Search Results (2,103)

Large-span structures may experience progressive collapse involving complex member collisions, for which efficient and accurate simulation remains a challenging problem in engineering practice. Conventional finite element methods are computationally inefficient in such scenarios due to repeated reconstruction of contact constraints and global stiffness matrices, while existing member discrete element method (MDEM) approaches lack a unified contact algorithm capable of handling both “point–line” and “line–line” contact modes. To address these limitations, this study extends the MDEM framework for structural collision analyses by establishing unified “point–line” and “line–line” contact models. A “virtual contact point pair” concept was introduced to define critical contact constraints, and corresponding contact force formulations were derived. A Fortran-based computational program was developed. Numerical validation through typical examples showed that the maximum relative error was 4.2% for the elastic ring problem and 3.1% for the double cantilever beam, while the rebound angle deviation in the flexible ring impact case was less than 2°. The proposed method avoids global stiffness matrix reconstruction and achieves a 95–98% accuracy compared to reference solutions under recommended parameters, providing an efficient approach for simulating member collisions in large-span structural collapse and supporting engineering analyses and design. Full article

Legal element recognition, which identifies discrete factual elements in Chinese court judgments to support judicial analysis and case retrieval, faces a severe long-tail challenge: head-to-tail label-frequency ratios exceed 100:1, and over 60% of sentences carry no label, starving rare elements of training signal. Static reweighting methods assign fixed weights prior to training and cannot respond to the model’s evolving confidence; sample-level meta-learning couples all co-occurring label gradients to a single scalar, preventing independent tail-label amplification. We propose BML-Trans, a boundary-aware meta-learning framework that addresses both limitations. A label-wise meta-weighting mechanism maintains per-label gradient weights updated via bilevel hypergradient descent, decoupling tail-label amplification from co-occurring head labels. A boundary-aware meta-set concentrates calibration signal on high-uncertainty, tail-triggering sentences rather than on easy negatives, and a lightweight Multi-Scale Adapter sharpens the warm-up probability estimates on which boundary selection depends. Concretely, BML-Trans achieves an average Avg-F1 of 82.5% on CAIL2019 across the labor, divorce, and loan domains, outperforming the strongest baseline by 1.2 percentage points overall and by up to 5.7 percentage points on tail-label Macro-F1, at only 14% additional training cost. Ablation confirms a cascade dependency among the three components, establishing that the gains are structural rather than incidental to threshold selection or initialization. Full article

Underwater dynamic target detection, classification, localization, and tracking (DCLT) is central to maritime surveillance and monitoring and increasingly relies on distributed AUV-based robotic sonar networks operating in passive listening and, when required, cooperative multistatic modes. Achieving a robust performance in realistic oceans remains challenging, because sensor placement must adapt to time-varying acoustic conditions and target priors while preserving acoustic communication connectivity, and because frequent reconfiguration under dynamic currents makes classical large-scale planning computationally expensive. This paper presents an integrated deep reinforcement learning (DRL)-based framework for passive-stage sonar placement and dynamic reconfiguration in distributed AUV networks. First, we cast placement as a constructive finite-horizon Markov decision process (MDP) and train a Proximal Policy Optimization (PPO) agent to sequentially build a collision-free layout on a discretized surveillance grid. The terminal reward is formulated to jointly optimize the environment-aware detection performance, computed from BELLHOP-based transmission loss models, and global network connectivity, quantified using algebraic connectivity. Second, to enable time-critical reconfiguration, we estimate flow-aware motion costs for all AUV–destination pairs using a PPO with a Long Short-Term Memory (LSTM) trajectory policy trained for partial observability. The learned policy can be deployed onboard, allowing each AUV to refine its path online using locally sensed currents, improving robustness to ocean-model uncertainty. The resulting cost matrix is solved via an efficient zero-element assignment method to obtain the optimal one-to-one reassignment. In the reported simulation studies, the proposed Sequential PPO placement method achieves a final reward 16–21% higher than Particle Swarm Optimization (PSO) and 2–3.7% higher than the Genetic Algorithm (GA), while the proposed PPO + LSTM planner reduces average travel time by 30.44% compared with A*. The proposed closed-loop architecture supports frequent re-optimization, scalable fleet operation, and a seamless transition to communication-supported cooperative multistatic tracking after detection, enabling efficient, adaptive DCLT in dynamic marine environments. Full article

