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To conduct a reliable, repeatable and accurate LIBS analysis, the optimization of the experimental setup is an important task. Hardware parameters of lasers and spectrometers used in the setup as well as additionally required components such as optics or process gas pipes must be carefully aligned and adjusted because factors like (i) focal conditions of the optics, (ii) alignment of the sample, (iii) process purge gas (types, flow rate) or (iv) measurement settings (integration time, accumulation of pulses) have a big impact on the signal quality. Therefore, in most cases the effect of different factors is evaluated empirically due to changing one factor at a time while keeping the overall configuration the same. In the end, the optimal configuration is selected based on the best parameters for each influencing factor. During optimization, a configuration of the experimental setup is aimed at, which allows e.g. the highest signal intensity or the lowest variation. In most cases, cross-correlation, interference and interaction among the various factors are not considered. For this reason, the possibilities of using Design of Experiment (DoE) to optimize a LIBS experiment will be shown and advantages of (i) reduction of testing plans using a feature space, (ii) identifying and considering cross-correlations and interactions, (iii) evaluating individual impacts on the measurement (e.g. contour and surface plots) as well as (iv) multivariate models for prediction of impacts will be presented.
This dataset contains raw data resulting from Impact-Echo measurements at the reference conrete block "Radarplatte", located at BAM (German Federal Institute for Materials Research and Testing). This specimen has been described in detail by Niederleithinger et al. (2021), who applied muon tomography, ultrasonic echo measurements, radar and X-ray laminography to visualize its internal structure.
The Impact-Echo method is based on the excitation of the zero-group-velocity frequency of the first symmetric Lamb mode of a plate-like structure, in order to assess its thickness. Numerous publication elaborate on Impact-Echo theory, examples are (Gibson and Popovics 2005, Schubert and Köhler 2008 , Abraham and Popovics 2010).
The measurements have been conducted using a setup that contains only commercially available components. The setup consists of an Olson CTG-2 concrete thickness gauge (Olsen Instruments, USA) for actuation and sensing and an 8-bit NI USB-5132 digital storage oscilloscope (National Instruments, USA) combined with the Echolyst software (Schweizerischer Verein für technische Inspektionen (SVTI), Switzerland) for data acquisition.
Measurements were conducted using a grid of 23x23 points with a spacing of 50 mm. At each point 8192 samples were recorded at a sampling rate of 1 MS/s.
The dataset contains the (X,Y) location in mm of the individual measurement points as well as the raw measurement data at those points.
The data is provided in the formats *.mir/*.mhdr (Echolyst), *.npy (Python) and *.mat (Matlab) and *.csv to ease the import in various post-processing tools.
Amorphous, porous materials represent by far the largest proportion of natural and men-made materials. Their pore networks consists of a wide range of pore sizes, including mesoand macropores. Within such a pore network, material moisture plays a crucial role in almost all transport processes. In the hygroscopic range, the pores are partially saturated and liquid water is only located at the pore fringe due to physisorption. Therefore, material parameters such as porosity or median pore diameter are inadequate to predict material moisture and moisture transport. To quantify the spatial distribution of material moisture, Hillerborg’s adsorption Theory is used to predict the water layer thickness for different pore geometries. This is done for all pore sizes, including those in the lower nanometre range. Based on this approach, it is shown that the material moisture is almost completely located in mesopores, although the pore network is highly dominated by macropores. Thus, mesopores are mainly responsible for the moisture storage capacity, while macropores determine the moisture transport capacity, of an amorphous material. Finally, an electrical analogical circuit is used as a model to predict the diffusion coefficient based on the pore-size distribution, including physisorption.
Digital Coplanar Translational Laminography (CTL) is a radiographic imaging technique that permits the visualization of structural details and discontinuities in the object of interest after 3D reconstruction from multiple projections. This technique becomes quite competitive regarding to computed tomography in situations of arrangements in which no complete rotation of the X-ray source - detector system around the object of interest is accessible or in cases where the part to be inspected has a high geometric asymmetry. The literature does not show many studies about image quality for different laminographic reconstructions and scan geometries.
Different methodologies for measuring the Modulation Transfer Function (MTF) as a key image quality parameter for the aforementioned technique are applied. The MTF was measured using different approaches, presampled MTF or sampled MTF, both based on the Fourier Transform-Magnitude Spectrum or the square wave
MTF using line pattern gauges. A sample known as Siemens Star with a converging line pattern was used to measure the circular square wave MTF. This circular MTF provides information on the direction dependent contrast transfer related to the measurement conditions, the reconstruction algorithms and the translational scan direction. For this purpose, several MTF measurements were performed in multiple angular directions. Beyond it, reconstructions were performed using different algorithms (Filtered Shifted Average) and an iterative one (MART – Multiplicative Algebraic Reconstruction Technique). Image quality analysis were done for both reconstruction methods. MART showed an image quality improvement for challenging conditions for laminographic arrangements, such as for a low number of projections (down to 25 for this study, considered as limited view, limited
angle reconstruction). Additionally, a Gadolinium gauge with parallel line patterns within a range from 10 μm to 1000 μm was used to compare the square wave MTF with the sine MTFs, measured by the different techniques mentioned above. The results show that the MTF techniques presented are equivalent in this study. The results obtained for this Gadolinium plate showed a good agreement between MTF10% and SRb image measurements. The methodology presented here is used for the characterization of the frequency dependent spatial resolution of measurements obtained from different laminographic reconstruction techniques and scan geometries. Finally, from the acquisitions and reconstructions obtained with the Siemens Star, cross laminographic images were calculated in order to improve the direction dependent sensitivity. The results showed a better detectability for cross laminographic images in comparison to unidirectional coplanar translational laminographic images covering dead zones.
The duraBASt area at the highway intersection “Köln-Ost” is a large test field for road testing.
It includes the duraBASt test bridge which is approximately 66 m long and 14.25 m broad. This bridge is part of the “road in the 21st Century” project and is equipped with several sensors for structural health monitoring. This feasibility study is carried out to investigate the prerequisites necessary for the constraction of intelligent bridges in the foture. Embedded sensors are able to measure quantities such as temperature, strain, moisture, corrosion, etc. In the presented work, the focus is set on passive RFID-based sensors. The communication and energy supply are realised by a mobile transmitter through the concrete cover. Hence, no cables or batteries are required. The sensors are designed to withstand the alkaline environment in concrete. Thus, moisture and corrosion values are measurable for several decades.
In the framework of non-destructive-testing advanced seismic imaging techniques have been applied to ultrasonic echo data in order to examine the integrity of an engineered test-barrier designed to be used for sealing an underground nuclear waste disposal site. Synthetic data as well as real multi-receiver ultrasonic data acquired at the test site were processed and imaged using Kirchhoff prestack depth migration reverse time migration (RTM). In general, both methods provide a good Image quality as demonstrated by various case studies, however deeper parts within the test barrier containing inclined reflectors were reconstructed more accurately by RTM. In particular, the image quality of a specific target reflector at a depth of 8 m in the test-barrier has been significantly improved compared to previous investigations using synthetic aperture Focusing technique, which justifies the considerable computing time of this method.
Air-coupled ultrasonic (ACU) testing has proven to be a valuable method for increasing the speed in non-destructive ultrasonic testing and the investigation of sensitive specimens. A major obstacle to implementing ACU methods is the significant signal power loss at the air–specimen and transducer–air interfaces. The loss between transducer and air can be eliminated by using recently developed fluidic transducers. These transducers use pressurized air and a natural flow instability to generate high sound power signals. Due to this self-excited flow instability, the individual pulses are dissimilar in length, amplitude, and phase. These amplitude and angle modulated pulses offer the great opportunity to further increase the signal-to-noise ratio with pulse compression methods.
In practice, multi-input multi-output (MIMO) setups reduce the time required to scan the specimen surface, but demand high pulse discriminability. By applying envelope removal techniques to the individual pulses, the pulse discriminability is increased allowing only the remaining phase information to be targeted for analysis. Finally, semi-synthetic experiments are presented to verify the applicability of the envelope removal method and highlight the suitability of the fluidic transducer for MIMO setups.
An approach to adhesive bond characterisation using guided acoustic waves in multi-layered plates
(2021)
An approach for the non-destructive characterisation of adhesive bonds using guided ultrasonic waves is presented. Pulsed laser radiation is used to thermoacoustically excite broadband ultrasonic waves in a multi-layered sample, consisting of a metal plate adhesively joined to a polymeric layer using synthetic resin. The resulting signals are received by a purpose-built piezoelectric transducer. Varying the distance between excitation and detection yields spatio-temporal measurement data, from which the dispersive properties of the propagating waves can be inferred using a two-dimensional Fourier transform, assuming the plates to act as coupled waveguides. Coupled multi-layered waveguides show an effect referred to as mode repulsion, where the distance between certain modes in the frequency-wavenumber domain is assumed to be a measure of coupling strength. Measurements at different stages of curing of the adhesive layer are performed and evaluated. A comparison of the results shows changes in the dispersive properties, namely an increased modal bandwidth for the fully cured sample as well as an increased modal distance.
Active thermography as a nondestructive testing modality suffers greatly from the limitations imposed by the diffusive nature of heat conduction in solids. As a rule of thumb, the detection and resolution of internal defects/inhomogeneities is limited to a defect depth to defect size ratio greater than or equal to one. Earlier, we demonstrated that this classical limit can be overcome for 1D and 2D defect geometries by using photothermal laser-scanning super resolution. In this work we report a new experimental approach using 2D spatially structured illumination patterns in conjunction with compressed sensing and computational imaging methods to significantly decrease the experimental complexity and make the method viable for investigating larger regions of interest.
