Elastic Wave Signals Research Articles

The acoustic Galton board

Phononic crystals are a class of materials with periodic structures that influence the propagation characteristics of acoustic waves through periodically arranged structural units. Here, we have developed the acoustic Galton board (AGB), a groundbreaking apparatus that serves as a cost-effective and user-friendly tool for demonstrating phononic crystal properties such as band gaps, Bragg scattering, and local resonance. The device comprises an elastic wave signal generator, an enhanced Galton board featuring a sophisticated pillar-nail array, and a signal receiver. The experimental results we have obtained demonstrate the significant impact of the AGB on elastic wave dispersion, effectively creating bandgaps that impede wave transmission within specific frequency ranges while allowing unhindered propagation in others. Furthermore, the AGB can simulate phononic crystals using both the Bragg scattering mechanism, achieved through the design of periodic rigid pillar-nail arrays, and the locally resonant mechanism, facilitated by the design of pillar-nail arrays with composite material structures. Additionally, the AGB can extend its applications to serve as a simulation tool for elastic metamaterials.

Detection of Hot Cracking for 6000 Series Aluminum Alloys using a Multi-Sensor Based Deep Learning Model

This study developed a monitoring technology using a multi-sensor based deep learning model to diagnose hot cracking in aluminum alloy laser welding. Hot cracking that occurs during the laser welding process of aluminum alloys is difficult to diagnose accurately with a single sensor signal, necessitating multi-sensor based process monitoring technology. To monitor these hot cracks, laser-induced plasma, acoustic, and elastic wave signals were simultaneously measured using a spectrometer, non-contact acoustic sensor, and contact acoustic sensor during the overlap laser welding process of 6000 series aluminum alloys. The welded specimens were classified into normal and cracked specimens through bead analysis, and features related to hot cracking were extracted from each sensor signal to utilize the measured multi-sensor signals for monitoring. The extracted features from each signal were used as inputs for a Deep Neural Network (DNN) model capable of learning complex nonlinear relationships, and the hyperparameters of the DNN model were optimized using a genetic algorithm. The DNN model trained with multi-sensor data diagnosed hot cracking with an accuracy of 93.75%.

Reconfigurable directional selective tunneling of p-type phonons in polarized elastic wave systems

There have been many studies on the ground state of phononic crystals, but few studies on the nature of the excited state. In this paper, we introduce the asymmetric Klein tunneling method in phononic systems, which enables selective direction and control of elastic waves by inducing polarization through an external field in an artificial barrier. Using tight-binding theory, we systematically studied phononics in a super-honeycomb structure, demonstrating the anisotropic transition properties of excited state phonons through a matrix model involving the ground state’s s-type and the first excited state’s p-type wave functions. Additionally, we exploit the thermal sensitivity of epoxy to achieve localized thermal field-induced distortion of the bottom flat band, forming a tiled Dirac cone, and thereby creating a reconfigurable polarized artificial barrier in the elastic wave system. Elastic waves propagate in these systems with topological charge conservation. Combining this with the theoretical of excited-state phonons, we demonstrate asymmetric Klein tunneling with directional selectivity in the elastic wave carriers, and systematically investigate the performance of this tunneling. Furthermore, we design a four-port elastic waveguide based on the principle of asymmetric tunneling, which achieves exceptional directional selectivity of elastic wave signals by adjusting the polarization direction of barriers at the junctions. These studies not only extend the application of Klein tunneling in elastic wave systems but also open new research avenues for the study of elastic wave devices controlled by various external fields, showing direct application potential in elastic wave signal processing.

Broadband vibration isolation in cylindrical shells embedded with total reflection elastic meta-shells

In this research, we propose a pioneering conceptual design paradigm of elastic meta-shells for broadband elastic wave control in cylindrical shells. We theoretically reveal the mechanism for wave isolation in cylindrical shells, which arises from the closure of all transmission channels (i.e., total reflection) when 0th-order diffraction is the only remaining diffraction mode. In addition, to solve the dynamic coupling behavior between multi-order diffraction modes, we extend the acoustic mode-coupling theory to elastic waves in cylindrical shells. Based on the diffraction theory and multiple reflection effect, we construct a total reflection elastic meta-shell and numerically demonstrate efficient broadband elastic wave isolation in the frequency range of 5 k–7 kHz. Finally, the vibration isolation performance is experimentally verified by embedding a total reflection elastic meta-shell in a finite thin-walled cylindrical shell waveguide. Results confirm the feasibility of the elastic meta-shell design concept and its ability to achieve fully passive, high-efficiency, and broadband vibration isolation. Our vibration isolation strategy could broaden the applicable scope of elastic meta-structures and open new horizons for vibration isolation, mechanical energy filtering, and elastic wave signal processing in cylindrical shells.

