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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.
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.
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.
The ultrasonic echo technique is frequently used in non-destructive testing (NDT) of concrete structures for thickness measurements, geometry determinations as well as localization of built-in components. To improve ultrasonic imaging of complex structures in concrete, we transferred a geophysical imaging technique, the reverse time migration (RTM), to NDT in civil engineering. In contrast to the conventionally used synthetic aperture focusing technique (SAFT) algorithms, RTM is a wavefield continuation method in time and uses the full wave equation. Thus, RTM can handle complicated wave propagations in any direction without dip limitation. In this paper, we focused on the application and evaluation of a two-dimensional (2D) elastic RTM algorithm considering compressional waves, vertically polarized shear waves, and Rayleigh waves. We tested the elastic RTM routine on synthetic ultrasonic echo data generated with a 2D concrete model consisting of several steps and circular air inclusions. As these complex structures can often be found in real-world NDT use cases, their imaging is especially important. By using elastic RTM, we were able to clearly reproduce vertical reflectors and lower edges of circular air voids inside our numerical concrete model. Such structures cannot be imaged with conventional SAFT algorithms. Furthermore, the used elastic RTM approach also yielded a better reconstruction of a horizontal reflector and upper boundaries of circular air inclusions. Our encouraging results demonstrate that elastic RTM has the potential to significantly improve the imaging of complex concrete structures and, thus, is a step forward for detailed, high-quality ultrasonic NDT in civil engineering.
The stress–strain behavior of ceramics, such as aluminum titanate, has certain features that are unusual for brittle materials—in particular, a substantial nonlinearity under uniaxial tension, and load–unload hysteresis caused by the sharp increase of the incremental stiffness at the beginning of unloading. These features are observed experimentally and are attributed to microcracking. Here we compare different degrees of stress–strain nonlinearity of aluminum titanate materials and quantitatively model them. We use advanced mechanical testing to observe the mechanical response at room and high temperature; electron microscopy, and X-ray refraction radiography to observe the microstructural changes. Experiments show that two types of microcracks can be distinguished: (i) microcracks induced by cooling from the sintering temperature (due to heterogeneity and anisotropy of thermal expansion), with typical sizes of the order of grain size, and (ii) much larger microcracks generated by the mechanical loading. The two microcrack types produce different effects on the stress–strain curves. Such microcracks and the features of the stress–strain behavior depend on the density of the cooling-induced microcracks and on the distribution of grain sizes. They are modeled analytically and numerically.
Phase-sensitive optical time-domain reflectometry (jOTDR) is a technology for distributed vibration sensing, where vibration amplitudes are determined by recovering the phase of the backscattered light. Measurement noise induces phase errors, which degrades sensing performance. The phase errors, using a differentiation and cross-multiplication (DCM) algorithm, are investigated theoretically and experimentally in a jOTDR system based on a phase retrieval configuration consisting of an imbalanced Mach–Zehnder interferometer (IMZI) and a 3 x 3 coupler. Analysis shows that phase error is highly dependent on the AC component of the obtained signal, essentially being inversely proportional to the product of the power of the light backscattered from two locations. An analytical expression was derived to estimate the phase error and was confirmed by experiment. When applied to the same measurement data, the error is found to be slightly smaller than that obtained using in-phase/quadrature (I/Q) demodulation. The error, however, increases for longer measurement times.
This paper presents reported machine learning approaches in the field of Brillouin distributed fiber optic sensors (DFOSs). The increasing popularity of Brillouin DFOSs stems from their capability to continuously monitor temperature and strain along kilometer-long optical fibers, rendering them attractive for industrial applications, such as the structural health monitoring of large civil infrastructures and pipelines. In recent years, machine learning has been integrated into the Brillouin DFOS signal processing, resulting in fast and enhanced temperature, strain, and humidity measurements without increasing the system’s cost. Machine learning has also contributed to enhanced spatial resolution in Brillouin optical time domain analysis (BOTDA) systems and shorter measurement times in Brillouin optical frequency domain analysis (BOFDA) systems. This paper provides an overview of the applied machine learning methodologies in Brillouin DFOSs, as well as future perspectives in this area.
Capillary active interior insulation materials are an important approach to minimize energy losses of historical buildings. A key factor for their performance is a high liquid conductivity, which enables redistribution of liquid moisture within the material. We set up an experiment to investigate the development of moisture profiles within two different interior insulation materials, calcium-silicate (CaSi) and expanded perlite (EP), under constant boundary conditions. The moisture profiles were determined by two different methods: simple destructive sample slicing with subsequent thermogravimetric drying as well as non-destructive NMR measurements with high spatial resolution. The moisture profiles obtained from both methods show good agreement, when compared at the low spatial resolution of sample slicing, which demonstrates the reliability of this method. Moreover, the measured T2-relaxation-time distributions across the sample depth were measured, which may give further insight into the saturation degree of the different pore sizes. In order to explain differences in the moisture profiles between CaSi and EP, we determined their pore-size distribution with different methods: conversion of the NMR T2 relaxationtime distribution at full saturation, mercury intrusion porosimetry and indirect determination from pressure plate measurements. CaSi shows a unimodal distribution at small pore diameters, while in EP, a bi-modal or wider distribution was found. We assume that the smaller pore diameters of CaSi lead to a higher capillary conductivity, which causes a more distributed moisture profile in comparison with that of EP.
Regardless of the experimental care practiced in acquiring X-ray computed tomography (XCT) data, artifacts might still exist, such as noise and blur. This is typical for fast XCT data acquisitions (e.g., in-situ investigations), or low-dose XCT. Such artifacts can complicate subsequent analysis of the data. Digital filters can moderately cure extensive artifacts. The selection of filter type, intensity, and order of application is not always straight forward. To tackle these problems, a complete sequential multilevel, multi-scale framework: BAM SynthCOND, employing newly designed deep convolutional neural networks (DCNNs), was formulated. Although data conditioning with neural networks is not uncommon, the main complication is that completely artifact-free XCT data for training do not exist. Thus, training data were acquired from an in-house developed library (BAM SynthMAT) capable of generating synthetic XCT material microstructures. Some novel DCNN architectures were introduced (2D/3D ACEnet_Denoise, 2D/3D ACEnet_Deblur) along with the concept of Assertive Contrast Enhancement (ACE) training, which boosts the performance of neural networks trained with continuous loss functions. The proposed methodology accomplished very good generalization from low resemblance synthetic training data. Indeed, denoising, sharpening (deblurring), and even ring artifact removal performance were achieved on experimental post-CT scans of challenging multiphase Al-Si Metal Matrix Composite (MMC) microstructures. The conditioning efficiencies were: 92% for combined denoising/sharpening, 99% for standalone denoising, and 95% for standalone sharpening. The results proved to be independent of the artifact intensity. We believe that the novel concepts and methodology developed in this work can be directly applied on the CT projections prior to reconstruction, or easily be extended to other imaging techniques such as: Microscopy, Neutron Tomography, Ultrasonics, etc.
