Search Results (1,404)

Stable circulation and limited mechanical loading are key requirements in the fluidized-bed coating of small vegetable seeds. For Chinese cabbage seeds, their small mass, irregular geometry, and mechanical sensitivity make it difficult to evaluate operating conditions using only global indicators, such as mean particle velocity and bed expansion height. In this study, a two-way coupled computational fluid dynamics–discrete element method (CFD-DEM) model was developed for a draft-tube fluidized-bed seed coater. Chinese cabbage seeds were represented by seven-sphere clumps, and an L9(3³) orthogonal array was used as a screening design to examine inlet air velocity, initial bed height, and bottom circulation inlet gap. The evaluation combined cycle time distribution (CTD), the global low-speed particle fraction R_s, the 95th-percentile normal contact force F_95,n, and the normalized high-percentile contact-load ratio η_c,95. Because the L9 array cannot resolve interactions or support a full quadratic model, factor effects were interpreted descriptively within the investigated range rather than as a confirmatory global optimization. Initial bed height produced the largest descriptive contribution to the circulation period, R_s, and F_95,n. Increasing inlet air velocity shortened the circulation period and reduced Rs but increased high-percentile contact loading. Across the nine cases, F_95,n ranged from 7.50 to 14.50 mN and η_c,95 from 0.18% to 0.35%; η_c,95 is used only as a normalized load ratio and not as a validated probability of seed damage. Case 4 ranked first under equal weighting and contact-load-priority weighting, whereas Case 7 ranked first under circulation-priority weighting. Case 4 is therefore described as a weight-dependent balanced candidate within the tested parameter range. Prototype experiments reproduced the ordering of circulation periods for three dry operating conditions, supporting qualitative consistency between simulated and observed circulation behavior. Visible breakage remained below 0.5%, but this observation provides only preliminary qualitative correspondence with the simulated contact-load trend. The proposed framework is intended for dry-stage screening and does not directly predict wet-coating quality, adhesion, agglomeration, or germination performance. Full article

Automotive thermal-comfort studies commonly focus on interactions between occupants and cabin air, although the seat forms the principal sustained contact interface between an occupant and a vehicle. This study presents a coupled computational fluid dynamics (CFD) framework that simultaneously resolves heat conduction through perforated leather, breathable sponge, heating pads, and foam; porous airflow through the seat; seat heating and ventilation; and convective heat transfer between the occupant and cabin air. Four total seat-heating powers (0, 60, 90, and 120 W) and four ventilation-fan speeds (0, 1500, 3000, and 4500 rpm) were simulated for 900 s. The results show that seat heating primarily alters temperatures in the contact region through conduction, whereas seat ventilation increases local airflow and cooling near the edges of ventilated contact regions. The principal contribution is a reproducible interface between cabin CFD and thermophysiological modeling. The framework generates spatially resolved fields of air temperature, air velocity, skin and contact-surface temperatures, and heat flux that can serve as boundary conditions for physiological models such as the Fiala and Berkeley models and for subsequent experimental validation. Because the present calculations constitute a comparative single-driver study, direct experimental validation, active thermoregulation, subjective thermal sensation, and interactions under full occupancy must be addressed before the framework can provide absolute comfort predictions. Full article

Aiming at the engineering pain points of insufficient sample size, inadequate working condition coverage, and poor generalization performance in traditional solution methods of vertical hydrodynamic coefficients for Autonomous Underwater Vehicles (AUVs), this paper constructs a high-precision prediction framework for vertical hydrodynamic coefficients Computational Fluid Dynamics (CFD) numerical simulation and a genetic algorithm-optimized back-propagation (GA-BP) neural network. Firstly, the overset grid technology and User-Defined Function (UDF) are adopted to simulate the pure heave motion of the Planar Motion Mechanism (PMM), completing the unsteady flow field numerical calculation. Secondly, 200 working condition simulation datasets covering different motion amplitudes, heave frequencies and inflow velocities are constructed, and a three-input and two-output BP neural network basic prediction model is established. Subsequently, the basic model is optimized by 5-fold cross-validation and genetic algorithm respectively, and the prediction performances of BP, K-fold-BP and GA-BP models are compared and analyzed. The results show that the determination coefficients of the GA-BP model for the dimensionless vertical hydrodynamic coefficients Z_a and Z_b reach 0.9976 and 0.9975 respectively, and the Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) are significantly lower than those of the other two models, with the optimal prediction accuracy and generalization performance. Finally, 1000 sets of full-working-condition hydrodynamic coefficient prediction are completed based on the GA-BP model, and the optimized dimensionless added mass coefficient and fluid damping coefficient are obtained by fitting. The prediction framework constructed in this paper can provide technical support for the rapid and high-precision acquisition of AUV full-working-condition hydrodynamic coefficients, and provide a reliable parameter basis for dynamic modeling and motion control system design. Full article

