Wave Characteristics Research Articles

In vivo imaging and computational modeling of nonlinear shear waves in living skeletal muscles

How the state of living muscles modulates the features of nonlinear elastic waves generated by external dynamic loads remains unclear because of the challenge of directly observing and modeling nonlinear elastic waves in skeletal muscles in vivo, considering their active deformation behavior. Here, this important issue is addressed by combining experiments performed with an ultrafast ultrasound imaging system to track nonlinear shear waves (shear shock waves) in muscles in vivo and finite element analysis relying on a physically motivated constitutive model to study the effect of muscle activation level. Skeletal muscle was loaded with a deep muscle stimulator to generate shear shock waves (SSWs). The particle velocities, second and third harmonics, and group velocities of the SSWs in living muscles under both passive and active states were measured in vivo. Our experimental results reveal, for the first time, that muscle states have a pronounced effect on wave features; a low level of activation may facilitate the occurrence of both the second and third harmonics, whereas a high level of activation may inhibit the third harmonic. Finite element analysis was further carried out to quantitatively explore the effect of active muscle deformation behavior on the generation and propagation of SSWs. The simulation results at different muscle activation levels confirmed the experimental findings. The ability to reveal the effects of muscle state on the features of SSWs may be helpful in elucidating the unique dynamic deformation mechanism of living skeletal muscles, quantitatively characterizing diverse shock wave-based therapy instruments, and guiding the design of muscle-mimicking soft materials.

Cumulative second harmonic Lamb wave generation and propagation in composite laminates: an insight into the influence of material anisotropy and damping

Significant strides have been taken in the structural design of fibrous composites in recent decades. Early detection of material degradation and damage in such materials is crucial for various industrial applications, yet poses challenges. Second harmonic Lamb waves have demonstrated their superior sensitivity to microstructural defects, making them an effective tool for structural health monitoring (SHM). However, understanding of the second harmonic Lamb wave generation and propagation in composite laminates remains inadequate due to the complexities introduced by material anisotropy and damping, which impede the practicality of SHM applications. This study investigates the cumulative second harmonic Lamb waves in composite laminates at low frequencies, considering both material anisotropy and damping. Theoretical analyses were carried out to explore how anisotropy and damping affect the generation and propagation of second harmonic Lamb waves. A nonlinear material constitutive model was proposed. It was used to conduct numerical simulations that verified the properties of second harmonic Lamb wave generation and propagation at different wave propagation angles, with a focus on the cumulative effect. Experiments were carried out to further validate the properties of the second harmonic Lamb waves in a carbon fiber reinforced panel. The findings indicate that the Lamb waves propagating at 0° showcase exceptional cumulative effect, rendering them suitable for SHM applications. Additionally, material damping induces a cumulative second harmonic Lamb wave with an initial increase followed by a decrease, creating a predictable “sweet” zone of larger amplitude that is easy to measure for SHM applications. The elucidation of the generation and propagation characteristics of the second harmonic Lamb waves provides guidance for structural damage detection and monitoring applications.

Simulation of ideal blackbody based on multi-space boundary condition in FDTD

Abstract Investigation shows that it is difficult to solve the electromagnetic field surrounding an ideal blackbody using the analytic method. To solve this problem, the simulation method should be adapted, and the Maxwell function should be expanded to multi space. In this paper, a multi space simulation scheme of finite difference time domain (FDTD) and a multi space boundary condition (MSBC) are proposed for the simulation of an ideal blackbody. Compared with the traditional absorbing boundary condition (ABC) or perfectly matched layer (PML), which can only be assigned in the outermost layers of the simulation space, the proposed MSBC is simpler and can be arranged inside the computing space. Numerical simulation shows that MSBC has good electromagnetic wave absorption performance and can simulate the ideal blackbody accurately. At the same time, the simulation results also show some interesting characteristics of electromagnetic waves around the ideal blackbody.