The knowledge about energy release and transient behaviour of flash lamps, used as short-term energy source in flash thermography investigations, is essential for a quantitative analysis of the results as well as for simulations regarding such experiments. Usually, only a rectangular pulse shape of a typical duration of a few milliseconds is regarded when flash lamps pulses are described. This note considers the afterglow period of a flash lamp explicitly and shows that negligence of this afterglow effect leads to a systematic underestimation of the pulse length and the related total energy release. In the reported case, the intensity transient recorded by a Silicon photo diode was transformed into a temperature transient, allowing the study of the real energy release. It turns out that approximately only 50% of the entire pulse energy were released during the usually regarded period of 2.8 ms, while the other half was released within a period of 20 ms with an exponential decay.
In the field of non-destructive testing, Lamb waves are often used for material characterisation. The increasing computational capabilities further enable complex and detailed simulations to predict the material behaviour in reality. Since adhesive bonding of different materials is a widely used method in modern applications, a reliable measurement system to determine the quality of these adhesive bonds is needed. Investigations of the dispersive behaviour of acoustic waves in adhesively bonded multi-layered waveguides show mode repulsions in the dispersion diagrams in regions where the modes of the single materials would otherwise intersect. In previous works, changes of the distance between those modes with respect to the bonding quality are observed. The experimental data for this investigation is generated using pulsed laser radiation to excite broadband acoustic waves in plate like specimens which are detected by a piezoelectric ultrasonic transducer. Numerical data is generated using simulations via a semi-analytical finite element method. Using a combination of experimental and numerical data, the present work introduces an approach to determine a parameter which indicates the bonding quality in relation
to an ideal material coupling.
The successful shift to NDE 4.0 will not only require developing and embracing new technologies associated with the fourth industrial revolution or becoming an integral part of the overall Industry 4.0, but also developing and adopting new ways of working. It is undoubtful that people will remain in charge of the inspections. However, it is arguable if the current “procedure-following” “level I-III” paradigm can withstand the changes that come along NDE 4.0. With the increased autonomy and interconnectedness expected with NDT 4.0, the majority of traditional NDE tasks will no longer be needed. Instead, different skills, such as that of programming and adapting systems, as well as problem solving, will become vital for the inspections. Therefore, we suggest that a new paradigm is needed—one in which inspector roles and, thus, also the requirements will have to be reinvented. We expect the inspectors to be relieved from the tedious and error prone aspects of the current system and to take responsibility for increasingly complex automated systems and work in closer collaboration with other experts. Thus, we propose that the traditional inspector roles will be transformed into that of the system developer, caretaker and problem solver, each requiring a specific set of skills and assuming different responsibilities. In this talk, we will present the new roles and discuss the challenges that may arise with them.
Nondestructive evaluation (NDE) is entering an era of the fourth industrial revolution and will undergo a major transformation. NDE is a vital part of industry and a successful move to NDE 4.0, it will require not just developing and embracing new technologies, but also developing and adopting new ways of working and becoming an integral part of the overall Industry 4.0. This will pose new challenges for the inspection personnel. To ensure the expected benefits from NDE 4.0, inspectors need stay in charge of the changing inspections. The promised autonomy and interconnectedness of NDE 4.0 will supersede the majority of traditional inspector tasks and will in turn require a different set of skills and raise different demands and challenges for the inspection personnel, thus conflicting the current “procedure-following”-“level I-III” paradigm. The new industry 4.0 technologies can be integrated into the current framework, but exploiting their full potential requires changes in the role of the inspectors. The inspectors will be relieved from the tedious and error-prone aspects of the current system. At the same time, they will need to take responsibility for increasingly complex automated systems and work in closer collaboration with other experts. We propose that the traditional inspector roles will be transformed into that of the system developer, caretaker, and problem solver, each requiring a specific set of skills and assuming different responsibilities. For full NDE 4.0, NDE must abandon its traditional role as a self-contained entity with well-defined boundaries and take its role in the wider system that is the industry 4.0.
The successful shift to NDE 4.0 will not only require developing and embracing new technologies associated with the fourth industrial revolution or becoming an integral part of the overall Industry 4.0, but also developing and adopting new ways of working. It is undoubtful that people will remain in charge of the inspections. However, it is arguable if the current “procedure-following” “level I-III” paradigm can withstand the changes that come along NDE 4.0. With the increased autonomy and interconnectedness expected with NDT 4.0, the majority of traditional NDE tasks will no longer be needed. Instead, different skills, such as that of programming and adapting systems, as well as problem solving, will become vital for the inspections. Therefore, we suggest that a new paradigm is needed—one in which inspector roles and, thus, also the requirements will have to be reinvented. We expect the inspectors to be relieved from the tedious and error prone aspects of the current system and to take responsibility for increasingly complex automated systems and work in closer collaboration with other experts. Thus, we propose that the traditional inspector roles will be transformed into that of the system developer, caretaker and problem solver, each requiring a specific set of skills and assuming different responsibilities. In this talk, we will present the new roles and discuss the challenges that may arise with them.
The successful shift to NDE 4.0 will not only require developing and embracing new technologies associated with the fourth industrial revolution or becoming an integral part of the overall Industry 4.0, but also developing and adopting new ways of working. It is undoubtful that people will remain in charge of the inspections. However, it is arguable if the current “procedure-following” “level I-III” paradigm can withstand the changes that come along NDE 4.0. With the increased autonomy and interconnectedness expected with NDT 4.0, the majority of traditional NDE tasks will no longer be needed. Instead, different skills, such as that of programming and adapting systems, as well as problem solving, will become vital for the inspections. Therefore, we suggest that a new paradigm is needed—one in which inspector roles and, thus, also the requirements will have to be reinvented. We expect the inspectors to be relieved from the tedious and error prone aspects of the current system and to take responsibility for increasingly complex automated systems and work in closer collaboration with other experts. Thus, we propose that the traditional inspector roles will be transformed into that of the system developer, caretaker and problem solver, each requiring a specific set of skills and assuming different responsibilities. In this talk, we will present the new roles and discuss the challenges that may arise with them.
That human factors (HF) affect the reliability of NDT is not novelty. Still, when it comes to reliability assessments, the role of people is often neglected. Reliability is typically expressed in terms of POD curves, and the effects of human and organisational factors on the inspection are typically tackled by the regulations, procedures and by the qualification and training of the inspection personnel. However, studies have shown that even the most experienced personnel can make mistakes and that the reliability in the field is never as high as the reliability measured in the POD experiments. Generally, HF are considered too unpredictable and too uncontrollable to model. If that is the fact, then what can we do? The engineering perspective to this problem has often been to find ways to automate inspections and, recently, to make use of artificial intelligence tools to decrease the direct effect of people on the inspection results and improve the overall efficiency and reliability. However, despite automation and AI, people remain the key players, though their tasks change. The contemporary approach to HF is not to engineer them out of the system but to design human-machine systems that make the best use of both. In this talk, ways of tackling HF in the design of systems and processes will be presented.
While contact and immersion ultrasonic testing are established methods in non-destructive testing (NDT), generating high power air-coupled ultrasound remains a challenging task. Solutions often involve setups that are restricted to lab environments. When field measurements are required, such as in NDT for civil engineering, a handy, robust and safe transducer is needed. For this purpose, an ultrasonic transducer based on a fluidic switch has been developed. A sonic air flow inside the device is switched rapidly so that an ultrasonic signal is generated. Both theory and previous flow simulations suggest that the control flow pressure ramp has only little influence on the switching time of the device. This publication gives an overview over the operating principle of the fluidic ultrasonic transducer and investigates the influence of control tube length and pulsing repetition rate on the ultrasonic pressure amplitude. High repetition rates are found to reduce the signal amplitude, whereas long tubing has only little negative influence on the amplitude while improving signal quality.
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.
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 lattice structures. These lattice structures shall be implemented in various industrial applications (e.g. gas turbines) for reasons of material savings or cooling
channels. However, internal defects, residual stress, and structural deviations from the nominal geometry are unavoidable.
In this work, the structural integrity of lattice structures manufactured by means of L-PBF was non-destructively investigated on a multiscale approach.
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. It was also observed that at least about 50% of the powder porosity was released during production of the struts.
Struts are the component of lattice structures and were investigated by means of laboratory CT. The focus was on the influence of the build angle on part porosity and surface quality. The surface topography analysis was advanced by the quantitative characterisation of re-entrant surface features. This characterisation was compared with conventional surface parameters showing their complementary
information, but also the need for AM specific surface parameters.
The mechanical behaviour of the lattice structure was investigated with in-situ CT under compression and successive digital volume correlation (DVC). The Deformation was found to be knot-dominated, and therefore the lattice folds unit cell layer wise.
The residual stress was determined experimentally for the first time in such lattice structures. Neutron diffraction was used for the non-destructive 3D stress investigation. The principal stress directions and values were determined in dependence of the number of measured directions. While a significant uni-axial stress state was found in the strut, a more hydrostatic stress state was found in the knot. In both cases, strut and knot, seven directions were at least needed to
find reliable principal stress directions.
Layer-by-layer additive manufacturing (AM) by means of laser-powder bed Fusion (L-PBF) offers many prospects regarding the design of lattice structures used, for example, in gas turbines. However, defects such as bulk porosity, Surface roughness, and re-entrant features are exacerbated in nonvertical structures, such as tilted struts. The characterization and quantification of these kinds of
defects are essential for the correct estimation of fracture and fatigue properties.
