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The combination of microstructural data with other experimental techniques and with modeling is paramount, if we want to extract the maximum amount of information on porous material properties. In particular, quantitative image analysis, statistical approaches, direct discretization of tomographic reconstructions represent concrete possibilities to extend the power of the tomographic 3D representation to insights into the material and component performance. I will show a few examples of possible use of X-ray tomographic data for quantitative assessment of porosity in ceramics.
Moreover, I will show how not-so-novel 2D characterization techniques, based X-ray refraction, can allow a great deal of insights in the damage evolution in microcracked (and porous) ceramics. I will show how X-ray refraction can detect objects (e.g. microcracks) below its own spatial resolution.
Finally, I will discuss the link between the microstructural findings and the mechanical properties of porous microcracked ceramics.
The combination of microstructural data with other experimental techniques and with modeling is paramount, if we want to extract the maximum amount of information on porous material properties. In particular, quantitative image analysis, statistical approaches, direct discretization of tomographic reconstructions represent concrete possibilities to extend the power of the tomographic 3D representation to insights into the material and component performance. I will show a few examples of possible use of X-ray tomographic data for quantitative assessment of porosity in ceramics.
Moreover, I will show how not-so-novel 2D characterization techniques, based X-ray refraction, can allow a great deal of insights in the damage evolution in microcracked (and porous) ceramics. I will show how X-ray refraction can detect objects (e.g. microcracks) below its own spatial resolution.
Finally, I will discuss the link between the microstructural findings and the mechanical properties of porous microcracked ceramics.
Thermographic super resolution techniques allow the spatial resolution of defects/inhomogeneities below the classical limit, which is governed by the diffusion properties of thermal wave propagation. In this work, we re-port on the extension of this approach towards a full frame 2D super resolution technique. The approach is based on a repeated spatially structured heating using high power lasers. In a second post-processing step, several measurements are coherently combined using mathematical optimization and taking advantage of the (joint) sparsity of the defects in the sample.
Additive Manufacturing (AM) in terms of laser powder-bed fusion (L-PBF) offers new prospects regarding the design of parts and enables therefore the production of complex structures. The quality of the feedstock material receives increasing attention, as it depicts the first part of the L-PBF process chain. The powder quality control in terms of flowability and powder bed packing density is therefore mandatory.
In this work, a workflow for quantitative 3D powder analysis in terms of particle size, particle shape, particle porosity, inter-particle distance and packing density was established. Synchrotron computed tomography (CT) was used to correlate the packing density with the particle size and particle shape for three different powder batches. The polydisperse particle size distribution (PSD) was transformed into a statistically equivalent bidisperse PSD. The ratio of the small and large particles helped to understand the powder particle packing density. While the particle shape had a neglectable influence, the particle size distribution was identified as major contributor for the packing density.
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).
Metal Additive Manufacturing (AM) technologies such as Laser Powder Bed Fusion (LPBF) are characterized by layer wise construction, which enable advancements of component design, leading to potential efficiency and performance improvements. However, the rapid cooling rates associated with the process consequently leads to the generation of high magnitude residual stresses (RS). Therefore, a deep understanding of the formation of RS, the influence of process parameters on their magnitude and the impact on mechanical performance is crucial for widespread application. The experimental characterization of these RS is essential for safety related engineering application and supporting the development of reliable numerical models. Diffraction-based methods for RS analysis using high energy synchrotron X-rays and neutrons enable non-destructive spatially resolved characterization of both surface and bulk residual stresses in complex components. This presentation will provide an overview of recent research conducted by the BAM at large scale facilities for the characterization of residual stresses in LPBF metallic alloys. Special focus will be given to the challenges posed by textured LPBF materials for the reliable choice of the diffraction elastic constants (DECs), which is crucial to the accurate calculation of the level of RS.
The focus of the presentation focus will be on 3D imaging by means of X-ray Computed Tomography (XCT) at the lab and at synchrotron, and the non-destructive residual stress (RS) characterization by diffraction of additively manufactured (AM) materials in BAM (Berlin, Germany). The manufacturing defects and high RS are inherent of AM techniques and affect structural integrity of the components. Using XCT the defects size and shape distribution as well as geometrical deviations can be characterized, allowing the further optimization of the manufacturing process. Diffraction-based RS analysis methods using neutron and synchrotron X-rays at large scale facilities offer the possibility to non-destructively spatially resolve both surface and bulk RS in complex components and track their changes following applied thermal or mechanical loads.
The overview of the activity of group 8.5 Micro-NDT (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).
Absorption edge tomography, also known as differential tomography at absorption edges, is a method which exploits the sudden change of the attenuation coefficient, when the photon energy crosses the absorption edge of an element. Synchrotron radiation is the best source for absorption edge tomography, because of its small bandwidth, high intensity and easily adjustable photon energy. The synchrotron beamline BAMline at the synchrotron radiation facility BESSY II in Berlin, which is operated by the Bundesanstalt für Materialforschung und -prüfung (BAM), provides a monochromatized beam in a photon energy range from 5 keV up to 80 keV with a bandwidth of 2%, when the double multilayer monochromator is used. Together with the microtomography setup, this enables differential tomography with submicron resolution at the K edge of the elements from chromium up to the lanthanides, and up to uranium, when the L edges are used as well.
