Search Results (9,387)

Large-scale wind farms operate under highly unsteady atmospheric inflows, where transient turbulence, dynamic wake interactions, and inflow-wake coupling reduce energy production and exacerbate turbine loads. Over the past five years, advances in high-fidelity computational fluid dynamics (CFDs), large eddy simulation (LES), machine learning (ML)-based wake modeling, and multi-objective optimization have reshaped wind farm layout optimization under dynamic inflow conditions. This review synthesizes recent progress in five key areas: dynamic inflow and high-fidelity wake modeling (including LES-driven transient wake evolution and turbulence-resolved inflow generation), data-driven wake prediction, multi-objective layout optimization (considering the annual energy production (AEP), fatigue load constraints, and the levelized cost of energy (LCOE)), blockage modeling for complex terrain and yaw misalignment, and real-time optimization addressing inflow, turbine performance, and modeling uncertainties. Coupling transient wake models with surrogate-assisted multi-objective optimization enables a computationally efficient and physically consistent layout design. Key open challenges (dynamic wake controllability, real-time optimization under uncertainty, and integration with next-generation farm-level control systems) and future directions for enhancing large-scale wind farm resilience and cost-competitiveness are also identified. However, despite significant progress, existing models still face fundamental limitations, such as oversimplified treatment of complex turbulence structures, poor generalization under extreme or atypical conditions, and inadequate capture of long-timescale dynamic responses, which constrain their reliability in practical optimization settings. Full article

Rapid depressurization and warming during recovery can trigger stress in deep-sea microbes and accelerate RNA degradation. We developed a remotely operated vehicle (ROV)-oriented multi-sequence microbial sampler for 2000 m sampling (20 MPa, 2 °C) that integrates in situ filtration with immediate RNAlater injection (an RNA stabilization reagent), collecting up to 12 samples per dive. A Dirichlet sampling–B-spline–SVM framework was used to optimize the cam profile of the sequence trigger for robust actuation under geometric constraints and realistic tolerances in both manufacturing and assembly. Relative to the baseline 3-4-5 motion law, the optimized design reduces nominal peak driving torque by ~18–20% and lowers the maximum torque under tolerance perturbations; tests show a further ~10–25% reduction using a SiC ball–ZrO₂ block pair versus a MoS₂-lubricated titanium pushrod–ZrO₂ block pair. A Darcy–Forchheimer porous-media computational fluid dynamics (CFD) model predicts earlier clogging on the lower membrane and a fast-to-slow RNAlater displacement process; greater membrane resistance mismatch delays 95% displacement and increases RNAlater loss. Simulations and Rhodamine B tests suggest an RNAlater consumption of 0.9 L per parallel filter (one membrane per side), and 20 MPa chamber tests confirm stable operation and membrane retrieval. Full article

To address the bottleneck issues of traditional ultrasonic polishing—such as unclear material removal mechanisms for ductile metals and difficulties in controlling machining outcomes—this paper employs a combined approach of computational fluid dynamics (CFD) simulation and non-contact fixed-point polishing experiments to systematically reveal the intrinsic relationship between the dynamic characteristics of the polishing flow field and the evolution of the material surface. Numerical simulations demonstrate that the cavitation effect significantly regulates the flow field structure: it not only confines the minimum pressure near the saturated vapor pressure but also markedly reduces the pressure peak while concurrently causing an overall decrease in flow velocity, forming a strongly coupled multi-parameter system of pressure, cavitation, and flow velocity. Experimental results indicate a clear spatial differentiation in the material removal mechanism: the central region is dominated by cavitation erosion, resulting in numerous pits and a 33.6% increase in residual compressive stress; the edge region is primarily governed by fluid-mechanical scraping, effectively improving surface finish and increasing residual stress by 22.3%; the transition zone, influenced by synergistic mechanisms, shows the smallest stress increase (19.7%). The enhancement of residual compressive stress can significantly improve the fatigue resistance of materials and prolong their fatigue life. This study comprehensively elucidates the multi-mechanism synergistic material removal process involving “cavitation impact, mechanical scraping, and fatigue spallation” in ultrasonic polishing, providing a key theoretical basis and process optimization direction for sub-micrometer ultra-precision machining. Full article

