Search Results (347)

This paper develops a two-dimensional fully Lagrangian meshless fluid–structure interaction solver by integrating the Moving Particle Semi-implicit (MPS) method with continuum mechanics to investigate the nonlinear interaction between waves and floating bodies. The stability and accuracy of the proposed model are validated through several benchmark cases. Furthermore, the solver is employed to analyze the dynamic response of a flat plate floating body in waves. The numerically generated waves exhibit a minimum error of approximately −0.5% and a period consistent with theoretical values, maintaining a smooth and continuous free surface. Due to the inherent limitations of the two-dimensional wave-floating body simulation, the Root Mean Square Error (RMSE) of the interaction results ranges from 5.4% to 15.2%. These findings indicate that the proposed method provides a valuable reference for the design and analysis of floating structures in ocean engineering. Full article

This paper presents a computational study of wave–bathymetry and wave–structure interaction problems using advanced numerical techniques based on high-fidelity, two-phase Navier–Stokes (TpNS) flow and reduced-order, fully nonlinear potential flow models. For high-fidelity simulations, the TpNS equations are discretized using the finite-element method, with free-surface evolution captured through a hybrid level-set (LS) and volume-of-fluid (VOF) formulation. A monolithic, phase-conservative LS equation is introduced to mitigate mass loss and interface smearing, combined with a semi-implicit projection scheme. Hydrodynamic forces are resolved using a high-order, phase-resolving cut finite-element method (CutFEM), which enables the representation of complex solid geometries within a fixed background mesh. An equivalent polynomial of Heaviside and Dirac distributions ensures accurate evaluation of surface and volume integrals. Hence, no explicit generation of cut cell meshes, adaptive quadrature, or local refinement is required. For reduced-order modeling, a fast regularized boundary integral method (RBIM) is employed to solve the fully nonlinear potential flow. Singular and near-singular integrals are treated using a subtract-and-addition technique based on auxiliary functions derived from Stokes’ theorem, allowing direct application of high-order quadrature without conventional boundary element discretization. An arbitrary Lagrangian–Eulerian (ALE) formulation is adopted to enforce free-surface boundary conditions while avoiding excessive mesh distortion. The proposed approaches are applied to investigate highly nonlinear wave transformation over complex bathymetry and wave-induced dynamics of floating structures, including eddy-making damping effects. Numerical results are validated against experimental measurements. These two modeling approaches represent complementary levels of physical fidelity and computational efficiency, and their systematic comparison clarifies the trade-offs between computational accuracy, efficiency, and cost for practical marine problems. Full article

This paper presents a practical optimization framework for improving trajectory feasibility in constrained nonlinear optimal control problems for agile unmanned aerial vehicles (UAVs). The proposed method addresses trajectory optimization problems with non-convex geometric constraints, where gradient-based solvers often fail to converge to feasible solutions. The framework combines Model Predictive Path Integral (MPPI) control and the Augmented Lagrangian iterative Linear Quadratic Regulator (AL-iLQR). MPPI is employed as a fast sampling-based guidance mechanism to explore feasible regions of the trajectory space, while AL-iLQR is used to efficiently refine locally optimal solutions with high numerical accuracy. By decoupling feasibility exploration from local optimal refinement, the proposed method mitigates the sensitivity of gradient-based trajectory optimization to initialization in highly constrained environments. Numerical simulations involving both simplified two-dimensional dynamics and full quadrotor models demonstrate that the proposed approach significantly improves the probability of converging to feasible and dynamically consistent trajectories compared with AL-iLQR alone. The proposed method does not aim to provide theoretical guarantees of global optimality; instead, it offers a practical and computationally efficient strategy for enhancing feasibility and robustness in real-time UAV trajectory optimization. Full article