In this work, metal organic frameworks (MOFs) embedded in polymer are characterized using differential tomography. MOFs are microporous structures of metal ions, coordinated by organic linker molecules, that can be used in a broad field of applications, especially in gas storage and catalysis. In this work, polymer embedded MOFs were extruded into filaments, which could be used for 3d-printing to profit from the specific properties of the MOFs in polymeric materials combined with the arbitrary shapes provided by 3d-printing. For the extrusion, different polymer classes like ABS, polyester- and polyetherurethanes, as well as different MOFs (ZIF-8, ZIF-67, HKUST-1) were used to create MOF containing filaments with a nominal diameter of 3.0 mm. Differential tomography at the edges of the Zn, Co, and Cu was then used to find the distribution of the corresponding MOF in the filament and to analyze the shape of the inclusions.
The Alpine Fault at the West Coast of the South Island (New Zealand) is a major plate boundary that is expected to rupture in the next 50 years, likely as a magnitude 8 earthquake. The Deep Fault Drilling Project (DFDP) aimed to deliver insight into the geological structure of this fault zone and its evolution by drilling and sampling the Alpine Fault at depth. Here we present results from a seismic survey around the DFDP-2 drill site in the Whataroa Valley where the drillhole almost reached the fault plane. This unique 3D seismic survey includes several 2D lines and a 3D array at the surface as well as borehole recordings. Within the borehole, the unique option to compare two measurement systems is used: conventional three-component borehole geophones and a fibre optic cable (heterodyne Distributed Vibration Sensing system (hDVS)). Both systems show coherent signals but only the hDVS system allowed a recording along the complete length of the borehole.
Despite the challenging conditions for seismic imaging within a glacial valley filled with sediments and steeply dipping valley flanks, several structures related to the valley itself as well as the tectonic fault system are imaged. The pre-processing of the seismic data also includes wavefield separation for the zero-offset borehole data. Seismic images are obtained by prestack depth migration approaches.
Within the glacial valley, particularly steep valley flanks are imaged directly and correlate well with results from the P-wave velocity model obtained by first arrival travel-time tomography. Additionally, a glacially over-deepened trough with nearly horizontally layered sediments is identified about 0.5 km south of the DFDP-2B borehole.
With regard to the expected Alpine fault zone, a set of several reflectors dipping 40-56° to the southeast are identified in a ~600 m wide zone between depths of 0.2 and 1.2 km that is interpreted to be the minimum extent of the damage zone. Different approaches image one distinct reflector dipping at 40°, which is interpreted to be the main Alpine Fault reflector. This reflector is only ~100 m ahead from the lower end of the borehole. At shallower depths (z<0.5 km), additional reflectors are identified as fault segments and generally have steeper dips up to 56°. About 1 km south of the drill site, a major fault is identified at a depth of 0.1-0.5 km that might be caused by the regional tectonics interacting with local valley structures. A good correlation is observed among the separate seismic data sets and with geological results such as the borehole stratigraphy and the expected surface trace of the fault.
In conclusion, several structural details of the fault zone and its environment are seismically imaged and show the complexity of the Alpine Fault at the Whataroa Valley. Thus, a detailed seismic characterization clarifies the subsurface structures, which is crucial to understand the transpressive fault’s tectonic processes.
The focus of the presentation focus will be on 3D imaging by means of X-ray Computed Tomography (XCT) at the lab and at synchrotron, and the non-destructive residual stress (RS) characterization by diffraction of different kind of materials in FB8.5 Micro-NDT BAM. For instance, the manufacturing defects and high RS are inherent of additively manufacturing techniques and affect structural integrity of the components. Using XCT the defects size and shape distribution as well as geometrical deviations can be characterized, allowing the further optimization of the manufacturing process. Diffraction-based RS analysis methods using neutron and synchrotron X-rays at large scale facilities offer the possibility to non-destructively spatially resolve both surface and bulk RS in complex components and track their changes following applied thermal or mechanical loads.
In general, wind turbines transform the kinetic energy of the wind into electric power. Thereby, the wind turbine blades are facing unsteady loads which are transferred to the hub to generate a rotation of the turbine’s axis. This brief introduction focuses on the aerodynamics of the blades and the corresponding loads. Starting with the basic flow field and loads of an airfoil, terms like stagnation point, boundary layer, Reynolds number, transition, and separation are introduced. For different geometries, lift and drag coefficient curves are discussed. Then, full wings will be considered, including their three-dimensional flow field due to wing tip vortices and crossflows. As a main source of increased loads, unsteady effects are explained in more detail such as gusts, tower passing, earth boundary layer crossing, free stream turbulences, yaw misalignment, etc. At the end, extra loads due to an oscillating free stream are introduced.
The simulation of ultrasonic waves in a linearly elastic body can be computationally intensive. The reason is the relatively short wavelength compared to the body size for high frequencies. One possible approach to counteract the high computational costs is to decompose the domain into small parts and strive for parallelization. The Mortar Method is a well-established approach for domain decomposition.
