Search Results (1,357)

Deep and ultra-deep drilling operations commonly encounter fractured and fracture-vuggy formations, where weak wellbore strength and well-developed fracture networks lead to frequent lost circulation, presenting a key challenge to safe and efficient drilling. Existing diagnostic practices mostly rely on drilling fluid loss dynamic models of single fractures or simplified discrete fractures to invert fracture geometry, which cannot capture the spatiotemporal evolution of loss in complex fracture networks, resulting in limited inversion accuracy and a lack of quantitative, fracture-network-based loss-dynamics support for bridge-plugging design. In this study, a geologically realistic wellbore–fracture-network coupled loss dynamic model is constructed to overcome the limitations of single- or simplified-fracture descriptions. Within a unified computational fluid dynamics (CFD) framework, solid–liquid two-phase flow and Herschel–Bulkley rheology are incorporated to quantitatively characterise fracture connectivity. This approach reveals how instantaneous and steady losses are controlled by key geometrical factors, thereby providing a computable physical basis for loss-zone inversion and bridge-plugging design. Validation against experiments shows a maximum relative error of 7.26% in pressure and loss rate, indicating that the model can reasonably reproduce actual loss behaviour. Different encounter positions and node types lead to systematic variations in loss intensity and flow partitioning. Compared with a single fracture, a fracture network significantly amplifies loss intensity through branch-induced capacity enhancement, superposition of shortest paths, and shortening of loss paths. In a typical network, the shortest path accounts for only about 20% of the total length, but contributes 40%–55% of the total loss, while extending branch length from 300 mm to 1500 mm reduces the steady loss rate by 40%–60%. Correlation analysis shows that the instantaneous loss rate is mainly controlled by the maximum width and height of fractures connected to the wellbore, whereas the steady loss rate has a correlation coefficient of about 0.7 with minimum width and effective path length, and decreases monotonically with the number of connected fractures under a fixed total width, indicating that the shortest path and bottleneck width are the key geometrical factors governing long-term loss in complex fracture networks. This work refines the understanding of fractured-loss dynamics and proposes the concept of coupling hydraulic deviation codes with deep learning to build a mapping model from mud-logging curves to fracture geometrical parameters, thereby providing support for lost-circulation diagnosis and bridge-plugging optimisation in complex fractured formations. Full article

Hydrogen-based direct reduction (H-DR) represents an environmentally benign and energy-efficient alternative in ironmaking that has significant industrial potential. This study reviews the current status of H-DR shaft furnaces and accompanying hydrogen-rich reforming technologies (steam and autothermal reforming), assessing the three dominant numerical frameworks used to analyze these processes: (i) porous medium continuum models, (ii) the Eulerian two-fluid model (TFMs), and (iii) coupled computational fluid dynamics (CFD)–discrete element method (DEM) models. The respective trade-offs in terms of computational cost and model accuracy are critically compared. Recent progress is evaluated from an engineering standpoint in four key areas: optimization of the pellet bed structure and gas distribution, thermal control of the reduction zone, sensitivity analysis of operating parameters, and industrial-scale model validation. Current limitations in predictive accuracy, computational efficiency, and plant-level transferability are identified, and possible mitigation strategies are discussed. Looking forward, high-fidelity multi-physics coupling, advanced mesoscale descriptions, AI-accelerated surrogate models, and rigorous uncertainty quantification can facilitate effective scalable and intelligent application of hydrogen-based shaft furnace simulations. Full article

