Search Results (12,296)

Deep learning-based flow field prediction for microclimate pollutant dispersion represents an emerging and promising methodology, where effectively integrating meteorological, spatial, and temporal information remains a critical challenge. To address this, we propose a novel non-intrusive reduced-order model (ROM) that synergizes a Dilated Convolutional Autoencoder (DCAE) with pre-trained large language models (LLMs). The DCAE, leveraging nonlinear mapping, was employed for extracting low-dimensional spatiotemporal flow field features. These features were then combined with textual prototypes via text embedding to enable few-shot inference using the LLM-based flow field prediction method. To optimize the utilization of pre-trained LLMs, we designed a specialized textual description template tailored for pollutant dispersion data, which enhances the contextual input of meteorological conditions to guide model predictions. Experimental validation through three-dimensional urban canyon simulations conclusively demonstrated the efficacy of the convolutional autoencoder and LLM-based framework in predicting pollutant dispersion flow fields. The proposed method exhibits remarkable transfer learning capabilities across varying street canyon geometries and meteorological conditions while significantly representing a 9.85× acceleration in prediction compared to Computational Fluid Dynamics (CFD). Full article

Piping systems must cope with the internal pressure of the fluid they carry. They are almost always well-designed for withstanding steady-flow pressures, but allowing for unsteady-flow pressures and for fatigue can be more challenging. Positive and negative gauge pressures induced by waterhammer waves are possibly the most extreme that piping is likely to face during its lifetime. It is widely accepted that this should be addressed by analyses during the design phase, but this is usually done under the assumption that consequential (non-hoop) structural movements do not affect the calculated pressures. However, the calculated pressures are used as input to the structural design. Commonly, attention focusses on static predictions of induced hoop stresses and on the risk of buckling, but attention sometimes has to be paid to dynamic responses. In these cases, the complexity of the structural analysis depends on the assumed degrees of freedom of possible movement, so it is desirable to avoid including unnecessary detail. The title of this paper poses one question that is frequently asked. However, the correct answer is not always obtained, partly because highly misleading answers were published in one early paper, the rebuttals to which were much less widely reported. The current contribution attempts to answer the question for both fixed and movable bends. Attention is paid to pressure transients arriving at bends from remote locations and potentially inducing pipe movement. Then, the opposite effect is considered, namely the generation of pressure transients by structural movements. To avoid distorting the picture by combining this with nominally unrelated causes, strong simplifications are made—e.g., disregarding all forms of energy dissipation. Full article

Liquefied natural gas (LNG) sloshing occurs during marine transportation and storage due to vessel motion or external disturbances, leading to complex fluid–structure interactions within the containment system. This study employs OpenFOAM to develop a numerical model of LNG sloshing. The model solves the incompressible multiphase Navier–Stokes equations and utilizes the Volume of Fluid (VOF) method to capture the dynamic behavior of gas–liquid interface. The numerical model was validated against experimental data. Based on this model, the key hydrodynamic characteristics are investigated for LNG sloshing, including nonlinear free surface, transient pressure distribution on the tank walls due to liquid impact, and energy dissipation mechanisms. By varying excitation frequencies, amplitudes, and the configuration of internal components such as baffles or anti-sloshing devices, the study explores the sloshing response and effective control strategies. The results indicate that appropriately designed baffles can significantly mitigate sloshing-induced impact pressures on tank walls and enhance system stability. In the future, this study could extend to multi-layer fluids, multi-degree-of-freedom motions, and simulations under more complex real-world conditions. Full article

Previous numerical simulations of polymer injectors often rely on fixed-viscosity models, which fail to accurately capture the severe shear degradation of non-Newtonian fluids under high-shear throttling conditions. To address this limitation and enhance polymer flooding efficiency, this study proposes an improved Carreau–Yasuda viscosity constitutive model to precisely simulate the flow behavior of polyacrylamide (HPAM) solutions. A comprehensive computational fluid dynamics (CFD) model was developed and validated, showing a viscosity prediction error of less than 8.6% across a wide shear rate range (0.1–10,000 s⁻¹). Based on this dynamic rheological model, the internal flow channel of the injector was optimized, resulting in a novel spindle-type throttling unit. Simulation and field validation results demonstrate that the optimized structure achieves a significant pressure drop of 6.03 MPa at an injection flow rate of 96 m³/d—representing a 65% improvement over traditional designs—while successfully maintaining a viscosity retention rate above 85%. This research overcomes the traditional design conflict between high pressure reduction and viscosity preservation, providing an accurate numerical framework and practical guidance for engineering high-flow, robust-throttling polymer injectors. Full article