Herein, cylindrical struts fabricated by L-PBF are investigated by means of X-ray computed tomography (XCT), with the aim of casting light on the dependence of the three kinds of defects (bulk porosity, surface roughness, and re-entrant features) on the build angle. Innovative analysis methods are proposed to correlate shape and position of pores, to determine the angular-resolved Surface roughness, and to quantify the amount of re-entrant surface features, q. A meshing of the XCT surface enables the correlation of q with the classical Surface roughness Pa. This analysis leads to the conclusion that there is a linear correlation between q and Pa. However, it is conjectured that there must be a threshold of surface roughness, below which no re-entrant features can be build.
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.
The neutron imaging instrument CONRAD was operated as a part of the user program of the research reactor BER‐II at Helmholtz‐Zentrum Berlin (HZB) from 2005 to 2020. The Instrument was designed to use the neutron flux from the cold source of the reactor, transported by a curved neutron guide. The pure cold neutron spectrum provided a great advantage in the use of different neutron optical components such as focusing lenses and guides, solid‐state polarizers, Monochromators and phase gratings. The flexible setup of the instrument allowed for implementation of new methods including wavelength‐selective, dark‐field, phase‐contrast and imaging with polarized neutrons. In summary, these developments helped to attract a large number of scientists and industrial customers, who were introduced to neutron imaging and subsequently contributed to the Expansion of the neutron imaging community.
Motivation:
• Air-coupled ultrasound (AC-US) enables faster measurements in non-destructive testing for civil engineering
• Current state of the art: piezo and capacitive transducers are mostly used for AC US
• Currently >99.9% sound intensity loss due to impedance mismatches
Innovation:
• Fluidic transducers generate US (30-60 kHz) by rapid switching of a supersonic jet
• Fluidic transducers rely on external components such as solenoid valves and tubing
--> How do repetition time and tube length influence the signal?
Understanding on how a machine learning model interprets data is a crucial step to verify its reliability and avoid overfitting. While the focus of the scientific community is nowadays orientated towards deep learning approaches, which are considered as black box approaches, this work presents a toolbox that is based on complementary methods of feature extraction and selection, where the classification decisions of the model are transparent and can be physically interpreted. On the example of guided wave benchmark data from the open guided waves platform, where delamination defects were simulated at multiple positions on a carbon fiber reinforced plastic plate under varying temperature conditions, the authors could identify suitable frequencies for further investigations and experiments. Furthermore, the authors presented a realistic validation scenario which ensures that the machine learning model learns global damage characteristics rather than position specific characteristics.
To date, the destructive extraction and analysis of drilling cores is the main possibility to obtain depth information about damaging water ingress in building floors. The time- and costintensive procedure constitutes an additional burden for building insurances that already list piped water damage as their largest item. With its high sensitivity for water, a ground-penetrating radar (GPR) could provide important support to approach this problem in a non-destructive way. In this research, we study the influence of moisture damage on GPR signals at different floor constructions. For this purpose, a modular specimen with interchangeable layers is developed to vary the screed and insulation material, as well as the respective layer thickness. The obtained data set is then used to investigate suitable signal features to classify three scenarios: dry, damaged insulation, and damaged screed. It was found that analyzing statistical distributions of A-scan features inside one B-scan allows for accurate classification on unknown floor constructions. Combining the features with multivariate data analysis and machine learning was the key to achieve satisfying results. The developed method provides a basis for upcoming validations on real damage cases.
Ultrasonic measurement technology has become indispensable in NDT. In order to reduce measurement time and extend the application to other materials, contactless ultrasound is the subject of many different research groups. Department 8 has been researching successfully in this field for years. A novel approach is based on so-called fluidic devices. These devices can be used to perform binary logic operations with the help of natural flow instabilities. Hence the abbreviated name, Fluidic (FLUID+LogIC). Only a pressure reservoir of the used fluid is required as energy supply. This enables the production of very robust actuators that generate ultrasonic signals in an extremely energy efficient way.
The presentation includes the research results of the ZIM innovation project OsciCheck. The original idea will be presented and its application on different building materials is validated. Beyond this, the possible application areas are much larger and a detailed outlook is given to discuss the future potential of fluidic ultrasonic actuators.
Machine learning predictions of surface migration barriers in nucleation and non-equilibrium growth
(2021)
Machine learning is playing an increasing role in the discovery of new materials and may also facilitate the search for optimum growth conditions for crystals and thin films. Here, we perform kinetic Monte-Carlo simulations of sub-monolayer growth. We consider a generic homoepitaxial growth scenario that covers a wide range of conditions with different diffusion barriers (0.4–0.55 eV) and lateral binding energies (0.1–0.4 eV). These simulations are used as a training data set for a convolutional neural network that can predict diffusion barriers and binding energies. Specifically, a single Monte-Carlo image of the morphology is sufficient to determine the energy barriers with an accuracy of approximately 10 meV and the neural network is tolerant to images with noise and lower than atomic-scale resolution. We believe this new machine learning method will be useful for fundamental studies of growth kinetics and growth optimization through better knowledge of microscopic parameters.
Pulse-compression thermography is an emerging technique that has shown versatility by combination of pulsed and lock-in thermography. Accordingly, several aspects of this technique are still unexplored, and some others not fully developed yet. Barker codes were widely used in radar applications due to their simplicity and their optimum autocorrelation function. Nevertheless, applications were limited by the amplitude of the sidelobes present in the autocorrelation function and therefore, several filters have been developed which aim to reduce the sidelobes. However, the filters usually depend on empirical parameters which must be determined for each application. A better alternative would improve the applicability of the Barker codes. In this work, we further develop the pulse-compression thermography technique by introducing a 13-bit modified Barker code (mBC): This allows to drastically reduce the sidelobes characteristic of the 13-bit Barker code (BC). Consequently, the thermographic impulse response, obtained by cross-correlation, is almost free of such sidelobes. Deeper defects become easier to detect in comparison with using a 13-bit Barker code. Numerical simulations using the finite element method are used for comparison and experimental measurements are performed in a sample of steel grade St 37 with machined notches of three different depths: 2 mm, 4 mm and 6 mm.
A joint project of partners from industry and research institutions for the research and construction of an analysis system for an automated, sensor-supported sorting of construction and demolition waste will be presented. This is intended to supplement or replace the previously practiced manual sorting, which harbors many risks and dangers for the staff and only enables obvious, visually detectable differences for separation. The method of laser-induced breakdown spectroscopy is to be used in combination with hyperspectral sensors. Due to the jointly processed information (data fusion), this should lead to a significant improvement in the separation of types. In addition to the sorting of different materials (concrete, main masonry building materials, organic components, glass, etc.), impurities such as SO3-containing building materials (gypsum, aerated concrete, etc.) could also be detected and separated.
The subsequent recycling and sales opportunities are examined, such as the use of recycled aggregates in concrete, the recycling of building materials containing sulphate as a gypsum substitute for the cement industry or the agglomeration of synthetic lightweight aggregates for lightweight concrete or as a substrate for green roofs. At the same time, it is investigated whether soluble components (sulfates, heavy metals, etc.) can be detected by LIBS without a wet chemical analysis and what impact the recycling materials have on the environment.
The entire value chain is examined using the example of the Berlin location in order to minimize economic / technological barriers and obstacles on a cluster level and to sustainably increase the recovery and recycling rates.
Pulse-compression thermography is an emerging technique that has shown versatility by combination of pulsed and lock-in thermography. Accordingly, several aspects of this technique are still unexplored, and some others not fully developed yet. Barker codes were widely used in radar applications due to their simplicity and their optimum autocorrelation function. Nevertheless, applications were limited by the amplitude of the sidelobes present in the autocorrelation function and therefore, several filters have been developed which aim to reduce the sidelobes. However, the filters usually depend on empirical parameters which must be determined for each application. A better alternative would improve the applicability of the Barker codes. In this work, we further develop the pulse-compression thermography technique by introducing a 13-bit modified Barker code (mBC): This allows to drastically reduce the sidelobes characteristic of the 13-bit Barker code (BC). Consequently, the thermographic impulse response, obtained by cross-correlation, is almost free of such sidelobes. Deeper defects become easier to detect in comparison with using a 13-bit Barker code. Numerical simulations using the finite element method are used for comparison and experimental measurements are performed in a sample of steel grade St 37 with machined notches of three different depths: 2 mm, 4 mm and 6 mm.
Corrosion of concrete reinforcement is one of the major damage mechanisms affecting both the load-bearing capacity and the serviceability of reinforced concrete structures significantly. The challenge of detecting corrosion is that the corrosion process in its various forms is not immediately visible, especially in the corrosion initiation phase inside the concrete. When externally discernible damages are observed during visual inspections on the structure, the extent of the damage inside the concrete is often already significant. Corrosion caused by carbonation often leads to severe discoloration of the surface or even large-area spalling of the concrete cover. In contrast, chloride-induced corrosion is usually difficult to observe visually, but can cause much more serious damage in less time. The effect occurs locally and can lead to weakening of the cross-section of the reinforcement. This, in turn, can cause sudden structural collapses without prior notice. Therefore, it is important to investigate whether there is protection against corrosion of the reinforcement in the concrete and to detect active corrosion in the structure at an early stage.
