The primary objectives of this study were (1) to analyze and compare the outcomes of manual calculations and computational fluid dynamics (CFD) simulations in determining the forces exerted by water flow and (2) to evaluate the effectiveness of a mathematical model as a pedagogical tool for teaching fluid mechanics to undergraduates. The sample included 30 mechanical engineering undergraduates from the Faculty of Engineering, Rajamangala University of Technology Lanna, Phitsanulok, divided into two groups of 15 students each. Research instruments comprised (1) commercial CFD software for fluid force calculations, (2) pre- and post-tests assessing students’ understanding of momentum and energy equations in water jet impact, and (3) a questionnaire measuring satisfaction with software integration in the learning process. Data were analyzed using descriptive statistics (mean and standard deviation). The findings showed that both groups achieved higher post-test scores than pre-test scores, indicating a positive impact on knowledge development. The quality evaluation of instructional media in terms of numerical modeling for design calculation yielded a mean score of 4.59 with a standard deviation of 0.52. Likewise, instructional worksheets and exercises received mean scores of 4.60, with standard deviations of 0.42 and 0.50, respectively. An experimental trial with 15 students in Group 2 revealed that the average accuracy in completing worksheets and exercises (E1) was 80.13%, while the average post-test score (E2) was 82.77%. Efficiency analysis confirmed that all values exceeded the 80% criterion, and post-test scores were significantly higher than pre-test scores at the 0.05 level. Students’ satisfaction with the instructional approach was also rated as “very high.” Overall, the results demonstrate that integrating CFD software with practice-based learning effectively enhances students’ understanding of fluid mechanics and improves academic performance.

This paper reports on the study of turbulence at various locations in Hong Kong during Typhoon Wipha in July 2025, including turbulence intensity based on Doppler Light Detection and Ranging (LIDAR) systems and radiosondes, observations by microclimate stations, and low-level windshear and turbulence at the Hong Kong International Airport (HKIA) by LIDAR, flight data, and pilot reports. Although the observation period was primarily limited to 20 July 2025, passage of a typhoon over a densely instrumented urban area is uncommon; these observations on turbulent flow associated with typhoons therefore can serve as valuable benchmarks for similar studies on turbulent flow associated with typhoons in other coastal areas, particularly for operational alerts in aviation. To assess the predictability of turbulence, the eddy dissipation rate (EDR) was derived from a high-resolution numerical weather prediction (NWP) model using diagnostic and reconstruction approaches. Compared with radiosonde data, both approaches performed similarly in the shear-dominated low-level atmosphere, while the diagnostic approach outperformed when buoyancy became important. This result highlights the importance of incorporating buoyancy effects in the reconstruction approach if the EDR diagnostic is not available. The high-resolution NWP was also used to provide time-varying boundary conditions for computational fluid dynamics simulations in urban areas, and its limitations were discussed. This study also demonstrated the difficulty of capturing low-level windshear encountered by departing aircraft in an operational environment and demonstrated that a trajectory-aware method for deriving headwind could align more closely with onboard measurements than the standard fixed-path product.

The role of spatial distance in SARS-CoV-2 nosocomial transmission.

Improvement of the aerodynamic characteristics of a high-speed hair dryer impeller based on computational fluid dynamics simulation

Optimization of operating conditions for egg setters using computational fluid dynamics simulations.

Self-regulating microfluidic system for lipid nanoparticle production.

Optimized personnel flow with minimal contamination: development and validation of an air-barrier cleanroom for cell products processing.

Optimizing topical delivery to the ostiomeatal complex after functional endoscopic sinus surgery using a bidirectional delivery method.

Review on computational fluid dynamics (CFD) modeling and simulation of CO2 adsorption

Evaluation of the application effect of surface immobilization technology on fuel ethanol production at industrial scale.

This research investigates both physics of fluids in Martian atmosphere over the vertical axis wind turbine (VAWT) and also examines the power performance of the turbine under different geometrical features. Computational fluid dynamics simulations of VAWTs are inherently challenging, as the blades in the downstream region are impacted by the wakes generated by the upstream blades. Furthermore, the distinct flow behavior caused by the low atmospheric density on Mars adds another layer of complexity, making this research both unique and technically demanding. The reduced atmospheric density on Mars leads to Reynolds numbers that differ substantially from those under terrestrial conditions, influencing boundary layer development and separation, and thereby altering the associated vorticity dynamics. Incorporating winglets into the blade design resulted in a maximum power coefficient (CP) of 0.2, demonstrating their effectiveness in significantly reducing tip vortex formation along the blade span. This CP value is consistent with the results reported by Kumar et al., who employed the double-multiple stream-tube method—which inherently neglects tip vortex effects—thereby supporting the validity of the current simulation approach. Results indicate that winglets are more effective than endplates, enabling greater power extraction from the turbine. Furthermore, the impact of dome placement—both with and without winglets—is investigated, and the results demonstrate that the maximum power performance of the VAWT increases significantly due to the accelerated flow over the dome.

