Search Results (49,388)

In response to the increasingly severe heat dissipation challenges in electronic devices, three types of manifold microchannel heat sinks (MMC) incorporating rhombic pin-fins were proposed. Under the constraint that the maximum temperature of the heat source surface remains below 343.15 K, numerical comparisons with a conventional straight rectangular microchannel heat sinks (MCHS) reveal that the design featuring a trapezoidal manifold exhibits superior comprehensive thermal performance and improved temperature uniformity. Furthermore, the influence of rhombic pin-fin geometry on thermal performance was investigated for both MCHS with and without the trapezoidal manifold under varying mass flow rates. Results show that for the MCHS without a manifold, performance evaluation criterion (PEC) reaches its maximum when the inlet angle of the rhombic pin-fin is 120°, the side length is 0.17 mm, and the pin-fin height is 0.18 mm. In contrast, for the MCHS with the trapezoidal manifold, optimal PEC is achieved at an inlet angle of 110°, a side length of 0.18 mm, and a pin-fin height of 2.2 mm. Additionally, a multi-objective optimization was conducted using the Latin hypercube sampling method. Three objective functions—maximum temperature (T_max), thermal performance (PEC), and temperature uniformity (σ_T)—were considered. A total of 150 sample points were used to train Kriging surrogate models for the rhombic pin-fin MCHS with trapezoidal manifold. The optimization results demonstrate a 34.05% enhancement in thermal performance and an 18.6% improvement in temperature uniformity. Full article

Tsunami-induced scour around coastal embankments and nearshore structures is a primary cause of structural instability and failure. However, the hydrodynamic mechanisms by which coastal vegetation mitigates this scour remain insufficiently understood. This study employs three-dimensional numerical simulations to investigate the influence of rigid and flexible vegetation on overflow-induced scour downstream of embankments and local scour around structures under tsunami-like inundation. The simulations were conducted using Ansys Fluent 2021R2, utilizing the Volume of Fluid (VOF) method to capture the free surface and the RNG $k-\epsilon$ turbulence model within the Reynolds-averaged Navier–Stokes (RANS) framework. Computational geometries were reconstructed from laboratory experiments, and the model’s reliability was validated against measured water surface profiles. The results demonstrated that vegetation significantly alters flow dynamics, velocity distributions, vortex structures, and both the magnitude and patterns of bed shear stress within scour holes. Specifically, in overflow-induced scour, vegetation suppresses scour intensity by inducing backwater effects, enhancing momentum diffusion, attenuating flow impingement on the bed, and reducing peak bed shear stress. Conversely, for local scour around structures, vegetation increases upstream water depth while intensifying downstream wake vortices, leading to scour hole elongation—particularly under dense and tall vegetation. These findings offer novel insights into the hydrodynamics of vegetation-induced scour mitigation and provide guidelines for optimizing vegetation configurations to enhance the tsunami resilience of coastal infrastructure. Full article

High-resolution marine gravity fields are critical for interpreting seafloor structure, investigating marine geodynamics, and enabling gravity-aided navigation. However, sparse shipborne observations, heterogeneous multi-source geodetic datasets, and the inability of conventional methods to handle nonlinear inversion limit accurate gravity recovery. To overcome these limitations, we propose a spectral physics-informed constraint deep-learning framework based on a multi-channel Swin Transformer to reconstruct high-resolution marine gravity anomaly fields. The model ingests multi-source geodetic inputs organized as 64 × 64 grid patches centered near each computation point and fuses them to predict the target gravity anomaly. We adopt a remove–compute–restore (RCR) strategy that isolates residual gravity signals, which improves numerical stability and accelerates training. Inputs include satellite-altimetry-derived vertical gravity gradients, vertical deflections, mean sea surface height, and topography; the model is trained on over 430,000 shipborne gravity samples from the South China Sea (0–30° N, 105–125° E). To enforce physical consistency, we embed a spectral-domain physics constraint derived from potential-field theory into the loss function; this constraint helps recover short-wavelength gravity signals. We also introduce an adaptive multi-domain multi-scale feature fusion module (AMAMFF) to improve the integration of heterogeneous inputs, and we demonstrate its benefits in experiments across complex terrain. Validation against independent shipborne gravity checkpoints yields an RMS error of 3.09 mGal, indicating a substantial performance advantage over existing deep-learning approaches and conventional gravity-field models. Full article