Ammonia (NH₃) has emerged as a promising carbon-free fuel for next-generation green energy systems due to its high hydrogen density, ease of storage and transport, and compatibility with existing infrastructure. These attributes contrast with hydrogen, which presents major challenges related to storage, safety, and high-pressure handling. Thus, ammonia offers a more practical alternative for combustion-based applications. However, its low reactivity and complex vaporization behavior, particularly under flash-boiling conditions, pose challenges for accurate modeling. This study presents a comprehensive numerical investigation of liquid-ammonia spray behavior under a range of ambient pressures, encompassing both flash-boiling and non-flashing conditions. Simulations were conducted using the Lagrangian particle tracking method, coupled with various turbulence models (the renormalization group (RNG) family, k-ω family, $\varsigma -f$, V2F models) to evaluate their predictive performance. Validation against experimental data for liquid and vapor penetration demonstrated that the V2F model achieved the best overall balance between accuracy and computational efficiency. Under strong flash-boiling conditions (2 bar), rapid droplet breakup and notable cooling were observed, with droplet temperatures decreasing to approximately 235 K within a few millimeters of the nozzle. In contrast, the cooling effect was more moderate under non-flashing conditions at higher ambient pressures (10–15 bar). Although the current findings were based on numerical simulations, experimental studies are ongoing to validate and refine the modeling framework further. This work provided valuable insights into the coupled effects of turbulence, phase change, and thermal transport in superheated ammonia sprays. Future research will build upon these results by extending the model to NH₃/H₂ dual-fuel systems, refining turbulence-phase interaction models, and exploring the potential application of ammonia-based flash-boiling cooling systems for electric vehicle (EV) battery thermal management. Full article

This study addresses the problem of optimal resource allocation in nonlinear multi-module dynamic systems arising in complex computational and techno-economic processes, where numerical stability and strict enforcement of structural constraints are critical. The objective is to develop a computationally efficient optimal control algorithm capable of handling bilateral control constraints and external balance conditions without resorting to large-scale nonlinear programming or boundary-value shooting. The proposed method is based on a modified Lagrangian formulation, in which bilateral Karush–Kuhn–Tucker (KKT) conditions are analytically embedded into the optimality system. The resulting computational scheme consists of a coupled system of matrix and vector differential equations solved through a non-iterative backward–forward integration procedure. Numerical experiments conducted on a nonlinear model with Cobb–Douglas-type operators demonstrate the stable convergence of the trajectories toward a stationary regime, strict satisfaction of bilateral constraints, and consistent enforcement of balance relations throughout the planning horizon. Empirical scalability analysis indicates approximately cubic computational complexity with respect to the state dimension, while sensitivity tests confirm the numerical robustness across different integration tolerances and ODE solvers. These results demonstrate that the proposed structure-preserving framework provides a computationally stable and practically implementable approach to constrained optimal control in nonlinear multi-module systems. Full article

In order to investigate the soil displacement effects and penetration resistance mechanisms of large-diameter PHC pipe piles (1200 mm) in complex railway geology, a tripartite framework combining field tests, theoretical analysis, and numerical simulations was established based on the Xiong’an–BDA Express Line project. A coupled discrete–continuum analysis using the Coupled Eulerian–Lagrangian (CEL) method was conducted to model the large-deformation process of pile driving in soft clay and stratified layers. The results indicate that the installation process induces a “squeezing effect” that critically enhances pile–soil interfacial friction. The theoretical analysis incorporating the extended Lade–Duncan yield criterion significantly improved prediction accuracy, reducing the relative error of side friction from 22% (using the Mohr–Coulomb model) to 5%. Furthermore, the CEL simulation demonstrated high reliability in predicting deep-depth friction and pile tip resistance, effectively capturing the stress redistribution in complex strata. Therefore, the combined application of pre-drilling and large-diameter piles is recommended for deformation-sensitive infrastructure, and the proposed validated framework offers practical guidance for design optimization and parameter selection in similar geological conditions. Full article

