3D Computational Fluid Dynamics Research Articles

Characteristics of transition to turbulence in a healthy thoracic aorta using large eddy simulation

This study employed large eddy simulation (LES) with the wall-adapting local eddy-viscosity (WALE) model to investigate transitional flow characteristics in an idealized model of a healthy thoracic aorta. The OpenFOAM solver pimpleFoam was used to simulate blood flow as an incompressible Newtonian fluid, with the aortic walls treated as rigid boundaries. Simulations were conducted for 30 cardiac cycles and ensemble averaging was employed to ensure statistically reliable results. Main hemodynamic parameters, such as velocity fields, turbulence intensity turbulent kinetic energy (TKE), oscillatory shear index (OSI) and wall shear stress (WSS), were analyzed throughout the circulatory system. Through 3D computational fluid dynamics (CFD) visualization, we explained the transition from laminar to turbulent flow and its development throughout the cardiac cycle. The results demonstrated that turbulence originates in the aortic arch following the peak systole phase and further develops in the aortic arch and descending aorta during the mid-deceleration and end-systole phases, with the maximum turbulence intensity exceeding 25%. WSS reached up to 30 Pa during the peak systole, with an average WSS of 6.5 Pa across the cardiac cycle. Low and oscillatory WSS were observed during diastole which can potentially contribute to the development of vascular diseases including, aortic dissection and atherosclerosis.

Comparative Aerodynamic Analysis and Parallel Performance of 2D CFD Simulations of a VAWT Using Sliding Mesh Interface Method

ABSTRACTWith rapid advancements in computer hardware and numerical modeling methods, Computational Fluid Dynamics (CFD) has gained prominence in simulating complex flows. As parallel computation becomes an industry standard, the computational efficiency of simulations has become critical. The flow around a Vertical Axis Wind Turbine (VAWT), characterized by complex dynamics and challenging rotating geometry, serves as an intriguing case for CFD studies. This study employs the open‐source CFD solvers SU2 and OpenFOAM to simulate the incompressible, unsteady, and turbulent flow around an H‐type Darrieus VAWT in two dimensions. Spatial and temporal discretization parameters are examined to balance computational cost and accuracy, revealing notable effects on power predictions. Simulations conducted under identical conditions allow for a comparison of the predictions and parallel performances of SU2 and OpenFOAM across three distinct tip speed ratios (TSRs). The findings show that discretization parameters behave differently at various TSRs. While power predictions from SU2 and OpenFOAM generally align with experimental data and with each other, discrepancies arise at lower TSRs, with thrust predictions showing better consistency. Although OpenFOAM provides a faster solution across all parallel configurations, SU2 demonstrates superior parallel scalability, achieving higher speedup and efficiency.

Development of a prototype spoiler for effective braking of a racing motorcycle, utilizing active aerodynamics

High-level competition motorcycles have incorporated "wings," regulated by the rules of the championships in which they are used. This article highlights the importance of these aerodynamic modifications to improve performance during braking and direction changes, crucial aspects in motorcycle competitions. Previous studies have evaluated how the wings in MotoGP increase drag and lift force according to the lean angle, fundamental to understanding their impact on the aerodynamics of competition motorcycles. Despite existing research, more study is needed on static wings, motivating this work to explore the effects of active wings, similar to those in high-end cars and F1 single seaters, through 3D modeling and computational fluid dynamics (CFD) simulations. The goal is to design wings that generate variable downforce on the sides and rear, optimizing aerodynamics and dynamics in extreme corners, improving performance and safety.

Thermal analysis of mineral oil‐based nanofluids of distribution transformers exposed to simultaneous current and voltage harmonics

