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Dieses Dokument enthält die Präsentationsfolien des BAM-Teams beim Abschlusstreffen des Forschungsprojekts DiMoWind-Inspect. Es wurden die Arbeitspakete Datenmanagement, Referenzkennzeichnungssystem, Grundlagen der Schadensbewertung, Risikobasierte Inspektions- und Instandhaltungsplanung und Schadensdetektion mittels Risslumineszenz sowie eine abschließende Bewertung des Projekts vorgestellt.
Aufbauend auf dem historischen Schadensfall von A. Martens im Jahr 1894 zur Explosion von H2-Gasflaschen auf dem Tempelhofer Feld und den dabei durchgeführten Untersuchungen wird im Hauptteil des Vortrages auf die Standardisierung der Hohlzugprüftechnik eingegangen. Dabei wird zunächst auf die Vor- und Nachteile unterschiedlicher Prüfmöglichkeiten zur Wasserstoffkompatibilität metallischer Werkstoffe und deren Schweißverbindungen eingegangen und im Weiteren die Umsetzung der Prüftechnik an der BAM beschrieben. Für die Standardisierung der Hohlzugprüftechnik wurden verschiedene Randbedingungen mit Einfluss auf die Ergebnisqualität überprüft. Dabei wurde der Pipelinestahl X65 als auch der additiv gefertigte Werkstoff 316L genutzt. Abschließend wird auf die Verwaltungspartnerschaft mit Namibia eingegangen und die umzusetzenden Projekte mit Bezug zur Schweißtechnik dargestellt.
Powder bed technologies are amongst the most successful Additive Manufacturing (AM) techniques. The application of these techniques to most ceramics has been difficult so far, because of the challenges related to the deposition of homogeneous powder layers when using fine powders.
In this context, the "layerwise slurry deposition" (LSD) has been developed as a layer deposition method enabling the use of powder bed AM technologies also for advanced ceramic materials. The layerwise slurry deposition consists of the layer-by-layer deposition of a ceramic slurry by means of a doctor blade, in which the slurry is deposited and dried to achieve a highly packed powder. Not only very fine, submicron powders can be processed with low organics, but also the dense powder bed provides excellent support to the parts built.
The latest development of this technology shows that it is possible to print ceramic parts in a continuous process by depositing a layer onto a rotating platform, growing a powder bed following a spiral motion. The unique mechanical stability of the layers in LSD-print allows to grow a powder bed several centimeters thick without any lateral support. The continuous layer deposition allows to achieve a productivity more than 10X higher compared to the linear deposition, approaching a build volume of 1 liter/hour.
Understanding interfacial chemistry: probing surface modifications by differential phage display
(2024)
Phage surface display combined with next-generation sequencing allows for the in-depth analysis of millions of sequences and enables the discovery of specific target binding peptides. The vast amount of valuable data from next-generation phage display experiments on material surfaces can be used to gain insight into peptide-based molecular interactions to reveal the local interfacial chemistry. The talk will discuss a developed differential strategy for data-driven probing of 3D printed electrodes before and after electrochemical activation.
Hybrid additive manufacturing plays a crucial role in the restoration of gas turbine blades, where e.g., the damaged blade tip is reconstructed by the additive manufacturing process on the existing blade made of a parent nickel-based alloy. However, inherent process-related defects in additively manufactured material, along with the interface created between the additively manufactured and the cast base material, impact the fatigue crack growth behavior in bi-material components. This study investigates the fatigue crack growth behavior in bi-material specimens of nickel-based alloys, specifically, additively manufactured STAL15 and cast alloy 247DS. The tests were conducted at 950 °C with stress ratios of 0.1 and -1. Metallographic and fractographic investigations were carried out to understand crack growth mechanisms. The results revealed significant retardation in crack growth at the interface. This study highlights the potential contributions of residual stresses and microstructural differences to the observed crack growth retardation phenomenon, along with the conclusion from an earlier study on the effect of yield strength mismatch on crack growth behavior at a perpendicular interface in bi-material specimens.
Therapeutic monoclonal antibodies are the fastest-growing class of biological agents and the development of reliable analytical methods for their quantification is becoming increasingly important. Liquid chromatography coupled with tandem mass spectrometry (LC–MS/MS) represents one of the leading technologies for antibody quantification. The serin protease trypsin has emerged as the gold standard enzyme for digesting intact protein into peptides for this approach. However, many protocols exist that often lead to different results. The talk will provide a brief introduction to the application of novel thermostable and surface-functionalized trypsin particles for improved antibody digestion as well as initial successes in polymer functionalization of the corundum surface to prevent nonspecific protein adsorption during the digestion procedure.