In this work, we report on our progress for investigating a new experimental approach for thermographic detection of internal defects by performing 2D photothermal super resolution reconstruction. We use modern high-power laser projector technology to repeatedly excite the sample surface photothermally with varying spatially structured 2D pixel patterns. In the subsequent (blind) numerical reconstruction, multiple measurements are combined by exploiting the joint-sparse nature of the defects within the specimen using nonlinear convex optimization methods. As a result, a 2D-sparse defect/inhomogeneity map can be obtained. Using such spatially structured heating combined with compressed sensing and computational imaging methods allows to significantly reduce the experimental complexity and to study larger test surfaces as compared to the one-dimensional approach reported earlier.
The osseointegration in/around additively manufactured (AM) lattice structures of a new titanium alloy, Ti–19Nb–14Zr, was evaluated. Different lattices with increasingly high sidewalls gradually closing them were manufactured and implanted in sheep. After removal, the bone–interface implant (BII) and bone–implant contact (BIC) were studied from 3D X-ray computed tomography images. Measured BII of less than 10 µm and BIC of 95% are evidence of excellent osseointegration.
Since AMnaturally leads to a high-roughness surface finish, the wettability of the implant is increased.
The new alloy possesses an increased affinity to the bone. The lattice provides crevices in which the biological tissue can jump in and cling. The combination of these factors is pushing ossification beyond its natural limits. Therefore, the quality and speed of the ossification and osseointegration in/around these Ti–19Nb–14Zr laterally closed lattice implants open the possibility of bone spline key of prostheses. This enables the stabilization of the implant into the bone while keeping the possibility of punctual hooks allowing the implant to be removed more easily if required. Thus, this new titanium alloy and such laterally closed lattice structures are appropriate candidates to be implemented in a new generation of implants.
For dangerous goods packagings, drop testing onto an essential unyielding target can be used to assess the mechanical resistance to impact loads. Adopted regulations like ADR/RID require that the impact surface provided shall be integral with a mass at least 50 times than that of the heaviest package to be tested. The problem is that many manufacturers do not possess impact targets that satisfy the required 50 times mass ratio for regulative drop tests during series production. The objective of this work is to verify existing and define improved criteria for impact target structures based on systematic investigations. Previous evidence highlights the relevance of other parameters in addition to the mass ratio. Therefore, in this research, a variation of drop test parameters was carried out experimentally. Furthermore, numerical vibration analysis was applied to investigate the deformability of the impact surface. The results conclude that the mass ratio of 1:50 cannot be defined as a decisive criterion. In order to determine the influence of further drop test parameters, the research findings were used to validate a parametric model which assesses impact target deflection. An approximation quality of over 90 % was achieved. As a result, new evaluation criteria are proposed. Firstly, a method for identifying critical impact target designs is provided. Secondly, a new comprehensive formula compares the approximated maximum deflection of a real impact target to the respective theoretical threshold derived from a worst-case assumption. In practice, this leads to great advantages in the evaluation of already installed impact targets for dangerous goods packagings.
The peak broadening in neutron diffraction experiments on tensile specimens of pure Al (99.8%) and an Al-Mg alloy pre-deformed at different creep strains is analysed. These results are combined with the kernel angular misorientation of electron backscatter diffraction data from the creep-deformed microstructures. It is found that differently oriented grains possess different microstrains. These microstrains vary with creep strain in pure Al, but not in the Al-Mg alloy. It is proposed that this behaviour can explain the power-law breakdown in pure Al and the large creep strain observed in Al-Mg. The present findings further corroborate a description of the creep-induced dislocation structure as a fractal, predicated on previous work.
The application and benefits of Semantic Web Technologies (SWT) for managing, sharing, and (re-)using of research data are demonstrated in implementations in the field of Materials Science and Engineering (MSE). However, a compilation and classification are needed to fully recognize the scattered published works with its unique added values. Here, the primary use of SWT at the interface with MSE is identified using specifically created categories. This overview highlights promising opportunities for the application of SWT to MSE, such as enhancing the quality of experimental processes, enriching data with contextual information in knowledge graphs, or using ontologies to perform specific queries on semantically structured data. While interdisciplinary work between the two fields is still in its early stages, a great need is identified to facilitate access for nonexperts and develop and provide user-friendly tools and workflows. The full potential of SWT can best be achieved in the long term by the broad acceptance and active participation of the MSE community. In perspective, these technological solutions will advance the field of MSE by making data FAIR. Data-driven approaches will benefit from these data structures and their connections to catalyze knowledge generation in MSE.
The dataset contains raw data gathered with the ultrasonic pulse-echo method on concrete specimens. The surfaces of the measuring objects were automatically scanned point by point. Pulse-echo measurements were performed at each of these measuring points. The test specimens represent two typical testing tasks in construction industry: the detection of objects and the determination of dimensions to describe the geometry of components. By automating the measurement process, the different test scenarios are examined with a high repeatability, precision and measuring point density. Longitu- dinal and transversal waves were used and the geometrical aperture of the testing system was varied. The low-frequency probes operate in a range of up to approximately 150 kHz. In addition to the specification of the geometrical dimensions of the individual probes, the directivity pattern and the sound field characteristics are provided. The raw data are stored in a universally readable format. The length of each time signal (A-scan) is two milliseconds and the sampling rate is two mega-samples per second. The provided data can be used for comparative studies in signal analysis, imag- ing and interpretation as well as for evaluation pur- poses in different, practically relevant testing scenarios.
The prediction of porosity is a crucial task for metal based additive manufacturing techniques such as laser powder bed fusion. Short wave infrared thermography as an in-situ monitoring tool enables the measurement of the surface radiosity during the laser exposure. Based on the thermogram data, the thermal history of the component can be reconstructed which is closely related to the resulting mechanical properties and to the formation of porosity in the part. In this study, we present a novel framework for the local prediction of porosity based on extracted features from thermogram data. The framework consists of a data pre-processing workflow and a supervised deep learning classifier architecture. The data pre-processing
workflow generates samples from thermogram feature data by including feature information from multiple subsequent layers.
Thereby, the prediction of the occurrence of complex process phenomena such as keyhole pores is enabled. A custom convolutional neural network model is used for classification. Themodel is trained and tested on a dataset from thermographic in-situ monitoring of the manufacturing of an AISI 316L stainless steel test component. The impact of the pre-processing parameters and the local void distribution on the classification performance is studied in detail. The presented model achieves an accuracy of 0.96 and an f1-Score of 0.86 for predicting keyhole porosity in small sub-volumes with a dimension of (700 × 700 × 50) μm3. Furthermore, we show that pre-processing parameters such as the porosity threshold for sample
labeling and the number of included subsequent layers are influential for the model performance. Moreover, the model prediction is shown to be sensitive to local porosity changes although it is trained on binary labeled data that disregards the actual sample porosity.