A rather new approach to discretize the emerging subdomains is the Scaled Boundary Finite Element Method. This semi-analytical method has many attractive properties. Some of these properties are listed subsequently. The grid consists of polygonal elements, which leaves much freedom in the meshing process. A variety of material distributions, including anisotropic materials, can be considered. High-order shape functions can be used for optimal convergence properties. The approach treats singularities at crack tips and corners analytically. Especially in the frequency domain, the Scaled Boundary Finite Element Method reduces the dimension of the approximation because only degrees of freedom which are associated with the boundary of a polygonal element are necessary. Those desirable properties make the method particularly suitable for calculating the dynamic responses in bodies with cracks, as it is essential for many non-destructive testing and structural health monitoring applications.
In this contribution, we present a combination of the Scaled Boundary Finite Element Method with the Mortar Method in two dimensions. The presentation starts with a theoretical overview of both approaches. Subsequently, numerical examples demonstrate the stability of the combination for the polygonal boundary of the elements. The numerical examples increase in complexity and are compared to results computed on non-divided domains with the Finite Element Method.
The Scaled Boundary Finite Element Method (SBFEM) for prismatic structures is an efficient method for the simulation of acoustic behavior. Hence a further development of the method is of great interest. The wave propagation can be calculated for isotropic and anisotropic materials in solids. As for many applications the acoustic behavior in fluids and the behavior in case of fluid-structure interaction (FSI) is subject of research, the implementation of a fluid model in SBFEM for prismatic structures is needed. In case of FSI the coupling between fluid and solid domains can be performed without additional effort when describing both domains in the same variables. Hence a displacement-based fluid description is used. As the discretized formulation leads to spurious modes, a penalty method to suppress the unphysical behavior is chosen. To validate the derived model a comparison with analytical solutions of purely fluid domains is made. As to verify that in case of FSI the model shows the right behavior, dispersion curves of water-filled pipes are calculated and compared to results obtained with Comsol.
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.
A paradigm shift in the description of creep in metals can only occur through multi-scale imaging
(2022)
The description of creep in metals has reached a high level of complexity; fine details are revealed by all sorts of characterization techniques and different theoretical models. However, to date virtually no fully microstructure-driven quantitative description of the phenomenon is available. This has brought to interesting inconsistencies; the classic description of (secondary) creep rests on the so-called power law, which however: a- has a pre-factor spanning over 10 orders of magnitude; b- has different reported exponents for the same material; c- has no explanation for the values of such exponents.
Recently, a novel description (the so-called Solid State Transformation Creep (SSTC) Model) has been proposed to tackle the problem under a different light. The model has two remarkable features: 1- it describes creep as the accumulation of elementary strains due to dislocation motion; 2- it predicates that creep is proceeding by the evolution of a fractal arrangement of dislocations. Such description, however, needs a great deal of corroborating evidence, and indeed, is still incomplete.
To date, we have been able to observe and somehow quantify the fractal arrangement of microstructures through Transmission Electron Microscopy (TEM), observe the accumulation of dislocations at grain boundaries by EBSD-KAM (Electron Back-Scattered Diffraction-Kernel Angular Misorientation) analysis, quantify the kinetic character (solid state transformation) of experimental creep curves, and estimate the sub-grain size of the fractal microstructure through X-ray refraction techniques. All pieces of the mosaic seem to yield a consistent picture: we seem being on the right path to reconstruct the whole elephant by probing single parts of it. What is still missing is the bond between the various scales of investigation.
Remote gas sensors like those based on the Tunable Diode Laser Absorption Spectroscopy (TDLAS) enable mobile robots to scan huge areas for gas concentrations in reasonable time and are therefore well suited for tasks such as gas emission surveillance and environmental monitoring.
A further advantage of remote sensors is that the gas distribution is not disturbed by the sensing platform itself if the measurements are carried out from a sufficient distance, which is particularly interesting when a rotary-wing platform is used.
Since there is no possibility to obtain ground truth measurements of gas distributions, simulations are used to develop and evaluate suitable olfaction algorithms.
For this purpose several models of in-situ gas sensors have been developed, but models of remote gas sensors are missing.
In this paper we present two novel 3D ray-tracer-based TDLAS sensor models. While the first model simplifies the laser beam as a line, the second model takes the conical shape of the beam into account.
Using a simulated gas plume, we compare the line model with the cone model in terms of accuracy and computational cost and show that the results generated by the cone model can differ significantly from those of the line model.
The propagation of ultrasonic waves in concrete is affected by its micro- and macro-structure, geometry and properties as well as external influences as stress, temperature or moisture. In addition, age and degradation have a strong influence. Therefore, Ultrasound has been used to monitor concrete samples and structures since decades. However, early applications using conventional techniques as time-of flight or changes in amplitudes have been limited to detect changes in a late stage close to serviceability or ultimate load states.
Around 2000, several new, more sensitive techniques adopted from geophysics or other field of material sciences have been introduced to research in ultrasonic monitoring of concrete. The most discussed methodologies are coda wave interferometry, a technique which allows to detect very subtle changes from repeated ultrasonic measurements. Nonlinear acoustic techniques help to identify e. g. cracks even in an inhomogeneous background. Both techniques can be combined.
This paper reviews methods and results achieved so far on the laboratory scale and with full scale models the directions for future research and application is given as well.
To date, there are only very few technologies available for the conversion of low temperature waste heat to electricity. In this talk, we first describe the principle of thermomagnetic generators. Then we focus on the impact of topology of the magnetic circuit within thermomagnetic generators. We demonstrate that the key operational parameters strongly depend on the genus, i.e. the number of holes within the magnetic circuit.
