Search Results (6,198)

We present a CFD-driven surrogate modeling framework that integrates a Convolutional Autoencoder (CAE) with a Deep Neural Network (DNN) for the rapid prediction of urban wind environments and their subsequent use in UAV trajectory planning. A Reynolds-Averaged Navier–Stokes (RANS) CFD database is generated, parameterized by boundary-condition descriptors, to train the surrogate for velocity magnitude and turbulent kinetic energy (TKE). The CAE compresses horizontal flow fields into a low-dimensional latent space, providing an efficient representation of complex flow structures. The DNN establishes a mapping from input descriptors to the latent space, and flow reconstructions are obtained through the frozen decoder. Validation against CFD demonstrates that the surrogate captures velocity gradients and TKE distributions with mean absolute errors below 1% in most of the domain, while residual discrepancies remain confined to near-wall regions. The approach yields a computational speed-up of approximately 4000× relative to CFD, enabling deployment on embedded or edge hardware. For path planning, the domain is discretized as a k-Non-Aligned Nearest Neighbors (k-NANN) graph, and an A* search algorithm incorporates heading constraints and surrogate-based TKE thresholds. The integrated pipeline produces turbulence-aware, dynamically feasible trajectories, advancing the integration of high-fidelity flow predictions into urban air mobility decision frameworks. Full article

The study of the destruction mechanisms of mineral component particles during processing in grinding units is a relevant scientific problem that requires further theoretical and experimental solutions. This work is dedicated to determining the kinetic characteristics of ferromagnetic bodies moving under the influence of an electromagnetic field within a vortex mill. Dependencies of the velocity of these bodies on the radial coordinate for various values of magnetic induction and its gradient were obtained, establishing that velocities can reach approximately 50 m/s. A model for the disintegration of Portland cement particles, caused by their interaction during mechanical processing in a vortex mill, has been developed. It is shown that the average number of disintegration events for the predominant portion of the studied particles is two, which is significantly lower than the total number of collisions. An analysis of the key factors influencing the intensity and nature of particle destruction was conducted, including the magnitude of magnetic induction, the switching frequency of electromagnets, and the magnetic susceptibility of the processed materials. Based on a statistical analysis of the particle size distributions of the mineral raw material after dispersion, a principle for dividing the space within the working volume of the unit into functional zones was formulated: (1) a zone of mixing, grinding, and particle activation (at ferromagnetic element speeds of 0–12 m/s); (2) a zone of intensive grinding and particle activation (with speeds of 12–50 m/s). Full article

The hydrodynamic performance of a rudder behind a propeller is critical for determining vessel maneuvering stability. During navigation, the coupled effects of the oblique flow angle (β) and the rudder angle (δ) significantly alter the wake velocity field and vortex patterns aft of the rudder. However, the synergistic control mechanism of these two variables requires further quantitative investigation. This study employs the RANS method with the SST k-ε turbulence model to numerically simulate flow under advance coefficients (J) ranging from 0.3 to 0.9, oblique flow angles (β) from 0° to 15°, and rudder angles (δ) from 0° to 35°. Hydrodynamic coefficients, including the lift coefficient, drag coefficient, and lift-to-drag ratio, were calculated for the rudder. The evolution of the horizontal velocity and vortex fields was captured, with the model validated through localized flow field visualization. The results reveal that when β ≤ 3°, δ is the dominant factor influencing rudder hydrodynamics. Conversely, when β ≥ 9°, β becomes the primary regulating factor. The coupling effect induces significant asymmetry in the velocity distribution across the rudder surfaces and pronounced flow separation on the windward side, generating a complex vortex system (including primary and secondary vortices) on the leeward side. This research elucidates the coupled control mechanism of oblique flow and rudder angle, providing insights for enhancing steering margins and a quantitative foundation for optimizing rudder profiles in challenging sea environments characterized by high oblique flow and large rudder angles. Full article