Double-skin façades (DSFs) offer a promising building-envelope strategy for improving thermal management by promoting heat’s removal from the façade cavity before it is transferred toward the indoor environment. This study numerically investigates the influence of cavity width on the thermo-fluid performance of a mechanically ventilated DSF under summer operating conditions. A two-dimensional computational fluid dynamics (CFD) model was developed using the RNG k-ε turbulence model together with the discrete ordinates radiation model. Mechanical ventilation was imposed through a velocity inlet of 0.765 m s⁻¹, with an inlet air temperature of 17 °C and a solar radiation intensity of 365.4 W·m⁻². The numerical model was validated against published experimental temperature measurements, yielding an average absolute relative error of approximately 5.65%. The validated model was subsequently applied to cavity widths ranging from 0.10 to 0.70 m. Increasing the cavity width substantially modified the airflow development and thermal field. The monitored temperature decreased from 31.66 °C at 0.10 m to 17.64 °C at 0.50 m, while further enlargement produced only minor reductions to 17.43 and 17.28 °C at 0.60 and 0.70 m, respectively. The total heat-transfer rate increased from approximately 1000 W at 0.10 m to a maximum of 1388 W at 0.50 m before slightly decreasing to 1379 and 1376 W at 0.60 and 0.70 m, respectively. This temperature reduction enhances heat removal from the façade cavity, helping to limit heat transfer toward the indoor environment and improve indoor thermal comfort under summer conditions. These results demonstrate a non-monotonic relationship between cavity width and heat-removal performance, with 0.50 m providing the highest heat-transfer rate among the investigated configurations. This result is specific to the geometry, boundary conditions, ventilation rate, and operating conditions considered in the present study. It should not be interpreted as a universally optimal cavity width for mechanically ventilated DSFs. The findings highlight the importance of cavity-width selection in the thermal management and design of mechanically ventilated DSFs for energy-efficient building envelopes. Full article

Continuous-flow technology offers advantages in fine chemical and pharmaceutical processes; however, high-solid-holdup (solid mass fraction) liquid–solid systems are prone to clogging and mass transfer deterioration. Although multiphase flow reactors are widely applied, their performance remains insufficiently characterized. In this study, computational fluid dynamics (CFD) coupled with the Mixture model and kinetic theory of granular flow (KTGF) is combined with residence time distribution (RTD) experiments to establish and validate a numerical model. The effects of feed flow rate, rotational speed, and solid holdup on mixing and solid-phase RTD are systematically investigated. Simulation results reveal that the reactor exhibits satisfactory radial and axial mixing performance, alongside non-ideal flow characteristics including recirculation, wall enrichment, and weak back-mixing. Increasing feed flow rate enhances axial mixing and suppresses back-mixing. In the solid holdup range of 10–30%, rotational speed significantly influences axial mixing uniformity ζ and dimensionless variance σ_θ²; in the 30–50% range, ζ continuously increases while σ_θ² first decreases and then increases. Based on CFD data within this range, an empirical correlation for the Péclet number Pe was established (with good fitting for Pe < 35); it serves only as an interpolation tool and does not possess predictive or general design capability. These findings provide a reference for applying multiphase flow reactors in high-solid-holdup liquid–solid mixing systems. Full article

