BAM Dissertationen ohne Nummerierung
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The present Ph.D. thesis provides a comprehensive experimental and theoretical study of the bulging-cracking relationship in laser beam welding of thick unalloyed steel sheets. It focuses on experimentally proving the existence of the bulging region and on developing a coupled multiphysics mathematical framework to analyze its influence on the three critical factors controlling the susceptibility to solidification cracking, namely the thermal, metallurgical, and mechanical factors.
The research employs a novel experimental setup, utilizing a combination of transparent quartz glass and thick unalloyed steel sheet, enabling real-time visualization of the weld pool geometry and confirming the existence of a distinctive bulging region. To deepen the understanding of these experimental insights, an extensive multiphysics mathematical framework was developed and rigorously verified and validated. This framework introduces an innovative approach using Lamé curves for accurately describing complex three-dimensional weld pool geometries, including the bulging region's characteristics. Through analytical solutions and numerical procedures, it facilitates the computation of solidification parameters, which are crucial for understanding the metallurgical aspects of crack formation. The framework also incorporates a mechanical model to assess and evaluate the local stress distribution within the bulging region.
The findings indicate that an elongated, sharply shaped bulging region significantly increases the susceptibility to solidification cracking. This is attributed to its adverse impact on the distribution and local dwell time of liquid metal residing at grain boundaries during solidification, combined with the localized tensile stresses identified in the bulging region.
In essence, this research contributes to the broader understanding of solidification cracking in laser beam welding of thick unalloyed steel sheets, with a particular focus on the bulging region. The insights and methodologies developed in this thesis are valuable for future research and advancements in the application of the laser beam welding technology for joining high-thickness unalloyed steel components.
Die additive Fertigung (AM) metallischer Werkstoffe ist eine Technologie, die zunehmend Gegenstand von Forschungsaktivitäten und industrieller Anwendung ist. Dennoch steht sie noch vor Herausforderungen, um eine breite Nutzung in sicherheitsrelevanten Anwendungen zu erreichen. Die Hauptgründe für die Verzögerung des technologischen Durchbruchs zugunsten von AM-Metallen gegenüber konventionell hergestellten Varianten sind das Fehlen eines tieferen Verständnisses der Prozess-Struktur-Eigenschafts-Beziehungen und die begrenzte Verfügbarkeit von Daten zu den Materialeigenschaften. In diesem Kontext stellt diese Arbeit einen Beitrag sowohl zum Verständnis der Prozess-Struktur-Eigenschafts-Beziehungen als auch zur Verbesserung der Datenlage von 316L dar, einem häufig als Konstruktionswerkstoff in verschiedenen Hochtemperaturbauteilen verwendeten Werkstoff. Die Arbeit legt den Fokus auf die mittels Laser-Pulverbettschmelzen hergestellte Werkstoffvariante, PBF-LB/M/316L. Eine konventionell hergestellte Variante, HR/316L, wurde auch untersucht. Bei PBF-LB/M/316L wurde zusätzlich der Effekt ausgewählter Wärmebehandlungen ausgewertet. Die Untersuchung umfasste die Charakterisierung der mechanischen Eigenschaften und der Verformungs- und Schädigungsmechanismen bei erhöhten Prüftemperaturen bei LCF und Kriechen, wo die Daten und Wissenslage am spärlichsten ist. Außerdem hat die untersuchte PBF-LB/M/316L-Wersktoffvariante einen geringen Porositätsgrad. Somit hat diese Arbeit die Mikrostruktur stärker in den Fokus genommen als die meisten bisher in der Literatur verfügbaren Studien.