In the meanwhile, various non-destructive and minimally invasive testing methods are available to evaluate the resistance to penetration of corrosion-promoting pollutants and to detect active corrosion. In this paper, a bridge crossing the river Regen (Germany) is used as a case-study to demonstrate how the information obtained applying different testing methods can be combined and evaluated in the context of structural reassessments. Both the results of the permeability testing (Torrent tester) and the electrical resistance measurement (Wenner probe) are considered, as well as active corrosion areas are localized using the half-cell potential mapping combined with the concrete cover measurement with the eddy current method and ground penetrating radar (GPR). The results are evaluated using drill cores and in addition laser-induced breakdown spectroscopy (LIBS) was applied to obtain information about possible ion transport in the concrete.
In this contribution, an approach is outlined to process non-destructively gath-ered measurement data in a comparable way in order to include the measured information in probabilistic reliability assessments of existing structures. An es-sential part is the calculation of measurement uncertainties. The effect of incor-porating evaluated NDT-results is demonstrated by means of a prestressed con-crete bridge and GPR measurements conducted on this bridge as a case-study. The bridge is assessed regarding SLS Decompression using the NDT-results.
This data article presents characteristic acoustic and flow data of a fluidic ultrasonic transducer as well as acoustic data of a commercial piezoelectric ultrasonic transducer used in non-destructive testing for civil engineering. The flow data has been acquired using hot-wire anemometry and a Pitot tube. The three-dimensional acoustic data of both devices has been acquired using a calibrated microphone. The distribution of characteristic acoustic properties of both transducers are extracted and given in addition to the raw data. The data presented in the article will be a valuable source for reference and validation, both for developing fluidic and alternate ultrasound generation technologies. Furthermore, they will give additional insight into the acoustic-flow interaction phenomena of high speed switching devices. This article is accompanying the paper Experimental Analysis of the Acoustic Field of an Ultrasonic Pulse Induced by a Fluidic Switch (Bühling et al., 2021) published in The Journal of the Acoustical Society of America, where the data is interpreted in detail and the rationale for characteristic sound properties of the fluidic transducer are given.
The reconstruction of cone-beam computed tomography data using filtered back-projection algorithms unavoidably results in severe artefacts. We describe how the Direct Iterative Reconstruction of Computed Tomography Trajectories (DIRECTT) algorithm can be combined with a model of the artefacts for the reconstruction of such data. The implementation of DIRECTT results in reconstructed volumes of superior quality compared to the conventional algorithms.
While X-ray based darkfield imaging with grating interferometers is already widely used, darkfield imaging with neutrons has still a relatively small user community focused mostly on magnetic materials. Here, we demonstrate the application of neutron darkfield imaging byTalbot-Lau type grating interferometry to fiber reinforced plastics. Common carbon and glass fiber composites have been investigated including characteristic damage structures. The darkfield images show a strong signal response caused by fiber delamination, suitable fiber direction, particles, pores and cracks. The basic principles of neutron darkfield imaging applied to fiber composites are highlighted.
Novel Technique for On-Line Monitoring of the Curing Process of Fiber Reinforced Polymer Composites
(2021)
A specially developed experimental set up has been integrated into a commercially available FT IR Spectrometer to study the curing of Epoxy Systems. MIR and FIR spectra measured during the curing process at different temperatures of an epoxy system will be presented in dependency of the curing time. The experiments and the selected set up are discussed to demonstrate its potential for future monitoring and ageing control applications during a manufacturing process of polymer composites.
The development of prevention methods and the detection of moisture related damages in buildings and transport infrastructure at an early stage are current issues
in the field of non-destructive testing in civil engineering. Especially the subject of partial saturation requires further research since it is more likely to occur than full saturation of the material. In fact, partial saturation in porous media is even more complicated because both fully and partly saturated pores (i.e. pores in which the surfaces are covered with thin water layers) are present.
As the non-destructive method nuclear magnetic resonance
(NMR) enables the measurement and quantification of relative low moisture contents, it is suitable for the investigation of partly saturated porous building materials. Nevertheless, the differentiation between partly and fully saturated pores is still a challenge. Therefore, in this study, we investigate two sandstones types (Bozanov and Schönbrunner sandstone) at various defined saturation states by using NMR. Furthermore, we measure the relative humidities within the samples and compute the water layer thicknesses (WLT) along the pore walls of all pore sizes to calculate the corresponding degree of pore saturation. To finally assign the NMR signals to pore sizes and to differentiate between partly and fully saturated pores, the water content distribution obtained from the WLT calculation
is used for calibration of the relaxation-time distribution.
The development of prevention methods and the detection of moisture related damages in buildings and transport infrastructure at an early stage are current issues in the field of non-destructive testing in civil engineering.
Especially the subject of partial saturation requires further research since it is more likely to occur than full saturation of the material. In fact, partial saturation in porous media is even more complicated because both fully and partly saturated pores (i.e. pores in which the surfaces are covered with thin water layers) are present.
As the non-destructive method nuclear magnetic resonance (NMR) enables the measurement and quantification of relative low moisture contents, it is suitable for the investigation of partly saturated porous building materials. Nevertheless, the differentiation between partly and fully saturated pores is still a challenge. Therefore, in this study, we investigate two sandstones types (Bozanov and Schönbrunner sandstone) at various defined saturation states by using NMR. Furthermore, we measure the relative humidities within the samples and compute the water layer thicknesses (WLT) along the pore walls of all pore sizes to calculate the corresponding degree of pore saturation. To finally assign the NMR signals to pore sizes and to differentiate between partly and fully saturated pores, the water content distribution obtained from the WLT calculation is used for calibration of the relaxation-time distribution. In this extended abstract, selected results only for Schönbrunner sandstone are presented.
Muon Tomography of the Interior of a Reinforced Concrete Block: First Experimental Proof of Concept
(2021)
Quality assurance and condition assessment of concrete structures is an important topic world-wide due to the aging infrastructure and increasing traffic demands. Common topics include, but are not limited to, localisation of rebar or tendon ducts, geometrical irregularities, cracks, voids, honeycombing or other flaws. Non-destructive techniques such as ultrasound or radar have found regular, successful practical application but sometimes suffer from limited resolution and accuracy, imaging artefacts or restrictions in detecting certain features. Until the 1980s X-ray transmission was used in case of special demands and showed a much better resolution than other NDT techniques. However, due to safety concerns and cost issues, this method is almost never used anymore. Muon tomography has received much attention recently. Novel detectors for cosmic muons and tomographic imaging algorithms have opened up new fields of application, such as the investigation of freight containers. Muon imaging also has the potential to fill some of the gaps currently existing in concrete NDT. As a first step towards practical use and as a proof of concept we used an existing system to image the interior of a reference reinforced 600 kg concrete block. Even with a yet not optimized setup for this kind of investigation, the muon imaging results are at least of similar quality compared to ultrasonic and radar imaging, potentially even better. The data acquisition takes more time and signals contain more noise, but the images allowed to detect the same important features that are visible in conventional high energy X-ray tomography. In our experiment, we have shown that muon imaging has potential for concrete inspection. The next steps include the development of mobile detectors and optimising acquisition and imaging parameters.
Making optimal decisions about the reliability of existing structures requires that the information used in assessment adequately represents the properties and the condition of the structures. The knowledge gap regarding a structure to be assessed can be successively filled by individually purposeful observations on site. This paper gives an overview of an approach for utilizing nondestructively gathered measurement results in reliability assessment of existing structures. An essential part of measurement-based stochastic modeling of basic variables is the calculation of measurement uncertainties, which serves to establish confidence in measurement, to ensure the comparability of unambiguously expressed measurement results, and to quantify the quality of the measured information. Regarding the current discourse on how to treat information collected on-site in the context of assessment, the authors recommend that measurement uncertainty becomes an uncertainty component mandatorily to be represented in measurement-based stochastic models. The main steps of the proposed concept are presented, and the advantages of its application are emphasized by means of a prestressed concrete bridge as case study. The bridge is assessed regarding the serviceability limit state decompression using ultrasonic and radar data measured at the structure.
An Ontology-Based Approach to Enable Data-Driven Research in the Field of NDT in Civil Engineering
(2021)
Although measurement data from the civil engineering sector are an important basis for scientific analyses in the field of non-destructive testing (NDT), there is still no uniform representation of these data. An analysis of data sets across different test objects or test types is therefore associated with a high manual effort. Ontologies and the semantic web are technologies already used in numerous intelligent systems such as material cyberinfrastructures or research databases. This contribution demonstrates the application of these technologies to the case of the 1H nuclear magnetic resonance relaxometry, which is commonly used to characterize water content and porosity distri-bution in solids. The methodology implemented for this purpose was developed specifically to be applied to materials science (MS) tests. The aim of this paper is to analyze such a methodology from the perspective of data interoperability using ontologies. Three benefits are expected from this ap-proach to the study of the implementation of interoperability in the NDT domain: First, expanding knowledge of how the intrinsic characteristics of the NDT domain determine the application of semantic technologies. Second, to determine which aspects of such an implementation can be improved and in what ways. Finally, the baselines of future research in the field of data integration for NDT are drawn.
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.
In recent years carbon über polymers have become a popular light-weight substitute for high-weight materials such as steel. One advantage of carbon fiber polymers is the high strength-to-weight ratio, thus some popular application areas are weight sensitive such as aeronautics or automobiles. As these application areas are especially sensitive to material failure it is of significant interest to characterize material defects which may arise. In this talk we will propose a method to characterize material defects in carbon fiber reinforced polymers using gradient-based optimization methods. The procedure is based on the solution of an inverse problem where simulation data and experimental data is fitted. Here,
gradients of the simulation will be supplied by an Algorithmic Differentiation (AD) tool which greatly enhances the quality of the solution. Numerical examples will be provided.
