Search Results (32,368)

Hydrodynamic models underpin Autonomous Underwater Vehicle (AUV) design, motion control, and performance evaluation. Existing methods face two critical bottlenecks: (1) conventional explicit CFD requires predefined trajectories, which fails to capture true motion responses under combined rudder-propeller action and creates a disconnect between simulation and real operations; (2) the widely adopted Standard Submarine Motion Equations (SSME) suffer from high parameter redundancy, while high-precision non-parametric models incur prohibitive computational costs, hindering embedded deployment. To address these gaps, this paper proposes an implicit CFD-driven framework for fully appended AUVs equipped with through-body thrusters. It requires no preset trajectories, directly coupling periodic propeller thrust and rudder angle excitations to achieve 5-degree-of-freedom (5DOF) spatial motion simulations aligned with real navigation states. Parametric and non-parametric models are identified via Least Squares (LS) and Neural Networks (NN), respectively. Sobol global sensitivity analysis reduces SSME dimensionality, yielding a Basic Submarine Motion Equation (BSME) with only 25 key parameters—cutting the parameter count by 55% with negligible accuracy loss. Validation shows the non-parametric NN model reduces prediction error by over 10% compared to its parametric counterpart, while the streamlined BSME enables real-time forecasting in low-power computing scenarios. This approach balances accuracy and efficiency for rapid hydrodynamic prediction during early AUV design and embedded controller deployment. Full article

As a major contaminant fungus in grains and by-products, Fusarium graminearum rapidly colonizes and proliferates, posing safety risks to feed commodities. In this study, artificial inoculation was adopted to simulate F. graminearum contamination in soybean meal. Dynamic changes in fungal population, protein secondary structure, microstructure and volatile organic compounds (VOCs) were systematically monitored across a 54-day storage period. Soybean meal exhibited a three-phase deterioration pattern: latent infection (0–30 d), accelerated spoilage at day 36, and severe deterioration (42–54 d). Fungal conidia counts increased sharply before declining moderately with extended incubation. Ordered protein conformations (α-helix and β-sheet) underwent continuous degradation and converted into disordered β-turn and random coil structures, accompanied by gradual disruption of the compact microstructure of soybean meal. In total, 99 VOCs spanning 13 chemical classes were identified throughout the contamination timeline. Combining orthogonal partial least squares discriminant analysis (OPLS-DA) and Pearson correlation analysis, five volatile biomarkers tightly associated with F. graminearum spoilage were screened: four upregulated fungal metabolites and one downregulated endogenous flavor compound. This work characterizes the dynamic deterioration profiles and volatile fingerprint of F. graminearum-inoculated soybean meal under controlled laboratory conditions, delivering preliminary laboratory evidence to support the future development of potential spoilage monitoring approaches. Full article

Cold recycled mixtures with bitumen emulsion (CRME) serving in seasonally frozen regions are susceptible to mechanical deterioration under repeated freeze-thaw (F-T) cycles, which is primarily manifested as interfacial damage and crack propagation. However, the micro-mechanical processes associated with the transmission and dissipation of frost-heaving stresses induced by water-ice phase transition within the interfacial transition zone (ITZ) between reclaimed asphalt pavement (RAP) and asphalt mortar remain to be further characterized. In this study, a numerical simulation approach coupling frost heave effects with the phase transition of water-ice particles was developed based on X-ray computed tomography (CT) and the discrete element method (DEM), and the micro-mechanical parameters of the RAP-asphalt mortar ITZ were determined through laboratory experiments. Combined with acoustic emission (AE) monitoring, the damage evolution characteristics of cold recycled mixtures and the associated interfacial damage mechanisms under freeze-thaw action were systematically investigated. The results indicate that the optimal micro-parameters of the RAP-asphalt mortar ITZ can be taken as approximately 85% of those of virgin asphalt mortar. After 20 freeze-thaw cycles, the number of shear cracks and tensile cracks in ITZ on RAP surface reached 493 and 92, respectively, which were much higher than 11 and five on the surface of new aggregate. ITZ was the main control weak area of freeze-thaw damage. Compared with the unfrozen specimens, the minimum effective contact number of mortar decreased by 1.63%, 4.52% and 8.52% respectively after 5, 10 and 20 freeze-thaw cycles, and the total effective contact number decreased from 75,842 to 69,383. Freeze-thaw cycles significantly reduce the strain energy storage capacity of CRME: the maximum energy storage capacity of the adhesive spring decreased from 2.15 J in the non-freeze-thaw state to 1.28 J in 10 cycles (a decrease of 40.47%) and 1.16 J in 20 cycles (a decrease of 46.05%), and the damage mode changed from brittle fracture to interface-controlled energy dissipation. The proposed water-ice phase transition-based DEM framework provides a reliable numerical tool for investigating freeze-thaw damage mechanisms and supporting durability-oriented design of cold recycled pavement materials. Full article