Fibers in vortex turbulence fields involve complex gas–solid coupling effects, significantly influencing the spinning process within vortex nozzles. This paper utilizes the Discrete Element Method (DEM) to refine the existing rigid bead–elastic rod model describing fiber constitutive behavior. This improved model is used to numerically simulate the dynamic behavior of a single flexible fiber within the vortex field of the nozzle. Based on elastic mechanics, this study establishes mapping functions converting relative displacement and angular displacement between beads into internal forces and torques within the beads. A contact model is also developed to handle fiber–wall interactions. The effects of different nozzle structures on fiber motion are investigated. The improved model successfully simulates the entire motion process of a single fiber during spinning. Its reliability is validated by comparing with experimentally collected fiber motion data. The study reveals that a twist chamber diameter of 6 mm, a conical cavity angle of 55 degrees, and a distance of 1.05 mm between the jet orifice and the hollow spindle yield optimal fiber twist count and wrapping density. This research provides effective insights for developing textile equipment that relies on airflow to drive fiber spinning and contributes to establishing a comprehensive twisting mechanism. Full article

Sugarcane is an important economic crop in southern China. Affected by typhoons, it is prone to lodging, which not only increases the difficulty and loss rate of mechanical harvesting but also reduces the sugar content. The mechanical properties of the sugarcane root–soil system are crucial to its lodging resistance. However, accurate discrete element parameters are still lacking for DEM-based research on the mechanical properties of this system. Therefore, this study adopts a method combining the angle of repose test, shear force test, and discrete element simulation of single roots to calibrate DEM parameters. Using the angle of repose and maximum shear force of a single root as response values, Plackett–Burman, steepest ascent, and Box–Behnken tests are sequentially carried out with Design-Expert 13 software to calibrate the contact and bonding parameters of individual sugarcane roots. The relative errors between the physical and simulation test results for the angle of repose and shear force are 1.29% and 0.66%, respectively. This study provides a reference for the establishment of discrete element simulation models for sugarcane roots and for the subsequent development of sugarcane root–soil composite models. Full article

High-pressure grinding rolls (HPGRs) are critical in mineral processing, making comprehensive research and analysis of their performance of great significance. This study focuses on the HPGR-3516 test prototype and develops an analytical model that combines the discrete element method (DEM) with multi-body dynamics (MBD). The influences of feed top size, roll speed, and specific press force on equipment performance were examined using analysis of variance (ANOVA) in conjunction with response surface methodology (RSM). A performance prediction model was established through regression analysis, followed by multi-objective optimization and experimental validation. The results indicate that increasing roll speed under high specific press force significantly reduces the roll gap, while the effect is negligible under low specific press force. Increasing roll speed improves throughput more substantially for fine feed than for coarse feed. The optimal process parameters were determined to be a feed top size of 8 mm, a roll speed of 0.37 m/s, and a specific press force of $4.84 \mathrm{N}/{\mathrm{m}\mathrm{m}}^2$. In comparison to the original parameters, throughput increased by 15.81%, qualified particle size passing rate (QPR) improved by 7.85%, and roll gap decreased by 10.24%. This study offers valuable insights into predicting the dynamic performance of HPGRs and has significant engineering implications. Full article