AbstractThe exact thermal evaluation of distribution transformers (DTs), which are critical and costly pieces of equipment for the power grids, may contribute to preventing the respective failures. Therefore, the present study non‐uniformly investigated DT for correct anticipation of hotspot temperature (HST). Optical fibre sensors (OFSs) were applied for assessing our newly developed non‐uniform 3D computational fluid dynamic (CFD)‐based modelling while performing the temperature rise test (TRT). It should be noted that this new 3D CFD‐based thermal analysis showed an error percentage of 0.11% (0.1°C) in comparison to the OFS measurement, reflecting the ideal efficiency and accuracy of the model. Moreover, thermography for both top‐oil temperature (TOT) and bottom‐oil temperature (BOT) was employed to validate the results from non‐uniform 3D (three‐dimensional) CFD‐based thermal evaluations. The results indicated an acceptable level of relationship between thermography and thermal analysis of 3D CFD at the specified two spots, with an error percentage of <0.65%, demonstrating the acceptable accuracy of the new non‐uniform 3D CFD‐based model. In the following, yet importantly, the new non‐uniform 3D model was subjected to the total harmonic distortions (THD) for the current and voltage of 5%, 10%, and 15%, which raised the HST more than the original model without harmonics by 3.3°C, 7.1°C, and 10.3°C, respectively. Ultimately, different mineral oil‐based nanofluids’, such as multi‐walled carbon nanotubes (MWCNTs) and diamond nanoparticles, influence on the HST decrement of DT in simultaneous current and voltage harmonics was investigated.

Three-Dimensional Pulsating Flow Simulation in a Multi-Point Gas Admission Valve for Large-Bore CNG Engines

This study examines the dynamic fluid behavior of a PWM-controlled Solenoid-Operated Gas Admission Valve (SOGAV) for large-bore CNG engines using 3D Computational Fluid Dynamics (CFD) simulations with dynamic mesh techniques. The research focuses on the influence of orifice geometry variations in the multi-hole restrictor and pressure differentials between the inlet and outlet on flow stability, turbulence, and valve performance. Results demonstrate that multi-hole restrictors with different-sized orifices improve flow uniformity and reduce turbulence, thereby mitigating flow resistance. Transient simulations further reveal standing wave formation and pressure wave interference, emphasizing that steady-state models cannot capture critical transient phenomena, such as accelerated and decelerated jet-like flows and flow separation. These findings provide key insights into SOGAV optimization, contributing to enhanced fuel efficiency and engine responsiveness, meeting the performance requirements of modern gas engines.

Numerical study of engine room air ventilation systems for landing ship tank class warships in supporting crew comfort and safety

Abstract The air ventilation system is one of the supporting systems in the machinery of a warship. High temperatures in the engine room can lead to an unpleasant atmosphere and, in particular, to heat stress for the operating personnel. This heat stress was caused by the design of the engine room ventilation system not meeting the requirements due to the supply and exhaust fan. Under the given conditions, the air temperature reached 50 °C, higher than the standard 45 °C. Therefore, it was necessary to conduct a thermal analysis and redesign the ventilation system using a 3D CFD (Computational Fluid Dynamic). The parameters included temperature distribution, Hlow distribution, and Hlow velocity in the engine room of the Landing Ship Tank class warship when the engine load reached 50%, 75%, and 100%. The results obtained from the simulation were in the form of quantitative data such as temperature gradients and iso contours of the air in the engine room inside the warship. The data comprised velocity contours, temperature, velocity vectors, streamlines, and particle trajectories in space. The results of the CFD approach showed that the quality of the ventilation system in the engine room inHluences extreme conditions in the engine room.

Performance of hump slab track in sandstorms using simulation and a wind tunnel experiment

Sandstorms have destructive effects on railway infrastructures due to the movement and erosion of sand. One of the proposed solutions to reduce the impact of windblown sand on desert railways is the hump slab track superstructure. This system entails removing the ballast layer and elevating the rails using concrete foundations called humps, which create sand movement channels beneath the rails. The hump’s geometry must not only meet optimal aerodynamic conditions but also ensure ample clearance for sand passage, maintaining structural stability and efficient railway performance. In this study, the aerodynamic evaluation of various hump geometry is examined considering the elliptical (EL) and semicircular-rectangular (CR) shapes. Simulations are carried out using 3D computational fluid dynamics in ANSYS Fluent software. A gas–solid two-phase model, comprising a distinct phase for sand particles and another for air, is developed to assess the sand movement capacity through the selected hump geometries. A wind tunnel experiment is then performed on a prototype of a hump slab track to validate the software model. The findings highlighted that the CR shape, with a height of 25 cm, resulted in the most favorable outputs.