Synergistic pollution–carbon mitigation is critical for China’s dual carbon targets. Taking coal-resource Shanxi Province as the case, this study developed an integrated Long-range Energy Alternatives Planning (LEAP)–Community Multiscale Air Quality (CMAQ) coupled framework combined with a three-dimensional vector model to simulate energy consumption, CO₂, and major air pollutant emissions (CO₂, CO, SO₂, NO₂, PM_2.5, and PM₁₀) under Baseline and Policy scenarios (2026–2050). The core novelty of this study lies in methodological innovation: the multi-model linkage realizes full-chain energy-emission-atmosphere simulation, remedying the isolation flaw of single models in prior research. The results indicated that low-carbon levels would rise steadily in both scenarios from 2026 to 2050. The Policy scenario achieved superior long-term low-carbon performance compared with the Baseline scenario and narrowed gaps in underdeveloped social subsystems, despite short-term transition costs. This scenario optimized the overall energy structure yet failed to fully reduce emission loads from residential and transport sectors. It drastically cut carbon and pollutant emissions, optimized spatial emission patterns, and decoupled most air pollutants from carbon emissions. However, this scenario still had prominent limitations: phased delays in emission abatement, strong coupling of CO, NO₂ and carbon emissions, and rising residential carbon emissions. Further pollution–carbon synergy assessment revealed worsening multi-dimensional imbalances under the Baseline scenario. While the Policy scenario experienced temporary systemic imbalance, its long-term coordination level improved steadily. This finding verified that systematic, long-term low-carbon governance constituted the core driver of Shanxi’s green transition. Targeted phased, classified collaborative governance strategies were proposed to resolve structural transformation risks for resource-based regions. Full article

Pneumatic soft actuators have been drawing considerable attention in the field of soft robotics, thanks to their inherent flexibility, high power density, and safe interaction. However, the strong, intricate coupling between the material’s hyperelastic behavior and the reinforcement of anisotropic fibers creates significant challenges for both analytical modeling and numerical characterization of these actuators. In this paper, we design and fabricate a fiber-reinforced pneumatic soft actuator using Ecoflex 00-30 silicone rubber as the base material and helically wound fibers as the reinforcing layer. We set up a theoretical framework that combines the Neo-Hookean model for isotropic silicone rubber with a strain energy-based formulation for anisotropic wound fibers. This framework describes how the actuator is stretched, expanded, twisted, and bent. Finite element simulations are then carried out, focusing on three key design parameters: winding fiber density (three levels: high, medium, low), air cavity offset distance from the central axis (1, 2, 3, and 4 mm), and air cavity cross-sectional geometry (cube vs. cylindrical). The simulations reveal that a higher winding fiber density promotes more uniform stress distribution across both the strain and confinement layers. In contrast, a low fiber density can lead to local bulging and large stress variations, which ultimately compromises the bending performance. The offset distance of the air cavity from the neutral axis is directly linked to the bending curvature: a larger offset produces greater air cavity deformation and higher actuation efficiency. Furthermore, the cuboid air cavity yields a larger bending angle (experimentally validated up to 90° at 0.045 MPa) and better efficiency, while the cylindrical air cavity distributes stress more evenly across the outer surface of the strain layer and reduces stress concentration at the edges. These findings provide useful quantitative guidance for optimizing the structure of fiber-reinforced soft actuators and establish a framework for hybrid analytical–numerical prediction of their mechanical behavior. Full article

