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This technical note highlights the fact that CF-LIBS algorithms work in mole fractions, while results of spectrochemical analysis are usually reported in mass fractions or mass percent. Ignoring this difference and not converting mole fractions to mass fractions can lead to errors in reported concentrations determined by the CF-LIBS method and inadequate comparison of these concentrations with certified concentrations. Here, the key points of the CF-LIBS algorithm are reproduced and the formulae for converting a mole fraction to a mass fraction and vice versa are given. Several numerical examples are also given, which show that the greater the difference between the molar mass of an individual element in a sample and the average molar mass, the greater the discrepancy between the mole and mass fractions.
Additive manufacturing of concrete structures is a novel and emerging technology. Freecontouring in civil engineering, which allows for entirely new designs, is a significant advantage. Inthe future, lower construction costs are expected with increased construction speeds and decreasingrequired materials and workers. However, architects and civil engineers rely on a certain quality ofexecution to fulfil construction standards. Although several techniques and approaches demonstratethe advantages, quality control during printing is highly challenging and rarely applied. Due to thecontinuous mixing process commonly used in 3D concrete printing, it is impossible to exclude varia-tions in the dry mixture or water content, and a test sample cannot be taken as a representative samplefor the whole structure. Although mortar properties vary only locally, a defect in one layer duringprinting could affect the entire integrity of the whole structure . Therefore, real-time process monitor-ing is required to record and document the printing process.At the Bundesanstalt für Materialforschung und -prüfung (BAM) a new test rig for the additive man-ufacturing of concrete is built. The primary purpose is measuring and monitoring the properties of amortar during the printing process.The following study investigates an approach for calculating yield stress and plastic viscosity based onexperimentally recorded pressure data. The calculations assume that fresh mortar behaves as a Bing-ham fluid and that the Buckingham-Reiner-equation is applicable. A test setup consisting of rigid pipeswith integrated pressure sensors at different positions is utilized.Monitoring the printing process with different sensors is crucial for the quality control of an ongoingprocess.
Determination of short carbon fiber orientation in zirconium diboride ceramic matrix composites
(2024)
In fiber-reinforced components, the fiber alignment and orientation have paramount influence on the thermomechanical properties of the resulting composite, for both short and continuous fiber. Here we present the case of an ultra-refractory matrix intended for extreme environment applications, ZrB2, reinforced with 20 vol% and 50 vol% short carbon fibers. In both cases, fibers tend to align perpendicular to the uniaxial pressure applied during shaping and sintering of a pellet, although the fiber tilt across the pellet thickness is difficult to determine. Moreover, for high volume fractions of reinforcement, the spatial distribution of the fibers is heterogeneous and tends to have domains of preferential orientations. We compare the information on the fiber distribution as collected by scanning electron microscopy images, X-ray computed tomography and synchrotron X-ray refraction radiography (SXRR). The three techniques prove to be complementary. Importantly, we demonstrate that SXRR yields the most statistically significant information due to the largest field of view, yet with a sensitivity down to the nanometer, and that can be successfully applied also to heavy matrix materials, such as zirconium boride.
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.
Powder Bed Fusion – Laser Beam (PBF-LB) of high γ’ strengthened Ni-base superalloys, such as CM247LC, is of great interest for high temperature applications in gas turbines. However, PBF-LB of CM247LC is challenging due to the high cracking susceptibility during PBF-LB processing (solidification cracking) and heat treatment (strain age cracking, mostly caused by residual stresses). This study focuses on understanding the impact of process parameters on microstructure, residual stresses and solidification cracking. Laser power (P), speed (v) and hatch spacing (h) were varied while the layer thickness (t) was fixed. The melt pool size and shape were found to be key factors in minimizing solidification cracking. Narrower and shallower melt pools, achieved using a low line energy density (LED = P/v ≤ 0.1 J/mm), gave low crack densities (0.7 mm/mm2). A tight hatch spacing (h = 0.03 mm) resulted in reduced lack of fusion porosity. Electron backscatter diffraction investigations revealed that parameters giving finer microstructure with 〈100〉crystallographic texture had low crack densities provided they were processed with a low LED. Atom probe tomography elucidated early stages of spinodal decomposition in the as-built condition, where Cr and Al cluster separately. The extent of spinodal decomposition was found to be affected by the LED and the hatch spacing. Samples with low LED and small hatch spacing showed higher degrees of spinodal decomposition. X-ray diffraction residual stress investigations revealed that the residual stress is proportional to the volumetric energy density (VED = P/(v. h. t)). Although low residual stresses can be achieved by using low VED, there is a high risk of lack of fusion. Hence, other parameters such as modified scan strategy, build plate pre-heating and pulsed laser mode, must be further explored to minimize the residual stresses to reduce the strain age cracking susceptibility.
A systematic, nature-inspired chemical engineering approach is employed to solve the issue of flooding in electrochemical devices. The mechanism of passive water transport utilized by lizards living in arid environments is leveraged to design flow-fields with a microchannel structure on their surface, through which capillary pressure rapidly removes the water generated in the electrochemical device. This water management strategy is implemented in proton exchange membrane fuel cells (PEMFCs) with a lunginspired flow-field, which ensures uniform distribution of reactants across the catalyst layer. Jointly, this nature-inspired approach results in flood-free, stable operation at 100% RH and a B60% increase in current (B1.9 A cm-2) and peak power density (B650 mW cm−2) compared to current PEMFCs with a flood-prone, serpentine flow-field (B0.8 A cm-2 and 280 mW cm-2, respectively). This significant advance allows for PEMFC operation at fully humidified conditions.
