The Optimized Analysis of Electronic Cooling by CFD Methods

Emergency condition should be evaluated during the siting of Nuclear Power Plants (NPP). One of the criteria is the capability of emergency evacuation for the purpose of protecting the NPP staff and public. Exposure dose received by evacuees is a key factor to evaluate the effectiveness of emergency evacuation, which can be characterized by the atmospheric dispersion factors over the evacuation paths. Gaussian plume model is usually applied in the atmospheric dispersion factor calculation for NPPs. However, for some NPP sites with complex terrain like mountain and lake which has significant influence on the local flow field and the nuclides transportation, the calculations based on Gaussian model will not be accurate enough for the evaluation of the evacuation capability. In such cases, Computational Fluid Dynamics (CFD) method with fine calculation grids and rich physical models can be used in the atmospheric dispersion modeling of small-scale region, to get much more accurate results. This paper is devoted to the research on the impact of these complex terrain on atmospheric dispersion with CFD method. The local atmospheric dispersion around a NPP site located on an island is modeled, where there is a mountain on the way of evacuation. For the limitation of the geographic barrier, two evacuation paths, which are located closely with small difference in direction, are planned along different sides of the mountain. Utilizing STAR-CCM+ CFD software, local atmospheric dispersion factors are fine simulated under six worse wind directions. Based on the simulation results, the impact of the mountain on the flow field and of the radiological plume on the evacuation paths is analyzed. Results show that due to the blocking effect of the mountain, those two evacuation paths have little probability to be simultaneously covered by the radiological plume. By the choosing of suitable routes during the evacuation, the radiological risk of public is acceptable and emergency evacuation can be carried out effectively. These results also demonstrate that CFD modeling method is effective in the evaluation of local atmospheric dispersion over complex terrain, which can be applied in the analysis of emergency evacuation of NPP sites with complex terrain.

As Computational Fluid Dynamics (CFD) methods evolve and mature, more engineering problems are being solved through computer simulation to reduce reliance on the costly and time-consuming experimental methods. This trend is also occurring in the gear manufacturing industry, where an increasing number of quality issues related to the oil quenching process are being investigated by CFD methods to find solutions. However, while the CFD theory and numerical methods have made significant advancements, gaps still exist between the academic research and industrial applications. In the case of the oil quenching processes, the prospect of using CFD methods to visualize and study the oil flow pattern in the gear quenching tank is promising yet challenging. The obstacle to simulating the oil quenching process using CFD methods lies not in the numerical method itself for solving the Navier-Stokes equation, but in building a computer simulation model that encompasses all the geometrical details of the quenching tank, fixtures, centrifugal pumps, and gears, including all the gear teeth. This task is particularly challenging for Finite Volume Method (FVM) CFD solvers, as the computation mesh could take days or weeks to build. In this research, a new solution method based on Smoothed Particle Hydrodynamics (SPH) is introduced to simulate the oil flow in the gear quenching tank. Since SPH is a mesh-free Lagrangian method, it not only greatly simplifies the mesh generation task for building the computational models but also handles the complex physics of the free surface flow and fluid-structure interaction with great ease. In addition, the oil flow in the gear quenching tank usually is driven by centrifugal pumps whose dynamics can be simulated directly in SPH methods, as opposed to FVM methods which require complicated moving mesh computation.

Full-scale experimental and computational fluid dynamics (CFD) methods were used to investigate the velocity and temperature fields in a mechanically ventilated room. Detailed airflow fields were measured in three cases of ventilation air temperature: an isothermal case, a hot case and a cold case. The ventilation system created a round jet which developed near the ceiling. The experimental data were used to test two turbulence models: a first order k-ε turbulence model and a second order RSM turbulence model. The RSM model predicted the temperature and velocity fields better than the k-ε turbulence model. In particular, experimental global values of velocity and temperature were in good agreement with the RSM turbulence model. This model is recommended for simulation of ventilated enclosures with thermal effects.

Aerodynamic characteristics of a guided rocket projectile are numerically simulated. Simulations are performed in a range of flight conditions using a commercial CFD software FLUENT, and variations of lift coefficients and drag coefficients with Mach numbers and angles of attack were demonstrated. The numerical results also indicate that the angle of canard deflection has significant influence on the flow field near tailfins.

This paper implements the parameter identification of ship roll motion based on vibration tests and the computational fluid dynamics (CFD) method. By applying sinusoidal moment excitations from a shaker, we successfully simulate the quasi-roll motion behavior of the ship model in the air. We conduct two vibration tests, including a constant-amplitude angular displacement test and a constant-amplitude angular velocity test, to identify the restoring moment and the damping moment coefficients of the quasi-roll motion. In addition, we perform the approximate equivalence of the fluid around the ship through the CFD method and the fluid-solid coupling technique. Thus, we obtain the hydrodynamic coefficients, such as the added mass moment of inertia and the equivalent damping, to accomplish the parameter identification of the ship’s real roll motion. Finally, the accuracy of the identified parameters is verified by means of numerical simulations based on the Runge–Kutta method.