Power Loss and Electrothermal Characterization of Hybrid Power Integrated Modules for Industrial Servo Motor Drives

This study aims to facilitate the assessment of the electromagnetic-electrical-thermal coupled response of a developed 30 kHz/12 kW silicon carbide (SiC)/silicon (Si) hybrid power-integrated module (hPIM) during load operation. To achieve this goal, an efficient electromagnetic-circuit-thermal coupling (ECTC) analysis methodology is introduced. This ECTC methodology incorporates a fully integrated electromagnetic-circuit coupling (EMCC) analysis model for parasitic extraction in order to addressing their effects on power losses, and a simplified electrothermal coupling (SETC) analysis model for temperature evaluation in order to consider the coupling influence of the instantaneous junction temperature on instantaneous power losses. The SETC model couples a simple lookup table that maps the power loss (P) in terms of the temperature (T) constructed using the developed EMCC model, and an equivalent Foster thermal network model established through three-dimensional (3D) computational fluid dynamics (CFD) thermal flow analysis. This PT lookup table, replacing the tedious and time-consuming EMCC simulation, is responsible for fast estimation of temperature-dependent power losses. The proposed analysis models, namely the CFD, EMCC, and SETC analysis models, are validated through thermal experiments and detailed modeling. Finally, the influence of various operation conditions on the power losses of the hPIM during the power conversion operation is explored through parametric analysis.

Fluid and thermal effect on temperature-dependent power increase of electric vehicle's permanent magnet synchronous motor using compound water cooling method

Taking advantage of compound housing water jacket (HWJ) and hollow-shaft water jacket (SWJ) cooling based on the temperature-dependent power of permanent magnet synchronous motor (PMSM) is a solution for enhanced electric vehicle (EV) performance. The fluid and temperature field of a 40 kW PMSM at three typical continuous working points were studied, covering low to high speeds of EVs. The influence of different coolant flowrates on power of motor was obtained by multi-physics field coupling analysis method. The impact of current control modes was also investigated. 3D computational fluid dynamics (CFD) conjugate heat transfer calculation combined with 3D lumped parameter thermal network (LPTN) was adopted to calculate the flow and temperature. Temperature-dependent material properties were taken into consideration in electromagnetic finite element analysis (FEA). The models were modified and validated by experiments. Once compounding SWJ on the basis of a strong HWJ cooling, the PM temperature can continue to decrease over 20 degC. The insensitive characteristic of PM temperature towards SWJ flow rate was observed. Under constant current control mode, 3.8 %, 6 % and 4 % PMSM power enhancement by compound cooling were proved at three typical working points. Under current open-loop, 7 %, 16 %, and 10 % increases with compound cooling were confirmed.

Integrated DNN and CFD model for real-time prediction of furnace waterwall slagging of coal-fired boiler

Slagging of furnace waterwall adversely affects the thermal performance and increases the operation and maintenance costs of coal-fired boilers. A real-time slagging prediction model is of great significance for the plant operators to monitor the furnace slagging conditions and make appropriate operation of soot blowers to maintain the cleanliness of waterwall. Three-dimensional (3D) computational fluid dynamics (CFD) can predict detailed furnace slagging distributions, but its high computational cost has been the major impediment hindering its application in large-scale combustion systems that require real-time information. To resolve this problem, a CFD-based deep neural network (DNN) model framework was developed in this study to realize the real-time prediction of furnace wall slagging distribution. A 3D CFD model was first developed and employed to generate the slagging database under typical boiler operating parameters. Then this database was utilized to train the DNN model to capture the mapping relationship between boiler operating parameters and wall slagging distributions. The core idea of this CFD-based DNN model is to generalize the wall slagging distributions under different boiler operating conditions based on this mapping relationship learned by the DNN model. This model was applied to a 350 MW coal-fired boiler. The prediction results by the CFD model demonstrated that the boiler operating parameters, such as boiler load and coal burner swirling blade angle, have strong effects on furnace wall slagging distributions, while the DNN model could precisely capture their relationship and make predictions with deviation from the CFD results below 5 %. More importantly, the DNN model could give the prediction results within seconds that is three to four orders of magnitude faster than the CFD model. Thus, it can respond to the rapidly changing boiler operating conditions and realize the real-time prediction of furnace wall slagging distributions.

Evaluation of the effect of hemodynamic factors on retinal microcirculation by using 3D confocal image-based computational fluid dynamics.

