latter. No signs of recrystallization were observed in any of the investigated SAs.
The damage mechanisms of metallic components produced by process laser powder bed fusion differ significantly from those typically observed in conventionally manufactured variants of the same alloy. This is due to the unique microstructures of additively manufactured materials. Herein, the focus is on the study of the evolution of creep damage in stainless steel 316L specimens produced by laser powder bed fusion. X-ray computed tomography is used to unravel the influence of the process-specific microstructure from the influence of the initial void distribution on creep damage mechanisms. The void distribution of two specimens tested at 600 °C and 650 °C is analyzed before a creep test, after an interruption, and after fracture. The results indicate that the formation of damage is not connected to the initial void distribution. Instead, damage accumulation at grain boundaries resulting from intergranular cracking is observed.
Fused filament fabrication (FFF) on desktop 3D printers is a material extrusion-based technique often used by educational institutions, small enterprises and private households. Polymeric filaments are melted and extruded through a heated nozzle to form a 3D object in layers. The extrusion temperature is therefore a key parameter for a successful print job, but also one of the main driving factors for the emission of harmful air pollutants, namely ultrafine particles and volatile organic gases, which are formed by thermal stress on the polymeric feedstock. The awareness of potential health risks has increased the number of emission studies in the past years. However, the multiplicity of study designs makes an objective comparison of emission data challenging because printer hardware factors such as the actual extruder temperature (TE) and also feedstockspecific emissions are not considered. We assume that across the market of commercial low- and mid-price FFF printers substantial deviations between actual and set extruder temperatures exist, which have a strong effect on the emissions and hence may bias the findings of exposure studies. In our last publication, we presented a standardized feedstock-specific emission test method and showed that for each investigated feedstock an increase in actual extruder temperature was accompanied by an increase in particle emissions (Tang and Seeger, 2022). Therefore, any systematic discrepancy between set and actual extruder temperature matters. In this study, we used a thermocouple and an infrared camera to measure the actual extruder temperatures at different heights. We found significant under- and overestimation of the actual extruder temperatures by the respective set temperatures in three commercial printers. This caused a broad variation of the measured total numbers of emitted particles (TP), even when the same feedstock was operated. For the determination of TP, we followed the DE-UZ 219 test guideline. In a second round we repeated the tests with all printers adjusted to exactly the same extruder temperatures, i.e., to TE=230°C for ABS and TE=210°C for PLA. All measurements were conducted in a 1 m³ emission test chamber. Particle emissions in the size range between 4 nm and 20 μm were detected. Printing on three different printer models without temperature adjustment resulted for each of the investigated feedstocks in a variation in TP of around two orders of magnitude. After temperature adjustment, this was substantially reduced to approx. one order of magnitude and hence minimizes the bias of printer hardware on the emissions. Our findings suggest that adjustment of the extruder temperature should be mandatory in emission testing standards. It also poses a more accurate benchmark and provides more reliable emission data for evaluation of indoor air quality or for health risk assessments. In addition, a proper temperature setting is in the interest of the user. Some commercial FFF printers may have a higher actual extruder temperature than displayed and unintended overheating may not only impair the print quality but may cause unnecessarily increased exposure to particle emissions.
Packagings for the transport of dangerous goods need to meet special requirements to get an approval. This includes free fall drop testing onto an essentially unyielding surface as a means to assess a package’s resistance to mechanical damage. A main requirement for drop tests is that the impact target’s mass shall be at least 50 times that of the heaviest package to be tested. Nevertheless, many manufacturers do not possess foundation structures with the required mass ratio. Previous evidence highlights that the mass ratio is not a decisive criterion on its own. Parameters such as the impact target foundation’s connection and the impulse experienced by the impacting object are essential as well. However, these factors are not easily verifiable since experimental measurements are not possible at most facilities. The objective of this work is to provide a detailed analysis on the interaction between impact target foundation and subgrade in dynamic impact testing using validated finite-element (FE) models. This research is highly beneficial for industrial application since it allows manufacturers to make informed predictions about the mechanical response of installed impact target foundations.
Defects are still common in metal components built with Additive Manufacturing (AM). Process monitoring methods for laser powder bed fusion (PBF-LB/M) are used in industry, but relationships between monitoring data and defect formation are not fully understood yet. Additionally, defects and deformations may develop with a time delay to the laser energy input. Thus, currently, the component quality is only determinable after the finished process.
Here, active laser thermography, a non-destructive testing method, is adapted to PBF-LB/M, using the defocused process laser as heat source. The testing can be performed layer by layer throughout the manufacturing process. The results of the defect detection using infrared cameras are presented for a custom research PBF-LB/M machine. Our work enables a shift from post-process testing of components towards in-situ testing during the AM process. The actual component quality is evaluated in the process chamber and defects can be detected between layers.
The focus of the presentation focus will be on 3D imaging by means of X-ray Computed Tomography (XCT) at the lab and at synchrotron, and the non-destructive residual stress (RS) characterization by diffraction of additively manufactured (AM) materials in BAM (Berlin, Germany). The manufacturing defects and high RS are inherent of AM techniques and affect structural integrity of the components. Using XCT the defects size and shape distribution as well as geometrical deviations can be characterized, allowing the further optimization of the manufacturing process. Diffraction-based RS analysis methods using neutron and synchrotron X-rays at large scale facilities offer the possibility to non-destructively spatially resolve both surface and bulk RS in complex components and track their changes following applied thermal or mechanical loads.
Safety-critical applications of products manufactured by laser powder bed fusion (PBF-LB/M) are still limited to date. This is mainly due to a lack of knowledge regarding the complex relationship between process, structure, and resulting properties. The assurance of homogeneity of the microstructure and homogeneity of the occurrence and distribution of defects within complexly shaped geometries is still challenging. Unexpected and unpredicted local inhomogeneities may cause catastrophic failures. The identification of material specific and machine specific process parameter windows for production of fully dense simple laboratory specimens is state of the art. However, the incorporation of changing thermal conditions that a complexly shaped component can be faced with during the manufacturing process is often neglected at the stage of a process window determination. This study demonstrates the tremendous effect of changing part temperatures on the defect occurrence for the broadly used stainless steel alloy AISI 316L. Process intrinsic variations of the surface temperature are caused by heat accumulation which was measured by use of a temperature adjusted mid-wavelength infrared (MWIR) camera. Heat accumulation was triggered by simple yet effective temporal and geometrical restrictions of heat dissipation. This was realized by a variation of inter layer times and reduced cross section areas of the specimens. Differences in surface temperature of up to 800 K were measured. A severe development of keyhole porosity resulted from these distinct intrinsic preheating temperatures, revealing a shift of the process window towards unstable melting conditions. The presented results may serve as a warning to not solely rely on process parameter optimization without considering the actual process conditions a real component is faced with during the manufacturing process. Additionally, it motivates the development of representative test specimens.