Distributed fiber optic sensors for structural health monitoring of composite pressure vessels
(2024)
In diesem Beitrag geben wir einen umfassenden Überblick über unsere Forschung auf dem Gebiet der verteilten faseroptischen Sensorik für die strukturelle Zustandsüberwachung von Wasserstoffdruckbehältern aus Verbundwerkstoffen. Insbesondere zeigen wir, wie die Integration von faseroptischen Sensoren in Druckbehälter aus Verbundwerkstoffen die Sicherheit erhöht und gleichzeitig die Wartungskosten senkt. Die geringe Größe von Lichtwellenleitern ermöglicht ihre Integration in Verbundwerkstoffstrukturen während des Herstellungsprozesses, wodurch eine kontinuierliche Überwachung sowie eine präzise Erkennung und Lokalisierung von Strukturschäden während des Betriebs der Druckbehälter ermöglicht wird. Wir erörtern auch das Potenzial modernster Signalverarbeitungsmethoden und des maschinellen Lernens für die Weiterentwicklung der vorausschauenden Instandhaltung. Die von uns vorgestellten Anwendungen von faseroptischen Sensoren zeigen, dass sie einen wichtigen Beitrag zur Energiewende hin zu erneuerbaren Energien leisten können.
A novel distributed acoustic sensing technique is proposed that exploits both phase and amplitude of the Rayleigh backscattered light to quantify the environmental variation. The system employs a wavelength-scanning laser and an imbalanced Mach-Zehnder interferometer to acquire the reflection spectra and the phase of the detected light, respectively. Fading-free and low-frequency measurements are realized via the crosscorrelation of the reflection spectra. The discrete crosscorrelation is used to circumvent the nonlinear frequency sweeping of the laser. Based on the phase of the backscattered light, it is possible to quantify fast environmental variations. The whole system requires no hardware modification of the existing system and its functionality is experimentally validated. The proposed system has the potential to monitor ground motion/movement at very low frequency band like subsidence around mining areas and at high frequency band like earthquakes and vibrations induced by avalanches.
With the reduction of large oil spills because of stricter regulations and safety measures, the question of how to manage smaller oil spills arises. Few on-site analytical tools are available for first responders or other law enforcement personnel to rapidly test for crude oil in the early management of localized polluted areas. The approach reported here relies on well-described computer-assisted multivariate data analysis of the intrinsic fluorescence fingerprints of crude oils to build a multivariate model for the rapid classification of crude oils and the prediction of their properties. Thanks to a dedicated robust portable reader, the method allowed classification and accurate prediction of various properties of crude oil samples like density (according to API, the American Petroleum Institute and viscosity as well as composition parameters such as volume fractions of paraffins or aromatics. In this way, autonomous operation in on-site or in-the-field applications becomes possible based on the direct (undiluted and untreated) measurement of samples and a rapid, tablet-operated readout system to yield a robust and simple analytical test with superior performance. Testing in real-life scenarios allowed the successful classification and prediction of a number of oil spill samples as well as weathered samples that closely resemble samples collected by first responders.
Locating and sizing delaminations is a common inspection task in the maintenance and quality control of construction and rehabilitation. Their detection is an important area of application of nondestructive testing in civil engineering (NDT-CE). To improve this application, NDT test systems and test solutions must be compared, for which specimens containing well-defined delaminations are needed to serve as a reference. Currently, there are no widely accepted procedures available for creating such flaws locally and reproducibly. This study presents procedures for creating artificial delaminations repeatably and as close as possible to natural delaminations. To produce the discontinuities only substances were used which can occur in concrete components and do not affect the application of NDT-CE methods. Ultrasonic pulse-echo (UPE) was used to test the flaws in the specimens. The delaminations were created by applying expansive mortar in prepared through holes. Three specimens with two delaminations each were built and tested using UPE.
An observation of the fracture process in front of the crack tip inside a dentin sample by means of ex-situ X-ray computed tomography after uniaxial compression at different deformation values was carried out in this work. This ex-situ approach allowed the microstructure and fracturing process of human dentin to be observed during loading. No cracks are observed up to the middle part of the irreversible deformation in the samples at least visible at 0.4μm resolution. First cracks appeared before the mechanical stress reached the compression strength. The growth of the cracks is realized by connecting the main cracks with satellite cracks that lie ahead of the main crack tip and parallel its trajectory. When under the stress load the deformation in the sample exceeds the deformation at the compression strength of dentin, an appearance of micro-cracks in front of the main cracks is observed. The micro-cracks are inclined (~60°) to the trajectory of the main cracks. The further growth of the main cracks is not realized due to the junction with the micro-cracks; we assume that the micro-cracks dissipate the energy of the main crack and suppressed its growth. These micro-cracks serve as additional stress accommodations, therefore the samples do not break apart after the compression test, as it is usually observed under bending and tension tests.
Efficient density evolution during sintering of the as-printed component is vital to reach full densification and required properties of binder jet (BJT) components. However, due to the high porosity and brittle nature of the green compact, analysis of the microstructure development during sintering is very difficult, resulting in lack of understanding of the densification process. Density development from green state (57 ± 1.6 %) up to full density (99 ± 0.3 %) was characterized by high-resolution synchrotron X-Ray computed tomography (SXCT) on BJT 316L samples from ex-situ interrupted sintering tests. Periodicity of density fluctuations along the building direction was revealed for the first time and was related to the layer thickness of ~ 42 μm during printing that decreased down to ~ 33 μm during sintering. Sintering simulations, utilizing a continuum sintering model developed for BJT, allowed to replicate the density evolution during sintering with a mean error of 2 % and its fluctuation evolution from green (1.66 %) to sintered (0.56 %) state. Additionally, simulation of extreme particle size segregation (1 μm to 130 μm) suggested that non-optimized printing could lead to undesirable density fluctuation amplitude rapid increase (~10 %) during sintering. This might trigger the nucleation of defects (e.g., layer delamination, cracking, or excessive residual porosity) during the sintering process.