Liquid sloshing in partially filled tanks is commonly studied because of its influence on vehicle stability, structural loading, and control performance. In experimental investigations, sloshing measurements can be contaminated by mechanically induced fluid–structure interactions originating from the actuation system itself. This study presents a bench-scale experimental investigation of the interaction between static magnetic fields and the dynamic response of a mechanically excited water-tank system, with particular emphasis on distinguishing sloshing-related motion from higher-frequency mechanical effects. A rectangular acrylic tank was subjected to near-resonant horizontal excitation at a fixed fill height. A ferromagnetic steel plate was mounted externally beneath the tank and kept identical in all experiments, while either permanent magnets or mass-matched nonmagnetic dummies were attached externally to one sidewall. Two configurations were examined: a symmetric split-wall layout (15 + 15) magnets and a single-wall high-field arrangement with 30 magnets (Mag–30@L) together with its dummy control (Dummy–30@L). The center-of-gravity motion ${\mathrm{CG}}_y\left(t\right)$ was reconstructed from four load cells and analyzed in the time and frequency domains. Band-limited analysis of the primary sloshing mode near 0.55 Hz revealed no statistically significant influence of the magnetic field, indicating that static magnets do not measurably affect the fundamental sloshing dynamics under the present conditions. In contrast, a higher-frequency response component in the 10–20 Hz range, attributed to mechanically induced fluid–structure interaction associated with actuator reversal dynamics, was consistently attenuated when magnets were present; this component is absent in corresponding CFD simulations and is, therefore, not associated with sloshing motion. Given the extremely small magnetic Reynolds and Stuart numbers for water, the observations do not support any volumetric magnetohydrodynamic mechanism; instead, they demonstrate a modest magnetic influence on a mechanically excited, high-frequency coupled mode specific to the present experimental system. The study is intentionally limited to bench scale and provides a reproducible dataset that may inform future investigations of magnetically influenced fluid–structure interactions in experimental sloshing rigs. Full article

The dynamics of gas–liquid two-phase flow at fracture junctions are crucial for optimizing fluid transport in the complex fracture networks of coal seams, particularly for coalbed methane (CBM) extraction and gas hazard management. This study presents a comprehensive numerical investigation of transient air–water flow in a two-dimensional, symmetric, cross-shaped fracture junction. Using the Volume of Fluid (VOF) model coupled with the SST k-ω turbulence model, the simulations accurately capture phase interface evolution, accounting for surface tension and a 50° contact angle. The effects of inlet velocity (0.2 to 5.0 m/s) on flow patterns, pressure distribution, and energy dissipation are systematically analyzed. Three distinct phenomenological flow regimes are identified based on interface morphology and force balance: an inertia-dominated high-speed impinging flow (Re > 4000), a moderate-speed transitional flow characterized by a dynamic balance between inertial and viscous forces (∼1000 < Re < ∼4000), and a viscous-gravity dominated low-speed creeping filling flow (Re < ∼1000). Flow partitioning at the junction—defined as the quantitative split of the total inflow between the main (straight-through) flow path and the deflected (lateral) paths—exhibits a strong dependence on the Reynolds number. The main flow ratio increases dramatically from approximately 30% at Re ∼ 500 to over 95% at Re ∼ 12,000, while the deflected flow ratio correspondingly decreases. Furthermore, the pressure loss (head loss, ΔH) across the junction increases non-linearly, following a quadratic scaling relationship with the inlet velocity (ΔH ∝ V₀^1.95), indicating that energy dissipation is predominantly governed by inertial effects. These findings provide fundamental, quantitative insights into two-phase flow behavior at fracture intersections and offer data-driven guidance for optimizing injection strategies in CBM engineering. Full article

The temperature fluctuations due to the mixing of two streams in a T-junction induce thermal stresses in the piping material, resulting in a pipe failure in Nuclear Power Plants. The numerical modeling of the thermal mixing in T-junctions is a challenging task in computational fluid dynamics (CFD) as it requires advanced turbulence modeling with scale-resolving capabilities for accurate prediction of the temperature fluctuations near the wall. One approach to address this challenge is using Partially Averaged Navier–Stokes modeling (PANS), which can capture the unresolved turbulent scales more accurately than traditional Reynolds-Averaged Navier–Stokes models. PANS modeling with k-ε closure gives encouraging results in the case of the Vattenfall T-junction benchmark case. In this study, PANS k-ω closure modeling is implemented for the WATLON T-junction Benchmark case. The momentum ratio (M_R) for two inlet streams is 8.14, which is a wall jet case. The time-averaged and root mean square velocity and temperature profiles are compared with the PANS k-ε and LES results and with experimental data. The velocity and temperature field results for PANS k-ω are close to the experimental data as compared to the PANS k-ε for a given filter control parameter f_k. Full article

