Search Results (5,191)

Supercritical carbon dioxide (SC-CO₂) fracturing has emerged as an environmentally friendly alternative to conventional water-based hydraulic fracturing; however, its inherently low viscosity restricts proppant-carrying efficiency and reduces fracture conductivity. To address this limitation, this study systematically investigates the rheological behavior and sand-carrying mechanisms of CO₂ dry fracturing fluid under various thermodynamic and compositional conditions. Rheological measurements were conducted to evaluate the effects of thickener concentration, temperature, and pressure on viscosity, while visualized experiments were performed to examine the influence of injection rate, sand ratio, thickener concentration, and temperature on proppant migration and deposition. A numerical model developed in Fluent was further employed to simulate the temporal evolution of proppant transport within the fracture. The results show that higher thickener concentrations and injection rates significantly enhance proppant transport distance and uniformity, whereas elevated temperature and sand ratio promote localized settling. The simulation results agree well with the experimental observations, validating the model’s reliability. This study elucidates the coupled effects of rheology and operating parameters on CO₂ dry fracturing behavior and provides theoretical and experimental guidance for optimizing CO₂-based fracturing fluids in low-permeability reservoirs. Full article

In indoor thermal analyses, the effect of humid air as a radiatively participating medium that absorbs and emits energy is often neglected. This simplification can underestimate important values in the results. This study presents a numerical investigation of the humid air that participates radiatively in the conjugate heat and mass transfer convection into a room modeled as a two-dimensional square cavity with a semitransparent wall (glass). The governing equations for mass, momentum, energy, species transport, turbulence, and radiative heat transfer were solved using the Finite Volume Method and coupled with the SIMPLEC algorithm. Two scenarios were analyzed: a radiatively participating medium (RPM) and a non-participating medium (NPM), under two climatic conditions (hot and cold). Results show that considering the radiatively participating medium breaks the symmetric patterns observed in the case of NPM. The energy absorbed by humid air enhances turbulent viscosity, buoyant forces, and indoor temperature. Humid air absorbs approximately 30–32% of the incident energy entering the enclosure. Finally, a correlation for the average temperature is proposed. The results provide insight into the influence of radiatively participating humid air on indoor-like thermal behavior. The study focuses on the analysis of fundamental transport mechanisms. Full article

Fluid–structure interaction (FSI) research is crucial for applications in fields such as naval engineering, geological hazards, and biomechanics. Traditional grid-based methods (such as CFD) often face challenges in simulating large-deformation flow fields and complex boundary conditions, where mesh distortion can compromise simulation accuracy. Building upon the DualSPHysics5.2 framework, this study leverages the strengths of weakly compressible SPH (WCSPH) in modeling free surface flows and large-deformation fluids, as well as the discrete element method (DEM), for accurately describing particle collisions and fragmentation behaviors. We propose an improved MSPH-DEM coupling algorithm that incorporates moving least squares (MLS) correction for kernel function gradient optimization. This algorithm utilizes MLS-based gradient correction to achieve smoother fluid surfaces as well as bidirectional coupling between fluids and particles. Experimental validation demonstrates that in dam break simulations, this method reduces pressure errors. In the dam break impacting a cube experiment, it enhances accuracy, while in the dam break impacting a baffle experiment, the horizontal displacement of marker points closely aligns with the experimental values from Liao et al. This approach effectively improves the accuracy of the simulations of FSI problems, offering a more reliable numerical simulation methodology for engineering applications such as geological hazard prevention. Full article

This paper presents a practical numerical procedure for the study of structures on foundations subjected to soil consolidation settlements, using the Finite Element Method (FEM) coupled with the Boundary Element Method (BEM). A theoretical application is presented for a structure built on saturated soft soil, employing the Kelvin–Voigt and Boltzmann viscoelastic models. The Kelvin–Voigt model is suitable for situations where uniform or negligible initial settlements are assumed before the onset of soil consolidation, whereas the Boltzmann model allows for the consideration of differential movements, including both immediate and time-dependent displacements. This study shows that, although the same viscoelastic parameters are adopted for both models, the differences in internal forces and resulting displacements can be significant due to the distinct relative stiffnesses. The choice of viscoelastic model directly impacts the prediction of structural behavior. The analyses were conducted considering an iterative coupling between the FEM and BEM systems, using an MATLAB R2024a routine developed by the authors. Despite the differences between the models, the results obtained were consistent with the technical literature, reinforcing the applicability of the proposed procedure. Full article

