Search Results (539)

Background: Humanitarian logistics decisions extend beyond immediate relief delivery to include preparedness, recovery, service continuity and the development of durable local capabilities. Simulation can support these decisions under uncertainty, yet the evidence remains fragmented across logistics domains, modelling approaches and phases of the relief–development continuum. This review synthesises how simulation has been used in humanitarian logistics and identifies where the evidence is concentrated and where important gaps remain. Methods: A systematic scoping review was conducted in accordance with PRISMA-ScR and PRISMA-S, using multi-disciplinary and specialist database searches supplemented by backward and forward citation searching. Included studies were coded by logistics decision problem, continuum phase, decision level, performance outcome, simulation approach and operational grounding. Results: The literature is concentrated in preparedness and response, particularly around coordination, network design, inventory, allocation, transport and capacity. System dynamics, agent-based modelling and discrete-event simulation are well established, whereas hybrid simulation and digital twin applications remain limited. Early recovery, reconstruction, development-oriented transition and practice-embedded modelling are comparatively underdeveloped. Conclusions: Simulation-supported humanitarian logistics is strongest for structured preparedness and response problems. Future research should connect decisions across phases and strengthen beneficiary-sensitive, operationally grounded modelling of recovery, localisation, service continuity and longer-term logistics capability. Full article

Powder Bed Fusion-Laser Beam/Polymer (PBF-LB/P) is a key additive manufacturing technology widely used in aerospace, but its process parameters are difficult to optimize for thermoplastic composites due to poor powder flowability and unstable melting regions. To address this challenge, this paper develops discrete element and finite element models to systematically determine the PBF process window for both powder spreading and sintering stages, with verified reliability. In the spreading stage, the powder layer performance is evaluated through surface profile, density, and uniformity. The effects of reinforcement phase, spreading speed, and layer thickness are analyzed, establishing reasonable spreading parameter windows. It is found that the optimal layer thickness for PEEK powder is determined to be 0.13 mm, while that for PEEK/CF composite powder is 0.12 mm. At the optimal layer thickness, the powder bed exhibits desirable properties, which minimize its adverse influence on the sintering process and serve as a prerequisite for subsequently establishing the sintering process window. For the sintering stage, sufficient sintering constraint criteria are established, and a systematic determination method is proposed. By analyzing microscopic sintering mechanisms and characterizing the effects of laser power, scanning speed, and hatching space on melt pool dimensions and temperature, a reasonable sintering process window can be efficiently determined. It is found that within the process window, the PEEK specimens achieved a maximum relative density of 99.31% and exhibited a tensile strength 13.1% higher than that of specimens processed outside the window, demonstrating a clear superiority. Full article

This paper presents a novel optimal control-based beamforming framework for phased antenna arrays, targeting advanced wireless communication and radar applications, including 5G systems. Unlike conventional beamforming techniques, such as Fourier-based methods and adaptive algorithms (e.g., LMS and RLS), the proposed approach formulates the beam synthesis problem as a discrete-time optimal control problem. The antenna array is modeled using a state-space representation, and a quadratic cost function is introduced to jointly minimize the deviation from a desired radiation pattern and the excitation power. The optimal excitation weights are derived using the Linear Quadratic Regulator (LQR) framework by solving the discrete-time algebraic Riccati equation. This formulation enables an effective trade-off between sidelobe suppression, main lobe accuracy, and power efficiency. Simulation results demonstrate that the proposed method achieves a well-focused main beam, significantly reduced sidelobe levels, and improved directivity compared to conventional approaches. Furthermore, the framework offers robustness and computational efficiency, making it a promising candidate for future FPGA and embedded implementations. Overall, the proposed optimal control-based beamforming approach provides a flexible, robust, and computationally efficient solution for next-generation antenna systems in 5G, beyond-5G (B5G), and radar applications. Full article

For condensed-phase detonation, we develop a block-structured adaptive multiresolution method for the reactive compressible Euler equations coupled with the ignition-and-growth model and the JWL (Jones–Wilkins–Lee) equation of state. A second-order Runge–Kutta local time-stepping strategy is employed, and the governing equations are advanced with a two-step operator-splitting procedure. First, the homogeneous conservation laws are discretized by fifth-order WENO (Weighted Essentially Non-Oscillatory) finite differences. Then, the chemical source term is integrated by solving an ordinary differential equation. Because condensed-phase detonations exhibit extremely small characteristic scales in the chemical reaction zone, the proposed method is designed to capture the detonation front, shock waves, and the reaction zone accurately and efficiently. It uses adaptive multiresolution with a reaction zone preservation treatment based on the reaction progress variable to maintain fine resolution in chemically active regions, thereby keeping the lead shock and the reaction zone at the finest grid level. This algorithm significantly improves computational efficiency without compromising key physical features. One-, two-, and three-dimensional benchmark cases are used for validation. The results show that the proposed method accurately captures detonation wave structures and reaction zone characteristics. In particular, compared with uniformly refined computations, it maintains high accuracy while substantially reducing the active-cell count and runtime. Full article

