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Although layer-based additive manufacturing methods such as laser powder bed fusion (PBF-LB) offer an immense geometrical freedom in design, they are typically subject to a build-up of internal stress (i.e. thermal stress) during manufacturing. As a consequence, significant residual stress (RS) is retained in the final part as a footprint of these internal stresses. Furthermore, localized melting and solidification inherently induce columnar-type grain growth accompanied by crystallographic texture. Although diffraction-based methods are commonly used to determine the RS distribution in PBF-LB parts, such features pose metrological challenges in their application. In theory, preferred grain orientation invalidates the hypothesis of isotropic material behavior underlying the common methods to determine RS. In this work, more refined methods are employed to determine RS in PBF-LB/M/IN718 prisms, based on crystallographic texture data. In fact, the employment of direction-dependent elastic constants (i.e. stress factors) for the calculation of RS results in insignificant differences from conventional approaches based on the hypothesis of isotropic mechanical properties. It can be concluded that this result is directly linked to the fact that the {311} lattice planes typically used for RS analysis in nickel-based alloys have high multiplicity and less strong texture intensities compared with other lattice planes. It is also found that the length of the laser scan vectors determines the surface RS distribution in prisms prior to their removal from the baseplate. On removal from the baseplate the surface RS considerably relaxes and/or redistributes; a combination of the geometry and the scanning strategy dictates the sub-surface RS distribution.
With increasing demand and environmental concerns, researchers are exploring new materials that can perform as well or better than traditional materials while reducing environmental impact. The BAMline, a real-life sample materials research beamline, provides unique insights into materials’ electronic and chemical structure at different time and length scales. The beamline specializes in x-ray absorption spectroscopy, x-ray fluorescence spectroscopy, and tomography experiments. This enables real-time optimization of material properties and performance for various applications, such as energy transfer, energy storage, catalysis, and corrosion resistance. This paper gives an overview of the analytical methods and sample environments of the BAMline, which cover non-destructive testing experiments in materials science, chemistry, biology, medicine, and cultural heritage. We also present our own synthesis methods, processes, and equipment developed specifically for the BAMline, and we give examples of synthesized materials and their potential applications. Finally, this article discusses the future perspectives of the BAMline and its potential for further advances in sustainable materials research.
Synchrotron X-ray computed tomography (SXCT) at BAMline has been paired with in-situ tensile loading to monitor damage evolution in LPBF Metal Matrix Composite (MMC) 7017 Aluminium alloy + 3 wt% Zr + 0.5 wt% TiC. The processing of the material leads formation to different categories of Zr-rich inclusions, precipitates and defects. In-situ SXCT test disclosed the critical role of the pre-cracks in the reinforcement phases in the failure mechanisms of LPBF MMC. The damage was initiated from lack-of-fusion defects and cracks propagated through coalescence with other defects.
Moisture testing and mapping
(2023)
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.
In this work, the limits of using spatially structured heating combined with subsequent photothermal super resolution reconstruction for the thermographic detection and resolution of internal defects are investigated. The approach is based on the application of modern high-power laser projector technology, which is used to repeatedly project varying spatially structured 2D pixel patterns to photothermally heat the object under test. After processing the generated thermographic data using nonlinear convex optimisation in conjunction with exploiting the joint-sparse nature of the defect signals within the individual measurements, a high-resolution 2D-sparse defect/inhomogeneity map is obtained. The main focus of the investigation is set on the influence of the number of individual measurements on the achievable reconstruction quality. Using numerical simulations based on an analytical representation of the forward solution to the underlying inverse problem, the convergence rate over performed measurements of the achievable reconstruction quality is determined. Finally, all findings are experimentally validated by reconstructing a set of internal defects in an additively manufactured sample. In this work, it is shown that for a variety of different defect separation distances, the projection of 50 different pixel patterns allows for a good trade-off between experimental complexity and reconstruction quality.