Gasquellenlokalisierungen (Gas Source Localization, GSL) tragen dazu bei, die Folgen von Industrieunfällen und Naturkatastrophen zu mildern. Während die GSL, wenn von Menschen durchgeführt, gefährlich und zeitaufwändig ist, können Schwärme von wendigen und kostengünstigen Nanodrohnen die Effizienz und Sicherheit der Suche erhöhen. Da die geringe Nutzlast von Nanodrohnen die Sensor- und Rechenressourcen einschränkt, werden Strategien zur Koordination des Roboterschwarms verwendet, die von biologischen Schwärmen, wie Kolonien sozialer Insekten, inspiriert sind. Die meisten Schwarm-GSL-Strategien verwenden das Maximum der Gaskonzentrationsverteilung zur Schätzung der Gasquellenposition. Experimente legen jedoch nahe, dass die Intermittenz der Gasverteilung vielversprechender ist. In diesem Beitrag wird eine neuartige GSL-Strategie für Schwärme vorgestellt, die auf Pheromonkommunikation und Intermittenz der Gasverteilung basiert. Die Agenten, d.h. die Nanodrohnen, emittieren Pheromonmarker in einer virtuellen Umgebung, wenn sie eine neue Gaswolke feststellen. Die Agenten werden durch virtuelle Kräfte gesteuert und nutzen abwechselnd das Wissen des Schwarms, indem sie dem Pheromongradienten folgen, oder erkunden den Suchraum, indem sie einen Zufallspunkt ansteuern. Zur Kollisionsvermeidung werden die Agenten durchgehend von anderen Agenten und Wänden abgestoßen. Die Strategie wurde auf drei Nanodrohnen implementiert und durch ein Experiment in einem Innenraum mit einer statischen Gasquelle validiert. Die Ergebnisse zeigen eine Verbesserung gegenüber maximabasierten Verfahren und geringe Lokalisierungsfehler in Windrichtung.
AbstractAir‐coupled ultrasonic testing (ACU) is a pioneering technique in non‐destructive testing (NDT). While contact testing and fluid immersion testing are standard methods in many applications, the adoption of ACU is progressing slowly, especially in the low ultrasonic frequency range. A main reason for this development is the difficulty of generating high amplitude ultrasonic bursts with equipment that is robust enough to be applied outside a laboratory environment. This paper presents the fluidic ultrasonic transducer as a solution to this challenge. This novel aeroacoustic source uses the flow instability of a sonic jet in a bistable fluidic switch to generate ultrasonic bursts up to 60 kHz with a mean peak pressure of 320 Pa. The robust design allows operation in adverse environments, independent of the operating fluid. Non‐contact through‐transmission experiments are conducted on four materials and compared with the results of conventional transducers. For the first time, it is shown that the novel fluidic ultrasonic transducer provides a suitable acoustic signal for NDT tasks and has potential of furthering the implementation of ACU in industrial applications.This article is protected by copyright. All rights reserved
In ultrasonic testing, material and structural properties of a specimen can be derived from the time-of-flight (ToF). Using signal features, such as the first peak or envelope maximum, to calculate the ToF is error-prone in multipath arrangements or dispersive and attenuating materials, which is not the case for the signal onset. Borrowing from seismology, researchers used the Akaike information criterion (AIC) picker to automatically determine onset times. The most commonly used formulation, Maeda's AIC picker, is reassessed and found to be based on inappropriate assumptions for signals often used in ultrasonic testing and dependent on arbitrary parameters. Consequently, an onset picker for ultrasonic through-transmission measurements is proposed, based on a spectral entropy criterion (SEC) to model the signal using the AIC framework. This SEC picker takes into account the spectral properties of the ultrasonic signal and is virtually free of arbitrary parameters. Synthetic and experimental data are used to compare the performance of SEC and AIC pickers. It is shown that the accuracy of onset picking is improved for densely sampled data.
AbstractHigh-strength aluminum alloys used in aerospace and automotive applications obtain their strength through precipitation hardening. Achieving the desired mechanical properties requires precise control over the nanometer-sized precipitates. However, the microstructure of these alloys changes over time due to aging, leading to a deterioration in strength. Typically, the size, number, and distribution of precipitates for a quantitative assessment of microstructural changes are determined by manual analysis, which is subjective and time-consuming. In our work, we introduce a progressive and automatable approach that enables a more efficient, objective, and reproducible analysis of precipitates. The method involves several sequential steps using an image repository containing dark-field transmission electron microscopy (DF-TEM) images depicting various aging states of an aluminum alloy. During the process, precipitation contours are generated and quantitatively evaluated, and the results are comprehensibly transferred into semantic data structures. The use and deployment of Jupyter Notebooks, along with the beneficial implementation of Semantic Web technologies, significantly enhances the reproducibility and comparability of the findings. This work serves as an exemplar of FAIR image and research data management.
Simulation-Assisted Augmentation of Missing Wedge and Region-of-Interest Computed Tomography Data
(2024)
This study reports a strategy to use sophisticated, realistic X-ray Computed Tomography (CT) simulations to reduce Missing Wedge (MW) and Region-of-Interest (RoI) artifacts in FBP (Filtered Back-Projection) reconstructions. A 3D model of the object is used to simulate the projections that include the missing information inside the MW and outside the RoI. Such information augments the experimental projections, thereby drastically improving the reconstruction results. An X-ray CT dataset of a selected object is modified to mimic various degrees of RoI and MW problems. The results are evaluated in comparison to a standard FBP reconstruction of the complete dataset. In all cases, the reconstruction quality is significantly improved. Small inclusions present in the scanned object are better localized and quantified. The proposed method has the potential to improve the results of any CT reconstruction algorithm.