In seismic data processing, noise not only affects velocity analysis and seismic migration, but also causes potential risks in post-stack processing because of the artifacts. The singular value decomposition (SVD) method based on the time domain and the frequency domain is effective for noise suppression, but it is very sensitive to singular value selection. This paper proposes a method of adaptive SVD denoising in both time and frequency domains (ASTF), with three steps. Firstly, two Hankel matrices are constructed in the time domain and frequency domain, respectively. Secondly, the parameters of the reconstruction matrix are adaptively selected based on the singular value second-order difference spectrum. Finally, the weights of these two matrices are learned through ternary search. Experiments were carried out on synthetic data and field data to prove the effectiveness of ASTF. The results show that this method can effectively suppress noise. Full article

A sediment suspension model is established to predict the sediment movement beneath asymmetric waves, in which the bottom boundary condition for the sediment concentration equation is specified by means of pickup function parameterized by a modified model of the bottom shear stress. The modified model of the bottom shear stress involves velocity and acceleration processes as well as the phase difference between the near-bed orbital velocity and bottom shear stress. Moreover, the phase difference is not a constant in one wave cycle but different in the durations of positive and negative velocities. And the phase differences are parameterized into a function that is dependent on the degree of wave asymmetry based on plenty of numerical data of the boundary layer obtained by large eddy simulation (LES) of oscillatory boundary layer flows. The bottom shear stress calculated by the modified model is compared with those obtained from both the experiments and the LES model, demonstrating that the modified model can capture the unsteady characteristics of the bottom shear stress beneath asymmetric waves accurately. Then, the proposed sediment suspension model is coupled with a numerical wave flume so as to obtain the progressive wave fields and the suspended sediment movement. The velocity and sediment concentration of both reduced- and large-scale hydrodynamic conditions calculated by the coupled model are compared with experimental data with a good agreement, suggesting reliability of the proposed model to predict sediment transport induced by asymmetric waves. Full article

Closed-loop geothermal systems (CLGSs) avoid groundwater production and offer stable deep heat supply, but their long-term performance hinges on reliable coupling between the wellbore, the near-well interface and the surrounding formation. Using the D22 well in the Xiongan New Area (deep carbonate reservoir), we built a three-domain thermo-hydraulic framework that updates CO₂ properties with temperature and pressure and explicitly accounts for wellbore-formation thermal resistance. Two geometries (U-tube and single-well coaxial) and two working fluids (CO₂ and water) were compared and optimized under field constraints. With the coaxial configuration, CO₂ delivers an average thermal power of 186.3 kW, exceeding that of water by 44.9%, while the fraction of wellbore heat loss drops by 3–5%. Under field-matched conditions, the predicted outlet temperature (76.8 °C) agrees with the measured value (77.2 °C) within 0.52%, confirming the value of field calibration for parameter transferability. Long-term simulations indicate that after 30 years of continuous operation the outlet temperature decline remains <8 °C for CO₂, outperforming water and implying better reservoir utilization and supply stability. Sensitivity and Pareto analyses identify a practical operating window, i.e., flow velocity of 0.9–1.1 m s⁻¹ and depth of 3000–3500 m, favoring the single-well coaxial + CO₂ scheme. These results show how field-calibrated modeling narrows uncertainty and yields implementable guidance on geometry, operating conditions, and wellbore insulation strategy. This study provides quantitative evidence that CO₂-CLGSs in deep carbonate formations can simultaneously increase thermal output and limit long-term decline, supporting near-term engineering deployment. Full article

Chemotherapy-induced peripheral neuropathy (CIPN) impairs quality of life and may result in discontinuation of anti-neoplastic therapy. In older patients, CIPN is associated with reduced executive function, more severe pain, comorbidities and polypharmacy. The use of magnetic fields to modulate central and peripheral neurons may offer some benefit for relieving neuropathic pain, with few adverse effects. The evidence of the benefits of using transcranial magnetic stimulation (TMS) or peripheral magnetic stimulation (PMS) in patients with CIPN is evaluated in this narrative review. Improved patient-reported outcomes and more rapid nerve conduction velocities in preliminary trials suggest efficacy in patients with CIPN. The potential for additional, broader applications in CIPN includes biomarkers of progression to chronic neuropathic pain, opioid-sparing benefits, and mitigating associated depression and anxiety. Because magnetic stimulation (MS) is relatively resource intense and time consuming, requiring multiple sessions of therapy, its availability is still limited, and multi-center trials are challenging. Further research with sham-controlled clinical trials, using standardized MS techniques and outcome assessments are needed. Full article