Safety-critical applications of products manufactured by laser powder bed fusion (PBF-LB/M) are still limited to date. This is mainly due to a lack of knowledge regarding the complex relationship between process, structure, and resulting properties. The assurance of homogeneity of the microstructure and homogeneity of the occurrence and distribution of defects within complexly shaped geometries is still challenging. Unexpected and unpredicted local inhomogeneities may cause catastrophic failures. The identification of material specific and machine specific process parameter windows for production of fully dense simple laboratory specimens is state of the art. However, the incorporation of changing thermal conditions that a complexly shaped component can be faced with during the manufacturing process is often neglected at the stage of a process window determination. This study demonstrates the tremendous effect of changing part temperatures on the defect occurrence for the broadly used stainless steel alloy AISI 316L. Process intrinsic variations of the surface temperature are caused by heat accumulation which was measured by use of a temperature adjusted mid-wavelength infrared (MWIR) camera. Heat accumulation was triggered by simple yet effective temporal and geometrical restrictions of heat dissipation. This was realized by a variation of inter layer times and reduced cross section areas of the specimens. Differences in surface temperature of up to 800 K were measured. A severe development of keyhole porosity resulted from these distinct intrinsic preheating temperatures, revealing a shift of the process window towards unstable melting conditions. The presented results may serve as a warning to not solely rely on process parameter optimization without considering the actual process conditions a real component is faced with during the manufacturing process. Additionally, it motivates the development of representative test specimens.
Guided wave ultrasonic features in composite overwrapped pressure vessels towards digital twin
(2023)
The digitalization of quality control processes and the underlying data infrastructures for safety relevant components, such as hydrogen pressure vessels, plays a significant role in the transition towards Industry 4.0. In the current safety regulations for hydrogen pressure vessels, there is no established concept for structural health monitoring. The development of a reliable structural health monitoring methodology for monitoring the structural integrity of pressure vessels enables a fast-forward transition from personnel- and costintensive recurring inspections, a.k.a. periodic maintenance, to predictive maintenance. In the work presented; we investigated the application of ultrasonic guided wave propagation to monitor and assess the condition of Type IV composite overwrapped pressure vessel (COPV). A sensor network of fifteen piezo-electric wafers is placed on the carbon fibre reinforced composite cylinder. Five different artificial damage configurations are created by gluing two different weight blocks on three different locations. The database containing measured guided wave data sets is enriched by two different boundary conditions. We utilized an open-source software, openBIS labnotebook, to store and analyse experimental datasets. The guided wave ultrasonic signals were investigated and analysed by using commonly used ultrasonic features (e.g., amplitude, frequency, time of flight) as well as non-traditional time-series features (kurtosis, skewness, variance). The features were used to calculate damage index and the detection performance for the results has been evaluated. The results suggest that both traditional and non-traditional features assume significant importance in artificial damage detection. The future works will additionally involve the impacts of operational conditions, such as periodic pressure variations temperature loadings as well as material degradations.
The global demand for concrete is growing, and with it, its carbon footprint. Current literature proposes biochar, a product of pyrolysis, as a possible car-bon sink to reduce the carbon footprint of concrete. This work investigates the microstructure of Portland cement pastes with 0%, 5%, and 25% of the cement replaced with wood biochar, since this should influence its macro-scopic mechanical properties. MIP, gas sorption, NMR, and µ-CT were used to analyze the pore space of the three materials. The combination of these methods, each with different resolution, enables a multi-scale investigation of biochar impact on the microstructure of cement pastes. NMR confirmed that biochar can absorb moisture and, thus, reduces the effective water-to-cement ratio. MIP and gas sorption results show 0% and 5% volume re-placement have similar gel pore structure. The results from µ-CT investiga-tions suggest that biochar may reduce the formation of larger pores. The in-clusion of non-reactive porous particles such as biochar increase the porosity of the material and should act as a weakness in terms of mechanical proper-ties. Overall, this study highlights the need to carefully tailor replacement rates to control the impact of biochar on the microstructure concrete mixtures and sees a strong need for further studies on mechanical properties.
For the wide acceptance of the use of additive manufacturing (AM), it is required to provide reliable testing methods to ensure the safety of the additively manufactured parts. A possible solution could be the deployment of in-situ monitoring during the build process. However, for laser powder bed fusion using metal powders (PBF-LB/M ) only a few in-situ monitoring techniques are commercially available (optical tomography, melt pool monitoring) but not researched to an extent that allows to guarantee the adherence to strict quality and safety standards.
In this contribution, we present results of a study of PBF-LB/M printed parts made of the nickel-based superalloy Haynes 282. The formation of defects was provoked by local variations of the process parameters and monitored by thermography, optical tomography and melt pool monitoring. Afterwards, the defects were characterized by computed tomography (CT) to identify the detection limits of the used in-situ techniques.
We discuss the non-linear stress–strain behavior of microcracked polycrystalline ceramics under uniaxial tension and compression (displacement control).
Micromechanics explanation and modeling of its basic features, such as non-linearity and hysteresis in stress–strain curves, are developed, with stable microcrack propagation and “roughness” of intergranular cracks playing critical roles in tension and crack sliding playing a critical role in compression. Experiments involving complex loading histories are explained, and themodel is shown to reproduce the basic features of the observed stress–strain curves.
Great complexity characterizes Additive Manufacturing (AM) of metallic components via laser powder bed fusion (PBF-LB/M). Due to this, defects in the printed components (like cracks and pores) are still common. Monitoring methods are commercially used, but the relationship between process data and defect formation is not well understood yet. Furthermore, defects and deformations might develop with a temporal delay to the laser energy input. The component’s actual quality is consequently only determinable after the finished process.
To overcome this drawback, thermographic in-situ testing is introduced. The defocused process laser is utilized for nondestructive testing performed layer by layer throughout the build process. The results of the defect detection via infrared cameras are shown for a research PBF-LB/M machine.
This creates the basis for a shift from in-situ monitoring towards in-situ testing during the AM process. Defects are detected immediately inside the process chamber, and the actual component quality is determined.