Panamax cargo-vessel excessive-roll dynamics based on novel deconvolution method

This study presents a state-of-the-art extreme-value-prediction methodology based on deconvolution that can be utilized in marine, offshore, and naval-engineering applications. First, a measured gust-windspeed dataset is utilized to illustrate the accuracy of the deconvolution method. Second, a real-time roll dynamics raw dataset measured onboard an operating loaded TEU2800 container vessel is analyzed, and the vessel motion data are measured during numerous trans-Atlantic crossings. The risk of container loss owing to excessive rolling motion is a key issue in cargo vessel transportation. The complex nonlinear and nonstationary characteristics of incoming waves and the associated cargo vessel movements render it challenging to accurately forecast excessive vessel roll angles. When a loaded cargo vessel sails through a harsh stormy environment, higher-order dynamic motion effects become evident and the effect of nonlinearities may increase significantly. Meanwhile, laboratory testing are affected by the wave parameters and similarity ratios used. Consequently, raw/unfiltered motion data obtained from cargo vessels traversing in adverse weather conditions provide valuable insights into cargo vessel reliability. Parametric extrapolations based on certain functional classes are typically employed to extrapolate and fit probability distributions estimated from the underlying dataset. This investigation aims to present an alternative nonparametric extrapolation methodology based on the intrinsic properties of the raw underlying dataset without introducing any assumptions regarding the extrapolation functional class.This novel extrapolation deconvolution method is suitable for contemporary marine-engineering and design applications, as well as serves as an alternative to existing reliability methods. The prediction accuracy of the deconvolution methodology is demonstrated by comparing it with a modified four-parameter Weibull-type extrapolation technique. Compared with its counterpart sub-asymptotic statistical methods, such as the modified Weibull-type fit, peaks over the threshold, and generalized Pareto, the advocated deconvolution method is superior in term of its extrapolation numerical stability.

Experimental study of the vertical structure of internal solitary waves in the continuous pycnocline

In order to reveal the complex structural characteristics of internal solitary waves (ISWs) in the actual ocean, an experimental study of the vertical structure of ISWs in the continuous pycnocline (a transition layer with sharp density changes) was conducted in a stratified fluid flume. The gravity collapse method was used to generate ISWs, and their wave-flow fields were measured using a coupled wave-flow measurement technique. The vertical structure of wave-flow fields was investigated as was the applicability of the Dubreil–Jacotin–Long (DJL) equation. The results show that the waveform of ISWs contains multiple isodensity lines that varied with fluid depth. The wave amplitude and wavelength of ISWs exhibited depth-dependent changes, which were negatively correlated. The vertical structure of the flow fields exhibited an approximate circular wave packet, with stronger horizontal flow than vertical flow. The larger the characteristic amplitude, the stronger the intensity of the flow field, and the faster the intensity of the vertical flow field increased. The applicability of the DJL equation was closely related to the stratified environment, with better agreement when the upper layer fluid constituted a larger ratio of the total fluid thickness.

Electromagnetic ion cyclotron emission from ion-scale magnetic holes

Ion-scale magnetic holes are nonlinear plasma structures commonly observed in the solar wind and Earth's magnetosphere. These holes are characterized by the magnetic field depletion filled by hot, transversely anisotropic ions and electrons and are likely formed during the nonlinear stage of ion mirror instability. Due to the plasma thermal anisotropy within magnetic holes, they serve as a host of electromagnetic ion cyclotron waves, whistler-mode waves, and electron cyclotron harmonic waves. This makes magnetic holes an important element of the Earth's inner magnetosphere, where electromagnetic waves generated within may strongly contribute to energetic ion and electron scattering. Such scattering, however, will modify the hot-ion distribution that is trapped within magnetic holes and responsible for the magnetic field stress balance. Therefore, hot ion scattering within magnetic holes likely determines the hole lifetime. In this study, we investigate how ion scattering by electromagnetic waves affects the stress balance and lifetime of magnetic holes. For illustration, we used typical characteristics of magnetic holes, ion populations, and ion cyclotron waves observed in the Earth's magnetosphere. We have demonstrated that ion distribution isotropization via scattering by waves does not change significantly magnetic hole magnitude, but ion losses due to scattering into the atmosphere may limit the hole life-times to 10–30 min in the Earth's inner magnetosphere.