Weakened by an infinite system of transverse periodic cracks piezoelectric waveguide as a filter of electroacoustic waves

Abstract The problem of propagation of an electroactive unidirectional elastic shear wave signal in an infinite piezoelectric waveguide weakened by a periodic system of transverse cracks is considered. Wave formation is investigated in cases of different anisotropies of the piezoelectric material, under different electromechanical conditions on the waveguide surfaces. In contrast to the case of a homogeneous waveguide, the presence of a system of periodic cracks leads to the formation of Floquet waves with a periodic structure. Different anisotropies and asymmetric electromechanical conditions on the waveguide surface lead to different localization of wave energy over the thickness of the waveguide, as well as to the presence of different zones of acceptable frequencies. A comparative analysis of the influence of the presence of a periodic system of transverse cracks on the frequency transmittance of the waveguide is carried out.

Discrete element method modelling of elastic wave propagation in a meso-scale model of concrete

This paper deals with the accurate modelling of ultrasonic wave propagation in concrete at the mesoscopic level. This was achieved through the development of a discrete element method (DEM) model capable of simulating elastic wave signals comparable to those measured experimentally. The main objective of the work was to propose a novel methodology for constructing a meso-scale model of concrete dedicated to the analysis of elastic wave propagation. All the material parameters necessary to prepare a numerical DEM model of concrete at the mesoscopic level were explored and explained. Calibration of the mechanical parameters of the DEM model to match the experimental values involved linking the local, micro-parameters between particles with the global response of the whole sample. The developed numerical model was further used to simulate the propagation of elastic waves in a cubic concrete sample, in the frequency range of 100–500 kHz. The results of the DEM calculations showed good agreement with the experimental ultrasonic signals.

Detection of interface states in an elastic plate using laser ultrasonic technology

An interface state of elastic waves in mirror-symmetric structured waveguides has been detected using laser ultrasonic technology. In antisymmetric periodic waveguides, the resonance coupling of different transverse guided modes can lead to a non-Bragg gap in the frequency domain. When two antisymmetric periodic waveguide structures with mirror-symmetry properties are combined, the elastic waves resonate locally at the connection, resulting in an observable elastic wave interface state. Simulations and experimental measurements confirm the generation of additional modes in the non-Bragg gap, giving rise to the interface states of the elastic waves. In addition, we examine the frequency shift mechanism of the interface states and find that the frequency of the interface state linearly depends on the connection length at the center of the waveguide. The discovery of interface states in mirror-symmetric elastic waveguides and their regulation provides important theoretical guidance for designing and preparing elastic waveguide structures. These have broad application prospects in elastic wave signal detection, modulation, and filtering.

Achromatic ribbed elastic meta-structure for ultra-broadband flexural wave manipulation

Elastic metasurfaces have shown remarkable ability in exotic wavefront manipulations based on the generalized Snell’s law (GSL), stimulating great promise for many potential applications, such as elastic wave signal processing, vibration control, and energy harvesting. However, elastic metasurfaces suffer from strong narrow-band confinement and dispersion modulation due to the inherent velocity-dispersive properties and the dispersion of the accumulated phase during propagation. To address this issue, we propose a novel conceptual design paradigm of achromatic ribbed elastic meta-structures (AREMs) beyond the narrow-band limit for the ultra-broadband manipulation of flexural waves in thin plates. We establish an analytical model for ribbed subunits to accurately solve the phase shift and amplitude of the transmitted waves. In addition, we reveal the relationship between broadband achromatic functionality and subunit phase shift dispersion. We theoretically design and numerically demonstrate three flexural wave manipulation functionalities in an ultra-broadband frequency range of 1–10 kHz, including flexural wave deflection, focusing, and splitting, with a relative bandwidth of 163.6 %. Finally, we experimentally verify the ultra-broadband flexural wave manipulation capabilities of AREMs. Our study may open new horizons for ultra-broadband high-efficiency achromatic and structurally simplified flexural wave-based devices, with promising extensions to other elastic wave modes.

