Search Results (4,931)

Double-skin façades (DSFs) can moderate heat transfer and airflow between the outdoor environment and the building interior; however, their performance in hot-arid climates is highly dependent on cavity geometry, ventilation arrangement, and the interaction between the airflow and any active cooling surfaces. The objective of this study is to establish, under a single idealised extreme hot-arid design point, how sealed, ventilated and actively cooled double-skin façade cavities differ in their predicted temperature, velocity and turbulent kinetic energy fields, and which arrangements merit controlled follow-up study. The four configurations are treated as an idealised comparative case study rather than as validated building-performance predictions. This exploratory study uses computational fluid dynamics (CFD) to compare the aerothermal behaviour of four DSF cavity configurations under prescribed external air and outer-wall temperatures of 50 °C, an inner-wall temperature of 24 °C, and an external inlet velocity of 3.06 m/s. The configurations comprise a sealed 0.4 m cavity (M1), a wind-driven ventilated 0.4 m cavity (M2), the same ventilated cavity with six 25 mm cooling pipes at 10 °C (M3), and a concept-stage lateral-flow arrangement combining a 0.10 m cavity, a 0.025 m slit and four 80 mm cooling pipes at 10 °C (M4). The simulations employ the standard k-ε turbulence model with fixed thermal boundary conditions. Along the reported sampling lines, M1 exhibited a nearly uniform air temperature of approximately 45.7 °C, whereas M2 remained close to the imposed 50 °C external-air temperature. M3 produced lower temperatures in the immediate vicinity of the cooling pipes, but most of the sampled profile remained near ambient conditions. M4 exhibited a broader spanwise temperature range of approximately 26.9–50 °C, with local pipe-adjacent air temperatures approaching 24 °C and cooler regions developing along parts of the lateral flow path. The findings provide preliminary concept-screening evidence and support further controlled parametric analysis, higher-fidelity modelling, and experimental validation. Full article

The maneuvering flight of future aircraft which employ morphing variable camber wings (VCWs) requires rapid and accurate aerodynamic regulation. However, the dynamic lift responses during fast morphing deflection exhibit unsteady hysteresis effects, hindering shape and flight control performance. This study proposes a novel modeling and feedforward compensation algorithm based on the Prandtl–Ishlinskii (PI) model to identify and mitigate such unsteady hysteresis effects from a control perspective. First, unsteady lift responses of a two-dimensional trailing-edge VCW under periodic and non-periodic morphing motions are analyzed, and the influences of morphing trajectories on lift characteristics are investigated. The results reveal that the maximum lift decreases significantly as the morphing frequency increases. Under point-to-point non-periodic morphing conditions, pronounced hysteretic lift responses are observed and are strongly influenced by the morphing trajectories. A forward model mapping “morphing trajectory-lift response” is developed using PI hysteresis operators and log(t)-creep operators, identified using time-domain data from two-dimensional computational fluid dynamics (CFD) calculations. From this, an inverse model of the “expected lift response-compensated morphing trajectory” is derived using a hysteresis compensation function. Simulations indicate that periodic lift hysteresis is effectively compensated, yielding a quasi-steady linear relationship. For fast terminal morphing, compensated trajectories enable lift to reach targets rapidly, smoothly, and stably without lag. Robustness is validated for varying lift targets and terminal times. This work offers new insights into fast morphing-wing and high-maneuverability control of future smart aircraft. Full article

This paper introduces a direct oil cooling concept for rotor coils of an electrically excited synchronous propulsion motor. The proposed approach utilizes a hollow shaft and two distinct laminations to guide non-conductive, ultra-low-viscosity automotive oil onto the rotor coils. Radial channels are positioned at the rotor center to transfer oil from the hollow shaft to the axial channels at the outer surface of the rotor. Axial channels direct the coolant from the radial channels and splash it onto the rotor end windings. The proposed approach enhances the thermal management of the heat generated by rotor coils, and helps improve the motor performance and power density. Computational fluid dynamics (CFD) simulations were conducted to analyze the effectiveness of the cooling method under various operating conditions. Full article