To date, there are only very few technologies available for the conversion of low temperature waste heat to electricity. In this talk, we first describe the principle of thermomagnetic generators. Then we focus on the impact of topology of the magnetic circuit within thermomagnetic generators. We demonstrate that the key operational parameters strongly depend on the genus, i.e. the number of holes within the magnetic circuit.
With 8% of man-made CO2 emissions, cement production is an important driver of the climate crisis. By using alkali-activated binders, part of the energy-intensive clinker production process can be dispensed. However, as numerous raw materials are involved in the manufacturing process here, the complexity of the materials increases by orders of magnitude. Finding a properly balanced binder formulation is like looking for a needle in a haystack. We have shown for the first time that artificial intelligence (AI)-based optimization of alkali-activated binder formulations can significantly accelerate research.
The "Sequential Learning App for Materials Discovery" (SLAMD) aims to accelerate practice transfer. With SLAMD, materials scientists have low-threshold access to AI through interactive and intuitive user interfaces. The value added by AI can be determined directly. For example, the CO2 emissions saved per ton of cement can be determined for each development cycle: the more efficient the AI optimization, the greater the savings.
Our material database already includes more than 120,000 data points of alternative binders and is constantly being expanded with new parameters. We are currently driving the enrichment of the data with a life cycle analysis of the building materials.
Based on a case study we show how intuitive access to AI can drive the adoption of techniques that make a real contribution to the development of resource-efficient and sustainable building materials of the future and make it easy to identify when classical experiments are more efficient.
Ultrasound measurements in concrete are a well-known technique in civil engineering and non-destructive testing. For consistent monitoring of a concrete structure, the common techniques, using external sensors can often not provide the appropriate degree of repeatability, as the surface of structures changes, and comparable coupling conditions cannot be guaranteed when a measurement is repeated after some time. By embedding ultrasound transducers in concrete, we aim to develop a strategy for long-term monitoring of infrastructure, especially bridges, as a supplement and extension to other techniques. Applying the so-called coda wave interferometry to these measurements we can detect subtle changes in the medium far beyond the resolution limit of traditional time of flight methods. A smart sensor layout enables cost-efficient sensing of the entire area of interest. Embedding the transducers might remove uncertainties like coupling or positioning changes, while other challenges remain. Temperature and moisture content influence the structure and the transducers. These drifts need to be recorded and removed and good coupling must be ensured while not being able to visually inspect the sensor. In a multidisciplinary research group funded by the German Research Foundation, we aim to solve these problems on the way towards an ultrasound monitoring system for reinforced concrete structures. In various experiments in the lab and field, we determine the influence of temperature variations on the measurements and the equipment. As the monitoring task is the detection of irreversible damages - not reversible changes - a smart system requires a smart way of discrimination between permanent damages and reversible changes. With the data collected in these experiments, we present an approach to an environmental correction to ultrasound data to avoid a misinterpretation of these environmental changes as damage indicators.
Monitoring of construction projects plays increasingly important role in the implementation of growing needs and requirements, especially in geologically difficult areas. This particularly concerns tunnelling and special civil engineering projects. The use of fiber optic sensors for structural health monitoring provides significant economic advantages regarding lower life-cycle costs of the civil infrastructure. We present our achievements in the development of distributed polymer optical fiber sensors based on Rayleigh and Brillouin scattering for early damage detection.
Acoustic Emission
(2018)
Das Phänomen Schallemission (eng. Acoustic Emission, AE) ist eine Begleiterscheinung bei aktiven Mechanismen und Prozessen wie sie in Werkstoffen auftreten, die einer Belastung durch Krafteinwirkung oder durch Änderung der Umgebungsbedingungen ausgesetzt sind. Plastische Verformung, Risswachstum, Korrosion oder der Übergang zu einer anderen Phase generieren u.a. transiente elastische Wellen, die sich im Werkstoff und an der Materialoberfläche ausbreiten. Auftretende Auslenkungen von wenigen hundert Pikometern sind mit piezo-elektrischen AE Sensoren detektierbar. Aufzeichnungsraten von bis zu 40 MHz ermöglichen dabei zeitliche Auflösungen von einigen Nano- bis Mikrosekunden. Die Dechiffrierung der detektierten Informationen ist für die Material- und Versagenscharakterisierung sowie für Anwendungen in der Struktur- oder Prozessüberwachung ein zentraler Forschungsschwerpunkt.
Nach einem kurzen Überblick zu den Grundlagen werden ausgewählte Ansätze der AE Methode vorgestellt und diskutiert:
1) AE Monitoring von Pipelines als Referenzmessung für die Entwicklung eines akustischen faseroptischen Monitorings (AGIFAMOR)
2) Schwellwertfreie AE Messung im 4-Punkt-Rohrbiegeprüfstand BAM_9.1 (AGIFAMOR)
3) Kombination von AE mit Röntgen-Mikrotomografie und die Anwendung der frequenzbasierten Mustererkennung ermöglichen eine Zuordnung von AE und Mechanismen (Ergebnisse aus dem SNSF Projekt Nr. 127'134, Baensch 2014, Diss. ETH No. 22372)
Acoustic emission and ultrasonic monitoring of a prestressed concrete bridge in its final years
(2021)
Many European bridges built in the 1950s, 60s and 70s must be re-placed in the next decade due to structural deficiencies, insufficient load capacity or other issues. However, the existing bridges must be used for another couple of years even if flaws and damages already have been detected.
