Search Results (264)

As a significant energy source enabling the global energy transition, efficient shale gas development is critical for diversifying supplies and reducing carbon emissions. Zipper fracturing widely enhances the stimulated reservoir volume (SRV) by generating complex fracture networks of shale reservoirs. However, recent trends of reduced well spacing and increased injection intensity have significantly intensified interwell interference, particularly fracture-driven interactions (FDIs), leading to early production decline and well integrity issues. This study develops a fully coupled hydro–mechanical–damage (HMD) numerical model incorporating an explicit discrete fracture network (DFN), opening and closure of fractures, and an aperture–permeability relationship to capture the nonlinear mechanical behavior of natural fractures and their role in FDIs. After model validation, sensitivity analyses are conducted. Results show that when the horizontal differential stress exceeds 12 MPa, fractures tend to propagate as single dominant planes due to stress concentration, increasing the risks of FDIs and reducing effective SRV. Increasing well spacing from 60 m to 110 m delays or eliminates FDIs while significantly improving reservoir stimulation. Fracture approach angle governs the interaction mechanisms between hydraulic and natural fractures, influencing the deflection and branching behavior of primary fractures. Injection rate exerts a dual influence on fracture extension and FDI risk, requiring an optimized balance between stimulation efficiency and interference control. This work enriches the multi-physics coupling theory of FDIs during fracturing processes, for better understanding the fracturing design and optimization in shale gas production. Full article

This study explores the critical role of the flow deflector in suppressing boundary layer separation and enhancing aerodynamic efficiency through systematic geometric parameterization and computational analysis. By defining eight key design variables, this research identifies optimal configurations that significantly delay flow separation at high angles of attack. Computational Fluid Dynamics (CFD) simulations reveal that optimized deflector geometries enhance suction peaks near the airfoil leading edge, redirect separated flow toward the upper surface, and inject momentum into the boundary layer to generate a more positive lift coefficient. The numerical results demonstrate that the optimized design achieves a 58.4% increase in lift coefficient and an 83.3% improvement in the lift–drag ratio by effectively mitigating large-scale vortical structures inherent in baseline configurations. Sensitivity analyses further highlight threshold-dependent “sudden-jump” behaviors in lift coefficients for parameters such as element spacing and deflection angles, while thickness exhibits minimal influence. Additionally, pre-stall optimizations show that strategically aligned deflectors preserve baseline performance with a 0.4% lift gain, whereas misaligned configurations degrade aerodynamic efficiency by up to 9.1%. These findings establish a direct correlation between deflector-induced flow redirection and separation suppression, offering actionable insights for passive flow control in stalled regimes. This research advances fundamental understanding of flow deflector-based separation management and provides practical guidelines for enhancing aerodynamic performance in aerospace applications. Full article

Compared with conventional gas reservoirs, deep shale gas reservoirs are characterized by developed faults and fractures, strong heterogeneity, high stress sensitivity, and complex in situ stress distribution. To address traditional 3D static models’ inability to predict in situ stress changes in strongly heterogeneous reservoirs during fracturing, this study takes the deep shale gas in the Zigong block of the Sichuan Basin as an example. By comprehensively considering the heterogeneity and anisotropy of geomechanical parameters and natural fractures in shale gas reservoirs, a 4D in situ stress multi-physics coupling model for shale gas reservoirs based on geology–engineering integration is established. Through coupling geomechanical parameters with fracturing operation data, the dynamic evolution laws of multi-scale stress fields from single-stage to platform-scale during large-scale fracturing of horizontal wells in deep shale gas reservoirs are systematically studied. The research results show the following: (1) The fracturing process has a significant impact on the magnitude and direction of the stress field. With the injection of fracturing fluid, both the minimum and maximum horizontal principal stresses increase, with the minimum horizontal principal stress rising by 1.8–6.4 MPa and the maximum horizontal principal stress by 1.1–3.2 MPa; near the wellbore, there is an obvious deflection in the direction of in situ stress. (2) As the number of fracturing stages increases, the minimum horizontal principal stress shows an obvious cumulative growth trend, with a more significant increase in the later stages, and there is a phenomenon of stress accumulation along the wellbore, with the stress difference decreasing from 15 MPa to 11 MPa. (3) The on-site adoption of the fracturing operation method featuring overall flush advancement and inter-well staggered fracture placement has achieved good stress balance; comparative analysis shows that the stress communication degree of the 400 m well spacing is weaker than that of the 300 m well spacing. This study provides a more reasonable simulation method for large-scale fracturing development of deep shale gas, which can more accurately predict and evaluate the dynamic stress field changes during fracturing, thereby guiding fracturing operations in actual production. Full article