To investigate the flow-field characteristics of a submerged pre-mixed abrasive water jet impinging on a wall, a physical model of the conical–cylindrical nozzle and computation domain of a submerged pre-mixed abrasive-water-jet flow field were established. Based on the software of FLUENT 2022R2, numerical simulation of the solid–liquid two-phase flow characteristics of the submerged pre-mixed abrasive water jet impinging on a wall was conducted using the DPM particle trajectory model and the realizable $k–\epsilon$ turbulence model. The simulation results indicate that a “water cushion layer” forms when the submerged pre-mixed abrasive water jet impinges on a wall. Tilting the nozzle appropriately facilitates the rapid dispersion of water and abrasive particles, which is beneficial for cutting. The axial-jet velocity increases rapidly in the convergent section of the nozzle, continues to accelerate over a certain distance after entering the cylindrical section, reaches its maximum value inside the nozzle, and then decelerates to a steady value before exiting the nozzle. In addition, the standoff distance has minimal impact on the flow-field characteristic inside the nozzle. When impinging on a wall surface, rapid decay of axial-jet velocity generates significant stagnation pressure. The stagnation pressure decreases with increasing standoff distance for different standoff-distance models. Considering the effects of standoff distance on jet velocity and abrasive particle dynamics, a standoff distance of 5 mm is determined to be optimal for submerged pre-mixed abrasive-water-jet pipe-cutting operations. When the submergence depth is less than 100 m, its effect on the flow-field characteristics of a submerged pre-mixed abrasive water jet impinging on a wall surface remains minimal. For underwater oil pipelines operating at depths not exceeding 100 m, the influence of submergence depth can be disregarded during cutting operations. Full article

There have been many attempts to model the flow of vehicular traffic in analogy to the flow of fluids. Given the evident change in distance between vehicles driving in platoons, the compressibility of traffic flow is inferred and, considering the reaction time-scales of the driver (human or autonomous), it is argued that this compressibility is increased as relative velocities increase—giving the lag in imposed redirection by the driver and the controller units a higher relative importance. Therefore, a supersonic compressible flow field has been opted for as the most analogous base flow. On this point, added to by the overall extreme similarities of the two above-mentioned flows, the non-dimensional group of the traffic Mach number M_T has been defined in the present research, providing the possibility of calculating a suggested flow field and its corresponding shockwave systems, for any given obstacle ahead of the traffic flow. This suggested flow field is then taken as the basis to obtain trajectories designed for avoiding collision with the obstacle, and in compliance with the physics of the underlying analogous fluid flow phenomena, namely the internal supersonic compressible flow around a double wedge. It should be noted that herein we do not model the traffic flow but propose these trajectories for more optimal collision avoidance, and therefore the above-mentioned similarities (explained in detail in the manuscript) suffice, without the need to rely on full analogies between the two flows. The manuscript further analyzes the applicability of the proposed analogy in the path-planning process for an autonomous passenger vehicle, through dynamics and control of a full-planar vehicle model with an autonomous path-tracking controller. Simulations are performed using realistic vehicle parameters and the results show that the fluid flow analogy is compatible with the vehicle dynamics, as it is able to follow the target path generated by fluid flow calculations with minor deviations. Simulation results demonstrate that the proposed method produces smooth and dynamically consistent trajectories that remain stable under varying traffic scenarios. The controller achieves accurate path tracking and rapid convergence, confirming the feasibility of the fluid-flow analogy for real-time vehicle control. Full article