The corner echo is a well-known effect in ultrasonic testing, which allows detection of surface breaking cracks with predominantly perpendicular orientation to the surface as, for example, corrosion cracks in metal pipes or shafts. This echo is formed by two planes, the surface of the crack and the surface which the crack breaks. It can also be classified as a half-skip method, since a reflection of the pulse occurs on the backwall before the reflection at the defect takes place. In combination with the diffraction from the crack tip, the corner echo also allows crack sizing. As shown in this paper, the corner reflection can be used in civil engineering for nondestructive inspection of concrete. Commercially available low frequency ultrasonic arrays with dry point contact sources generate SH transversal waves with sufficient divergence of the sound field in order to detect corner reflections. Ultrasonic line-scans and area-scans were acquired with a linear array on flat concrete specimens, and the data were reconstructed by the Synthetic aperture focusing technique. If the angles and the area of reconstruction are chosen accordingly, the corner echo reflection can be distinguished from other ultrasonic information. The corner echo can thus be used as a method for deciding whether a crack is a partial-depth crack or a full-depth crack and thus for obtaining a statement about crack depth. This paper presents corresponding experimental results obtained on concrete specimens with artificial test defects and cracks induced under controlled conditions.
Two test series were examined using nondestructive measuring methods by six independent laboratories before determining their compressive strength. The nondestructive test methods used were the rebound hammer and ultrasonic pulse velocity measurement. Two types of geometries were investigated: drilled cores and cubes. The measurement procedure for each of these datasets is conditioned to the geometry and is therefore different.
The first series consists of 20 drilled cores (approximately diameter/height = 10 cm/20 cm) from the 55-year-old Lahntal Viaduct near Limburg, Germany. After preparation in the first laboratory, the lateral surface of the drilled cores was tested with the rebound hammer using a given pattern. Every laboratory tested every drilled core at different locations.
Ultrasonic measurements in transmission were performed repeatedly at predefined points on the flat surfaces of the specimen.
The second series consisted of 25 newly manufactured concrete cubes of a mix with a target concrete strength class of C30/37. The edge length was 15 cm. Each laboratory received five specimens of this test series. Thus, contrary to the first series, each specimen was tested by only one laboratory. Two side faces of each cube were tested with the rebound hammer. In addition, ultrasonic measurements were performed by one laboratory. The time of flight was measured between the tested side faces of the rebound hammer at different positions.
For both series, rebound hammers were used to determine the R-value as well as the Q-value. The rebound hammer models within the laboratories were always the same, while they differed between the laboratories. The ultrasonic measurements took place with different measurement systems and couplants. Finally, both specimen series were tested destructively for compressive strength.
The dataset contains the raw data summarized in tabular form. In addition, relevant calculated data are included in some cases. For the ultrasonic measurements, the time of flight has already been converted into the ultrasonic velocity. Besides, in addition to the raw data of the compressive strength test (force, weight, and geometry values), the calculated compressive strengths and densities are also provided.
Using digital twins for decision making is a very promising concept which combines simulation models with corresponding experimental sensor data in order to support maintenance decisions or to investigate the reliability. The quality of the prognosis strongly depends on both the data quality and the quality of the digital twin. The latter comprises both the modeling assumptions as well as the correct parameters of these models. This article discusses the challenges when applying this concept to realmeasurement data for a demonstrator bridge in the lab, including the data management, the iterative development of the simulation model as well as the identification/updating procedure using Bayesian inference with a potentially large number of parameters. The investigated scenarios include both the iterative identification of the structural model parameters as well as scenarios related to a damage identification. In addition, the article aims at providing all models and data in a reproducibleway such that other researcher can use this setup to validate their methodologies.
The damage mechanisms of metallic components produced by process laser powder bed fusion differ significantly from those typically observed in conventionally manufactured variants of the same alloy. This is due to the unique microstructures of additively manufactured materials. Herein, the focus is on the study of the evolution of creep damage in stainless steel 316L specimens produced by laser powder bed fusion. X-ray computed tomography is used to unravel the influence of the process-specific microstructure from the influence of the initial void distribution on creep damage mechanisms. The void distribution of two specimens tested at 600 °C and 650 °C is analyzed before a creep test, after an interruption, and after fracture. The results indicate that the formation of damage is not connected to the initial void distribution. Instead, damage accumulation at grain boundaries resulting from intergranular cracking is observed.
NMR is becoming increasingly popular for the investigation of building materials as it is a non-invasive technology that does not require any sample preparation nor causes damage to the material. Depending on the specific application it can offer insights into properties like porosity and spatial saturation degree as well as pore structure. Moreover it enables the determination of moisture transport properties and the (re-)distribution of internal moisture into different reservoirs or chemical phases upon damage and curing. However, as yet most investigations were carried out using devices originally either designed for geophysical applications or the analysis of rather homogeneous small scale (< 10 mL) samples. This paper describes the capabilities of an NMR tomograph, which has been specifically optimized for the investigation of larger, heterogeneous building material samples (diameters of up to 72 mm, length of up to 700 mm) with a high flexibility due to interchangeable coils allowing for a high SNR and short echo times (50 - 80 m s).
Wavefield measurements by a scanning laser Doppler vibrometer are generally carried out in a cartesian coordinate. As a piezoelectric transducer generates Lamb waves following radial paths, the use of a polar coordinate can be a suitable alternative to the use of a cartesian coordinate. Therefore, in the proposed method, using a single transducer placed on the center of the specimen, the measured wavefields are transformed into polar coordinates, making several identical radial line inspections from the center in a direction of incident waves. Taking advantage of the properties of the polar coordinates, a signal processing technique is proposed through a frequency-wavenumber filtering process in these coordinates. In this technique, by using proper filters, unwanted wave modes of the incident wave along with all reflected waves are filtered out. In addition, the conventional features of RMS and Euclidean distance are adapted for the polar coordinate system to image the bonded plate. The proposed signal processing and damage imaging are first introduced through a numerical simulation. Then, the performance of the proposed technique is presented by experimental measurements of two specimens including adhesively bonded carbon fiber-reinforced plastic composite plates and bonded aluminum plates.