Background: Cell migration is a biological process influenced by biochemical signals and mechanical stimuli from the microenvironment. In this context, the accurate characterization of the mechanical microenvironment generated within microfluidic platforms represents an essential step for the design and interpretation of cell migration studies. Understanding how hydrodynamic forces influence the mechanical microenvironment experienced by cells remains a challenge, especially in confined and biomimetic systems. Methods: In this study, a three-dimensional microfluidic device was developed in silico to characterize the effects of flow variation on mechanofluidic parameters and to provide a quantitative basis for designing future cell-migration experiments. Computational fluid dynamics simulations were performed to characterize the velocity, pressure, and wall shear stress (WSS) distributions under different inlet flow rates (0.5, 1, and 5 µL/min) and three distinct inlet/outlet configurations within the same three-dimensional geometry. Rigid hemispherical probe structures were incorporated into the model to quantify the local shear stress acting on cell-sized surfaces. Results: The results demonstrated a direct and linear relationship between the applied flow rate and the WSS, modulated by the channel geometry and the inlet and outlet configuration. Regions near micropores and lateral channels showed high WSS values, while central regions experienced less mechanical stimulation, depending on flow conditions. Comparison with WSS values and ranges associated with cellular responses reported in the literature indicated that certain operational configurations generated mechanical conditions comparable to those previously investigated in cell-based studies, including cell migration applications. Conclusions: Overall, the study highlights the importance of controlling flow conditions in microfluidic platforms and provides a quantitative basis for the development and optimization of three-dimensional microfluidic devices intended for designing future cell-migration experiments. The systematic comparison of three inlet/outlet configurations across three flow rates within the same three-dimensional geometry provides a comparative framework for identifying configuration-dependent changes in the local mechanofluidic environment, supporting the selection of operational conditions for future mechanobiological and cell-migration studies. Full article

Computational fluid dynamics methods range from Reynolds-Averaged Navier–Stokes (RANS) simulations to Direct Numerical Simulations (DNSs). RANS offers low computational cost at the expense of accuracy, while DNS provides high accuracy but at a prohibitive cost. The aim of this study is to evaluate whether multi-fidelity neural networks can learn a corrective mapping from RANS to DNS for a small canonical dataset and to determine how training-set composition and model architecture influence generalisation across geometries. In this study, multi-fidelity neural networks for data fusion between low-fidelity RANS and high-fidelity DNS data were applied to turbulent flow (Re = 5600) over parameterised periodic hills, defined by a geometry parameter characterising the steepness ratio. The inputs to the models were the coordinates and the corresponding RANS velocity components, and the outputs were the DNS velocity components, with data from both fidelities mapped onto the same mesh. Both a single-branch and a two-branch architecture were considered. Generalisability was assessed within a small dataset of five periodic hills defined by different values of the geometry parameter $\alpha$ (0.5, 0.8, 1.0, 1.2, 1.5). Both model architectures were trained on data from different combinations of the geometry parameter to evaluate interpolation and extrapolation capabilities. Both networks successfully corrected RANS flow fields for unseen geometries in interpolation regimes. When interpolating, the single-branch architecture achieved more than a 69% reduction in error, while the two-branch architecture achieved more than a 60% reduction, with both improving key flow features such as recirculation zones and jet structures. A key finding is that the single-branch architecture consistently outperformed the two-branch formulation, particularly in low-data regimes. The results show that multi-fidelity neural networks can improve RANS predictions using small datasets and simple inputs, provided that the training set spans the relevant geometric space. As the model does not require the geometry parameter as an explicit input, it is applicable to geometries lacking straightforward parameterisation. The demonstrated advantage of the single-branch architecture highlights the importance of architectural simplicity when training data is limited. Full article

Convective drying of Zingiberaceous roots, particularly ginger (Zingiber officinale), requires a uniform distribution of airflow and temperature to ensure energy efficiency and product quality. However, many drying systems exhibit aerothermal limitations that produce temperature gradients and non-uniform drying conditions. To address this issue, this study proposes a dual-swirl dryer featuring two air inlets: an upper helical inlet and a lower tangential inlet. Both inlet configurations generate swirling airflow patterns that enhance thermal uniformity and increase the residence time of hot air within the drying chamber. The internal flow behavior was investigated using Computational Fluid Dynamics (CFD) simulations in ANSYS Fluent2025 R1 version. A three-dimensional polyhedral mesh was generated to improve computational efficiency and numerical accuracy. Turbulence and recirculation phenomena were modeled using the Realizable k–$ϵ$ turbulence model, while temperature distribution was analyzed through the energy conservation equation. Numerical predictions were experimentally validated using temperature sensors integrated into an automatic control system. The comparison between numerical and experimental results demonstrated that the dual-swirl configuration improves airflow redistribution, reduces thermal stagnation zones, and promotes a more homogeneous temperature field throughout the drying chamber. These findings confirm that the proposed system is an efficient alternative for agro-industrial drying applications. Full article