Die zerstörungsfreie Prüfung von Eisenbahnschienen auf betriebsbedingte Schädigungen wird mit Schienenprüfzügen mittels Ultraschall- und Wirbelstromprüfverfahren durchgeführt [1]. Die Auswertung der Prüfdaten erfolgt überwiegend manuell, die eingesetzte Software unterstützt die Auswertenden lediglich durch eine Vorauswahl relevanter Anzeigen. Die Überprüfung der Ergebnisse erfolgt anschließend vor Ort mittels handgeführter Prüfgeräte. Instandhaltungsmaßnahmen werden auf Basis der Befundung vor Ort abgeleitet.
Ziel des durch das Bundesministerium für Digitales und Verkehr (BMDV) im Rahmen von mFUND unter dem Förderkennzeichen 19FS2014 geförderten Vorhabens AIFRI (Artificial Intelligence For Rail Inspection) ist es, durch den Einsatz von KI-Methoden den Automatisierungsgrad des Prüfprozesses von der Auswertung der Daten bis hin zur Planung von Instandhaltungsmaßnahmen zu erhöhen. Die Genauigkeit der Fehlerdetektion soll gesteigert werden, um eine automatisierte Einstufung der aufgefundenen Anzeigen in Risikoklassen zu ermöglichen. Hierfür werden Daten sowohl von Wirbelstromprüfungen als auch Ultraschallprüfungen verwendet.
Im Rahmen des IT-orientierten Projektes werden relevante Schienenschädigungen und in der Schiene vorhandene Artefakte analysiert und in einen parametrierbaren digitalen Zwilling übertragen. Mit diesem digitalen Zwilling werden virtuelle Schädigungsbilder generiert, mit denen KI-Algorithmen auf die Defekterkennung und -klassifizierung trainiert werden. Insbesondere werden hierbei Synergien genutzt, die durch die Verknüpfung von Daten der Wirbelstrom- und Ultraschallprüfung bei einer gemeinsamen Bewertung entstehen. Mit Hilfe von Zuverlässigkeitsbetrachtungen werden die entwickelten und trainierten Algorithmen hinsichtlich der Detektion und Charakterisierung von Schienenschädigungen bewertet.
Im Verlauf des Projektes soll mit dem entwickelten IT-Werkzeug ein Demonstrator aufgebaut und im Feld mit realen Datensätzen getestet werden
Ontologies and data pipelines - a field report from the development of multilayer ferrite inductors
(2024)
Digitalization is a current and prominent cross-cutting topic in ceramics and materials science in general. Many research initiatives and levels of significance are associated with this term. The Initiative Platform MaterialDigital (PMD), for example, aims to create a material data space filled with semantically linked data. The concept envisages that semantic relationships between the data are described as ontologies and that processing of data takes place via automated data pipelines. Various research projects from all areas of materials science are working on the implementation of this concept based on specific use cases. In the project presented here, the use case is the development of multilayer ferrite inductors as passive microelectronic components. The inductors are fabricated by ceramic multilayer technology and co-firing of metallized tapes of NiCuZn ferrite and a dielectric base material. Investigations focus on the effects of fabrication technology on the permeability of the ferrite. A data pipeline is introduced that automatically processes the unstructured experimental data into structured, machine-readable and semantically linked data. The concrete implementation of the data pipeline and a domain ontology is presented using examples. Challenges and advantages are discussed.
Bias Identification Approaches for Model Updating of Simulation-based Digital Twins of Bridges
(2024)
Simulation-based digital twins of bridges have the potential not only to serve as monitoring devices of the current state of the structure but also to generate new knowledge through physical predictions that allow for better-informed decision-making. For an accurate representation of the bridge, the underlying models must be tuned to reproduce the real system. The updated model can be eventually used for the extension of the service life of the bridge based on an accurate description of the structure. Nevertheless, the necessary assumptions and simplifications in these models irremediably introduce discrepancies between measurements and model response. We will prove that quantifying the extent of the uncertainties generated by said discrepancies provides a better understanding of the real system, enhances the model updating process, and creates more robust and trustworthy digital twins. Among others, we identify that the inclusion of the explicit bias term through a Bayesian inference framework corrects the tuned parameters, allows the identification of non-prescribed noise sources and enables the introduction of additional information in the system without modifying the simulation model. The performance of selected model bias identification approaches will be compared in the context of digital twins of bridges. The different methods will be applied to a representative demonstrator case based on the Nibelungenbrücke of Worms. The findings from this work are englobed in the initiative SPP 100+, whose main aim is the extension of the service life of structures through monitorization and digitalization, especially through the implementation of digital twins.
