Search Results (344)

The pull-back method for determining dynamic tensile strength assumes one-dimensional stress wave propagation and material homogeneity. This study validates these assumptions for unidirectional reinforced concrete (UDRC) through experiments and numerical simulations. Split Hopkinson pressure bar tests were conducted on plain concrete, plain UDRC, and deformed UDRC specimens containing a central 6 mm steel bar. Ultra-high-speed digital image correlation at 500,000 fps enabled precise local strain rate measurements (3 s⁻¹ to 55 s⁻¹) at fracture locations. Finite element simulations revealed that while reinforcement induces localized multi-axial stresses near the steel–concrete interface, the bulk concrete maintains predominantly uniaxial stress conditions. Experimental results showed less than 1% variation in pull-back velocity between specimen types. Statistical analysis confirmed a unified strain rate-strength relationship: ${\sigma }_{\mathrm{spall}}=4.1+4.7{log}_{10}\left(\dot{\epsilon }\right)$$\mathrm{M}\mathrm{Pa}$, independent of reinforcement configuration (ANCOVA: $p=0.2182$ for interaction term). The dynamic tensile strength is governed by concrete matrix properties rather than reinforcement type. These findings are the first to experimentally and numerically validate the pull-back method’s applicability to UDRC systems, establishing that dynamic tensile failure is matrix-dominated and enabling simplified one-dimensional analysis for reinforced concrete under impact. Full article

This study addresses the limitations of conventional evaluation methods caused by low porosity, strong heterogeneity, and complex pore structures in tight sandstone reservoirs. Through integrated rock physics experiments and multi-physical field modeling, the research systematically investigates the coupled response mechanisms between electrical and elastic parameters. The experimental approach includes pore structure characterization, quantitative mineral composition analysis, resistivity and polarizability measurements under various saturation conditions, P- and S-wave velocity testing, and scanning electron microscopy (SEM) imaging. The key findings show that increasing porosity leads to significant reductions in resistivity and elastic wave velocities, while also increasing surface conductivity. Specifically, clay minerals enhance surface conductivity through interfacial polarization effects and decrease rock stiffness, which exacerbates wave velocity attenuation. Furthermore, resistivity exhibits a nonlinear negative correlation with water saturation, with sharp increases at low saturation levels due to the disruption of conductive pathways. By integrating the Modified Generalized Effective Medium Theory of Induced Polarization (MGEMTIP) and Kuster–Toksöz models, this study establishes quantitative relationships between porosity, saturation, and electrical/elastic parameters, and constructs cross-plot templates that correlate elastic wave velocities with resistivity and surface conductivity. These analyses reveal that high-porosity, high-saturation zones are characterized by lower resistivity and wave velocities, coupled with significantly higher surface conductivity. The proposed methodology significantly improves the accuracy of reservoir evaluation and enhances fluid identification capabilities, providing a solid theoretical foundation for the efficient exploration and development of tight sandstone reservoirs. Full article

Acoustic tomography is a non-destructive technique used in the internal assessment of standing trees. Various researchers have focused on developing analytical tools using this technique, demonstrating that they can detect internal biodeterioration in cross-sections with good accuracy. This study evaluates the use of two ultrasonic wave devices with different frequencies (USLab and Sylvatest Duo) and a stress wave device (Microsecond Timer) to generate acoustic tomography using ImageWood VC1 software. The tests were carried out on 12 cross-sections of urban trees in the city of Madrid of the species Robinia pseudoacacia L., Platanus × hybrida Brot., Ulmus pumila L., and Populus alba L. Velocity measurements were made, forming a diffraction mesh in both standing trees and logs after cutting them down. An inspection was carried out with a perforation resistance drill (IML RESI F-400S) in the radial direction in each section, which allowed for more precise identification of defects and differentiating between holes and cracks. The various defects were determined with greater accuracy in the tomographic images taken with the higher-frequency equipment (45 kHz), and the combination of ultrasonic tomography and the use of the inspection drill can provide a more accurate representation of the defects. Full article

The deflagration-to-detonation transition (DDT) is a critical process for achieving reliable ignition in detonation-based propulsion systems, such as Rotating Detonation Engines (RDEs). This study experimentally investigates the effect of spatial variations in blockage ratio (BR) on flame acceleration and detonation onset within a modular pre-detonator. Three DDT device configurations (converging, constant, and diverging) were designed to have an identical average BR of 0.5 and were tested over equivalence ratios ranging from 0.64 to 1.6. High-speed imaging, pressure transducers, and schlieren visualization were employed to characterize flame propagation velocity, pressure evolution, and exit wave structures. The converging configuration consistently promoted earlier detonation onset and higher success rates, especially under fuel-rich conditions (ϕ = 1.6), while the diverging configuration failed to initiate detonation in all cases. Enhanced flame compression in the converging layout led to strong coupling between the shock and reaction fronts, facilitating robust detonation formation. These findings indicate that the spatial distribution of BR, rather than average BR alone, plays a decisive role in DDT performance. This work offers validated design insights for optimizing pre-detonator in RDE applications. Full article