The photoacoustic measurement technique is a powerful yet underrepresented method to characterize the thermal transport properties of thin films. For the case of isotropic low thermal diffusivity samples, such as glasses or polymers, we demonstrate a general approach to extract the thermal conductivity with a high degree of significance. We discuss in particular the influence of thermal effusivity, thermal diffusivity, and sample layer thickness on the significance and accuracy of this measurement technique. These fundamental thermal properties guide sample and substrate selection to allow for a feasible thermal transport characterization. Furthermore, our data evaluation allows us to directly extract the thermal conductivity from this transient technique, without separate determination of the volumetric heat capacity, when appropriate boundary conditions are fulfilled.
Using silica, poly(methyl methacrylate) (PMMA) thin films, and various substrates (quartz, steel, and silicon), we verify the quantitative correctness of our analytical approach.
Pressure vessels for the transport of hazardous gases are subjected to a hydraulic internal pressure test. Basis for the design of metallic pressure vessels is the fatigue strength according to Wöhler, whereby the number of load changes can be equated with the number of filling / emptying cycles of the pressure vessel. Metallic pressure vessels are increasingly replaced by composite pressure vessels due to the weight savings. However, at composite preasure vessels it is not possible to conclude from the number of load cycles on the fatigue strength, because composite pressure vessels are ageing even at constant internal pressure. Non-destructive conventional and high frequency eddy current testing of the metallic liner and load bearing CFRP layer are presented as an alternative to hydraulic internal pressure test.
The effective gas diffusion coefficient describes the process of gas diffusion in porous materials. Several materials have a significant number of micropores in the lower nanometre range leading to a reduction of gas diffusion (Knudsen effect). In the case of partial pore saturation during adsorption, the available pore space is further reduced, as is the gas diffusion. In this study, the influence of partially saturated pores on the Knudsen effect and on the gas diffusion is quantified. Three different pore geometries are investigated (slit, cylindrical and spherical pores) and three different types of pore size distribution, including a broad equal distribution, three narrow normal distributions and two measured distributions of concrete.
Besides the intensive computation of the exact pore saturation, a simplified model with low computational requirements is suggested. This study shows that the influence of the water layer thickness on the effective diffusion becomes significant for pore radii below 50 nm and the assumed pore geometry is important. At the end, the overall effect is quantified for an amorphous material with most pore
radii below 30 nm. At a moisture level of 50% relative humidity, the effective diffusion is reduced by 35% due to partial saturation.
In many industrial sectors, Structural Health Monitoring (SHM) is considered as an addition to Non-Destructive Testing (NDT) that can reduce maintenance effort during lifetime of a technical facility, structural component or vehicle. A large number of SHM methods is based on ultrasonic waves, whose properties change depending on structural health. However, the wide application of SHM systems is limited due to the lack of suitable methods to assess their reliability. The evaluation of the system performance usually refers to the determination of the Probability of Detection (POD) of a test procedure. Up to now, only few limited methods exist to evaluate the POD of SHM systems, which prevent them from being standardised and widely accepted in industry. The biggest hurdle concerning the POD calculation is the large amount of samples needed. A POD analysis requires data from numerous identical structures with integrated SHM systems. Each structure is then damaged at different locations and with various degrees of severity. All of this is connected to high costs. Therefore, one possible way to tackle this problem is to perform computer-aided investigations. In this work, the POD assessment procedure established in NDT according to the Berens model is adapted to guided wave-based SHM systems. The approach implemented here is based on solely computer-aided investigations. After efficient modelling of wave propagation phenomena across an automotive component made of a carbon fibre-reinforced composite, the POD curves are extracted. Finally, the novel concept of a POD map is introduced to look into the effect of damage position on system reliability.
Composite-overwrapped pressure vessels (COPV) are increasingly used in the transportation industry due to their high strength to mass ratio. Throughout the years, various designs were developed and found their applications. Currently, there are five designs, which can be subdivided into two main categories - with a load-sharing metal liner and with a non-load-sharing plastic liner. The main damage mechanism defining the lifetime of the first type is fatigue of the metal liner, whereas for the second type it is fatigue of the composite overwrap. Nevertheless, one damage type which may drastically reduce the lifetime of COPV is impact-induced damage. Therefore, this barely visible damage needs to be assessed in a non-destructive way to decide whether the pressure vessel can be further used or has to be put out of service. One of the possible methods is based on ultrasonic waves. In this contribution, both conventional ultrasonic testing (UT) by high-frequency bulk waves and wavenumber mapping by low frequency guided waves are used to evaluate impact damage. Wavenumber mapping techniques are first benchmarked on a simulated aluminium panel then applied to experimental measurements acquired on a delaminated aluminium-CFRP composite plate which corresponds to a structure of COPV with a load-sharing metal liner. The analysis of experimental data obtained from measurements of guided waves propagating in an aluminium-CFRP composite plate with impact-induced damage is performed. All approaches show similar performance in terms of quantification of damage size and depths while being applied to numerical data. The approaches used on the experimental data deliver an accurate estimate of the in-plane size of the large delamination at the aluminium-CFRP interface but only a rough estimate of its depth. Moreover, none of the wavenumber mapping techniques used in the study can quantify every delamination between CFRP plies caused by the impact, which is the case for conventional UT. This may be solved by using higher frequencies (shorter wavelengths) or more advanced signal processing techniques. All in all, it can be concluded that imaging of complex impact damage in fibre-reinforced composites based on wavenumber mapping is not straightforward and stays a challenging task.
Additively manufactured (AM) metallic sheet-based Triply Periodic Minimal Surface Structures (TPMSS) meet several requirements in both bio-medical and engineering fields: Tunable mechanical properties, low sensitivity to manufacturing defects, mechanical stability, and high energy absorption. However, they also present some challenges related to quality control, which can prevent their successful application. In fact, the optimization of the AM process is impossible without considering structural characteristics as manufacturing accuracy, internal defects, as well as surface topography and roughness. In this study, the quantitative non-destructive analysis of TPMSS manufactured from Ti-6Al-4V alloy by electron beam melting was performed by means of X-ray computed tomography (XCT). Several advanced image analysis workflows are presented to evaluate the effect of build orientation on wall thicknesses distribution, wall degradation, and surface roughness reduction due to the chemical etching of TPMSS. It is shown that the manufacturing accuracy differs for the structural elements printed parallel and orthogonal to the manufactured layers. Different strategies for chemical etching show different powder removal capabilities and both lead to the loss of material and hence the gradient of the wall thickness. This affects the mechanical performance under compression by reduction of the yield stress. The positive effect of the chemical etching is the reduction of the surface roughness, which can potentially improve the fatigue properties of the components. Finally, XCT was used to correlate the amount of retained powder with the pore size of the functionally graded TPMSS, which can further improve the manufacturing process.
The work to be presented focuses on our most recent studies to laser excited super resolution (SR) thermography. The goal of nondestructive testing with SR is to facilitate the separation of closely spaced defects. Photothermal SR can be realized by performing structured illumination measurements in com-bination with the use of deconvolution algorithms in post-processing. We explain that stepwise as well as continuous scanning techniques are applicable to generate structured illumination measurements. Finally, we discuss the effect of experimental parameters and image processing techniques to find the optimal SR technique which leads to the highest reconstruction quality within laser thermography.
The work to be presented focuses on our most recent studies to laser excited super resolution (SR) thermography. The goal of nondestructive testing with SR is to facilitate the separation of closely spaced defects. Photothermal SR can be realized by performing structured illumination measurements in com-bination with the use of deconvolution algorithms in post-processing. We explain that stepwise as well as continuous scanning techniques are applicable to generate structured illumination measurements. Finally, we discuss the effect of experimental parameters and image processing techniques to find the optimal SR technique which leads to the highest reconstruction quality within laser thermography.
The morphology of the antennal hearts in the head of Phasmatodea and Embioptera was investigated with particular reference to phylogenetically relevant key taxa. The antennal circulatory organs of all examined species have the same basic construction: they consist of antennal vessels that are connected to ampullae located in the head near the antenna base. The ampullae are pulsatile due to associated muscles, but the points of attachment differ between the species studied. All examined Phasmatodea species have a Musculus (M.) interampullaris which extends between the two ampullae plus a M. ampulloaorticus that runs from the ampullae to the anterior end of the aorta; upon contraction, all these muscles dilate the lumina of both ampullae at the same time. In Embioptera, only the australembiid Metoligotoma has an M. interampullaris. All other studied webspinners instead have a M. ampullofrontalis which extends between the ampullae and the frontal region of the head capsule; these species do not have M. ampulloaorticus. Outgroup comparison indicates that an antennal heart with a M. interampullaris is the plesiomorphic character state among Embioptera and the likely ground pattern of the taxon Eukinolabia. Antennal hearts with a M. ampullofrontalis represent a derived condition that occurs among insects only in some embiopterans. These findings help to further clarify the controversially discussed internal phylogeny of webspinners by supporting the view that Australembiidae are the sister group of the remaining Embioptera.
This presentation shows how the dispersive behavior of ultrasonic guided waves in isotropic materials can be used by means of Convolutional Neural Networks to determine the elastic parameters. For this purpose, the preprocessing, the training, the chosen architecture and the results are evaluated on the basis synthetic image data. This presentation was given at the SMSI 2021.