Capillary active interior insulation materials are an important approach to minimize energy losses of historical buildings. A key factor for their performance is a high liquid conductivity, which enables redistribution of liquid moisture within the material. We set up an experiment to investigate the development of moisture profiles within two different interior insulation materials, calcium-silicate (CaSi) and expanded perlite (EP), under constant boundary conditions. The moisture profiles were determined by two different methods: simple destructive sample slicing with subsequent thermogravimetric drying as well as non-destructive NMR measurements with high spatial resolution. The moisture profiles obtained from both methods show good agreement, when compared at the low spatial resolution of sample slicing, which demonstrates the reliability of this method. Moreover, the measured T2- relaxation-time distributions across the sample depth were measured, which may give further insight into the saturation degree of the different pore sizes. In order to explain differences in the moisture profiles between CaSi and EP, we determined their pore-size distribution with different methods: conversion of the NMR T2 relaxationtime distribution at full saturation, mercury intrusion porosimetry and indirect determination from pressure plate measurements. CaSi shows a unimodal distribution at small pore diameters, while in EP, a bi-modal or wider distribution was found. We assume that the smaller pore diameters of CaSi lead to a higher capillary conductivity, which causes a more distributed moisture profile in comparison with that of EP.
Capillary active interior insulation materials are an important approach to minimize energy losses of historical buildings. A key factor for their performance is a high liquid conductivity, which enables redistribution of liquid moisture within the material. We set up an experiment to investigate the development of moisture profiles within two different interior insulation materials, calcium-silicate (CaSi) and expanded perlite (EP), under constant boundary conditions. The moisture profiles were determined by two different methods: simple destructive sample slicing with subsequent thermogravimetric drying as well as non-destructive NMR measurements with high spatial resolution. The moisture profiles obtained from both methods show good agreement, when compared at the low spatial resolution of sample slicing, which demonstrates the reliability of this method. Moreover, the measured T2-relaxation-time distributions across the sample depth were measured, which may give further insight into the saturation degree of the different pore sizes. In order to explain differences in the moisture profiles between CaSi and EP, we determined their pore-size distribution with different methods: conversion of the NMR T2 relaxationtime distribution at full saturation, mercury intrusion porosimetry and indirect determination from pressure plate measurements. CaSi shows a unimodal distribution at small pore diameters, while in EP, a bi-modal or wider distribution was found. We assume that the smaller pore diameters of CaSi lead to a higher capillary conductivity, which causes a more distributed moisture profile in comparison with that of EP.
In dentistry it is of great interest to achieve good sealing interzones between tooth tissue and restoration materials to avoid, e. g. secondary caries. μXRF and CμXRF are suitable to investigate the elemental composition at these interzones in respect to diffusion of elements. Synchrotron X-ray refraction radiography (SXRR) and μCT measurements deliver highly resolved structural information and make structural changes such as micro cracks within the filling and the tooth tissue visible. The presented measurements are part of the DFG funded project IXdent (Integrative X-ray techniques for chemical and structural characterizations of dental interzones.)
The depth-resolved CμXRF measurements are affected by absorption effects, making a quantitative investigation of the interzone in depth difficult. Full 3D quantification of heterogenous samples requires a complete model including dark matrix and density for each voxel. The combination of different techniques paves the way for a quantitative analysis of dental interzones.
Metal Additive Manufacturing (AM) technologies such as Laser Powder Bed Fusion (LPBF) are characterized by layer wise construction, which enable advancements of component design, leading to potential efficiency and performance improvements. However, the rapid cooling rates associated with the process consequently leads to the generation of high magnitude residual stresses (RS). Therefore, a deep understanding of the formation of RS, the influence of process parameters on their magnitude and the impact on mechanical performance is crucial for widespread application. The experimental characterization of these RS is essential for safety related engineering application and supporting the development of reliable numerical models. Diffraction-based methods for RS analysis using high energy synchrotron X-rays and neutrons enable non-destructive spatially resolved characterization of both surface and bulk residual stresses in complex components. This presentation will provide an overview of recent research conducted by the BAM at large scale facilities for the characterization of residual stresses in LPBF metallic alloys. Special focus will be given to the challenges posed by textured LPBF materials for the reliable choice of the diffraction elastic constants (DECs), which is crucial to the accurate calculation of the level of RS.
The high cooling rates (~106 K/s) occurring during Laser Powder Bed Fusion (PBF-LB/M) of AlSi10Mg induce to the formation of a fine nanometric silicon network in the as-built condition. Such unprecedented microstructure enhances the mechanical strength when compared to equivalent as-cast materials. Nevertheless, PBF-LB/M also leads to high magnitude residual stress (RS) due to the extreme localized temperature gradients. The presence of RS can be detrimental to the fatigue life of engineering components, and great efforts are focused on understanding their generation and evolution after post-process heat treatments. Typically, T6 heat treatments are used to mitigate RS and improve mechanical performances by Mg2Si precipitation during ageing at 160-180°C. Nevertheless, the solutionizing at 500-540°C vanishes the fine silicon network, leading to the formation of micrometric (average of ~2-5 µm) polygonal Si particles, similar to those observed in T6 heat-treated Al-Si cast materials. Therefore, the aim of this work is to evaluate the ability of two so-called low temperature heat treatments (i.e., at 265°C and 300°C) to mitigate RS while retaining the fine as-built microstructure inherent to PBF-LB/M AlSi10Mg. The fatigue behavior of the as-built material is subsequently compared to the two low temperature conditions.
LTCCs (Low-temperature co-fired ceramics) consist of three-dimensionally distributed, hermetically bonded ceramic and metallic components with structure sizes within [10; 100] µm. A non-destructive imaging technique is needed that provides 3D, sharp, high-contrast resolution of these structures, as well as porosity and defect analysis, which is made difficult by the very different X-ray absorption coefficients of the individual components of the microstructure. A HDR method is being developed that allows a combination of different tomograms, each with X-ray energies adapted to individual materials.
Der Vortrag gibt eine Übersicht über aktuelle zerstörungsfreie Prüfmethoden, die verwendet werden können, um eine Zustandsbewertung von Bauteilen im Bestand vorzunehmen und mögliche Wiederverwendungsstrategien zu entwickeln. Ebenfalls zeigt der Vortrag, welche Möglichkeiten es gibt, künstliche Intelligenzmethoden zu verwenden, um aus recykelten Materialien wieder hochwertige, neue Baustoffe zu entwickeln.