Transfer learning from computational fluid dynamics simulation data to experimental data for the fault diagnosis of axial piston pumps

Augmenting water quality resilience in water distribution systems: A stress-driven model for ice slurry pigging optimisation strategy.

Anion Exchange Membrane Water Electrolysis (AEMWE) technology plays an important role in achieving efficient and sustainable energy conversion. There are many factors contributing to the performance of the AEMWE. This study aims to investigate the effects of parallel flow field design on fluid transport within AEMWE systems. While PEMWE properties are well-documented, comprehensive analysis of AEMWE performance, especially regarding catalysts, flow fields, and bipolar plate fluid dynamics, remains limited. Advancements in these areas are crucial for enhancing electrolyzer efficiency and durability. Through ANSYS Fluent Computational Fluid Dynamics (CFD) simulations, seven flow field models were evaluated, revealing the critical influence of flow field geometry on pressure distribution, hydrogen concentration, and current density. The single-inlet parallel flow field design demonstrated superior pressure uniformity and operational simplicity, with an optimal channel-to-rib ratio of η = 1, improving both efficiency and manufacturability. The results also show that while increasing voltage enhances hydrogen production, it introduces flow turbulence and localized flooding risks, necessitating precise control of operational parameters. The simulation achieved a hydrogen concentration of 35.52 mol/m³ under standard operating conditions, with an improved RMSE of 0.0274, reflecting better accuracy than earlier models. These findings underscore the importance of optimizing both geometric and operational factors to enhance the performance and reliability of AEMWE systems. This research opens the path for efficient energy conversion processes and contributes to the advancement of sustainable energy technologies.

The global transition towards sustainable energy has intensified the need for alternative power generation technologies, particularly in regions with limited natural resources. Wind energy is a promising option; however, in Malaysia the average wind speed is approximately 2 m/s, which is insufficient for the efficient operation of conventional horizontal-axis wind turbines that generally require at least 4 m/s. This study investigates the potential of Vortex Bladeless Wind Turbines (VBWT), which harness vortex-induced vibrations rather than rotational blades, as a feasible solution for low wind speed environments. Three configurations, namely simple cylindrical, conical cylindrical and complex cylindrical, were evaluated using a comprehensive methodology consisting of a literature review, comparative analysis with a Pugh matrix, and computational fluid dynamics (CFD) simulations. Validation was conducted using real wind and temperature data from Klebang Besar, Melaka, Malaysia. The findings reveal that the simple cylindrical VBWT demonstrates superior aerodynamic stability, a smaller wake-rotation region and lower drag values compared to the other designs. At a wind speed of 1.32 m/s, the simple cylindrical configuration achieved a drag coefficient of 0.37, indicating consistent energy capture efficiency under low wind conditions. In contrast, the conical and complex cylindrical designs exhibited higher turbulence and drag coefficients, limiting their effectiveness. This study concludes that the simple cylindrical VBWT is the most promising design for Malaysia’s wind conditions, with further research recommended on structural durability, optimisation of energy output and economic viability for large-scale deployment.

To investigate the advantages of microstructure in enhancing multiple performance characteristics of conveyor idler bearings and other friction pairs in open-pit coal mines, this study conducted computational fluid dynamics (CFD) simulations on NU205 cylindrical roller bearing. Based on the structural features of prototype bearings, we designed an elliptical-opening offset parabolic microstructure (hereinafter referred to as EOOPT) configuration for the inner raceway surface. Response surface analysis was employed to investigate the influence patterns of microstructure characteristic parameters on bearing performance. Through multi-objective optimization design, optimal microstructure parameters were determined. Comparative analysis with prototype bearings demonstrated that the optimized microstructure significantly improved average bearing pressure by 15.58% while reducing average friction coefficient by 16.33%, temperature by 9.28%, and wear volume by 6.37%. Experimental studies revealed the influence of microstructure column count on vibration suppression characteristics, temperature stability, and torque variation. This study innovatively designs an elliptical-opening offset parabolic microstructure (EOOPT) for cylindrical roller bearings in open-pit coal mines-filling the gap in existing research that lacks exploration of non-simple microstructure opening shapes, cross-sectional depth optimization, and their integrated impact on bearing thermal stability; meanwhile, it establishes a multi-objective optimization model for EOOPT parameters, realizing the synergistic improvement of bearing load capacity, friction reduction, and vibration suppression, which is rarely reported in studies on mine conveyor bearings.