Fractal theory provides a powerful tool for quantifying complex geometric patterns such as concrete cracks. The box-counting method is widely employed for fractal dimension (FD) calculation due to its intuitive principles and compatibility with image data. However, two critical limitations persist in existing studies: (1) the selection of scale parameters (including minimum measurement scale and cutoff scale) lacks systematization and exhibits significant arbitrariness; (2) insufficient attention to the sensitivity of counting origins compromises the stability and comparability of FDs, severely limiting reliable engineering application. To address these limitations, this study first employs classical fractal images and crack samples to systematically analyze the impact of four minimum measurement scales (2, $\sqrt{2}$, 3, $\sqrt{3}$) and three cutoff scale coefficients (cutoff-to-minimum image side ratios: 1, 1/2, 1/3) on computational accuracy. Subsequently, the farthest point sampling (FPS) method is adopted to select counting origins, comparing two optimization strategies—Count-FD-Mean (mean of fits from multiple origins) and Count-Min-FD (fit using minimal box counts across scales). Finally, the optimized approach is validated through static loading tests on concrete beams. Key findings demonstrate that: the optimal scale combination (minimum scale: $\sqrt{2}$; cutoff coefficient: 1) yields a mere 0.5% average error from theoretical FDs; the Count-Min-FD strategy delivers the highest stability and closest alignment with theoretical values; FDs of beam cracks increase continuously with loading, exhibiting an exponential correlation with midspan deflection that effectively captures crack evolution; uncalibrated scale parameters and counting strategies may induce >40% errors in inferred mechanical parameters; results stabilize with 40–45 counting origins across three tested fractal patterns. This work advances standardization in fractal analysis, enhances reliability in concrete crack assessment, and provides critical support for the practical application of fractal theory in structural health monitoring and damage evaluation. Full article

Cyborg insects offer a biologically powered solution for locomotion control, but conventional methods typically rely on invasive electrical stimulation. Here, we introduce a noninvasive, phototaxis-based strategy to steer walking Endebius florensis beetles using light-emitting diode (LED) stimuli. Electroretinogram recordings revealed spectral sensitivity to blue, green, and yellow light, with reduced response to red. Behavioral assays demonstrated robust positive phototaxis to blue light and negative phototaxis to yellow. Using these findings, we built a wireless microcontroller-based backpack emitting directional blue light to induce steering. The beetles reliably turned toward the activated light, achieving angular deflections over 60° within seconds. This approach enables repeatable, trauma-free insect control and establishes a new paradigm for biohybrid locomotion systems. Full article