In Leichtbauanwendungen sind Materialien mit geringen Dichten und hohen Festigkeiten gefragt. Insbesondere Faser-Kunststoff-Verbunde (FKV) erfüllen diese Anforderungen und werden zunehmend für Strukturbauteile eingesetzt. Die Oberflächen moderner Rotorblätter von Windkraftanlagen werden aus FKV gefertigt. Das Versagen dieser Materialien hat massiven Einfluss auf die Einsatzfähigkeit der gesamten Windkraftanlage. Daher ist die Kenntnis des Versagensverhaltens dieser Komponenten unter statischer und zyklischer Belastung von großem Interesse, um die Betriebsbeanspruchung abzuschätzen. Im Idealfall wird die Schadensentwicklung unter Betriebslast mit zerstörungsfreien in-situ-Prüfverfahren ermittelt. Hier berichten wir über die Beobachtung der Rissentwicklung in Carbon-Faserverstärkten Kunststoffen (CFK) unter kontinuierlicher Zugbelastung durch in-situ Synchrotron-Röntgenrefraktionsradiographie. Eine selbst entwickelte elektromechanische Zugprüfmaschine mit einem Kraftbereich bis zu 15 kN wurde in den Strahlengang an der BAMline (BESSY II) integriert. Da in herkömmlichen (Absorptions-) Radiographien Defekte wie Zwischenfaserbrüche oder Faser-Matrix-Enthaftung keinen ausreichenden Kontrast verursachen, wird zur Kontrastanhebung die Röntgenrefraktion benutzt. Hier wird das sogenannte Diffraction Enhanced Imaging (DEI) angewandt, um Primär- und gebrochene Strahlung mit Hilfe eines Analysatorkristalls zu trennen. Diese Technik ermöglicht schnelle Messungen mit einem Gesichtsfeld von einigen Quadratmillimetern (hier: 14 mm × 7.2 mm) und ist ideal für in-situ Untersuchungen. Die Bildgebung und der Zugversuch erfolgen mit einer Bildfrequenz von 0.7 / s und einer Dehnrate von 0.00055 / s . Bei 0°/90° Fasergelegen treten die ersten Zwischenfaserrisse bei 380 MPa (Dehnung 0.8 %) auf. Vor dem Versagen bei ca. 760 MPa (Dehnung 2.0 %) beobachten wir die Ausbildung eines nahezu äquidistanten Rissmusters (Risse in ca. 1 mm Abstand), das sich im geschädigten Zustand über die gesamte Probe erstreckt.
In Leichtbauanwendungen sind Materialien mit geringen Dichten und hohen Festigkeiten gefragt. Insbesondere Faser-Kunststoff-Verbunde (FKV) erfüllen diese Anforderungen und werden zunehmend für Strukturbauteile eingesetzt. Die Oberflächen moderner Rotorblätter von Windkraftanlagen werden aus FKV gefertigt. Das Versagen dieser Materialien hat massiven Einfluss auf die Einsatzfähigkeit der gesamten Windkraftanlage. Daher ist die Kenntnis des Versagensverhaltens dieser Komponenten unter statischer und zyklischer Belastung von großem Interesse, um die Betriebsbeanspruchung abzuschätzen. Im Idealfall wird die Schadensentwicklung unter Betriebslast mit zerstörungsfreien in-situ-Prüfverfahren ermittelt. Hier berichten wir über die Beobachtung der Rissentwicklung in Carbon-Faserverstärkten Kunststoffen (CFK) unter kontinuierlicher Zugbelastung durch in-situ Synchrotron-Röntgenrefraktionsradiographie. Eine selbst entwickelte elektromechanische Zugprüfmaschine mit einem Kraftbereich bis zu 15 kN wurde in den Strahlengang an der BAMline (BESSY II) integriert. Da in herkömmlichen (Absorptions-) Radiographien Defekte wie Zwischenfaserbrüche oder Faser-Matrix-Enthaftung keinen ausreichenden Kontrast verursachen, wird zur Kontrastanhebung die Röntgenrefraktion benutzt. Hier wird das sogenannte Diffraction Enhanced Imaging (DEI) angewandt, um Primär- und gebrochene Strahlung mit Hilfe eines Analysatorkristalls zu trennen. Diese Technik ermöglicht schnelle Messungen mit einem Gesichtsfeld von einigen Quadratmillimetern (hier: 14 mm × 7.2 mm) und ist ideal für in-situ Untersuchungen. Die Bildgebung und der Zugversuch erfolgen mit einer Bildfrequenz von 0.7 / s und einer Dehnrate von 0.00055 / s . Bei 0°/90° Fasergelegen treten die ersten Zwischenfaserrisse bei 380 MPa (Dehnung 0.8 %) auf. Vor dem Versagen bei ca. 760 MPa (Dehnung 2.0 %) beobachten wir die Ausbildung eines nahezu äquidistanten Rissmusters (Risse in ca. 1 mm Abstand), das sich im geschädigten Zustand über die gesamte Probe erstreckt.
In this study, we present an enhanced deep learning framework for the prediction of porosity based on thermographic in-situ monitoring data of laser powder bed fusion processes. The manufacturing of two cuboid specimens from Haynes 282 (Ni-based alloy) powder was monitored by a short-wave infrared camera. We use thermogram feature data and x-ray computed tomography data to train a convolutional neural network classifier. The classifier is used to perform a multi-class prediction of the spatially resolved porosity level in small sub-volumes of the specimen bulk.
Die Brechung von Röntgenstrahlen (Röntgenrefraktion) an Grenzflächen zwischen Materialien unterschiedlicher Dichte ist analog zur Ablenkung von sichtbarem Licht an z.B. Glasoberflächen. Es gibt jedoch zwei wesentliche Unterschiede:
a) konvexe Grenzflächen verursachen Divergenz (d.h. der Brechungsindex n ist kleiner als 1), und
b) die Ablenkungswinkel sind sehr klein, und reichen von einigen Bogensekunden bis zu einigen Bogenminuten (d.h. n ist nahe bei 1);
Wie auch bei sichtbarem Licht ist die Ablenkungsrichtung der Röntgenstrahlen abhängig von der Orientierung der durchstrahlten Grenzfläche. Aufgrund dieser Eigenschaften eignen sich Röntgenrefraktionsmethoden hervorragend für:
a) die Erkennung und Quantifizierung von Defekten wie Poren und Mikrorissen und
b) die Bewertung von Porosität und Partikeleigenschaften wie Orientierung, Größe und räumliche Verteilung.
Wir zeigen die Anwendung der Röntgenrefraktionsradiographie (2,5D Technik) und der -tomographie (3D Technik) für die Untersuchung verschiedener Probleme in der Werkstoffwissenschaft und -technologie:
a) Sintern von SiC-Grünkörpern
b) Porositätsanalyse in Dieselpartikelfiltersilikaten
c) Faser-Matrix-Haftung in Metall- und Polymermatrixverbundwerkstoffen
d) Mikrorissbildung in Glaskeramik.