Lamb waves are a common tool in the field of non-destructive testing and are widely used for materialcharacterisation. Further, the increasing computational capability of modern systems enables the Simulation of complex and detailed material models. This work demonstrates the possibility of simulating an adhesive-bonded multilayer system by characterising each layer individually, and introduces an Approach for determining the dispersive behaviour of acoustic waves in a multilayer system via real measurements.
Lamb waves are a common tool in the field of non-destructive testing and are widely used for material characterisation. Further, the increasing computational capability of modern systems enables the Simulation of complex and detailed material models. This work demonstrates the possibility of simulating an adhesive-bonded multilayer system by characterising each layer individually, and introduces an Approach for determining the dispersive behaviour of acoustic waves in a multilayer system via real measurements.
Poor air quality, particularly in urban areas, causes various diseases and degrades living standards. Air Quality could be affected by emissions of odor, Volatile Organic Compounds (VOCs), and other gases. Therefore, assessment and monitoring of odorous air quality using sensitive, simple, rapid, accurate and portable tools is very important for public health. This study aimed to characterize odor emissions to detect malfunctions in facilities and to prevent air pollution and olfactory nuisance in the environment. A gas chromatographic method, in conjunction with sensorial analysis were performed for odorous air samples analysis collected from neighborhood of Meknes city (Morocco). Advanced multivariate statistical approaches, such as Principal Components Analysis (PCA), Discriminant Function Analysis (DFA), Support Vector Machines (SVMs), and Hierarchical Cluster Analysis (HCA), were used to describe samples similarities. The electronic nose (e-nose) data processing exhibits a satisfactory discrimination between the odorous air samples. Twenty-four VOCs with known molecular formulas were identified with Thermal Desorption-Gas Chromatography-Mass Spectrometry (TD-GC-MS). A validated Partial Least Square (PLS) model foresees good calibration between e-nose measurement and TD-GCMS analysis. The finding indicates that TD-GC–MS approach in conjunction with e-nose unit could be suitable tool for environmental measurement-based odor emissions.
In the context of Industry 4.0 and especially in the field of Structural Health Monitoring, Condition Monitoring and Digital Twins, simulations are becoming more and more important. The exact determination of material parameters is required for realistic results of numerical simulations of the static and dynamic behavior of technical structures. There are many possibilities to determine
elastic material parameters. One possibility of non-destructive testing are ultrasonic guided waves. For the evaluation of the measurement results, mostly inverse methods are applied in order to be able to draw conclusions about the elastic material parameters from analysing the ultrasonic guided wave propagation. For the inverse determination of the elastic material Parameters with ultrasonic guided waves, several investigations were carried out, e.g. the determination of the isotropic material parameters through the point of zero-groupvelocity or anisotropic material parameters with a simplex algorithm. These investigations are based on the evaluation of dispersion images. Machine learning and in particular Convolutional Neural Networks (CNN) are one possibility of the automated evaluation from Image data, e.g. classification or object recognition problems. This article shows how the dispersive behavior of ultrasonic guided waves and CNNs can be used to determine the isotropic elastic constants of plate-like structures.
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.
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.
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 report 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
This paper presents deep unfolding neural networks to handle inverse problems in photothermal radiometry enabling super resolution (SR) imaging. Photothermal imaging is a well-known technique in active thermography for nondestructive inspection of defects in materials such as metals or composites. A grand challenge of active thermography is to overcome the spatial resolution limitation imposed by heat diffusion in order to accurately resolve each defect. The photothermal SR approach enables to extract high-frequency spatial components based on the deconvolution with the thermal point spread function. However, stable deconvolution can only be achieved by using the sparse structure of defect patterns, which often requires tedious, hand-crafted tuning of hyperparameters and results in computationally intensive algorithms. On this account, Photothermal-SR-Net is proposed in this paper, which performs deconvolution by deep unfolding considering the underlying physics. This enables to super resolve 2D thermal images for nondestructive testing with a substantially improved convergence rate. Since defects appear sparsely in materials, Photothermal-SR-Net applies trained blocksparsity thresholding to the acquired thermal images in each convolutional layer. The performance of the proposed approach is evaluated and discussed using various deep unfolding and thresholding approaches applied to 2D thermal images. Subsequently, studies are conducted on how to increase the reconstruction quality and the computational performance of Photothermal-SR-Net is evaluated.
Thereby, it was found that the computing time for creating high-resolution images could be significantly reduced without decreasing the reconstruction quality by using pixel binning as a preprocessing step.
Learned block iterative shrinkage thresholding algorithm for photothermal super resolution imaging
(2020)
Block-sparse regularization is already well-known in active thermal imaging and is used for multiple measurement based inverse problems. The main bottleneck of this method is the choice of regularization parameters which differs for each experiment. To avoid time-consuming manually selected regularization parameters, we propose a learned block-sparse optimization approach using an iterative algorithm unfolded into a deep neural network. More precisely, we show the benefits of using a learned block iterative shrinkage thresholding algorithm that is able to learn the choice of regularization parameters. In addition, this algorithm enables the determination of a suitable weight matrix to solve the underlying inverse problem. Therefore, in this paper we present the algorithm and compare it with state of the art block iterative shrinkage thresholding using synthetically generated test data and experimental test data from active thermography for defect reconstruction. Our results show that the use of the learned block-sparse optimization approach provides smaller normalized mean square errors for a small fixed number of iterations than without learning. Thus, this new approach allows to improve the convergence speed and only needs a few iterations to generate accurate defect reconstruction in photothermal super resolution imaging.
In 2019, 3.1 billion Euro of damage was caused by piped water, accounting for the largest share (53%) of building insurance claims in Germany. In the event of damage, the accurate determination and localization of water ingress is essential to plan for and perform efficient renovations. Neutron probes are already applied successfully on building floors to localize the source of damage and other affected areas. However, additional information about the depth of moisture penetration can only be obtained by the destructive extraction of drilling cores, which is a time- and cost-intensive procedure. With its high sensitivity to water and fast measurement procedure, Ground Penetrating Radar (GPR) can serve as a suitable extension to the neutron probe, enabling more precise characterization of common forms of moisture damage.
In this research project, we study the influence of common types of moisture damage in differing floor constructions using GPR and a neutron probe. A measurement setup with interchangeable layers is used to vary the screed material (cement or anhydrite) and insulation material (Styrofoam, Styrodur, glass wool, perlite), as well as the respective layer thickness. Every configuration is measured for the following main cases: 1) dry state; 2) with a damaged insulation layer and 3) a damaged screed layer.
The evaluation is focused on the extraction of distinctive signal features for GPR, which can be used to classify the underlying case of damage. Furthermore, possible combinations of these features are investigated using multivariate data analysis and machine learning in order to evaluate the influence of different floor constructions.
To validate the developed methods, practical measurements on real damage cases in Germany are carried out and compared to reference data obtained from drilling cores.
We combine three different approaches to greatly enhance the defect reconstruction ability of active thermographic testing. As experimental approach, laser-based structured illumination is performed in a step-wise manner. As an intermediate signal processing step, the virtual wave concept is used in order to effectively convert the notoriously difficult to solve diffusion-based inverse problem into a somewhat milder wavebased inverse problem. As a final step, a compressed-sensing based optimization procedure is applied which efficiently solves the inverse problem by making advantage of the joint sparsity of multiple blind measurements. To evaluate our proposed processing technique, we investigate an additively manufactured stainless steel sample with eight internal defects. The concerted super resolution approach is compared to conventional thermographic reconstruction techniques and shows an at least four times better spatial resolution.
Thermographic super-resolution techniques allow the resolution of defects/inhomogeneities beyond the classical limit, which is governed by the diffusion properties of thermal wave propagation. Photothermal super-resolution is based on a combination of an experimental scanning strategy and a numerical optimization which has been proven to be superior to standard thermographic methods in the case of 1D linear defects. In this contribution, we report on the extension of this approach towards a full frame 2D photothermal super-resolution technique. The experimental 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. In our work we extend the possibilities of the method to efficiently detect and resolve defect cross sections with a fully 2D-structured blind illumination.
Thermographic super-resolution techniques allow the resolution of defects/inhomogeneities beyond the classical limit, which is governed by the diffusion properties of thermal wave propagation. Photothermal super-resolution is based on a combination of an experimental scanning strategy and a numerical optimization which has been proven to be superior to standard thermographic methods in the case of 1D linear defects. In this contribution, we report on the extension of this approach towards a full frame 2D photothermal super-resolution technique. The experimental 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. In our work we extend the possibilities of the method to efficiently detect and resolve defect cross sections with a fully 2D-structured blind illumination.