Sustainable and demand-adaptive railway operation requires frameworks capable of aligning service capacity with time-varying demand while ensuring safe, operationally feasible, and energy-efficient service. This paper proposes an integrated control-and-planning framework for modular pod-based railway operation based on virtual coupling. The framework combines a convoy control layer, which ensures safe and dynamically feasible virtually coupled operation, with a planning layer formulated as a mixed-integer linear programming (MILP) model for daily service allocation and convoy sizing. This hierarchical framework combines dynamically feasible convoy-control simulations with service-level planning to adapt capacity to passenger demand. The proposed methodology is evaluated through comparative simulations under peak-hour, shoulder-period, and off-peak demand scenarios, as well as over a daily schedule of 20 services. Its performance is compared with a conventional fixed-composition diesel–electric multiple unit (DEMU)-based operation. Results show that the pod-based configuration increases energy consumption under peak-hour conditions, remains comparable during shoulder periods, and substantially reduces energy consumption in off-peak operation, achieving a 57% saving in that regime. At the daily level, total energy consumption decreases from 3864 kWh to 3075 kWh, corresponding to a 20% reduction. These findings indicate that the main value of the proposed framework lies in transforming convoy composition into a demand-adaptive operational variable, thereby improving energy performance at the daily system level while preserving the safe and dynamically feasible operation of virtually coupled pod formations. Full article

Shale gas is a major unconventional energy resource in China. Its low porosity and permeability require large-scale volumetric fracturing to create conductive fracture networks. However, most induced fractures are propped discontinuously because shale reservoirs are geometrically complex. Fracture conductivity and proppant placement efficiency therefore directly control stimulation performance. Following SY/T 6302-2009, this study used linear flow-through experiments and a large-scale visual fracture simulation system to investigate the effects of proppant particle-size distribution, injection sequence, flow rate, and closure pressure on fracture conductivity and placement. The results show that the 20/40:40/70 mesh dual-particle-size combination at a 3:2 ratio provides the best overall performance. A fine-particle content of no more than 16.7% limits conductivity loss and improves the match between particle size and fracture aperture. Multilayer placement at fracture corners distributes high-stress loading and maintains conductivity. Injecting 70–140 mesh fine proppant before 40–70 mesh coarse proppant at 3.6 m³/h improves transport distance, coverage, and placement uniformity. The optimized scheme maintains stable conductivity at closure stresses of 10–80 MPa and achieves at least 95% propped-area coverage. These findings provide experimentally supported parameters for discontinuous propping and can inform shale gas fracturing design. Full article

Early and reliable diagnosis of inter-turn short-circuit (ITSC) faults is critical to maintaining the reliability, availability, and safe operation of doubly fed induction generators (DFIGs) used in wind energy conversion systems (WECSs). Incipient winding faults are particularly challenging to identify because their electrical signatures can be masked by the inherent spectral complexity of DFIG operation and variations in wind and operating conditions. This study proposes a hybrid Fast Fourier Transform-Adaptive Neuro-Fuzzy Inference System (FFT–ANFIS) diagnostic framework for the detection, localization, and severity assessment of ITSC faults in both stator and rotor windings. The proposed approach employs the FFT method to extract fault-sensitive harmonic components from stator-current signals, which are subsequently used as diagnostic features by an Adaptive Neuro-Fuzzy Inference System (ANFIS). By integrating spectral feature extraction with nonlinear neuro-fuzzy classification, the proposed framework provides an efficient and interpretable mechanism for distinguishing healthy and faulty operating conditions and assessing fault severity. The methodology is evaluated using MATLAB/Simulink simulations under healthy and multiple ITSC fault conditions with different fault locations and severity levels. The results demonstrate 100% classification accuracy for stator faults, rotor faults, and multiple short-circuit (MSC) fault conditions, together with near-zero prediction error in fault-severity estimation. These results confirm the high discriminative capability of the selected FFT-based spectral features and the effectiveness of ANFIS in establishing the nonlinear relationship between fault signatures and fault conditions. In addition, the proposed framework maintains low computational complexity and is therefore suitable for real-time condition-monitoring applications. Compared with existing diagnostic approaches, the proposed method provides a unified framework for multi-fault diagnosis while combining high diagnostic accuracy, computational efficiency, and interpretable decision-making. The proposed FFT–ANFIS framework consequently offers a practical approach for early fault detection and condition-based maintenance of DFIG-based wind turbines, with the potential to reduce unplanned downtime, maintenance requirements, and energy-production losses. Full article

For the application of unmanned aerial vehicle (UAV)-based passive target localization, the positions of the UAVs play an important role because different UAV configurations provide distinct TDOA measurement geometries. In addition, the uncertainty of the target position affects the localization performance of different UAV configurations. Focusing on the problem of target localization by UAVs, this paper studies a UAV path optimization method for passive target localization considering target-position uncertainty. First, a passive localization signal model is established, and the TDOA method based on the Chan algorithm is deployed for target passive localization. Second, the Cramer–Rao lower bound (CRLB) for the Chan–TDOA localization method is derived as the criterion of the UAVs’ path optimization. To consider target-position uncertainty, the global CRLB is calculated within the uncertainty region of the target position instead of only applying the traditional single-point CRLB. Third, to improve computational efficiency, an analytical approximation of the global CRLB is derived from a second-order Taylor expansion instead of repeatedly calculating the multiple integral terms. By combining this objective with the PSO algorithm, the UAVs’ configuration is searched and applied at each time step. Finally, numerical simulations are performed to verify the validity and effectiveness of the proposed analytical global CRLB path-optimization method. Full article