The interest in using computer simulations of dimensional x-ray computed tomography (dXCT) for various metrological purposes—such as measurement planning, performance prediction, performance optimisation and, finally, measurement uncertainty estimation—is increasing along with the ever-growing demand for more reliable measurements with dXCT. However, before a piece of simulation software can be used for tasks related to coordinate metrology, it has to be ensured that it is able to simulate physical laws, characteristic effects and basic CT system functionalities correctly and with sufficient accuracy. In short, the software must be qualified for dimensional metrology tasks. As one part of such a qualification process, a method is presented here for determining conformity intervals of 2D tests (projection-based tests) based on 3D tests (testing based on dimensional evaluations in a reconstructed volume) for the assessment of dXCT simulation software. The method consists of varying relevant parameter values in order to verify their influence on 3D measurement results. The results of the 3D tests with varied parameter values are then transferred to the quantities tested in the 2D tests and used as the basis for determining conformity intervals. Two approaches are applied for determining whether or not a variation of a parameter value is significant: (a) statistical and (b) heuristic. Two examples are presented, each based on simulated images, which show the application of the two different approaches for determining conformity intervals for the results of the 2D tests.
Fused filament fabrication (FFF) is a material extrusion-based technique often used in desktop 3D printers. Polymeric filaments are melted and are extruded through a heated nozzle to form a 3D object in layers. The extruder temperature is therefore a key parameter for a successful print job but also one of the main emission driving factors as harmful pollutants (e.g., ultrafine particles) are formed by thermal polymer degradation. The awareness of potential health risks has increased the number of emission studies in the past years. However, studies usually refer their calculated emission data to the printer set extruder temperature for comparison purposes. In this study, we used a thermocouple and an infrared camera to measure the actual extruder temperature and found significant temperature deviations to the displayed set temperature among printer models. Our result shows that printing the same filament feedstocks with three different printer models and with identical printer set temperature resulted in a variation in particle emission of around two orders of magnitude. A temperature adjustment has reduced the variation to approx. one order of magnitude. Thus, it is necessary to refer the measured emission data to the actual extruder temperature as it poses a more accurate comparison parameter for evaluation of the indoor air quality in user scenarios or for health risk assessments.
Self-healing agents have the potential to restore mechanical properties and extend service life of composite materials. Thermoplastic healing agents have been extensively investigated for this purpose in epoxy matrix composites due to their strong adhesion to epoxy and their ability to fill in microcracks. One of the most
investigated thermoplastic additives for this purpose is poly(ethylene-co-methacrylic acid) (EMAA). Despite the ability of thermoplastic healing agents to restore mechanical properties, it is important to assess how the addition of thermoplastic healing agents affect properties of the original epoxy material. In this work, EMAA was added to epoxy resin and the effect of the additive on fracture toughness of epoxy was evaluated. Results indicate that although added in low concentrations, EMAA can affect fracture toughness.
The electron density and temperature of a laser-induced plasma can be determined from the width and intensity of the spectral lines, provided that the corresponding optical transitions are optically thin. However, the lines in laser induced plasma are often self-absorbed. One of the methods of correction of this effect is based on the use of the Planck function and an iterative numerical calculation of the plasma temperature. In this study, the method is further explored and its inherent errors and limitations are evaluated. For this, synthetic spectra are used that fully correspond to the assumed conditions of a homogeneous isothermal plasma at local thermodynamic equilibrium. Based on the error analysis, the advantages and disadvantages of the method are discussed in comparison with other methods of self-absorption correction.
The hard X-ray beamline BAMline at BESSY II (Berlin, Germany) has now been in service for 20 years. Several improvements have been implemented in this time, and this review provides an overview of the imaging methods available at the BAMline. Besides classic full-field synchrotron X-ray computed tomography (SXCT), also absorption edge CT, synchrotron X-ray refraction radiography (SXRR), and synchrotron X-ray refraction tomography (SXRCT) are used for imaging. Moreover, virtually any of those techniques are currently coupled in situ or operando with ancillary equipment such as load rigs, furnaces, or potentiostats. Each of the available techniques is explained and both the current and the potential usage are described with corresponding examples. The potential use is manifold, the examples cover organic materials, composite materials, energy-related materials, biological samples, and materials related to additive manufacturing. The article includes published examples as well as some unpublished applications.
Two biopolyol-based foams derived from banana leaves (BL) or stems (BS) were produced, and their compression mechanical behavior and 3D microstructure were characterized. Traditional compression and in situ tests were performed during 3D image acquisition using X-ray microtomography. A methodology of image acquisition, processing, and analysis was developed to discriminate the foam cells and measure their numbers, volumes, and shapes along with the compression steps.
The two foams had similar compression behaviors, but the average cell volume was five times larger for the BS foam than the BL foam. It was also shown that the number of cells increased with increasing compression while the average cell volume decreased. Cell shapes were elongated and did not change with compression. A possible explanation for these characteristics was proposed based on the possibility of cell collapse. The developed methodology will facilitate a broader study of biopolyol-based foams intending to verify the possibility of using these foams as green alternatives to the typical petrol-based foams.
Characterization is a very important step in dealing with materials and waste streams generated during the operational and decommissioning phases of nuclear installations, including nuclear power plants. Characterization allows differentiation between materials that can be released from regulatory control and those that require further treatment and conditioning to become a stable waste form suitable for future storage and final disposal according to its waste classification. Characterization is also needed in the pre-disposal stages of radioactive waste management to demonstrate compliance with the waste acceptance criteria of the facilities that will accept the different waste forms. This work will present the strategies developed and implemented by the three projects for in-depth and accurate waste characterization and investigation of the different radioactive waste packages considered. CHANCE, MICADO, and PREDIS will present their goals, the methods developed, the technologies used and the (preliminary) results contributing to the improvement of the safety and the data and information quality of the waste packages analyzed at the different stages of the waste management process. Special emphasis will also be given to complementary approaches highlighting the usability of the technologies, the accessibility of the data, and the problem-solving of the three projects within the European panorama.
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 (< 1 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. This effect becomes most prominent in the meso-pore range and might alter the effective diffusion coefficient by more than 100 %.
The greatest challenge when using deep convolutional neural networks (DCNNs) for automatic segmentation of microstructural X-ray computed tomography (XCT) data is the acquisition of sufficient and relevant data to train the working network. Traditionally, these have been attained by manually annotating a few slices for 2D DCNNs. However, complex multiphase microstructures would presumably be better segmented with 3D networks. However, manual segmentation labeling for 3D problems is prohibitive. In this work, we introduce a method for generating synthetic XCT data for a challenging six-phase Al–Si alloy composite reinforced with ceramic fibers and particles. Moreover, we propose certain data augmentations (brightness, contrast, noise, and blur), a special in-house designed deep convolutional neural network (Triple UNet), and a multi-view forwarding strategy to promote generalized learning from synthetic data and therefore achieve successful segmentations. We obtain an overall Dice score of 0.77. Lastly, we prove the detrimental effects of artifacts in the XCT data on achieving accurate segmentations when synthetic data are employed for training the DCNNs. The methods presented in this work are applicable to other materials and imaging techniques as well. Successful segmentation coupled with neural networks trained with synthetic data will accelerate scientific output.