In Germany, several prestressed concrete bridges have been instrumented with acoustic emission detection systems to detect wire breaks and to provide early warning signs before failure. To evaluate and interpret the consequences of wire breaks additional instrumentation and accompanying measures as finite element modeling are required.
At a bridge in southern Germany we have complemented such a system with active ultrasonic monitoring. Repeated ultrasonic measurements are evaluated with a very sensible algorithm called coda wave interferometry. This method, inspired by seismology, has been shown to deliver early warning signs in lab experiments. Large volumes of concrete can be monitored with a limited network of ultrasonic transducers. We will report on the installation, capabilities, and lim-itations as well as first results.
Typically, the near-eutectic Al-Si alloys consist of highly interconnected three-dimensional network of the eutectic Silicon (Si) and intermetallics embedded into Aluminium (Al) matrix. For further improvement of the mechanical properties of such alloys, often, one single ceramic reinforcement phase, e.g. silicon carbide (SiC) or aluminium oxide (Al2O3) in the form of fibres or particles is added. However, hybrid reinforcements (fibres and particles) can further improve wear resistance and fracture toughness, and additionally, reduce anisotropy of the material. The engineering of metal matrix composites (MMC) for specific application requirements benefits from a comprehensive knowledge of the failure behaviour. Therefore, damage evolution under compression was investigated on:
- pure near-eutectic AlSi12CuMgNi matrix alloy
- type I: matrix reinforced with random-planar oriented Al2O3 short fibres (15 vol.%)
- type II: matrix reinforced with random-planar oriented Al2O3 short fibres (7 vol.%) and additional SiC particles (15 vol.%)
The analysis of damage mechanism was carried out in two rather independent but complementary studies. First, selected sister samples of every material were exposed to quasi-static compression (traverse control). The compression tests were interrupted at different strain levels. Miniature cylinders with a diameter of 1mm were extracted from the pre-strained samples and investigated by synchrotron computed tomography (SX-µCT) with a spatial resolution of about 0.7 µm. For the pure matrix alloy, microcracks are confined to the intermetallic particles and to the eutectic Si, hence no damage was observed in the Aluminium. The composite type II revealed a more effective strain accumulation (less damage) than type I at low plastic strain (up to 5 %), but a more catastrophic damage development due to cracking of the SiC clusters at higher strain levels.
The second approach to study the damage initiation and accumulation in the materials subjected to compressive load was Acoustic Emission (AE) analysis. In this case the in-situ monitoring of the acoustic emission signal was performed during compression tests on specimens with dimension of several mm. For all three material types, AE activity set at 2% strain. Differences in AE behaviour of the three materials was proven based on AE hitrate, signal peak amplitudes as well as weighted peak frequencies (WPF). Future work focuses on combination of AE and SX-µCT aiming for more detailed knowledge on damage mechanism of metal matrix composites.
Acoustic emission testing
(2018)
Acoustic-structure interaction in the scaled boundary finite element method for primsatic geometries
(2019)
Due to the short wavelength compared to the dimensions of the structure, the simulation of ultrasonic waves is still a challenging task. A numerical method well suited for this purpose is the semi-analytical Scaled Boundary Finite Element Method (SBFEM). When applying this method, only the boundary of a computational domain is discretized using finite elements, while the interior is described by an analytical ansatz. Hence, the number of degrees of freedom is reduced significantly compared to the classical Finite Element Method (FEM).
In recent years, a particular formulation of the SBFEM for the simulation of ultrasonic guided waves was developed. The method constitutes an efficient algorithm for prismatic structures of arbitrary length, such as plates, pipes, or beams. Wave propagation phenomena in such structures can be modeled for isotropic and anisotropic inhomogeneous waveguides. Even though the method is an efficient tool for the simulation of guided waves in solid media, a reliable model for the simulation of acoustic wave propagation in fluids as well as acoustic-structure interaction in terms of SBFEM is still missing. In principle, the fluid can be described by a displacement-based formulation and thus be implemented in existing SBFEM algorithms for solid bodies. However, due to the discretization with classical finite elements, spurious modes occur, which cannot be separated from the physical modes straightforwardly. The spurious modes can be suppressed using a penalty parameter. Although very accurate results were achieved for some problems, this procedure has been proven unreliable for certain cases.
For this reason, we propose a different approach in this contribution. We employ a pressure model to simulate the acoustic behavior of fluids. The implementation of the pressure model results in a higher effort due to the necessity of incorporating coupling terms, but it presents a stable alternative without spurious modes. The accuracy of the method is demonstrated in comparison with analytical solutions and results obtained using the FEM.
Due to the multi-physical appearance of gas discharges the possibilities of interaction with their surrounding environment are very wide. Some of the most common applications are the surface or material modification and acting as an ion source for mass spectroscopy applications. Since atmosphere plasma generates a massive amount of thermal energy caused by collisions in the sheath, this temperature alternation is also able to produce acoustic waves in the ambient gas volume (as lightning and thunder), which is called thermoacoustic effect.