The study addresses trajectory tracking control for underactuated vessels with uncertain backlash-type hysteresis. First, an improved practical L1-based guidance strategy is developed by embedding the L1 mechanism into the virtual ship framework to eliminate steering overshoot and yaw angle error accumulation, which can facilitate the smooth turning of ships along waypoint-based paths with large curvature. Next, to mitigate control performance degradation induced by backlash-like hysteresis nonlinearity, an improved quadratic function is utilized to boost the closed-loop system’s convergence capability. Moreover, system model uncertainty-induced perturbations are compensated using the resilient neural damping method, which can simplify the structure and reduce the computation burden of the proposed controller. Utilizing Lyapunov-based approaches and the special Young’s inequality, uniformly ultimately bounded stability over a semi-global domain is established. Finally, numerical simulations are executed to validate the efficacy of the developed control architecture. Full article

Resonant Wave Energy Converter 1 (REWEC1) is a submerged caisson breakwater integrating a device designed to absorb incoming wave energy. Although the wave energy-extraction performance of this system and its hydraulic characteristics have been extensively investigated, its potential role in reducing coastal inundation, as an alternative to traditional rubble-mound breakwaters, has not yet been examined. In this context, the present study analyzes the mitigation effects on coastal flooding induced by the installation of REWEC1 barriers. The analysis focuses on the coast of Cetraro, located along the Tyrrhenian Sea in the province of Cosenza (Calabria, Southern Italy). The effectiveness of REWEC1 farms in reducing coastal flooding was assessed by considering fixed-air and no-air operation modes, as well as different spatial configurations. The input wave conditions were propagated in the nearshore using the SWAN model to simulate wave–structure interactions, while the XBeach model was employed to investigate coastal inundation processes based on the wave field behind the caissons, also accounting for Sea Level Rise (SLR). The results were evaluated in terms of maximum flooded areas and water penetration lengths along the emerged coast, as well as wave run-up and set-up along selected transects. To assess the robustness of the results, a sensitivity analysis was carried out by varying the transmission coefficients of the REWEC1 units within a plausible uncertainty range, and the corresponding variability in flooding indicators was quantified. The numerical results indicate a progressive reduction in these hydrodynamic response indicators as the spacing between adjacent REWEC1 devices decreases, and show that the relative mitigation performance of REWEC1 remains consistent when accounting for uncertainties in wave–structure interaction parameters. Further analyses were conducted to compare the effectiveness of REWEC1 farms with that of conventional rubble-mound breakwaters in reducing coastal flooding. Full article

Mathematical modeling of heat and mass transfer processes in porous media using fractional derivative equations is of great practical importance. Within the framework of such models, obtaining analytical solutions to the corresponding initial–boundary value problems is generally difficult. In this work, we numerically investigate quasilinear parabolic problems involving Caputo time-fractional derivatives. First, the well-posedness and existence of weak solutions are discussed. Then, we construct and implement a finite-difference scheme that is fourth-order accurate in space and second-order accurate in time. Convergence in the maximum norm is proven. Numerical experiments confirm the accuracy and efficiency of the proposed approach. Full article

In mountain areas, long linear transport infrastructures (roads, motorways, railways, etc.) are exposed to numerous natural hazards, especially hydrological and gravity-driven events such as slope instabilities, rockfalls, or torrential hazards. These phenomena can damage infrastructure, or even lead to the destruction of large sections, causing a risk for users and a deterioration of service. Infrastructure managers face several difficulties in handling these risks. One of them is identifying and representing them, due to the scale of the infrastructure, which is composed of numerous structures and exposed to multiple hazards. In this context, a model is proposed to represent all potential failure scenarios for such infrastructures. This model is based on system reliability analysis methods: functional analysis, failure mode and effect analysis (FMEA), and fault tree analysis (FTA). It is intended to be applied to a linear infrastructure, several kilometres long, exposed to various hazards. The proposed approach allows for the identification of all possible failure modes, including damage to structures and its functional consequences. Its applicability is being tested on a simple case study. Full article