In this work, we present a novel approach to photothermal super resolution based thermographic resolution of internal defects using two-dimensional pixel pattern-based active photothermal laser heating in conjunction with subsequent numerical reconstruction to achieve a high-resolution reconstruction of internal defect structures. With the proposed adoption of pixelated patterns generated using laser coupled high-power DLP projector technology the complexity for achieving true two-dimensional super resolution can be dramatically reduced taking a crucial step forward towards widespread practical viability. Furthermore, based on the latest developments in high-power DLP projectors, we present their first application for structured pulsed thermographic inspection of macroscopic metal samples. In addition, a forward solution to the underlying inverse problem is proposed along with an appropriate heuristic to find the regularization parameters necessary for the numerical inversion in a laboratory setting. This allows the generation of synthetic measurement data, opening the door for the application of machine learning based methods for future improvements towards full automation of the method. Finally, the proposed method is experimentally validated and shown to outperform several established conventional thermographic testing techniques while conservatively improving the required measurement times by a factor of 8 compared to currently available photothermal super resolution techniques.
Recently, the photothermal determination of the thermophysical properties of concrete under lab conditions was reported. Their values are mainly needed to look at the energy consumption of buildings. Additionally, changes in their values in relation to the initial state might also be a good indicator for material quality or for moisture. The present contribution explains the photothermal method in a more general way to indicate the potential for on-site application. Secondly, a special application case is regarded: the detection of moisture in concrete. Two concrete samples were soaked with water, followed by a drying period, to obtain different levels of water penetration. The water contents were determined by weighing, and the photothermal response was measured. The results show a large influence on the measured temperature transients, which is larger than expected from the original simple model. They clearly provide two points: the photothermal method is suited to detect moisture in concrete, but the magnitude of the actual measurement effect is not yet understood.
What is meant by ‘Micro Non-Destructive Testing and Evaluation’? This was the central subject of debate in this Special Issue.
At present, sub-millimeter-size components or even assemblies are pervading the industrial and scientific world. Classic examples are electronic devices and watches (as well as parts thereof), but recent examples encompass additively manufactured lattice structures, stents, or other microparts. Moreover, most assemblies contain micro-components. Testing such components or their miniaturized parts would fit well within the topic of micro non-destructive testing and evaluation.
In all cases, performance and integrity testing, quality control, and dimensional tolerances need to be measured at the sub-millimeter level (ideally with a spatial resolution of about a micron); most of the time, such features and components are embedded in much larger assemblies, which also need to be taken into account. The solution to this dilemma (i.e. measuring large parts with high resolution) depends on the part and on the problem under consideration.
Another possible definition of micro non-destructive testing and evaluation can relate to the characterization of micro-features (e.g., the microstructure) in much larger specimens, such as damage in concrete cores or porosity in additively manufactured components. A further aspect is the use of microscopic probes to evaluate macroscopic properties. This is the case, for instance but not at all exclusively, in the use of diffraction techniques to determine macroscopic stress.
The splits between testing and characterization at the micro-level (or of micro parts) from one side and handling of macroscopic assemblies on the other represent a great challenge for many fields of materials characterization. On top of that, including the use of microscopic methods to test integrity would add a further level of complexity.
Imaging, mechanical testing, non-destructive testing, measurement of properties, structural health monitoring, and dimensional metrology all need to be re-defined if we want to cope with the multi-faceted topic of micro non-destructive testing and evaluation.
The challenge has already been accepted by the scientific and engineering communities for a while but is still far from being universally tackled. This Special Issue yields an interesting answer to the questions posed above. It presents the progress made and the different aspects of the challenge as well as at indicates the paths for the future of NDT&E.
A phase-sensitive optical time domain reflectometer based on coherent heterodyne detection of geometric phase in the beat signal of light, is reported for the first time to our knowledge. The use of the geometric phase to extract strain makes it immune to polarisation diversity fading. This is because a polarisation mismatch between the interfering beams is not a hindrance to its measurement. The geometric phase is calculated using the amplitude of the beat signal and individual beam intensities without any need for phase unwrapping. It is measured per beat period and can be equated with the traditionally measured dynamic phase with appropriate scaling. The results show that the system based on the geometric phase successfully measures strain, free from polarisation mismatch fading and phase unwrapping errors, providing a completely novel solution to these problems.
Air-coupled ultrasound sensors have advantages over contact ultrasound sensors when a sample should not become contaminated or influenced by the couplant or the measurement has to be a fast and automated inline process. Thereby, air-coupled transducers must emit high-energy pulses due to the low air-to-solid power transmission ratios (10−3 to 10−8). Currently used resonant transducers trade bandwidth—a prerequisite for material parameter analysis—against pulse energy. Here we show that a combination of a non-resonant ultrasound emitter and a non-resonant detector enables the generation and detection of pulses that are both high in amplitude (130 dB) and bandwidth (2 µs pulse width). We further show an initial application: the detection of reflections inside of a carbon fiber reinforced plastic plate with thicknesses between 1.7 mm and 10 mm. As the sensors work contact-free, the time of flight and the period of the in-plate reflections are independent parameters. Hence, a variation of ultrasound velocity is distinguishable from a variation of plate thickness and both properties are determined simultaneously. The sensor combination is likely to find numerous industrial applications necessitating high automation capacity and opens possibilities for air-coupled, single-side ultrasonic inspection.
Data science (digitalisation and artificial intelligence) became more than an important facilitator for many domains in fundamental and applied sciences as well as industry and is disrupting the way of research already to a large extent. Originally, data sciences were viewed to be well-suited, especially, for data-intensive applications such as image processing, pattern recognition, etc. In the recent past, particularly, data-driven and physics-inspired machine learning methods have been developed to an extent that they accelerate numerical simulations and became directly usable for applications related to the nuclear waste management cycle. In addition to process-based approaches for creating surrogate models, other disciplines such as virtual reality methods and high-performance computing are leveraging the potential of data sciences more and more. The present challenge is utilising the best models, input data and monitoring information to integrate multi-chemical-physical, coupled processes, multi-scale and probabilistic simulations in Digital Twins (DTw) able to mirror or predict the performance of its corresponding physical twins. Therefore, the main target of the Topical Collection is exploring how the development of DTw can benefit the development of safe, efficient solutions for the pre-disposal and disposal of radioactive waste. A particular challenge for DTw in radioactive waste management is the combination of concepts from geological modelling and underground construction which will be addressed by linking structural and multi-physics/chemistry process models to building or tunnel information models. As for technical systems, engineered structures a variety of DTw approaches already exist, the development of DTw concepts for geological systems poses a particular challenge when taking the complexities (structures and processes) and uncertainties at extremely varying time and spatial scales of subsurface environments into account.