It can be difficult to efficiently model ultrasonic waves in 3D structures, especially when the computational model needs to account for complex geometries. This contribution presents a solution based on the Scaled Boundary Finite Element Method (SBFEM). It is a numerical tool suitable for elastodynamic problems. A space-tree discretisation, namely quad-trees, is used. This technique allows the decomposition of an image into quadrilaterals or quads, which are extruded to generate the 3D plate geometry. In particular, small quads resolve regions with discontinuities, allowing them to represent fine details in the structure. Moreover, this meshing technique allows for exploiting cell similarities, making the calculation procedure more efficient. The space-tree discretisations are generated from a high-resolution image containing all the information about damaged regions or boundary conditions. The resulting SBFEM polyhedral domains employ transition elements to ensure correct coupling between cells of different sizes. The analytical solution of a cylindrical scatterer serves as a reference to validate the proposed approach. Other examples also demonstrate the validity of the methodology and its flexibility.
Functionally graded porous scaffolds (FGPS) constructed with pores of different size arranged as spatially continuous structure based on sheet-based gyroid with three different scaling factors of 0.05, 0.1 and 0.2 were produced by electron beam powder bed fusion. The pore dimensions of the obtained scaffolds satisfy the values required for optimal bone tissue ingrowth. Agglomerates of residual powder were found inside all structures, which required post-manufacturing treatment. Using X-ray Computed Tomography powder agglomerations were visualized and average wall thickness, wall-to-wall distances, micro- and macro-porosities were evaluated. The initial cleaning by powder recovery system (PRS) was insufficient for complete powder removal. Additional treatment by dry ultrasonic vibration (USV) was applied and was found successful for gyroids with the scaling factors of 0.05 and 0.1. Mechanical properties of the samples, including quasi-elastic gradients and first maximum compressive strengths of the structures before and after USV were evaluated to prove that additional treatment does not produce structural damage. The estimated quasi-elastic gradients for gyroids with different scaling factors lie in a range between 2.5 and 2.9 GPa, while the first maximum compressive strength vary from 52.5 for to 59.8 MPa, compressive offset stress vary from 46.2 for to 53.2 MPa.
In this study, we present an enhanced deep learning framework for the prediction of porosity based on thermographic in-situ monitoring data of laser powder bed fusion processes. The manufacturing of two cuboid specimens from Haynes 282 (Ni-based alloy) powder was monitored by a short-wave infrared camera. We use thermogram feature data and x-ray computed tomography data to train a convolutional neural network classifier. The classifier is used to perform a multi-class prediction of the spatially resolved porosity level in small sub-volumes of the specimen bulk.
In this study, we present an enhanced deep learning framework for the prediction of porosity based on thermographic in-situ monitoring data of laser powder bed fusion processes. The manufacturing of two cuboid specimens from Haynes 282 (Ni-based alloy) powder was monitored by a short-wave infrared camera. We use thermogram feature data and x-ray computed tomography data to train a convolutional neural network classifier. The classifier is used to perform a multi-class prediction of the spatially resolved porosity level in small sub-volumes of the specimen bulk.
Robot-assisted laser thermography for surface breaking crack detection on complex shaped components
(2023)
Laser thermography using a focused (spot or line) beam has proved to be effective for detection of surface breaking cracks on planar samples. In this work, we use the same principle, but applied to complex shaped components, like a rail cross-section, a gear, and a gas turbine blade. We use a six-axis robot to move the sample in-front of our thermographic setup. Several scanning-path and thermographic parameters are explored: scanning speed, density of points in each scanning slice, laser power, camera framerate. Additionally, we explore semi-automatic evaluation algorithms for crack detection, as well as 2D-to-3D registration of the found indications.
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.
This data set contains three different data types obtained from concrete specimens. For each specimen, the rebound numbers, ultrasonic data (ultrasonic velocity, time of flight), and destructive concrete strength are given. Two kind of specimen geometries were tested: cubes and drilled cores. The files are labeled according to the specimen geometry as "cube" or "core" and the type of measurement data as "compressive_strength", "rn_R" and "rn_Q" for rebound numbers as well as "us" for ultrasonic data. The ultrasonic data were generated by six independent laboratories, the rebound numbers by five independent laboratories and the destructive tests by one laboratory. The designation of each specimen establishes the relationship between the different data types.