Computational modelling and experimental validation of drug entrainment in a dry powder inhaler

The demand for high-efficiency air vehicles and the development of distributed electric propulsion systems for aircraft are exposing the need for accurate aerodynamic prediction of multiple integrated propulsion systems. Conventional high-fidelity computational methods are too expensive, and low-cost low-fidelity methods make too many aerodynamic assumptions to be applied to these analyses. Dual-solver hybrid computational fluid dynamics (CFD) methods bridge the gap between these two categories of solvers, but many lack capabilities that are needed for complex vehicles. Recent improvements to the hybrid solver OVERFLOW-CHARM provide efficient and accurate analysis of integrated propulsion systems with hybrid CFD methods, as demonstrated on the wing–propeller system of the AIAA Workshop for Integrated Propeller Prediction. Predictions of propeller thrust are within 1% of conventional CFD data, and wing pressure coefficient distributions agree well with both experimental data and conventional CFD methods. The dual-solver results were obtained at half the computational cost of the full CFD simulation.

With the upscaling of wind turbine,models of wind shear and tower shadow play an increasingly significant role in the aerodynamic calculation. Although Computational Fluid Dynamic (CFD) method gives more accurate results than Blade Element Momentum (BEM)method, BEM remains the primary method for calculating aerodynamics and aeroelasticity of wind rotor. Firstly, this paper reviews several 2D and 3D potential tower interference models for BEMmethod. 2D model is much easier to compute but cannot simulate the “end effect” of tower. Previous 3D model can provide more accurate result than 2D model, but it yields an incorrect approximation of nonzero vertical velocity on ground.Then, in this paper, a new 3Dmodel is proposed to address this problem and is compared to previous models. A CFD method is used to verify the level of fidelity of the models. The normal velocity on tower surface and the attachment point of the variable models are compared, while the induced velocity on ground and the upstream velocity of the tower in x-direction at several distances are analyzed. Finally, NREL-5MW RWT was used as an example to show how the model is used in BEMmethod.

Fires in underground metal mines pose significant risks to worker safety and operational continuity. This study analyses the performance of the ventilation system after a fire in an underground metal mine using the Computa-tional Fluid Dynamics (CFD) method. Three different fire scenarios were modelled, examining temperature distri-bution, toxic gas dispersion, and airflow dynamics during the fire. Simulation results reveal how the fire spreads in other areas and assess the efficiency of the existing ventilation system. Findings indicate that the ventilation system is insufficient in certain areas for smoke extraction, and the post-fire gas clearance process varies across different locations. In particular, the positioning of auxiliary fans and the airflow direction are key factors in determining the spread of smoke after a fire. Based on these analyses, optimising post-fire ventilation strategies and enhancing emergency action plans are recommended. This study highlights the critical role of CFD analyses in the mining in-dustry in improving safety and efficiency and contributes to developing safer underground mine ventilation sys-tems. Furthermore, this study stands to make a substantial impact on the practical implementation of the "ventila-tion on demand" concept, advancing our understanding and application of this critical approach. On the other hand, the most important result of this study is that an underground mine with a very large volume is subject to cdf analysis as a whole. Because it is the first study to reveal that the direction of air flow changes as a fire in any part of the mine changes the thermodynamic conditions of the entire mine.

This study designed a vertical take-off and landing tailsitter unmanned aerial vehicle (UAV) with a long endurance time. Nine parameters of the tailsitter UAV were investigated. Using a 2k full factorial test, 512 experiments on the nine parameters were conducted at their maximum and minimum values. The time coefficient and air resistance were calculated using the computational fluid dynamics (CFD) method under different parameter combinations. The analysis of variance determined that the specific factors influencing the time coefficient and air resistance were the root chord, wingtip chord, wingspan, and sweep angle. By carrying out a central composite design (CCD) test, 25 sample points of the four particular factors were constructed. The time coefficient and air resistance were simulated under different structural parameter combinations using the CFD method. CFD simulation was verified by carrying out a wind tunnel test, and the results revealed that the aerodynamic coefficient error was less than 5%, while the air resistance error was less than 6%. The response surface methodology (RSM) for the time coefficient and air resistance was established using a genetic aggregation method. A multi-objective genetic algorithm (MOGA) was used to optimize the parameters with regard to the maximum time coefficient and minimum air resistance. The optimal structural parameters were wing root chord length at 315 mm, wingtip chord length at 182 mm, wingspan length at 1198 mm, and sweep angle at 16°. Compared with the original layout and size, the time coefficient of the new design of the tailsitter UAV improved by 19.5%, while the air resistance reduced by 34.78%. The results obtained by this study are significant for the design of tailsitter UAVs.