If a CO₂ reservoir or transmission pipeline were to leak, both the surrounding ecology and maritime traffic safety could be put at risk. To better understand and prepare for this risk, multiphase Computational Fluid Dynamics (CFD) models were built in ANSYS Fluent to capture the behavior of a leak once it enters the water. A 3D Eulerian–Eulerian model was used for validation, while a simplified 2D model was applied to simulate conditions at a 50-m depth. The models integrate bubble dynamics, gas holdup, CO₂ dissolution, dissolved species transport, and seawater acidification into a unified CFD framework. Mass transfer was calculated using the Hughmark correlation, and local seawater temperature and salinity were factored in to determine dissociation behavior and the relevant Henry’s Law constant. To confirm the 3D model’s accuracy, results were checked against two experimental datasets: the QICS field study and the Hauser Tank experiments. The team also modeled a hypothetical release scenario at the High Island 10L site and compared the results with earlier published work. The results show that at a depth of 50 m, the surrounding water column can completely absorb a CO₂ release at a rate of 35 kg/s, since the gas dissolves into the seawater as it rises toward the surface. Beyond confirming this mitigation capacity, the simulations shed light on how a leak would actually unfold in the environment, including the shape and movement of the rising bubble plume, how much CO₂ dissolves along the way, and the resulting shifts in seawater pH and pCO₂. Together, this provides a practical framework for assessing how CO₂ leaks could affect marine environments in the Gulf of Mexico. Full article

During the X-ray Diffraction (XRD) identification of the traditional Chinese medicine Os Draconis, the identification model often suffers from limited classification accuracy due to the difficulty in determining optimal parameters. To address this issue, this paper proposes a Hydrodynamic Improved Particle Swarm Optimization (HIIPSO) algorithm for the deep optimization of model parameters. In practical identification scenarios, the high complexity of XRD data poses severe challenges to the convergence speed and global search capability of optimization algorithms. To enhance model performance, this study introduces the interaction mechanism from fluid dynamics into the particle swarm optimization process. Specifically, HIIPSO incorporates a Voronoi neighbor topology to enhance population diversity and spatial distribution rationality. Concurrently, a hydrodynamic interaction mechanism is constructed to simulate the cooperative behavior of particles in a fluid environment, thereby effectively preventing the algorithm from falling into local optima. A theoretical analysis of the computational complexity of the HIIPSO algorithm in the parameter search task for XRD identification models was conducted, confirming that it falls within an ideal range for engineering applications. Statistical analysis of the experimental results demonstrates that, in the parameter optimization task for the Os Draconis identification model, the HIIPSO algorithm significantly outperforms traditional and other baseline algorithms across key metrics, including the optimal value, mean, standard deviation, and median of the objective function. The experimental data indicates that the HIIPSO algorithm can substantially improve the robustness and identification accuracy of the XRD-based Os Draconis identification model, making it an optimal solution for parameter optimization problems in the digital identification of complex mineral-based traditional Chinese medicines. Full article

In recent years, hydrogen-fueled internal combustion engines offer significant potential for achieving high efficiency and near-zero carbon emissions. However, stable combustion remains challenging due to the limited time available for fuel–air mixing, particularly in direct-injection concepts. This study investigates the influence of injector orientation on in-cylinder charge preparation in a heavy-duty spark-ignition engine operating with a side-mounted hydrogen direct-injection strategy. Three-dimensional computational fluid dynamics (CFD) simulations are performed to evaluate the effects of injector blow-cap inclination and azimuthal alignment on hydrogen jet evolution, flow-field development, and mixture formation. Under high-pressure injection conditions, hydrogen enters the cylinder as a highly under-expanded jet with strong momentum, resulting in significant interaction with the in-cylinder flow field. The results show that injector inclination influences jet impingement behavior, wall-guided flow development, and subsequent vortex evolution, while injector rotation modifies the interaction between the jet trajectory and in-cylinder swirl motion, affecting aerodynamic shear and flow-field complexity. The resulting mixture formation is evaluated through local air–fuel ratio distribution together with flow-field analysis and streamline evolution, demonstrating strong sensitivity to injector orientation and its coupling with in-cylinder aerodynamic structures. Quantitatively, injector orientation produces significant changes in the local air–fuel ratio distribution, with up to 25% reduction in the standard deviation of local air–fuel ratio for inclination variations and up to 35% for azimuthal variations between the extreme configurations, indicating improved mixture uniformity. Configurations promoting earlier jet disruption and enhanced spatial dispersion achieve more homogeneous charge preparation, whereas stronger wall-guided jet attachment results in localized fuel-rich regions. The findings provide physical insight into the role of jet–wall interaction, aerodynamic shear, and vortex restructuring in governing hydrogen mixing processes. The simulation framework captures the relevant in-cylinder flow physics and provides trends consistent with available experimental observations in the literature, which report improved efficiency and reduced NOx emissions under enhanced mixture homogeneity conditions. Full article