Precise segmentation of high-magnification titanium alloy micrographs under few-shot scenarios remains a non-trivial task, primarily owing to the intricate morphology, heterogeneous discrete distribution, and weak phase boundaries of the primary α phase. To address these issues, this paper presents MaterialAlphaSAM, a lightweight domain-adaptive segmentation framework built upon the Segment Anything Model (SAM). Leveraging SAM’s powerful global context modeling capability, the proposed method incorporates two key modules: a Geometry-Constrained Prompt Prior (GCPP) module and a Domain-Adaptation Adapter (DAA) module. The GCPP module explicitly embeds geometric and morphological priors to generate semantically guided prompts, effectively alleviating prompt redundancy and noise sensitivity. The DAA module performs cross-domain alignment of the encoder features, reducing the domain discrepancy between natural images and metallic microstructures. Extensive experiments demonstrate that both modules consistently boost segmentation performance. On the titanium alloy dataset, MaterialAlphaSAM achieves 89.53% IoU and a 94.40% F1-score, outperforming FCN, UNet, DeepLabV3, PSPNet and the vanilla SAM. It exhibits superior robustness to weak boundaries, fine-scale α phases, and complex background interference. Full article

Two crucial yet opposing design criteria govern the performance of packed bed latent thermal energy storage systems (PBLTESS): energy storage capacity and thermal power. While the former depends on the packing density of the phase change material (PCM) capsules forming the packed bed, the latter is influenced by the surface-area-to-volume ratio (SVR) of these capsules. This study introduces novel superellipsoidal geometries for PCM capsules to address both these factors and quantifies the impact of design parameters on both mentioned performance criteria. First, by using discrete element method (DEM) simulations, we performed virtual bed filling experiments and generated packed beds from 116 superellipsoidal designs with similar volume. These simulations revealed a maximum packing density of 65.2%—significantly higher than conventional spherical capsule designs. Validation through bed filling experiments using 3D-printed superellipsoids confirmed the results of the DEM simulations, with an average deviation of less than 5%. Additionally, the SVR of each superellipsoidal design was determined through CAD analyses. Subsequently, six superellipsoidal designs as well as a spherical design were selected for further investigation using a 1D PBLTESS model to simulate charging and discharging. With up to 85% higher storage capacity (due to increased packing density) and up to 50% higher thermal power (resulting from enhanced heat transfer), the superellipsoidal geometries clearly outperformed the spherical design. Full article

A massive number of early-constructed small-to-medium-span bridges are collectively entering an “aging” phase in China. Meanwhile, vast amounts of unstructured bottom-level inspection texts remain underutilized. To address them, this paper proposes a data governance method. Large Language Models were leveraged to process unstructured defect data from 18,238 real-world bridges nationwide. The data were structurally cleaned and mapped into discrete features, revealing multidimensional vulnerabilities. On this basis, the Stable Contrastive Pattern Risk (SCPR) intelligent decision-making model was developed. The results demonstrate that, following robust filtration, 6 nationwide common risk rules were extracted from 2064 initial candidate combinations. These rules converge into three core risk patterns: the heavy-duty aging pattern, the substructure-dominated pattern, and the over-water small-span low-seismic-design pattern. Guided by these robust rules and specific damage enrichment characteristics, risk stratification and differentiated management strategies were further formulated for Class III bridges. This research facilitates a paradigm shift in bridge maintenance. It moves from reactive, post-event symptom characterization toward data-driven, proactive early warnings. This shift provides a substantive scientific foundation for optimizing resource allocation and enabling precise investment decisions at the road network level. Full article

The growing demand for high-speed marine transportation requires continuous improvement in ship design to achieve higher hydrodynamic efficiency. From an engineering design perspective, hull form modification is a key approach to optimizing the performance of planing vessels, particularly through the implementation of stepped hull configurations. This study aims to investigate the effects of step geometry and step position on the resistance and trim characteristics of a planing hull based on Taunton et al.’s Model C, with the objective of improving vessel efficiency. The design methodology integrates hull geometry modification, parametric variation in step position and step height, and numerical performance assessment. In this research, the governing equations are solved using the Reynolds-Averaged Navier–Stokes (RANS) framework with the Finite Volume Method (FVM) as the discretization technique. The turbulence model used is k-ω SST, while the interaction between water and air phases is represented using the Volume of Fluid (VOF) method. From a design performance perspective, the results demonstrate that stepped hull geometry significantly influences resistance and trim characteristics. The optimal design configurations achieved a resistance reduction of up to 17.93% and a trim of 1.53° was achieved with a stepped position of 430 mm from the transom and a stepped height of 25 mm (Model A3) at Fr 2.28. Meanwhile, a resistance reduction of 15.49% and a trim of 1.46° were observed for a stepped position of 860 mm from the transom and a stepped height of 25 mm (Model B3) at Fr 2.72. These findings highlight the importance of step geometry and placement as key design variables in improving planing hull performance. This study demonstrates that CFD-based evaluation can effectively support engineering design decisions for stepped hull optimization, providing a systematic approach for improving hydrodynamic efficiency in high-speed vessel design. Full article