To investigate local hemodynamic changes resulting from elevated intraocular pressure (IOP) in different vasculature networks using a computational fluid dynamics model based on 3D reconstructed confocal microscopic images. Three-dimensional rat retinal vasculature was reconstructed from confocal microscopy images using a 3D U-Net-based labeling technique, followed by manual correction. We conducted a computational fluid dynamics (CFD) analysis on different retinal vasculature networks derived from a single rat. Various venule and arteriole pressures were applied to mimic the effects of elevated intraocular pressure (IOP), a major glaucoma risk factor. An increase in IOP typically correlates with a decrease in venous pressure. We also varied the percentage of capillary dropout, simulating the loss of blood vessels within the capillary network, by reducing the volume of the normal capillary network by 10%, 30%, and 50%. Based on the output of the CFD analysis, we calculated velocity, wall shear stress (WSS), and pressure gradient for different vasculature densities. Arteriolar pressure, venular pressure, and capillary dropout appear to be important factors influencing wall shear stress in the rat capillary network. Our study revealed that the pressure gradient between arterioles and venules strongly affects the local wall shear stress distribution across the 3D retinal vasculature. Specifically, under a pressure gradient of 3,250Pa, the wall shear stress was found to vary between 0 and 20Pa, with the highest shear stress observed in the region of the superficial layer. Additionally, capillary dropout led to a 25% increase or decrease in wall shear stress in affected areas. The hemodynamic differences under various arteriole and venule pressures, along with different capillary dropout conditions, could help explain the development of various optic disorders, such as glaucoma, diabetic retinopathy, and retinal vein occlusion.

Development of a Machine Learning Natural Ventilation Rate Model by Studying the Wind Field Inside and Around Multiple-Row Chinese Solar Greenhouses

This paper experimented with a methodology of machine learning modelling using virtual samples generated by fast CFD (Computational Fluid Dynamics) simulations in order to predict the greenhouse natural ventilation. However, the output natural ventilation rates using fast two-dimensional (2D) CFD models are not always consistent with the three-dimensional (3D) one for all the scenarios. The first contribution of this paper is a proposed comparative modelling methodology between two-dimensional and three-dimensional CFD studies, regarding its validity, especially when buildings are in rows. The results show that the error of the ventilation rate prediction could exceed 50%, if 2D models are not properly used. Subsequently, in those scenarios where the 2D and the 3D models had equal accuracy, nearly one thousand samples were generated using fast 2D CFD simulations to train a natural ventilation rate regression tree model. This model is efficient to deal with the combined effect of wind pressure and thermal gradients under various vent configurations, with only four necessary inputs. In addition, by analyzing the wind speed distribution contour of the outdoor wind field around the greenhouse rows, the optimal wind speed-measuring locations were determined to eliminate interference for predicting the natural ventilation rate.

Liquid lithium divertor analysis using coupled plasma material interaction model

A liquid lithium divertor can improve performance of future fusion devices by creating efficient power exhaust and improving the energy confinement via pumping of the hydrogen isotopes. In addition, significantly higher heat fluxes can be handled if controlled vapor shielding is used to redistribute the divertor heat flux over a wider area. Design and optimization of such a system calls for an analysis model which includes a strong two-way coupling between the plasma and divertor material. The incoming plasma heat and particle flux will affect the divertor surface temperature, which is a defining factor of the lithium evaporative and sputtered flux going into the plasma. Results of the coupled model based on the plasma edge code SOLPS-ITER and the computational fluid dynamics (CFD) code ANSYS-CFX will be presented for different configurations. An analytical slab flow model is used as a heat transfer boundary condition for SOLPS, defining particle flux from the wall via calculation of the surface temperature. At the final step, results of the SOLPS analysis are verified using a 3D CFD magnetohydrodynamics (MHD) analysis which uses heat and particle flux from SOLPS as a boundary condition. In addition to plasma heat flux, both analytical and CFD temperature models include several plasma material interaction effects, such as lithium evaporation, condensation and sputtering based on deuterium target flux. New adatom sputtering model based on the available experimental data is presented. Analytical model is expanded to include free surface axisymmetric configurations. Results of parametric studies of the divertor configurations with different lithium inlet temperature and velocity will be presented leading to the optimal design resulting in the lowest possible lithium contamination in the core.