In this work, the thermal properties of ternary Li₃ₓCo₇₋₄ₓSb₂₊ₓO₁₂ solid solutions are studied for different concentrations in the range 0 ≤ x ≤ 0.7. Samples are elaborated at four different sintering temperatures: 1100, 1150, 1200 and 1250 °C. The effect of increasing the content of Li⁺ and Sb⁵⁺, accompanied by the reduction of Co²⁺, on the thermal properties is studied. It is shown that a thermal diffusivity gap, which is more pronounced for low values of x, can be triggered at a certain threshold sintering temperature (around 1150 °C in this study). This effect is explained by the increase of contact area between adjacent grains. Nevertheless, this effect is found to be less pronounced in the thermal conductivity. Moreover, a new framework for heat diffusion in solids is presented that establishes that both the heat flux and the thermal energy (or heat) satisfy a diffusion equation and therefore highlights the importance of thermal diffusivity in transient heat conduction phenomena.
AbstractLithium‐ion cells connected in series are prone to an electrical safety risk called overdischarge. This paper presents a comprehensive investigation of the overdischarge phenomenon in lithium‐ion cells using operando nondestructive imaging. The study focuses on understanding the behavior of copper dissolution and deposition during overdischarge, which can lead to irreversible capacity loss and internal short‐circuits. By utilizing synchrotron X‐ray computed tomography (SXCT), the concentration of dissolved and deposited copper per surface area is quantified as a function of depth of discharge, confirming previous findings. The results also highlight for the first time a nonuniform distribution pattern for copper deposition on the cathode. This research provides insights for safer battery cell design.
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.
The Large Aperture Ultrasound System (LAUS) developed at BAM is known for its ability to penetrate thick objects, especially concrete structures commonly used in nuclear waste storage and other applications in civil engineering. Although the current system effectively penetrates up to ~9 m, further optimization is imperative to enhance the safety and integrity of disposal structures for radioactive or toxic waste. This study focuses on enhancing the system’s efficiency by optimizing the transducer spacing, ensuring that resolution is not compromised. An array of twelve horizontal shear wave transducers was used to find a balance between penetration depth and resolution. Systematic adjustments of the spacing between transmitter and receiver units were undertaken based on target depth ranges of known reflectors at depth ranges from 5 m to 10 m. The trade-offs between resolution and artifact generation were meticulously assessed. This comprehensive study employs a dual approach using both simulations and measurements to investigate the performance of transducer units spaced at 10 cm, 20 cm, 30 cm, and 40 cm. We found that for depths up to 5 m, a spacing of 10 cm for LAUS transducer units provided the best resolution as confirmed by both simulations and measurements. This optimal distance is particularly effective in achieving clear reflections and a satisfactory signal-to-noise ratio (SNR) in imaging scenarios with materials such as thick concrete structures. However, when targeting depths greater than 10 m, we recommend increasing the distance between the transducers to 20 cm. This increased spacing improves the SNR in comparison to other spacings, as seen in the simulation of a 10 m deep backwall. Our results emphasize the critical role of transducer spacing in achieving the desired SNR and resolution, especially in the context of depth imaging requirements for LAUS applications. In addition to the transducer spacing, different distances between individual sets of measurement positions were tested. Overall, keeping the minimal possible distance between measurement position offsets provides the best imaging results at greater depths. The proposed optimizations for the LAUS in this study are primarily relevant to applications on massive nuclear structures for nuclear waste management. This research highlights the need for better LAUS efficiency in applications such as sealing structures, laying the foundation for future technological advances in this field.
Offshore wind turbines continuously increase in size and weight and demand adequate offshore foundations concepts like monopiles, tripods, or jackets. These components are typically constructed using submerged arc welding (SAW) with high-strength thick steel plates like the S420ML. During welding, the occurrence of delayed hydrogen-assisted cracking (HAC) must be anticipated. HAC is a critical combination of the local hydrogen concentration within a susceptible microstructure under certain mechanical load, i.e., the occurring (welding) residual stresses. The welding sequence of the thick-walled plates complicates the residual stress distribution due to the necessary repeated thermal cycling, i.e., welding seam/layer deposition to fill the joint. For that purpose, SAW with two-wire-technique was used to weld a specially designed and prototype-like mock-up of a real component with a thickness of 50 mm, filled with over 20 passes and a seam length of 1000 mm. Additional welded stiffeners simulated the effect of a high restraint, to achieve critical HAC conditions. The necessity of a minimum waiting time (MWT) before the NDT can be conducted (to exclude HAC) was critically verified by the application of ultrasonic testing of the welded joint at different time-steps of the NDT of up to 48 h after the completion welding. The residual stresses were determined by a robot XRD goniometer. Tensile residual stresses up to the yield limit are found both in the weld metal and in the heat-affected zone. Numerical modeling allowed the qualitative estimation of the hydrogen diffusion in the weld. No noticeable HAC occurrence was identified and confirms the high cracking resistance of the investigated material. Finally, the applicability of the MWT concept should be critically discussed.