Modelling and simulation for the investigation on the ultrasonic propagation mechanism in advanced microelectronic packages

The miniaturisation, ultra-thinness and high-density multi-layer structure of advanced microelectronic packages complicate the propagation mechanism of ultrasonic waves. In this paper, a finite element model is used to simulate ultrasonic wave propagation in flip chip packages, investigating the laws of transmission and reflection at the lamination boundaries. The acoustic field of ultrasonic transducers is simulated using MATLAB and Abaqus software. The angular spectrum method (ASM) based on the Fourier transform is adopted to more precisely reveal the distribution characteristics and attenuation relationship of near‐field ultrasonic waves. The influence of the frequency and size of the ultrasonic transducer on the propagation characteristics of ultrasonic waves is analysed. Based on an acoustic field map generated by the detection model, the waveform conversions of acoustic waves in a multi-layer structure are analysed. The results show that ultrasonic waves are mainly presented in the form of reflected and transmitted waves at the layered interface and the model with a perfectly matched layer (PML) has higher accuracy. Therefore, this method is applied to ultrasonic testing in a flip chip package, which cannot only effectively exclude interference from boundary reflection but also greatly improve the reliability of waveform conversions analysis.

Nonlinear elastic waves generated by surface wave interaction with local plasticity in thick-walled structures

Thick-walled structures (TWSs) are frequently utilized as primary load-bearing structures across diverse industrial sectors, illustrated by train axles. Proper health monitoring, particularly for early damage detection, is required to ensure the operational safety and structural integrity of such structures. Nonlinear elastic-wave-based structural health monitoring techniques present a potentially efficacious methodology, which relies heavily upon the understanding of nonlinear wave generation and propagation characteristics. Unfortunately, due to the complexity introduced by various wave modes in TWSs, a comprehensive understanding of nonlinear elastic waves is still lacking. Considering practical local plasticity on the surface of a TWS, this study investigates the characteristics of nonlinear elastic wave generation and propagation resulting from the fundamental surface wave-local plasticity interaction. Theoretical analyses were carried out to examine the scattering features of the generated nonlinear bulk waves based on Snell’s law. Finite element simulations were then performed to confirm the predicted scattering characteristics of the nonlinear bulk waves, with the introduction of a local material nonlinearity to replicate the plasticity in a TWS. Using the extrusion method, a local plastic zone was produced on an aluminum thick-walled beam. Experiments were finally carried out using a laser vibrometer to confirm the scattering features of nonlinear elastic waves. It was found that the nonlinear shear bulk waves are mainly generated due to the fundamental surface interaction with local plasticity. Furthermore, the generated nonlinear shear bulk waves propagate at a fixed angle towards the interior of the TWS, which can be measured on the opposite surface. The elucidation of the nonlinear elastic wave generation and propagation characteristics paves the way for an effective sensor arrangement in early damage detection applications.

Improved Energy Resolution Measurements of Electron Precipitation Observed During an IPDP‐Type EMIC Event

AbstractHigh energy resolution DEMETER satellite observations from the Instrument for the Detection of Particle (IDP) are analyzed during an electromagnetic ion cyclotron (EMIC)‐induced electron precipitation event. Analysis of an Interval Pulsation with Diminishing Periods (IPDP)‐type EMIC wave event, using combined satellite observations to correct for incident proton contamination, detected an energy precipitation spectrum ranging from ∼150 keV to ∼1.5 MeV. While inconsistent with many theoretical predictions of >1 MeV EMIC‐induced electron precipitation, the finding is consistent with an increasing number of experimentally observed events detected using lower resolution integral channel measurements on the POES, FIREBIRD, and ELFIN satellites. Revised and improved DEMETER differential energy fluxes, after correction for incident proton contamination shows that they agree to within 40% in peak flux magnitude, and 85 keV (within 40%) for the energy at which the peak occurred as calculated from POES integral channel electron precipitation measurements. This work shows that a subset of EMIC waves found close to the plasmapause, that is, IPDP‐type rising tone events, can produce electron precipitation with peak energies substantially below 1 MeV. The rising tone features of IPDP EMIC waves, along with the association with the high cold plasma density regime, and the rapidly varying electron density gradients of the plasmapause may be an important factor in the generation of such low energy precipitation, co‐incident with a high energy tail. Our work highlights the importance of undertaking proton contamination correction when using the high‐resolution DEMETER particle measurements to investigate EMIC‐driven electron precipitation.