We report, to our knowledge for the first time on simultaneous distributed temperature and strain sensing in a standard telecom optical fiber using a machine learning assisted Brillouin frequency domain analysis (BOFDA) system. The well-known temperature and strain cross-sensitivity problem is addressed by developing a BOFDA system with a high signal-to-noise ratio and applying machine learning. The spectrum consists of four highly resolved peaks, whose Brillouin frequency shifts are extracted and serve as features for the machine learning algorithms. The spectra result from a 450-m standard SMF-28 optical fiber, and particularly from a segment of 30 m. This fiber segment is coiled around a stretcher and placed in a climate chamber. The applied temperature and strain values range from 20 °C to 40 °C and from 0 µɛ to 1380 µɛ, respectively. The total measurement time to achieve a high SNR and resolve four peaks with a spatial resolution of 6 m is 16 min. To discriminate temperature and strain effects, simple frequentist and more sophisticated Bayesian-based algorithms are employed with the powerful Gaussian process regression (GPR) delivering the best performance in terms of temperature and strain errors, which are found to be 2 °C and 45 µɛ, respectively. These errors are calculated using leave-one-out cross-validation, so that an unbiased estimation of the sensor’s performance is provided.
Metastable austenitic stainless steel (304L) samples with a rectangular cross-section were plastically deformed in torsion during which they experienced multiaxial stresses that led to a complex martensitic phase distribution owing to the transformation induced plasticity effect. A three-dimensional characterization of the phase distributions in these cm-sized samples was carried out by wavelength-selective neutron tomography. It was found that quantitatively correct results are obtained as long as the samples do not exhibit any considerable preferential grain orientation. Optical microscopy, electron backscatter diffraction, and finite element modeling were used to verify and explain the results obtained by neutron tomography. Altogether, neutron tomography was shown to extend the range of microstructure characterization methods towards the meso- and macroscale.
Performance of calcium phosphate cements in the augmentation of sheep vertebrae - An ex vivo study
(2021)
Oil-based calcium phosphate cement (Paste-CPC) shows not only prolonged shelf life and injection times, but also improved cohesion and reproducibility during application, while retaining the advantages of fast setting, mechanical strength, and biocompatibility. In addition, poly(L-lactideco-glycolide) (PLGA) fiber reinforcement may decrease the risk for local extrusion. Bone defects (diameter 5 mm; depth 15 mm) generated ex vivo in lumbar (L) spines of female Merino sheep (2–4 years) were augmented using: (i) water-based CPC with 10% PLGA fiber reinforcement (L3); (ii) Paste-CPC (L4); or (iii) clinically established polymethylmethacrylate (PMMA) bone cement (L5). Untouched (L1) and empty vertebrae (L2) served as controls. Cement performance was analyzed using micro-computed tomography, histology, and biomechanical testing. Extrusion was comparable for Paste-CPC(-PLGA) and PMMA, but significantly lower for CPC + PLGA. Compressive strength and Young’s modulus were similar for Paste-CPC and PMMA, but significantly higher compared to those for empty defects and/or CPC + PLGA. Expectedly, all experimental groups showed significantly or numerically lower compressive strength and Young’s modulus than those of untouched controls. Ready-to-use Paste-CPC demonstrates a performance similar to that of PMMA, but improved biomechanics compared to those of water-based CPC + PLGA, expanding the therapeutic arsenal for bone defects. O, significantly lower extrusion of CPC + PLGA fibers into adjacent lumbar spongiosa may help to reduce the risk of local extrusion in spinal surgery.
This study addressed a 7017 Al-alloy tailored for powder bed fusion – laser beam (PBF-LB) process. The alloy was prepared by mixing 3 wt% Zr and 0.5 wt% TiC powder to standard pre-alloyed 7017 grade aluminium powder. This made printing of the alloys possible avoiding solidification cracking in the bulk and achieving high relative density (99.8 %). Such advanced alloys have significantly higher Young’s modulus (>80 GPa) than conventional Al-alloys (70–75 GPa), thus making them attractive for applications requiring high stiffness. The resulting microstructure in as-printed condition was rich in particles originating from admixed powders and primary precipitates/inclusions originating from the PBF-LB process. After performing a T6-like heat treatment designed for the PBF-LB process, the microstructure changed: Zr-nanoparticles and Fe- or Mg/Zn- containing precipitates formed thus providing 75 % increase in yield strength (from 254 MPa to 444 MPa) at the cost of decreasing ductility (∼20 % to ∼9 %). In-situ tensile testing combined with SXCT, and ex-situ tensile testing combined with fracture analysis confirmed that the fracture initiation in both conditions is highly dependent on defects originated during printing. However, cracks are deflected from decohesion around Zr-containing inclusions/precipitates embedded in the Al-matrix. This deflection is seen to improve the ductility of the material.
While laser powder-bed fusion has overcome some of the design constraints of conventional manufacturing methods, it requires careful selection of process parameters and scan strategies to obtain favorable properties. Here we show that even simple scan strategies, complex ones being inevitable when printing intricate designs, can inadvertently produce local alterations of the microstructure and preferential grain orientation over small areas – which easily remain unnoticed across the macroscale. We describe how a combined usage of neutron imaging and electron backscatter diffraction can reveal these localized variations and explain their origin within cm-sized parts. We explain the observed contrast variations by linking the neutron images to simulated data, pole figures and EBSD, providing an invaluable reference for future studies and showing that presumably minor changes of the scan strategy can have detrimental effects on the mechanical properties. In-situ tensile tests reveal that fracture occurs in a region that was re-melted during the building process.
A new type of ultrasonic borehole probe is currently under development for the quality assurance of sealing structures in radioactive waste repositories using existing research boreholes. The goal is to examine the sealing structures made of salt concrete for possible cracks, delamination, and embedded objects. Earlier prototype probes use 12 or 16 individual dry point contact (DPC) horizontal shear wave transducers grouped into a transmitter and a receiver array, each made up of six or eight individual transducers. They are operated with a commercially available portable ultrasonic flaw detector used in the civil engineering industry. To increase the generated sound pressure of the borehole probe, the number of transducers in the novel probe is increased to 32. In addition, timed excitation of each probe is used to direct a focused sound beam to a specific angle and distance based on calculated time delays. Hence, the sensitive test volume is limited, and the signal-to-noise ratio of the received signals is improved. This paper presents the validation of the newly developed phased array borehole probe by beam computation in CIVA software and experimental investigations on a semi-cylindrical test specimen to investigate the directional characteristics. In combination with geophysical reconstruction techniques, an optimised radiation pattern of the probe is expected to improve the signal quality and thus increase the reliability of the imaging results.
This is of great importance for the construction of safe sealing structures needed for the disposal of radioactive or toxic waste.