Background: Despite the survival benefit of ICDs in patients with HFrEF, most recipients do not receive appropriate therapy during follow-up. Existing risk models based on echocardiographic and clinical parameters show limited predictive accuracy for arrhythmic events. This study aimed to assess whether ECG-derived markers outperform conventional measures in predicting appropriate ICD shocks. Methods: This retrospective observational study included 375 patients with HFrEF who underwent ICD implantation for primary prevention at least six months before study enrollment. Twelve-lead surface ECGs were analyzed for a QTc interval, Tp-e/QT ratio, frontal QRS-T angle, and maximum deflection index (MDI). Clinical, echocardiographic, and arrhythmic event data obtained from device interrogations were evaluated. Receiver operating characteristic (ROC) curve analysis and multivariate logistic regression were performed to identify independent predictors of appropriate ICD shocks. Results: Patients who experienced appropriate ICD shocks had significantly higher rates of a complete bundle branch block, digoxin use, QRS duration, QTc, Tp-e/QT ratio, frontal QRS-T angle, MDI, and right-ventricular pacing ratio. Conversely, beta-blocker use was significantly lower in this group. In multivariate analysis, independent predictors of appropriate shocks included the patient’s digoxin use (OR = 2.931, p = 0.003), beta-blocker use (OR = 0.275, p = 0.002), frontal QRS-T angle (OR = 1.009, p < 0.001), QTc interval (OR = 1.020, p < 0.001), and Tp-e/QT ratio (OR = 4.882, p = 0.050). The frontal QRS-T angle had a cutoff value of 105.5° for predicting appropriate ICD shocks (sensitivity: 73.6%, specificity: 85.2%, AUC = 0.758, p < 0.001). Conclusions: Electrocardiographic markers, particularly the frontal QRS-T angle, QTc interval, and Tp-e/QT ratio, demonstrated superior predictive power for appropriate ICD shocks compared to conventional echocardiographic and clinical measures. These easily obtainable, non-invasive ECG parameters may improve current risk stratification models and support more individualized ICD implantation strategies. Full article

The superb dynamic performance of steel-plate composite (SC) structures under unexpected impact loading depends on the good design of the connection between the SC wall and foundation. This study investigated the flexural behavior and dynamic responses of SC wall-to-foundation connections subjected to low-velocity impact. Impact tests were performed on three SC connection specimens to evaluate failure mode, impact force, deflection, and strain responses. The effects of concrete strength grade and impact energy were analyzed in detail. All specimens exhibited flexural failure, with three distinct stages observed during impact. The experimental results demonstrated that compared to the specimen with C30 concrete, the specimen with C50 concrete significantly reduced wall damage, decreased deflections, and enhanced deflection recovery ability. It can be concluded that increasing the concrete strength grade effectively improves the impact resistance of SC wall-to-foundation connections. In addition, peak impact force, global deflection response, residual strains, and interface crack length were highly sensitive to changes in impact energy, whereas deflection recovery exhibited lower sensitivity. Furthermore, a finite element model was developed and validated against experimental results. Parametric studies explored the influence of key parameters with expanded ranges on the impact responses of SC wall-to-foundation connections. Full article

Aging railroad bridges present complex challenges due to advancing deterioration and outdated design assumptions. This study develops a comprehensive analytical approach for assessing an aging steel truss railroad bridge through finite element (FE) modeling, sensitivity analysis, and model updating, supported by field testing. An initial FE model of the bridge was created based on original drawings and field observations. Field testing using a laser Doppler vibrometer captured the bridge’s dynamic response (vibrations and deflections) under regular train traffic. Key structural parameters (material properties, section properties, support conditions) were identified and varied in a sensitivity analysis to determine their influence on model outputs. A hybrid sensitivity analysis combining log-normal sampling and a genetic algorithm (GA) was employed to explore the parameter space and calibrate the model. The GA optimization tuned the FE model parameters to minimize discrepancies between simulated results and field measurements, focusing on vertical deflections and natural frequencies. The updated FE model showed significantly improved agreement with observed behavior; for example, vertical deflections under a representative train were matched within a few percent, and natural frequencies were accurately reproduced. This validated model provides a more reliable tool for predicting structural performance and fatigue life under various loading scenarios. The results demonstrate that integrating field data, sensitivity analysis, and model updating can greatly enhance the accuracy of structural assessments for aging railroad bridges, supporting more informed maintenance and management decisions. Full article

The offshore implementation of vertical-axis wind turbines (VAWTs) presents a promising new paradigm for advancing marine wind energy utilization, owing to their omnidirectional wind acceptance, compact structural design, and potential for lower maintenance costs. However, VAWTs still face major aerodynamic challenges, particularly due to the pitching motion, where the angle of attack varies cyclically with the blade azimuth. This leads to strong unsteady effects and susceptibility to dynamic stalls, which significantly degrade aerodynamic performance. To address these unresolved issues, this study conducts a comprehensive investigation into the dynamic stall behavior and wake vortex evolution induced by Darrieus-type pitching motion (DPM). Quasi-three-dimensional CFD simulations are performed to explore how variations in blade geometry influence aerodynamic responses under unsteady DPM conditions. To efficiently analyze geometric sensitivity, a surrogate model based on a radial basis function neural network is constructed, enabling fast aerodynamic predictions. Sensitivity analysis identifies the curvature near the maximum thickness and the deflection angle of the trailing edge as the most influential geometric parameters affecting lift and stall behavior, while the blade thickness is shown to strongly impact the moment coefficient. These insights emphasize the pivotal role of blade shape optimization in enhancing aerodynamic performance under inherently unsteady VAWT operating conditions. Full article