Wir zeigen, dass der Einsatz von Röntgenrefraktionsmethoden quantitative Ergebnisse liefert, die direkt als Parameter in Werkstoffmodellen verwendet werden können.
Die Brechung von Röntgenstrahlen (Röntgenrefraktion) an Grenzflächen zwischen Materialien unterschiedlicher Dichte ist analog zur Ablenk-ung von sichtbarem Licht an z.B. Glasoberflächen. Es gibt jedoch zwei wesentliche Unterschiede:
a) konvexe Grenzflächen verursachen Divergenz (d.h. der Brechungsindex n ist kleiner als 1), und
b) die Ablenkungswinkel sind sehr klein, und reichen von einigen Bogensekunden bis zu einigen Bogenminuten (d.h. n ist nahe bei 1);
Wie auch bei sichtbarem Licht ist die Ablenkungsrichtung der Röntgenstrahlen abhängig von der Orientierung der durchstrahlten Grenzfläche. Aufgrund dieser Eigenschaften eignen sich Röntgenrefraktionsmethoden hervorragend für:
a) die Erkennung und Quantifizierung von Defekten wie Poren und Mikrorissen und
b) die Bewertung von Porosität und Partikeleigenschaften wie Orientierung, Größe und räumliche Verteilung.
Wir zeigen die Anwendung der Röntgenrefraktionsradiographie (2,5D Technik) und der -tomographie (3D Technik) für die Untersuchung verschiedener Probleme in der Werkstoffwissenschaft und -technologie:
a) Sintern von SiC-Grünkörpern
b) Porositätsanalyse in Dieselpartikelfiltersilikaten
c) Faser-Matrix-Haftung in Metall- und Polymermatrixverbundwerkstoffen
d) Mikrorissbildung in Glaskeramik.
Wir zeigen, dass der Einsatz von Röntgenrefraktionsmethoden quantitative Ergebnisse liefert, die direkt als Parameter in Werkstoffmodellen verwendet werden können.
In this study, we present an enhanced deep learning framework for the prediction of porosity based on thermographic in-situ monitoring data of laser powder bed fusion processes. The manufacturing of two cuboid specimens from Haynes 282 (Ni-based alloy) powder was monitored by a short-wave infrared camera. We use thermogram feature data and x-ray computed tomography data to train a convolutional neural network classifier. The classifier is used to perform a multi-class prediction of the spatially resolved porosity level in small sub-volumes of the specimen bulk.
Self-healing agents have the potential to restore mechanical properties and extend service life of composite materials. Thermoplastic healing agents have been extensively investigated for this purpose in epoxy matrix composites due to their strong adhesion to epoxy and their ability to fill in microcracks. One of the most
investigated thermoplastic additives for this purpose is poly(ethylene-co-methacrylic acid) (EMAA). Despite the ability of thermoplastic healing agents to restore mechanical properties, it is important to assess how the addition of thermoplastic healing agents affect properties of the original epoxy material. In this work, EMAA was added to epoxy resin and the effect of the additive on fracture toughness of epoxy was evaluated. Results indicate that although added in low concentrations, EMAA can affect fracture toughness.
The overview of the activity of Federal Institute for Material Research and Testing (BAM, Belin, Germany) in the field of additively manufacturing material characterization will be presented. The research of our group is focused on the 3D imaging of AM materials by means of X-ray Computed Tomography at the lab and at synchrotron, and the residual stress characterization by diffraction (nondestructive technique).
Al-Si alloys produced by Laser Powder Bed Fusion (PBFLB) allow the fabrication of lightweight free-shape components. Due to the extremely heterogeneous cooling and heating, PBF-LB induces high magnitude residual stress (RS) and a fine Si microstructure. As the RS can be deleterious to the fatigue resistance of engineering components, great efforts are focused on understanding their evolution in as-built state (AB) and after post-process heat treatments (HT). RS in single edge notch bending (SENB) subjected to different HT are investigated (HT1: 1h at 265°C and HT2: 2h at 300°C).
Metastable austenitic stainless steel (304L) samples with a rectangular cross-section were plastically deformed in torsion during which they experienced multiaxial stresses that led to a complex martensitic phase distribution owing to the transformation induced plasticity effect. A three-dimensional characterization of the phase distributions in these cm-sized samples was carried out by wavelength-selective neutron tomography. It was found that quantitatively correct results are obtained as long as the samples do not exhibit any considerable preferential grain orientation. Optical microscopy, electron backscatter diffraction, and finite element modeling were used to verify and explain the results obtained by neutron tomography. Altogether, neutron tomography was shown to extend the range of microstructure characterization methods towards the meso- and macroscale.
Die additive Fertigung von metallischen Bauteilen (Additive Manufacturing - AM; auch 3D-Druck genannt) bietet eine Vielzahl an Vorteilen gegenüber konventionellen Fertigungsmethoden. Durch den schichtweisen Auftrag und das selektive Aufschmelzen von Metallpulver im Laser Powder Bed Fusion Prozess (L-PBF) sind u.a. optimierte und flexibel anpassbare Designs und die Nutzung von neuartigen Materialien möglich. Aufgrund der Komplexität des AM-Prozesses und der Menge an Einflussfaktoren ist eine Qualitätssicherung der gefertigten Bauteile unabdingbar. Verschiedene in-situ Monitoringansätze werden bereits angewendet, jedoch findet eine dedizierte Prüfung erst im Nachgang der Fertigung ex-situ statt. Der Grund dafür ist, dass die Entstehung von geometrischen Abweichungen und Defekten auch zeitversetzt zum eigentlichen Materialauftrag und damit auch zum Monitoring stattfinden kann. Die Notwendigkeit geeigneter in-situ Prüfmethoden für L-PBF, um die Erforderlichkeit einer Nacharbeitung frühzeitig festzustellen und Ausschuss zu vermeiden ist angesichts kostenintensiver Ausgangsstoffe und einer oftmals mehrstündigen bis mehrtägigen Prozessdauer besonders hoch.
Daraus motiviert wird im Rahmen des Projektes ATLAMP die Möglichkeit der aktiven Laserthermografie mit Hilfe des defokussierten Fertigungslasers untersucht. Damit ist, bei vergleichsweise geringer Laserleistung, eine zerstörungsfreie Prüfung mittels Flying Spot Thermografie möglich. Diese findet jeweils anschließend an die Fertigung einer Schicht statt, womit der reale Status des Bauteils im Verlauf des AM-Prozesses geprüft wird.