A novel wide-neck classifier (WNC) was designed to address the problem that thickeners cannot achieve classification prior to flocculation in a single unit. Using the computational fluid dynamics-discrete phase method and PIV experimental method, the reliability of the model was validated. We studied the motion characteristics of different particles within the novelty-designed WNC. The primary forces acting on coal slime particles in the composite force field were gravity, drag force, pressure gradient force, and virtual mass force. Drag force dominated the classification and sedimentation processes. In contrast, gravity, pressure gradient, and virtual mass forces promoted downward sedimentation but hindered upward overflow. The classification of slime particles in WNC was divided into initial classification after tangential feeding and centrifugal classification in a cone. Both simulation and experimental results demonstrate that, under consistent feed conditions, mineral density significantly affected the distribution of particles at the classification underflow and classification overflow. Among the three minerals, kaolinite has the highest classification effect, followed by quartz, while coal has the lowest classification effect. Full article

Blast furnace (BF) ironmaking is a complex multiphase process involving gas–solid flow, heat transfer, chemical reactions, burden movement, and phase transformation under high-temperature conditions. Since many internal states of the blast furnace cannot be directly observed during operation, numerical simulation and mathematical modeling have become important tools for understanding furnace behavior and optimizing operational parameters. This paper reviews recent advances in blast furnace numerical simulation and internal state reconstruction methods. Existing approaches, including packed-bed flow models, cohesive zone reconstruction methods, burden distribution models, and temperature field prediction methods, are summarized and discussed. In addition, the evolution of blast furnace mathematical models from early one-dimensional steady-state formulations to modern three-dimensional multifluid and hybrid simulation approaches is reviewed. Recent developments in computational fluid dynamics (CFD), the discrete element method (DEM), digital twin, and data-driven modeling are also discussed. Compared with traditional simplified models, modern multidimensional and hybrid approaches show improved capability in describing asymmetric furnace inner states, multiphase transport behavior, and operational parameter effects under industrial conditions. However, challenges still remain in achieving computational efficiency, parameter calibration, multiphase coupling, and real-time industrial application. Future studies are expected to focus on the integration of mechanism-based simulation and intelligent data-driven methods to improve prediction accuracy, operational adaptability, and intelligent control capability in blast furnace ironmaking. Full article

Water damage under the coupled effects of traffic load and pore water pressure (PWP) is a primary cause of early failure in asphalt pavements. Although dense-graded pavements generally have low void ratios, excess PWP poses a severe threat to durability under extreme conditions. These conditions include heavy rainfall, water accumulation in wheel tracks, and upward capillary water rise. In this study, a mesoscopic model considering fluid–solid coupling effects was established using the Particle Flow Code in the 2 Dimensions (PFC2D) platform, which is based on the discrete element method (DEM). A parallel-bonded stress corrosion model was introduced to describe damage evolution. The results show that the maximum positive PWP increased monotonically with load, reaching a distinct peak value at a critical loading frequency under specific load amplitudes. At this critical frequency, the fatigue life was significantly shortened compared to lower-frequency conditions. The PWP response exhibited a clear phase lag relative to the applied load, with the lag angle increasing alongside frequency. Furthermore, the absolute value of the minimum PWP continued to increase with fatigue damage accumulation. This indicates that regions with a vacuum suction effect were continuously expanding, which is a key reason for asphalt film stripping from the aggregate surface. These findings provide a theoretical basis for understanding mesoscopic water damage mechanisms in asphalt pavements and offer a reference for durability design. Full article

