Search Results (357)

Fracture size governs fluid mobility in shale, yet its direct quantification remains challenging. Nuclear Magnetic Resonance (NMR) transverse relaxation time (T₂) offers a unique, non-destructive probe of fracture size distributions; however, a physically grounded conversion from transverse relaxation time to pore radius r (T₂−r) is essential to translate NMR signals into quantitative geometric constraints on fluid mobility. This study introduces a capillary-constrained experimental method for T₂−r transformation into shale fractures. The workflow uses computed tomography (CT) scanning to extract fracture geometry. The gas-displacing-water process is precisely controlled by integrating the pore capillary pressure and back-pressure feedback algorithm. The NMR-CT conversion method performed in this study differs significantly from the T₂−r transformation based on conventional MICP. Differential spectral analysis isolates fracture-specific T₂ responses, and least-squares fitting derives the T₂−r conversion. Constraining displacement pressure and controlling segmental pressure are effective methods for ensuring the accuracy of fracture displacement. By emphasizing the governing role of capillary pressure during displacement, this method achieves accurate fracture-targeted displacement and reliable T₂−r mapping. The results significantly advance the use of NMR for quantifying fracture size and evaluating fluid transport in shale. Full article

Membrane technologies play a role in water treatment, energy conversion, and industrial separation processes; however, their performance is limited by fouling, polarization phenomena, transport inefficiencies, and energy consumption. This study presents a review of the integration of computational fluid dynamics and machine learning in membrane technologies, complemented by an environmental and engineering assessment of representative membrane materials. A systematic literature screening based on PRISMA guidelines was conducted using the Scopus (Elsevier B.V., Amsterdam, The Netherlands) and Web of Science (Clarivate, Philadelphia, PA, USA) databases, yielding 1421 records, of which 54 studies met the predefined relevance criteria. The analysis revealed a transition from conventional physics-based approaches toward hybrid simulation–machine learning frameworks, with artificial neural networks, surrogate models, and optimization emerging as the dominant methodologies. Energy consumption was identified as the most frequently investigated variable, particularly in desalination, fuel cell, electrodialysis, and hydrogen production systems. A complementary material-level assessment showed that conventional polymeric membranes, especially polyamide-based systems, remain dominant due to their performance and economic feasibility, whereas advanced materials such as graphene, carbon nanotubes, and perovskites offer promising functional properties but face challenges. The findings highlight the potential of integrated simulation–machine learning–material assessment frameworks to accelerate the development of intelligent and sustainable membrane technologies for future applications. Full article

Laminar counterflow multi-branch flames provide a canonical configuration for investigating interactions between oxidizer-rich and fuel-rich streams in liquid-oxygen/methane combustion systems. This study numerically investigates their flame structure and stability under transcritical conditions, with stability characterized by the extinction strain rate. Ideal-fluid (IF), partial real-fluid (PRF), and real-fluid (RF) models are compared to distinguish the effects of real-fluid thermodynamics and high-pressure transport corrections. The multi-branch flame comprises two premixed branches coupled with a central diffusion branch. Heat release from the premixed branches creates high-temperature plateaus that preheat the stagnation-region mixture and sustain the diffusion branch. Although the three models predict similar flame topologies, the IF model gives an extinction strain rate of $3.306\times {10}^6{\mathrm{s}}^{-1}$, whereas both PRF and RF predict $3.256\times {10}^6{\mathrm{s}}^{-1}$. Thus, the ideal-fluid treatment slightly overpredicts the extinction limit under the present reference condition, while high-pressure transport corrections influence the ignition location, peak temperature, and thermal diffusivity. Increasing pressure from 10 MPa to 40 MPa raises the extinction strain rate from $9.336\times {10}^5{\mathrm{s}}^{-1}$ to $4.867\times {10}^6{\mathrm{s}}^{-1}$ by strengthening heat release and reducing thermal diffusion from the high-temperature region. Oxidizer preheating markedly enhances flame stability, whereas fuel preheating has a weak effect. These findings establish the connection between real-fluid thermodynamics, branch interaction, and extinction stability, providing a physical basis for model selection, operating-condition optimization, and stability-margin assessment in transcritical liquid-oxygen/methane combustion systems. Full article