Als Grundlage dafür werden im Rahmen dieser Arbeit mit AM gefertigte, defektbehaftete Probekörper zunächst losgelöst vom Fertigungsprozess untersucht. Damit werden die Grundlagen für den neuartigen Ansatz der aktiven in-situ Laserthermografie im L-PBF-Prozess mittels des Fertigungslasers geschaffen. Auf diese Weise lassen sich auch zeitversetzt auftretende Defekte zerstörungsfrei im Prozessverlauf feststellen und eine aussagekräftige Qualitätssicherung des Ist-Zustands des Bauteils erreichen.
A new type of ultrasonic borehole probe is currently under development for the quality assurance of sealing structures in radioactive waste repositories using existing research boreholes. The goal is to examine the sealing structures made of salt concrete for possible cracks, delamination, and embedded objects. Earlier prototype probes use 12 or 16 individual dry point contact (DPC) horizontal shear wave transducers grouped into a transmitter and a receiver array, each made up of six or eight individual transducers. They are operated with a commercially available portable ultrasonic flaw detector used in the civil engineering industry. To increase the generated sound pressure of the borehole probe, the number of transducers in the novel probe is increased to 32. In addition, timed excitation of each probe is used to direct a focused sound beam to a specific angle and distance based on calculated time delays. Hence, the sensitive test volume is limited, and the signal-to-noise ratio of the received signals is improved. This paper presents the validation of the newly developed phased array borehole probe by beam computation in CIVA software and experimental investigations on a semi-cylindrical test specimen to investigate the directional characteristics. In combination with geophysical reconstruction techniques, an optimised radiation pattern of the probe is expected to improve the signal quality and thus increase the reliability of the imaging results.
This is of great importance for the construction of safe sealing structures needed for the disposal of radioactive or toxic waste.
Laser powder bed fusion (PBF-LB/M) of metallic alloys is a layer wise additive manufacturing process which provides significant scope for more efficient designs of components, benefiting performance and weight, leading to efficiency improvements for various sectors of industry. However, to benefit from these design freedoms, knowledge of the high produced induced residual stress and mechanical property anisotropy associated with the unique microstructures is critical. X-ray and neutron diffraction are considered the benchmark for non-destructive characterization of surface and bulk internal residual stress. The latter, characterized by the high penetration power in most engineering alloys, allows for the use of diffraction angle close to 90° enabling a near cubic sampling volume to be specified. However, the complex microstructures of columnar growth with inherent crystallographic texture typically produced during PBF-LB/M of metallics present significant challenges to the assumptions typically required for time efficient determination of residual stress. These challenges include the selection of an appropriate set of diffraction elastic constants and a representative strain-free reference for the material of interest. In this presentation advancements in the field of diffraction-based residual stress analysis of L-PBF Inconel 718 will be presented. The choice of an appropriate set of diffraction-elastic constants depending on the underlying microstructure will be described.
Ein Umlaufkühler ist im Betrieb explodiert. Splitter des zerborstenen Gehäuses aus Kunststoff wurden mit dem Kühlwasser in die Umgebung geschleudert, am Betriebsort entstand Personenschaden. Bei Funktionsprüfungen am beschädigten Gerät traten unerwartet - aber reproduzierbar - Knalleffekte bei Berührung der Außenoberfläche der Kupfer-Kühlschlange auf. Ein möglicher Mechanismus konnte im Labor durch Synthese von Kupferazid auf Kupferproben und Auslösung vergleichbarer Knalleffekte nachgestellt werden. Damit ist die Plausibilität des beschriebenen Schadensereignisses mit diesem oder einem ähnlich reagierenden Stoff belegt. Ein eindeutiger Nachweis darüber, dass bei dem aufgetretenen Schadensfall dieselbe chemische Reaktion stattgefunden hat, war nicht möglich, da die Belag-Überreste aus dem explodierten Kühlgerät für eine Analyse nicht mehr in ausreichender Menge verfügbar gewesen sind.
WEBSLAMD
(2022)
The objective of SLAMD is to accelerate materials research in the wet lab through AI. Currently, the focus is on sustainable concrete and binder formulations, but it can be extended to other material classes in the future.
1. Summary
Leverage the Digital Lab and AI optimization to discover exciting new materials Represent resources and processes and their socio-economic impact.
Calculate complex compositions and enrich them with detailed material knowledge. Integrate laboratory data and apply it to novel formulations. Tailor materials to the purpose to achieve the best solution.
Workflow
Digital Lab
Specify resources: From base materials to manufacturing processes – "Base" enables a detailed and consistent description of existing resources
Combine resources: The combination of base materials and processes offers an almost infinite optimization potential. "Blend" makes it easier to design complex configurations.
Digital Formulations: With "Formulations" you can effortlessly convert your resources into the entire spectrum of possible concrete formulations. This automatically generates a detailed set of data for AI optimization.
AI-Optimization
Materials Discovery: Integrate data from the "Digital Lab" or upload your own material data. Enrich the data with lab results and adopt the knowledge to new recipes via artificial intelligence. Leverage socio-economic metrics to identify recipes tailored to your requirements.
With 8% of man-made CO2 emissions, cement production is an important driver of the climate crisis. By using alkali-activated binders, part of the energy-intensive clinker production process can be dispensed. However, as numerous raw materials are involved in the manufacturing process here, the complexity of the materials increases by orders of magnitude. Finding a properly balanced binder formulation is like looking for a needle in a haystack. We have shown for the first time that artificial intelligence (AI)-based optimization of alkali-activated binder formulations can significantly accelerate research.
The "Sequential Learning App for Materials Discovery" (SLAMD) aims to accelerate practice transfer. With SLAMD, materials scientists have low-threshold access to AI through interactive and intuitive user interfaces. The value added by AI can be determined directly. For example, the CO2 emissions saved per ton of cement can be determined for each development cycle: the more efficient the AI optimization, the greater the savings.
Our material database already includes more than 120,000 data points of alternative binders and is constantly being expanded with new parameters. We are currently driving the enrichment of the data with a life cycle analysis of the building materials.
Based on a case study we show how intuitive access to AI can drive the adoption of techniques that make a real contribution to the development of resource-efficient and sustainable building materials of the future and make it easy to identify when classical experiments are more efficient.
With 8% of man-made CO2 emissions, cement production is an important driver of the climate crisis. By using alkali-activated binders, part of the energy-intensive clinker production process can be dispensed. However, as numerous raw materials are involved in the manufacturing process here, the complexity of the materials increases by orders of magnitude. Finding a properly balanced binder formulation is like looking for a needle in a haystack. We have shown for the first time that artificial intelligence (AI)-based optimization of alkali-activated binder formulations can significantly accelerate research.