We propose a novel iterative segmentation algorithm (i.S.Sy.Da.T.A: Iterative Segmentation Synthetic Data Training Algorithm) employing Deep Convolutional Neural Networks and synthetic training data for X-ray tomographic reconstructions of complex microstructures. In our method, we reinforce the synthetic training data with experimental XCT datasets that were automatically segmented in the previous iteration. This strategy produces better segmentations in successive iterations. We test our algorithm with experimental XCT re constructions of a 6-phase Al-Si Matrix Composite reinforced with ceramic fibers and particles. We perform the analysis in 3D with a special network architecture that demonstrates good generalization with synthetic training data. We show that our iterative algorithm returns better segmentations compared to the standard single training approach. More specifically, phases possessing similar attenuation coefficients can be better segmented: for Al2O3 fibers, SiC particles, and Intermetallics, we see an increase of the Dice score with respect to the classic approach: from 0.49 to 0.54, from 0.66 to 0.72, and from 0.55 to 0.66 respectively. Furthermore, the overall Dice score increases from 0.77 to 0.79. The methods presented in this work are also applicable to other materials and imaging techniques.
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.
The microstructure of an apatite-wollastonite (code name AP40) glass-ceramic is analyzed in this study by combining 2D microscopy, phase analysis, X-ray absorption and synchrotron X-ray refraction computed tomography (XCT and SXRCT, respectively). It is shown that this combination provides a useful toolbox to characterize the global microstructure in a wide scale range, from sub-micrometer to millimeter. The material displays a complex microstructure comprising a glassy matrix with embedded fluorapatite and wollastonite small crystals. In this matrix, large (up to 200 μm) spike-shaped structures are distributed. Such microstructural features are oriented around a central sphere, thereby forming a structure resembling a sea urchin. A unique feature of SXRCT, in contrast to XCT, is that internal interfaces are visualized; this allows one to show the 3D distribution of these urchins with exceptionally good contrast. Furthermore, it is revealed that the spike-shaped structures are not single crystals, but rather composed of sub-micrometric crystals, which are identified as fluorapatite and diopside phases by SEM-EDX analysis.
This contribution attempts to shed light on the application of POD analyses and measurement uncertainty calculations in nondestructive testing of concrete structures to provide useful and quality-assured information for reliability assessments of our built environment - with an emphasis on ground penetrating radar. It is shown that signal processing techniques affect POD analysis results to varying degrees, that measurement uncertainties are useful to validate PODs, and that the utilization of both POD analysis and measurement uncertainty calculations can pave the way to NDT-based reliability assessment, which will be exemplarily demonstrated in conclusion – generally aiming to derive those maintenance strategies and actions that are in line with actual demands.
Klebeverbindungen sind aus vielen Anwendungen wie dem Leichtbau nicht mehr wegzudenken. Durch die Verklebung gleicher oder ungleicher Materialien entstehen viele Vorteile gegenüber konservativen Fügeverfahren. Jedoch stellen schwache Haftfestigkeiten eine sehr unbeliebte Fehlerart dar, die schlecht zu detektieren sind und zu einem frühzeitigen Versagen der Verklebung bei vergleichsweise geringen Belastungen führen können. Aufgrund hoher Sicherheits- und Qualitätsansprüche wird die Haftfestigkeit dieser Verbindungen jedoch noch immer zerstörend geprüft. Zufriedenstellende zerstörungsfreie Verfahren, um Haftfestigkeiten zu prüfen, sind nicht vorhanden und Thema gegenwärtiger Forschung. Ein Ansatz, der in diesem Projekt verfolgt wird, liegt in der Verwendung geführter Ultraschallwellen.