To address the weak interfacial transition zone and insufficient mechanical properties of recycled aggregate pervious concrete, this study proposes a dual modification strategy using basalt fibers and ultra-fine mineral powder. The macroscopic mechanical and hydraulic properties of the material were analyzed through orthogonal experiments. Techniques including X-ray diffraction, scanning electron microscopy, and micro-computed tomography were employed to systematically reveal the microstructural evolution and internal pore network topology of the modified system. Based on range analysis of mechanical stiffness and drainage efficiency, the optimal mix proportions were determined as 5–10 mm aggregate, a water–cement ratio of 0.31, and a fiber content of 0.50%. Microscopic tests confirm that the pozzolanic reaction of ultra-fine mineral powder increases matrix density and enhances the shear bond strength between fibers and the cement paste, enabling the physical bridging effect of basalt fibers. The dual modification exhibits a synergistic effect on load-bearing capacity and crack resistance. CT scan results show that the internal pore cross-sectional area follows a unimodal skewed distribution, with the characteristic distribution peak located at 3.5 mm². This homogeneous microporous network limits the critical defect size, optimizing the stress transfer path while ensuring fluid transport. Full article

Unmanned Aerial Vehicles (UAVs) are seeing increased use in agricultural settings due to their potential to be integrated with systems for applying pesticides. They can target specific areas while offering the potential to reduce chemical waste and improve application efficiency. However, this means that spray deposition efficiency is strongly influenced by rotor-induced downwash, which affects droplet transport, drift, and uniformity. This study presents a combined computational and experimental investigation of downwash–spray interactions in a hexacopter platform. CFD is used to predict the performance of various sprayer configurations that differ in the number, spacing, and positioning of nozzles. Rotor-induced airflow is modeled using an actuator disk approach in ANSYS Fluent 2025, and spray behavior is predicted using the Discrete Phase Model. Pure water was used as the working fluid for both the CFD simulations and experimental validation to ensure consistency between numerical and physical testing conditions. Numerical results indicate that a two-nozzle under-rotor setup maximizes performance characteristics such as deposition area, density, and uniformity for the designed agricultural UAV, providing a theoretically effective deposition area of 9.375 m², an effective application rate of 0.03387 mL/m², and a coefficient of variation of 45.3%. Compared to the best-performing boom configuration, this represents an approximately 13.5% improvement in spray uniformity. These results are validated through experimental testing using a modular UAV sprayer system and deposition measurements obtained from water-sensitive paper in controlled indoor conditions, achieving a droplet size of 502 µm, swath width of 1.8 m, 0.8% area coverage, and a coefficient of variation of 36.5%. While differences were observed between predicted and measured droplet size distributions, the CFD and experimental results demonstrated similar trends in spray coverage and deposition uniformity. Future work will refine simulations to better match experimental conditions and investigate canopy interaction, crosswind effects, and field-scale performance. Full article

The two-dimensional thermal liquid jet of a non-Newtonian power-law fluid is investigated under shear-rate-dependent thermal diffusivity, resulting in a one-way coupled nonlinear system governing momentum and thermal transport. Two physically distinct free-surface thermal boundary conditions are examined: adiabatic insulation and convective heat loss. Conservation laws and conserved quantities for the governing system are derived systematically using the multiplier method. By coupling an appropriate conserved vector with an admitted Lie point symmetry, the governing partial differential equations are reduced to a coupled system of ordinary differential equations. Closed-form parametric families of solutions are then obtained for the thermal field. The analysis reveals fundamentally different thermal transport mechanisms across rheological regimes: shear-thinning fluids enhance thermal redistribution and become increasingly sensitive to convective cooling as the Biot number increases, whereas shear-thickening fluids suppress internal thermal transport, promoting greater thermal retention within the jet core and reducing the influence of free-surface cooling. These findings clarify the interplay between rheology, nonlinear thermal diffusion and free-surface cooling and provide new analytical insight into downstream thermal transport in non-Newtonian liquid jets. Full article

Proppant transport and deposition directly control fracture conductivity during hydraulic fracturing, especially under low-viscosity fracturing fluid conditions where strong convection, settling, deposition, and erosion coexist. To improve the computational efficiency of proppant transport simulation, this study develops a dual-network physics-informed neural network (dual-PINN) framework based on a previously developed fifth-order WENO proppant transport model. In the proposed framework, PINN_c is used to predict the proppant concentration field, while PINN_hp is used to predict the deposited proppant bed height. The governing physical constraints, including convection, effective diffusion, settling, deposition, and erosion, are embedded into the loss function to achieve coupled concentration–deposition prediction. The model is validated using a benchmark case with a fracture length of 100 m, fracture height of 30 m, fracture width of 0.002 m, injection rate of 0.015 m³/s, and inlet proppant concentration of 0.1. Compared with the fifth-order WENO reference solution, the RMSE values of the predicted proppant concentration at 100 s, 400 s, and 1500 s are 6.36 × 10⁻³, 7.38 × 10⁻³, and 8.28 × 10⁻³, respectively. The offline training time of the dual-PINN model is approximately 15 min, and the trained model requires only about 3 ms for one forward prediction. In comparison, the fifth-order WENO method requires 0.43–22.3 s for a single simulation under the tested mesh resolutions, corresponding to an online speed-up of approximately 143 to 7430. Sensitivity analyses further show that the proposed model maintains stable and physically consistent responses for inlet proppant concentrations of 0.01–0.25 and injection rates of 0.01–0.06 m³/s. These results demonstrate that the proposed dual-PINN framework can provide an efficient mesh-free surrogate for rapid proppant transport prediction and fracturing parameter optimization. Full article