The "Sequential Learning App for Materials Discovery" (SLAMD) aims to accelerate practice transfer. With SLAMD, materials scientists have low-threshold access to AI through interactive and intuitive user interfaces. The value added by AI can be determined directly. For example, the CO2 emissions saved per ton of cement can be determined for each development cycle: the more efficient the AI optimization, the greater the savings.
Our material database already includes more than 120,000 data points of alternative binders and is constantly being expanded with new parameters. We are currently driving the enrichment of the data with a life cycle analysis of the building materials.
Based on a case study we show how intuitive access to AI can drive the adoption of techniques that make a real contribution to the development of resource-efficient and sustainable building materials of the future and make it easy to identify when classical experiments are more efficient.
Vorstellung der Themen der Nachwuchsgruppe "Materialcharakterisierung und -informatik für die Nachhaltigkeit im Bauwesen" von Prof. Sabine Kruschwitz (TU Berlin und BAM)
High greenhouse gas emissions from the production of building materials are a major contributor to the current climate crisis. However, developing alternative building materials is complex. Traditional laboratory methods are reaching their limits. Artificial intelligence, on the other hand, can give research a new dynamic.
Novel materials are usually developed manually in the laboratory rather than on a computer. This makes the processes time-consuming, difficult and expensive. With the app SLAMD (Sequential Learning App for Materials Discovery), materials researchers can explore the potential of artificial intelligence to speed up materials research and easily apply AI in the lab. The app was developed by our team at the Federal Institute for Materials Research and Testing (BAM) led by Prof. Sabine Kruschwitz together with a team in the Department of Building Materials and Construction Chemistry at TU Berlin led by Prof. Dietmar Stephan.
It uses material composition and characterization data to predict ideal material candidates. It can be used to optimize many material properties simultaneously and even incorporates database information such as carbon footprint, material cost or resource availability. Unlike the usual data-intensive AI methods, SLAMD optimally integrates existing knowledge and human feedback, and provides numerous decision support tools to precisely navigate complex scientific knowledge processes towards success.
In this talk, we will present some case studies where we were able to find suitable advanced materials in a few months instead of several years. We will talk about the challenges we overcame and the future potential we see for this approach to developing the green materials of the future.
SLAMD-FIB-Case-Study
(2022)
With 8% of man-made CO2 emissions, cement production is an important driver of the climate crisis. By using alkali-activated binders part of the energy-intensive clinker production process can be dispensed with. However, because numerous chemicals are involved in the manufacturing process here, the complexity of the materials increases by orders of magnitude. Finding a properly balanced cement formulation is like looking for a needle in a haystack. We have shown for the first time that artificial intelligence (AI)-based optimization of cement formulations can significantly accelerate research. The „Sequential Learning App for Materials Discovery“ (SLAMD) aims to accelerate practice transfer. With SLAMD, materials scientists have low-threshold access to AI through interactive and intuitive user interfaces. The value added by AI can be determined directly. For example, the CO2 emissions saved per ton of cement can be determined for each development cycle: the more efficient the AI optimization, the greater the savings. Our material database already includes more than 120,000 data points of alternative cements and is constantly being expanded with new parameters. We are currently driving the enrichment of the data with a life cycle analysis of the building materials. Based on a case study we show how intuitive access to AI can drive the adoption of techniques that make a real contribution to the development of resource-efficient and sustainable building materials of the future and make it easy to identify when classical experiments are more efficient.
With 8% of man-made CO2 emissions, cement production is an important driver of the climate crisis. By using alkali-activated binders, part of the energy-intensive clinker production process can be dispensed. However, as numerous raw materials are involved in the manufacturing process here, the complexity of the materials increases by orders of magnitude. Finding a properly balanced binder formulation is like looking for a needle in a haystack. We have shown for the first time that artificial intelligence (AI)-based optimization of alkali-activated binder formulations can significantly accelerate research.
The "Sequential Learning App for Materials Discovery" (SLAMD) aims to accelerate practice transfer. With SLAMD, materials scientists have low-threshold access to AI through interactive and intuitive user interfaces. The value added by AI can be determined directly. For example, the CO2 emissions saved per ton of cement can be determined for each development cycle: the more efficient the AI optimization, the greater the savings.
Our material database already includes more than 120,000 data points of alternative binders and is constantly being expanded with new parameters. We are currently driving the enrichment of the data with a life cycle analysis of the building materials.
Based on a case study we show how intuitive access to AI can drive the adoption of techniques that make a real contribution to the development of resource-efficient and sustainable building materials of the future and make it easy to identify when classical experiments are more efficient.
Since metal additive manufacturing (AM) becomes more and more established in industry, also the cost pressure for AM components increases. One big cost factor is the quality control of the manufactured components. Reliable in-process monitoring systems are a promising route to lower scrap rates and enhance trust in the component and process quality.
The focus of this contribution is the presentation and comparison of two optical tomography based multi measurand in-situ monitoring approaches for the L-PBF process: the bicolor- and the RGB-optical tomography. The classical optical tomography (OT) is one of the most common commercial in-situ monitoring techniques in industrial L-PBF machines. In the OT spatial resolved layer-images of the L-PBF process are taken from an off-axis position in one near infrared wavelength window. In addition to the explanatory powers classical OT, both here presented approaches enable the determination of the maximum surface temperature. In contrast to thermography that may also yield maximum temperature information, the needed equipment is significantly cheaper and offers a higher spatial resolution. Both approaches are implemented at a new in-house developed L-PBF system (Sensor-based additive manufacturing machine - SAMMIE). SAMMIE is specifically designed for the development and characterization of in-situ monitoring systems and is introduced as well.
Im Auftrag des Bundesministeriums für Wirtschaft und Klimaschutz haben DIN und DKE im Januar 2022 die Arbeiten an der zweiten Ausgabe der Deutschen Normungsroadmap Künstliche Intelligenz gestartet. In einem breiten Beteiligungsprozess und unter Mitwirkung von mehr als 570 Fachleuten aus Wirtschaft, Wissenschaft, öffentlicher Hand und Zivilgesellschaft wurde damit der strategische Fahrplan für die KI-Normung weiterentwickelt. Koordiniert und begleitet wurden diese Arbeiten von einer hochrangigen Koordinierungsgruppe für KI-Normung und -Konformität.
Mit der Normungsroadmap wird eine Maßnahme der KI-Strategie der Bundesregierung umgesetzt und damit ein wesentlicher Beitrag zur „KI – Made in Germany“ geleistet.
Die Normung ist Teil der KI-Strategie und ein strategisches Instrument zur Stärkung der Innovations- und Wettbewerbsfähigkeit der deutschen und europäischen Wirtschaft. Nicht zuletzt deshalb spielt sie im geplanten europäischen Rechtsrahmen für KI, dem Artificial Intelligence Act, eine besondere Rolle.