Recent studies have demonstrated the potential of hyperbolic paraboloid (hypar), a doubly curved geometry, in coastal engineering applications. Predicting pressure distribution, critical for subsequent finite element analysis, on such novel three-dimensional structures require Computational Fluid Dynamics (CFD) simulations, which are computationally intensive. To address this challenge, the current study develops an artificial neural network (ANN) surrogate to predict pressure distributions on hypar free-surface breakwaters (FSBWs) under solitary wave loading. Using Smoothed Particle Hydrodynamics (SPH) as the CFD tool, simulations generate the supervised learning dataset, where inputs are the hypar warping Rn, breakwater draft dr, and wave height H. The targets consist of two 30×30 pressure maps at wave arrival (hydrostatic) and peak, together with the wave rise time {P(t0), P(tpeak), Δt=tpeak−t0}. Three architectures, FNN, CNN, and DeepONet, are trained with homoscedastic uncertainty loss weighting, each at two parameter sizes (~50k and ~500k). Results for training and testing show that all models achieve low errors, with models with ~50k parameters found to be sufficient, and scaling to ~500k yields some generalization improvement. Further reducing the parameters (~5k) degrades accuracy for all models, with DeepONet proven most robust to parameter size reduction. Overall, this study introduces a novel SPH-ANN workflow for predicting wave pressures on hypar FSBWs, where inference on new samples occurs in a few milliseconds per sample, delivering orders-of-magnitude speedups relative to running new SPH simulations. This computational efficiency enables rapid design iteration and optimization of hypar FSBWs, facilitating their potential deployment in coastal defense.

Convective losses due to wind affect the thermal efficiency of external central receivers of solar power towers (SPT), but their full characterization is still an unresolved question. Furthermore, detailed assessment of these convective losses in new designs, such ribbed tube central receivers, is nearly inexistent. The aim of this study is (a) to parameterize the wind convection coefficient and its local distribution in all the tubes and panels of an external central receiver, and (b) to compare the wind convection coefficients in conventional plain tube receivers and in ribbed tubes receivers designed to enhance heat transfer from the tube wall to the heat transfer fluid (HTF). To gain a detailed understanding of the complex heat transfer phenomena involved, this work is entirely developed through Computational Fluid Dynamics (CFD) simulations in a three-dimensional (3D) domain that describes all the absorber tubes in the receiver. Overall results of the simulations are practically validated against experimental results available in the literature [1].

Computational Fluid Dynamics (CFD) on unstructured meshes are widely used to simulate complex flow problems. Geometric Multigrid (GMG) is an essential method to accelerate CFD simulations. However, achieving high efficiency and scalability for unstructured geometric multigrid CFD is very challenging, due to data conflicts or data dependencies at shared-memory level as well as communication bottlenecks at distributed-memory level. Traditional hybrid parallelization schemes, which typically employ domain decomposition for MPI at distributed-memory level and mesh coloring for OpenMP at shared-memory level, fail to scale on modern HPC architectures. This paper proposes an efficient and scalable hybrid parallelization scheme for unstructured geometric multigrid CFD. To begin with, we extend our previous work 1 , the Task Dependency Tree (TDT) approach [33], to expose shared-memory parallelism from unstructured mesh computations while respecting both data conflicts and data dependencies. We adapt TDT to handle multiple GMG levels with complex mesh boundaries. TDT can be implemented using a task-based programming model such as OpenMP task , which offers a unique opportunity to fine-grained computation-communication overlap in hybrid parallelization. Therefore, at distributed-memory level we introduce the one-sided asynchronous multithreaded Partitioned Global Address Space (PGAS) model, and develop a PGAS+TDT hybrid scheme. We propose an adaptive scheduling strategy to maximize the overlap of communication and computation tasks in our hybrid scheme. Our work was implemented and evaluated in a production-level unstructured CFD software on both x86 and ARM multi-core architectures. On a single compute node, TDT dramatically outperforms the prior shared-memory approaches, delivering a speedup of up to 5.2 ×. For large-scale tests, our PGAS+TDT hybrid scheme enhances performance by up to 2.0 × over the engineer-tuned MPI-only version, with a strong scalability of about 70% when scaling to 128 compute nodes.

This study focuses on the suitability of Core Annular Flow (CAF) technologies for transporting heavily viscous oil lubricated with water in a horizontal conduit. Using Computational Fluid Dynamics (CFD) and Large Eddy Simulation (LES) techniques with ANSYS Fluent software (Ansys 2022 R2), the research aims to analyze the flow behaviour of heavy oil-water mixtures in horizontal pipes. Specifically, the study examines turbulent CAF to gain insights into how gravity influences the three-phase flow of heavy oil, water, and air. The simulations consider standard horizontal pipes and explore the impact of temperature variations and the presence of air on the annular flow’s behaviour and pressure gradients. The study’s findings, supported by both simulated and experimental results from literature, demonstrate consistent outcomes and contribute to understanding the effectiveness of LES in modelling such complex flows. Overall, this work is novel because it uses an integrated approach to apply advanced numerical techniques, such as LES, to heavy oil, water, and air flows in a horizontal pipe. This approach advances both fundamental understanding and real-world applications in industrial contexts.