Hierzu wird anhand von Simulationen mittels der Scaled Boundary Finite Element Methode gezeigt, dass die gezielte Auswertung bestimmter Bereiche des Dispersionsdiagrams, den sogenannten vermiedenen Kreuzungen (engl. mode repulsion regions), eine Charakterisierung der Haftfestigkeiten zulassen könnten. Dies liegt darin begründet, dass die mittleren mechanischen Belastungen der Kleberschicht in diesen Bereichen ein lokales Maximum aufweisen und daher eine erhöhte Sensitivität auf Materialänderungen haben. Es wird gezeigt, wie sensitiv diese Bereiche auf Materialänderungen in der Klebergrenzschicht sind und welche potenziellen Fehlergrößen existieren.
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).
For how trivial or provocative it can sound, the best neutron spectrometer in the world does not produce science and technology by itself. By definition of “Materials Science”, neutron scattering data on engineering materials must be used as a tool to understand, and even tailor, materials performance. In order for this to happen, neutron data need to be
1. Acquired under the most relevant condition possible
2. Coupled to other experimental techniques
3. Capitalized by means of proper simulations and data analysis
Point 1- calls for an intense use and the development of top-notch of in-situ techniques; Point 2- means that the sole use of neutron data will not lead to any solution of a global problem; All points above hint to the fact that access to neutron sources is not routine, and therefore it is imperative to search ways to make neutron data rentable and sustainable for the material science and industrial research community.
In this presentation, and based on two examples, we will show a couple of strategies to combine neutron data with other experiments, and with theoretical models to raise the validity of experiments to the level of problem-solving. As one might imagine, these are only a few among the almost infinite combinations possible to help improving material properties, performance, and safety, i.e., ripe for everyday use.
In plate-like structures, ultrasonic waves propagate as Lamb waves. Their use is important for many applications from non-destructive testing to structural health monitoring. Efficient simulation tools contribute to a significant value add e.g. in designing systems for these applications. Under which conditions an acceptable accuracy of these models with affordable computational costs can be achieved is an open question. Many of these applications include the usage of a plane wavefront, simulated in 2D crossesctional models to reduce complexity. In this contribution, a comparative case study between simulations and experiments is presented. The aim is to verify and compare a 2D cross-sectional model with experimental data. The experimental setup for this case study consists of an aluminum plate. A rectangular piezoelectric transducer is mounted for guided wave excitation. A laser Doppler vibrometer (LDV) measures out-of-plane velocities on the plate. A 2D cross-sectional model based on the Scaled Boundary Finite Element Method (SBFEM) is used to simulate the wave propagation of the experimental setup. The first data points near the transducer are used to fit the excitation tractions of the model, while additional points further away from the source are used to validate the model. The comparison between the recorded measurements and the simulated velocities shows a high degree of compatibility.
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.
Laser-induced breakdown spectroscopy (LIBS) is a spectroscopic method for detecting the chemical composition of optically accessible surfaces. In principle, the measurement of all elements of the periodic table is possible. System calibrations allow the quantification of element concentrations. In combination with scanner systems, the two-dimensional element distribution can be determined. Even rough surfaces can be measured by online adjustment of the laser focus. To detect element ingress into the concrete, typically cores are taken, cut in half, and LIBS measurements are performed on the cross-section. The high spatial resolution as well as the simultaneous multi-element analysis enables a separate evaluation of the binder-matrix and aggregates. Therefore, the element concentrations can be determined directly related to the cement paste. LIBS measurements are applicable in the laboratory, on-site and also over a distance of several meters.
Common applications include the investigation of material deterioration due to the ingress of harmful ions and their interaction in porous building materials. LIBS is able to provide precise input parameters for simulation and modelling of the remaining lifetime of a structure. Besides the identification of materials, also their composition can be determined on hardened concrete, such as the type of cement or type of aggregate. This also involves the identification of environmentally hazardous elements contained in concrete. Another possible application is the detection of the composition of material flows during dismantling. Non-contact NDT for “difficult to assess” structures as an example application through safety glass or in combination with robotics and automation are also possible.