To investigate the damage behavior of a truncated-cone concrete target (TCCT) under the coupled action of reactive-jet penetration and deflagration, full-scale experiments were conducted to characterize the damage induced in the TCCT by different reactive shaped charge liner (RSCL) structures. The results show that, under the coupled action of reactive-jet penetration and deflagration, the TCCT exhibits a damage mode characterized by upper crushing and lower fracture, which is significantly affected by the RSCL structure. Based on a combined analysis of a segmented numerical simulation method for reactive-jet penetration and deflagration and the full-scale experimental results, the gain relationship between the residual mass of the reactive jet and the deflagration enhancement effect was revealed. The study shows that the internal damage of the concrete target is mainly caused by compressive waves, whereas the damage to the bottom and sidewalls is mainly caused by tensile waves reflected from the walls. The deflagration enhancement effect of the reactive jet is positively correlated with its residual mass. On average, the deflagration enhancement increased the final damaged depth and the fully damaged cross-sectional area of the TCCT by 33.4% and 117.4%, respectively. Full article

To improve the threshold accuracy of inertial switches, this study proposes a monolithic metal MEMS inertial switch with nonlinear springs. The switch uses two sets of inclined beams with asymmetric initial angles as suspension springs. Geometric nonlinearity produces low displacement sensitivity away from the design threshold and high sensitivity near the threshold. This response improves threshold discrimination and reduces the deviation between the actual and design thresholds. A nonlinear switch and a linear reference switch are designed with the same static threshold of 27.5 g. Their responses are compared using Abaqus static and explicit dynamic simulations. Both switches are monolithically fabricated from 50 μm thick 304 stainless steel by induction-electrode through-mask electrochemical micromachining (IETMEMM). Key dimensional deviations are below 2.5%. Drop-weight tests show measured nonlinear-switch thresholds of 27.8, 27.8, 26.9, and 25.4 g under half-sine shocks with pulse widths of 4, 6, 8, and 10 ms, respectively. The maximum threshold deviation is 2.1 g. The overall threshold accuracy is 92.4%, substantially higher than the 56.0% of the linear reference switch. This work combines a nonlinear threshold-regulation mechanism with monolithic IETMEMM fabrication and provides a new strategy for metal MEMS inertial switches with high threshold accuracy. Full article

Search-and-rescue (SAR) operations in disaster environments require drone swarms to coordinate efficiently despite incomplete information and potential communication failures. Existing stigmergy-based approaches provide low-bandwidth coordination but rely on fixed rules, whereas multi-agent reinforcement learning (MARL) can learn adaptive behaviors but often struggles with coordination under partial observability. To address these limitations, this paper proposes a Hybrid stigmergy–MARL framework that introduces directional pheromone-gradient observations, enabling each drone to infer the direction of likely victims and unexplored regions using locally available information. The proposed framework combines reinforcement learning with four virtual pheromone layers representing coverage history, victim likelihood, environmental risk, and communication quality. Victim detection is modeled through an abstract short-range thermal/visual sensing mechanism, while environmental information is shared through pheromone-based environmental memory to reduce dependence on direct communication. The simulated environment consists of a 40 × 40 grid, where each grid cell represents a discrete two-dimensional location. Victims occupy a single grid cell, and obstacles are modeled as static two-dimensional impassable cells. Experimental results show that the proposed approach achieved 98.9% area coverage and 93.3% victim detection, compared with 81.8% coverage and 71.7% victim detection for the RL-only baseline. Ablation experiments confirmed that directional gradient observations are the primary contributor to these improvements, while communication-loss experiments demonstrated robust performance even under complete communication outage. These findings indicate that directional pheromone-gradient observations provide an effective and communication-efficient mechanism for decentralized swarm coordination, improving search effectiveness and operational robustness in post-disaster SAR scenarios. Full article