The internal thermal insulation structure serves as a vital subsystem within the thermal insulation system of high-temperature devices, playing a crucial role in effectively maintaining a high-temperature environment, reducing energy consumption, and enhancing testing efficiency. However, during the operation of these devices, the internal thermal insulation structure is inevitably subjected to high temperatures. Therefore, it is essential to focus on the heat transfer performance of this structure. Initially, the internal thermal insulation structure is designed, and the relative dimensions and materials of each component are determined. Subsequently, a finite element model of the internal thermal insulation structure is established, and numerical simulations of heat transfer are conducted under the device’s operating conditions to analyze the thermal insulation structure. This analysis is ultimately validated through high-temperature experiments conducted on specimens of the internal thermal insulation structure. The results indicate that the designed internal thermal insulation structure effectively maintains the high-temperature environment within the device and demonstrates excellent thermal insulation performance, with a maximum heat flux of 66.7 W/m² and an outer wall surface temperature of 25.98 °C. This work is significant as it lays the groundwork for the design and construction of such devices. 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

Elastocaloric cooling is an emerging solid-state refrigeration technology that leverages the latent heat exchange of shape memory alloys under mechanical stress. This study investigates the energy performance of a solid-to-solid elastocaloric cooling heat pump to enhance heat transfer efficiency and overall system performance. A Matlab-based numerical model, developed using the finite volume method, was employed to simulate the system. The energy performances of the elastocaloric heat pump are analyzed by varying the frequency of the cycle, the elastocaloric refrigerants, and the types of thermal diodes, from ideal up to realistic Peltier switches. The results demonstrate that the strategic use of thermal diodes significantly improves heat flow directionality, reducing thermal losses and enhancing the efficiency of the elastocaloric cooling process with a system that employs a realistic Peltier thermal diode, guaranteeing specific cooling powers up to 6500 W kg⁻¹. The maximum COPs of the system with ideal thermal diodes range from 60 to 10. These findings contribute to the development of more efficient solid-state cooling technologies, offering a viable alternative to conventional systems, especially for electronic circuit cooling applications. Full article

Hooked-head spur dikes are a specialized type of spur dike, where their geometry significantly influences flow diversion, sediment transport, and bank protection. This study establishes a three-dimensional numerical model utilizing the renormalization group (RNG) k-ε turbulence closure and the volume of fluid (VOF) method to explore the effects of hook angle (90°, 120°, and 150°) and hook-length ratio (L/D = 1/2, 1/3, and 1/4) on the flow structure surrounding a hooked-head spur dike. The study comprises nine simulation cases, and the distributions of mainstream velocity and turbulent kinetic energy (TKE) are analyzed. The results demonstrate that a hook angle of 120° yields the greatest increase in the mean dimensionless mainstream velocity (V*), corresponding to enhancements of 4.26% and 9.09% relative to the angles of 90° and 150°, respectively. When the hook angle is fixed at 120°, increasing the hook length enhances the mainstream velocity; specifically, at L/D = 1/2, the mean V* increases by 10.58% and 14.64% compared to at L/D = 1/3 and 1/4, respectively. Meanwhile, the TKE in the downstream recirculation zone decreases as either the hook angle or the hook length increases. At a hook angle of 90°, the mean dimensionless TKE (E*) is 8.80% and 10.65% higher than at 120° and 150°, respectively. For a fixed hook angle of 120°, the mean E* at L/D = 1/2 decreases by 3.46% and 9.35% compared to at L/D = 1/3 and 1/4, respectively. In summary, the appropriate selection of hook angle and hook length can effectively guide flow toward the channel center, increase conveyance capacity, and enhance hydraulic performance for river regulation. Full article