Uneven seed spacing, skewed stalk posture, and inconsistent planting depth remain major challenges in horizontal sugarcane planting. To address these issues, a semi-automatic transverse sugarcane planter integrating a supply–buffer–discharge seeder and multiple soil-engaging components was developed. The seed placement process and the interaction between stalk discharge and soil disturbance were investigated through Discrete Element Method (DEM) simulations and experiments. First, the working principle and key component parameters of the whole machine were determined. It integrated the processes of soil crushing, furrowing, seeding, ridge covering. In addition, a dynamic analysis was conducted on the inter-particle disengagement effect during the two-step seed filling process of lifting and discharging. Secondly, a discrete element simulation model for the entire process of soil-engaging seed arrangement operations was established for the machine. The effects of forward speed and seed outlet position were studied using a discrete element method (DEM) simulation model that coupled soil disturbance flow with stalk-seed discharge behaviour. Furthermore, a response surface methodology (RSM) experiment was performed on the seeding test bench to quantify the effects of guiding parameters on seed placement uniformity. The determination coefficient (R²) of the established regression model exceeded 0.9, indicating high prediction accuracy. The optimal collaborative parameter combination was optimized as follows: forward speed of 1.2 m·s⁻¹, buffer inclination angle of 55°and supply roller speed of 26 r·min⁻¹. After verification, the seed placement uniformity coefficient of the seeder reached 91.8 ± 1.4%, which met the expected accuracy requirements for horizontal planting. Full article

To investigate the non-smooth behaviour of cage-less ball bearings with localised functional grooves, this article first designs temperature-varying comparative experiments and rolling element discrete performance test protocols. Subsequently, it analyses the principles of heat generation, transmission, and exchange within ball bearings, establishing a mathematical model for bearing thermal displacement using a dynamic model. This is followed by an analysis of rolling element discrete conditions. Finally, based on experimental results, a comparative analysis of ball bearing temperature variations under combined multi-variable loading conditions is conducted. By altering radial load, axial load, and rotational speed to measure bearing friction torque under different operating conditions, the suitability of bearing operating conditions is analysed, evaluated, and optimised. Full article

This study presents a unified mechanics-based framework for evaluating bonded composite patch repairs. Discrete fracture, fatigue, and adhesive responses are transformed into continuous master equations over the design space. Low-order polynomial surfaces model stress intensity and concentration responses, enabling continuous prediction of repair performance without repeated finite-element analyses. A fracture-based repair efficiency index is derived from the analytical master surface. This index quantifies the average reduction in crack-driving force across the domain. Combined with adhesive stiffness and strength, it defines an adhesive-based repair efficiency index (A-REI), providing a direct link between structural response and material properties. The results show that repair effectiveness is strongly influenced by both geometric severity and adhesive properties. Fatigue performance decreases significantly with increasing notch ratio in single-sided repairs. Double-sided configurations maintain consistently higher efficiency. Symmetric reinforcement more effectively reduces stress concentration, with improvements exceeding 40% at intermediate notch ratios. Adhesive selection is governed by stiffness and strength. Structural adhesives achieve significantly higher A-REI values, whereas compliant adhesives contribute negligibly. Overall, repair symmetry controls the magnitude of improvement, while adhesive properties determine performance ranking. This framework provides a clear, practical basis for design and material selection. Full article

The dynamic modulus of asphalt mixtures is a key design parameter in pavement design, which significantly impacts the mechanical properties of asphalt pavements. This study simulated dynamic modulus tests of asphalt mixtures using the three-dimensional (3D) discrete element method (DEM) to investigate mechanical behaviors such as the loading-bearing ratio of individual aggregates. Fine-grained AC-13 and medium-grained AC-20 asphalt mixture models were randomly constructed in the DEM program using user-defined methods. The dynamic modulus and phase angle values of the asphalt mixtures were predicted. By comparing laboratory experiments with DEM simulation results, the model was validated, and the effects of temperature and loading frequency on the dynamic modulus were explored. Further exploration was conducted on the loading-bearing ratio and mechanical interactions among aggregates of different sizes within the mixtures. The results show that the 3D DEM model can accurately predict the dynamic modulus and phase angle of asphalt mixtures. Temperature and frequency have an impact on these parameters, and the increase in gradation has an impact on the loading-bearing ratio, due to the proportion of coarse aggregates. Full article