Bench slopes in open-pit mines are highly susceptible to progressive deformation and instability due to the coupled effects of excavation disturbance, rock mass weathering, and extreme rainfall, posing significant challenges to rapid risk assessment and engineering decision-making. To address the limitations of conventional methods in efficiency and adaptability under complex multi-factor conditions, this study proposes a hybrid simulation–artificial intelligence framework for rapid slope stability assessment and bench face angle optimization. Multi-scenario numerical simulations were conducted by integrating geological investigation data, laboratory and in situ mechanical parameters, and extreme rainfall conditions to characterize slope deformation and failure mechanisms and generate a dataset for machine learning model training. Machine learning models were trained using slope height, bench face angle, unit weight, cohesion, and friction angle as inputs, and safety factors under natural and extreme rainfall conditions as outputs, with hyperparameters optimized by Bayesian optimization. The results indicate that highly weathered rock masses dominate shallow deformation and act as critical weak zones, while extreme rainfall significantly accelerates instability evolution and reduces slope safety factors. Among the RF, SVR, and ELM models, the Bayesian-optimized support vector regression (BO-SVR) exhibits the best predictive performance (R² > 0.98). SHapley Additive exPlanations (SHAP) analysis reveals that slope height and shear strength parameters are the dominant controlling factors, whereas unit weight has a relatively limited influence. Validation using real landslide cases shows good agreement with numerical simulations, confirming the reliability of the proposed framework. The developed approach enables rapid risk evaluation and supports bench face angle optimization, providing an effective tool for intelligent slope management in open-pit mining. Full article

We develop a theoretical model for the flexoelectric instability in bent-core nematic liquid crystals, focusing on the coupling between elastic distortions and an external electric field through flexoelectric polarization. The analysis is carried out in the nematic phase close to the twist-bend transition, where both the flexoelectric coefficients and the effective bend elastic constant exhibit strong temperature dependence. Within a Landau–de Gennes framework, we derive analytical expressions for the threshold electric field and the corresponding wave vector of the emerging periodic modulation by minimizing the total free energy and assuming $K_1=K_2$. Numerical simulations illustrate the temperature dependence of the threshold parameters and the role of dielectric anisotropy and elastic constants. The results indicate that the flexoelectric instability may occur only within a finite temperature interval above the transition into the twist-bend phase and that both the threshold electric field and the periodic structure’s wave vector decrease as the temperature decreases. Full article

Submicron particulate matter in the 0.1–1.0 µm range is difficult to remove using conventional air pollution control devices because of its low capture efficiency. Condensation-induced particle enlargement has therefore been proposed as a preconditioning method to increase particle size before collection. This study aims to numerically investigate the condensation-induced growth of submicron particles in a cylindrical tube under different pressure-recovery conditions and to clarify how pressure-controlled supersaturation affects droplet-growth kinetics. A three-dimensional computational fluid dynamics (CFD) model was developed in ANSYS Fluent by coupling the Discrete Phase Model (DPM) with a custom User-Defined Function (UDF) growth law to predict droplet growth, condensation time, and associated heat and mass transfer characteristics. Initial particle diameters of 0.1–1.0 µm were examined for growth to a target diameter of 5 µm under initial pressure conditions of 0.5–0.9 bar followed by recovery to 1 atm, corresponding to calculated nominal supersaturated RH values of 202.65–112.58%, respectively. The results show that pressure-induced supersaturation is the dominant factor controlling condensation kinetics. Lower initial pressures resulted in shorter condensation times and higher mass and heat transfer rates. For an initial diameter of 0.5 µm, the condensation time decreased from approximately 0.1434 s at 0.9 bar to 0.0167 s at 0.5 bar, corresponding to an 88.35% reduction. These findings indicate that pressure-controlled supersaturation can significantly accelerate submicron particle enlargement and provide design guidance for condensation-assisted fine-particle removal technologies. Full article

An investigation is presented into the coupled thermo-mechanical behavior of a fiber-reinforced composite solid, with specific consideration given to the influences of gravity and thermal preconditions under inclined loading. The theoretical foundation of this work is based on the generalized dual-phase Green–Naghdi theory for constitutive modeling. Normal mode analysis has been utilized in the fundamental equations of coupled thermoelasticity. Ultimately, the derived equations are expressed as a vector-matrix differential equation, which is subsequently solved using the eigenvalue method. The outcomes of this analysis are then interpreted through numerical simulations, the details of which are presented graphically and discussed comprehensively to draw pertinent conclusions. A detailed parametric study was conducted to elucidate the individual and synergistic effects of these parameters on the material’s behavior. The findings confirm the model’s efficacy in capturing complex thermo-mechanical couplings, providing a robust framework for the design and optimization of composite structures in different environments. Analysis of the results indicates that the gravity field, reference temperature, and inclined load all exert a notable influence on the physical field variables. Furthermore, the numerical calculations performed in MATLAB R2013a demonstrate close consistency with the theoretical solution, verifying the model’s accuracy. Full article