The Peregrine breather (PB), a classical localized solution of the nonlinear Schrödinger equation (NLSE), is widely used to describe the evolution of deep-water rogue waves. However, the influence of variable bathymetry on PB focusing remains insufficiently understood. A two-dimensional RANS–VOF numerical wave tank is therefore established using computational fluid dynamics (CFD) to investigate deterministic PB propagation over variable bathymetry. The model is validated through mesh- and time-step-sensitivity analyses and comparison with the analytical PB solution. Relative water depth, bathymetric interaction length, and bathymetric position are systematically examined. The results reveal for the first time a bathymetry-induced delayed-focusing phenomenon: the PB undergoes local defocusing over elevated topography and refocuses farther downstream after re-entering deeper water. The delay increases as water depth decreases. For k₀h_shelf > 1.363, increasing the interaction length mainly enhances the focusing delay, while self-focusing recovers in deeper water. In contrast, for k₀h_shelf < 1.363, an interaction length of approximately two carrier wavelengths disrupts the coherent PB structure and splits it into two wave packets. The onset position of bathymetric forcing has only a minor effect on the final delay. These results clarify how variable bathymetry modulates PB focusing and structural stability and provide a theoretical reference for nearshore extreme-wave risk assessment. Full article

Brazed-plate heat exchangers (BPHEs) are widely used as recuperators in organic Rankine cycle (ORC) systems, but their corrugated passages make full-scale Computational Fluid Dynamics (CFD) simulations prohibitively expensive, limiting the use of CFD for performance prediction and for deriving design-oriented heat-transfer correlations. This work presents a validated domain-reduced CFD methodology for a BPHE recuperator operating with R134a. The computational domain is reduced to a single exchange unit (one vapor and one liquid corrugated channel separated by one heat-transfer plate), further downscaled by truncating the plate length to the fully developed corrugated region, exploiting longitudinal symmetry, and approximating the corrugation profile with a trapezoidal shape; the resulting mesh (≈4.5 × 10⁶ cells) is approximately 44.5 times smaller than the estimated 2 × 10⁸-cell full-stack mesh. Five steady operating points from a micro-scale ORC test rig (mass-flow rate 0.08–0.22 kg/s, Re ≈ 500–18,500) are used for validation by mapping experimental data to the reduced domain through an ε–NTU formulation. CFD predictions of hot- and cold-side temperature changes agree within 1–10% of the reference values. Building on this validated model, single-phase Nusselt-number correlations are proposed, valid over 500 < Re < 1400 for the liquid phase and 6000 < Re < 18,500 for the vapor phase. The proposed method and results support preliminary, geometry- and model-specific assessment of BPHE recuperators; broader transferability requires additional geometries, operating points and model-form validation. Full article

A building façade normally keeps the weather out, lets in daylight, allows ventilation, and shapes how a building looks from outside. This study asks whether it can also help generate electricity without giving any of that up. Solar chimney power plants (SCPPs) generate clean electricity from solar heat, but they have mostly been studied for open, land-abundant rural sites. Mounting one onto a façade instead risks the very things a façade is meant to protect: thermal comfort, natural ventilation, and architectural freedom. No prior study has looked at energy output, thermal behaviour, double-skin façade (DSF) operability, and architectural freedom together for solar chimneys integrated into high-rise buildings, and this is the gap this work addresses. We coupled solar chimney power plants with double-skin façades across five configurations, evaluated using Computational Fluid Dynamics (CFD) validated against the Manzanares pilot plant to achieve 3.3% for velocity and 3.0% for temperature. Using the DSF as both collector and absorber (Model 1) pushes power to its highest point, 78.7 kW, but it drives inner-façade air to 327.1 K and shuts off ventilation entirely. Confining the collector to the roof and upper chimney instead (Model 5) settles for a more modest 31.1 kW, but it preserves DSF ventilation over most of the façade height and keeps inner air below 305.8 K through the majority of that range, with only the uppermost portion becoming thermally unsuitable for natural ventilation. Weighing power, thermal load, ventilation, and façade freedom together in a composite score, Model 5 comes out as the preferred configuration under the adopted equal-weight multi-criteria assessment. A parametric study of height, irradiance, and ambient temperature for Model 5 produced design equations that, paired with a Random Forest climate forecast, benchmarked against three alternative algorithms and evaluated on a chronological hold-out set (city-level test R² up to 0.83 for irradiance and 0.94 for temperature), power a predictive framework for hourly-to-annual energy output at any height and city, demonstrated here for seven cities across five continents. Full article