This study investigates the non-destructive detection of delaminations in concrete plates using non-contact laser ablation, instead of the conventional hammer excitation, as part of the impact echo method. We performed tests on five concrete specimens of different sizes, two of which contained artificial delaminations. A range of steel ball hammers was used as reference impulse sources, the responses of which were compared with wave excitation generated by a 7 ns pulsed 1064 nm Nd:YAG laser with 150 mJ pulse energy. Signals were recorded by surface-mounted accelerometers and two contactless methods: microphones and a laser Doppler vibrometer. The laser generates frequencies across a broad range of frequencies (0 to 150 kHz) but with much less energy than the hammers' narrower frequency spectra; the laser pulse energy transferred into the specimen is 0.07 mJ, corresponding to about 0.5 ‰ of the impulse source energy. Because of this, the thick intact plates' characteristic thickness stretch resonance frequency can be reliably detected by the hammer excitations but not when using laser excitation. However, the laser can excite low-frequency flexural vibration modes over a shallow delamination at 3 cm depth. The low-frequency flexural vibration results are verified by numerical natural frequency analysis.
Before the final disposal of radioactive wastes, various processes can be implemented to optimise the waste form. This can include different chemical and physical treatments, such as thermal treatment for waste reduction, waste conditioning for homogenisation and waste immobilisation for stabilisation prior to packaging and interim storage. Ensuring the durability and safety of the waste matrices and packages through performance and condition assessment is important for waste owners, waste management organisations, regulators and wider stakeholder communities. Technical achievements and lessons learned from the THERAMIN and PREDIS projects focused on low- and intermediate-level waste handling is shared here. The recently completed project on Thermal Treatment for Radioactive Waste Minimization and Hazard Reduction (THERAMIN) made advances in demonstrating the feasibility of different thermal treatment techniques to reduce volume and immobilise different streams of radioactive waste (LILW) prior to disposal. The Pre-Disposal Management of Radioactive Waste (PREDIS) project addresses innovations in the treatment of metallic materials, liquid organic waste and solid organic waste, which can result from nuclear power plant operation, decommissioning and other industrial processes. The project also addresses digitalisation solutions for improved safety and efficiency in handling and assessing cemented-waste packages in extended interim surface storage.
The aim of this work is to achieve reliable nondestructive evaluation (NDE) of adhesively bonded aerospace components by developing novel multidimensional data fusion techniques, which would combine the information obtained by ultrasonic and X-ray NDE methods. Separately, both NDE techniques have their advantages and limitations. The integration of data obtained from pulse echo immersion ultrasound testing and radiography holds immense potential to help improve the reliability of non-destructive evaluation. In this study, distinctive features obtained from single techniques, traditional ultrasonic pulse echo testing, and radiography, as well as fused images, were investigated and the suitability of these distinctive features and fusion techniques for improving the probability of defect detection was evaluated. For this purpose, aluminum single lap joints with brass inclusions were analyzed using ultrasound pulse echo and radiography techniques. The distinctive features were extracted from the data obtained, and images of features obtained by both techniques were fused together. Different combinations of features and fusion algorithms were investigated, considering the desire to automate data evaluation in the future.
Validation of novel ultrasonic phased array borehole probe by using simulation and measurement
(2022)
Low-frequency ultrasonic testing is a well-established non-destructive testing (NDT) method in civil engineering for material characterization and the localization of cracks, reinforcing bars and delamination. A novel ultrasonic borehole probe is developed for in situ quality assurance of sealing structures in radioactive waste repositories using existing research boreholes. The aim is to examine the sealing structures made of salt concrete for any possible cracks and delamination and to localize built-in components. A prototype has been developed using 12 individual horizontal dry point contact (DPC) shear wave transducers separated by equidistant transmitter/receiver arrays. The probe is equipped with a commercially available portable ultrasonic flaw detector used in the NDT civil engineering industry. To increase the sound pressure generated, the number of transducers in the novel probe is increased to 32 transducers. In addition, the timed excitation of each transducer directs a focused beam of sound to a specific angle and distance based on the previously calculated delay time. This narrows the sensitivity of test volume and improves the signal-to-noise ratio of the received signals. In this paper, the newly designed phased array borehole probe is validated by beam computation in the CIVA software and experimental investigations on a half-cylindrical test specimen to investigate the directional characteristics. In combination with geophysical reconstruction methods, it is expected that an optimised radiation pattern of the probe will improve the signal quality and thus increase the reliability of the imaging results. This is an important consideration for the construction of safe sealing structures for the safe disposal of radioactive or toxic waste.
This paper considers an indirect measurement approach to reconstruct a defect in a two-dimensional waveguide model for a non-destructive ultrasonic inspection via derivative-based optimization. The propagation of the mechanical waves is simulated by the scaled boundary finite element method that builds on a semi-analytical approach. The simulated data are then fitted to given data associated with the reflected waves from a defect which is to be reconstructed. For this purpose, we apply an iteratively regularized Gauss-Newton method in combination with algorithmic differentiation to provide the required derivative information accurately and efficiently. We present numerical results for three kinds of defects, namely, a crack, delamination, and corrosion. The objective function and the properties of the reconstruction method are investigated. The examples show that the parameterization of the defect can be reconstructed efficiently as well as robustly in the presence of noise.
A steel pipeline segment of 2.5 m length was subjected to quasi-static four-point bending load in three steps for studying the initial cracking and damage accumulation based on the Acoustic Emission (AE) technique and by the direct current potential drop (DCPD) technique. For the latter, a new post-test analysis method was established.
AE is found more sensitive to crack initiation than DCPD. Formation of mesoscopic and macroscopic cracks as well as their closure and the resulting friction generate weighted peak frequencies below 400 kHz, whereas microscopic cracking produces AE with broad band spectra identifiable by weighted peak frequencies above 400 kHz. Critical states alike the maximum load level and the leak opening were accompanied by peak amplitudes above 85 dBAE. This rather fundamental study provides a data base for possibly developing advanced strategies of detection and alarm systems based on acoustic monitoring of pipelines, or at least, steel structures.
Influence of a 265 °C heat treatment on the residual stress state of a PBF-LB/M AlSi10Mg alloy
(2022)
Laser Powder Bed Fusion (PBF-LB/M) additive manufacturing (AM) induces
high magnitude residual stress (RS) in structures due to the extremely heterogeneous cooling and heating rates. As the RS can be deleterious to the fatigue resistance of engineering components, great efforts are focused on understanding their generation and evolution after post-process heat treatments. In this study, one of the few of its kind, the RS relaxation induced in an as-built PBF-LB/M AlSi10Mg material by a low-temperature heat treatment (265 °C for 1 h) is studied by means of X-ray and neutron diffraction. Since the specimens are manufactured using a baseplate heated up to 200 °C, low RS are found in the as-built condition. After heat treatment a redistribution of the RS is observed, while their magnitude remains constant. It is proposed that the redistribution is induced by a repartition of stresses between the a-aluminium matrix and the silicon phase, as the morphology of the silicon phase is affected by the heat treatment. A considerable scatter is observed in the neutron diffraction RS profiles, which is principally correlated to the presence (or absence) of pockets of porosity developed at the borders of the chessboard pattern.
