Search Results (2,053)

This study develops a reduced-order predictive model of the Sit-To-Stand (STS) task to examine whether a simplified biomechanical representation can reproduce key STS patterns reported in the literature and to investigate the role played in movement by a flexible trunk. The model represents the human body as a planar multibody system and formulates STS as an optimization problem within a discrete mechanics framework. This formulation combines reduced model complexity, explicit torso flexibility, and a structure-preserving numerical approach for trajectory generation. Simulations were used to evaluate the effects of movement duration, reduced joint strength, and seat height on joint torques, kinematics, trunk motion, and ground reaction forces (GRFs). The results reproduced several qualitative trends reported in previous experimental studies, including increased peak joint torques and GRFs with shorter movement duration, lower joint strength, and reduced seat height, as well as greater compensatory trunk motion under more demanding conditions. These findings suggest that the proposed framework captures key adaptive features of STS mechanics and may provide useful insights for rehabilitation analysis and the design of assistive technologies such as lower-limb exoskeletons and rehabilitation devices. At the same time, the present work should be regarded as an initial methodological study, since validation is currently qualitative and further experimental calibration, quantitative validation, and sensitivity analysis remain part of ongoing work. Full article

This article proposes a novel time-space two-grid high-order compact difference scheme for the one-dimensional nonlinear Schrödinger equation subject to Dirichlet boundary conditions. In comparison with the fully nonlinear compact difference scheme, the proposed methodology combines a small-scale nonlinear fourth-order compact difference algorithm on a time-space coarse grid and a large-scale linearized correction compact difference algorithm on a fine grid. In contrast to the time two-grid compact difference method, the proposed scheme applies the two-grid technique in both the spatial and temporal domains, thereby further improving computational efficiency. Solutions from the coarse grid are projected onto the fine grid via a temporally linear and spatially cubic Lagrange interpolation operator. Unconditional stability and optimal convergence rates, which are fourth-order in space and second-order in time, are proven in both the discrete $L^2$ and $L^{\infty }$ norms, without any constraints on the grid ratio. In addition to the standard techniques of the energy method, a discrete Sobolev inequality and an a priori error estimate are employed to demonstrate stability and high-order convergence. Finally, the theoretical results are validated through numerical experiments, which confirm the robustness and reliability of the proposed approach. A single-soliton experiment demonstrates that, compared with the fully nonlinear compact difference scheme, the proposed method achieves a significant reduction in CPU time while maintaining a comparable level of accuracy. Additional experiments further illustrate the algorithm’s effectiveness in simulating two-soliton interactions and soliton birth. These findings establish the proposed scheme as a highly efficient alternative to conventional nonlinear approaches. Full article

In response to the problem that sensors cannot be directly installed at key local positions on the surface of ship hull structures during the transient strong shock process of underwater explosions due to spatial constraints or large plastic deformations, this paper investigates the chaotic-like nonlinear transient behavior of structural dynamic response systems under strong shock and proposes a key position structural response reconstruction method based on dynamic inversion. Since the structural response under a transient strong shock exhibits significant non-stationarity and nonlinearity, signals from neighboring measurement points cannot directly characterize the dynamic behavior at key positions. Therefore, the shock response signals are discretized in both time and space dimensions. The phase space reconstruction method is employed to characterize the motion trajectory of acceleration responses in a two-dimensional phase space, establish mapping functions for system motion evolution, and use their control parameters to characterize the system’s nonlinear dynamic behavior. Furthermore, based on the spatiotemporal dynamic equations, a spatiotemporal coupled mapping model for spatial state points is established to achieve the theoretical inversion of acceleration responses at key positions. This method provides theoretical support for analyzing the dynamic characteristics of structures at key positions under strong shock environments, characterizing the shock environment, and assessing and designing equipment for shock safety. However, the current validation is based on high-fidelity numerical simulations rather than physical prototype tests; therefore, the predictive capability of this method in actual physical environments requires further validation through subsequent physical model tests. Full article

Three-dimensional (3D) epicuticular wax coverage on plant surfaces contributes to multifunctional surface properties, such as enhanced water repellence, reduced pathogen adherence, modified optical properties, and reduced insect adhesion. The diversity in wax projection morphology, size, abundance, and spatial arrangement among plant species results in a broad spectrum of anti-adhesive effects, reflecting both phylogenetic history and ecological function. This study presents a numerical model consisting of 3D tubular-shaped structures randomly deposited on a substrate and forming a highly porous layer. The simulations based on this model demonstrate a strong reduction in adhesion to the contacting insect adhesive pad. It is found that a structure formed by sufficiently long tubes, where the length is enough to support the tubes in space and build a porous 3D structure with a very low density, at relatively weak attraction to the underlying substrate, leads to the weakest adhesion. The model is constructed on the basis of our recent works combining discrete and continuous approaches in biological modeling. It mainly exploits the technique of the movable digital automata, allowing modeling of numerous numerically elastic cylinders that can be moved in 3D space, elastically collide with one another and with boundaries, and build self-consistent surface structures, which can be used to mimic nano- or microscale surface coverages of real plants. 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