This study presents a mathematical model of the dynamics of a cavitation bubble oscillating near a rigid wall under an electromagnetic field. The model utilizes a modified Keller–Miksis equation incorporating the compressibility effects of the surrounding Newtonian conducting fluid. The rigid boundary’s effects, modeled using the image method, contributed to an additional pressure, which altered the cavitation bubble’s radial dynamics. Electromagnetic effects were incorporated through the Maxwell stresses induced by an external electric field, electrostatic pressure from surface charge accumulated at the bubble’s interface, and magnetic damping arising from the electric currents induced in the conducting fluid. The resulting nonlinear ordinary differential equation was solved using a fourth- and fifth-order Runge–Kutta scheme. Validation against previous theoretical and experimental studies showed good agreement, confirming the model’s reliability. A parametric analysis showed that the bubble–wall distance, electric field intensity, magnetic field strength, and surface charge magnitude considerably influence the behaviors of oscillating bubbles. Electric fields and surface charges promote bubble expansion, whereas magnetic fields and nearby surfaces restrict its size, thereby influencing its collapse. These behaviors can be attributed to the governing equation and the magnitude of its nonlinear terms. The proposed model provides a consistent mathematical framework for analyzing the electro-magnetohydrodynamic cavitation phenomena near rigid boundaries. Full article

Urban green spaces (UGSs) provide essential ecological services but also accumulate heavy metals (HMs) in their soils, posing a paradoxical health risk through dermal exposure. Traditional risk assessments, based solely on total HM concentrations, often overestimate threats by ignoring bioavailability (the fraction actually absorbed by organisms) and dynamic skin microenvironment factors. This review synthesizes recent advances to propose a precision assessment framework that integrates bioavailability. The framework advocates for the incorporation of bioaccessibility (the fraction of pollutants dissolved in body fluids)-driven exposure metrics (e.g., physiologically based extraction tests), mechanistic dermal permeation models (e.g., Franz diffusion cells, 3D skin constructs), and population-specific susceptibility factors (e.g., children, individuals with compromised skin). We elucidate how soil properties (pH, organic matter) and metal speciation (e.g., Cr(III)/Cr(VI)) modulate cutaneous uptake, and detail toxicological mechanisms including oxidative stress, ferroptosis/cuproptosis, immunotoxicity, and pigmentation disorders. Case studies reveal heterogeneous HM hotspots in high-traffic and densely populated areas, while in vitro–in vivo extrapolation highlights the potential for misestimation in traditional models. Consequently, we discuss the limitations and future directions of this framework, aiming to shift UGS risk management from over-conservative assessment to bioavailability-based precision governance, thereby supporting the health security of sustainable urban habitats. Full article

The Hybrid Barjeel of the ORA House, designed for the Solar Decathlon Middle East 2018 in Dubai, is a contemporary reinterpretation of the traditional windcatcher—Barjeel, integrating vernacular cooling principles with modern mechanical systems to enable passive precooling of intake air in hot, arid climates. This study aims to evaluate the thermal performance of several horizontal windcatcher configurations developed during the ORA House design process and compare them with the conventional vertical windcatcher typology. Numerical simulations were performed using Computational Fluid Dynamics to analyse airflow behaviour and thermal characteristics—factors that directly influence cooling loads and indoor air quality, and ultimately contribute to carbon savings and cost efficiency. The results show that the horizontally integrated windcatcher effectively reduces the temperature of the supply air, demonstrating its viability as a passive precooling strategy; however, the performance improvement relative to the vertical configuration is modest. Overall, the findings suggest that horizontal windcatcher designs offer an architecturally flexible alternative for contemporary residential buildings, enabling better morphological integration without compromising functional potential. Full article

A cross-construction method is proposed to establish a wind turbine wake dataset with significantly reduced computational fluid dynamics (CFD) costs. This method involves adjusting one operating parameter, such as the tip speed ratio (TSR), while maintaining the others at their optimal values. This procedure is repeated across another parameter (inflow velocity) to generate a sparse but informative dataset. CFD simulations were performed using large eddy simulation (LES) coupled with an actuator line model (ALM) to generate data. A pre-training and fine-tuning network based on error classification (PFNEC) was developed, achieving high prediction accuracy with coefficients of determination of 0.9750 and 0.9851 for two validation conditions. Two models based on a softmax function and a residual block were designed, and they achieved the best performance, with coefficients of determination of 0.9921 and 0.9891 under different conditions. The Fourier embedding was applied to enhance input features of neural networks. Four samples added to the original dataset improved the prediction accuracy for extreme operating conditions, from coefficient of determination values of 0.7143 and 0.7034 to 0.9939 and 0.9886 with Fourier embedding. This cross-construction method can significantly reduce the cost of dataset establishment. The models exhibited reliable generalization and prediction accuracy. Full article

