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This study investigates the non-destructive detection of delaminations in concrete plates using non-contact laser ablation, instead of the conventional hammer excitation, as part of the impact echo method. We performed tests on five concrete specimens of different sizes, two of which contained artificial delaminations. A range of steel ball hammers was used as reference impulse sources, the responses of which were compared with wave excitation generated by a 7 ns pulsed 1064 nm Nd:YAG laser with 150 mJ pulse energy. Signals were recorded by surface-mounted accelerometers and two contactless methods: microphones and a laser Doppler vibrometer. The laser generates frequencies across a broad range of frequencies (0 to 150 kHz) but with much less energy than the hammers' narrower frequency spectra; the laser pulse energy transferred into the specimen is 0.07 mJ, corresponding to about 0.5 ‰ of the impulse source energy. Because of this, the thick intact plates' characteristic thickness stretch resonance frequency can be reliably detected by the hammer excitations but not when using laser excitation. However, the laser can excite low-frequency flexural vibration modes over a shallow delamination at 3 cm depth. The low-frequency flexural vibration results are verified by numerical natural frequency analysis.
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.
The ultrasonic echo technique is frequently used in non-destructive testing (NDT) of concrete structures for thickness measurements, geometry determinations as well as localization of built-in components. To improve ultrasonic imaging of complex structures in concrete, we transferred a geophysical imaging technique, the reverse time migration (RTM), to NDT in civil engineering. In contrast to the conventionally used synthetic aperture focusing technique (SAFT) algorithms, RTM is a wavefield continuation method in time and uses the full wave equation. Thus, RTM can handle complicated wave propagations in any direction without dip limitation. In this paper, we focused on the application and evaluation of a two-dimensional (2D) elastic RTM algorithm considering compressional waves, vertically polarized shear waves, and Rayleigh waves. We tested the elastic RTM routine on synthetic ultrasonic echo data generated with a 2D concrete model consisting of several steps and circular air inclusions. As these complex structures can often be found in real-world NDT use cases, their imaging is especially important. By using elastic RTM, we were able to clearly reproduce vertical reflectors and lower edges of circular air voids inside our numerical concrete model. Such structures cannot be imaged with conventional SAFT algorithms. Furthermore, the used elastic RTM approach also yielded a better reconstruction of a horizontal reflector and upper boundaries of circular air inclusions. Our encouraging results demonstrate that elastic RTM has the potential to significantly improve the imaging of complex concrete structures and, thus, is a step forward for detailed, high-quality ultrasonic NDT in civil engineering.
Thanks to its good strength/mass ratio, a glass fibre reinforced plastic (GFRP) composite is a common material widely used in aviation, power production, automotive and other industries. In its turn, active infrared (IR) nondestructive testing (NDT) is a common inspection technique for detecting and characterizing structural defects in GFRP. Materials to be tested are typically subjected to optical heating which is supposed to occur on the material surface. However, GFRP composite is semitransparent for optical radiation of both visual and IR spectral bands. Correspondingly, the inspection process represents a certain combination of both optical and thermal phenomena. Therefore, the known characterization algorithms based on pure heat diffusion cannot be applied to semi-transparent materials. In this study, the phenomenon of GFRP semi-transparency has been investigated numerically and experimentally in application to thermal NDT. Both Xenon flash tubes and a laser have been used for thermal stimulation of opaque and semi-transparent test objects. It has been shown that the Penetration of optical heating radiation into composite reduces detectability of shallower defects, and the signal-to-noise ratio can be enhanced by applying the technique of thermographic signal reconstruction (TSR). In the inspection of the semi-transparent GFRP composite, the most efficient has been the laser heating followed by the TSR data processing. The perspectives of defect characterization of semi-transparent materials by using laser heating are discussed. A neural network has been used as a candidate tool for evaluating defect depth in composite materials, but its training should be performed in identical with testing conditions.
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.
In the rapidly expanding composite industry, novel inspection methods have been developed in recent years. Particularly promising for air-coupled testing are cellular polypropylene transducers which offer better impedance matching to air than piezoelectric transducers. Furthermore, broadband transmitters (laser-induced ultrasound and thermoacoustic emitters) and receivers (optical microphones) have opened a completely new chapter for advanced contact-free ultra-sound inspection. X-ray dark-field radiography offers a different approach to detect porosity and microcracks, employing small angle X-ray scattering. These innovative ultrasonic and radiographic alternatives were evaluated in comparison with well-established inspection techniques. We applied thirteen different non-destructive methods to inspect the same specimen (a carbon fiber-reinforced polymer laminate with induced impact damage): air-coupled ultrasound testing (using piezoelectric transducers, broadband optical microphones, cellular polypropylene transducers, and a thermoa-
coustic emitter), laser-induced ultrasound testing, ultrasonic immersion testing, phased array ultrasonic testing, optically excited lock-in thermography, and X-ray radiography (projectional absorption and dark-field, tomosynthesis, and micro-computed tomography). The inspection methods were qualitatively characterized by comparing the scan results. The conclusions are advantageous for a decision on the optimal method for certain testing constraints.