This study investigates the deformation and fracture mechanisms of a Ti₆₁Al₁₆Cr₁₀Nb₈V₅ multi-principal element alloy (Ti61V5 alloy) under quasi-static and dynamic compression. The alloy comprises an equiaxed BCC matrix (~35 μm) with uniformly dispersed nano-sized B2 precipitates and a ~3.5% HCP phase along grain boundaries, exhibiting a density of 4.82 g/cm³, an ultimate tensile strength of 1260 MPa, 12.8% elongation, and a specific strength of 262 MPa·cm³/g. The Ti61V5 alloy exhibits a pronounced strain-rate-strengthening effect, with a strain rate sensitivity coefficient (m) of ~0.0088 at 0.001–10/s. Deformation activates abundant {011} and {112} slip bands in the BCC matrix, whose interactions generate jogs, dislocation dipoles, and loops, evolving into high-density forest dislocations and promoting screw-dominated mixed dislocations. The B2 phase strengthens the alloy via dislocation shearing, forming dislocation arrays, while the HCP phase enhances strength through a dislocation bypass mechanism. At higher strain rates (960–5020/s), m increases to ~0.0985. Besides {011} and {112}, the BCC matrix activates high-index slip planes {123}. Intensified slip band interactions generate dense jogs and forest dislocations, while planar dislocations combined with edge dislocation climb enable obstacle bypassing, increasing the fraction of edge-dominated mixed dislocations. The Ti61V5 alloy shows low sensitivity to adiabatic shear localization. Under forced shear, plastic-flow shear bands form first, followed by recrystallized shear bands formed through a rotational dynamic recrystallization mechanism. Microcracks initiate throughout the shear bands; during inward propagation, they may terminate upon encountering matrix microvoids or deflect and continue when linking with internal microcracks. Full article

The drilling and blasting method is commonly employed for the rapid demolition of outdated buildings by destroying key structural components and inducing progressive collapse. The residual bearing capacity of these components is governed by the deformation morphology of the longitudinal reinforcement, characterized by bending deflection and exposed height. This study develops and validates a finite element (FE) model of a reinforced concrete (RC) column subjected to demolition blasting. By varying concrete compressive strength, the yield strength of longitudinal reinforcement, the longitudinal reinforcement ratio, and the shear reinforcement ratio, 45 FE models are established to simulate the post-blast morphology of longitudinal reinforcement. Two databases are created: one containing 45 original simulation cases, and an augmented version with 225 cases generated through data augmentation. To predict bending deflection and the exposed height of longitudinal reinforcement, artificial neural network (ANN) and random forest (RF) models are optimized using the hunter–prey optimization (HPO) algorithm. Results show that the HPO-optimized RF model trained on the augmented database achieves the best performance, with MSE, MAE, and R² values of 0.004, 0.041, and 0.931 on the training set, and 0.007, 0.057, and 0.865 on the testing set, respectively. Sensitivity analysis reveals that the yield strength of longitudinal reinforcement has the most significant impact, while the shear reinforcement ratio has the least influence on both output variables. The partial dependence plot (PDP) analysis indicates that the ratio of shear reinforcement has the most significant impact on the deformation of longitudinal reinforcement. Full article