We propose a coupled gas–particle two-phase model for particle transport in a compressible carrier gas with interphase momentum and energy exchange, and we incorporate a diffusion-based mechanism to represent gas–particle reactions. The governing equations are discretized in an Arbitrary Lagrangian–Eulerian (ALE) finite-volume framework using an HLLC-type two-dimensional Riemann solver (HLLC-2D). The solver employs a nodal-conservation construction that enforces consistency between numerical fluxes and nodal contact velocities, which helps reduce spurious oscillations near discontinuities on moving meshes. In addition, a particle-search-based Courant–Friedrichs–Lewy(CFL)-like time-step restriction is introduced to enhance robustness in coupled simulations. Numerical tests are presented to assess the method and to illustrate particle-induced modifications of wave dynamics, as well as reaction-driven variations in velocity and temperature fields. Full article

AlSi7Mg0.6 aluminum alloy is widely adopted in many industrial fields due to its favorable mechanical properties and lightweight merits. In the catenary system of high-speed railways, AlSi7Mg0.6 aluminum alloy is adopted as the substrate of the positioning hook and positioning support, which exhibit abnormal wear in some railways. Thus, it is very important to reveal the underlying wear characteristics and discover the key factors involved. In this study, the influences of displacement (0.5 mm, 1.5 mm, and 3.0 mm) and applied load (20 N, 50 N, 100 N, and 200 N) on the wear performance of AlSi7Mg0.6 aluminum alloy are investigated experimentally and numerically. Wear experiments are time-consuming and costly, but the finite element method (FEM) can effectively solve this problem. A UMESHMOTION user-defined subroutine integrated with an ABAQUS Arbitrary Lagrangian–Eulerian (ALE) adaptive mesh technique was developed to simulate the wear evolution process of the aluminum alloy under varying displacements and applied loads. The results indicate that the wear evolution process of AlSi7Mg0.6 aluminum alloy can be effectively simulated using the UMESHMOTION subroutine. The maximum wear depth (MWD) from the FEM deviates from the experimental results by no more than 10%, and the deviation is smaller than the experimental values. The largest deviation occurs when the displacement is 3.0 mm and the applied load is 100 N, where the discrepancy reaches 7.53%. The wear volume (WV) obtained from the FEM shows a deviation of less than 20% compared to experimental results. For the case with a displacement of 0.5 mm, the numerical results underestimate the wear volume, while for the case with displacements of 1.5 mm and 3.0 mm, the numerical results overestimate the wear volume. The largest deviation in this case occurs for the case with a displacement of 3.0 mm and applied loading of 100 N, with a discrepancy of 16.33%. Full article

Urban logistics systems are under mounting pressure to decarbonize while meeting growing freight demand. This study addresses this dual challenge by formulating a novel Time-Dependent Green Location-Routing Problem with Spatio-Temporal Variations (TDGLRP-STV). Our proposed framework integrates a dynamic carbon emission calculation method that explicitly links real-time traffic dynamics with the energy consumption patterns of electric logistics vehicles (ELVs), enabling precise, spatio-temporally resolved emission quantification. To tackle the NP-hard complexity arising from the coupling of emission objectives with location-routing decisions, we devise a Two-Stage Interactive Optimization Algorithm (TSI-LR-IACO). This algorithm synergizes Lagrangian Relaxation (LR) and an Improved Ant Colony Optimization (IACO) through a bidirectional feedback mechanism, effectively coordinating strategic facility location with tactical vehicle routing. Numerical experiments based on real-world metropolitan road network data from Beijing demonstrate the efficacy of our approach. The TSI-LR-IACO achieves a 5% reduction in total carbon emissions with a merely 0.01% increase in total system cost, validating its ability to balance environmental and economic objectives. This research provides a scalable and scientifically robust decision-support framework for advancing low-carbon urban logistics. Full article