This work presents the state of the art concerning LIBS investigations on concrete by showing exemplary laboratory and on-site applications.
Laser-induced breakdown spectroscopy (LIBS) is a spectroscopic method for the analysis of the chemical composition of sample materials. Generally, the measurement of all elements of the periodic table is possible. In particular, light elements such as H, Li, Be, S, C, O, N and halogens can be measured. Calibration with matrix-matching standards allows the quantification of element concentrations. In combination with scanner systems, the two-dimensional element distribution can be determined. Even rough surfaces can be measured by online adjustment of the laser focus. LIBS can also be used on-site with mobile systems. Hand-held systems are available for point measurements.
Common applications include the investigation of material deterioration due to the ingress of harmful ions and their interaction in porous building materials. Due to the high spatial resolution of LIBS and the consideration of the heterogeneity of concrete, the determination of precise input parameters for simulation and modelling of the remaining lifetime of a structure is possible. In addition to the identification of materials, it is also possible to assess the composition for example of hardened concrete, which involves the cement or aggregate type used. Other important fields of application are the detection of environmentally hazardous elements or the material classification for sorting heterogeneous material waste streams during dismantling. Non-contact NDT for “difficult to assess” structures as an example application through safety glass or in combination with robotics and automation are also possible.
In this work, an overview of LIBS investigations on concrete is given based on exemplary laboratory and on-site applications.
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.
The rails of modern railways face an enormous wear and tear from ever increasing train speeds and loads. This necessitates diligent non-destructive testing for defects of the entire railway system.
Non-destructive testing of rail tracks is carried out by rail inspection trains equipped with ultrasonic and eddy current test devices. However, the evaluation of the gathered data is mainly done manually with a strong focus on ultrasonic data, and defects are checked on-site using hand-held testing equipment. Maintenance measures are derived based on these on-site findings.
The aim of the AIFRI project (Artificial Intelligence For Rail Inspection) is to
- increase the degree of automation of the inspection process, from the evaluation of the data to the planning of maintenance measures,
- increase the accuracy of defect detection,
- automatically classify detected indications into risk classes.
These aims will be achieved by training a neural network for defect detection and classification. Since the current testing data is unbalanced, insufficiently labeled and largely unverified we will supplement fused, simulated eddy current and ultrasonic testing data in form of a configurable digital twin.
This dataset contains raw data acquired in ultrasound measurements on a reference specimen made of concrete at Bundesanstalt für Materialforschung und -prüfung (BAM), Berlin (Germany). The internal specimen identifier is “Pk050”. The measurements were conducted using the pulse-echo method. The upper surface of the specimen was defined as measuring area. The aim of the measurements is to determine the geometrical dimensions (thickness) of the specimen “Pk050”. In addition to this, a dataset of a second specimen with identifier “Pk266” has been acquired. Pk266 has the same geometrical dimensions and concrete recipe as Pk050, but contains tendons [Reference: https://doi.org/10.7910/DVN/NUU0WZ].
This dataset contains raw data acquired in ultrasound measurements on a reference specimen made of concrete at Bundesanstalt für Materialforschung und -prüfung (BAM), Berlin (Germany). The internal specimen identifier is “Pk266”. The measurements were conducted using the pulse-echo method. The upper surface of the specimen was defined as measuring area. The aim of the measurements is to determine both the geometrical dimensions (thickness) and the position of tendons to the measuring area. In addition to this, a second dataset of a second specimen with identifier is existing named “Pk050” has been acquired. Pk050 has the same geometrical dimensions and concrete recipe as Pk266 recipe but does not contain tendons [Reference: https://doi.org/10.7910/DVN/9EID5D].