Ensuring numerical robustness in deep neural networks (DNNs) is critical, as defects like overflow or NaN can cause silent failures. However, automated repair is challenged by fragmented domain knowledge and the semantic gap for general-purpose large language models (LLMs). This work proposes NCKG, a Numerical–Conceptual Knowledge Graph-based method for retrieval-augmented repair of DNN numerical defects. NCKG introduces a unified semantic formalization that explicitly models DNN execution contexts, numerical defects, mitigation methods, and constraint knowledge, transforming dispersed defect knowledge into a consistent, machine-interpretable representation. Based on this formalization, a multi-view semantic graph index is constructed, enabling a hybrid semantic-driven retrieval mechanism that combines structure-aware graph matching with vector similarity. Retrieved, semantically aligned defect–repair knowledge is then used to guide LLMs in generating context-aware repairs. Experimental results demonstrate that NCKG significantly outperforms standard retrieval baselines and consistently improves the quality and correctness of LLM-generated fixes across different model scales. This work demonstrates that explicit semantic structuring and retrieval of domain knowledge are crucial for enabling reliable, automated numerical defect repair in DNNs. Full article

This paper investigates the prediction of the depth of penetration (DOP) for concrete targets under high-speed projectile impact using multiple simulation algorithms in LS-DYNA. Three numerical methods, i.e., the traditional finite element method (FEM), a fixed-coupling FEM-SPH (Smooth Particle Hydrodynamics) model, and an adaptive coupling FEM-SPH model, are employed to simulate the penetration processes. The computational results are compared against established empirical formulas to evaluate their predictive accuracy and efficiency. The findings indicate a distinct trade-off between numerical precision and computational cost. The adaptive FEM-SPH algorithm achieves the highest accuracy, with a maximum error of less than 10% across considered velocity ranges, and effectively captures cavity expansion effects. The standard FEM algorithm offers the highest computational efficiency, requiring less than half the time of the other methods, albeit with a maximum error of up to 25%. The fixed-coupling FEM-SPH model provides an intermediate solution, showing improved accuracy at velocities above 400 m/s but lower efficiency. This comparative analysis offers a practical guideline for selecting appropriate simulation techniques in protective structure design, balancing the demands for rapid estimation, detailed physical insight, and final safety verification. Full article

Numerical simulations of (1) two aerosol types such as organic carbon (i.e., spherical) and dust (i.e., non-spherical) particles, and (2) their mixtures are carried out. Optical and microphysical parameters of these aerosols in our simulations are provided by MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications, version 2). The inversion routine is performed with TiARA (Tikhonov Advanced Regularization Algorithm) using the Lorenz–Mie (i.e., spherical) light-scattering model in unsupervised and automated, i.e., autonomous mode. The results of our numerical simulations show that the accuracy of the inversion results for the aerosol mixtures from synthetic optical data perturbed by ±10% random error is comparable to the accuracy observed for the inversion results of the “pure” spherical particles. In particular, the retrieval uncertainties of effective radius, and number, surface-area, and volume concentrations of these mixtures are ±30%, ±10%, between –50% and +100% and ±30%, respectively. However, we need to apply a modified version of the gradient correlation method (GCM) to stabilize the inversion results. The results of this study will form the baseline for future work, where we plan to apply TiARA to optical data products obtained from real lidar observations in the framework of the SCC (Single Calculus Chain) of EARLINET (European Aerosol Research Lidar Network). Full article

The Cairo Monorail System presents significant geotechnical challenges due to its integrated structural configuration and its alignment across heterogeneous soil conditions, including collapsible and swelling soils. This study investigates the foundation performance of the monorail through a combination of advanced site investigations, full-scale pile load testing under dry and wetted conditions, and finite-element modeling incorporating soil–structure interaction. Field load tests on large-diameter bored piles founded in collapsible soils demonstrated a pronounced increase in settlement and a reduction in stiffness following wetting, confirming the sensitivity of pile behavior to moisture variations. Three-dimensional numerical analyses of the integrated monorail system showed that differential settlements between adjacent columns are generally limited to less than 9 mm under serviceability loading conditions, satisfying passenger comfort requirements. Long-term coupled seepage–deformation analyses conducted using PLAXIS indicated that surface water infiltration into swelling soils may induce time-dependent monopile heave of approximately 10 mm over a 50-year design life, which remains within acceptable serviceability limits. The results demonstrate that detailed geotechnical characterization, combined with appropriate numerical modeling strategies, can effectively control differential deformation and long-term heave in continuous monorail systems, ensuring their operational safety and long-term performance. Full article