Defective phononic crystals (PnCs) have garnered significant attention for their ability to localize and amplify elastic wave energy within defect sites or to perform narrowband filtering at defect-band frequencies. The necessity for continuously tunable defect characteristics is driven by the variable excitation frequencies encountered in rotating machinery. Conventional tuning methodologies, including synthetic negative capacitors or inductors integrated with piezoelectric defects, are constrained to fixed, offline, and incremental adjustments. To address these limitations, the present study proposes an active feedback approach that facilitates online, wide-range steering of defect bands in a one-dimensional PnC. Each defect is equipped with a pair of piezoelectric sensors and actuators, governed by three independently tunable feedback gains: displacement, velocity, and acceleration. Real-time sensor signals are transmitted to a multivariable proportional controller, which dynamically modulates local electroelastic stiffness via the actuators. This results in continuous defect-band frequency shifts across the entire band gap, along with on-demand sensitivity modulation. The analytical model that incorporates these feedback gains has been demonstrated to achieve a level of agreement with COMSOL benchmarks that exceeds 99%, while concurrently reducing computation time from hours to seconds. Displacement- and acceleration-controlled gains yield predictable, monotonic up- or down-shifts in defect-band frequency, whereas the velocity-controlled gain permits sensitivity adjustment without frequency drifts. Furthermore, the combined-gain operation enables the concurrent tuning of both the center frequency and the filtering sensitivity, thereby facilitating an instantaneous remote reconfiguration of bandpass filters. This framework establishes a new class of agile, adaptive ultrasonic devices with applications in ultrasonic imaging, structural health monitoring, and prognostics and health management. Full article

Fine-mesh netting, with mesh dimensions of the order of a few millimeters, is widely used in sampling nets for the collection of larval and juvenile fishes. The wave force characteristics of fine-mesh netting significantly affect the operational performance of these nets. This study employed both wave tank experiments and numerical simulations to analyze the hydrodynamic performance of fine-mesh netting under varying wave conditions. A series of numerical simulations and particle image velocimetry (PIV) experiments were conducted to investigate the damping effects of fine-mesh netting on wave propagation. The results revealed that horizontal wave forces increased with both the wave period and wave height. When the wave period was held constant, the drag and inertial coefficients of the netting generally decreased as the Reynolds number and the Keulegan–Carpenter (KC) number increased. The wave transmission coefficients of the netting decreased as the wave height increased for the same wave period. However, at a constant wave height, the transmission coefficients initially increased and then decreased with the increasing wave period. The water particle velocity was significantly affected by the netting, with a notable reduction in velocity downstream of the netting at both the wave crest and trough phases. The simulation results and PIV measurements of the water particle velocity field distribution were in good agreement. This study provides important insights for the design and optimization of sampling nets. Full article

As humans continue to develop the undersea engineering ecosystem of systems, the consequences of catastrophic events must continue to be investigated and understood. Almost every undersea pressure vessel, from pipelines to sensors to unmanned vehicles, has the potential to experience a catastrophic collapse, known as an implosion. This collapse can be caused by hydrostatic pressure or any combination of external loadings from natural disasters to pressure waves imparted by other implosion or explosion events. During an implosion, high-magnitude pressure waves can be emitted, which can cause adverse effects on surrounding structures, marine life, or even people. The imploding structure, known as an implodable volume, can be in a free-field or confined environment. Confined implosion is characterized by a surrounding structure that significantly affects the flow of fluid around the implodable volume. Often, the confining structure is cylindrical, with one closed end and one open end. This work seeks to understand the effect of fluid flow restriction on the physics of implosion inside a confining tube. To do so, a comprehensive experimental study is conducted using a unique experimental facility. Thin-walled aluminum cylinders are collapsed inside a confining tube within a large pressure vessel. High-speed photography and 3D Digital Image Correlation are used to gather structural displacement and velocities during the event while an array of dynamic pressure sensors capture the pressure data inside the confining tube. The results of this work show that by changing the size of the open end, referred to as the flow area ratio, there can be a significant effect on the structural deformations and implosion severity. It also reveals that only certain configurations of holes at the open end of the tube play a role in the dynamic pressure pulse measured at the closed end of the tube. By understanding the consequences of an implosion, designers can make decisions about where these pressure vessels should be in relation to other pressure vessels, critical infrastructure, marine life, or people. In the same way that engineers design for earthquakes and analyze the impact their structures have on the environment around them, contributors to the undersea engineering ecosystem should design with implosion in mind. Full article