Droplet-based microfluidics has emerged as a powerful platform for precise fluid manipulation in biomedical, chemical, and material science applications. Among various geometries, T-junction microchannels are widely utilized for droplet generation and splitting due to their simplicity and reliability. This review provides a comprehensive overview of droplet splitting mechanisms in T-junction microfluidic systems, with particular emphasis on the role of actuation methods in enhancing control and functionality. We first discuss the fundamental physics governing droplet behavior, including the influence of capillary and viscous forces, flow regimes, and geometric parameters. Passive strategies based on flow rate tuning and channel design are outlined, followed by an in-depth examination of active actuation techniques: thermal, electrical, magnetic, acoustic, and pneumatic and their effects on droplet dynamics. In addition, the review highlights computational modeling approaches and experimental tools used to characterize and predict splitting behavior. Finally, we explore the current challenges and future directions in integrating multifunctional actuation systems for real-time, programmable droplet control in lab-on-a-chip platforms. This article serves as a foundational resource for researchers aiming to advance microfluidic droplet manipulation through actuator-enabled strategies. Full article

Impinging jet ventilation (IJV) systems have attracted significant attention due to their potential to augment indoor thermal comfort and airflow distribution. Previous studies have primarily investigated corner and mid-wall IJV installations; however, comparative analyses focusing on different diffuser geometries remain limited. Accordingly, this study examines the combined effects of IJV diffuser geometry and installation location on thermal comfort indices and airflow characteristics. A full three-dimensional computational fluid dynamics (CFD) model, without the use of symmetry, is developed to simulate a realistic office environment (3 × 3 × 2.9 m³), operating in cooling mode under hot summer climatic conditions. Three IJV diffuser cross-section geometries—triangular, square, and circular—are evaluated at four installation locations (two corners and two mid-wall positions), assuming a fixed occupant location. A combined return and exhaust outlet configuration is adopted. The results indicate that the IJV location influences airflow and temperature distributions more strongly than the diffuser geometry. Nevertheless, the circular diffuser exhibits superior performance compared to the triangular and square geometries. The mid-wall location placed behind the occupant and away from the hot exterior wall demonstrates reduced thermal stratification, improved airflow characteristics, and weaker vortex formation, making it the most favorable configuration. From an architectural perspective, these findings highlight the importance of early coordination between ventilation design and office spatial planning, as diffuser placement directly influences occupant comfort zones and furniture layout. Moreover, the preference for mid-wall installations supports a more flexible façade design and allows for greater freedom in organizing workspaces without compromising thermal performance. Full article

Gas–liquid–solid (G-L-S) mechanically agitated reactors are commonly used in chemical, pharmaceutical and bioprocessing applications due to their low operating costs and controlled and effective mixing. Computational Fluid Dynamics (CFD) is a powerful tool that enhances the understanding of flow dynamics, phase interactions and reactor performance. However, the CFD modeling of G-L-S mechanically agitated reactors is not extensively studied in the literature due to complex multiphase interactions, along with reactor design variations. This paper provides a critical synthesis of the literature, offering an overview not only of G-L-S stirred tank CFD modeling approaches but also of practical guidance on their selection and validation. Emerging high-resolution experimental techniques such as Electrical Resistance Tomography (ERT) coupled with pressure transducers, and Machine Learning (ML) models combined with experimental data, look promising to overcome current three-phase validation limitations. Future work to enhance predictive capabilities and reactor design and operation includes developing real-time digital twins, physics-based ML models and/or hybrid CFD-ML models. Full article