Copper sulfide shows some unique physico-chemical properties that make it appealing as a cathode active material (CAM) for solid-state batteries (SSBs). The most peculiar feature of the electrode reaction is the reversible formation of μm-sized Cu crystals during cycling, despite its large theoretical volume change (75%). Here, the dynamic microstructural evolution of CuS cathodes in SSBs is studied using in situ synchrotron X-ray tomography. The formation of μm-sized Cu within the CAM particles can be clearly followed. This process is accompanied by crack formation that can be prevented by increasing the stack pressure from 26 to 40 MPa. Both the Cu inclusions and cracks show a preferential orientation perpendicular to the cell stack pressure, which can be a result of a z-oriented expansion of the CAM particles during lithiation. In addition, cycling leads to a z-oriented reversible displacement of the cathode
pellet, which is linked to the plating/stripping of the Li counter electrode. The pronounced structural changes cause pressure changes of up to 6 MPa within the cell, as determined by operando stack pressure measurements. Reasons for the reversibility of the electrode reaction are discussed and are attributed to the favorable combination of soft materials.
Vertebrate bones are made of a nanocomposite consisting of water, mineral and organics. Water helps bone material withstand mechanical stress and participates in sensation of external loads. Water diffusion across vertebrae of medaka (bone material lacking osteocytes) and zebrafish (bone material containing osteocytes) was compared using neutron tomography. Samples were measured both wet and following immersion in deuterated-water (D2O). By quantifying H+ exchange and mutual alignment with X-ray lCT scans, the amount of water expelled from complete vertebra was determined. The findings revealed that anosteocytic bone material is almost twice as amenable to D2O diffusion and H2O exchange, and that unexpectedly, far more water is retained in osteocytic zebrafish bone. Diffusion in osteocytic bones (only 33 % – 39 % water expelled) is therefore restricted as compared to anosteocytic bone (~ 60 % of water expelled), presumably because water flow is confined to the lacunar-canalicular network (LCN) open-pore system. Histology and Raman spectroscopy showed that anosteocytic bone contains less proteoglycans than osteocytic bone. These findings identify a previously unknown functional difference between the two bone materials. Therefore, this study proposes that osteocytic bone retains water, aided by non-collagenous proteins, which contribute to its poroelastic mechano-transduction of water flow confined inside the LCN porosity.
Ultrasonic Coda Wave interferometry has the potential to detect minute changes in scattering materials like concrete. By permanently installing ultrasonic transducers in concrete, DFG Research unit CoDA aims to develop methods for concrete damage assessment in Germany's aging infrastructure. To test the methods developed in simulations and laboratory experiments on a large scale, we have implemented several ultrasonic transducers at the Gänstorbrücke Ulm, one of Germany's most monitored road bridges. Since fall 2020 we are monitoring parts of the center of the Bridge, as well as an abutment, and compare the results to the commercial monitoring system. All data is recorded with a self-made data collection device, the so-called W-Box, and analyzed with different coda wave-based algorithms to detect signal and volumetric velocity changes. The long-term measurements show that the influence of temperature changes on strains and therefore ultrasound velocity changes calculated with coda waves can be monitored. The capabilities and limitations of the coda wave-based monitoring system are tested in a controlled experiment. Static loading using a truck with varying loads at several positions allows the calibration of the system to improve the detectability of possibly damaging loads and changes induced by this loading. A map of velocity change analyzing data from this load experiment shows that the influence of load on the material and strain distribution can be detected with array measurements.
Hydration is the exothermic reaction between anhydrous cement and water, which forms the solid cement matrix of concrete. Being able to evaluate the hydration is of high interest for the use of both conventional and more climate-friendly building materials. The experimental monitoring is based on temperature or moisture measurements. The first needs adiabatic conditions, which can only be achieved in laboratory. The latter is often measured comparing the weight of the material sample before and after oven drying, which is time-consuming. This study investigates the moisture content of two cement-based and two calcium sulphate based mixtures for the first 90 days by using the calcium carbide method and oven drying at 40 °C and 105 °C (Darr method). Thereby, the amount of chemically bound water is determined to derive the degree of hydration. The calcium carbide measurements highly coincide with oven drying at 40 °C. The calcium carbide method is therefore evaluated as a suitable alternative to the time-consuming Darr drying. The prompt results are seen as a remarkable advantage and can be obtained easily in laboratory as well as in the field.
Attenuation of ultrasonic signals in concrete has the potential to carry much information about the microstructure of the material. In this work a series of concrete specimens of varying porosities and pore size distributions were internally imaged with x-ray computed tomography (CT), and then subsequently examined with throughtransmission ultrasound. The CT images were used to quantify both capillary porosity of cement paste as well as internal interfaces that are likely to produce elastic wave scattering. Ultrasound signals were represented as a diffusion process such that absorption and scattering attenuation could be isolated. As implemented, the diffusion model was a poor predictor of capillary porosity, while diffusivity was a reasonable predictor of scattering interfaces. Diffusivity was found to scale extremely well with small scale porosity, which made it a good predictor of compressive strength.
The retroreflective corner echo is used, for example, in ultrasonic non-destructive testing of metals to find fatigue cracks in tubes or shafts. If the much weaker crack tip signal is additionally detected, the crack length can also be determined. A corner reflection occurs in cases of surface breaking cracks with predominantly perpendicular orientation to the surface. The intensity of the corner reflection depends on the angle of incidence and on the ultrasonic wave mode used. For the reliable detection of vertical surface breaking cracks in metals, transversal waves are commonly used, which propagate at an angle of 37° to 53° to the inspection surface. As shown in this contribution, the wide spread low frequency ultrasonic arrays with dry point contact sources available for ultrasonic testing of concrete also allow to receive corner echoes. These devices generate transversal waves in concrete structures with a large divergence of the sound field. A series of experiments was carried out with such dry point contact arrays on concrete specimens with artificial test defects and controlled induced cracks of different depths. The ultrasonic time-of-flight signals were recorded, exported and reconstructed utilising the SAFT (Synthetic Aperture Focusing Technique) algorithm. The SAFT reconstruction parameters were adjusted to visualize the corner echo indication. As will be shown, with this targeted processing, the reproducible detection of surface breaking cracks in concrete is possible. The retroreflective corner echo can thus be exploited in civil engineering for non-destructive inspection of concrete.
This contribution summarizes actual developments and draft fundamental teaching topics in the field of nondestructive testing in civil engineering (NDT-CE). It is based on the first memorandum on teaching and research in the field of NDT-CE at German speaking universities and provides an overview of the academic education and highlights possible focuses, especially in teaching but also takes into account noteworthy developments and topics in research in the field of NDT-CE.
Suggestions are given for the development and advancement of the teaching curricula in regards to a comprehensive and sound professional education of students in civil engineering and adjacent disciplines.