In gas reservoirs, high gas velocity causes significant inertial effects, leading to a nonlinear relationship between pressure gradient and velocity, especially near wellbores or fractures. In such cases, Darcy’s law is inadequate, and the Forchheimer equation is commonly used to model nonlinear flow behavior. Although the Forchheimer equation improves simulation accuracy for high-velocity flow in porous media, incorporating it into conventional numerical simulations greatly increases computational time, as nonlinear flow equations must be solved over the entire reservoir. This difficulty is exacerbated in heterogeneous fractured reservoirs, where complex fracture–matrix interactions and localized high-velocity flow complicate solving nonlinear equations. To address this, this work proposes a fast numerical simulation method based on diffusive time of flight (DTOF). By using DTOF as a spatial coordinate, the original three-dimensional flow equations incorporating the Forchheimer equation are reduced to a one-dimensional form, enhancing computational efficiency. DTOF represents the diffusive time for a pressure disturbance from a well to reach a specific reservoir location and can be efficiently computed by solving the Eikonal equation via the fast marching method (FMM). Once the DTOF field is obtained, the three-dimensional problem is transformed into a one-dimensional problem. This dimensionality reduction enables fast and reliable modeling of nonlinear high-velocity gas transport in complex reservoirs. The proposed method’s results show good agreement with those from COMSOL Multiphysics, confirming its accuracy in capturing nonlinear gas flow behavior. Full article

This study aims to qualitatively and quantitatively assess the ability of the flow solver “reactingFoam” of the open-source OpenFOAM software v.2506 for a control-volume-based computational fluid dynamics (CFD) solver in treating the reacting flow problem of a popular benchmarking bluff-body-stabilized turbulent diffusion (non-premixed) flame, that is, the HM1 flame. The HM1 flame has a fuel stream composed of 50% hydrogen (H₂) and 50% methane (CH₄) by mole. Thus, the acronym “HM1” stands for “hydrogen–methane, with level 1 of jet speed”. This fuel stream is surrounded by a coflow of oxidizing air jet. This flame was studied experimentally at the University of Sydney. A measurement dataset of flow and chemical fields was compiled and made available freely for validating relevant computational models. We simulate the HM1 flame using the reactingFoam solver and report here various comparisons between the simulation results and the experimental results to aid in judging the feasibility of this open-source CFD solver. The computational modeling was conducted using the specialized wedge geometry, suitable for axisymmetric problems. The turbulence–chemistry interaction (TCI) was based on the Chalmers’ partially stirred reactor (CPaSR) model. The two-equation k-epsilon framework is used in modeling the small eddy scales. The four-step Jones-Lindstedt (JL) reaction mechanism is used to describe the chemical kinetics. Two meshes (coarse and fine) were attempted, and a converged (mesh-independent) solution was nearly attained. Overall, we notice good agreement with the experimental data in terms of resolved profiles of the axial velocity, mass fractions, and temperature. For either mesh resolution, the overall deviation between the computational results and the experimental results is approximately 8% (mean absolute deviation) and 10% (root mean square deviation). These are favorably low. The current study, and the presented details about the reactingFoam solver and its implementation, can be viewed as a good case study in CFD modeling of reacting flows. In addition, the information we provide about the measurement dataset, the emphasized recirculation zone, the entrainment phenomena, and the irregularity in the radial velocity can help other researchers who may use the same HM1 data. Full article

The purpose of this study is to develop a multiphysical model of agglomeration of low-grade phosphorites with the addition of phosphate-siliceous shales and oil sludge. To achieve these tasks, a numerical approach was used in the COMSOL Multiphysics environment, based on solving the related problems of heat transfer and hydrodynamics during heat treatment of the material. A laboratory vertical tubular furnace made of heat-resistant quartz glass with electric heating was used to study the effect of the temperature field and the velocity of gases on the degree of sintering and the dynamics of phosphorous agglomerate formation under various technological conditions. It has been established that the optimal temperature for the agglomeration process is a layer temperature of 950–1000 °C at a gas flow rate of 1.5–2 m/s, which ensures the formation of durable granules and minimizes sintering heterogeneity. The maximum sintering layer height of the test charge reaches 210–230 mm at pressures of 0.015–0.027 MPa. A comparison of the numerical simulation results with experimental data showed a good agreement, which confirms the practical significance of the proposed model for the design and optimization of industrial processes of agglomeration of phosphorous raw materials. Modern physical and chemical analyses have established the phase, microstructural, and element-by-element characteristics of the studied phosphate-siliceous shale and the product of agglomeration firing. The results of modeling the hydrodynamics of the charge agglomeration process can be recommended to increase the efficiency of processing phosphate-containing waste and reduce energy consumption. Full article