Chromium (Cr) exists in multiple oxidation states, with Cr(III) and Cr(VI) being the most environmentally and industrially relevant due to their distinct toxicity profiles and chemical behaviour. This study presents a comprehensive method that combines chemical simulation modelling, emission spectroscopy for quantification, and the controlled laboratory production of Cr species. Key findings include that acid digestion effectively extracted the Cr(III) and total Cr species, while thermodynamic modelling forecasted their stability and speciation under various environmental conditions. Thematic analysis indicates that the current quantification of Cr species is still in early development and remains centralized. Mineralogical and surface investigations showed that samples 1 and 2 have a BET surface area below 1 m²/g, whereas samples 3 and 4 exceed this. All samples are crystalline, with approximately 54.3 weight percent Cr₂O₃, 7.3 weight percent SiO₂, 17.75 weight percent of MgO, and 8.3 weight percent Al₂O₃, suggesting Al and Fe²⁺ replacement of Cr in the spinel structure. Computational fluid dynamics (CFD) modelling revealed that longer residence times are necessary for higher Cr metallization under H₂-CH₄-reducing conditions, and accurately predicted carbon deposition on pellets. These results demonstrate that CFD can optimize the H₂:CH₄ ratio to minimize carbon deposition and enhance gas transport to reaction sites. Full article

This is a review article that covers the history of the development of the equation of motion for solid particles in fluids, starting with the early work, before the Navier–Stokes equations were developed. Particular emphasis is placed on the development of the transient equation of motion, which features the history (or memory) term and the added mass (virtual mass) term. The salient features of the equation and the methods of their derivation are pointed out. Creeping, non-inertia flows as well as advective flows are surveyed, with particular emphasis on their effects on the functional form of the history term. Modifications to the hydrodynamic force due to possible interface slip are also examined. The review also deals with the inclusion of the weaker lateral (lift) forces and the inclusion of the effects of Brownian movement, which gives rise to thermophoresis—an important source of nanoparticle movement and surface deposition. The drag on irregularly shaped particles—another important feature of nanoparticles—is also examined. The review concludes with a short section on significant unknown issues and work that may be carried out in the near future for the theoretical and computational development of the subject. Full article

The problem of the post-harvest loss of perishable products has been a loss facing food security, especially in areas that lack adequate cold chain facilities. This issue is directly connected with sustainability objectives because post-harvest losses are the major source of food wastage, unneeded energy use, and related greenhouse gas emissions. Cold storage with phase-change material (PCM) is a promising alternative, as it aims at stabilizing temperatures and enhancing energy consumption, but current analyses of performance have been conducted through experimental testing and computational fluid dynamic (CFD) simulations, which are precise but computationally expensive. To handle this drawback, the current work constructs a machine learning predictive model to predict the dynamics of charging and discharging temperature of PCM cold storage systems. Four regression models, namely Random Forest, Extreme Gradient Boosting (XGBoost), Support Vector Regression (SVR), and K-Nearest Neighbors (KNNs), were trained and tested on experimental datasets that were obtained for varying storage layouts. The various error and accuracy measures used to determine model performance comprised MSE, MAE, R², MAPE, and percentage accuracy. The findings suggest that Random Forest provides the best accuracy during both the charging and the discharging process, with the highest R² values of over 0.98 and with minimal mean absolute errors. The KNN model was competitive in the discharge process, especially in cases of consistent thermal recovery patterns, and XGBoost was consistent in layout accuracy. However, SVR had relatively lower robustness, particularly when using nonlinear charged dynamics. Among the evaluated models, the Random Forest algorithm demonstrated the highest predictive accuracy, achieving coefficients of determination (R²) exceeding 0.98 for both charging and discharging processes, with mean absolute errors below 0.6 °C during charging and 0.3 °C during discharging. This paper has proven that machine learning is an efficient surrogate to CFD and experimental-only methods and can be used to predict the thermal behavior of PCM quickly and precisely. The proposed framework will allow for developing cold storage systems based on energy efficiency, low costs, and sustainability, especially in the context of decentralized and resource-limited agricultural supply chains, with the help of quick and data-focused forecasting of PCM thermal behavior. Full article