Ballistic impact wave and bulge profile propagation characteristics and blunt injury assessment of UHMWPE laminate composite

Amid escalating localized conflicts worldwide, the elucidation of the mechanisms and quantification blunt trauma the emergency services and military personnel confronted becomes imperatively. However, the understanding of bullet-induced bulge formation on the laminate's back face, impact wave propagation, and consequent trauma assessment methods remains incomplete. This study applies 3-dimension digital image correlation (3D-DIC) method to reveals these phenomena by utilizing a lead-core bullet traveling at 334.93 m/s to impact an ultra-high molecular weight polyethylene (UHMWPE) laminate. The results show that the initial transverse propagation velocity of bulge profile is 24.79% smaller than the theoretical calculation, which indicates the reduction caused by cohesive matrix. The transverse wave demonstrates a double exponential attenuation pattern, which could be decomposed into two single exponential attenuation curves. The bulge profile shows hyperbolic pattern, which reveals the stability of the bulge shape and the temporal evolution pattern. Increasing the laminate-body gap leads to a decline in Blunt Criterion (BC) and the Abbreviated Injury Scale (AIS) values reduce from 2 to 0 correspondingly. The numerical model confirms the compression wave velocity as 1447.77 ± 123.10 m/s in the thickness direction and 9542.86 ± 3087.75 m/s in the fiber direction. These findings reveals and quantified the propagation patterns of back bulge and compressive wave, and thus could provide data-driven insights to improve body armor performance and blunt trauma assessment for individual soldiers.

Effect of moisture on the sensing capabilities of piezoelectric actuator/sensor pairs on flax fibre reinforced composite laminates

The sensitivity of the piezoelectric actuators’ response to the moisture uptake has been investigated on flax fibre reinforced composite laminates. Non-woven flax fabric was impregnated with epoxy and composite laminates were fabricated using hand lay-up and cured in a compression moulding machine. The laminates were initially impacted with a drop-weight impact machine at a low energy level, with the aim to generate an artificial surface crack that will allow the moisture to enter the fibre-matrix interface more effectively. A set of piezoelectric actuators and sensors were adhered on the surfaces of the composite panels in a specific rectangular arrangement to allow for wave capturing at various directions. The wave characteristics of the samples were extracted in pristine stage and then the samples were impacted and immersed in distilled water until saturation. At regular intervals after the water immersion, the panels’ weight was measured using a laboratory scale and the wave propagation characteristics of the materials ware measured in order to investigate the gradual effect of moisture on the capabilities of the actuators and sensors. The propagation of stress waves in the dry and wet samples was investigated and the effect of moisture absorption was examined experimentally using piezoelectric wafers until the saturation was reached. Finally, a continuum damage mechanics layerwise time domain spectral finite element model, both for the composite laminate and the rich resin layers, was also developed to simulate the materials’ performance under impact and evaluate the wave propagation within the material at the dry state.

A Numerical Study of Tropical Cyclone and Ocean Responses to Air‐Sea Momentum Flux at High Winds

AbstractThe relationship between minimum sea level pressure (MSLP) and maximum wind speed, is a commonly employed metric for assessing tropical cyclone (TC) forecast skill. However, accurately reproducing this relationship in TC forecasts is challenging. By introducing a new air‐sea momentum flux scheme considering both wave state and saturation (decrease) effect at high winds into a fully coupled atmosphere‐ocean‐wave model, our numerical results reveal that the maximum wind speed and MSLP respond oppositely to the air‐sea momentum flux change. The simulated wind‐pressure relationship aligns well with observations when the new flux scheme is used. This study highlights the large sensitivity of wind‐pressure relationship to the air‐sea momentum flux parameterization at high winds. Furthermore, the air‐sea momentum flux has a significant effect on ocean wave characteristics and sea surface temperature (SST) cooling in TC simulations.

Machine learning-based improvement of crack localization in concrete structures

Acoustic emission (AE) method is useful for damage detection in structures. However, processing the massive amount of AE data with traditional analysis methods is time-consuming. Therefore, machine learning (ML) integration provides a more rational and efficient solution by accelerating the data analysis and improving the damage detection accuracy. This study aims to improve source localization, which provides to identify cracking patterns by signal-based analysis, by training the ML model with the AE dataset for accurate damage diagnosis of concrete structures. Analyzes were conducted on the ML model using AE data collected on a concrete member under laboratory conditions. In this way, the ML model that learned signals with multi-variable wave characteristics and parameters was integrated into the source localization algorithm and thus, AE source location results were enhanced. Furthermore, due to its ability to identify damaged areas, this approach is essential for structural safety by providing early damage detection and accurate localization of cracks. This integration of the machine learning model with AE data will be considered as an advanced tool for the effective monitoring of damages in structures.