A novel DAS setup based on geometric phases in coherent heterodyne detection is applied for the first time to the characterisation of the Earth’s subsurface. In addition, an optimisation of the proposed setup in terms of its spatial resolution is also presented for the first time. The surface waves are generated by strong blasts of 25 kg of explosives at a dedicated test site. A 10 km dark fiber link in the vicinity of the test site connected to the test setup records the resulting strain signals. The spike-free and low-noise strain data thus obtained minimize post-processing requirements, making the setup a candidate for real-time seismic monitoring. An analysis of the dispersion characteristics of the generated surface waves is performed using a recently reported optimised seismic interferometric technique. Based on the dispersion characteristics, the shear wave velocities of the surface waves as a function of the depth profile of the Earth’s crust are determined using an optimised evolutionary algorithm.
The ultrasonic echo technique is widely used in non-destructive testing (NDT) of concrete objects for thickness measurements, geometry determinations and localization of built-in components. To improve ultrasonic imaging of complex concrete structures, we transferred a seismic imaging technique, the Reverse Time Migration (RTM), to NDT in civil engineering. RTM, in contrast to the conventionally used synthetic aperture focusing technique (SAFT) algorithms, considers all wavefield types and thus, can handle complex wave propagations in any direction with no limit on velocity variations and reflector dip. In this paper, we focused on the development, application and evaluation of a two-dimensional elastic RTM algorithm considering horizontally polarized shear (SH) waves only. We applied the elastic SH RTM routine to synthetic ultrasonic echo SH-wave data generated with a concrete model incorporating several steps and circular cavities. As these features can often be found in real-world NDT use cases, their imaging is extremely important. By using elastic SH RTM, we were able to clearly reproduce almost all reflectors inside the concrete model including the vertical step edges and the cross sections of the cavities.We were also capable to show that more features could be mapped compared to SAFT, and that imaging of complex reflectors could be sharpened compared to elastic P-SV (compressional-vertically polarized shear) RTM. Our promising results illustrate that elastic SH RTM has the potential to significantly enhance the reconstruction of challenging concrete structures, representing an important step forward for precise, high-quality ultrasonic NDT in civil engineering.
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 application of composite overwrapped pressure vessels (COPV) to store hydrogen and other compressed gases, especially when operating at high pressures, imposed the need for an innovative and reliable approach to ensure the safe operation of the system. Continuous structural health monitoring (SHM) based on ultrasonic guided waves (GWs) is a promising approach due to the ability of the wave to propagate for long distances and go around complex structures, moreover the high sensitivity to various failure modes such as delamination, matrix cracking and debonding. In this study, we scrutinize the behavior of (GWs) within the COPV using a network of PZT elements that are used for excitation and sensing. A laser doppler vibrometer (LDV) was also used to scan the surface of the vessel in various directions. L(0,1) and L(0,2) were observed in the captured signal. The L(0, 2) appeared to be a dominant mode in the COPV and was capable of propagating along the entire length and maintaining a good signal-to-noise ratio. The L(0,2) mode maintained the same phase velocity when it is captured at various excitation angles (0, 45, and 90 degrees). The reduced effect of the orthotropy of the materials on the propagating waves is an important result as it will reduce the complexity in data processing when performing damage identification.
It is shown that preconditioning of experimental X‐ray computed tomography (XCT) data is critical to achieve high‐precision segmentation scores. The challenging experimental XCT datasets and deep convolutional neural networks (DCNNs) are used that are trained with low‐resemblance synthetic XCT data. The material used is a 6‐phase Al–Si metal matrix composite‐reinforced with ceramic fibers and particles. To achieve generalization, in our past studies, specific data augmentation techniques were proposed for the synthetic XCT training data. In addition, two toolsets are devised: (1) special 3D DCNN architecture (3D Triple_UNet), slicing the experimental XCT data from multiple views (MultiView Forwarding), the i.S.Sy.Da.T.A. iterative segmentation algorithm, and (2) nonlocal means (NLM) conditioning (filtering) for the experimental XCT data. This results in good segmentation Dice scores across all phases compared to more standard approaches (i.e., standard UNet architecture, single view slicing, standard single training, and NLM conditioning). Herein, the NLM filter is replaced with the deep conditioning framework BAM SynthCOND introduced in a previous publication, which can be trained with synthetic XCT data. This leads to a significant segmentation precision increase for all phases. The proposed methods are potentially applicable to other materials and imaging techniques.
The applications of composite overwrapped pressure vessels (COPVs) in extreme conditions, such as storing hydrogen gases at very high pressure, impose new requirements related to the system's integrity and safety. The development of a structural health monitoring (SHM) system that allows for continuous monitoring of the COPVs provides rich information about the structural integrity of the component. Furthermore, the collected data can be used for different purposes such as increasing the periodic inspection intervals, providing a remaining lifetime prognosis, and also ensuring optimal operating conditions. Ultimately this information can be complementary to the development of the envisioned digital twin of the monitored COPVs. Guided waves (GWs) are preferred to be used in continuous SHM given their ability to travel in complex structures for long distances. However, obtained GW signals are complex and require advanced processing techniques. Machine learning (ML) is increasingly utilized as the main part of the processing pipeline to automatically detect anomalies in the system's integrity. Hence, in this study, we are scrutinizing the potential of using ML to provide continuous monitoring of COPVs based on ultrasonic GW data. Data is collected from a network of sensors consisting of fifteen Piezoelectric (PZT) wafers that were surface mounted on the COPV. Two ML algorithms are used in the automated evaluation procedure (i) a long short-term memory (LSTM) autoencoder for anomaly detection (defects/impact), and (ii) a convolutional neural network (CNN) model for feature extraction and classification of the artificial damage sizes and locations. Additional data augmentation steps are introduced such as modification and addition of random noise to original signals to enhance the model's robustness to uncertainties. Overall, it was shown that the ML algorithms used were able to detect and classify the simulated damage with high accuracy.