In water injection development of tight oil reservoirs (TORs), the complex fracture network formed by hydraulic fracturing and water injection induction is the key factor determining the development effectiveness. Accurate inversion of water injection-induced fracture parameters holds significant importance for enhancing reservoir development outcomes. This paper innovatively proposes a parameter inversion framework that integrates the Embedded Discrete Fracture Model (EDFM) with intelligent optimization algorithms. EDFM efficiently characterizes complex unstructured fracture systems while maintaining mass conservation between the matrix and fractures; intelligent optimization algorithms automatically invert parameters such as fracture half-length, orientation, and conductivity. First, a three-dimensional geological model of the TOR is constructed, utilizing EDFM to handle the impact of fractures on the seepage field. Based on considerations of fracture geometry, conductivity, and stress sensitivity, a coupled fluid dynamics model for fractures and matrix is developed. Subsequently, an objective function is built based on water injection production dynamic data, and the Projection-Iterative-Methods-based Optimizer (PIMO) algorithm is employed to achieve efficient inversion of fracture parameters. Taking a TOR in the Ordos Basin as an example for verification, through synthetic model validation, this method significantly improves the accuracy and efficiency of history matching, with inversion results reliably guiding numerical simulation predictions. The results demonstrate that this method can effectively enhance the precision of fracture parameter identification, offering clear advantages in inversion speed and accuracy over traditional trial-and-error approaches. This study provides new insights for modeling induced fractures in TORs and optimizing water injection development strategies. Full article

Fluid-driven fracture processes are central to the development of subsurface energy systems such as geothermal and hydrocarbon reservoirs. Although phase-field formulations have become a widely used tool for describing fracture initiation and growth, the diffuse representation of cracks makes it difficult to resolve flow behavior accurately inside discrete fracture networks (DFNs) and to represent hydro-mechanical coupling in a sharp-interface sense. This study develops a hybrid-dimensional iterative framework for lubrication-flow simulation in deformable fractured geomaterials. By leveraging phase-field point clouds together with non-conforming discretization schemes for both the solid matrix and fracture domains, the proposed framework enables the dynamic reconstruction of evolving fracture networks. The theoretical formulation and numerical implementation of the coupling strategy are presented in detail. Hydraulic benchmark examples verify the performance of the fluid flow solver under various physical conditions. The classical Sneddon problem and Khristianovic–Geertsma–de Klerk (KGD) model are employed to validate the solid deformation solver, confirming accurate predictions of crack opening displacement and mesh independence in fracture width calculation. Additional simulations with complex pre-existing fracture patterns further demonstrate the applicability of the framework to coupled hydro-mechanical analysis in fractured media. Full article

Hydraulic transients in pressurized pipe systems are significantly influenced by the presence of entrapped air, which alters wave propagation through increased compressibility and energy dissipation. Traditional discrete cavity models, such as the Discrete Gas Cavity Model (DGCM), often assume a constant wave celerity, which limits their accuracy under high gas content conditions. This study evaluated different approaches for representing the effects of gas cavities and unsteady friction in closed pipe transients. The work introduces the Adjustable-celerity Gas Cavity Model (AGCM), a formulation that explicitly couples local air volume and pressure to dynamically adjusted celerity values. Two variants are considered, a non-iterative (AGCM.v1) and an iterative approach (AGCM.v2), the latter ensuring consistency between pressure head and celerity at each time step. The models were evaluated through numerical simulations using both experimental datasets and a hypothetical test case with increasing air fractions. Results show that the AGCM was able to represent celerity magnitudes in unsteady flows with large fractions of air. Also, while constant-celerity models perform well under low-air conditions, variable-celerity formulations offer superior consistency in predicting wave amplitudes and celerity dynamics as gas content increases. These findings underscore the importance of dynamic celerity coupling in transient flow modeling and validate the AGCM as a useful approach for transient modeling in conditions with higher air phase fractions. Full article

Finite Rate of Innovation (FRI) sampling has been widely used to sampling parametric signals at sub-Nyquist sampling rates. Nevertheless, real-world systems generally handle real-valued signals, posing challenges for acquiring complex domain Fourier coefficients directly. To overcome this limitation, we propose a Chebyshev polynomial-based FRI sampling framework that enables processing entirely in the real domain. Projecting the FRI signal onto the Chebyshev basis and employing a improved annihilating filter reformulates the parameter estimation problem into a classical spectral estimation task. Furthermore, the integration of the discrete Hilbert transform allows for a further reduction in both sampling channels and total sample count. Numerical simulations validate the effectiveness of the proposed approach and the generalizability of FRI theory across different signal bases. 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