To address the challenge of efficient catalytic elimination of carbon monoxide (CO) generated from spontaneous coal combustion in goaf and blasting operations in underground coal mines under low-velocity laminar flow conditions, we propose a perforated spiral-insert catalytic tube. The design inserts a spiral vane with surface micro-holes into a straight tube; the vane surface and internal pore walls are coated with a CuMnOx catalyst. A porous medium equivalent model describes the flow and catalytic reaction characteristics in the perforated region. A three-dimensional Computational Fluid Dynamics (CFD) model coupling flow, mass transfer, and surface catalytic reactions is developed. After grid independence verification, three sets of L9 orthogonal experiments systematically investigate the effects of inlet velocity, helix pitch, vane height, opening ratio, and pore diameter on CO conversion and flow resistance. Range analysis, variance analysis, and the comprehensive performance factor are used for multi-objective optimization. $PEC$ results show that inlet velocity is the primary factor affecting both conversion and comprehensive performance, and its dominance is independent of the number of vanes. At a low velocity of 0.2 m/s, the four-vane configuration achieves a maximum conversion of 51.07%. For a balanced trade-off between conversion and flow resistance, four vanes with a high opening ratio, large pore diameter, and large helix pitch yield the best comprehensive performance. If low resistance is the primary goal, two vanes with a high opening ratio achieve a resistance of only 0.29 Pa and a per-unit-resistance conversion efficiency of 97.72 Pa⁻¹. A further predicted optimal combination is validated by simulation, achieving a conversion of 64.96%, confirming the effectiveness of the parameter optimization. Under low-velocity conditions, the flow resistance of this design is only about 0.3–1.3 Pa, allowing passive operation using the natural negative pressure of the extraction pipeline. The design offers modular replaceability of the catalyst insert and operates without external power input beyond the natural negative pressure of the pipeline under the simulated low-velocity conditions, providing a theoretical basis and parameter optimization method for in situ CO catalytic elimination in coal mines. Full article

Oil-pool fires involving liquid hydrocarbons are difficult to suppress and pose substantial economic risks. This study characterizes three widely used Class B fire suppressants through physical property measurements, cold oil-surface spreading tests, and burning oil-pool fire experiments, coupled with transient computational fluid dynamics (CFD) simulations in ANSYS Fluent. The results show that 3% aqueous film-forming foam (3% AFFF) and 3% alcohol-resistant aqueous film-forming foam (3% AFFF-AR) spread spontaneously on oil surfaces, whereas 3% fluoroprotein foam (3% FP) has a negative spreading coefficient and covers oil surfaces only through gravitational accumulation. Although 3% AFFF exhibits the fastest cold-state spreading, 3% AFFF-AR achieves the shortest fire-extinguishing time under combustion conditions because of its superior thermal stability and longer drainage time. In contrast, 3% FP shows the poorest fire-extinguishing performance. The CFD simulations capture the main temporal evolution of foam spreading and agree reasonably with experimental observations, particularly in the temporal consistency between simulated foam front propagation under the simplified elevated-temperature boundary condition and measured extinguishment times. Within the scope of the present simplified model and small-scale experiments, the results suggest that a positive spreading coefficient serves as a necessary but insufficient thermodynamic condition for effective foam spreading. Under high-temperature conditions, foam thermal stability critically influences the sustainability of spreading by resisting thermal degradation and bubble rupture, while drainage behavior and spreading kinetics modulate the coverage rate; collectively, these factors determine the overall fire suppression effectiveness under the tested conditions. These findings provide preliminary support for optimizing firefighting foam performance, pending validation under larger-scale and more fully resolved combustion scenarios. Full article