"This data set contains three different data types obtained from concrete specimens. For each specimen, the rebound numbers, ultrasonic data (ultrasonic velocity, time of flight), and destructive concrete strength are given. Two kind of specimen geometries were tested: cubes and drilled cores. The files are labeled according to the specimen geometry as "cube" or "core" and the type of measurement data as "compressive_strength", "rn_R" and "rn_Q" for rebound numbers as well as "us" for ultrasonic data. The ultrasonic data were generated by six independent laboratories, the rebound numbers by five independent laboratories and the destructive tests by one laboratory. The designation of each specimen establishes the relationship between the different data types."
Non-destructive testing of rail tracks is carried out by using rail inspection cars equipped with ultrasonic and eddy current measurement. The evaluation of test data is mainly done manually, supported by a software tool which pre-selects relevant indications shown to the evaluators. The resulting indications have to be checked on-site using hand-held testing equipment. Maintenance interventions are then derived on the basis of these on-site findings.
Overall aim of the AIFRI (Artificial Intelligence For Rail Inspection) project - funded by the German Federal Ministry of Digital and Transport (BMDV) as part of the mFUND programme under funding code 19FS2014 – is to increase the degree of automation of the inspection process from the evaluation of the data to the planning of maintenance interventions. The accuracy of defect detection shall be increased by applying AI methods in order to enable an automated classification of detected indications into risk classes. For this purpose, data from both eddy current inspections and ultrasonic inspections will be used in combination.
Within the framework of this data-driven project, relevant defect patterns and artefacts present in the rail are analysed and implemented into a configurable digital twin. With the help of this digital twin virtual defects can be generated and used to train AI algorithms for detection and classification. With the help of reliability assessment trained AI algorithms will be evaluated with regard to the resulting quality in defect detection and characterisation.
A particular aspect of the development of AI methods is the data fusion of different NDT data sources: Thereby, synergies are used that arise from linking eddy current and ultrasonic inspection data in a combined model.
In the course of the project a demonstrator consisting of the developed IT-tool and an asset management system will be implemented and tested in the field using real-world data.
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.
X-ray refraction is analogous to visible light deflection by matter; it occurs at boundaries between different media. The main difference between visible light and X-rays is that in the latter case deflection angles are very small, from a few seconds to a few minutes of arc (i.e., the refraction index n is near to 1). Trivially but importantly, deflection of X-rays is also sensitive to the orientation of the object boundaries. These features make X-ray refraction techniques extremely suitable to a) detect defects such as pores and microcracks and quantify their densities in bulk (not too heavy) materials, and b) evaluate porosity and particle properties such as orientation, size, and spatial distribution (by mapping). While X-ray refraction techniques cannot in general image single defects, their detectability is simply limited by the wavelength of the radiation.
We thereby show the application of X-ray refraction 2D mapping (topography) and tomography to different sorts of problems in materials science and technology: 1) Sintering of SiC green bodies; 2) Porosity analysis in additively manufactured alloys; 3) Fiber de-bonding in metal and polymer matrix composites.
Such techniques, especially at the Synchrotron BESSY II, Berlin, Germany, can be used in-situ, i.e. when the specimen is subjected to temperatures or external loads. Applications of in-situ X-ray refraction radiography on aluminum alloys and composites are also shown.
The use of X-ray refraction analysis yields quantitative information, which can be directly input in kinetics, mechanical and damage models.
Vortrag über die Berechnung von Messunsicherheiten und die POD-Analyse zur Aufbereitung von ZfP-Ergebnissen für die Zuverlässigkeitsbewertung bestehender Bauwerke.
Structural health monitoring techniques associate strongly with damage detection and characterization. Ultrasonic guided waves (UGW), for such scope, arise as one of the most promising methods for many reasons i.e. UGW are able to travel long distances and they have high sensitivity to damage. In this context, the necessity to model realistic wave-defect interaction occurs to be critical.
Realistic damage scenarios can be modeled through the usage of image-based quadtree meshes. Images, such as the outcome from X-ray scans, C-scans, etc., can be converted into meshes for further integration in a computational domain. Quadtree meshes are created by converting the intensity of the pixels to quadrilateral cells. Homogeneous regions inside one image result in one quad, whereas fine features such as discontinuities can be described with smaller quads.