Architecture Prediction of 3D Composites Using Machine Learning and No‐Destructive Technique

AbstractThe field of composites has seen a surge in the adoption of machine learning techniques due to their ability to achieve once unattainable goals. Presently, machine learning research in composites primarily centers around predicting composite properties or optimizing microstructures to attain specific properties. This paper presents a data‐driven approach to predict the complete architecture of composites. A multi‐output machine learning model, based on conventional XGBoost algorithms, is developed to comprehend the intricate correlation between composite architecture and elastic wave propagation in them. The machine learning model uses input elastic wave signals collected at one face of the composite cube, induced by an actuator on the opposite face of the cube, as features. The composition labels are 3D matrices that represent the architectures of the composite cubes. The results show that the architecture of composites can be predicted using a short period of elastic wave travel through the composites, with up to 96% accuracy. This method can be readily adapted and implemented for any industry application requiring the determination of the architecture of unknown composites without destruction.

Electromagnetic pulse-induced acoustic testing enables reliable evaluation of debonding between rebar and concret

An electromagnetic Pulse-Induced Acoustic Testing (EPAT) method was investigated for evaluating debonding between rebar and concrete. Debonding specimens were prepared by wrapping polystyrene foam around a rebar to induce debonding between the concrete and rebar. An acoustic emission sensor was placed on the concrete specimen surface to collect elastic wave signals. A powerful pulsed electromagnetic force was applied to the specimens and the elastic waves of the rebar were analyzed. By comparing the differences in signal reach time of the elastic waves between specimens with and without a debonding, it was demonstrated that EPAT is useful for non-destructive evaluation of debonding. Finite element simulations were also conducted, validating the reliability of EPAT for examining debonding in reinforced concrete.

Arrival-time detection with histogram distance for acoustic emission signals

Arrival-time picking is a fundamental step in time-of-arrival (TOA)-based localisation in current and future acoustic emission (AE), microseismic and seismic localisation systems. The accurate detection of TOA is of great importance for high localisation accuracy. This work presents a histogram distance-based method for TOA detection of elastic wave signals. The authors treat an original elastic waveform that includes the arrival as two different locally stationary segments, namely the intervals following and preceding arrival. To determine the optimal separation of these two stationary segments, ie the arrival time, histograms of these intervals are calculated and a measure of the distance between them modified from the Bhattacharyya coefficient is proposed. The performance of the proposed method is evaluated using TOA picking for AE. The method is shown to provide accurate and robust picks on AE signals under various signal-to-noise ratios. To evaluate the adaptability of the method to other TOA picking scenarios, it is applied to detect the seismic P-phase. The detection accuracy is adequate and errors are constrained to within a few seconds. Factors that influence the detection accuracy are discussed. The results suggest that the proposed method has the potential to detect TOA in various fields.

Passive seismic monitoring in conventional tunnelling – An innovative approach for automatic process recognition using support vector machines

For the underground construction sector as in conventional tunnelling, there is still a lack of automatization and digitalization progresses, especially concerning tunnel construction monitoring. A manual documentation of the time intervals for subsequent processes by the respective employee is currently state of the art. This study addresses a cost and time effective data acquisition and evaluation method using conventional geophones for the differentiation of the processes involved in tunnel construction by analysis of elastic wave signals. The field experiments were executed at the construction site of “Zentrum am Berg” in Austria where seismic signals were recorded during the conventional tunnel excavation process. The seismic emissions induced by the respective machinery during different constructuon steps are distinguished with a machine learning approach using support vector machines, leading to the possibility of associating them with the corresponding time of the machinery in use. The semi-automatic evaluation of the gathered data should facilitate the documentation of the daily working diagrams, supplement project management and effective planning and optimize predictive maintenance possibilities in the underground construction industry.