The changes in the use and maintenance of track systems poses new challenges for the periodic mechanized in-service testing of rails using ultrasound and eddy current. The methods currently applied have been used since decades with only minor changes. To face the new challenges generated by modern drive systems, higher speeds, heavier loads adapted techniques have to be developed to detect new defect types and artefacts generated by new production methods. Especially the area where rolling contact fatigue takes place is under focus.
Going beyond the standard conventional ultrasound setups used since the 1950 enables a more detailed detection and classification of rail defects and size estimation. Eddy current methods are applied for surface crack detection and head check depth quantification at the gauge corner of railway tracks. An extension of the tested zone to the running surface uncloses rail defect signal types other than head checks to be detected and estimated in type and size.
For the automated evaluation of the recorded data algorithms based on artificial intelligence being trained based on simulation will be applied. Typically, the testing parameter vary depending on the track condition and the probe wear. To identify variables and parameters which have a significant influence on the overall performance of the test run modelling of the setup can be used.
Actual developments will be presented in this talk
Die mechanisierte zerstörungsfreie Prüfung von Eisenbahnschienen auf betriebsbedingte Schädigungen wird mit Schienenprüfzügen mittels Ultraschall- und Wirbelstromprüfverfahren durchgeführt. Die Auswertung der Prüfdaten erfolgt durch Auswerter, die Überprüfung der Ergebnisse erfolgt am identifizierten Schienensegment vor Ort mittels handgeführter Prüfgeräte. Instandhaltungsmaßnahmen werden anschließend auf Basis der Befundung der zerstörungsfreien Prüfung abgeleitet. Im Rahmen eines vom BMVI geförderten Verbundvorhabens im Programm „Digitale, datenbasierte Innovationen und Ideen für die Mobilität 4.0“ (mFUND) soll dieses Konzept modernisiert und weiterentwickelt werden.
Ziele des Vorhabens AIFRI (Artificial Intelligence For Rail Inspection) sind es, durch den Einsatz von KI-Methoden den Automatisierungsgrad des Prüfprozesses zu erweitern, die Genauigkeit der Fehlerdetektion zu erhöhen und eine automatisierte Einstufung der aufgefundenen Anzeigen in Risikoklassen zu ermöglichen. Weiterhin wird auf dieser Basis ein risikobasiertes Instandhaltungskonzept erarbeitet, welches zukünftig das bisherige präventive Vorgehen ablösen kann.
Im Rahmen des IT-orientierten Projektes werden relevante Schienenschädigungen und in der Schiene vorhandene Artefakte analysiert und in skalierbare Modelle übertragen. Mit diesen Modellen werden virtuelle Schädigungsbilder generiert, mit denen KI-Algorithmen auf die Defekterkennung und -klassifizierung trainiert werden. Mit Hilfe von Zuverlässigkeitsbetrachtungen werden die entwickelten und trainierten Algorithmen hinsichtlich der Detektion und Charakterisierung von Schienenschädigungen bewertet.
Im Verlauf des Projektes wird mit dem entwickelten IT-Werkzeug ein Demonstrator aufgebaut und im Feld mit realen Datensätzen getestet.
Das Projekt wird durch das Bundesministerium für Verkehr und digitale Infrastruktur (BMVI) im Rahmen von mFund unter dem Förderkennzeichen 19FS2014 gefördert.
Aktuelles aus der Normung
(2024)
The creation and use of Digital Twins of existing structures, such as bridges, implies precise digital replicas that accurately mirror their physical counterparts. Ensuring the trustworthiness of Digital Twins and facilitating informed decision-making necessitates a robust approach to Uncertainty Quantification (UQ). A suitable model-updating scheme is key in preserving the quality and robustness of simulation-based Digital Twins. Model bias, stemming from discrepancies between computational models and real-world systems, poses a significant challenge in achieving this goal. This study delves into the challenges posed by model bias within Bayesian updating of Digital Twins of bridges. Two alternative model bias identification methods —a modularized version of Kennedy and O’Hagan’s approach and another one based on Orthogonal Gaussian Processes — are evaluated in comparison with the classical Bayesian inference framework. A key innovation lies in the modification of the aforementioned approaches to incorporate additional information into the Digital Twin framework via the bias term. This enables the extension of the model non-intrusively, leveraging large pools of data inherent in Digital Twins. The study showcases the potential of this approach to correct predictions, quantify uncertainties, and enhance the system with previously untapped information. This underscores the importance of everaging available data within Digital Twins to identify deficiencies and guide potential future model improvements.