Die mechanische Prüfkampagne umfasste Zugversuche zwischen Raumtemperatur und 650 °C, LCF-Versuche zwischen Raumtemperatur und 600 °C sowie Kriechversuche bei 600 °C und 650 °C. In Ermangelung konkreter Richtlinien und Normen wurde die Charakterisierung zumeist anhand der bestehenden internationalen Prüfnormen und Probengeometrien durchgeführt. Aus jedem dieser Prüfverfahren wurden die entsprechenden Festigkeits- und Verformungskennwerte ermittelt. Darüber hinaus wurde mit Hilfe gezielter mikrostruktureller Untersuchungen ein Beitrag zum Verständnis des Zusammenhangs zwischen der Mikrostruktur und den mechanischen Eigenschaften in Bezug auf die Verformungs- und Schädigungsmechanismen geleistet.
Die Dehngrenze von PBF-LB/M/316L ist etwa doppelt so hoch wie die von HR/316L und dieser Trend setzt sich mit ansteigender Prüftemperatur fort. Die Bruchdehnung ist bei allen Prüftemperaturen geringer. PBF-LB/M/316L weist über den größten Teil der Ermüdungslebensdauer vor allem bei Raumtemperatur höhere zyklische Spannungen als HR/316L auf. Ausschließlich bei den kleinsten Dehnungs-schwingbreiten sind die Ermüdungslebensdauer ausgeprägt kürzer. Das Wechselverformungsverhalten von PBF-LB/M/316L ist durch eine Anfangsverfestigung gefolgt von einer kontinuierlichen Entfestigung charakterisiert, welche bis zum Auftreten der zum Versagen führenden Entfestigung stattfindet. Die Kriechbruchzeiten und die Dauer jeder Kriechphase sind bei allen Kombinationen von Prüfparametern bei PBF-LB/M/316 kürzer als bei HR/316L. Die Spannungsabhängigkeit von PBF-LB/M/316L ist im Vergleich zu HR/316L geringer und die Duktilität beim Kriechen kleiner. Die minimale Kriechrate wird bei allen geprüften Parameterkombinationen bei deutlich geringeren Kriechdehnungen erreicht. Eine Wärmebehandlung bei 450 °C / 4 h bewirkt keine wesentliche Änderungen der Mikrostruktur und Zugversuchseigenschaften. Eine zusätzliche Wärmebehandlung bei 900 °C / 1 h verursacht eine Abnahme der Dehngrenze des PBF-LB/M/316L. Diese blieb aber immer noch um den Faktor 1,5x höher als bei HR/316L. Die Verformungsmerkmale wurden kaum davon beeinflusst. Bezüglich des Kriechverhaltens hat die Wärmebehandlung bei 900 °C / 1 h längere sekundäre und tertiäre Kriechstadien bewirkt und die Kriechdehnung hat sich signifikant erhöht. Die Bruchbilder unterscheiden sich generell nicht nur aber vor allem mit ansteigender Prüftemperatur, bei der bei PBF-LB/M/316L oft interkristalline Rissbildung beobachtet wurde. Die Zellstruktur trägt als der Hauptfaktor zu den unterschiedlichen mechanischen Eigenschaften im Vergleich zur HR/316L-Variante bei. Darüber hinaus spielen mutmaßlich die Kornmorphologie, die Stapelfehlerenergie und der Stickstoffgehalt eine Rolle.
Additive manufacturing (AM) offers significantly greater freedom of design compared to conventional manufacturing processes since the final parts are built layer by layer. This enables metal AM, also known as metal 3D printing, to be utilized for improving efficiency and functionality, for the production of parts with very complex geometries, and rapid prototyping. However, despite many technological advancements made in recent years, several challenges hinder the mass adoption of metal AM. One of these challenges is mechanical anisotropy which describes the dependency of material properties on the material orientation. Therefore, in this work, stainless steel 316L parts produced by laser-based powder bed fusion are used to isolate and understand the root cause of anisotropy in AM parts. Furthermore, an efficient and accurate multiscale numerical framework is presented for predicting the deformation behavior of actual AM parts on the macroscale undergoing large plastic deformations. Finally, a novel constitutive model for the plastic spin is formulated to capture the influence of the microstructure evolution on the material behavior on the macroscale.