Impact of diatoms on the load-deformation response of marine sediments during drained shear: Small-to-large strain stiffness

A comprehensive characterization of the seafloor is difficult, as natural marine sediments comprise granular materials. In particular, the presence of diatoms in granular mixtures significantly alters the engineering properties and behavior. Herein, we investigate the critical role of diatoms in the load-deformation response, shear strength, and small-to-large strain stiffness in sand-silt-diatom mixtures during the drained shear process. Mixtures with different fines contents (FCs) of 0%, 10%, 20%, and 30% were prepared in a triaxial cell incorporated with bender and piezo disk elements for elastic wave measurements. Triaxial tests were conducted under four different confining effective stresses, and elastic wave signals were monitored at every 0.5% of the axial strain. Test results show that a distinct transition exists in the stress-strain response and shear strength characteristics at FC = 20%. Using volumetric gravimetric analysis, we could clearly anticipate percolation threshold FC, where the specimen with 20% FC appeared to be on the boundary between the sand-controlled and transition zones in the textural triangular chart. For coarse-dominant mixtures (FC < 20%), silts enhanced particle interlocking and contributed to an increase in the contact area. In contrast, the internal friction of transitional mixtures (FC = 20%, 30%) decreased when a diatom with an excessively low shear modulus participated in load-carrying mechanisms. Using large-strain stiffness, we assessed fabric changes that reflect friction and the coordination number. Using small-strain stiffness from elastic waves, we estimated the state for a constant fabric. The characteristics of the moduli at large strain and those at small strain were distinctly different.

Accurate Prediction of Microstructure of Composites using Machine Learning

AbstractIn this prospective work, a machine learning (ML) model based on multiple independent random forest models to predict the configuration of binary composite bars is developed. The input variables to the ML model are elastic wave signals collected at one end of the composite bar, while the targets of the ML model are binary vectors representing the configuration of the bars. This study results indicate: First, a short period of elastic wave propagated through a composite bar can collect and carry the detailed information of the entire bar; second, the patterns hidden in the collected signals can be detected, extracted, and used by the ML model; finally, the ML model can be well trained using a relatively small dataset pool (less than 0.1% of all possible samples), and make accurate predictions. For the 30 sections of bars used in this study, the average prediction accuracy for each section of this bar can reach 95% and even higher. This ML guided technique can be modified and used in different functionalities and applications such as composites characterization, structure health monitoring, limestone determination, and archaeological detection.

Research on the Attenuation Characteristics of High-Frequency Elastic Waves in Rock-Like Material.

In order to study the frequency-dependent attenuation characteristics of high-frequency elastic waves in rock-like materials, we conducted high-frequency elastic wave attenuation experiments on marble, granite, and red sandstone rods, and investigated the frequency dependence of the attenuation coefficient of high-frequency elastic waves and the frequency dependence of the attenuation of specific frequency components in elastic waves. The results show that, for the whole waveform packet of the elastic wave signal, the attenuation coefficient and the elastic wave frequency have an approximate power relationship, with the exponents of this power function being 0.408, 0.420, and 0.384 for marble, granite, and red sandstone, respectively, which are close to 1/2 the exponent value obtained theoretically by the Kelvin–Voigt viscoelastic model. However, when the specific frequency components are tracked during the elastic wave propagation, the exponents of the power relationship between the attenuation coefficient and frequency are 0.982, 1.523, and 0.860 for marble, granite, and red sandstone, respectively, which indicate that the relationship between the attenuation coefficient and frequency is rock-type dependent. Through the analysis of rock microstructure, we demonstrate that this rock-type-dependent relationship is mainly caused by the scattering attenuation component due to the small wavelength of the high-frequency elastic wave. Therefore, the scattering attenuation component may need to be considered when the Kelvin–Voigt model is used to describe high-frequency elastic wave attenuation in rock-like materials. The results of this research are of good help for further understanding the attenuation characteristics of high-frequency elastic waves in rock-like materials.

Assessment of Wooden Beams from Historical Buildings Using Ultrasonic Transmission Tomography

ABSTRACT The main goal of this study was non-destructive evaluation of wooden elements using ultrasonic waves. The inspection was carried out on wooden beams from a historical object. Elastic wave signals were processed by ultrasonic transmission tomography to obtain imaging of the internal structure of tested elements without disturbing their state and integrity. The focus was on the influence of wood anisotropy on the propagation of ultrasonic waves. A novel method of determining the position of the cross-section pith was proposed. The study presented that the proposed imaging approach was capable to assess the technical condition of historic wooden beams by determining the degree of wood damage and the location of discontinuities, scratches or fibrosis in the tested cross-section.