Numerical simulation has become a powerful and versatile toolkit for investigating gas–solid flow behavior in metallurgical fluidization processes. This review summarizes recent advances in the application of computational fluid dynamics (CFD)-based approaches, particularly the Eulerian–Eulerian and Eulerian–Lagrangian methods, within the field of metallurgical fluidization. It covers model development, particle and bubble dynamics, reactor flow field analysis, and structural optimization. The study demonstrates that numerical simulation plays a crucial role in elucidating fluidization mechanisms, optimizing process parameters, and guiding reactor design. For example, numerical simulation provides key quantitative insights, such as the enhancement of iron ore reduction rates by up to 40% with increased gas velocity and the optimization of reactor cone angles to 5–10° for improved stability, in the design of hydrogen-based iron oxide reduction reactors. However, this review identifies that current research is predominantly focused on iron ore reduction, while numerical studies on fluidized-bed smelting of non-ferrous metals, such as zinc, copper, and aluminum, remain relatively limited. Future efforts should aim to broaden the application of numerical simulation in non-ferrous metallurgy, develop efficient multi-scale coupled computational methods, and integrate artificial intelligence technologies to advance metallurgical fluidization toward greater efficiency, energy savings, and intelligent operation. Full article

This study employs numerical simulation methods to systematically analyze the multiphase flow and heat transfer characteristics in a circulating fluidized bed flue gas desulfurization (CFB-FGD) reactor handling ascharite ore roasting flue gas. Based on the simulation results, key structural optimization strategies are proposed. A three-dimensional mathematical model was developed based on the Fluent 19.1 platform, and the multiphase flow process was simulated using the Eulerian-Lagrangian method. The study examined the effects of venturi tube structure, atomized water nozzle installation height, and gas injection disruptor configuration on reactor performance. Optimization strategies for key structural components were systematically evaluated. The results show that the conventional inlet structure leads to significant non-uniformity in the velocity field. Targeted adjustments to the dimensions of venturi tubes at different positions markedly improve the velocity distribution uniformity. Reducing the atomized water nozzle installation height from 1.50 m to 0.75 m increased the temperature distribution uniformity index in the middle part of the straight pipe section by 5.5%. Moreover, a gas injection disruptor was installed in the upper part of the straight pipe section of the CFB-FGD reactor. Increasing the gas injection velocity from 15 m/s to 30 m/s increased the average residence time of desulfurization sorbents by 17.0%. This increase effectively enhances gas–solid mixing within the CFB-FGD reactor. The optimization strategies described above significantly reduced the extent of flow dead zones and low-temperature regions in the CFB-FGD reactor and improved flow conditions. This study provides important theoretical and technical support for the optimization and industrial application of CFB-FGD technology for ascharite ore roasting flue gas. Full article

In this study, a novel and efficient solid-state additive manufacturing technique, friction rolling additive manufacturing (FRAM), was employed to fabricate an aluminum alloy ring component, significantly reducing process complexity and mitigating solidification defects typical of melt-based techniques. However, previous studies on FRAM have primarily focused on the microstructural characteristics and mechanical properties of flat components, with limited attention paid to ring-shaped components. Owing to the unique geometric constraints imposed during the forming process, ring components exhibit markedly different microstructural evolution and defect formation mechanisms compared with flat counterparts, and these mechanisms remain insufficiently and systematically understood. To address this knowledge gap, the coupled Eulerian–Lagrangian (CEL) method was introduced for the first time to numerically simulate the temperature distribution and residual stress evolution during the FRAM process of ring-shaped components. In addition, tracer particles were incorporated into the simulations to analyze the material flow behavior, thereby systematically elucidating the forming behavior and microstructural evolution characteristics under geometric constraint conditions. Moreover, scanning electron microscopy (SEM) and electron backscatter diffraction (EBSD) were employed to systematically characterize the microstructural evolution and defect morphology. The CEL numerical simulations exhibited good consistency with the experimental observations, demonstrating the reliability and accuracy of the simulation method. The results showed that the peak temperatures were primarily concentrated at the advancing side of the rotation tool, and the temperature on the outer diameter side of the ring was consistently higher than that on the inner diameter side. The lack of shoulder friction on the inner side led to an increased heat dissipation rate, thereby resulting in higher residual stress compared to other regions. The particle analysis revealed that, due to ring geometry, material flow varied across radial regions, resulting in distinct microstructures. Further EBSD analysis revealed that, after the rotating tool passed, the material first developed a preferential orientation with {111} planes parallel to the shear direction, and with more layers, dynamic recrystallization produced an equiaxed grain structure. This study provides a theoretical basis and process reference for the application of the FRAM technique in the manufacturing of large ring components. Full article