The contamination of drinking water with pharmaceuticals represents a severe health risk. In order to monitor the drinking water quality continuously and enable quick countermeasures in case of contamination, novel sensors are required. Here, immunoanalytical methods based on the binding of the analyte to highly selective antibodies can be helpful. In this work, magnetic bead-based immunoassays (MBBAs) have been developed for the detection of two relevant contaminants of drinking water: diclofenac (DCF) and amoxicillin (AMX). In case of the latter, not only the parent drug is of interest in the risk assessment but also its hydrolysis products (HPs). In a comprehensive study, the influence of external factors and intrinsic properties of the water on the rate of hydrolysis was investigated. As the hydrolysis of AMX further impacts the recognition by the antibody, a strategy to analyze samples with unknown hydrolysis degree of AMX was established employing the enzyme β-lactamase in sample preparation. For both analytes, the MBBAs enable the fast quantification with results obtained in less than one hour which represents a major improvement over conventional immunoassays like the enzyme-linked immunosorbent assay (ELISA). Compared to the respective ELISAs with the same antibodies, the MBBAs further exhibit improved analytical parameters such as a broader measurement range and lower limits of detection. Due to the magnetic properties of the beads that serve as a platform for the assays, they are suitable for the mobile and automated detection at the point-of-care. An integrated diagnostic system was designed in which electrochemical detection with chronoamperometry on a microfluidic chip allows for further miniaturization of the system to enable monitoring of the drinking water quality online in water supply pipes at waterworks.
Development of electrochemical antibody-based and enzymatic assays for mycotoxin analysis in food
(2023)
Electrochemical methods are promising to meet the demand for easy-to-use devices monitoring key parameters in the food industry. Many companies run own lab procedures for mycotoxin analysis, but it is a major goal to simplify the analysis. The enzyme-linked immunosorbent assay using horseradish peroxidase as enzymatic label, together with 3,3',5,5' tetramethylbenzidine (TMB)/H2O2 as substrates allows sensitive mycotoxin detection with optical detection methods. For the miniaturization of the detection step, an electrochemical system for mycotoxin analysis was developed. To this end, the electrochemical detection of TMB was studied by cyclic voltammetry on different screen-printed electrodes (carbon and gold) and at different pH values (pH 1 and pH 4). A stable electrode reaction, which is the basis for the further construction of the electrochemical detection system, could be achieved at pH 1 on gold electrodes. An amperometric detection method for oxidized TMB, using a custom-made flow cell for screen-printed electrodes, was established and applied for a competitive magnetic bead-based immunoassay for the mycotoxin ochratoxin A. A limit of detection of 150 pM (60 ng/L) could be obtained and the results were verified with optical detection. The applicability of the magnetic bead-based immunoassay was tested in spiked beer using a handheld potentiostat connected via Bluetooth to a smartphone for amperometric detection allowing to quantify ochratoxin A down to 1.2 nM (0.5 µg/L). Based on the developed electrochemical detection system for TMB, the applicability of the approach was demonstrated with a magnetic bead-based immunoassay for the ergot alkaloid, ergometrine. Under optimized assay conditions a limit of detection of 3 nM (1 µg/L) was achieved and in spiked rye flour samples ergometrine levels in a range from 25 to 250 µg/kg could be quantified. All results were verified with optical detection. The developed electrochemical detection method for TMB gives great promise for the detection of TMB in many other HRP-based assays. A new sensing approach, based on an enzymatic electrochemical detection system for the mycotoxin fumonisin B1 was established using an Aspergillus niger fumonisin amine oxidase (AnFAO). AnFAO was produced recombinantly in E. coli as maltose-binding protein fusion protein and catalyzes the oxidative deamination of fumonisins, producing hydrogen peroxide. It was found that AnFAO has a high storage and temperature stability. The enzyme was coupled covalently to magnetic particles, and the enzymatically produced H2O2 in the reaction with fumonisin B1 was detected amperometrically in a flow injection system using Prussian blue/carbon electrodes and the custom-made wall-jet flow cell. Fumonisin B1 could be quantified down to 1.5 µM (≈ 1 mg/L). The developed system represents a new approach to detect mycotoxins using enzymes and electrochemical methods.