High-intensity magnetic fields in tokamak structures for nuclear fusion generate significant ferromagnetic forces that must be properly estimated for a reliable design of the mechanical structures. Accurate numerical modeling of these electromagnetic problems is likely to entail high computational costs due to the complexity of the geometries and the need to account for nonlinear material behavior. However, electromagnetic forces are not the only loads acting on tokamaks, as other phenomena, such as seismic forces, must also be considered in their design. Therefore, it is highly beneficial to develop coarse estimates of the electromagnetic loads in order to compare their magnitude with that of other loads. Such estimates are useful not only in the early stages of design, but also in the final design phase, particularly if these forces prove to be negligible. To this end, this paper proposes a semi-analytical method to quickly estimate the forces acting on ferromagnetic components located outside the vessel. The method is based on the calculation of the magnetization by means of a well-established integral method after a coarse discretization of the volume occupied by the ferromagnetic materials. The proposed method is implemented in computational routines made available within this paper, enabling the estimation of these forces even for users who lack the expertise required to operate commercial simulation tools. The method is applied to case studies related to some export components of the ITER tokamak, and the validation is carried out with reference to the accurate numerical solutions provided by both commercial and in-house simulation tools. Full article

Nowadays, numerical simulation methods are advanced and widely used in industry, enabling the modeling of complex systems from printed circuit boards (PCBs) to full power converters. Among many isolated topologies, the phase-shift full-bridge (PSFB) topology is a well-established solution for isolated DC–DC conversion in electric vehicles. Therefore, this paper proposes a broadband electromagnetic compatibility (EMC) modeling methodology for a custom-designed 1 kW gallium nitride (GaN)-based PSFB converter intended for an electric vehicle (EV) DC powertrain. Moreover, the approach combines full-wave electromagnetic simulation with circuit-level simulation, including parasitic effects from PCB layout, power harnesses, and discrete components. Thus, the virtual prototype is assessed within a complete virtual test bench compliant with the standard Comité International Spécial des Perturbations Radioélectriques (CISPR) 25 over the 150 kHz–108 MHz range to capture common-mode (CM) and differential-mode (DM) conducted electromagnetic interference (EMI). Results show that the converter achieves efficiencies of 97.26% in standalone mode and 97.03% when integrated into the full DC powertrain. However, the conducted EMI assessment reveals that both CM and DM emissions exceed CISPR 25 Class 2 limits across the entire spectrum, with excess levels reaching up to 72 dBµV. Therefore, power harnesses significantly increase EMI levels at low frequencies due to the distributed inductance and stray capacitance. Finally, this study demonstrates the value of virtual prototyping for simulation-based EMI prediction in early-stage power converter design. Full article

Exhaust piping in diesel engines is subject to severe thermal stress arising from high-temperature, high-pressure gas flows, and spray cooling with atomizing nozzles has become a widely adopted method to safeguard structural reliability. However, at present, the understanding of the spray fragmentation mechanism of two-phase flow under low inlet pressure is still not comprehensive. This study establishes a three-dimensional model of a gas–liquid impinging-jet nozzle and applies a coupled Volume-of-Fluid to Discrete-Phase-Model (VOF–DPM) approach to resolve the liquid breakup process in detail. High-speed imaging experiments were carried out to validate the numerical results. Orthogonal tests were conducted at five pressure levels for both gas and water—0.28, 0.24, 0.20, 0.16, and 0.12 MPa—producing 25 data pairs of spray cone angle and Sauter Mean Diameter (SMD). Within the 0–0.3 MPa air inlet pressure range explored here, raising the pressure consistently reduced the SMD and widened the cone angle, although both trends weakened as the pressure increased. Water inlet pressure exhibited a nonlinear influence, with local extrema appearing in the higher-pressure region. The overall SMD reached a minimum of 34.12 μm and a maximum of 149.04 μm. Using these 25 data points, a genetic algorithm was employed to optimize the pressure ratio under the constraint of total hydraulic power, yielding optimization strategies for different power budgets. An additional outcome of the simulation was the identification of a structural weakness: by reshaping the original flat impingement surface into a full conical surface, atomization quality improved by 29.36% under identical boundary conditions. These findings clarify the atomization mechanism of gas–liquid impinging jets under low inlet pressure and offer practical guidance for nozzle optimization. Full article

The microstructure of metal matrix composites is inherently governed by fabrication routes and processing parameters, yet technological and physical constraints often prevent the realization of intended structural designs. In particle-reinforced composites produced via casting, interactions between the solidification front and inclusions frequently lead to agglomeration, segregation, and hence, a non-uniform distribution of the inclusions concentration. To mitigate these effects, post-processing techniques such as Friction Stir Processing offering particular promise for cast materials by refining microstructures and enhancing phase homogeneity. This study addresses these challenges by application of Fourier transform analysis to characterize stochastic inclusion distributions. Building on the Windows Washing method, we extend its application to heterogeneous media with varying inclusion concentrations. Through computer simulations and experimental analysis of real composites, we demonstrate that discrete Fourier transform can reveal hidden stochastic periodicity. The proposed framework provides a pathway toward improved predictive models and optimization strategies for metal matrix composites processing and performance. Full article