This paper presents a numerical study of fluid–structure interaction (FSI) applied to wind turbines, combining computational fluid dynamics (CFD) and finite element analysis (FEA). The study focuses on a 3D wind turbine blade inspired by the GE 1.5XLE model. The blade features a twisted geometry with S818, S825, and S826 aerodynamic profiles, and is made of an orthotropic composite material with variable thickness and an internal spar. The fluid domain is defined by two circular sections upstream and downstream, aligned along the Z-axis. Simulations are performed under a wind speed of 12 m/s and a rotational speed of −2.22 rad/s (Tip Speed Ratio (TSR) = 8), with air modeled as an incompressible fluid at ambient temperature. On the CFD side, a periodic and symmetric modeling approach is applied, reducing the fluid domain to one-third of the full configuration by simulating flow around a single blade and extrapolating results to the remaining ones. This method achieves a 47% reduction in computation time while maintaining high accuracy in aerodynamic results. On the FEA side, spar condensation is performed by creating a superelement using the substructuring method. This strategy reduces structural computation time by 45% while preserving reliable predictions of displacements, stresses, and natural frequencies. These results confirm the effectiveness of the proposed techniques for accurate and computationally efficient aeroelastic simulations. Full article

Background: Impaired mucus drainage from the paranasal sinuses is often associated with nasal obstruction and reduced airway function in growing patients. Orthopedic maxillary protraction and expansion techniques can enhance airway dynamics, but their underlying fluid–structure mechanisms remain insufficiently understood. Objective: To validate that the Right Angle Maxillary Protraction Appliance (RAMPA), combined with a semi-rapid maxillary expansion (sRME) intraoral device gHu-1, improves mucus drainage by enhancing nasal airflow through nasal cavity expansion. Methods: The effects of RAMPA therapy were analyzed using computational fluid dynamics (CFD) for single-phase (air) and two-phase (air–mucus) flows within the nasal cavity, employing the unsteady RANS turbulence model. Finite element method (FEM) results from prior studies were synthesized to assess changes in the center and radius of maxillary rotation induced by RAMPA-assisted sRME. A male patient (aged 8 years 7 months to 11 years 7 months) treated with extraoral RAMPA and the intraoral appliance (gHu-1) underwent pre- and post-treatment cone-beam computed tomography (CBCT) and ear, nose, and throat (ENT) evaluation. Results: FEM analysis revealed an increased radius and elevated center of maxillary rotation, producing expansion that was more parallel to the palatal plane. CFD simulations showed that nasal cavity expansion increased airflow velocity and pressure drop, enhancing the suction effect that promotes mucus clearance from the frontal sinus. Clinically, nasal passages widened, paranasal opacities resolved, and occlusal and intermolar widths improved. Conclusions: RAMPA combined with sRME improves nasal airflow and maxillary skeletal expansion, facilitating paranasal mucus clearance and offering a promising adjunctive approach for enhancing upper airway function in growing patients. Full article

Simulating the dispersion of high-buoyancy pollutant is challenging because of the change in fluid density. A species transport (ST) model, which accounts for variable fluid density, was first validated by simulating light and heavy gas dispersion around a cubic building using computational fluid dynamics (CFD). This validated model was then employed to study wind flow and gas dispersion with varying plume buoyancies inside a two-dimensional street canyon. The applicability of a commonly used passive scalar transport (PST) model for simulating high-buoyancy gas dispersion was evaluated through comparisons with the ST model. The simulations demonstrated that the difference between the results of PST and ST models was negligible when a small amount of high-buoyancy pollutant was released, regardless of the gas type. However, when the emission rate was high, the fluid density was significantly altered, causing the results of the PST model to deviate substantially from those of the ST model. A clockwise recirculation was observed in all cases. This recirculation was strengthened when a large amount of light gas was released because of the positive buoyancy effect, resulting in low pollution levels. In contrast, the recirculation was suppressed, leading to high pollution levels in the case of heavy gas dispersion. This study indicated that both pollutant type and emission rate must be considered when using the PST model to simulate high-buoyancy gas dispersion. Full article