Every day, there are new headlines in the media about microplastics (1-1000 µm, ISO/TR 21960:2020) and nanoplastics (< 1 µm, ISO/TR 21960:2020) findings all over the planet with high variations in particle number and mass. The challenges in analytics are very complex, e.g. representative sampling, non-destructive sample preparation with concentrated particles and homogeneous distribution and true detection. All together lead to lacks in harmonization and results, which are hardly comparable. On the other hand, monitoring of microplastics is mandatory in the future strictly regulated by the EU commission in the Drinking water and Wastewater Framework Directive. One step to accurate and precise results will be the development of suitable reference materials mimicking particles in the environment.
BAM developed test materials, which are produced by mixing a small portion of microplastic particles with a water-soluble matrix. After solid phase dilution and homogenisation small portions are pressed into tablets and bottled in glass vials (Figure 1). These tablets are well characterized with particle size distribution and SEM images. Additionally, they are tested as reference material candidate according to homogeneity and stability for particle number with µ-IR and µ-Raman as well as on particle mass with Py-GC/MS and TED-GC/MS after ISO Guide 35. Results are promising. The material passed the homogeneity control. No changes are observed within 6 months of storage.
The same tested reference material is finally used in sample preparation experiments, where environmental suspended particular matter from surface water or baby milk powders are spiked with the tablets.
Microplastic determination in food and surface waters will be increasingly carried out in the course of future directives and regulations, such as EU drinking water directive and wastewater directive. In addition to unique identification, this also includes reliable quantification. Two different methodological approaches are used for the quantification. With vibrational spectroscopic techniques such as µ-FTIR and µ-Raman, results are obtained in the form of particle number, size and shape. Instead, with thermal analytical technics as TED-GC/MS and Py-GC-MS the results are expressed as mass concentration.. Both concepts offer different information variables. In terms of routine monitoring, it is necessary to obtain a rapid sequence from sampling to the detection result. For this reason, this study focuses on TED-GC/MS and Py-GC-MS. Even though thermal analytical methods generally require less sample preparation, some matrices require it. This is usually done if the analyte concentration is too low or if strong matrix effects such as signal suppression and false positive signals occur.
This talk presents advanced sample preparation for baby milk powder as food example and density separation for microplastic analysis in surface waters.
A preparation protocol based on citric acid was selected for the milk to remove as much as possible of the matrix. The low pH value leads to a fast and effective protein precipitation and minimizes filter cake formation, making filtration possible, reduces the number and the amount of compounds in detection and hence, simplifies the evaluation.
Microplastics in surface waters and sediments must be concentrated not only because of their low microplastics mass content but also in terms of homogeneity. For this purpose, a density separation was carried out using a concentrated sodium iodide solution, which led to a high reduction of the inorganic mineral matrix and made possible to obtain a representative subsample of initial masses of up to 80 g.
Die Gruppe der PFAS (Per- und polyfluorierte Alkylsubstanzen) mit mehr als 10.000 Substanzen stellt ein zunehmendes Problem bei der Bewertung und Entsorgung belasteter Abfälle dar. Die zuverlässige PFAS-Analytik stellt hier aufgrund der Vielzahl an Einzelparametern mit zum Teil sehr großen Konzentrationsunterschieden eine komplexe Herausforderung dar.
Der Vortrag gibt zunächst einen Überblick über grundlegende Anforderungen an die LC-MS/MS Analytik von PFAS-Targetsubstanzen. Am Beispiel eines von BAM und SenMVKU organisierten Ringversuches 2024 zur Bestimmung von PFAS in Bodenproben (Feststoffe und Eluate) wird auf spezifische Fragestellungen zur PFAS-Analytik eingegangen.
Zur Verbesserung von Richtigkeit und Vergleichbarkeit ist die Einhaltung von Normvorgaben und die Anwendung von Qualitätssicherungsmaßnahmen unerlässlich. Hierzu gehören u.a. die Verwendung zuverlässiger Kalibrierstandards, die Kalibrierung mit definierten n-Isomeren, die Quantifizierung der Summe aus n-/br-Isomeren, der Einsatz isotopenmarkierter interner Standards für die LC-MS/MS Analyse, die Verwendung von Matrix-Referenzmaterialien sowie die Teilnahme an Ringversuchen.
In September 2023, the European Commission introduced a new regulation to
reduce microplastic (MP) emissions into the environment, including the sale and
use of intentionally added (large) MP < 5 mm (ISO/TR 21960: 2020). This explicitly
applies to the use of synthetic rubber granulate infill in artificial turf installations,
which are complex multi-component systems consisting of multiple synthetic
polymers (Fig. 1). In addition, abrasions of synthetic grass fibres and other turf
components are also considered as MP sources. Although this has a major impact
on public recreational sports, there is so far no sufficient data to estimate the MP
emissions from artificial turf sports pitches into the environment and thus their
relevance as a source of MP pollution.