Seismic imaging in areas with complex geological structures, such as steeply dipping strata and lateral velocity variations, remains a significant challenge in geophysical exploration. In this paper, a Kirchhoff pre-stack depth and pre-stack time migration imaging method under the constraint of an initial model is proposed. By establishing the initial velocity model, the method is iteratively optimized under the horizon constraint, and the travel time difference is used to update the model. Finally, Kirchhoff pre-stack imaging is realized. Numerical simulations using a synthetic five-layer velocity model demonstrate that removing direct wave interference and incorporating horizon constraints significantly improve the signal-to-noise ratio and structural accuracy of the migration results. A field case study in a coalfield with monoclinic structures and high-angle faults further validates the method’s effectiveness. Comparative analysis with pre-stack time migration reveals that Kirchhoff pre-stack depth migration achieves superior fault delineation, diffraction wave homing, and event continuity, particularly in steeply dipping formations. The results highlight the method’s potential for improving seismic interpretation accuracy in complex structural settings, offering practical value for coal mine safety and resource exploration. Full article

As a significant geological hazard in large–scale engineering construction, deep subsurface voids demand effective and precise detection methods. Cross–hole radar tomography overcomes depth limitations by transmitting/receiving electromagnetic (EM) waves between boreholes, enabling the accurate determination of the spatial distribution and EM properties of subsurface cavities. However, conventional inversion approaches, such as travel–time/attenuation tomography and full–waveform inversion, still face challenges in terms of their stability, accuracy, and computational efficiency. To address these limitations, this study proposes a deep learning–based imaging method that introduces the concept of travel–time fingerprints, which compress raw radar data into structured, low–dimensional inputs that retain key spatial features. A large synthetic dataset of irregular subsurface cavity models is used to pre–train a UNET model, enabling it to learn nonlinear mapping, from fingerprints to velocity structures. To enhance real–world applicability, transfer learning (TL) is employed to fine–tune the model using a small amount of field data. The refined model is then tested on cross–hole radar datasets collected from a highway construction site in Guizhou Province, China. The results demonstrate that the method can accurately recover the shape, location, and extent of underground cavities, outperforming traditional tomography in terms of clarity and interpretability. This approach offers a high–precision, computationally efficient solution for subsurface void detection, with strong engineering applicability in complex geological environments. Full article

Effective vertical seismic profiling (VSP) of upgoing and downgoing wave separation is essential for high-quality imaging. However, VSP wavefield separation is particularly challenging under complex geological conditions. Existing solutions encompass one derived from the mathematical characteristics of upgoing and downgoing waves, employing signal decomposition methodologies, and another that utilizes data-driven machine learning techniques, achieving wavefield separation by training sample data to identify the distinct characteristics of upgoing and downgoing waves. This study introduces a VSP wave-separation method using signal knowledge representation, primarily by constructing knowledge representations of upgoing and downgoing waves. Physics-informed recurrent neural network FWI and Poynting vector physical knowledge representation yielded accurate velocity models. Axial gradient information was utilized to construct morphological knowledge representations of upgoing and downgoing waves. Directional differentiation knowledge representations were established based on kinematic characteristic disparities between upgoing and downgoing waves in the time-depth domain. These wave knowledge representations (KRs) built a dual convolutional autoencoder. Its distinct branches extracted up/down wave information, while the KRs, transformed into loss functions, enabled knowledge-driven unsupervised VSP wave separation. The proposed methodology was validated using a homogeneous layer and Marmousi models, demonstrating the effective separation of upgoing and downgoing waves from the VSP seismic records. Full article

Cross-Track Interferometric Synthetic Aperture Radar (XTI-SAR) can utilize variations in interferometric phase to measure sea surface velocity along radar radial direction and sea surface height, which can be used for ocean wave parameter inversion. However, research on the imaging mechanisms of XTI-SAR systems for ocean waves remains understudied, and there are still some problems in its perception. To further study the imaging mechanism of XTI-SAR measurement systems for ocean waves, this paper describes research based on the nonlinear integral transform model and the quasi-linear integral transform model derived by Bao in 1999, which relate the XTI-SAR ocean wave spectrum to the phase spectrum. Firstly, this work derived another quasi-linear integral transform model based on the nonlinear integral transform model, and also optimized the quasi-linear integral transform model derived by Bao. The optimized quasi-linear integral transform model eliminates the need for complex calculations of cross-correlation functions between sea surface height and radar radial orbital velocity components of ocean waves, as well as the radar line-of-sight velocity transfer function, while maintaining high integral transform accuracy. Secondly, based on two-dimensional sea surface simulations, we analyzed the differences between the quasi-linear integral transform models and the nonlinear integral transform model corresponding to different XTI-SAR system configurations and different sea states. The numerical simulation results show that, for the XTI-SAR system, in general, the difference between the quasi-linear integral transform model derived in this work and the nonlinear integral transform model is greater than that of the quasi-linear integral transform model derived by Bao. However, the difference between the optimized quasi-linear integral transform model and the nonlinear integral transform model in this study is smaller, and it is more convenient when transforming the ocean wave spectrum to the phase spectrum. Full article