Lightweight design of high-speed-train water tanks can easily lower the natural frequency of baffles, increasing the risk of resonance and fatigue failure and thus threatening operational safety. To address this issue, a lightweight optimization method that does not reduce the first-order natural frequency of the baffle is proposed, taking a suspended water tank of a certain type of CRH electric multiple unit (EMU) as the research object. First, a two-way fluid–structure interaction (FSI) finite element model was established based on the computational fluid dynamics (CFD) method. The design of experiments method was employed to determine the optimal number of baffles inside the tank, and the response surface methodology was applied to construct quadratic polynomial surrogate models for baffle mass, maximum water tank stress, baffle deformation, and the first-order natural frequency. Analysis of variance was conducted to verify the fitting accuracy and significance of each model. After clarifying the influence of design variables on the response indicators, and to overcome the shortcomings of the standard multi-objective particle swarm optimization (MOPSO) algorithm, such as susceptibility to local optima, simplistic constraint handling, and premature convergence, an improved multi-objective particle swarm optimization (IMOPSO) algorithm integrating chaotic initialization, adaptive parameter adjustment, and a dynamic mutation strategy was proposed. With the first-order natural frequency serving as a constraint, multi-objective optimization of the baffle structure was carried out. Finally, the prediction accuracy of the surrogate models was numerically validated using finite element simulation software. The results show that after optimization, the baffle mass was reduced by 16.13%, the first-order natural frequency increased by 0.41 Hz (by FEM), the maximum water tank stress decreased by 288 Pa (by FEM), and the baffle deformation was reduced by 7.66% according to FEM verification (RSM surrogate-model prediction gave a reduction of 9.07%). The maximum prediction error of the surrogate models was only 1.53%, confirming the effectiveness and feasibility of the proposed method. This study can provide a theoretical basis and engineering reference for the improvement and performance optimization of water tanks on CRH EMUs and other similar tank structures. Full article

The increasing complexity of environmental analysis requires new approaches for interactive-scale simulation across indoor and urban spaces. While computational fluid dynamics (CFD) models provide detailed representations of gas dispersion and aerosol transport, they are often computationally intensive for interactive environmental analysis and integration into digital twin platforms. This pilot study presents a GPU-accelerated voxel simulation framework for modeling three-dimensional gas dispersion and aerosol transport using structured voxel representations derived from BIM, LiDAR, GIS, and other 3D built-environment datasets. The framework provides physically informed, CFD-inspired simulation at sub-meter to meter-scale spatial resolutions while maintaining interactive runtime performance suitable for building management, ventilation analysis, environmental monitoring, hazard assessment, and emergency response applications. Transport dynamics are modeled using a discretized advection–diffusion formulation incorporating airflow-driven advection, diffusion, source emissions, and voxel-level sink mechanisms. A key contribution is the development of a voxel-native GPU-parallel computational architecture implemented in Python 3.10.20 using Taichi kernels. Prototype simulations and comparative validation against a benchmark ANSYS Fluent 20.1 simulation demonstrate stable transport behavior, encouraging agreement with the CFD solution, browser-based three-dimensional visualization, and efficient execution on commodity GPU hardware. Experimental scenarios include a voxelized three-story Industry Foundation Classes (IFC) building model comprising approximately 34.5 million active voxels ($582\times 382\times 155$ voxels) and an urban-scale 3D city model spanning approximately $300\times 300\times 150$ m and containing up to 13.9 million active voxels. Simulations containing tens of millions of voxels were completed within minutes on a single consumer-grade GPU, demonstrating the scalability of the framework. These results demonstrate that the proposed framework provides an efficient voxel-based approximation of gas dispersion suitable for interactive environmental analysis and can support future integration with digital twin and AI-assisted environmental simulation systems. Full article

Precise prediction of pressure drop and drag-reduction performance is essential for improving the hydraulic efficiency and reducing the energy demand of crude-oil pipeline transportations. Therefore, this study aims to develop an integrated computational fluid dynamics (CFD)–machine learning (ML) framework for predicting pressure drop (∆p), drag reduction (DR), pumping power reduction (PPR), energy savings (ES), and flow-rate enhancement (Q) in turbulent crude-oil pipeline flow containing drag-reducing agents (DRAs). The investigated system considers the effect of pipeline length (L), diameter (D), surface roughness (ε), operating temperature (T), and DRA concentration (25–200 ppm). The Reynolds-average Navier–Stokes equations (RANS) were solved using the shear stress transport (SST) k-ω turbulence model approaching near-wall resolution of y⁺ ≈ 1 for DRA3 at 20 ppm. The CFD modelling was first used to validate an experimental benchmark and subsequently used to expand the available dataset over the investigated operating conditions. The combined experimental–CFD dataset was then employed to develop a multi-output Kolmogorov–Arnold network (KAN) surrogate model. The proposed framework predicted DR up to 44.2%, PPR of approximately 55 W, ES of 30%, and flow-rate enhancement up to 5–10(${\displaystyle \frac{\mathrm{L}}{\mathrm{d}\mathrm{a}\mathrm{y}}}$). The KAN model effectively captured the nonlinear relationships among DRA characteristics, pipeline geometry, and operating conditions, achieving R² = 0.9318 for PPR prediction. The novelty of the proposed work lies in integrating a validated, near-wall-resolved SST k-ω CFD model with a multi-output KAN surrogate model, combining physics-based flow analysis with rapid data-driven prediction of hydraulic and energy-performance indicators. Full article