Capacitive micromachined ultrasonic transducers (CMUTs) have been widely applied in fields such as air-coupled ultrasonic nondestructive testing, gesture recognition, and 3D imaging. However, most current CMUTs struggle to simultaneously achieve both low power consumption and high performance, which limits their application in relevant fields. In this paper, a dual-layer CMUT is proposed, and its structural optimization design is also analyzed. The dual-layer CMUT consists of a top-layer circular CMUT cell and a bottom-layer annular CMUT cell. A movable pillar connects the top and bottom cells of the double-layer CMUT. This design increases the total deflection and reduces the stiffness, making the membrane more susceptible to deformation under external forces, thereby achieving low power consumption and high reception performance. The finite element method (FEM) results showed that, compared with conventional CMUTs, the structural optimization design of the dual-layer CMUT had a 13.7% reduction in collapse voltage. The improvements in the maximum deflection, average deflection, electromechanical coupling coefficient, transmitting sensitivity, and receiving sensitivity were 41.2%, 68.0%, 84.6%, 17.7%, and 101.6%, respectively. Therefore, the dual-layer CMUT has low power consumption and high reception performance while maintaining transmission performance, and it has potential for applications in portable, low-power devices and air-coupled ultrasonic nondestructive testing. Full article

To address the challenge of evaluating a radar cross-section (RCS) for a non-cooperative aircraft with limited aerodynamic shape information, this paper presents a multi-source, data-driven inverse reconstruction method. This approach integrates data fusion techniques to facilitate an initial shape reconstruction, followed by an iterative optimization process that utilizes computational fluid dynamics (CFD) to enhance the shape, accounting for the aerodynamic performance. Additionally, an inverse deduction analysis is effectively employed to ascertain the characteristics of the power system, leading to the design of a double S-curved tail nozzle layout with stealth capabilities. An aerodynamic analysis demonstrates that at Mach 0.6, the lift-to-drag ratio peaks at 27.3 for the attack angle of 4°, after which it declines as the angle increases. At higher angles of attack, complex flow separation occurs and expands with the increasing angle. The electromagnetic simulation results indicate that under vertical polarization, the omnidirectional RCS reaches its peak as the incident angle is deflected downward by 10° and reduces with the growth of the angle, demonstrating angular robustness. Conversely, under horizontal polarization, the RCS is more sensitive to edge-induced rounding. The findings illustrate that this methodology enables accurate shape modeling for non-cooperative targets, thereby providing a fairly solid basis for stealth performance evaluation and the assessment of surprise effectiveness. Full article

This study employs the simultaneous phase-shift interferometry (SPSI) system to diagnose laser-induced plasma (LIP) and shock wave (SW). In high-density LIP diagnostics, the Faraday rotation effect causes probe light polarization deflection, rendering traditional fixed-phase-demodulation methods ineffective, the Carré phase-recovery algorithm is adopted and its applicability is verified. Uncertainty analysis and precision verification show that the total phase shift uncertainty is controlled within 0.045 radians, equivalent to a refractive index accuracy of $8.55\times {10}^{-6}$, with sensitivity to weak perturbations improved by approximately one order of magnitude compared to conventional carrier-frequency interferometry. Experimental results demonstrate that the SPSI system precisely captures the initial spatiotemporal evolution of LIP and tracks shock waves at varying attenuation levels, exhibiting notable advantages in weak shock wave detection. This research validates the SPSI system’s high sensitivity to transient weak perturbations, offering a valuable diagnostic tool for high-vacuum plasmas, low-pressure shock waves, and stress waves in optical materials. Full article

In this work, photothermal beam deflection spectrometry (BDS), combined with a passive sampling technique of diffusive gradients in thin film (DGT), is optimized to improve the method’s sensitivity. The limit of detection (LOD) is then reduced by a factor of 2 (to the value of 20 nM). The functionality of the technique is compared for Chelex-100 (Ch-100) and suspended particulate reagent–iminodiacetate resin (SPR-IDA), used as binding resins in passive samplers. The absorption capacity of SPR-IDA resin is found to be less than 1 μM and far below that one of Chelex-100 resin (around 6 μM). The BDS technique is applied for determination of iron redox species concentration in sediment porewater. It is found that Fe in sediment porewater occurs both in Fe²⁺ (0.073 μM) and Fe³⁺ (0.095 μM) forms. The validation of the presented method reveals that the BDS technique ensures good repeatability, reproducibility, and reliability. Full article