Computational fluid dynamics (CFD)-driven optimization of engineering systems is often constrained by high computational cost, particularly when surrogate models must be constructed from limited simulation samples. Although surrogate-assisted multi-objective optimization can substantially reduce CFD evaluations, local prediction errors in decision-sensitive Pareto regions may alter feasibility classification and engineering recommendations near active constraints. To address this issue, this study proposes a Pareto-active-region-guided sequential surrogate modeling framework (PAR-SSM) for multi-objective optimization of liquid-cooled battery thermal management systems. Starting from 15 face-centered central composite design (FCCD) samples, the framework selectively introduces additional high-fidelity CFD evaluations into Pareto-active and constraint-sensitive regions, yielding a 21-sample refined surrogate model. Rather than uniformly improving global prediction accuracy, PAR-SSM directs the limited CFD budget toward regions where surrogate errors can directly influence engineering decisions. After model freezing, three independent Fluent cases were used exclusively for validation, yielding mean absolute deviations of 0.098 °C for maximum temperature and 0.341 °C for temperature difference, while also revealing residual feasibility risk near active constraint boundaries. Application to an autonomous underwater vehicle (AUV) battery module showed that the N = 3 configuration dominated the nominally constrained Pareto set and provided a favorable thermal–hydraulic trade-off under low auxiliary energy consumption. Overall, PAR-SSM provides a decision-oriented strategy for balancing computational cost and optimization credibility in CFD-intensive, constrained multi-objective design. Full article

The dipole antenna is one of the oldest and most widely used devices in electromagnetic engineering, yet the behavior of its near-field during emission remains only partially captured by classical models. In the source-free region surrounding the arms, the vacuum Maxwell–Heaviside equations provide an insufficient number of configurations to describe the transient through which a bound signal becomes a freely propagating wave. We revisit the model equations, introducing an extended formulation in which an auxiliary velocity field complements the electromagnetic fields. Similarly to plasma physics, the outgoing signal is treated as an electromagnetic fluid carrying a charge density. As the far field is concerned, the resulting system admits an exact family of spherical free-wave solutions that follow the rules of geometrical optics. The near-to-far field transition also acquires a concrete dynamical description, thanks to the introduction of the pseudocharge, which is a charge-like density identified with the divergence of the electric field. In addition, a pressure-like potential, vanishing in the far field, tracks the conversion between bound and radiating energy. The approach is illustrated on a standard dipole antenna through direct numerical simulation of the full coupled system. The results suggest a unified analytical and computational pathway for antenna modeling, with natural extensions to more complex geometries and other radiating devices. Full article

With the continuous expansion of deep-sea resource exploration, marine environmental monitoring, and underwater operations, Autonomous Underwater Vehicles (AUVs) have been increasingly widely applied. Aiming at the demand for high-performance main propulsion systems of Autonomous Underwater Vehicles (AUVs), this paper conducts research on the structural design and hydrodynamic performance of a 30 kW rim-driven thruster (RDT) and its coupling mechanism with AUVs. By combining computational fluid dynamics (CFD) simulations and experimental methods, the influence of the advance coefficient on the open-water performance of the thruster is revealed. An integrated coupling simulation model of the AUV and RDT is established to analyze the performance attenuation law of the thruster and the characteristics of the coupled flow field under wake flow conditions, and to clarify the two-way interaction mechanism between the thruster and AUV. Towing tank tests were carried out at sailing speeds ranging from 1 to 4 kn, which verifies the reliability of the numerical simulation model and the matching performance between the thruster and AUV. The results show that the open-water efficiency of the thruster reaches a peak value of 0.536 at the advance coefficient $\mathrm{J}=0.8$, which is close to the optimal efficiency range with good matching performance of the propulsion system Under wake flow conditions, the attenuation range of the thrust coefficient of the thruster is 12.45–16.53% with the increase in advance coefficient. The main reasons are the uneven inflow velocity and unstable flow field pressure distribution caused by the non-uniform wake flow at the AUV stern. At the ship speeds of 2 kn, 3 kn and 4 kn, the self-propulsion rotational speeds obtained from test fitting are in good agreement with the simulation results, with all relative errors less than 8%. This study provides a theoretical basis and technical reference for the engineering design of medium and high-power rim-driven thrusters as well as the matching optimization of AUV-thruster systems. Full article