Low-velocity impact source localization in a composite sandwich structure using a broadband piezoelectric sensor network

An online structural health monitoring strategy for real-time impact source localisation in composite sandwich structure (CSS) is presented in this paper. A broadband piezoelectric (PZT) sensor-network based laboratory experiments and finite element method based numerical simulations of low-velocity steel-ball drop impacts at different locations on a CSS have been carried out. It is observed that the arrival-time of the impact-induced elastic wave signals increases with the increase in source-to-sensor distance. Further, the influence of impactor drop-height variations is studied by conducting a series of numerical simulations in ABAQUS. An arrival-time difference calculation based impact source localisation strategy is proposed to locate the impact regions in the CSS. The proposed monitoring strategy uses the registered impact signals (time-domain) at the PZTs to predict impact locations in real-time. Eventually, a study on the estimation of localisation error has been carried out to check the effectiveness of the proposed SHM strategy.

Stochastically homogenized peridynamic model for dynamic fracture analysis of concrete

Dynamic compact tension tests in concrete are investigated using an intermediately-homogenized peridynamic (IH-PD) model, and the results are compared with a fully-homogenized peridynamic (FH-PD) model as well as with experimental data from the literature. In the IH-PD model, concrete is considered as a two-phase material composed of aggregate and mortar, partially homogenized via a stochastic procedure. Both the FH and IH-PD models capture well the experimentally measured reaction-force time-evolution and crack paths for a wide range of dynamic loading rates, without the need for an explicit representation of microstructure geometry of the concrete material or of rate-dependent parameters. The IH-PD model is more accurate than the FH-PD in reproducing the peak loads and produces crack path tortuosity and randomness, similar to what is observed experimentally. These benefits come from the preservation of some micro-scale heterogeneity, stochastically generated to match the concrete’s aggregate volume fraction. We also find that it matters where one measures the reaction force when trying to connect it to fracture and damage progression in the sample: only when measured on the dynamically loaded side of the pre-notch are features in the reaction-force profile matching critical moments like crack initiation, crack branching, and sample final failure. These results provide guidance for future experiments seeking best placement of damage detection sensors and using elastic wave signal analysis in structural health-monitoring of concrete structures.

Evaluation of Thawing and Stress Restoration Method for Artificial Frozen Sandy Soils Using Sensors.

Undisturbed frozen samples can be efficiently obtained using the artificial ground freezing method. Thereafter, the restoration of in situ conditions, such as stress and density after thawing, is critical for laboratory testing. This study aims to experimentally explore the effects of thawing and the in situ stress restoration process on the geomechanical properties of sandy soils. Specimens were prepared at a relative density of 60% and frozen at −20 °C under the vertical stress of 100 kPa. After freezing, the specimens placed in the triaxial cell underwent thawing and consolidation phases with various drainage and confining stress conditions, followed by the shear phase. The elastic wave signals and axial deformation were measured during the entire protocol; the shear strength was evaluated from the triaxial compression test. Monotonic and cyclic simple shear tests were conducted to determine the packing density effect on liquefaction resistance. The results show that axial deformation, stiffness, and strength are minimized for a specimen undergoing drained thawing, restoring the initial stress during the consolidation phase, and that denser specimens are less susceptible to liquefaction. Results highlight that the thawing and stress restoration process should be considered to prevent the overestimation of stiffness, strength, and liquefaction resistance of sandy soils.

Underwater low-velocity gas flow measurement based on passive acoustics with stable volume resolution

Underwater gas escape is widespread in the marine and industrial fields and the low-velocity gas caused by trace gas escape is difficult to be detected or measured. An underwater low-velocity gas flow measurement method based on passive acoustics with stable volume resolution is proposed in this paper. The elastic wave signal generated by the underwater gas is acquired by a hydrophone and filtered by the wavelet packet filtering method. The flow rate can be cumulatively estimated by the relationship between the bubble and the spectrum characteristics. The volume resolution of the bubble is stable, which is achieved by adjusting the signal frequency resolution. This method is adaptive to the processing of bubbles in different volumes. The stable volume resolution is helpful to reduce the random error for the cumulative continuous bubble volume estimation. Underwater gas leakage experimental platforms were established under laboratory conditions and lake conditions. The results show that the method has high accuracy and stability. For a single bubble and low-velocity flow conditions under laboratory conditions, the minimum error is 0.3% and the maximum error is 3.9% between 5 and 25 ml min−1. For the low-velocity flow under lake conditions, the minimum error is 0.8% and the maximum error is 8% between 10 and 60 ml min−1.