Audio Classification on the FSDKaggle2018 Dataset using Tensorflow, Keras

This project explores audio classification leveraging representation learning within the TensorFlow framework. The methodology focuses on the initial engineering of wave features derived from raw audio data, which are subsequently used to train convolutional neural networks (CNNs) for effective representation learning. By transforming the audio signals into a structured format amenable to convolutional processing, our system is designed to capture the intrinsic properties and patterns embedded in the sound waves. The feature engineering process is detailed where various envelope features such as the homomorphic envelogram, hilbert envelogram and wavelet decompositions help in extracting meaningful information from the raw audio signals. These engineered features provide a robust foundation for the subsequent layers of convolutional networks. The CNNs are meticulously architected to learn hierarchical representations, effectively capturing both low-level and high-level audio characteristics.This study attempts to reinforces the significance of tailored feature engineering in deep learning and demonstrate an effective audio classification pipeline using representation learning and open up new avenues for research in audio signal processing and machine learning.

Conductive Hydrogel Tapes for Tripolar EEG: A Promising Solution to Paste-Related Challenges.

Electroencephalography (EEG) remains pivotal in neuroscience for its non-invasive exploration of brain activity, yet traditional electrodes are plagued with artifacts and the application of conductive paste poses practical challenges. Tripolar concentric ring electrode (TCRE) sensors used for EEG (tEEG) attenuate artifacts automatically, improving the signal quality. Hydrogel tapes offer a promising alternative to conductive paste, providing mess-free application and reliable electrode-skin contact in locations without hair. Since the electrodes of the TCRE sensors are only 1.0 mm apart, the impedance of the skin-to-electrode impedance-matching medium is critical. This study evaluates four hydrogel tapes' efficacies in EEG electrode application, comparing impedance and alpha wave characteristics. Healthy adult participants underwent tEEG recordings using different tapes. The results highlight varying impedances and successful alpha wave detection despite increased tape-induced impedance. MATLAB's EEGLab facilitated signal processing. This study underscores hydrogel tapes' potential as a convenient and effective alternative to traditional paste, enriching tEEG research methodologies. Two of the conductive hydrogel tapes had significantly higher alpha wave power than the other tapes, but were never significantly lower.

Hybrid broadband simulation of long-period ground motion in far-field basins based on group delay model

Shallow seismic events often induce long-period ground motions in distant sedimentary basins, which can cause damage to structures. The current design earthquake input is usually based on amplitude, while the equally essential phase characteristics of far-field basin seismic waves are often ignored. To address this issue, this paper proposes a semi-empirical model based on group delay, which integrates the effects of source, path, local site, and basin on group delay, we characterize randomness of group delay through a parametric Gaussian probability framework, and approximates the frequency non-stationarity of positive and negative dispersion by introducing piecewise spline gradient regression. As an improvement of the stochastic finite fault method, the proposed method solves the problem that the original method cannot sufficiently reflect the phase characteristics and frequency non-stationarity of basin-induced seismic waves. Based on this model, the stochastic finite fault method and the spectral element method are combined to perform the hybrid simulation of basin ground motion, and the earthquake of 2003 Tokachi-Oki verifies the reliability of the proposed method.

Oblique Compressible Waves in the Reconnection Exhaust Region Embedded in the Inner Heliospheric Current Sheet Observed by Parker Solar Probe

Magnetic reconnection is an important physical process of energy conversion in the heliosphere. Parker Solar Probe (PSP) passes through current sheets of the inner heliosphere and is likely to encounter magnetic reconnection events there. PSP traversed a magnetic reconnection exhaust region that occurred in the coronal streamer during its perihelion Encounter 8. We report an observation of the counterstream of strahl electrons and compressible waves in the exhaust region on the antisunward side of the reconnection site. We analyze the wave characteristics using electromagnetic singular value decomposition techniques and find that the propagation direction of the compressible waves is quasi-perpendicular to the local magnetic field. Combining with the topology of the magnetic field, we infer that the compressible waves converge from the edge to the center of the exhaust region, and then propagate away from it. Further, we select 12 magnetic reconnection events during Encounter 5–8 for statistics and find that the oblique compressible waves are commonly detected throughout the inner heliospheric current sheet. In addition, we discuss the possible nature of wave branches for these compressible waves. Our work shows that magnetic reconnection in the heliosphere not only changes the topology of the large-scale magnetic field in the heliosphere, but also affects the transport characteristics of solar wind plasma and suprathermal particles, and regulates the states of waves and turbulence in the heliosphere.