LIBS‐ConSort: Development of a sensor‐based sorting method for construction and demolition waste
(2023)
AbstractA joint project of partners from industry and research institutions approaches the challenge of construction and demolition waste (CDW) sorting by investigating and testing the combination of laser‐induced breakdown spectroscopy (LIBS) with near‐infrared (NIR) spectroscopy and visual imaging. Joint processing of information (data fusion) is expected to significantly improve the sorting quality of various materials like concrete, main masonry building materials, organic components, etc., and may enable the detection and separation of impurities such as SO3‐cotaining building materials (gypsum, aerated concrete, etc.)Focusing on Berlin as an example, the entire value chain will be analyzed to minimize economic / technological barriers and obstacles at the cluster level and to sustainably increase recovery and recycling rates.The objective of this paper is to present current progress and results of the test stand development combining LIBS with NIR spectroscopy and visual imaging. In the future, this laboratory prototype will serve as a fully automated measurement setup to allow real‐time classification of CDW on a conveyor belt.
This data article introduces a dataset comprising 1630 alkali-activated concrete (AAC) mixes, compiled from 106 literature sources. The dataset underwent extensive curation to address feature redundancy, transcription errors, and duplicate data, yielding refined data ready for further data-driven science in the field of AAC, where this effort constitutes a novelty. The carbon footprint associated with each material used in the AAC mixes, as well as the corresponding CO2 footprint of every mix, were approximated using two published articles. Serving as a foundation for future expansions and rigorous data applications, this dataset enables the characterization of AAC properties through machine learning algorithms or as a benchmark for performance comparison among different formulations. In summary, the dataset provides a resource for researchers focusing on AAC and related materials and offers insights into the environmental benefits of substituting traditional Portland concrete with AAC.
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.
Large-language models (LLMs) such as GPT-4 caught the interest of many scientists. Recent studies suggested that these models could be useful in chemistry and materials science. To explore these possibilities, we organized a hackathon. This article chronicles the projects built as part of this hackathon. Participants employed LLMs for various applications, including predicting properties of molecules and materials, designing novel interfaces for tools, extracting knowledge from unstructured data, and developing new educational applications. The diverse topics and the fact that working prototypes could be generated in less than two days highlight that LLMs will profoundly impact the future of our fields. The rich collection of ideas and projects also indicates that the applications of LLMs are not limited to materials science and chemistry but offer potential benefits to a wide range of scientific disciplines.
The lack of traceability to meter of X-ray Computed Tomography (CT) measurements still hinders a more extensive acceptance of CT in coordinate metrology and industry. To ensure traceable, reliable, and accurate measurements, the determination of the task-specific measurement uncertainty is necessary. The German guideline VDI/VDE 2630 part 2.1 describes a procedure to determine the measurement uncertainty for CT experimentally by conducting several repeated measurements with a calibrated test specimen. However, this experimental procedure is cost and effort intensive. Therefore, the simulation of dimensional measurement tasks conducted with X-ray computed tomography can close these drawbacks. Additionally, recent developments towards a resource and cost-efficient production (“smart factory”) motivate the need for a corresponding numerical model of a CT system (“digital twin”) as well. As there is no standardized procedure to determine the measurement uncertainty of a CT system by simulation at the moment, the project series CTSimU was initiated, aiming at this gap. Concretely, the goal is the development of a procedure to determine the measurement uncertainty numerically by radiographic simulation. The first project (2019-2022), "Radiographic Computed Tomography Simulation for Measurement Uncertainty Evaluation - CTSimU" developed a framework to qualify a radiographic simulation software concerning the correct simulation of physical laws and functionalities. The most important outcome was a draft for a new guideline VDI/VDE 2630 part 2.2, which is currently under discussion in the VDI/VDE committee. The follow-up project CTSimU2 "Realistic Simulation of real CT systems with a basic-qualified Simulation Software" will deal with building and characterizing a digital replica of a specific real-world CT system. The two main targets of this project will be a toolbox including methods and procedures to configure a realistic CT system simulation and to develop tests to check if this replica is sufficient enough. The result will be a draft for a follow-up VDI/VDE guideline proposing standardized procedures to determine a CT system's corresponding characteristics and test the simulation (copy) of a real-world CT system which we call a "digital twin".
Li dendrites penetration through solid electrolytes (SEs) challenges the development of solid-state Li batteries (SSLBs). To date, significant efforts are devoted to understand the mechanistic dynamics of Li dendrites nucleation, growth, and propagation in SEs, and various strategies that aim to alleviate and even inhibit Li dendrite formation have been proposed. Nevertheless, most of these conventional strategies require either additional material processing steps or new materials/layers that eventually increase battery cost and complexity. In contrast, using external fields, such as mechanical force, temperature physical field, electric field, pulse current, and even magnetic field to regulate Li dendrites penetration through SEs, seems to be one of the most cost-effective strategies. This review focuses on the current research progress of utilizing external physical fields in regulating Li dendrites growth in SSLBs. For this purpose, the mechanical properties of Li and SEs, as well as the experimental results that visually track Li penetration dynamics, are reviewed. Finally, the review ends with remaining open questions in future studies of Li dendrites growth and penetration in SEs. It is hoped this review can shed some light on understanding the complex Li dendrite issues in SSLBs and potentially guide their rational design for further development.
In the present study, in-situ observation of Hot Isostatic Pressure (HIP) procedure of laser powder bed fusion manufactured Ti-6Al-4V parts was performed to quantitatively estimate the densifcation rate of the material and the infuence of the defect initial size and shape on such rate. The observations were performed in-situ using the Ultrafast Tomography Paris-Edinburgh Cell and the combination of fast phase-contrast synchrotron X-ray tomography and energy dispersive difraction. With this strategy, we could quantify how the efectiveness of HIP depends on the characteristics of a defect. Smaller defects showed a higher densifcation rate, while the defect shape did not have signifcant efect on such rate.