This talk presents an overview of the experimental acoustic analysis of surface dielectric barrier and micro hollow cathode discharges. Regarding other methods of acoustic excitation, the thermoacoustic approach benefits of its massless working principle and the proper impedance matching. In addition to the characterisation, possible applications (e.g. plasma acoustic loudspeaker or transducer for air-coupled ultrasonic testing) concerning these discharge types are presented.
Active IR thermography
(2018)
Active IR Thermography
(2019)
Active thermography with flash and halogen light excitation is used as a method for non-destructive testing of 3D-printed polymer components. Test specimens with artificial defects have been generated, using laser sintering and fused layer modeling. These test specimens have been investigated in different measurement configurations with both excitation methods. Afterwards, the different measurement conditions were compared regarding their capability to detect the defects. Furthermore, advanced analysis methods are used, to fully exploit the capabilities of these techniques.
Turbine blades for gas turbines are exposed to extreme working conditions in a demanding environment. In-service inspection, maintenance and refurbishment of the heavily stressed parts is necessary to ensure both safety and efficiency, e.g. based on immersion ultrasound testing (UT).
In the course of NDE 4.0, the European project MRO 2.0 aims to innovate the maintenance, repair and overhaul of turbine blades by linking these with modern digital methods. For this, the goal of this project is to go beyond conventional automated and manual UT testing techniques.
The aim is to measure the actual geometry and wall thickness of the complex shaped parts by applying an adaptive TFM that takes into account the refraction of the ultrasonic waves at the transition from the coupling material (water) to the inspected part (steel). In this setup the phased array probe is held by a robotic arm that allows the part to be scanned while remaining mainly perpendicular to the inspected surface. In this way, even complex geometries can be inspected and a 3D model of the actual condition of the part can be created.
The laboratory setup is equipped with a Vantage 64 phased array instrument from Verasonics Inc. and an industrial robot from ABB. A 64 element linear array probe operating at 10 MHz is attached to the robot.
The focus is on optimizing resolution, reliability and inspection speed, as the reconstructed model will be fed to the digital twin at a later stage of the project and used for targeted repairs. In addition to enhancing the reconstruction algorithms, required probe geometry and the parameters needed to inspect turbine blades with partially thin walls and anisotropic materials will also be investigated.
This talk will describe the 3-year project and present the results of the first year. The main focus will be on the development of the reconstruction algorithms used and the experimental setup.
Direct energy deposition additive manufacturing technologies that utilize an electric arc have great potential for generating large volume metal components. However, selecting process parameters that yield the desired near net shape design and requested mechanical component behavior is not a trivial task due to the complex relationship between all process parameters and material characteristics. This presentation exemplifies the application of a newly developed solid welding wire doped with TiB to enhance grain refinement in the deposited metal for additive manufacturing based on DED-Arc of high-strength precipitation hardening AlMgSi-aluminum alloys. It is worth noting that the solid wire is the result of our preliminary metallurgical studies on grain refinement in aluminum weld metal.
Consequently, research focuses on the correlation between process parameters and component quality to understand the underlying mechanisms. This is crucial for evaluating a robust process parameter space that yields component quality in line with corresponding standards which are mainly taken from welding technology.
Specifically, we examine component quality by analyzing pore size and distribution, as well as grain morphology. To enhance the mechanical properties of the deposited metal, a post-weld heat treatment was conducted, comprising of solution treatment, quenching, and artificial aging. The study also evaluates the effects of various heat treatment strategies on the final mechanical properties of the material.
To demonstrate the applicability of 3D metal printing of high-strength aluminium alloys, a more complex demonstrator was created. It has been shown that DED-Arc can produce high-volume aluminium parts with the same quality as the corresponding subtractive processing strategy.
Additionally, the entire additive manufacturing chain has been digitally integrated, enabling traceability of all relevant process steps, which is essential for reliable subsequent quality assessment.
Fatigue is one of the most prevalent issues, which directly influences the service life expectancy of concrete structures. Fatigue has been investigated for years for steel structures. However, recent findings suggest that concrete structures may also be significantly subjected to the fatigue phenomena that could lead to premature failure of certainfatigue prone structural elements. To date, fatigue of reinforced concrete has been given little focus. and Kknowledge on the influence factors and durability/capacity effects on this material should be improved. Current technological means to measure fatigue in civil structures like bridges and wind turbines (both onshore and offshore) are outdated, imprecise and inappropriate.
Meanwhile, this topic has got much more attention as dynamic loading on concrete structures plays an increasing role, e.g. in bridges with increasing traffic and heavier trucks, in wind energy production due to inherent vibrations e.g. in offshore wind turbine support structures affected by wind and waves.
The European Innovative Training Networks (ITN) Marie Skłodowska-Curie Actions project INFRASTAR (Innovation and Networking for Fatigue and Reliability Analysis of Structures - Training for Assessment of Risk) provides research training for 12 PhD students. The project aims to improve knowledge for optimizing the design of new structures as well as for more realistic verification of structural safety and more accurate prediction of the remaining fatigue lifetime of existing structures.