To address the challenge of deformation control in operating tunnel structures, this study investigates a novel reinforcement method for operating shield tunnels using a basalt-fiber-reinforced polymer-wrapped concrete-filled steel tube (BFRP-CFST) composite profile. Two primary study variables were considered. At the segment level, the reinforcement condition comprised two levels: unreinforced and BFRP-CFST-reinforced, with three replicate specimens at each level (US-1 to US-3 and RS-1 to RS-3, respectively). At the full-ring level, the number of installed composite profile frames comprised five levels (n = 0, 1, 2, 3, and 4), where n = 0 represented the unreinforced reference condition. A combined experimental and numerical framework was established, including full-scale four-point bending tests on individual tunnel segments and finite element simulations of full-ring linings. Experimental results demonstrate that the ultimate bearing capacity of reinforced segments increased from 534.4 kN to 921.3 kN, corresponding to a 72.4% improvement. The load level before visible cracking increased by 84.2%. At maximum crack widths of 0.2 mm and 2.0 mm, the mid-span displacement of the reinforced segments was reduced by 30.0% and 21.4%, respectively. The test observations indicate that the prefabricated composite profiles effectively delayed crack development and improved the post-cracking stiffness of the segment. Full-ring numerical simulations further showed that installing one to four composite profile frames increased the external load corresponding to a convergence displacement of approximately 10.5 cm by 12.4%, 21.1%, 28.5%, and 37.4%, respectively. Scientifically, the results reveal a staged load-transfer process in which adhesive bonding provides distributed load transfer during the initial response, while mechanical anchors maintain residual load transfer after local interface debonding; they also establish a quantitative relationship between the number of profile frames and full-ring convergence resistance. From an applied engineering perspective, the proposed profile increased the ultimate load and crack-initiation load of the segments by 72.4% and 84.2%, respectively, while its lightweight and prefabricated configuration provides a potentially rapid rehabilitation option for operating shield tunnels. Full article

Extreme precipitation events have grown more common as a result of global climate change, and conventional static hazard assessments find it difficult to account for the dynamic progression of flood disasters. This study considers extreme precipitation factors for different return times and creates different extreme precipitation scenarios based on multiyear historical precipitation data and actual storm events. The study proposes a method for the dynamic assessment of regional flood hazard that takes extreme rainfall scenarios into account by simulating the dynamic flood inundation processes under each scenario using the Accumulated Runoff and Flood Estimation Model (AccRo v.1.0), iterative flow accumulation, and hydrological calculations. A dynamic assessment and zoning of flood hazards was carried out in Laiyuan County, Hebei Province. The results reveal that high-hazard zones coincide with the distribution of historically badly damaged townships, concentrated in the river valley plains along the Juma River. The results show that spatial patterns are simultaneously influenced by precipitation, terrain, and the river network. In the temporal dimension, under Scenario 3, the superimposition of the 50-year return period daily maximum rainfall at the 12th hour increased the high-hazard area by approximately 110% compared with that at the 11th hour. In addition, the non-uniform multi-peak rainfall pattern in Scenario 4 represented the rise, peak, and recession stages of the flood process. A combined assessment of water depth and flow velocity can effectively distinguish between two disaster-causing modes—deep water with low flow velocity and shallow water with high flow velocity—thereby addressing the underestimation of hazard in transition zones associated with the use of water depth as a single indicator. Full article

Large-scale spiking neural network simulation requires numerical integration that preserves membrane dynamics and spike timing without making fine-resolution updates prohibitively expensive. This balance is difficult for conductance-based leaky integrate-and-fire (LIF) networks because synaptic decay, threshold crossings, resets, and refractory periods form a hybrid dynamical system. To address this difficulty, we introduce a spike-aware propagation (SAP) approximation method that combines exact receptor-trace updates, analytic homogeneous membrane propagation, Gauss–Legendre quadrature, and spike localization, improving the accuracy–efficiency Pareto frontier. We establish an error bound and conditional convergence under consistent refinement for the proposed SAP. At h = 1 ms, the single-realization T = 1000 ms comparison showed a lower voltage RMSE for SAP than for Euler at the same width in the two high-activity regimes. The five-seed T = 200 ms robustness experiment likewise showed lower voltage RMSE for SAP than for NEST at the same width. At the highest drive, the paired mean reduction was 3.91 mV (95% CI, 3.85–3.97 mV). This quantified gain supports SAP as a practical route to an improved accuracy–efficiency balance in large-scale conductance-based LIF simulation while underscoring the method’s configuration-dependent and regime-dependent scope. Full article