To close this gap, this study compared environmental contaminant emissions of
three artificial turf scenarios at different ageing states (unaged, artificially and
real-time aged): the past (old turf: fossil based, synthetic infill), present (most
commonly installed in Germany: fossil based, EPDM infill) and future (turf with
recycled grass fibres, no synthetic infill). Accelerated ageing by UV weathering and
mechanical stress was carried out to simulate the outdoor weathering during the
lifespan of approx. 15 years. MP emissions and released environmentally relevant
contaminants posing a risk to the groundwater were simultaneously sampled using
the newly developed Microplastic Eluate Lysimeter manufactured at BAM (Fig. 2).
MP contents were analysed using smart microfilter crucibles (mesh size: 5 μm)
with subsequent MP detection by TED-GC/MS. Additionally, concentrations of
polycyclic aromatic hydrocarbons were determined using GC/MS and heavy metals
using ICP-AES.
This presentation gives an overview on the importance of joining processes for component fabrication in hydrogen technologies. For that reason, the current need and future research and developement activites are highlighted for the three technological fields: hydrogen storage, transport and use (in terms of the emerging field of additive manufacturing). Finally, some remarks are given for necessary changes in the standardization.
A lack of harmonised terminology hinders accurate description of many nano-object properties. An overview on nanoscale reference materials for environmental , health and safety measurements has been provided by Stefaniak et al. Since then several nanoscale reference materials were produced as finely dispersed nanoparticles, including catalytic active silver nanoparticles and iron oxide nanocubes. Polymeric nanoparticles made of polypropylene (PP), polyethylene (PE) and poly(ethylene terephthalate) (PET) are ongoing reference materials projects. A first study on PP has shown that mechanical breakdown of macroscopic PP towards nano PP is possible. Hereby the nano PP is stabilized by a strongly negative zeta potential of – 44 mV. This provides a long-term stability of the nanoparticles at ambient conditions in cases of low ionic strength. Since this nano PP has no added colloidal stabilizers, we suggest this as a potential reference materials candidate for reliable determination PP nanoplastics. Moreover, the nano PP may function as a reference for the estimation of possible toxic effects of nanoplastics. Efforts in producing nano PP labeled with ultra-small gold nanoparticles are reported.
Compound semiconductors (CS) are promising materials for the development of high-power electrical applications. They have low losses, can withstand high temperatures and can operate at very high voltages and currents. This makes them a key technology for the electrification of many high energy applications, especially electromobility and HVDC power lines.
The challenge with CS technology is that most of the process technology has to be developed anew to the high standards required by electronic applications. Today, compound semiconductors can be produced in thin layers on top of substrates fabricated from classical crystal growth processes that are already well established. A promising method for this is metal organic vapour phase epitaxy (MOVPE). With this method, many different compounds with semiconducting properties can be synthesized. Additionally, this process technology is a direct thin layer deposition method. Therefore, complex multilayer systems can be generated directly by the deposition process and without the need of doping after growing.
There are a number of critical defects that can originate from the deposition process of these thin film devices. Within this project, we intend to develop new correlative imaging and analysis techniques to determine defect types, to quantify defect size and number density, as well as to characterise defects for process optimisation.
We report here on the use of spectroscopic ellipsometry and imaging ellipsometry to investigate defects in several different compound semiconductor materials used in high-power electronic devices. The materials we investigated are β-Ga2O3, SiC, GaN, AlN, and AlGaN materials as well as oxidised SiC surfaces. All of these materials have their typical defects and require optimised measurement and analysis schemes for reliable detection and analysis. Spectroscopic ellipsometry is a highly sensitive method for determining the thicknesses and dielectric function of thin layers, yielding potentially a high number of microscopic properties. The combined method between ellipsometry and optical microscopy is called imaging ellipsometry and is especially powerful for the large amount of data it produces. We have analysed defects in SiC- and AlN-based thin film semiconductors as well as characterised the properties of different types of SiO2 layers created on top of SiC monocrystals. We developed ellipsometric models for the data analysis of the different semiconductor materials.
If the defects have geometric features, it is useful to combine the ellipsometric analysis with topometry method like interference microscopy and scanning probe microscopy. We have successfully characterised function-critical defects in MOVPE SiC layers and correlated the findings with topography from WLIM measurements. We have developed an imaging ellipsometric measurement methodology that allows to estimate the relative defect area on a surface by a statistical raw data analysis.