In this study, nanoscopic particles of magnesium Fluoride (MgF2) and calcium fluoride (CaF2) also known as nano metal fluorides (NMFs), were evaluated for their potential to improve wood durability. Even though these fluorides are sparingly soluble, their synthesis in the form of nano-sized particles turns them into promising candidates for wood preservation. Their distinct property of low-water solubility is proposed to maintain long-lasting protection of treated wood by reducing the leaching of fluoride. Analytical methods were used to characterize the synthesized NMFs and their distribution in treated wood specimens. Transmission electron microscopy images showed that these fluoride particles are smaller than 10 nm. In nano metal fluoride (NMF) treated specimens, aggregates of these particles are uniformly distributed in the wood matrix as confirmed with scanning electron microscopy images and their corresponding energy-dispersive X-ray spectroscopy maps. The fluoride aggregates form a protective layer around the tracheid walls and block the bordered pits, thus reducing the possible flow path for water absorption into wood. This is reflected in the reduced swelling and increased hydrophobicity of wood treated with NMFs. The biocidal efficacy of NMFs was tested against brown-rot fungi (Coniophora puteanaand Rhodonia placenta), white-rot fungus (Trametes versicolor), and termites (Coptotermes formosanus). The fungal and termite tests were performed in accordance with the EN 113 (1996) and EN 117 (2012) standards, respectively. Prior to fungal tests, the NMF treated wood specimens were leached according to the EN 84 (1997)standard. Compared to untreated specimens, the NMF treated wood specimens have a higher resistance to decay caused by brown-rot fungi, white-rot fungus, and termites. Although all NMF treatments in wood reduce the mass loss caused by fungal decay, only the combined treatment of MgF2 and CaF2 has efficacy against both brown-rot fungi and white-rot fungus. Similarly, wood treated with the combined NMF formulation is the least susceptible to attack by C. formosanus.It is proposed that combining MgF2 and CaF2changes their overall solubility to promote the release of fluoride ions at the optimal concentration needed for biocidal efficacy against fungi and termites. In this thesis, it was proven that even after leaching, sufficient fluoride was present to protect NMF treated wood from fungal decay. This shows that NMFs are robust enough for above ground contact outdoor applications of wood, where permanent wetness cannot be avoided according to Use Class 3.2, as per the EN 335 (2013) standard. Also, they pose a low risk to human health and the environment because they are sparingly soluble. Since NMFs significantly reduce the decay of wood, the CO2 fixed in it will be retained for longer than in unpreserved wood. Overall, the novel results of this study show the potential of NMFs to increase the service life of building materials made from non-durable wood.
Air-coupled ultrasonic testing is widely used in the industry for the non-destructive testing of compound materials. It provides a fast and efficient way to inspect large concrete civil infrastructures for damage that might lead to catastrophic failure. Due to the large penetration depths required for concrete structures, the use of traditional piezoelectric transducer requires high power electric systems. In this study, a novel fluidic transducer based on a bistable fluidic amplifier is investigated. Previous experiments have shown that the switching action of the device produces a high-power broadband ultrasonic signal. This study will provide further insight into the switching behaviour of the fluidic switch. Therefore, parametric CFD simulations based on compressible supersonic RANS simulations were performed, varying the inlet pressure and velocity profiles for the control flow. Switching times are analyzed with different methods, and it was found that These are mostly independent of the slope of the velocity profile at the control port. Furthermore, it was found that an inversely proportional relationship exists between flow velocity in the throat and the switching time. The results agree with the theoretical background established by experimental studies that can be found in the literature.
Classification of Spot-Welded Joints in Laser Thermography Data Using Convolutional Neural Networks
(2021)
Spot welding is a crucial process step in various industries. However, classification of spot welding quality is still a tedious process due to the complexity and sensitivity of the test material, which drain conventional approaches to its limits. In this article, we propose an approach for quality inspection of spot weldings using images from laser thermography data. We propose data preparation approaches based on the underlying physics of spot-welded joints, heated with pulsed laser thermography by analyzing the intensity over time and derive dedicated data filters to generate training datasets. Subsequently, we utilize convolutional neural networks to classify weld quality and compare the performance of different models against each other. We achieve competitive results in terms of classifying the different welding quality classes compared to traditional approaches, reaching an accuracy of more than 95 percent. Finally, we explore the effect of different augmentation methods.
The applicability of three methods developed by finite element analysis (FEM) and proposed in the literature are studied on steel S355. Instrumented indentation tests using spherical indenters of radius 200 and 500 μ m are performed in the macro range at depths of more than 6 μ m. The results of the selected methods are compared with the tensile test. To evaluate the partially strongly varying results, the uncertainties of the calculated strain hardening exponent, n, and yield stress, Y, are estimated. Recommendations for an appropriated procedure of the indentation test are given. The machine compliance and the determination of the zero point of Depth play an essential role. If the certain conditions are considered, the instrumented indentation Tests can be used, in particular for investigations of specimens with inhomogeneous elastoplasticity.
The literature has shown that the application of laminography provides advantages as 3D radiographic imaging with depth information for in house and mobile testing. This permits to distinguish between overlapping indications, measure the extension along radiation direction and classify indications as surface open or subsurface
ones as required in critical engineering assessment. This work provides a comparative study and measurements of the three techniques Digital Radiography (DR) with Digital Detector Arrays (DDA), Coplanar Translational Laminography (CTL) and Computed Tomography (CT), applied for composite pipeline inspection. It is demonstrated that CTL and CT provide advantages for the evaluation of pipe-to-pipe connections and the evaluation of adhesive applications. They show indications of discontinuities with higher contrast sensitivity than radiography.
Beyond it, two specimen, namely Phantom 1 and Phantom 2, were developed and manufactured by additive manufacturing to analyze the preferential detection sensitivity and the direction of features and depth information for laminographic measurements. Another goal was to show the laminographic capabilities to distinguish between overlapping discontinuities. CTL is especially suitable for mobile inspection. Special glass fiber reinforced polymer samples (GRP) were manufactured for further analysis and comparisons between the abovementioned techniques. Finally, Phantoms 1 and 2 show the capability of laminography to detect overlapping indications and also show that discontinuities oriented perpendicular to the scan direction have the highest contrast sensitivity for laminographic measurements.
Experimental analysis of the acoustic field of an ultrasonic pulse induced by a fluidic switch
(2021)
Ultrasonic inspection is a common tool for non-destructive testing in civil engineering (NDT-CE). Currently, transducers are coupled directly to the specimen surface, which makes the inspection time-consuming. Air-coupled ultrasound (ACU) transducers are more time-efficient but need a high pressure amplitude as the impedance mismatch between the air and the concrete is high and large penetration depth is needed for the inspection. Current approaches aim at eliminating the impedance mismatch between the transducer and the air to gain amplitude; however, they hardly fulfill the NDT-CE requirements. In this study, an alternative approach for ultrasound generation is presented: the signal is generated by a fluidic switch that rapidly injects a mass flow into the ambience. The acoustic field, the flow field, and their interaction are investigated. It is shown that the signal has dominant frequencies in the range of 35–60 kHz, and the amplitude is comparable to that of a commercial ACU transducer.
The competitiveness of the process industry is based on ensuring the required product quality while making optimum use of equipment, raw materials and energy. Chemical companies have to find new paths to survive successfully in a changing environment, while also finding more flexible ways of product and process development to bring their products to market more quickly – especially high-quality high-end products like fine chemicals or pharmaceuticals. The potential of digital technologies belongs to these.
One way is knowledge-based production, taking into account all essential equipment, process and regulatory data of plants and laboratories. Today, the potential of this data is often not yet consistently used for a comprehensive understanding of production. Another approach uses flexible and modular chemical plants, which can produce different high-quality products using multi-purpose equipment with short downtimes between campaigns and reduce the time to market of new products. Digital transformation is enabling completely new production concepts that are being used increasingly. Intensified continuous production plants also allow for difficult to produce compounds.
This contribution aims to encourage a more holistic approach to the digitalization and use of machine-assisted methods in (bio) process engineering by introduction of integrated and networked systems and processes, which have the potential to speed up the high-quality production of specialty chemicals and pharmaceuticals.
Irrespective of the experimental care used to acquire Computed Tomography Data, certain artifacts might still exist such as: Noise, Blurring, Ring Artifacts etc. To tackle this problem, a complete multi-level framework employing AI (Deep Artificial Neural Nets), targeting specific artifacts individually, is presented. The goal is to render the data suitable for subsequent unproblematic segmentation without any loss of information, compared to manual conditioning with traditional filters.
The strategy can therefore be used to acquire faster CT data (e.g. in-situ investigations) and ensure legacy with existing data obtained, perhaps, on older instruments.
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.
This paper studies the dispersion of GPR wave’s phase velocity at different wideband frequencies in plywood and concrete with varying moisture content. This study makes use of two GPR antennas with 2 GHz centre frequency operating in wide angle reflection and refraction (WARR) mode and with computation of spectral analysis of the surface wave (SASW). Computation of phase velocities is based on the Acquisition of the cross-power spectrum and phase unwrap of two distorted ground waves at positions Closer to and farther away from the transmitting antenna. The velocities of the ground waves are found to experience greater dispersion in low frequency regimes within the effective frequency bandwidths determined and thresholded by time–frequency analysis (TFA) and coherence plotting of the ground waves.
This study validates not only the methodology, but also identifies the optimal distance between the first (Rx1) and second (Rx2) receivers as k/2, which is based on a fixed transmitter (Tx) minus the first Receiver (Rx1) distance. It serves as an indication of changeable separation distance when other lower frequency GPR is used because the distances of Tx-Rx1 and Rx1-Rx2 are wavelength dependent and thus also frequency dependent. Effects of moisture contents and chloride contamination in concrete were also characterized according to the dispersion plots . that wave traelling in lower frequencies in GPR wave is much decelerated than that in higher frequencies. This research also contributes to the building of the ‘‘GPRWARR machine” suggested in Annan and Jackson (2017) [1], within which the effects of wave Dispersion on phase velocity can be inversely modelled to characterize variations in the material properties of infrastructure as a means of detecting surface damage.