Long-term safety assessment of deep geological repositories for spent nuclear fuel requires explicit evaluation of thermo-mechanical (TM) processes induced by decay heat and their influence on fractured host rock. A safety-relevant, though low-probability, scenario concerns shear reactivation of fractures intersecting deposition holes, which could compromise canister integrity if displacement exceeds design limits. This study presents a three-dimensional discrete element modelling approach to analyze the thermal evolution of the Forsmark repository (Sweden) and the associated long-term response of a discrete fracture network (DFN) during the post-closure phase. The model explicitly represents repository panel, deterministic deformation zones, and a stochastically generated fracture network embedded in a bonded particle assembly representing the rock for Particle Flow Code (PFC) numerical simulations. Time-dependent heat release from spent nuclear fuel canisters is implemented using a physically based decay power function. A deposition panel-scale heat-loading formulation accounts for deposition-hole and tunnel spacing. Two emplacement scenarios are analyzed: (a) a simultaneous all-panel heating scenario, used as a conservative bounding case, and (b) a sequential panel heating scenario representing staged emplacement and closure. The simulations show that temperature and thermally induced stress evolution are sensitive to the emplacement and closure sequence. Sequential heating produces a more gradual thermal build-up and lower peak temperatures than simultaneous heating, indicating that thermal and stress perturbations in the host rock can be influenced not only through repository design, but also by operational strategy. Thermally induced fracture shear displacement displays a systematic temporal response. Fractures located within the deposition panel footprint develop shear displacement rapidly during the early post-closure period, reaching peak values at approximately 200 years, followed by gradual relaxation as temperatures decline. The average peak shear displacement on fractures is on the order of 2–3 mm, while fractures outside the panel footprint show smaller early-time displacements and a more prolonged long-term response. All simulated shear displacements remain more than one order of magnitude below the commonly cited canister damage threshold for Forsmark of approximately 50 mm, even for the conservative simultaneous heating case. These results indicate that thermally induced fracture shear is unlikely to cause direct mechanical damage to canisters. At the same time, the persistence of residual shear displacement after heating implies permanent fracture dilation, which may influence long-term hydraulic properties and indirectly affect processes such as groundwater flow and canister corrosion. The modelling framework and results presented here were conducted for review purposes independently from the Swedish safety case, and provide a mechanistic basis for evaluating thermally induced fracture deformation in crystalline rock repositories and contribute to bounding the role of thermo-mechanical processes in the safety assessment of spent nuclear fuel disposal at Forsmark. Full article

As the most prevalent type of existing building in China, masonry structures are susceptible to cracking due to the low tensile strength of the masonry material. In the event of a sudden, strong earthquake, they are highly prone to brittle collapse, leaving occupants little time and space to escape. Based on this, combining the advantages of the elastoplastic mechanical theory and the nonlinear finite element (FE) method, this study adopts different modeling methods: integral modeling (IM), contact element discrete modeling (CEDM), spring element discrete modeling (SEDM), and co-node discrete modeling (CNDM). FE models of unreinforced masonry walls (UMWs) are established, respectively, and a monotonic pushover mechanical performance analysis is carried out. The accuracy of the adopted modeling methods is verified against existing test results for UMW specimens. Through parametric analysis of aspect ratios (0.5, 0.75, 1.0, and 1.25), axial compression ratios (0.1, 0.3, 0.5, 0.7, and 0.8), and mortar strengths (M5, M7.5, and M10), the characteristic mechanical performance factors of UMWs are determined. A novel strength index is proposed to discriminate between failure modes and elucidate the damage mechanism of UMWs. The results indicate that the ultimate load and its corresponding displacement change systematically with variations in aspect ratios, axial compression ratios, and mortar strengths. Furthermore, integrating stress cloud maps with the proposed strength index provides a quantitative basis for discriminating between flexural and shear failure modes in UMWs. All four modeling methods can, to varying degrees, capture the pushover behavior of UMWs, and quantifiable selection schemes are provided to balance analysis accuracy and computational cost. The analytical methods and findings presented in this work can be applied to performance assessment, seismic design, and engineering practice of UMWs. Full article