This study presents the development of a three-dimensional (3D) filament assembly model for predicting the air permeability of woven fabrics composed of spun yarns. To address the limitations of conventional single-line yarn models, the proposed framework incorporates fiber-level geometric representations using non-uniform rational B-splines (NURBS) and simulates multiple weave patterns—including plain, basket, twill, and rib—under various set density configurations. Each yarn was modeled with accurate filament distribution and cross-sectional layering, enabling the construction of realistic unit-cell-based CAD geometries. Computational fluid dynamics (CFD) simulations were performed using the k-ε turbulence model in SolidWorks Flow Simulation and validated against experimental measurements conducted under ISO 9237:1995 conditions. The filament assembly model achieved high predictive accuracy, exhibiting a lower of percentage prediction errors than the single-line yarn path model, thereby more effectively capturing airflow behavior through inter-yarn and intra-yarn pores. These findings highlight the capability of integrated CAD/CFD methodologies for virtual prototyping of breathable textiles and provide a robust foundation for high-precision performance prediction in functional and technical fabric design. Full article

The choroid plexus (CP) has traditionally been regarded as a cerebrospinal fluid-producing structure; however, increasing evidence indicates that it functions as a dynamic regulatory interface involved in immune surveillance, metabolic homeostasis, and brain clearance. Neuroimaging studies consistently report CP enlargement across aging and diverse neurological and neuropsychiatric disorders, yet the underlying cellular mechanisms remain poorly integrated. In this review, we synthesize morphological, molecular, and imaging evidence to propose a sequential degenerative model of the CP epithelium. This model comprises: (1) regulated epithelial cell loss via apical extrusion, (2) compensatory hypertrophy of residual cells, (3) mitochondrial remodeling with oncocytic-like change, and (4) progressive blood–cerebrospinal fluid barrier dysfunction. At the molecular level, alterations in epithelial adhesion systems—particularly SPINT1-mediated protease regulation and E-cadherin–based adherens junction stability—may initiate epithelial instability. Hypertrophic epithelial cells exhibit increased mitochondrial burden, reflected by Tom20 expression, which may initially support metabolic adaptation but ultimately contribute to oxidative stress and functional decline. At the macroscopic level, the cumulative effects of cell loss, hypertrophy, and mitochondrial remodeling likely underlie CP enlargement detectable by magnetic resonance imaging. This framework positions CP enlargement as an imaging-visible manifestation of epithelial stress and provides a structural–molecular basis for interpreting CP alterations in brain aging and neurodegenerative disorders. Full article

Braking drag is a typical fault of brake systems, and clarifying the correlation mechanism between vehicular working conditions and braking drag is critical for brake design improvement. Based on fluid mechanics and contact mechanics, this paper establishes a dynamic model for braking drag mechanism analysis, combined with the return mechanism and force-bearing state of brake pistons. Firstly, a commercial vehicle brake system dynamic model is built via Amesim, and piston sliding resistance is identified as the key factor leading to insufficient piston retraction through user operational data analysis. Subsequently, a fluid-structure interaction-based dynamic coupling model of drag mechanism is established, typical braking conditions are extracted via K-means clustering, and piston friction, displacement and drag torque are solved with the system model outputs as inputs. Finally, drag-prone working conditions are determined, and the disc brake drag mechanism is revealed. The results show that piston sliding resistance is the primary factor in braking drag; medium-low speed prolonged braking has high drag susceptibility; and the seal contact area is in mixed lubrication, with contact pressure and friction dominated by asperity shear stress. This work enables accurate identification of drag-prone conditions, providing guidance for brake system optimization. Full article