A methodology utilizing low-resolution camera data is proposed to mitigate clutter effects on radar sensors in smart indoor environments. The proposed technique suppresses clutter in distance–velocity (range–Doppler) images obtained from millimeter-wave radar by estimating clutter locations using approximate spatial information derived from low-resolution camera images. Notably, the inherent blur present in low-resolution images closely corresponds to the distortion patterns induced by clutter in radar signals, making such data particularly suitable for effective sensor fusion. Experimental validation was conducted in indoor path-tracking scenarios involving a moving subject within a 10 m range. Performance was quantitatively evaluated against baseline range–Doppler maps obtained using radar data alone, without clutter mitigation. The results show that our approach improves the signal-to-noise ratio by 2 dB and increases the target detection rate by 8.6% within the critical 4–6 m range, with additional gains observed under constrained velocity conditions. Full article

Background: Several imaging studies have confirmed ocular involvement in systemic sclerosis (SSc). However, elastography has not yet been used for this purpose in the literature. Thus, this study aimed to evaluate ocular involvement in SSc using shear wave elastography (SWE). Methods: This study included 29 SSc patients and 30 age- and sex-matched healthy controls. All participants underwent independent ophthalmological evaluations by two ophthalmologists. Subsequently, SWE was used to evaluate the retina–choroid–sclera (RCS), optic disc (OD), optic nerve (ON), and retrobulbar adipose tissue (RBFT) of the right eye. The median shear wave elasticity (kPa) and velocity (m/s) values were automatically calculated using the ultrasound device’s integrated software. Results: The elasticity and velocity values of RBFT in SSc patients were significantly higher than those in the control group. However, no notable differences were observed in other analyzed areas. A strong association was found between digital ulcers and velocity values of the RCS, while no significant differences were noted for other parameters. Conclusions: This study revealed increased stiffness in the RBFT of SSc patients. To our knowledge, this is the first evidence suggesting that SSc can affect RBFT. Further studies are required to confirm this finding and investigate its link to the disease. Additionally, we found a strong association between digital ulcers and increased RCS stiffness. Using SWE for the first time, we have demonstrated that microcirculatory disruption in SSc extends beyond the skin and can affect multiple tissues simultaneously. Full article

Preliminary tunnel surveys are essential for identifying geological hazards such as aquifers, faults, and karstic zones. While first-arrival tomography is effective for imaging shallow anomalies, traditional seismic sources face significant limitations in forested mountainous regions due to mobility, cost, and environmental impact. To address this, we deployed a seismic source delivered by an unmanned aerial vehicle (UAV) for a highway tunnel survey in Lijiang, China. The UAV system, paired with nodal geophones, enabled rapid, low-impact, and high-resolution data acquisition in rugged terrain. To enhance the weak far-offset refractions affected by near-surface attenuation, we applied supervirtual refraction interferometry (SVI), which significantly improved the signal-to-noise ratio and expanded the usable first-arrival dataset. The combined use of UAV excitation and SVI processing produced a high-precision P-wave velocity model through traveltime tomography, aligned well with borehole data. This model revealed the spatial distribution of weathered zones and bedrock interfaces, and allowed us to infer potential fracture zones. The results offer critical guidance for tunnel alignment and hazard mitigation in complex geological settings. Full article

To study the mantle structure of the North China Craton (NCC) and its tectonic implications, in particular, the evolution of the rift systems in the Trans-North China Orogen (TNCO), we used teleseismic data recorded by 250 portable seismic stations to invert for the P-wave velocity (Vp) structures of the mantle beneath the NCC. Our results show a large-scale low-Vp anomaly in the shallow mantle and high-Vp anomalies in the deeper upper mantle beneath the eastern NCC, with fine-scale high-Vp anomalies at the lithosphere–asthenosphere boundary, indicating multi-stage lithospheric delamination during the Cenozoic. In the Yan Mountains (YanM), an east–west striking high-Vp anomaly between 60 to 200 km depths and low heat flow suggest the preservation of a thick mantle root. In the TNCO, high-Vp bodies in the upper mantle and the upper part of the mantle transition zone (MTZ) are imaged. The shallower high-Vp anomaly located beneath the Shanxi–Shaanxi Rift (SSR), along with an overlying local-scale low-Vp anomaly, indicates local hot material upwelling due to lithospheric root removal. The India–Eurasia collision’s far-field effects are proposed to cause lithospheric thickening, subsequent root delamination, and the formation and evolution of the SSR. Full article