Temporal Convolutional Neural Network-Based Prediction of Vascular Health in Elderly Women Using Photoplethysmography-Derived Pulse Wave during Exercise.

(1) Background: The objective of this study was to predict the vascular health status of elderly women during exercise using pulse wave data and Temporal Convolutional Neural Networks (TCN); (2) Methods: A total of 492 healthy elderly women aged 60-75 years were recruited for the study. The study utilized a cross-sectional design. Vascular endothelial function was assessed non-invasively using Flow-Mediated Dilation (FMD). Pulse wave characteristics were quantified using photoplethysmography (PPG) sensors, and motion-induced noise in the PPG signals was mitigated through the application of a recursive least squares (RLS) adaptive filtering algorithm. A fixed-load cycling exercise protocol was employed. A TCN was constructed to classify flow-mediated dilation (FMD) into "optimal", "impaired", and "at risk" levels; (3) Results: TCN achieved an average accuracy of 79.3%, 84.8%, and 83.2% in predicting FMD at the "optimal", "impaired", and "at risk" levels, respectively. The results of the analysis of variance (ANOVA) comparison demonstrated that the accuracy of the TCN in predicting FMD at the impaired and at-risk levels was significantly higher than that of Long Short-Term Memory (LSTM) networks and Random Forest algorithms; (4) Conclusions: The use of pulse wave data during exercise combined with the TCN for predicting the vascular health status of elderly women demonstrated high accuracy, particularly in predicting impaired and at-risk FMD levels. This indicates that the integration of exercise pulse wave data with TCN can serve as an effective tool for the assessment and monitoring of the vascular health of elderly women.

Vibro stone as periodic wave barriers for train-induced vibration attenuation of Lamb and surface waves

The rising cost of traditional foundations (e.g., concrete piles) and their environmental limits have prompted using natural ways to strengthen poor soils. The Vibro stone column technique has grown in popularity in the building industry because it is a cost-effective and ecologically friendly way of strengthening the soil-bearing capacity of poor soil and avoiding the risk of soil liquefaction. The usage of stone columns in soft clay as periodic wave barriers to attenuate undesirable waves is numerically examined in this paper. The finite element method was used to investigate the band gap characteristics of Lamb and surface waves in the periodic structures of the stone column. In both wave analyses, eigenfrequency simulation, mode shapes simulation, frequency domain simulation, and time transient simulation are used to investigate the traditional vibroflot shape and proposed square and notch types vibroflot. It was established that the notch type vibroflot performed excellently in attenuating Lamb and surface waves compared to the traditional and square vibroflot types. The numerical outcomes in the frequency and time domains support the attenuation impact of finite Vibro stone in the band gap as well as the phenomena of attenuation broadening brought on by the dissipation of leak modes into the bulk. As a result, the proposed barriers can be used to shield the broadband incident waves generated by both Lamb and surface waves by trains in a tunnel.

A theoretical model and verification of soil column deformation under impact load based on the Duncan-Chang model

The dynamic compaction method has been widely adopted in foundation treatment to densify the soil fillers. However, for the complexity of the impact behavior and soil mechanical properties, the theoretical research of dynamic compaction lags behind its practice for complex soil properties and stress paths. This paper presents a theoretical model applied to describe soil column plastic deformation under impact load. The relationship among stress increment, strain increment, and plastic wave velocity was derived from the aspect of propagation characteristics of stress waves in soil first. Combined with the Duncan-Chang Model, a one-dimensional theoretical model was established then. A numerical model was developed further to check the performance of the model. It showed that the deformation at the end of the soil column was mushroom-shaped. Both the axial and lateral deformation increased with the impact velocity. While some particles located at the side of the soil column end may splash under repeated impact. The theoretical deformations of the soil column were consistent with the experimental results both in the direction of axial and lateral.