Optimizing supply conditions and use of return air in UFAD system: Assessment of IAQ, thermal comfort and energy performance

This study is the first to optimize the use of return air, along with other supply conditions, in underfloor air distribution (UFAD) systems to achieve acceptable indoor air quality (IAQ) and thermal comfort while minimizing energy consumption. A comprehensive 3D computational fluid dynamics (CFD) model has been developed to simulate airflow patterns, thermal fields, and CO2 distribution in a standard office environment. The CFD approach used in this research has been validated against experimental data found in the literature. A parametric study was conducted, varying supply diffuser size, supply air velocity and temperature, and the return air ratio to identify the optimal UFAD system settings. These settings aim to minimize energy use while keeping CO2 levels within the recommended 1100 ppm in the breathing zone and ensuring that the percentage of people dissatisfied (PPD) remains at 10%. The findings indicate that using a 20 cm × 20 cm supply diffuser, setting the supply air temperature to 17°C, supply velocity to 1.2 m/s, and recirculating 29% of the return air will result in optimal performance.

Spatially Resolved Measurements in a Stagnation‐Flow Reactor: Kinetics of Catalytic NH3 Decomposition

AbstractA stagnation‐flow reactor was employed to investigate the decomposition of ammonia over a Ni/Al2O3 catalyst across a range of system pressures and ammonia mole fractions. The results indicate that the system pressure has a negligible impact on the light‐off behavior and the concentration profiles of NH₃. A comparison of 1D modelling with 3D computational fluid dynamics (CFD) computations justifies the use of the simpler flow model. Good agreement between experiments and the 1D simulation is achieved for two different kinetic models from literature in the mainly diffusion‐controlled regime. For lower temperatures, at which the process is kinetically controlled, the two mechanisms exhibit significant differences. The stagnation‐flow reactor concept is shown to be a promising tool for understanding, developing, and validating the reaction kinetics of heterogeneous catalytic processes.

Numerical study of fluid-structure interaction for enhanced heat transfer in microchannels with an oscillating elastic wall

The present numerical study explores the performance of fluid-structure interaction (FSI) in a microchannel with an oscillating elastic wall. A two-dimensional (2D) Computational Fluid Dynamics (CFD) simulation was performed to investigate the influence of the elastic wall's frequency and amplitude on fluid flow behavior, pressure drop, and heat transfer enhancement. The FSI governing equations were solved using the Arbitrary Lagrangian-Eulerian (ALE) method. The results indicated that the Nusselt number (Nu) decreases as oscillation frequency increases. In contrast, the Nu increased linearly with the oscillation amplitude. Additionally, the Prandtl number (Pr) showed an insignificant influence on the Nu number for the studied operating range. An optimal operating condition was identified for the microchannel with an oscillating wall, achieving a spatial average Nu number of 16.796 compared to 14.577 for a simple microchannel channel, representing a 15.23 %% enhancement in heat transfer. A correlation is derived for the spatial average Nu number as a function of the Reynolds number (Re), Strouhal number (St), Pr, and vibration amplitude ratio, providing a valuable tool for designing and optimizing microchannel systems with FSI. Finally, the Maxwell boundary conditions are incorporated into the simulation of a microchannel with a vibrating upper wall to evaluate the slip conditions.

Mathematical Approach for Directly Solving Air–Water Interfaces in Water Emptying Processes

Emptying processes are operations frequently required in hydraulic installations by water utilities. These processes can result in drops to sub-atmospheric pressure pulses, which may lead to pipeline collapse depending on soil characteristics and the stiffness of a pipe class. One-dimensional mathematical models and 3D computational fluid dynamics (CFD) simulations have been employed to analyse the behaviour of the air–water interface during these events. The numerical resolution of these models is challenging, as 1D models necessitate solving a system of algebraic differential equations. At the same time, 3D CFD simulations can take months to complete depending on the characteristics of the pipeline. This presents a mathematical approach for directly solving air–water interactions in emptying processes involving entrapped air, providing a predictive tool for water utilities. The proposed mathematical approach enables water utilities to predict emptying operations in water pipelines without needing 2D/3D CFD simulations or the resolution of a differential algebraic equations system (1D model). A practical application is demonstrated in a case study of a 350 m long pipe with an internal diameter of 350 mm, investigating the influence of air pocket size, friction factor, polytropic coefficient, pipe diameter, resistance coefficient, and pipe slope. The mathematical approach is validated using an experimental facility that is 7.36 m long, comparing it with 1D mathematical models and 3D CFD simulations. The results confirm that the derived mathematical expression effectively predicts emptying operations in single water installations.