This study presents the development and evaluation of a novel solid–gas reactor designed to enhance the hydrogen reduction kinetics of tellurium oxide (TeO₂) under atmospheric pressure. Such gas–solid reactions can be processed in several types of reactors, including but not limited to fixed-bed reactors, moving-bed reactors, and fluidised-bed reactors. A combination of computational fluid dynamics (CFD) and experimental validation was employed to design and optimise a reactor’s geometry and gas-flow distribution. Single-phase CFD simulations were performed using the k–ω SST turbulence model to examine gas-flow behaviour, temperature uniformity, and gas-flow dead zones for two lance designs. The modified lance produced a stable swirling flow that improved gas distribution and eliminated stagnation regions. Experimental trials confirmed the simulation outcome in optimised gas-flow: the redesigned reactor achieved up to 65% conversion after 1 h and 70% after 2 h, a marked improvement over the rotary kiln, which required 5–6 h to reach similar levels. However, excessive gas flow led to cooling effects that reduced conversion efficiency. These results demonstrate the effectiveness of integrated CFD-guided reactor design for accelerating hydrogen-based oxide reduction and advancing sustainable metallurgical processes. Full article

Centrifugal compressors are vital components in industrial applications, but they are prone to a disruptive phenomenon known as surge, which can lead to mechanical stress and temperature increase. Surge occurrence is influenced by machine design, plant layout, and geometry. Engineers often deploy long (cold) and short (hot) recycle valves to address this issue. To ensure surge prevention, a fluid dynamic model is indispensable. In this study, a 1D Computational Fluid Dynamics (1D-CFD) model was developed using Amesim for a two-section centrifugal compressor. The main objective was to investigate the impact of various parameters on surge occurrence and compare different plant layouts to determine the most suitable solution for the specific study case. Here, the focus is on the influence of vent valves over the plant performance. To achieve this comparison, transient simulations of emergency shutdown (ESD) operations were performed. This study contributes to a better understanding of how machine design and operational factors affect surge behavior. By systematically evaluating different plant layouts, we identified the most effective strategies for preventing surge and enhancing compressor performance. This research provides valuable insights for engineers and operators striving to optimize industrial processes and improve the reliability and efficiency of centrifugal compressor systems. Full article

Inefficient management of dissolved oxygen (DO) in intensive aquaculture systems limits fish welfare and productivity by creating oxygen-deficient zones and promoting hydrodynamic conditions that hinder their dispersion. Because water movement directly influences how oxygen is transported and mixed within the culture unit, inadequate flow management can allow localized hypoxia to persist even when total oxygen input appears sufficient. To address this issue, this study proposes an integrated methodology that combines in situ respirometry measurements with Computational Fluid Dynamics (CFD) simulations to evaluate the spatial distribution of DO and diagnose the operational performance of aquaculture systems. The methodology quantifies oxygen consumption using intermittent-flow respirometry, applies a three-dimensional two-phase CFD model (water–oxygen) incorporating experimental oxygen consumption rates as boundary conditions, and validates the model under real operating conditions, focusing on active metabolism as the most demanding physiological state. The model generates a spatial distribution of DO patterns that are significantly modified by pond geometry, water flow characteristics, the metabolism of the fish and fish positioning. The differences between experimental and simulated values ranged from 7.8% to 10.7%, confirming the accuracy of the proposed method. The integration of in situ metabolic measurements with CFD modeling provides a realistic representation of DO dynamics, enabling system optimization and promoting more efficient and sustainable aquaculture. Full article

To address the fluctuation and instability of renewable power generation and the steady-state demands of chemical processes, a single-channel, non-isothermal computational fluid dynamics 3D model was developed. This model explicitly incorporates the coupling effects of electrochemical reactions, two-phase flow, and heat transfer. Subsequently, the influence of key operating parameters on proton exchange membrane water electrolyzer (PEMWE) system performance was investigated. The model accurately predicts the current–voltage polarization curve and has been validated against experimental data. Furthermore, the CFD model was employed to investigate the coupled effects of several key parameters—including operating temperature, cathode pressure, membrane thickness, porosity of the porous transport layer, and water inlet rate—on the overall electrolysis performance. Based on the numerical simulation results, the evolution of the ohmic polarization curve under temperature gradient, the block effect of bubble transport under high pressure, and the influence mechanism of the microstructure of the multi-space transport layer on gas–liquid, two-phase flow distribution are mainly discussed. Operational strategy analysis indicates that the high-efficiency mode (4.3–4.5 kWh/Nm³) is suitable for renewable energy consumption scenarios, while the economy mode (4.7 kWh/Nm³) reduces compression energy consumption by 23% through pressure–temperature synergistic optimization, achieving energy consumption alignment with green ammonia synthesis processes. This provides theoretical support for the optimization design and dynamic regulation of proton exchange membrane water electrolyzers. Full article