In the event of moisture deterioration, rapid detection and localization is particularly important to prevent further deterioration and costs. For building floors, the layered structure poses a challenging obstacle for most moisture measurement methods. But especially here, layer-specific information on the depth of the water is crucial for efficient and effective repairs. Ground Penetrating Radar (GPR) shows the potential to generate such depth information. Therefore, the present work investigates the suitability of GPR in combination with machine learning methods for the automated classification of the typical deterioration cases (i) dry, (ii) wet insulation, and (iii) wet screed.
First, a literature review was conducted to identify the most common methods for detecting moisture in building materials using GPR. Here, it especially became clear that all publications only investigated individual time-, amplitude- or frequency features separately, without combining them. This was seen as a potential aspect for innovation, as the multivariate application of several signal features can help to overcome individual weaknesses and limitations.
Preliminary investigations carried out on drying screed samples confirmed the profitable use of multivariate evaluations. In addition to the general suitability and dependencies of various features, first limitations due to possible interference between the direct wave and the reflection wave could be identified. This is particularly evident with thin or dry materials, for which the two-way travel times of the reflected radar signals become shorter.
An extensive laboratory experiment was carried out, for which a modular test specimen was designed to enable the variation of the material type and thickness of screed and insulation, as well as the simulation of moisture deteriorations. The data collected revealed clear differences between dry and deteriored structures within measured B-scans. These deviations were to be detected with the newly introduced B-scan features, which evaluate the statistical deviation of A-scan features within a survey line. In this way, deteriorations to unknown floor structures are recognized, regardless of the material parameters present. In a subsequent training and cross-validation process of different classifiers, accuracies of over 88 \% of the 504 recorded measurements (252 different experimental setups) were achieved. For that, the combination of amplitude and frequency features, which covered all relevant reflections of the radar signals, was particularly beneficial. Furthermore, the data set showed only small differences between dry floors and deteriored screeds for the B-scan features, which could be attributed to a homogeneous distribution of the added water in the screeds. The successfully separation of these similar feature distributions raised the suspicion of overfitting, which was examined in more detail by means of a validation with on-site data.
For this purpose, investigations were carried out at five different locations in Germany, using the identical measurement method like in the laboratory. By extracting drilling cores, it was possible to determine the deterioration case for each measurement point and thus generate a corresponding reference. However, numerous data had to be sorted out before classification, since disturbances due to underfloor heating, screed reinforcements, steel beams or missing insulation prevented comparability with the laboratory experiments. Validation of the remaining data (72 B-scans) achieved only low accuracy with 53 \% correctly classified deterioration cases. Here, the previously suspected overfitting of the small decision boundary between dry setups and deteriored screeds within the laboratory proved to be a problem. The generally larger deviations within (also dry) on-site B-scans were thus frequently misclassified as screed deterioration. In addition, there were sometimes strongly varying layer thicknesses or changing cases of deterioration within a survey line, which caused additional errors due to the local limitation of the drilling core reference. Nevertheless, individual on-site examples also showed the promising potential of the applied signal features and the GPR method in general, which partly allowed a profound interpretation of the measurements. However, this interpretation still requires the experience of trained personnel and could not be automated using machine learning with the available database. Nevertheless, such experience and knowledge can be enriched by the findings of this work, which provide the basis for further research.
Future work should aim at building an open GPR data base of on-site moisture measurements on floors to provide a meaningful basis for applying machine learning. Here, referencing is a crucial point, whose limitations with respect to the moisture present and its distribution can easily reduce the potential of such efforts. The combination of several reference methods might help to overcome such limitations. Similarly, a focus on monitoring approaches can also help to reduce numerous unknown variables in moisture measurements and increase confidence in the detection of different deterioration cases.