Modeling local scour around complex bridge supports using CFD and a shear-stresses-based simplified approach

This study presents a simplified numerical modeling approach that estimates the local scour depths around bridge supports based on the bed shear stresses. It is developed using 3D computational fluid dynamics and coding through ANSYS workbench scripting along with C++ language. The proposed model is called SCFDS (Simplified Computational Fluid Dynamics Scour). The model’s main idea is to lower the bed bathymetry at the locations affected by flow obstruction until the shear stresses reach stable target values. The developed model is assessed by applying it to a complex pier of a real bridge over the Nile-River, and its scour data is calculated using the Hec-18 empirical equations. The outcomes of the model’s assessment show that it can depict the local scour around complex bridge supports. The developed approach is a novel and efficient tool that can help the designers in simulating local scour in the vicinity of flow obstructions. However, more verification studies are necessary to reach a generalized conclusion.

CFD and predictive modeling of temperature and calcination in a rotary lime kiln – Potential for steadier kiln operation

Rotary lime kilns are used in the pulp and paper industry to calcine lime mud to lime. Lime kiln models provide a means to understand the complex phenomena occurring within the kiln to aid in problem-solving during operation. A two-dimensional (2D) computational fluid dynamics (CFD) and one-dimensional (1D) bed model was previously developed for steady-state and transient analysis. This study explores data extracted from the model over a longer time period. The simulated outlet gas and shell temperature are compared to measured data for validation. The capability of using the model to estimate the production rate, accounting for the residence time within the kiln, is discussed. The maximum refractory wall temperature is analyzed during operation. Fluctuations in the calcination location are compared to outer shell heat-map data to correlate the calcination location and ring formation and growth. The model results to date indicate that fluctuations in the calcination zone may contribute to problematic ring growth, though a direct correlation has yet to be established. Additionally, a method for steadier kiln control is introduced and discussed. A machine learning model is also developed to predict the calcination start location from industrial data and is compared to the CFD model for validation. This model can generate results quickly and without the need for knowledge in CFD software and theory. Good agreement is found between the CFD and machine learning model during operation, with a mean absolute error (MAE) of 0.46 m, a mean absolute percentage error (MAPE) of 0.92%, and a root mean square error (RMSE) of 1.17 m.

The mechanism of the increased ratio of nitrogen dioxide to nitrogen oxides in methanol/diesel dual fuel engines

In the heavy-duty transportation sector, using methanol to partially replace diesel in engines can help reduce carbon-based emissions and thus has the potential for widespread use. However, methanol/diesel dual fuel engines exhibit a high NO2/NOx ratio despite the small energy contribution from methanol, a phenomenon unique compared to diesel engines. To uncover the underlying mechanism causing the increased NO2/NOx ratio in methanol/diesel dual-fuel engines, which is limited in existing studies, this study first utilizes a three-dimensional (3D) computational fluid dynamics (CFD) model to reproduce the NO2 concentration surge phenomenon. Each cell in the combustion chamber is then assumed to be a zero-dimensional (0D) closed homogeneous batch reactor to conduct chemical kinetic analysis, focusing on the regions with NO2 formation. The 3D CFD simulation results show that, compared to pure diesel operation, methanol/diesel dual-fuel operation has two areas with significant NO2 formation during the late oxidation process: the near-squish zone and the periphery of the main diffusion flame in the bowl. The 0D kinetic analysis indicates that the elementary reaction NO+HO2↔NO2+OH is primarily responsible for converting NO to NO2. Additionally, in the region just outside the diffusion flame, where high temperatures are maintained due to heat transfer, methanol forms HO2, which converts NO to NO2. In the low-temperature regions of the near-squish zone, NO2 forms where CH3OH and NO meet due to flow motion during the piston downward movement, with HO2 generated from the low-temperature oxidation of CH3OH. Overall, these findings deepen the understanding of NO2 formation in methanol/diesel dual-fuel engines, laying a foundation for the development of effective NO2 emission control strategies and supporting the sustainable advancement of methanol/diesel dual-fuel technologies.