First, the INFRASTAR research framework is detailed. Then it will be exemplified through the presentation of the major results of the four PhD students involved in the work package dealing with auscultation and monitoring. This includes the development and improvement of Fiber Optics (FO) and Coda Wave Interferometry (CWI) for crack sizing and imagery, new sensor technologies and integration, information management, monitoring strategy for fatigue damage investigation and lifetime prediction.
This PhD project is part of the Marie Skłodowska-Curie International Training Network MUMMERING. The overarching goal of MUMMERING is the creation of a research tool that exploits the wealth of 3D imaging modalities applied in materials engineering.
The focus of this work is advanced reconstruction algorithms. The primary objective is the development and implementation of the DIRECTT algorithm. Due to restrictions introduced by the sample or the imaging setup during a measurement, it is not always possible to acquire data that fulfil the Nyquist sampling criterion. The DIRECTT algorithm is intended to produce reconstructions of superior quality for such cases of limited data sets, compared to those of other available algorithms, such as algebraic iterative ones. Although DIRECTT has been developed primarily for the reconstruction of volumes from data acquired by an X-ray Computed Tomography scanner, it can also be applied to the different modalities, such as laminography.
The talk describes the reconstruction principle of DIRECTT. Furthermore, reconstructions of measured data are presented and compared to reconstructions produced by other established algorithms.
Austenitic stainless steel welds as well as dissimilar metal welds with nickel alloy filler material, used in safety relevant parts of nuclear power plants, still challenge the ultrasonic inspection. The weld material forms large oriented grains which lead on the one hand to high sound scattering and on the other hand – to inhomogeneity and to the acoustic anisotropy of the weld structure. The ultrasonic wave fronts propagate not linearly, as in ferritic weld joints, but along the curves, which depend on the specific grain structure of the weld. Due the influence of these phenomena, it is difficult to analyze the inspection results and to classify the ultrasonic indications, which could be both from the weld geometry and from the material defects. A correct flaw sizing is not possible.
In an ongoing research project, different techniques to improve the reliability of ultrasonic testing at these kinds of welds are investigated. In a first step (in the previous research project) two ultrasonic inspection techniques were developed and validated on plane test specimens with artificial and realistic flaws. In the ongoing project, these techniques are applied to circumferential pipe welds with longitudinal and transverse flaws.
The technique developed at the Federal Institute for Materials Research and Testing (BAM) in Germany uses a combination of ray tracing and synthetic aperture focusing technique (SAFT). To investigate the unknown grain structure, the velocity distribution of weld-transmitting ultrasound waves is measured and used to model the weld by ray tracing.
The second technique, developed at the Fraunhofer Institute for Nondestructive Testing (IZFP) in Germany, uses Sampling Phased Array (Full Matrix Capture) combined with the reverse phase matching (RPM) and the gradient elastic constant descent algorithm (GECDM). This inspection method is able to estimate the elastic constants of the columnar grains in the weld and offers an improvement of the reliability of ultrasonic testing through the correction of the sound field distortion. The unknown inhomogeneity and anisotropy are investigated using a reference indication and the special optimization algorithm.
Both reconstruction techniques give quantitative inspection results and allow the defect sizing. They have been compared to conventional ultrasonic testing with techniques, which are state of the art for components in nuclear power plants. The improvement will be quantified by the comparison of the probability of detection (POD) of each technique.
Conventional ultrasonic testing involves the application of a fluid couplant for impedance matching. Increasing use of lightweight structures, composite materials and adhesive joints mostly in aerospace and automotive industry created an increasing interest in air-coupled ultrasonic testing methods, to protect sensitive surfaces and simplify maintenance. Commercially available air-coupled transducers consist of a piezocomposite material and matching layers to reduce the impedance mismatch between the transducer and air. This contribution is an overview of innovative approaches using new piezoelectric materials and other physical principles to transmit and receive an ultrasonic pulse in air.
Capacitive and piezoelectric micromachined ultrasonic transducers (CMUTs and PMUTs) produce high pressure levels, but they exhibit a very narrow bandwidth. Optical laser-based methods for transmitting and receiving ultrasound promise a higher bandwidth, but do not achieve the same sensitivity as conventional air-coupled transducers. Ferroelectrets are charged cellular polymers exhibiting piezoelectric properties, having a very small acoustic impedance well matched to air. Ferroelectret transducers achieve about the same bandwidth as the most broadband conventional air-coupled transducers, having a higher sensitivity. Thermoacoustic transducers use heat to initiate an acoustic wave, acting as transmitters in ultrasonic range. Thermoacoustic transducers enable excitation of extremely broadband pulses while producing high pressure levels, which opens new possibilities for advanced signal processing. The newest member of the family of air-coupled ultrasonic transmitters is the plasma-based transducer, using both the thermoacoustic effect and the movements of the ions (so called ionic wind) to create acoustic waves.
Recent years have seen extended use of ultrasonic techniques for concrete infrastructure assessement. They are applied for quality assurance and condition assessement at bridges, power plants, dams and other important objects. However, there are still a couple of significant limitations. They include, but are not limited to depth of penetration, imaging complex structures or early stage detections of distributed damage. The talk will give information on recent research in this area. Specifically, the application of the unique deep penetration system LAUS is shown. Ultrasonic monitoring using embedded transducers to check for subtle and sudden changes in the material is introduced as well. Comments on initiatives for validation, standardization and certification will be given.