The industrial sintering process used to produce metallic matrix pads has been altered to diminish the amount of copper used. Unfortunately, replacing a large part of the copper with iron seems to have reached a limit. In the high-energy, emergency-type rail braking used in this study, the materials are put to the very limit of their usage capacity, allowing us to observe the evolution of the microstructure and mechanical properties of sintered, metallic matrix pads. After the braking test, their compressive behaviour was assessed using digital image correlation (DIC), and their microstructure with scanning electron microscopy (SEM). The worn material has three flat layers with different microstructures and compressive behaviours. The boom layer seems unmodified. Macroscopic and microscopic cracks run through the intermediate layer (2–15 mm depth). The top layer has stiffened thanks to resolidification of copper. The temperature reaches 1000 °C during the braking test, which also explains the carbon diffusion into iron that result in the weakening of iron–graphite interfaces in the pad. Finally, submicronic particles are detected at many open interfaces of the worn and compressed pad. Associated with the predominant role of graphite particles, this explains the weak compressive behaviour of the pads.
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.
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.
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.
Information about an existing structure can be collected at certain costs to evaluate the reliability and condition as realistically as necessary. This information can be relevant or irrelevant, true or biased, precise or imprecise. The incorporation of relevant and quality-assessed measured information into reliability reassessment offers the chance to extend remaining lifetimes and support decision making about optimal actions or maintenance strategies. This paper shows recent developments in a national research project that aims to produce a guideline on the NDT-based, structure-specific modification of partial safety factors. The general methodology, results from recalculations according to the Eurocodes and metrologically solvable testing tasks relevant in the recalculation of the concrete bridges are shown and compared with the non-destructive testing methods applicable to concrete bridges. A case study is used to demonstrate that as-built drawings, in this case of the positions of tendons and shear reinforcement, can be verified using the radar method.
This paper presents a novel approach for developing sustainable building materials through Sequential Learning. Data sets with a total of 1367 formulations of different types of alkali-activated building materials, including fly ash and blast furnace slag-based concrete and their respective compressive strength and CO2-footprint, were compiled from the literature to develop and evaluate this approach. Utilizing this data, a comprehensive computational study was undertaken to evaluate the efficacy of the proposed material design methodologies, simulating laboratory conditions reflective of real-world scenarios. The results indicate a significant reduction in development time and lower research costs enabled through predictions with machine learning. This work challenges common practices in data-driven materials development for building materials. Our results show, training data required for data-driven design may be much less than commonly suggested. Further, it is more important to establish a practical design framework than to choose more accurate models. This approach can be immediately implemented into practical applications and can be translated into significant advances in sustainable building materials development.
Im DIN-Normenausschuss Materialprüfung (NMP) wurde das Normungsgremium NA 062-08-28 AA „Qualifizierung von zerstörungsfreien Prüfungen“ reaktiviert. Das Ziel der Reaktivierung ist die Erarbeitung einer Norm für einen standardisierten Prozess zur probabilistischen Bewertung von Prüfverfahren.
In der zerstörungsfreien Prüfung (ZfP) führt die Ermittlung von Mess- / Prüfunsicherheiten von Prüfverfahren, in normativer Hinsicht in Deutschland und Europa, noch ein Schattendasein. Die Norm ISO IEC 17025 und auch der VDA-Band 5 wurden weiter in Richtung Messunsicherheit entwickelt, allerdings führt ihre Anwendung in der ZfP zu Problemen.
Der Arbeitsausschuss NA 062-08-28 AA soll hier den Brückenschlag zwischen Messunsicherheit, objektiver statistischer Bewertung für ZfP-Verfahren und eine weitere Stärkung der probabilistischen Bruchmechanik erreichen. Geplant ist daher die Erarbeitung einer DIN-Norm, welche die Kriterien für eine korrekte Versuchsplanung, ein praktikables Vorgehen zur Bewertung der Prüfergebnisse und die mathematische Überführung in eine Zuverlässigkeitsaussage enthält. Es soll ein Leitfaden erstellt werden, der für ein möglichst breites Branchenspektrum eingesetzt werden kann, unabhängig von den Besonderheiten verschiedener Industriezweige.
Dargestellt werden das relevante Normungsgremium sowie der Hintergrund des zu erstellenden Dokuments.
Almost all building materials in civil engineering have an open porosity and interact with or are affected by the environmental conditions. Structures might suffer from effects such as moisture adsorption, carbonation, corrosion, penetration of salt ions and chemical substances, etc. In the hygroscopic range, these processes are mostly driven by diffusion. Due to the confinement of small pores (less than1 µm), the Knudsen effect reduces the molecular diffusion. This reduction can become more significant in case of temporal changing pore systems because of physisorption of water vapor, carbonation, or chemisorption.
In this study, unstabilised earth blocks and earth masonry are investigated. In a first step, the pore size distribution of the blocks is measured and sorption isotherms are recorded in experiments. Besides the ordinary physisorption, the involved clay minerals undergo swelling or shrinking due to chemisorption. The following two effects must be considered: first, the reduction of the available pore space by the adsorbed water layer. For this, the Hillerborg sorption theory is used, which is a combination of the well-known Brunauer-Emmett-Teller sorption theory and the Kelvin equation. This allows the computation of adsorbed water layers even in curved pore geometries. Second, the variation of the initial pore size distribution due to chemisorption needs to be modelled. Based on these two models, the effective diffusion coefficient can be predicted. For validation, arrays of relative humidity sensors were embedded into a free-standing earth masonry wall. This monitoring was carried out over more than a year to have a broad variety of environmental conditions and was located in Berlin, Germany.