Compressed CO₂ energy storage (CCES) in deep sedimentary basins offers a promising option to integrate carbon management with long-duration energy storage. However, most existing subsurface energy-storage studies focus on salt caverns or generic porous reservoirs, while the potential of evaporite-bounded carbonate reservoirs remains insufficiently explored. This study presents the first application-oriented numerical assessment of CCES in Southern Ontario. It investigates the feasibility of CCES in the Upper Silurian Salina Group beneath offshore Lake Huron, focusing on a porous A-2 carbonate interval vertically confined by B and A-2 halite caprocks. A fully coupled three-dimensional thermo-hydro-mechanical model is developed in COMSOL Multiphysics 6.3 to simulate two-phase (brine-CO₂) Darcy flow, heat transfer, and poroelastic deformation under a realistic Michigan Basin stress, pressure and geothermal regime. After an initial cushion-gas stage at 8 kg/s that establishes a caprock-parallel supercritical CO₂ wedge beneath the B-salt, 24 h injection-production cycles are imposed for two years, followed by a five-month high-resolution window. Three well completion strategies are compared: full-length, upper-only, and split (upper + lower) perforations. Results indicate that in all simulations the CO₂ plume stabilizes as a persistent gas cap beneath the B-salt, far-field pressures remain close to hydrostatic, and reservoir deformations are very small, pointing to a substantial geomechanical safety margin. Among the three completion strategies, the split completion provides the best compromise: it maintains high and relatively stable CO₂ production while avoiding the stronger lower-zone depressurisation seen in the full-length case and the more limited working volume of the upper-only case. These findings suggest that a Salina A-2 carbonate reservoir bounded by B and A-2 salts can accommodate cyclic CCES under realistic basin conditions, and that appropriately designed split completions offer a practical balance between storage utilisation and operational robustness in this setting. Full article

A 7224C high-speed angular contact ball bearing used in a multi-wire sawing machine is selected as the research object to investigate the cage dynamic characteristics under oil-lubricated operating conditions. First, in order to determine the oil-phase volume fraction on the cage surface, a fluid-domain model of the bearing cavity is established, and numerical simulations are performed using the VOF multiphase-flow method coupled with the RNG k-ε turbulence model. The effects of the guiding clearance, pocket clearance, and rotational speed are analyzed, and a regression equation for the cage-surface oil-phase volume fraction is developed based on a uniform test design. Subsequently, a bearing dynamic model is constructed, in which lubrication-related parameters are determined based on the regression equation, and the force balance and equations of motion for each component are derived. Finally, using the slip ratio and the deviation ratio of the cage-centroid whirl velocity as evaluation indices, the influences of multiple parameters on cage stability are examined. The results indicate that increasing the clearances and rotational speed leads to a higher slip ratio, whereas increasing the axial and radial loads reduces the slip ratio. Moreover, enlarging the guiding clearance and increasing the axial load improve cage stability, while a larger pocket clearance and an excessively high radial load deteriorate cage stability. Full article

Driven by global climate change and carbon reduction targets, nuclear energy has gained increasing prominence as a clean baseload power source. Enhancing the energy efficiency of key equipment in nuclear power plants is essential for achieving a low-carbon transition. This study addresses the trade-off between separation efficiency and pressure drop under multi-parameter coupling in hooked corrugated plate separators by proposing a multi-objective optimization strategy that integrates automated numerical simulation with data-driven optimization. An automated CFD framework was developed to efficiently generate a comprehensive dataset covering inlet velocity, droplet diameter, plate spacing, and hook length. A multilayer perceptron (MLP) surrogate model was then constructed, achieving high predictive accuracy with coefficients of determination (R²) of 0.95 for separation efficiency and 0.91 for pressure drop. Using the trained surrogate model, the NSGA-II algorithm was employed for multi-objective optimization, and the TOPSIS method was applied to identify the optimal compromise solutions. The results show that for representative droplet diameters of 5, 10, and 15 μm, the optimized structures improve separation efficiency by 25.71–29.14%. The integrated automated CFD–surrogate model–multi-objective optimization framework established in this study provides an efficient and generalizable approach for the design of gas–liquid separation equipment, contributing to energy consumption reduction in nuclear and process industries and supporting the realization of global carbon neutrality goals. Full article