AdvanCT Virtual CT
(2021)
Simulation becomes more and more important in modern CT imaging. It is increasingly used to optimize techniques for complex applications, and for educational purposes. Simulation can also be used for uncertainty estimation of dimensional CT measurements. The radiographic simulator aRTist is a modelling tool which simulates X-ray imaging using a hybrid analytical and Monte-Carlo method to efficiently model the radiation transport. In addition to the relevant physical effects such as absorption and scattering, simplified fast models are employed to describe the characteristics of the X-ray source and the detector. aRTist is well equipped to model realistic X-ray imaging setups due to the ability to load exported CAD object descriptions. By repetitive simulation runs aRTist can function as virtual CT device. A simple CT scan module is contained in aRTist which allows the simulation of standard (circular cone beam) scanning trajectories.
AdvanCT is a module for aRTist which allows to set up more complex scanning trajectories by attaching geometrical modification functions to the objects in the radiographic scene. In this way, advanced scanning modes can be realized. In addition to deterministic motion, also random variations can be introduced. By combining random variations with deterministic motion, non-ideal (realistic) CT scan geometries can be simulated, e.g. focal spot drift and mechanical instability of the axis of rotation. The AdvanCT module conveniently allows to construct these scenarios in a graphical interface and provides a preview before starting the (potentially long running) batch job. Therefore, deviations from ideal CT scan trajectories can be easily adjusted which is a necessary step towards uncertainty determination from simulation.
Laser powder bed fusion (LPBF) is an additive manufacturing process for materials which inherently tends to yield various degrees of metastable hierarchical microstructures, defects and high residual stresses in the as-built condition depending on the process parameters. The understanding of the evolution of these typical features during heat treatment and subsequent thermal and mechanical ageing is crucial for the wider acceptance for safety critical structures. A multi-disciplinary research project at BAM studying the development of the microstructure, defects, residual stresses typical of LPBF 316L and their evolution during thermal and mechanical ageing has led to insights into the stability of these inherent features. This presentation aims to give a broad overview of the project with a few specific cases of investigation. Firstly, the formation of residual stresses, the nature of the initial microstructure, the tensile properties and a modelling approach to understand the anisotropy will be presented. This will be followed by examples of studies of their evolution during heat treatment, long term thermal exposure, and room temperature and high temperature mechanical testing compared to a baseline of conventional wrought variant of the same alloy.
An overview of the BAM funed Focus Area Materials Project "AGIL" will be presented. AGIL focussed on the stdiy of the ageing characteristics of additively manufactured austenitic stainless steel with a "powder to mechanical failure" Approach. Recent Highlights are presented and a perspective for future studies.
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.
The necessity and demand for nondestructive testing of wood-based materials which can
automatically scan huge areas of wood is increasing. Air-coupled ultrasound (ACU) is used to detect defects and damage without altering the structure permanently. Using through transmission it is possible to detect even small holes and missing adhesive. If only one side of an object is accessible the reflection mode is preferred at the expense of a reduced resolution and penetration depth. Novel ferroelectret transducers with a high signal-to-noise ratio (SNR) enable a high-precision structure recognition. The transducers made of cellular polypropylene (PP) are quite suitable for ACU testing due to their extremely low Young’s modulus and low density which result in a favorable acoustic impedance for the transmission of ultrasonic waves between the transducer and air. Thus, defects such as delamination, rot, and cracks can be detected. Promising results were obtained under laboratory conditions with frequencies from 90 kHz to 200 kHz. The advantage of these ACU transducers is that they do not require contact to the sample, are accurate, and cost effective. Ultrasonic quality assurance for wood is an important attempt to increase the acceptance of wooden structures and towards sustainability in civil engineering in general.
Common air-coupled transducers for non-destructive testing consist of a piezocomposite material and several matching layers. Better acoustical matching to air is achieved by transducers based on charged cellular polypropylene (PP). This material has about hundred times lower acoustic impedance than any piezocomposite, having about the same piezoelectric coefficient. The piezoelectric properties of cellular PP are caused by the polarization of air cells. Alternatively, a ferroelectret receiver can be understood as a capacitive microphone with internal polarization creating permanent internal voltage. The sensitivity of the receiver can be increased by applying additional bias voltage. We present an ultrasonic receiver based on cellular PP including a high-voltage module providing bias voltage up to 2 kV. The application of bias voltage increased the signal by 12 to 15 dB with only 1 dB increase of the noise.
This receiver was combined with a cellular PP transmitter in through transmission to inspect several test specimens consisting of glass-fiber-reinforced polymer face sheets and a porous closed-cell PVC core. These test specimens were inspected before and after load. Fatigue cracks in the porous PVC core and some fatigue damage in the face sheets were detected. These test specimens were originally developed to emulate a rotor blade segment of a wind power plant. Similar composite materials are used in lightweight aircrafts for the general aviation. The other inspected test specimen was a composite consisted of glass-fiber-reinforced polymer face sheets and a wooden core. The structure of the wooden core could be detected only with cellular PP transducers, while commercial air-coupled transducers lacked the necessary sensitivity. Measured on a 4-mm thick carbon-fiber-reinforced polymer plate, cellular PP transducers with additional bias voltage achieved a 32 dB higher signal-to-noise ratio than commercial air-coupled transducers.