While fixed, unactuated rotor tilt is increasingly utilised in commercial multi-rotor unmanned aerial vehicles (UAV), its impact on forward flight performance remains poorly documented in the literature. The current work addresses this gap in the literature by systematically quantifying the performance trade-offs of rotor tilt across various airspeeds. Furthermore, a novel rotor configuration is proposed to mitigate some of the tilted rotor configuration’s inherent drawbacks. The different configurations are evaluated using a computationally affordable numerical approach that combines steady-state computational fluid dynamics (CFD) simulations, a simple proportional–integral (P–I) trimming algorithm, and actuator disk rotor modelling (ADM). The findings reveal that the aircraft’s power requirements can be reduced by more than 29% for airspeeds greater than 20 m/s, while its range can be increased by up to 22% with the alternative rotor configurations. However, the modifications were found to have a significantly lesser impact on endurance, as only a 2.9% increase is noted at best. Full article

This study presents a microfluidic platform for non-Newtonian fluid viscosity sensing, integrating a high-flow-rate flow field stabilizer to mitigate flow uniformity limitations under elevated flow rate conditions. Building upon an established dual-phase laminar flow principle that determines relative viscosity via channel occupancy, this research aimed to extend the measurable viscosity range from 1–10 cP to 1–50 cP, which covers viscosity regimes relevant to biomedical fluids, dairy products during gelation, and low-to-moderate viscosity industrial liquids. A flow stabilizer was developed through computational fluid dynamics simulations, optimizing three key design parameters: blocker position, porosity, and the number of outlet paths. The N5 design proved most effective, providing over 50% reduction in standard deviation for asymmetric velocity distribution in high-flow simulations. The system was validated using simulated blood and dairy samples, achieving over 95% viscosity accuracy with less than 5% sample volume error compared to conventional viscometers. The chip successfully captured viscosity transitions during milk acidification and gelation, demonstrating excellent agreement with standard measurements. This low-volume, high-precision platform offers promising potential for applications in food engineering, biomedical diagnostics, and industrial fluid monitoring, enhancing microfluidic rheometry capabilities. Full article

Natural ventilation, as a key passive strategy in building energy-efficient design, holds potential for reducing energy consumption and improving indoor air quality in high-rise office buildings and contributes directly to the advancement of sustainable urban development. However, its application in cold regions during winter is constrained by the conflict between low outdoor temperatures and indoor heating demands. Perforated panel external windows, as a novel ventilation form, can maintain the integrity and safety of the building curtain wall while ensuring ventilation rates through reasonable perforation design. Nevertheless, their ventilation performance and winter applicability lack systematic research. This paper combines wind tunnel tests and Computational Fluid Dynamics (CFD) simulations to validate the effectiveness of the porous medium model in simulating ventilation through perforated panels and systematically analyzes the impact of window opening size and perforation rate on ventilation effectiveness. Furthermore, taking Beijing as an example, the study explores ventilation effectiveness and the indoor thermal environment under different window opening forms and proportions during winter in cold regions. Results indicate that ventilation effectiveness primarily depends on the effective ventilation area and has little correlation with the window opening size. Under winter conditions, rationally controlling the window opening proportion and perforation rate can achieve effective ventilation while maintaining the indoor minimum temperature (≥18 °C). The ventilation strategies proposed in this paper provide a theoretical basis and practical guidance for the natural ventilation design of high-rise office buildings that balances energy savings and comfort during the cold season. The proposed ventilation strategies provide practical guidance for sustainable design in high-rise office buildings, offering a viable pathway toward energy-saving, healthy, and climate-responsive built environments during the heating season. Full article