The anisotropic permeability tensor governs interdendritic fluid flow and solute transport during the directional solidification of metallic alloys, fundamentally influencing crystal growth kinetics and microstructural evolution. Traditional scalar models, notably the Kozeny–Carman equation, are fundamentally limited by isotropic assumptions that contradict the inherent anisotropy of dendritic microstructures and preclude description of microstructure–transport coupling. Recent advances in multiscale computational crystal growth modeling, integrating phase-field simulations of dendritic morphology, lattice Boltzmann calculations of interdendritic flow, and synchrotron X-ray tomography for in situ microstructural characterization, have enabled tensor-resolved quantification of permeability evolution, yet the dynamic feedback between solid skeleton deformation and permeability remains poorly understood. This work establishes a critically assessed mechanistic framework coupling dendritic microstructure evolution, anisotropic permeability tensor dynamics, and solidification transport phenomena. By explicitly addressing the hitherto unresolved dynamic feedback between solid skeleton deformation and permeability, this review provides a theoretical foundation and a conceptual framework for future predictive modeling for solidification microstructure control, offering fundamental insights into the physics of crystal growth and interdendritic transport in metallic systems. Full article

Mobile pipeline refers to a type of pipeline that can be laid and recovered at any time as required, mainly used for product oil transportation. After the completion of the transportation mission, the oil remaining inside the pipeline needs to be evacuated before recovering. Water-driven oil evacuation is commonly used for this purpose. In this paper, the water-driven oil evacuation in an inclined inverted U-shaped pipe was investigated. A numerical model coupling the VOF interface-capturing method, the CSF surface-tension model, and the SST k–ω turbulence model was established and validated against visualization experiments. The oil–water two-phase displacement characteristics in this special pipe configuration were systematically analyzed. The results show that a critical inlet superficial water velocity exists during the evacuation process. Complete oil evacuation can be achieved only when the inlet superficial water velocity exceeds this critical value. The critical velocity increases with increasing pipe inclination angle and pipe diameter. When the inlet superficial water velocity is lower than the critical value, vortical structures and backflow are readily generated at the oil front and within the oil phase, leading to oil accumulation near the end of the upper horizontal section and the formation of a stable retained oil layer in the downward-inclined section. Moreover, larger inclination angles and pipe diameters intensify oil retention and reduce the evacuation efficiency under subcritical conditions. All conclusions are drawn based on the No. 0 diesel–water system at 25 °C, and the applicable scope is limited to working conditions with similar fluid physical properties. Full article

This study addresses the poorly understood fracture propagation mechanisms in continental shale oil reservoirs with multi-lithologic combinations, specifically those in the lower third member of the Shahejie Formation, Bonan Sag, which exhibit complex lithology, coexistence of bedding planes and natural fractures, and pronounced mechanical anisotropy. We conduct small scale true triaxial hydraulic fracturing physical simulation experiments using limestone mudstone, felsic–lime mixed shale, and their combined rock samples. We innovatively introduce the hydraulic fracture complexity coefficient (F_h), the bedding plane fracture complexity coefficient (F_l), and the comprehensive fracture complexity coefficient (F_T) to enable quantitative evaluation of fracture complexity. The results show that high-viscosity fracturing fluid promotes vertical propagation and improves proppant placement, but yields relatively simple fracture geometry. Low-viscosity fracturing fluid readily activates bedding plane fractures, yet limits fracture height; a combined viscosity strategy can synergistically optimize the overall fracturing performance. The “high–low–high” viscosity sequence achieves the highest comprehensive fracture complexity coefficient (F_T), simultaneously providing large fracture height, high complexity, and effective proppant transport. Although increasing the injection rate significantly reduces the breakdown pressure and increases fracture width, it contributes marginally to vertical fracture growth. For fracturing multi-lithologic shale oil reservoirs, the recommended technical strategy is a “high-low-high” viscosity sequence combined with a moderately increased injection rate” to maximize the stimulated reservoir volume and overall fracturing effectiveness. Full article