Laser-based active thermography is a contactless non-destructive testing method to detect material defects by heating the object and measuring its temperature increase with an infrared camera. Systematic deviations from predicted behavior provide insight into the inner structure of the object. However, its resolution in resolving internal structures is limited due to the diffusive nature of heat diffusion. Thermographic super resolution (SR) methods aim to overcome this limitation by combining multiple thermographic measurements and mathematical optimization algorithms to improve the defect reconstruction.
Thermographic SR reconstruction methods involve measuring the temperature change in an object under test (OuT) heated with multiple different spatially structured illuminations. Subsequently, these measurements are inputted into a severely ill-posed and heavily regularized inverse problem, producing a sparse map of the OuT’s internal defect structure. Solving this inverse problem relies on limited priors, such as defect-sparsity, and iterative numerical minimization techniques. Previously mostly experimentally limited to one-dimensional regions of interest (ROIs), this thesis aims to extend the method to the reconstruction of two-dimensionalROIs with arbitrary defect distributions while maintaining reasonable experimental complexity. Ultimately, the goal of this thesis is to make the method suitable for a technology transfer to industrial applications by advancing its technology readiness level (TRL).
In order to achieve the aforementioned goal, this thesis discusses the numerical expansion of a thermographic SR reconstruction method and introduces two novel algorithms to invert the underlying inverse problem. Furthermore, a forward solution to the inverse problem in terms of the applied SR reconstruction model is set up. In conjunction with an additionally proposed algorithm for the automated determination of a set of (optimal) regularization parameters, both create the possibility to conduct analytical simulations to characterize the influence of the experimental parameters on the achievable reconstruction quality. On the experimental side, the method is upgraded to deal with two-dimensional ROIs, and multiple measurement campaigns are performed to validate the proposed inversion algorithms, forward solution and two exemplary analytical studies. For the experimental implementation of the method, the use of a laser-coupled DLP-projector is introduced, which allows projecting binary pixel
patterns that cover the whole ROI, reducing the number of necessary measurements per ROI significantly (up to 20x).
Finally, the achieved reconstruction of the internal defect structure of a purpose-made OuT is qualitatively and qualitatively benchmarked against well-established thermographic testing methods based on homogeneous illumination of the ROI. Here, the background-noise-free two-dimensional photothermal SR reconstruction results show to outclass all defect reconstructions by the considered reference methods.
This thesis investigates ultrasonic guided waves (GW) in multi-layered plates with the focus on higher order modes. The aim is to develop techniques for hybrid structures such as of adhesive bonds and composite pressure vessels (COPV) which are widely used in automotive and aerospace industries and are still challenging to inspect non-destructively. To be able to analyse GW, numerical methods and precise material properties are required. For this purpose, an efficient semi-analytical approach, the Scaled Boundary Finite Element Method, is used. The material properties are inferred by a GW-based optimisation procedure and a sensitivity study is performed to demonstrate the influence of properties on GW. Then, an interesting feature, called mode repulsion, is investigated with respect to weak and strong adhesive bonds. The results show that the coupling between two layers influences the distance between coupled modes in a mode repulsion region, thus allowing for the characterisation of adhesive bonds. At next, wave-damage interaction is studied in the hybrid structure as of the COPV. Results show that the wave energy can be concentrated in a certain layer enabling damage localisation within different layers. Further investigations are carried out on the hybrid plate with an impact-induced damage. Two well-known wavenumber mapping techniques, which allow to quantify the damage in three dimensions, are implemented and their comparison is done for the first time.
Additive manufacturing technologies provide unique possibilities in the production of topologically optimized, near-net shape components. The main limiting factors affecting the structural integrity of Laser Powder Bed Fusion (LPBF) parts are manufacturing defects and residual stress (RS) because both of them are virtually inevitable. Taking into account the complex thermal history of LPBF materials, a prediction of the material behavior is not possible without experimental data on the microstructure, defect distribution, and RS fields. Therefore, this thesis aims to understand the factors that influence the LPBF Ti-6Al-4V material performance the most, covering both the production and the post-processing steps of manufacturing.