Since nuclear magnetic resonance with focus on 1H protons is highly sensitive to pore filling fluids, it is nowadays often applied for the investigation of porous media. Mainly in materials research and especially in the field of non-destructive testing in civil engineering it is increasingly used. Scientific questions about and based on NMR meanwhile cover a broad spectrum. To give an overview, we have reviewed various studies dealing with the determination of moisture contents and parameters such as the pore-size distribution, surface relaxivity, porosity, etc. In some papers, the monitoring of moisture transport in connection with degradation processes or admixtures was the main objective. In other papers, NMR was used for pore space analysis or even applied on site to assess the state of conservation of cultural heritage. Building materials that have been investigated in the presented studies are for example cement, concrete, woods, sandstones etc. In this paper, short descriptions and the significant results of the reviewed articles are summarized and their measurement problems and discrepancies are pointed out. A special feature of this review article is the concise tabular compilation of determined 𝑇1 and 𝑇2 relaxation times, as well as of surface relaxivity values for various materials and components. Finally, relevant aspects are summed up and conclusions about the increasing potential of NMR relaxometry for investigations of porous building materials are drawn, followed by an outlook about future applications and the need for technical development.
After a general presentation of the beamline, specifically the workflow for ex-situ CT at BAMline is presented. Although being used in a broad variety of research fields the usual workflow for CT experiments is in most cases similar in terms of sample mounting, tomographic scan and reconstruction. Specific scanning schemes allow for a preview reconstruction carried out during the scan. A detailed description of the used hardware as well as the self-coded programs applied in the data pipeline will be given. This will be accompanied by a practical demonstration of the software involved in the entire process.
After a general presentation of the beamline, specifically the workflow for ex-situ CT at BAMline is presented. Although being used in a broad variety of research fields the usual workflow for CT experiments is in most cases similar in terms of sample mounting, tomographic scan and reconstruction. Specific scanning schemes allow for a preview reconstruction carried out during the scan. A detailed description of the used hardware as well as the self-coded programs applied in the data pipeline will be given. This will be accompanied by a practical demonstration of the software involved in the entire process.
Frass (fine powdery refuse or fragile perforated wood produced by the activity of boring insects) of larvae of the European house borer (EHB) and of drywood termites was tested as a natural and novel feedstock for 3D-printing of wood-based materials. Small particles produced by the drywood termite Incisitermes marginipennis and the EHB Hylotrupes bajulus during feeding in construction timber, were used. Frass is a powdery material of particularly consistent quality that is essentially biologically processed wood mixed with debris of wood and faeces. The filigree-like particles flow easily permitting the build-up of woodbased structures in a layer wise fashion using the Binder Jetting printing process. The Quality of powders produced by different insect species was compared along with the processing steps and properties of the printed parts. Drywood termite frass with a Hausner Ratio HR = 1.1 with ρBulk = 0.67 g/cm3 and ρTap = 0.74 g/cm3 was perfectly suited to deposition of uniformly packed layers in 3D printing. We suggest that a variety of naturally available feedstocks could be used in environmentally responsible approaches to scientific material sciences/additive manufacturing.
High quality tubular products are essential to the oil and gas industry. Quality control during their production focuses on the non-destructive detection of surface defects. The structured light technique is a candidate for the challenge to detect, monitor and evaluate such defects in real-time.
In the present study the automatic processing of structured light measurements is performed and validated. The algorithm for the automatic Analysis of inspection data has an advantage over current data evaluation methods based on individual assessments of operators.
With a goal to improve our understanding of the relationships between microstructural features and ultrasonic signal behavior, concrete specimens of varying water-to-cement ratio were imaged using X-ray computed tomography (CT), and subsequently subjected to ultrasonic testing. From the CT scans, measurements were made of cement paste density and number of interfaces. Ultrasonic signals produced using a through-transmission configuration were analyzed and fit to a diffusion model to separate absorption from scattering attenuation. The results showed that at the frequencies tested, ultrasonic dissipation rate correlated weakly with paste density, while diffusivity correlated well with number of interfaces, but only if entrained air is considered separately. Cement paste density was found to be very well predicted by diffusivity, leading to a clear power-law relationship between diffusivity and compressive strength.
When applying Ground Penetrating Radar (GPR) to assess the moisture content of building materials, different medium properties, dimensions, interfaces and other unknown influences may require specific strategies to achieve useful results. Hence, we present an overview of the various approaches to carry out moisture measurements with GPR in civil engineering (CE). We especially focus on the applied Signal features such as time, amplitude and frequency features and discuss their limitations. Since the majority of publications rely on one single feature when applying moisture measurements, we also hope to encourage the consideration of approaches that combine different signal features for further developments.
News from NDT@BAM
(2021)
The presentation summarizes some recent research at BAM in the field of NDT in civil engineering. the firste xample decribes lab experiments on the degardation of concrete during tunnel fires. Radar measuremenst were sucessfully used to detect interior damage. The second example decribes the first ever experiment on using muon imaging to evaluate concrete constructions.
Reinforced concrete bridges are iconic parts of modern infrastructure. They are designed for a minimum service life of 100 years. However, environmental factors and/or inappropriate use might cause overload and accelerate the deterioration of bridges. In extreme cases, bridges could collapse when necessary maintenance lacks. Thus, the permanent monitoring for structure health assessment has been proposed, which is the aim of structural health monitoring (SHM). Studies in laboratories have shown that ultrasonic (US) coda wave interferometry (CWI) using diffuse waves has high sensitivity and reliability to detect subtle changes in concrete structures. The creation of micro-cracks might be recognized at an early stage. Moreover, large-volume structures can be monitored with a relatively small number of US transducers. However, it is still a challenge to implement the CWI method in real SHM practical applications in an outdoor environment because of the complex external factors, such as various noise sources that interfere with the recorded signals. In this paper, monitoring data from a 36-m long bridge girder in Gliwice, Poland, instrumented with embedded US transducers, thermistors, and vibrating wire strain gauges, is presented. Noise estimation and reductionmethods are discussed, and the influence of traffic, as well as temperature variation, are studied. As a result, the relative velocity variation of US waves following the temperature change with a very high precision of 10−4% is shown, and a good bridge health condition is inferred. The influence of lightweight real traffic is negligible. The study verified the feasibility of the implementation of the CWI method on real bridge structures.
The evaluation of measurement uncertainty is essential for testing and calibration laboratories. This paper provides a general process description for the determination of the measurement uncertainty of quantitative data and its application to the conformity assessment with examples, and how to deal with the uncertainty of qualitative (Boolean) results, e. g. when "Alarm" or "No alarm" occours in an instrument display.
Subfloors are layered structures, consisting largely of porous building materials, such as screed. They are often suffering damage from tap water leakage, which is a typical problem in buildings, and which has largely contributed to repair costs of almost 3 billion Euro in 2018 alone in Germany. In this context, especially mould plays a role, which is both destroying the structure and posing severe health risks.
To determine the damaging effects of moisture, it is necessary to know the respective processes occurring in building materials, especially to quantify the amount of moisture and its progress in the material. In this study, humidity sensors are used to derive the material moisture experimentally.
Capacitive sensors recording the relative humidity are embedded into the screed and in the insulation materials such as expanded polystyrene, extruded polystyrene, perlite and glass wool. For the application in screed, the sensors need to be shielded against the aggressive alkaline materials. To ensure an appropriate exchange with the environment, a permeable membrane is requested. Different membrane materials have been investigated regarding their robustness and their permeability.
In the first experimental setup, two humidity sensor arrays with seven individual sensors are embedded in homogeneous screed samples. The measured corresponding relative humidity of the screed is converted to the material moisture based on the approach of Hillerborg. In a second experimental setup, a layered structure of a complete subfloor is built in a box of 0.8 m times 0.8 m. The humidity sensors are positioned in the different insulation materials of various thicknesses. By adding water, leakage damage is simulated and its progress and effect is investigated experimentally.
The investigations point at the question if the observed moisture is able to generate damage such as mould. The moisture and corresponding humidity values are discussed. It will be shown that this low-cost hygrometric approach can be used easily for moisture monitoring of screed and insulation materials as well
The purpose of this contribution is to introduce and to apply the developed approach of incorporating non-destructively gathered measurement results (instead of deterministic information and assumptions) into a reassessment model of a typical prestressed concrete road bridge and to outline the advantages. An essential part is the quality evaluation of the non-destructively measured information, that deals primarily with two questions. Could the object or parameter to be obtained reliably detected and if, how accurate are the inspection results achieved? Therefore, the importance of the combination of a probability of detection (POD)-approach and measurement uncertainty calculations is emphasized. With regard to the introduced case-study it is shown, for which structure parameters an assumption deviating from the actual (and measurable) situation has a particularly strong (and possibly arithmetically unfavorable) influence on the structural reliability. Measurements on such parameters are particularly beneficial for a reliable and robust reassessment. In conclusion, the individual reassessment results without consideration and with consideration of evaluated non-destructive inspection results are compared.
The dispersive properties of Lamb waves can be utilised for material characterisation because the frequency-wavenumber-relationship, as well as the group velocity, depend on material parameters. These dependencies make a non-destructive estimation of an elastic constant possible. This preliminary study investigates the sensitivity of dispersion curves caused by a change in elastic constants. The Scaled Boundary Finite Element Method is used to compute special dispersion curves, which show the sensitivity value of the frequency and group velocity as a colour value. This representation allows for easy identification of patterns and local effects. Two sets of dispersion curves are presented, one set for a steel plate and the other set for a plate made of a carbon fibre reinforced polymer. In general, we notice that the sensitivity often increases with the frequency and that higher-order modes seem to be more suitable for material characterisation. Moreover, specific modes respond to material changes while others are relatively unaffected, which must be taken into consideration for material characterisation.