This study presents a comparative performance modeling and optimization framework for a 5 kWp rooftop photovoltaic (PV) system in Qatar, using two widely adopted simulation tools, PVsyst and the System Advisor Model (SAM). The research addresses a key limitation in existing PV modeling practice: the restricted capability of standard software to represent site-specific soiling and dynamic albedo effects under arid climatic conditions. To overcome these limitations, the Humboldt State University (HSU) soiling model was calibrated using field measurements from a DustIQ sensor, and its parameters, rainfall cleaning threshold and particulate deposition velocity were optimized through a Differential Evolution algorithm. Additionally, the study utilized dynamic albedo inputs to better account for ground-reflectance effects in energy yield simulations. The optimized approach reduced the root mean square error (RMSE) of predicted soiling ratios from 7.30 to 1.93 and improved the agreement between simulated and measured monthly energy yields for 2024, achieving normalized RMSE values of 4.66% in SAM and 4.86% in PVsyst. The findings demonstrate that coupling data-driven soiling optimization with refined albedo representation modernizes the predictive capabilities of PVsyst and SAM, yielding more reliable performance forecasts. This methodological advancement supports better-informed design and operation of rooftop PV systems in desert environments where soiling and reflectivity effects are pronounced. Full article

Ice accretion alters the airfoil profile of the unmanned aerial vehicle (UAV), degrading the aerodynamic performance and potentially triggering safety incidents. The computation of droplet impingement characteristics is the primary task for ice accretion analysis and the design of anti-icing/de-icing systems for UAVs. To address the disadvantages of the conventional Eulerian method and the Lagrangian method, a streamline-based Eulerian method is established to obtain the droplet impingement characteristics. It only solves the momentum equation to derive the velocity field, eliminating the computational load of the droplet continuity equation. Droplet streamlines are generated via backward integration in the droplet velocity field, allowing impingement characteristics to be calculated. In this scheme, the droplet collection efficiency is computed without the predetermination of droplet release locations or tracking a large number of droplet trajectories. The proposed method is applied to obtain the droplet collection efficiencies in the cases of an NACA0012 airfoil, a two-dimensional (2D) cylinder, an MS (1)-0317 airfoil, and an RG-15 airfoil. The results show good agreement with the data in the literature; therefore, the feasibility and effectiveness of this streamline-based Eulerian method are confirmed. This work can provide a reference for ice accretion analysis and anti-icing/de-icing system design for UAVs. Full article

Cancers are diseases described by the irregular spread of cells that have developed invasive features, enabling them to invade adjacent tissues. The specific diagnosis and effective management of oncological treatments depend on the timely detection of circulating tumor cells (CTCs) in a patient’s bloodstream. One of the most promising approaches to CTC separation from blood fractions involves the dielectrophoresis (DEP) technique. This research presents a new DEP-based bionic system designed for MDA-MB-231 breast cancer cell isolation from white blood cell (WBC) subtypes with a viable approach to cell viability. This work leverages the principle that every cell type possesses a unique dielectric fingerprint. This dielectrophoresis microfluidic device is designed to act as a scanner, reading these fingerprints to achieve a continuous, label-free separation of cancer cells from blood components with a high efficiency. In the proposed system that consists of three different stages, the first stage allows for separating B-lymphocytes and Monocytes from Granulocytes and MDA-MB-231 cells. The separation of B-lymphocytes from Monocytes occurs in the second step, while the last step concerns the separation of Granulocytes and MDA-MB-231 cells. In the analysis, x-y graphs of the electric potentials, velocity fields, pressure distributions, and cellular DEP forces applied to the cells, as well as the resulting particle paths, are provided. The model predicts that the system operates with a separation efficiency of nearly 92%. This work focuses on an investigation of the impact of electrode potentials, the velocity of cells, the number of electrodes, the width of the channel, and the output angles on enhancing the separation efficiency of particles. Full article