While traditional frameworks often simplify fluid dynamics, non-ideal thermodynamic characteristics, driven by intermolecular forces and spatial confinement, significantly alter bulk flow at the nanometer scale. To address this gap, we propose a novel transport model that rigorously couples nanoscale gas slippage with dynamic fluid properties. This approach uniquely integrates varying molecular interactions, seamlessly transitioning from attractive to repulsive regimes, alongside confinement-induced shifts in critical parameters. Taking the deep shale formation in the Sichuan Basin, China, as a representative geological context, accurately modeling methane transport is essential. Our analytical results reveal that incorporating non-ideal thermodynamics profoundly amplifies the predicted boundary slip. Specifically, the corrected mean free path is amplified by a factor of up to 4.7 relative to standard ideal gas assumptions. This enhancement scales strongly with elevated pressure but remains negligible near 1 MPa. Furthermore, we demonstrate that relying on ideal gas laws can inflate nanopore flow capacity estimates by more than 75%, an error primarily driven by density reductions and viscosity increases under high-pressure regimes. We also identify a specific thermodynamic window, sub-10 MPa pressures combined with temperatures below 290 K, where corrected transport metrics actually surpass conventional predictions, an anomaly governed predominantly by intensified slip dynamics. Ultimately, these findings highlight widespread inaccuracies in current permeability estimations, providing a more robust physical foundation for forecasting production and conducting numerical reservoir simulations. Full article

A frequent and sudden two-phase (solid–liquid) geological hazard in mountainous areas, the evolution of debris flows involves the coupling of multiple physical fields, making monitoring and early warning particularly challenging. To accurately reveal the dynamic patterns of debris flow evolution and improve early-warning accuracy, this study focused on the Ni Chang Valley area in Shimian County, Ya’an City, Sichuan Province. Based on the COMSOL Multiphysics coupling simulation platform, a multiphysics bidirectionally strongly coupled numerical model was proposed and constructed, integrating the SPH (smoothed particle hydrodynamics) meshless particle method, FLO-2D shallow-water dynamics, and the MassFlow full-process simulation approach. Using COMSOL as a unified framework, this model employs MassFlow’s deep-integration, continuous medium method to simulate rainfall triggering and material source activation, FLO-2D’s shallow-water equations to describe macroscopic flow-deposition processes, and SPH’s mesh-free particle method to accurately capture large deformations and free-surface flow. The model fully reproduces the entire dynamic chain of debris flow processes, from rainfall triggering and soil mobilization to fluid transport and channel deposition. The reliability and accuracy of the model were verified by comparing it with field measurements from the 20 September 2022 historical debris flow event at Ni Chang Valley. Quantitative analysis indicates that when the viscosity coefficient increases from 0.1 Pa·s to 100 Pa·s, the flow velocity decreases by approximately 47% and the flow depth increases by approximately 62%. When the yield stress increases from 1 Pa to 100 Pa, the deposition area shrinks from 269,900 m² to approximately 109,000 m², a reduction of about 60%. Combining the results of the dynamic analysis, daily maximum temperature, daily precipitation, moisture content, mud-water level, and ground surface displacement were selected as core monitoring indicators. The analytic hierarchy process (AHP) was used to determine the weights of each indicator, and a data- and physics-driven weighted summation model for debris flow monitoring and early warning was constructed to achieve a five-level debris flow monitoring and early-warning system. Historical disaster cases demonstrate that this early-warning model can provide advance predictions of debris flow disasters up to 2 h and 40 min in advance. The warning lead time is sufficient, the grading logic is clear, and the model is capable of accurately capturing precursor information on disasters. Full article

This study presents a computational analysis of degradation caused by cavitation and hydro-abrasive erosion in a low-head axial microturbine ($H=4\mathrm{m}$), incorporating strategic air injection as a passive mitigation technique. Using Computational Fluid Dynamics (CFD) within ANSYS CFX 2025 R2, the study investigates hydrodynamic performance and the spatial distribution of surface wear across the runner blades. The turbine geometry was developed from aerofoil profiles mapped onto cylindrical coordinates, using a structured three-dimensional mesh with localized refinement to ensure grid independence. Physical modeling employed the Shear Stress Transport (SST) turbulence model, with cavitation dynamics governed by the Rayleigh–Plesset equation and sediment transport modeled using a Lagrangian framework incorporating the Finnie erosion model. The numerical framework showed good agreement with reference characteristic curves, confirming its predictive accuracy. The results indicate that vapor cavities form predominantly on the suction side, whereas solid particle erosion highly concentrated on the pressure side of the blades, where the outer $20\%$ of the span accounts for over $91\%$ of the total erosion intensity. Parametric assessments of controlled air injection revealed a highly non-linear mitigation response, identifying IAVF 2 as the optimal air-injection case. This configuration reduced integrated erosion by $0.95\%$ and maximum localized erosion by $6.17\%$. In contrast, excessive air volumes accelerated material removal due to localized flow distortion. The findings indicate that carefully controlled air injection is a viable strategy for extending the operational lifespan of small-scale hydropower assets. Full article