With the growing requirements for multi-particle process simulation, improving computational accuracy, efficiency, and scalability has become a critical challenge. This study generally focused on comprehensive analyses of existing numerical methods for simulating particle–substrate interactions in gas–thermal spraying (including gas–dynamic spraying processes), covering both single-particle and multi-particle models to develop practical recommendations for the optimization of modern coating spraying processes. First of all, this paper systematically analyzes the key limitations of current approaches, including their inability to handle high deformations effectively or high computational complexity and their insufficient accuracy in dynamic scenarios. A comparative evaluation of four numerical methods (Lagrangian, Arbitrary Lagrangian–Eulerian (ALE), Coupled Eulerian–Lagrangian (CEL), and Smoothed Particle Hydrodynamics (SPH)) revealed their strengths and weaknesses in modeling of real gas–thermal spraying processes. Furthermore, this study identifies the limitations of the widely used Johnson–Cook (JC) constitutive model under extreme conditions. The authors considered the Zerilli–Armstrong (ZA), Mechanical Threshold Stress (MTS), and Preston–Tonks–Wallace (PTW) models as more realistic alternatives to the Jonson–Cook model. Finally, comparative analyses of theoretical and realistic deformation and defect-generation processes in gas–thermal coatings emphasize the critical need for fundamental changes in the simulation strategy for modern gas–thermal spraying processes. Full article

Dam-break flows involve strong non-linearity and complex fluid–solid interactions, often causing severe flooding and structural damage. Particle-based CFD methods, such as the Moving Particle Semi-implicit (MPS) method, are effective in modeling such flows due to their mesh-free, Lagrangian nature. This study presents an improved MPS method with a novel friction model and enhanced fluid–solid interaction scheme to simulate dam-break-induced flows over fixed and mobile beds. The model is validated using experimental and analytical benchmarks, demonstrating improved accuracy and stability. Simulation results show that mobile beds significantly influence wave attenuation, energy dissipation, and sediment transport. In particular, step-down bed conditions promote sediment motion and modify wave behavior. These findings emphasize the importance of accounting for mobile seabed dynamics in numerical modeling of coastal and dam-break scenarios. The proposed MPS model offers a reliable and efficient tool for capturing key phenomena associated with fluid–solid interactions in naval and ocean engineering applications. Full article

Smoothed particle hydrodynamics (SPHs) is a Lagrangian meshless method with distinct strengths in managing unstable and complex interface behaviors. This study develops an integrated multiphase SPH framework by merging multiple algorithms and techniques to enhance stability and accuracy. The multiphase model is validated by several benchmark examples, including square droplet deformation, single bubble rising, and two bubbles rising. The selection of numerical parameters for multiphase simulations is also discussed. The validated model is then applied to simulate oil–water–gas bubbly flows. Interface behaviors, such as coalescence, fragmentation, deformation, etc., are reproduced, which helps to take into account multiphysics interactions in industrial processes. The rising processes of many oil droplets for oil–water separation are first simulated, showing the advantages and stability of the SPH model in dealing with complex interface behaviors. To fully explore the potential of the model, the model is further extended to the field of wax removal. The melting process of the wax layer due to heat conduction is simulated by coupling the thermodynamic model and the phase change model. Interesting behaviors such as wax layer cracking, droplet detachment, and thermally driven flow instabilities are captured, providing insights into wax deposition mitigation strategies. This study provides an effective numerical model for bubbly flows in petroleum engineering and lays a research foundation for extending the application of the SPH method in other engineering fields, such as multiphase reactor design and environmental fluid dynamics. Full article