Bariatric surgery is an effective treatment for morbid obesity but is frequently complicated by anastomotic leaks, fistulas, and strictures, which can significantly impair patient outcomes. Optimal management of these complications relies on a timely and accurate diagnostic assessment; however, effective treatment strategies are central to improving clinical recovery. This review primarily focuses on the endoscopic management of post-bariatric surgery complications, while providing a concise overview of the diagnostic imaging modalities that guide therapeutic decision-making. Contrast-enhanced imaging techniques, including computed tomography (CT) and fluoroscopy, as well as endoscopic ultrasound (EUS), are briefly discussed in relation to their role in identifying complications, defining their extent, and selecting the most appropriate endoscopic intervention. The core of this review is dedicated to current endoscopic treatment approaches, including endoscopic internal drainage with double pigtail plastic stents, self-expanding metal stents (SEMSs), endoscopic vacuum therapy (EVT), and EUS-guided drainage of fluid collections. Particular emphasis is placed on indications, technical considerations, and outcomes of these therapies. Finally, this review highlights emerging endoscopic technologies that may further optimize the management of post-bariatric surgery complications and improve patient outcomes, underscoring the evolving role of minimally invasive endoscopic treatment within a multidisciplinary framework. Full article

Pediatric odontogenic tumors are rare but are frequently overlooked because they often mimic simple cysts on routine radiographic examinations. The radiographic appearance on panoramic imaging and cone-beam computed tomography (CBCT) frequently does not correlate with the true biological nature of these lesions. On CBCT, classic odontogenic tumors often demonstrate mixed radiolucent–radiopaque patterns with ill-defined borders, internal calcifications, septations, or other structural features. The diagnostic challenge arises when an odontogenic tumor mimics a unilateral, well-defined radiolucent area or a cystic lesion with clear borders and no associated tooth displacement, erosion, root resorption, or cortical bone dehiscence. Panoramic radiography has inherent diagnostic limitations but remains widely used for routine dental screening. CBCT provides enhanced three-dimensional assessment and improves diagnostic accuracy in the evaluation of jaw lesions. A marked increase in dental follicle diameter necessitates differentiation between cystic transformation, inflammatory processes, and other odontogenic pathologies. Cortical swelling and bone asymmetry warrant careful evaluation. In this context, an atypical cyst-like lesion detected on routine panoramic radiography prompted a needle aspiration biopsy, which revealed a dry tap and suggested a solid lesion. This prompted CBCT evaluation. Two juvenile cases are presented in which clinical findings, panoramic radiography, and CBCT provided discordant diagnostic impressions of cystic-appearing lesions with well-defined borders and bone expansion. These cases illustrate a diagnostic pathway in which imaging demonstrates a cyst-like appearance with benign radiological features, fine-needle aspiration biopsy reveals the absence of cystic fluid, and histopathology confirms that radiology alone cannot reliably distinguish true cysts from solid odontogenic tumors in pediatric patients. Full article

High-speed rotating machinery often demands bearings with superior load capacity and thermal stability. Here, a four-chamber radial hydrodynamic sliding bearing using supercritical carbon dioxide (S-CO₂) as a lubricant is investigated to address these requirements. The work is carried out on the ANSYS Workbench 2024 R1 platform. Computational fluid dynamics (CFD) and structural mechanics are combined to build a fluid–structure interaction (FSI) numerical model. The model accounts for real-gas thermophysical property variations. S-CO₂ properties are dynamically retrieved using the REFPROP database and MATLAB curve fitting. Unlike previous studies that mainly focused on hydrostatic structures and general parameters, this research examines hydrodynamic lubrication behavior under ultra-high-speed conditions. It systematically analyzes the effects of rotational speed on oil film pressure distribution, load capacity, friction coefficient, and housing deformation. It also investigates cavitation characteristics in a specific speed range. Simulation outcomes reveal that higher rotational speeds lead to an increase in both oil film load capacity and peak pressure. In particular, when the speed rises from 4000 r/min to 12,000 r/min, the maximum positive pressure increases from about 10 MPa to approximately 10.4 MPa. Meanwhile, the negative pressure region becomes significantly larger, which raises the cavitation risk and indicates a less stable lubrication state at very high speeds. These results confirm that lubrication simulations incorporating real-gas effects can reliably represent the operating behavior and provide useful guidance. It also provides new theoretical support for the design optimization and engineering application of S-CO₂-lubricated bearings in high-speed machinery. Full article