The prediction of the effective diffusion coefficient can also be transferred to other processes and allows the investigation of materials having temporarily changing pore systems. Examples are the carbonation of cementitious materials, alkali silica reaction, calcium leaching of long-lasting structures, etc. These effects are prominent in the meso-pore range and might significantly alter the effective diffusion coefficient.
A major advantage in the reassessment of existing structures is the possibility of including measured data that describe the actual properties and the current condition of the structure to be reassessed. Currently, the incorporation of such measured information is mostly unregulated. However, the use of measurement results is vitally important, since a measured data-based improvement of the computation models level of approximation can lead at least to more meaningful results, possibly to extended remaining life times of the structure and in the best case to a saving of resources. Conversely, not appreciating well measurable and relevant information can be equated with a waste of resources. In this paper, a concept for the comparable use of non-destructively measured data as basic variables in probabilistic reliability assessments is outlined and examined using a typical prestressed concrete road bridge as a case-study. An essential requirement is the calculation of measurement uncertainties in order to evaluate the quality of the measurement results comparably. In conclusion, the example of ultrasonic and radar measurement data is used to demonstrate the effects that the incorporation of the measured information has on the reliability of the structure.
In this study, the wavefield radiated from a building to its surroundings is identified and extracted from M4.6 earthquake recordings collected by sensors installed in a building and on the nearby athletic field in Matera (Italy) using a new approach for soil-structure interaction assessment. The proposed approach for earthquake data analysis combines in an innovative way two methods already used in seismology and engineering seismology: deconvolution and polarization analysis. The approach enables the identification, reconstruction, and characterization of the wavefield radiated from a vibrating building into its surroundings, and the estimation of the amount of energy associated with it. The approach consists of four steps: estimation of the resonant frequencies of the building, deconvolution of the earthquake recordings from a building and its surroundings, identification of the seismic phases, reconstruction of the signal transmitted from the building to its surroundings, and estimation of its energy, and polarization analysis. Analysis of recordings of the M4.6 event highlighted that the motion related to the wavefield radiated from the building to the ground was mostly linearly polarized in the radial and transverse planes, while a clear ellipticity was observed only in the horizontal plane. The wavefield radiated from the building might be dominated by unconventionally polarized surface waves, i.e., quasi-Rayleigh waves or a combination of quasi-Rayleigh and quasi-Love waves. The results indicated that the energy transmitted from the analyzed vibrating building to its surroundings was significant and decreased the ground motion shaking due to the out-of-phase motion.
Weather-dependent passive thermography and thermal simulation of in-service wind turbine blades
(2023)
. To cope with the increase in the manufacturing and operation of wind turbines, wind farm operators need inspection tools that are able to provide reliable information while keeping the downtime low. Current inspection techniques require to stop the wind turbine. This work presents the current progress in the project EvalTherm, in which passive thermography is evaluated as a possible non-destructive inspection tool for operational wind turbine blades (WTBs). A methodology to obtain thermal images of rotating WTBs has been established in this project. However, the quality of the results is heavily dependent on various aspects such as weather conditions, information on the inspected WTB, damage history, etc. In this work, a section of a used WTB is simulated using finite-element modelling (FEM) as well as experimentally tested for evaluating the accuracy of the model. Such a model will provide insight into the potential thermal response of a certain structure (with specific material properties) in given weather (boundary) conditions. The model is able to provide satisfactory predictions of the thermal response of the structure, as well as indicate what thermal contrast(s) result from artificial defects introduced in the structure.
Reliability assessment of existing concrete bridges with geometrical NDT results - Case studies
(2023)
The results of and the validity in reliability assessment of existing bridges essentially depend on the information available about the considered system. Information about the actual condition as well as structural and material characteristics can be observed on-site to refine the computation models used in assessment. Non-destructive testing (NDT) methods for concrete structures are capable of reconstructing missing, questioned, or inconsistent as-built plans. This contribution summarizes recent developments within the scope of the national pre-standardization project “ZfPStatik”, which aims to prepare a guideline about NDT-supported structural analyses. The focus is on the purposeful and explicit utilization of geometrical tendon and reinforcement bar positions (measured on-site using the ultrasound echo and ground penetrating radar (GPR) techniques) in probabilistic reliability analyses — shown by means of real case studies. The well-established first order reliability method is applied to different concrete bridges, which are typical for the German road bridge stock, to demonstrate the utility of incorporating quality-evaluated NDT-results in terms of changes in structural reliability.
The present work is part of the AIFRI project (Artificial Intelligence For Rail Inspection), where we and our project partners train a neural network for defect detection and classification. Our goal at BAM is to generate artificial ultrasound and eddy current training data for the A.I. This paper has an exploratory nature, where we focus on the simulation of eddy current signals for head check cracks, one of the most important rail surface defects. The goal of this paper is twofold. On the one hand, we present our general simulation setup. This includes geometric models for head check cracks with features like branching and direction change, a model for the HC10 rail testing probe, and the configuration of the Faraday simulation software.
On the other hand, we use the Faraday software to simulate eddy current testing signals with a strong focus on the influence of the damage depth on the signal, while differentiating between different crack geometries. Here, we observe an early saturation effect of the test signal at a damage depth of 2 mm (at a crack angle of 25◦ to the surface). That is about 2 mm earlier than we would expect from measurements at a crack angle of 90◦. This behavior will be investigated further in a future paper. Finally, we interpolate the simulated signals in a two-step curve fitting process. With these interpolations we may generate eddy current test signals for any damage depth within the simulated range.