We develop a fast numerical method for solving nonlinear diffusion equations with memory phenomena, a class of problems arising within viscoelastic materials, anomalous transport, and hereditary systems. The primary computational problem is the nonlocal temporal dependence captured by Volterra-type memory operators, which makes direct evaluation scale quadratically with the number of time steps ($O\left(N_t^2\right)$), rendering prolonged simulations prohibitively expensive. To address this bottleneck, we develop a novel synthesis that combines a high-order spectral method for spatial discretization with a fast memory algorithm based on a sum-of-exponentials approximation. The spectral method obtains exponential spatial convergence for smooth solutions. At the same time, the fast memory algorithm reduces memory usage and computational complexity to $O\left(N_t\right)$, yielding computational speedups exceeding 414x for prolonged simulations. We rigorously prove that the proposed scheme preserves the discrete energy dissipation law of the continuous system under mild assumptions on the memory kernel, thereby ensuring unconditional stability. Error analysis verifies spectral accuracy in space and first-order temporal convergence. Extensive numerical experiments using exponentially decaying and weakly singular kernels validate the theoretical results and illustrate the method’s effectiveness for modeling viscoelastic transport phenomena and irregular diffusion in complex systems. Full article

This study proposes an innovative spacer design for use in spiral-wound membrane filtration systems as a high-performance alternative to conventional woven spacers. By eliminating interwoven filaments, this structure fundamentally reshapes flow patterns while maintaining mechanical support. A novel aspect of this methodology is the inaugural application of coupled computational fluid dynamics (CFD) and the discrete phase model (DPM) for modeling microbial particle transport and deposition dynamics, which has been a critical gap in prior studies that focused solely on hydrodynamic analysis without addressing biocolloid dynamics. Numerical simulations demonstrated that the novel design reduces stagnant zones by a significant amount compared to standard woven spacers and achieves a greater velocity uniformity. For all eight configurations of the novel design, the DPM-derived microbial distribution maps revealed a reduction of circa 65% in particle colonization density on the spacer surface, and this reaches a 77% reduction for the optimal design. These measurements directly linking structural geometry to antifouling efficacy provide mechanistic insight unattainable through conventional velocity field analysis alone. Experimental validation using optical coherence tomography (OCT) revealed a 40% reduction in TOC deposition, while confocal laser scanning microscopy (CLSM) quantified a 54% decrease in biofilm viability through adenosine triphosphate (ATP) measurements. The incorporation of the optimal spacer in the plate-and-frame test module demonstrated that the lower degree of fouling caused both a 23% increase in permeation flux together with 76% lower energy consumption compared to the commercial design. Full article

Brushless motors are characterized by extreme power density, thermal management and steady dynamic performance which are commonly utilized in aerospace, high-end robotics and precision medical equipment. The nonlinear solutions and the corresponding stabilities in the brushless DC motor system reveal the inherent current-speed properties. In this study, the semi-analytical solutions and the corresponding stabilities in the brushless DC motor system are obtained via a discretized mapping method. The governing equations are discretized into nonlinear polynomials through an implicit mid-point scheme. The semi-analytical solution trees from period-1 to period-2 and period-1 to period-4 are obtained. Some independent periodic solutions are observed. The stability and bifurcations are obtained quantitatively where the period-doubling bifurcations trigger the bifurcation trees and saddle-node bifurcations bound the independent solutions. Interestingly, unstable bifurcation trees are also observed. For verification, numerical simulation is conducted. The stable and unstable properties of current–velocity coupling dynamics are discussed finally. Full article

This article addresses the challenges of regulation and trajectory tracking in a nonlinear, multivariable drone quadrotor system using a discrete-time Generalized Proportional Integral (GPI) controller, which is the discrete-time version of its continuous-time counterpart. The discrete-time formulation offers several advantages, including simplified trajectory planning by eliminating time derivatives, reduced computational demands, and lower complexity in nominal feed-forward input functions. The proposed GPI controller ensures asymptotic exponential stability for both attitude and position, enabling effective trajectory tracking. Its effectiveness has been validated through numerical simulations, which demonstrate excellent stabilization and tracking performance even in the presence of atmospheric disturbances and measurement noise. Full article

This paper presents a new perspective on the energy decay of a nonlocal truncated Timoshenko–Ehrenfest system. By using the non local elasticity theory, this model is a generalization of the standard truncated Timoshenko system. The well-posedness of the proposed model is established via the Faedo-Galerkin method. Energy stability and decay properties are then derived using suitable multiplier techniques. Finally, a numerical scheme is constructed, and the exponential decay of the discrete energy is given special attention. Numerical simulations are provided to illustrate and validate the theoretical results. Full article