Indeed, a parametric study on the influence of manufacturing process and post-processing on RS, defects and microstructure was performed. It was found that the volumetric energy Density (EV), commonly used for the LPBF process optimization, does neither consider the pore shapes and distribution, nor the influence of individual parameters on the volume fraction of pores.
Therefore, it was recommended not to use EV without great care. It was shown that the Position on the base plate has a great impact on the amount of RS in the part.
The micromechanical behavior of LPBF Ti-6Al-4V was also studied using in-situ Synchrotron X-ray diffraction during tensile and compression tests. Diffraction elastic constants (DEC), connecting macroscopic stress and (micro) strain, of the LPBF Ti-6Al-4V showed a difference
from the DEC of conventionally manufactured alloy. This fact was attributed to the peculiar microstructure and crystallographic texture. It was therefore recommended to determine experimentally DECs whenever possible.
Low Cycle Fatigue (LCF) tests at a chosen operating temperature were performed to evaluate the effect of post-treatment on the mechanical performance. Through the information on the microstructure, the mesostructure, and the RS, the LCF behavior was (indirectly) correlated to the process parameters. It was found that the fatigue performance of LPBF samples subjected to hot isostatic pressing is similar to that of hot-formed Ti-6Al-4V. The tensile RS found at the
surface of LPBF as-built samples decreased the fatigue life compared to the heat-treated samples. The modification of the microstructure (by heat treatment) did not affect the Fatigue performance in the elastic regime. This shows that in the absence of tensile RS, the manufacturing defects solely control the failure of LPBF components and densification has the strongest effect on the improvement of the mechanical performance.
In this work, two X-ray refraction based imaging methods, namely, synchrotron X-ray refraction radiography (SXRR) and synchrotron X-ray refraction computed tomography (SXRCT), are applied to analyze quantitatively cracks and porosity in metallic materials.
SXRR and SXRCT make use of the refraction of X-rays at inner surfaces of the material, e.g., the surfaces of cracks and pores, for image contrast. Both methods are, therefore, sensitive to smaller defects than their absorption based counterparts X-ray radiography and computed tomography. They can detect defects of nanometric size.
So far the methods have been applied to the analysis of ceramic materials and fiber reinforced plastics. The analysis of metallic materials requires higher photon energies to achieve sufficient X-ray transmission due to their higher density. This causes smaller refraction angles and, thus, lower image contrast because the refraction index depends on the photon energy. Here, for the first time, a conclusive study is presented exploring the possibility to apply SXRR and SXRCT to metallic materials. It is shown that both methods can be optimized to overcome the reduced contrast due to smaller refraction angles. Hence, the only remaining limitation is the achievable X-ray Transmission which is common to all X-ray imaging methods. Further, a model for the quantitative analysis of the inner surfaces is presented and verified.
For this purpose four case studies are conducted each posing a specific challenge to the imaging task. Case study A investigates cracks in a coupon taken from an aluminum weld seam. This case study primarily serves to verify the model for quantitative analysis and prove the sensitivity to sub-resolution features. In case study B, the
damage evolution in an aluminum-based particle reinforced metal-matrix composite is analyzed. Here, the accuracy and repeatability of subsequent SXRR measurements is investigated showing that measurement errors of less than 3% can be achieved. Further, case study B marks the fist application of SXRR in combination with in-situ tensile loading. Case study C is out of the highly topical field of additive manufacturing. Here, porosity in additively manufactured Ti-Al6-V4 is analyzed with a special interest in the pore morphology. A classification scheme based on SXRR measurements is devised which allows to distinguish binding defects from keyhole pores even if the defects cannot be spatially resolved. In case study D, SXRCT is applied to the analysis of hydrogen assisted cracking in steel. Due to the high X-ray attenuation of steel a comparatively high photonenergy of 50 keV is required here. This causes increased noise and lower contrast in the data compared to the other case studies. However, despite the lower data quality a quantitative analysis of the occurance of cracks in dependence of hydrogen content and applied mechanical load is possible.