This study examines the evolving patterns and zoning characteristics of gas migration and storage zones during coal seam mining, taking the 215 fully mechanized longwall face at Huangling No. 2 Coal Mine as the engineering background. By integrating theoretical analysis, physical similarity simulation experiments, and field measurements, the research systematically explores the zonal linkage evolution mechanism of mining-induced depressurization gas migration and storage zones, together with the associated depressurization gas extraction technology. A flow regime determination equation, driven by the fracture expansion coefficient and permeability, is established on the basis of the fluid Reynolds number criterion. According to differences in gas flow states and medium morphology, the mining-induced fracture field is divided into five distinct zones: a high-permeability zone dominated by turbulent transport, a medium-to-high permeability zone with transitional flow as the secondary dominant region, a low-permeability zone featuring linear laminar flow with micro-permeability, an extremely low-permeability zone characterized by linear laminar flow in a locked state, and a zone of abrupt permeability change associated with gas enrichment. The dynamic evolution of depressurization gas migration and storage zones and their regional linkage mechanisms are clarified. On the basis of these findings, a dynamic targeted layout strategy for high-level boreholes is proposed that is consistent with the spatiotemporal evolution of the overburden permeability field. Field engineering practice shows that the optimized high-level borehole layout maintains the overall gas extraction rate at the drilling site stably above 70%, with a peak value of 93.7%, thereby ensuring safe and efficient mining of the working face. Full article

Under the background of the green transformation and energy conservation in the aviation field, hydrogen-fueled aero-engines are the primary direction for achieving sustainable aviation power development. However, the unique thermophysical properties of hydrogen fuel induce extreme thermal load challenges to engine thermal management. Based on the requirements of energy conservation and digital-intelligent technologies, this paper reviewed the recent research progress, important challenges, and future development directions in the thermal management field for hydrogen-fueled aero-engines, and filled the gaps in existing related reviews. (1) As for the liquid hydrogen thermal properties and thermal management requirements, the unique thermal physical properties of liquid hydrogen can easily cause fluctuations in heat load, large temperature differences, and material compatibility issues such as hydrogen embrittlement during storage, transportation, and combustion. The application of thermal barrier coatings, the design of targeted cooling structures, and the regulation of heat loss in the pipeline of the hydrogen supply system require particular attention. (2) As for the technical architecture and optimization of thermal management, the optimization of the high-pressure side manifolds in the cooled cooling air heat exchanger increases the flow uniformity by 18.8% and reduces the weight by 22.5%. The intercooled recuperated engine with the optimum area ratio reduces specific fuel consumption by 5.3% compared to the baseline engine in cruise. However, the system-level optimization research of the above widely recognized solutions is relatively limited in terms of coordinating the energy flow of engines. The baseline engine employed the method of system integration optimization to achieve a 2.99% increase in thrust and a 6.78% reduction in fuel consumption. (3) As for the thermal management modeling and simulation, the intelligent optimization method based on computational fluid dynamics reduces the pressure loss coefficient of the vane-integrated heat exchanger by 36%. Nevertheless, the multiphysics coupling model confronts a contradiction between computational cost and accuracy. (4) As for the comprehensive evaluation method, the advanced configuration of the hydrogen-fueled aero-engine can approximately reduce specific fuel consumption by 68.5% and NOx emission by 12.7% under the same maximum thrust condition. The hydrogen consumption of the proton exchange membrane fuel cells system model compared with the baseline system, optimized by the multi-objective optimization algorithm, has decreased by 15%, while the thermal uniformity has improved by 20–30%. However, the current evaluation system mostly focuses on a single dimension, lacking the analysis of nonlinear coupling among multiple factors and a closed-loop mechanism for evaluation, optimization, and verification. Future research should focus on the matching model of liquid hydrogen’s thermophysical properties and full flight conditions, global multi-energy flows optimization methods, multidimensional collaborative numerical simulation, multiphysics coupling models, and multidimensional comprehensive evaluation systems, to provide closed-loop theoretical support for the efficient, intelligent, and reliable thermal management system for hydrogen-fueled aero-engines. Full article