Thermally-induced moisture transport in high-performance concrete studied by X-ray-CT and 1H-NMR
(2019)
The thermohydraulic damage mechanism is one of the primary causes for explosive spalling of highperformance concrete. This paper presents the spatially- and temporally-resolved analysis of the thermally-induced moisture transport and reconfiguration processes by means of X-ray-CT and 1HNMR.
Thermal testing results for a high-performance concrete, which is sensitive to explosive spalling and which was prepared with and without added polypropylene fibres, are presented in this paper. These results indicate that the addition of fibres leads to a faster and deeper migration of the drying front and, thus, to a lower likelihood of vapour-pressure induced explosive spalling.
In this study, an Impulse Response Function analysis of pile response to sine-sweep excitation by a low cost, portable Shaker was used to identify defects in piles. In straightforward impact-echo methods, echoes from the pile toe and defects are visible in the time domain measurements. However, these echoes are not present in the time domain records of piles subjected to sine-sweep excitations, due to interactions between the input and output signals. For this reason, the impulse response function in the time domain has been calculated and is able to identify the echoes from pile impedance changes. The proposed methodology has been evaluated both numerically and experimentally. A one-dimensional pile-soil interaction system was developed, and a finite difference method used to calculate the pile response to sine-sweep excitation. The numerical simulations indicate that impulse response measurements with a synthesized logarithmic, sine-sweep excitation could be an effective tool for detecting defects in piles. The methodology was further tested with field trials on 6 cast in situ concrete test piles including 1 intact pile and 5 defective piles subjected to sine-sweep excitations by a shaker. In 5 of the 6 cases the echoes from the pile toe could be identified in the deconvoluted waveforms—the impulse Response functions. Damage detection is more difficult and dependent on the selection of the optimal regularization parameter. Further research and optimization of the deconvolution process is needed to evaluate the effectiveness compared to standard pile integrity testing methods.
For the first time, synchrotron X-ray refraction radiography (SXRR) has been paired with in-situ heat treatment to monitor microstructure and porosity evolution as a function of temperature. The investigated material was a laser powder bed fusion (LPBF) manufactured AlSi10Mg, where the initial eutectic Si network is known to disintegrate and spherodize into larger particles with increasing temperature. Such alloy is also prone to thermally induced porosity (TIP). We show that SXRR allows detecting the changes in the Si-phase morphology upon heating, while this is currently possible only using scanning electron microscopy. SXRR also allows observing the growth of pores, usually studied via X-ray computed tomography, but on much smaller fields-of-view. Our results show the great potential of in-situ SXRR as a tool to gain in-depth knowledge of the susceptibility of any material to thermally induced damage and/or microstructure evolution over statistically relevant volumes.
Uncertainty quantification of multimodal surface wave inversion using artificial neural networks
(2023)
An inversion of surface waves dispersion curves is a non-unique and ill-conditioned problem. The inversion result has a probabilistic nature, which becomes apparent when simultaneously restoring the shear wave (S-wave) velocity and layer thickness. Therefore, the problem of uncertainty quantification is relevant. Existing methods through deterministic or global optimization approaches of uncertainty quantification via posterior probability density (PPD) of the model parameters are not computationally efficient since they demand multiple solutions of the inverse problem. We present an alternative method based on a multi-layer fully connected artificial neural network (ANN). We improve the current uni-modal approach, which is known from publications, to multi-modal inversion. The learned ANN maps the phase velocity dispersion curves to values of the S-wave velocity and layers thickness. To estimate the uncertainties, we adapt the Monte-Carlo simulation strategy and project onto the resulting velocity model both frequency-dependent data noise and inverse operator errors, which are evaluated by the prediction of the training data set. The proposed combination of surface waves data processing methods, configured with each other, provides a novel surface waves multi-modal dispersion data inversion and uncertainty quantification approach. We first test our approach on synthetic experiments for various velocity models: a positive velocity gradient, a low-velocity layer and a high-velocity layer. This is done considering uni-modal inversion at first and then compared to the multi-modal inversion. Afterwards, we apply our approach to field data and compare resulting models with the body S-wave processing by the generalized reciprocal method (GRM). The experiments show high-potential results using ANN yields the possibility to accurately estimate PPD of restored model parameters without a significant computational effort. The PPD-based comparison demonstrates advantages of a multi-modal inversion over uni-modal inversion. The trained ANN provides reasonable model parameters predictions and related uncertainties in real-time.