As a critical regulating component in subsea Christmas tree systems, the cage-type choke valve governs the overall production efficiency and operational reliability of offshore oil and gas exploitation owing to its unique internal flow field characteristics. In accordance with the in situ operating conditions of the target oilfield, this paper performs a numerical simulation and systematic analysis on the flow field behaviors of a cage-type choke valve. Based on the fundamental theories of computational fluid dynamics (CFD), a three-dimensional coupled flow and heat transfer numerical model for the target choke valve is constructed via the FLUENT solver. Flow parameters under diverse pressure difference conditions are measured, validating the accuracy and feasibility of the established numerical model. Corresponding model hypothesis criteria and boundary condition configuration schemes are explicitly defined. Spatial distribution characteristics of the internal temperature, velocity, and pressure fields of the choke valve under different operating conditions are obtained through numerical simulation. Ten monitoring nodes uniformly arranged along the fluid domain from the inlet to the outlet are selected for quantitative analysis. The research results clarify that lower seawater temperature intensifies heat dissipation, leading to the observed temperature decrement, and confirm that the cage orifice structure dominates the flow acceleration, with the pressure drop magnitude linearly correlating with the inlet–outlet differential pressure. The research methodology and numerical findings of this study can provide a reliable basis for structural optimization and operating condition matching of cage-type choke valves applied in subsea oil and gas production systems. Full article

High gas–oil ratio (GOR) well streams challenge the stable operation of oilfield gathering systems because positive-displacement multiphase pumps lose volumetric efficiency, amplify pressure pulsation, and suffer seal degradation as the inlet gas fraction rises. Targeting GOR = 100–300 Nm³/t (≈480–1450 scf/STB), this study proposes a jet pump-based oil–gas multiphase transportation system together with an evaluation framework that couples localized computational fluid dynamics (CFD) with a one-dimensional (1D) transient pipeline network model. The methodological novelty is a GOR-dependent source-term closure embedded in the 1D momentum equation: the pump pressure rise is evaluated at every time step as $\mathsf{\Delta }{p}_{\mathrm{p}\mathrm{u}\mathrm{m}\mathrm{p}}\left(t\right)=k_g\left(\mathrm{G}\mathrm{O}\mathrm{R}\right)·{\Pi }_p\left(\mathrm{G}\mathrm{O}\mathrm{R},p_w\right)·\left(p_w-p_s\right)$ from CFD-derived maps of entrainment ratio, pressure recovery, and high-gas correction, so that the jet pump enters the network simulation as a dynamic source rather than a steady boundary condition, a capability that neither pump-level transient CFD nor conventional 1D codes provide. Transient simulations under slug disturbances give three main results. (i) At GOR = 200 Nm³/t and constant working-fluid pressure, slug arrivals drive the outlet pressure transiently below the ±5% band (0.76–0.84 MPa), and it returns to the band of the 0.80 MPa set point within ≈150 s. (ii) As GOR increases from 100 to 300 Nm³/t, ${\displaystyle \frac{{\sigma }_p}{p_{\mathrm{s}\mathrm{e}\mathrm{t}}}}$ rises from 0.031 to 0.089 and the peak-to-peak ratio from 0.18 to 0.50, with stability criterion C1 violated beyond ≈275 Nm³/t. (iii) Three applicability zones are delineated: preferred (100–200), controllable (200–260), and marginal (260–300 Nm³/t), where the marginal zone requires inlet peak-shaving, ≥30% working-fluid pressure margin, and feedforward–feedback control. Mesh independence (${\mathrm{G}\mathrm{C}\mathrm{I}}_{\mathrm{f}\mathrm{i}\mathrm{n}\mathrm{e}}=0.23–0.35$%) and a CFD–1D transfer mismatch ≤3% support internal consistency; the delineated boundaries remain model predictions pending experimental and field validation. Full article