In tubular ice machines, water flows gravitationally through tubes, while refrigerant flows through the shell side. The tube configuration and the water flow velocity are important parameters affecting the ice production rate. In this study, the flows in a 39 mm diameter tube and in an annular tube with a 39 mm outer diameter and a 10 mm inner diameter were investigated. The experiments were carried out for Computational Fluid Dynamic (CFD) model validation. The CFD simulation was performed for initial velocities ranging from 0.03 to 0.45 m/s. The results showed that the flow through the annular tube resulted in a lower ice thickness (δ) and ice growth rate (G), but a higher initial ice growth rate. This is because the annular tube has a higher heat transfer coefficient. G increases as the flow velocity decreases and decreases as time progresses. When the initial velocities exceeded the critical velocities of 0.40 and 0.35 m/s for the tube and the annular tube, respectively, the flow passages were filled with ice incompletely. For ice production, the flow velocity should be kept as low as possible. Annular tubes proved unsuitable for tubular ice machines. Full article

The propulsion performance and propeller design of ships have traditionally been evaluated mainly under calm-water conditions. However, under actual sea conditions, waves can increase added resistance, change the stern wake distribution, reduce propulsive efficiency, and affect cavitation behavior. This study evaluates the propulsion performance and designs a propeller for an 1800 TEU container ship under regular wave conditions using computational fluid dynamics. Resistance and self-propulsion simulations are conducted for eleven wavelength ratios in the range of $0.5\le \lambda /L_{PP}\le 2.0$, with a fixed wave steepness of $H/\lambda =0.01$. The results show that the required power increases significantly in the resonance wavelength range because of the combined effects of added resistance, wake variation, and reduced propulsive efficiency. The Brake Horsepower (BHP) transfer function obtained from the regular wave simulations is combined with representative sea-state spectra using the spectral method to estimate the Daily Fuel Oil Consumption (DFOC) under actual operating sea states. The total long term DFOC is estimated as 37.084 t/day. For the propeller design, the wake distribution at the propeller plane is analyzed at $\lambda /L_{PP}=1.1$, as a representative wave condition where the ship motion and propulsion performance variation become significant. The wake analysis shows that the instantaneous inflow changes considerably according to the wave phase, which can affect blade loading and cavitation. Based on this analysis, a new propeller geometry is designed with the cavitation performance as the primary consideration while also improving the propulsion performance. The designed propeller reduces the cavity volume over the selected wave phases and decreases the delivered power by approximately 2.1% in calm water and 3.4% in wave conditions. These results demonstrate the importance of considering wake variation and cavitation characteristics in practical propeller design under actual operating conditions. Full article

Doppler Light Detection and Ranging (LIDAR) systems and a mesoscale meteorological model coupled with computational fluid dynamics (CFD) for the monitoring of low-level wind and turbulence have been extensively applied for the Hong Kong International Airport. This study represents the first application in Hong Kong to apply such techniques for the exploration of providing meteorological support for the operation of Unmanned Aircraft Systems (UASs) in a sandbox project in Hong Kong. The flight route under consideration is between the western coast of Hong Kong Island and an outlying island called Lamma Island, with a sea channel in between. Based on the LIDAR observations in three different prevailing wind directions, low-level turbulence may arise from wind flow disruptions by natural terrain and human-made buildings. Simulations of the wind and turbulence are attempted using the GPU-based FastEddy, with the turbulent kinetic energy equation being used to output the eddy dissipation rate (EDR). Comparisons between observed and simulated fields showed broadly consistent patterns across wind speed, wind direction, and EDR. Quantitative validation yielded RMSE of 1.35 m/s for wind speed, 28.4° for wind direction, and 0.032 m²/s² for EDR, with corresponding R² values of 0.72, 0.48, and 0.07, respectively. However, point-to-point comparison as in the scatter plot of the two datasets is still challenging, due to low correlation for EDR. Nonetheless, FastEddy is found to shed preliminary insights to generate reasonable simulations of low-level winds and turbulence to support the operation of UASs for the cases under study. These findings should be considered preliminary and exploratory given the limited number of case studies analyzed. More cases would need to be studied to find out the performance of FastEddy in other meteorological conditions. Full article