Understanding the mechanical behavior of lunar regolith is critical for the success of future lunar excavation and construction missions. Irregular particle morphology and low geostatic stress are recognized as key factors contributing to the high internal friction angle of this unique extraterrestrial geomaterial. However, the underlying mechanisms by which low geostatic stress enhances shear strength remain unclear, and the multiscale effects of particle morphology on shear strength evolution are not yet fully elucidated. In this study, consolidated drained triaxial compression tests were performed on CUMT-1 lunar regolith simulant and Fujian standard sand to investigate their macroscopic mechanical behavior. Complementary discrete element simulations of biaxial compression were conducted to analyze mesoscopic mechanical responses of granular materials under the influence of multiscale particle morphology and confining stress. A robust macroscopic–mesoscopic strength correlation model was established, incorporating normalized mean interparticle contact force and mean coordination number to predict the normalized deviatoric stress of granular assemblies. Based on this model, the mesoscopic mechanisms through which irregular particle morphology and low geostatic stress enhance the internal friction angle were quantitatively investigated. The findings offer new insights into the shear strength characteristics of in situ lunar regolith and provide theoretical support for lunar surface construction and excavation operations. Full article

The performance of ballasted railway tracks under cyclic loading is a critical issue in urban railway systems, where high traffic frequency and geometric constraints accelerate track degradation, leading to the accumulation of plastic deformations that may reduce operational efficiency. This study presents a numerical framework for rail track performance assessment based on two complementary modeling approaches: a fully continuous Finite Difference Method (FDM) model, and a hybrid Discrete Element Method–Finite Difference Method (DEM–FDM) model. The continuous FDM simulations are employed to evaluate the global mechanical response of the track support system and to compute conventional stability indicators, including the factor of safety (FS). In parallel, the hybrid DEM–FDM simulations explicitly represent the ballast layer using DEM to capture inter-particle interactions, accumulation of permanent deformation, and particle fragmentation under cyclic loading, while rails, sleepers, sub-ballast, and subgrade are modeled using FDM to describe system-level load transfer. Ballast performance is assessed by linking safety factors obtained from the continuous models with mechanically derived permanent deformation and stress measures extracted from the hybrid simulations. The proposed dual-modeling framework enables a systematic investigation of the influence of ballast layer thickness and material type on deformation accumulation, stress transmission, and granular degradation mechanisms. The results reveal distinct behavioral trends among different ballast materials, showing that increased ballast thickness generally improves track performance, while material-specific degradation mechanisms govern the evolution of permanent deformation under repeated loading. The proposed approach establishes a quantitative bridge between traditional stability-based design metrics and deformation-based performance indicators, providing a rational basis for performance-based evaluation, comparison, and optimization of ballast configurations through a set of robust numerically derived relationships for railway track design. Full article

Time–space fractional diffusion equations are widely used to model anomalous transport in heterogeneous biological tissues, where memory effects, spatial nonlocality, and coefficient variability are intrinsically coupled. However, existing numerical approaches typically treat these aspects in isolation, and a fully discrete framework that simultaneously accounts for heterogeneity, long-memory effects, and computational efficiency remains lacking. In this work, a fully discrete numerical method is developed and analyzed. The method integrates heterogeneous diffusion coefficients and memory-efficient temporal discretization within a unified variational framework. It combines a finite element approximation of a spectral fractional elliptic operator with an implicit $L^1$ discretization of the Caputo derivative enhanced by a sum-of-exponentials approximation of the memory kernel. Unconditional stability, preservation of a discrete energy structure, and a fully discrete error estimate are established, explicitly separating temporal, spatial, and kernel approximation errors. The proposed approach reduces memory complexity from $\mathcal{O}\left(N\right)$ to $\mathcal{O}(logN)$ without compromising accuracy. Numerical experiments confirm the theoretical convergence rates, demonstrate stable behavior across all tested configurations, and illustrate the impact of heterogeneous coefficients on anomalous transport dynamics. Full article