In order to design suitable heat-dissipating clothing for people engaged in high-temperature conditions, the vapor-dominated moisture transfer and heat dissipation properties of polyester fabric (Coolmax) with irregular cross-section in sweat-wicking protective clothing were analyzed by establishing a three-dimensional thermal–moisture coupled numerical model. In this study, moisture transport was mainly considered as water vapor transport within the porous fabric domain under a prescribed vapor-input boundary condition, rather than as a complete liquid-sweat-wicking, condensation, and re-evaporation process. The effects of convective heat transfer coefficient, ambient temperature, fabric thickness, and porosity on the thermal and moisture regulation behavior of the fabric were analyzed. The results show that Coolmax fabric can realize more efficient vapor transfer and heat diffusion under different ambient conditions due to its irregular grooved fiber structure, and its skin-side temperature is lower, and the relative-humidity distribution is more uniform than that of cotton material. Through the comparative analysis of temperature and relative humidity under different parameter combinations, the reasonable structural parameter range considering heat dissipation efficiency and perspiration ability is determined as follows: a fabric thickness of 0.8–1.2 mm and a porosity of 0.70–0.80, which can effectively improve the heat and moisture regulation performance of fabrics. This study provides a theoretical basis and numerical simulation reference for material selection and structure design of sweat-protective clothing and functional sportswear, which is helpful to improve wearing comfort and reduce thermal stress. Full article

The post-tensioned cross-laminated timber (CLT) rocking wall is a recently developed resilient CLT lateral force-resisting system with a self-centering feature. The structural responses of the systems with different designs need to be determined and evaluated efficiently to promote the development and standardization of industrial applications. This study developed a computationally efficient, component-assembled numerical model for post-tensioned cross-laminated timber (PT CLT) rocking walls that captures decompression, post-tension self-centering, and energy dissipation within a framework. The single wall model was assembled using nonlinear zero-length springs for the compression at the CLT bottom, truss bar element for the PT tendon, and elastic shell element for the CLT panel deformation. The energy dissipation device, the UFP, was modeled with nonlinear one-dimensional springs between the wall panels in the coupled wall model. The wall models were separately calibrated considering the wall designs of single-panel walls and coupled walls. Both single and coupled wall models predicted the initial stiffness, decompression, yielding, post-yield stiffness, and reloading/unloading stiffness. The residual drift and nonlinear unloading captured with the PT model were also validated with the test data. A two-story platform structure model was established based on the NHERI Tallwood project, assembled with the coupled wall model and CLT slab in shell elements and columns in Euler beam elements. With recorded ground acceleration signals from the test, the platform structure’s peak story displacement and inter-story drift were simulated with less than 30% differences for most cases. Unlike existing detailed contact-based models, the proposed approach balances local damage fidelity and computational efficiency. The validated model provides a framework for evaluating PT CLT wall design parameters considering their influence on full structures. Full article

This paper presents a surrogate-based uncertainty quantification (UQ) framework for coupled structural–acoustic systems subject to material and geometric variability. The proposed methodology integrates the Finite Element Method (FEM) with two metamodeling techniques—the Quadratic Response Surface (QRS) and Kriging—and Monte Carlo Simulations (MCS), to efficiently characterize the probabilistic behavior of the acoustic response. Two accuracy metrics (cross-validation error and prediction error) are used to validate the surrogate models. Numerical experiments demonstrate that the Kriging metamodel trained with 30 Latin Hypercube Sampling (LHS) points achieves superior predictive accuracy, with a Relative Maximum Error of 4.125 × 10⁻⁷. Monte Carlo Simulations conducted via the Kriging surrogate reduce the computational cost by more than six orders of magnitude compared to direct FEM-based MCS, while maintaining high accuracy. The proposed framework is validated on a rectangular cavity coupled with two flexible aluminum plates, and provides an efficient and accurate tool for vibro-acoustic UQ in complex engineering systems. Full article

Modern engineering systems may require multidisciplinary design optimization (MDO) to account for the interactions between coupled physical phenomena. When uncertainties affect model parameters or design variables, these analyses must be extended to uncertainty-based MDO (UMDO), in which objectives and/or constraints are expressed as statistical quantities. However, solving UMDO problems is computationally demanding, especially when costly simulators are involved and the budget must be allocated among uncertainty quantification, multidisciplinary coupling resolution, and optimization. This article introduces a generic multi-fidelity strategy, implemented in the open-source GEMSEO framework, to efficiently address UMDO problems. A fidelity level is defined by a number of samples to estimate the statistics; the higher the fidelity, the higher the number. The strategy solves the UMDO problem for each level by using the solution of the previous level as an initial guess. Numerical experiments are deployed on a simplified overall aircraft design (OAD) problem and a hybrid electric regional aircraft (HERA) case. The results show that, with two fidelity levels, restricting samples and iterations at the low-fidelity stage improves overall performance. This allows the multi-fidelity framework to significantly reduce computational cost compared with single-fidelity approaches (up to 45% for OAD and 40% for HERA) while maintaining or improving solution accuracy. Full article