This contribution proposes an efficient methodology to model wave defect interaction, using as a framework the scaled boundary finite element method (SBFEM) and quadtree meshes. Problems as non-conforming regions in the mesh due to the space tree decomposition can be easily avoided using SBFEM’s polygonal elements. Moreover, the semi-analytical nature of the SBFEM allows the modeling of arbitrarily long prismatic/undamaged regions of the waveguides without an increase in the computational burden.
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 %.
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 m), 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.
Concrete structures experience severe damage during service, for example due to pitting corrosion of rebars caused by the ingress of chlorine (Cl) into the porous concrete structure. The ingress can be monitored using laser-induced breakdown spectroscopy (LIBS), a recently introduced civil engineering technique used to detect Cl in concrete structures in addition to conventional wet chemistry methods. The key advantages of LIBS are high spatial resolution, which is important when analyzing heterogeneous concrete samples, as well as the almost complete absence of sample preparation. To assess LIBS as a reliable analytical method, its accuracy and robustness must be carefully tested. This paper presents the results of an interlaboratory comparison on the analysis of Cl in cement paste samples conducted by 12 laboratories in 10 countries. Two sets of samples were prepared with Cl content ranging from 0.06 to 1.95 wt% in the training set and 0.23–1.51 wt% in the test set, with additional variations in the type of cement and Cl source (salt type). The overall result shows that LIBS is suitable for the quantification of the studied samples: the average relative error was generally below 15%. The results demonstrate the true status quo of the LIBS method for this type of analysis, given that the laboratories were not instructed on how to perform the analysis or how to process the data.
This thesis investigates ultrasonic guided waves (GW) in multi-layered plates with the focus on higher order modes. The aim is to develop techniques for hybrid structures such as of adhesive bonds and composite pressure vessels (COPV) which are widely used in automotive and aerospace industries and are still challenging to inspect non-destructively. To be able to analyse GW, numerical methods and precise material properties are required. For this purpose, an efficient semi-analytical approach, the Scaled Boundary Finite Element Method, is used. The material properties are inferred by a GW-based optimisation procedure and a sensitivity study is performed to demonstrate the influence of properties on GW. Then, an interesting feature, called mode repulsion, is investigated with respect to weak and strong adhesive bonds. The results show that the coupling between two layers influences the distance between coupled modes in a mode repulsion region, thus allowing for the characterisation of adhesive bonds. At next, wave-damage interaction is studied in the hybrid structure as of the COPV. Results show that the wave energy can be concentrated in a certain layer enabling damage localisation within different layers. Further investigations are carried out on the hybrid plate with an impact-induced damage. Two well-known wavenumber mapping techniques, which allow to quantify the damage in three dimensions, are implemented and their comparison is done for the first time.
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.
The overview of the activity of Federal Institute for Material Research and Testing (BAM, Belin, Germany) in the field of additively manufacturing material characterization will be presented. The research of our group is focused on the 3D imaging of AM materials by means of X-ray Computed Tomography at the lab and at synchrotron, and the residual stress characterization by diffraction (nondestructive technique).
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.
Decades of non-destructive evaluation (NDE) for the quality assurance of concrete bridges revealed the necessity of developing procedures for building reference specimens for different defects. External objects have been widely used in specimen construction to represent defects. However, embedded materials can alter the actual defect characteristics, interrupting the NDE responses. This study proposes new approaches to fabricating reference specimens for reinforced concrete that feature substantial defects, including cracks, delamination, honeycombing and rebar corrosion, without external objects. As a result, realistic responses can be acquired to identify promising NDE methods for characterising actual deteriorations. The procedures were produced with the intent of being reproducible in any laboratory. Destructive and non-destructive testing methods were performed to verify the effectiveness of the processes in creating defects. This study provides research laboratories with techniques for
fabricating reference specimens for characterising defects and assessing the performance of NDE technologies.