Small multi-rotor UAVs face endurance limitations during long-range missions due to high rotor energy consumption and limited battery capacity. This paper proposes a folding-wing range extender integrating a sliding-rotating two-degree-of-freedom folding wing—which, when deployed, quadruples the fuselage length yet folds within its profile—and a tail-thrust propeller. The device can be rapidly installed on host small multi-rotor UAVs. During cruise, it utilizes wing unloading and incoming horizontal airflow to reduce rotor power consumption, significantly extending range while minimally impacting portability, operational convenience, and maneuverability. To evaluate its performance, a 1-kg-class quadrotor test platform and matching folding-wing extender were developed. An energy consumption model was established using Blade Element Momentum Theory, followed by simulation analysis of three flight conditions. Results show that after installation, the required rotor power decreases substantially with increasing speed, while total system power growth slows noticeably. Although the added weight and drag increase low-speed power consumption, net range extension emerges near 15 m/s and intensifies with speed. Subsequent parametric sensitivity analysis and mission profile analysis indicate that weight reduction and aerodynamic optimization can effectively enhance the device’s performance. Furthermore, computational fluid dynamics (CFD) analysis confirms the effectiveness of the dihedral wing design in mitigating mutual interference between the rotor and the wing. Flight tests covering five conditions validated the extender’s effectiveness, demonstrating at 20 m/s cruise: 20% reduction in total power, 25% improvement in endurance/range, 34% lower specific power, and 52% higher equivalent lift-to-drag ratio compared to the baseline UAV. Full article

The increasing global demand for cleaner transportation has intensified the importance of efficient AdBlue^® (AUS32) production, a key chemical in selective catalytic reduction (SCR) systems that reduces nitrogen oxides (NOx) emissions from diesel engines. This work presents a computational fluid dynamics (CFD) simulation study of the urea–water mixing process within a high shear mixer (HSM), aiming to enhance the sustainability of AdBlue^® manufacturing. The model evaluates the hydrodynamic characteristics critical to optimising the dissolution of urea pellets in deionised water, which conventionally requires significant preheating. Experimental validation was conducted by comparing pressure drop simulation results with operational data from an active industrial facility in the United Kingdom. Therefore, this study validates the CFD model against an industrial two-stage Rotor–stator under real operating conditions. The computational framework combines a refined mesh with the k-ω SST turbulent model to resolve flow structures and capture near-wall effects and shear stress transport in complex flow domains. The results reveal opportunities for process optimisation, particularly in reducing thermal energy input without compromising solubility, thus offering a more sustainable pathway for AdBlue^® production. The main contribution of this work is to close existing gaps in industrial practice and propose and computationally validate strategies to improve the numerical design of HSM for solid dissolution. Full article

The use of liquid hydrogen (LH₂) as an energy carrier is gaining traction across sectors such as aerospace, maritime, and large-scale energy storage due to its high gravimetric energy density and low environmental impact. However, the cryogenic nature of LH₂, with storage temperatures near 20 K, poses significant thermodynamic and safety challenges. This review consolidates the current state of modelling approaches used to simulate LH₂ behaviour during storage and transfer operations, with a focus on improving operational efficiency and safety. The review categorizes the literature into two primary domains: (1) thermodynamic behaviour within storage tanks and (2) multi-phase flow dynamics in storage and transfer systems. Within these domains, it covers a variety of phenomena. Particular attention is given to the role of heat ingress in driving self-pressurization and boil-off gas (BoG) formation, which significantly influence storage performance and safety mechanisms. Eighty-one studies published over six decades were analyzed, encompassing a diverse range of modelling approaches. The reviewed literature revealed significant methodological variety, including general analytical models, lumped-parameter models (0D/1D), empirical and semi-empirical models, computational fluid dynamics (CFD) models (2D/3D), machine learning (ML) and artificial neural network (ANN) models, and numerical multidisciplinary simulation models. The review evaluates the validation status of each model and identifies persistent research gaps. By mapping current modelling efforts and their limitations, this review highlights opportunities for enhancing the accuracy and applicability of LH₂ simulations. Improved modelling tools are essential to support the design of inherently safe, reliable, and efficient hydrogen infrastructure in a decarbonized energy landscape. Full article