Seit der Antike gehört die Medea-Sage zu den bekanntesten Geschichten der Weltliteratur. Der berühmte französische Künstler Carle Van Loo hat sich dieses Epos um 1759 angenommen und ein beeindruckendes Ölgemälde mit Abmessungen von 2,30x3,28m² erschaffen. Mit Mademoiselle Clairon als Medea und Henri Louis Le Kain als Jason ist ein Kunstwerk entstanden, das seitdem einige Veränderungen und Restaurierungen erfahren hat.
Die Bundesanstalt für Materialforschung und -prüfung (BAM) hatte 2020 die Möglichkeit, dieses und ein zweites Kunstwerk, im Neuen Palais in Potsdam, für die Stiftung Preußische Schlösser und Gärten Berlin-Brandenburg, radiografisch zu untersuchen. Hierbei wurden sowohl technologisch als auch kunsthistorisch einige interessante Entdeckungen gemacht, die im vorliegenden Beitrag vorgestellt werden.
Als bildgebendes und zerstörungsfreies Verfahren eignet sich die Röntgen-Computertomographie (CT) insbesondere bei der Untersuchung von Kunst- und Kulturgütern. Die für Werkstoffprüfung und Materialanalyse konzipierten CT-Anlagen bieten dank hoher Röntgenleistung die Möglichkeit zusätzlich zu Holz, Keramiken und Kunststoffen auch stark schwächende Materialien, wie bspw. Metalle, zu durchdringen. Für eine hohe räumliche Auflösung im unteren Mikrometerbereich (2-200µm) sorgen entsprechend ausgelegte CT-Anlagen. In der Bundesanstalt für Materialforschung und -prüfung (BAM) stehen mehrere solcher CT-Anlagen für unterschiedliche Fragestellungen sowie Probengrößen und - materialien zur Verfügung. Einige Beispiele aus den vergangenen Arbeiten der BAM veranschaulichen das große Potential dieser Untersuchungsmethode.
Da bei einer CT-Messung in der Regel das gesamte Untersuchungsobjekt erfasst und in ein digitales Volumenmodell überführt wird, eröffnet sich für Archäologen und Restoratoren die Möglichkeit Untersuchungen hinsichtlich Materialzusammensetzung, Erhaltungszustand und Herstellungstechnik am virtuellen Objekt vorzunehmen, ohne die Originalsubstanz zu beeinträchtigen. Gegenüber der klassischen Radiografie, bei der nur eine zweidimensionale Abbildung erreicht wird, bietet die CT-Untersuchung die Möglichkeit innenliegende Strukturen dreidimensional zu erfassen. Die notwendige Bestimmung der Objektoberfläche erlaubt zudem die Erstellung eines Oberflächenmodells des untersuchten Gegenstandes. Damit lassen sich unter anderem mechanische Simulationen (Belastung, Durchbiegung, Durchströmung) durchführen. Der erzeugte Datensatz kann somit auch zur Herstellung eines Replikats im 3D-Druckverfahren genutzt werden. Anhand der Untersuchung der Mandoline von Smorsone wird gezeigt, wie eine CT-Messung durchgeführt wird und wie in dem anschließend rekonstruierten 3D-Datensatz mittels Koordinatenmesstechnik Maße (Abstände, Wandstärken, Winkel) exakt ermittelt werden können.
Additive manufacturing methods such as laser powder bed fusion (LPBF) allow geometrically complex parts to be manufactured within a single step. However, as an aftereffect of the localized heat input, the rapid cooling rates are the origin of the large residual stress (RS) retained in as-manufactured parts. With a view on the microstructure, the rapid directional cooling leads to a cellular solidification mode which is accompanied by columnar grown grains possessing crystallographic texture. The solidification conditions can be controlled by the processing parameters and the scanning strategy. Thus, the process allows one to tailor the microstructure and the texture to the specific needs. Yet, such microstructures are not only the origin of the mechanical anisotropy but also pose metrological challenges for the diffraction-based RS determination. In that context the micromechanical elastic anisotropy plays an important role: it translates the measured microscopic strain to macroscopic stress. Therefore, it is of uttermost importance to understand the influence of the hierarchical microstructures and the texture on the elastic anisotropy of LPBF manufactured materials.
This study reveals the influence of the build orientation and the texture on the micro-mechanical anisotropy of as-built Inconel 718. Through variations of the build orientation and the scanning strategy, we manufactured specimens possessing [001]/[011]-, [001]-, and [011]/[111]-type textures. The resulting microstructures lead to differences in the macroscopic mechanical properties. Even further, tensile in-situ loading experiments during neutron diffraction measurements along the different texture components revealed differences in the microstrain response of multiple crystal lattice planes. In particular, the load partitioning and the residual strain accumulation among the [011]/[111] textured specimen displayed distinct differences measured up to a macroscopic strain of 10 %. However, the behavior of the specimens possessing [001]/[011]-and [001]-type texture was only minorly affected. The consequences on the metrology of RS analysis by diffraction-based methods are discussed.
The formation of irregularities such as keyhole porosity pose a major challenge to the manufacturing of metal parts by laser powder bed fusion (PBF-LB/M). In-situ thermography as a process monitoring technique shows promising potential in this manner since it is able to extract the thermal history of the part which is closely related to the formation of irregularities. In this study, we investigate the utilization of machine learning algorithms to detect keyhole porosity on the base of thermographic features. Here, as a referential technique, x-ray micro computed tomography is utilized to determine the part's porosity. An enhanced preprocessing workflow inspired by the physics of the keyhole irregularity formation is presented in combination with a customized model architecture. Furthermore, experiments were performed to clarify the role of important parameters of the preprocessing workflow for the task of defect detection . Based on the results, future demands on irregularity prediction in PBF-LB/M are derived.
The appearance of irregularities such as keyhole porosity is a major challenge for the production of metal parts by laser powder bed fusion (PBF-LB/M). The utilization of thermographic in-situ monitoring is a promising approach to extract the thermal history which is closely related to the formation of irregularities. In this study, we investigate the utilization of convolutional neural networks to predict keyhole porosity based on thermographic features. Here, the porosity information calculated from an x-ray micro computed tomography scan is used as reference. Feature engineering is performed to enable the model to learn the complex physical characteristics of the porosity formation. The model is examined with regard to the choice of hyperparameters, the significance of thermal features and characteristics of the data acquisition. Based on the results, future demands on irregularity prediction in PBF-LB/M are derived.