Gas–liquid cyclone separators are an efficient and emerging method for air removal in hydraulic systems, yet often suffer from excessive pressure loss. A novel contracting inlet guiding structure is proposed to minimize hydraulic losses. This study adopts a comprehensive methodology combining theoretical modeling, computational fluid dynamics (CFD) using the Reynolds Stress Model (RSM), and experimental validation. A theoretical pressure-loss model incorporating the diminishing-returns effect of the contraction angle was established. Simulations revealed that increasing the contraction angle reduces energy dissipation by improving the uniformity of the tangential-velocity field. Based on the balance between pressure-loss reduction and degassing potential, a contraction angle of 11° was identified as the optimal design and experimental tests on a prototype confirmed the validity of the numerical model. The results demonstrate that, compared to the conventional straight tangential inlet, the optimized inlet reduces the pressure loss by approximately 30% under rated conditions. The experimental–numerical discrepancy decreases significantly with flow rate, achieving a relative error of approximate 10% at the design flow rate. These findings provide a theoretical basis and practical guidance for the low-energy design of hydraulic cyclone separators. Full article

Shale oil reservoirs are characterized by ultra-low matrix permeability. After large-scale hydraulic fracturing is applied to horizontal wells, fluid transport becomes highly complex, posing major challenges for accurately predicting production performance. In this study, a coupled multi-mechanism numerical model is developed for shale oil reservoirs with complex fracture networks. Using the Embedded Discrete Fracture Model (EDFM), the mass transport between the fracture and matrix and within the hydraulic fracture network can be accurately quantified. Based on core analysis and fluid experimental data, the dynamic evolution of rock and fluid properties is characterized by incorporating nanopore confinement effects, stress sensitivity, and threshold pressure gradient behavior. Numerical simulations are then conducted to investigate the impacts of multiple mechanisms, including nanopore confinement effects, stress sensitivity, and threshold pressure gradient, as well as their coupling effects on shale oil production. A field application is carried out using Well H1 in the Qingcheng shale oil reservoir. Simulation results indicate that nanopore confinement reduces bubble-point pressure, leading to a 3.60% increase in cumulative oil production and a noticeable reduction in the producing gas–oil ratio. Stress sensitivity causes a 2.68% decrease in cumulative oil production and suppresses gas production. The threshold pressure gradient exerts the strongest negative impact, resulting in an 8.01% reduction in cumulative oil production and a slight decrease in gas–oil ratio. When all mechanisms are simultaneously considered, strong nonlinear interactions emerge, yielding a 7.09% reduction in cumulative oil production—significantly different from the linear superposition of individual effects. These results demonstrate the necessity of accounting for multi-mechanism coupling to achieve reliable production forecasting in fractured shale oil reservoirs. Full article

In this work, we present the scale-up of a batch anaerobic fermentation system for the production of succinic acid from glycerol using A. succinogenes. The system has been successfully scaled up from an initial bioreactor working volume of 1 L (laboratory scale) to a working volume of 100 L (pilot scale). At the same time, we have developed a hybrid model, combining the intrinsic kinetics of the microbial growth, with a computational fluid dynamics model (CFD) of the bioreactor. The proposed model is able to predict the productivity drop, usually observed while scaling up a bioprocess. In our process, this is a result of the limitations on the mass transfer of CO₂ between the gas and the liquid phase of the system. The model is successfully used to predict the amount of aeration needed in order to achieve increased succinic acid productivity. Using the model, the final succinic acid increased by 4.3%, and the succinic acid productivity increased by 8.5%, while the fermentation by-products decreased by approxiamtely 3% each. Full article

This study experimentally investigates the settling behavior of bent (V-shaped and curved) and straight rods in a quiescent fluid at low and finite Reynolds numbers ($\mathrm{Re}<3$). The impact of the rod morphology on the terminal settling velocity and drag coefficient was examined, with a particular focus on V-shaped rods compared to straight rods of the same dimensions (diameter and length) and curved rods of the same dimensions and projected area. The results show that V-shaped rods consistently settle faster than straight rods, with velocity differences influenced by the bend angle. This velocity difference reaches a maximum of 57% for a V-shaped rod with a diameter of 0.50 mm, an aspect ratio of 90, and a bend angle of 45 degrees. When compared to curved rods, V-shaped rods exhibit slightly higher terminal velocities, with a maximum difference of 4% in this study, attributed to differences in mean inclination angles. Furthermore, the drag coefficient trends reflect the interplay between the settling velocity and projected area changes with the rod geometry. A new semi-empirical model with an RMS error of 7.1% was also developed to predict the drag coefficients and terminal velocities of straight and bent rods within the ranges studied. These findings and the model presented underscore the significance of the fibre shape in accurately predicting settling dynamics, with implications for atmospheric transport modeling and industrial applications involving fibrous particles. Full article