In order to correct the solar radiation error of relative humidity, the mainstream capacitive sounding humidity sensor HC103M2 is selected and investigated by simulation analysis and experimental verification. First, the basic theories for solar radiation error and sensor error itself are elaborated, and simulational and experimental platforms are introduced. The computational fluid dynamics (CFD) method is utilized to theoretically investigate the dry error of the humidity sensor caused by solar radiation heating, which is related to radiation intensity, altitude, and solar elevation angle as well as reflectivity, thickness, and shape of the shield. Then, in order to verify the accuracy of the simulation, an experimental platform including a humidity sensor and two temperature sensors to measure the solar radiation heating is built to analyze the relative error of humidity obtained by the CFD simulation and experiment. It is found that their maximum deviation is 3.30% and the average error is 1.94%, which indicates that the calculation using the CFD method is accurate and feasible. In order to easily and operationally predict the solar radiation heating of the humidity sensor, a back propagation (BP) neural network fusion algorithm based on three inputs of radiation intensity, air pressure, and solar elevation angle is proposed. Compared with the solar radiation heating obtained by CFD simulation, the maximum absolute error is about 0.2K, and the relative error of humidity is about ±1.30%. Finally, a case of vertical humidity profile correction considering the temperature-sensitive error of HC103M2 is analyzed. The response time of sensor measurement and the airflow into the shield are discussed as well. The corrected results after taking solar radiation heating into account are more similar to those measured by RS92 and cryogenic frost point hygrometer (CFH). This result shows that the prediction model is accurate, which may be applied to correct the dry error and further improve the accuracy of humidity measurement.

With the development of the wind power industry, wind turbine blades are increasingly adopting ultra-large-scale designs. However, as the size of blades continues to increase, existing aerodynamic calculation methods struggle to achieve both relatively high computational accuracy and efficiency simultaneously. To tackle this challenge, this research focuses on the low accuracy issues of the traditional Blade Element Momentum theory (BEM) in predicting the aerodynamic performance of wind turbine blades. Consequently, a correction framework is proposed, to integrate the Computational Fluid Dynamics (CFD) method with the Multilayer Perceptron (MLP) neural network. In this approach, the CFD method is used to predict the airflow characteristics around the blades, and the MLP neural network is employed to model the intricate functional relationships between multiple influencing factors and key aerodynamic parameters. This process results in high-precision predictive functions for key aerodynamic parameters, which are then used to correct the traditional BEM. When this correction framework is applied to the rotor of the IEA 15 MW wind turbine, the effectiveness of MLP in predicting key aerodynamic parameters is demonstrated. The research findings suggest that this framework can enhance the accuracy of BEM aerodynamic load predictions to a level comparable to that of RANS.

Tracheal Bronchus (TB) is a rare congenital anomaly characterized by the presence of an abnormal bronchus originating from the trachea or main bronchi and directed toward the upper lobe. The airflow pattern in tracheobronchial trees of TB subjects is critical, but has not been systemically studied. This study proposes to simulate the airflow using CT image based models and the computational fluid dynamics (CFD) method. Six TB subjects and three health controls (HC) are included. After the geometric model of tracheobronchial tree is extracted from CT images, the spatial distribution of velocity, wall pressure, wall shear stress (WSS) is obtained through CFD simulation, and the lobar distribution of air, flow pattern and global pressure drop are investigated. Compared with HC subjects, the main bronchus angle of TB subjects and the variation of volume are large, while the cross-sectional growth rate is small. High airflow velocity, wall pressure, and WSS are observed locally at the tracheal bronchus, but the global patterns of these measures are still similar to those of HC. The ratio of airflow into the tracheal bronchus accounts for 6.6-15.6% of the inhaled airflow, decreasing the ratio to the right upper lobe from 15.7-21.4% (HC) to 4.9-13.6%. The air into tracheal bronchus originates from the right dorsal near-wall region of the trachea. Tracheal bronchus does not change the global pressure drop which is dependent on multiple variables. Though the tracheobronchial trees of TB subjects present individualized features, several commonalities on the structural and airflow characteristics can be revealed. The observed local alternations might provide new insight into the reason of recurrent local infections, cough and acute respiratory distress related to TB.

Objective To perform the virtual Fontan operations on patients who had undergone the bilateral bidirectional Glenn procedure, and to simulate the blood flow in different types of opera-tive strategies by the method of computational fluid dynamics (CFD). Methods Three-dimensional re-construction was performed with Mimics 12. 0(R) according to the results of magnetic resonance imaging (MRI). Virtual operations were performed by changing the virtual anastomotic sites of bilateral supe-rior vena cava (SVC) and pulmonary arteries (PAs), and by connecting the inferior vena cava (IVC) to different sites of PAs. Numerical simulations were established to analyze the CFD of blood flows in patients undergoing 4 different types of virtual operative strategies at different predetermined flow split distribution ratios of left pulmonary artery (LPA) to right pulmonary artery (RPA) (at 30: 70,40 : 60, 50:50,60:40 and 70:30, respectively). Results When the distance between the anastomotic sites of the bilateral SVCs to the PAs was relatively long and the anastomotic site of IVC and PAs was in the middle of the SVC-PA anastomotic sites, the control volume power loss (CVPL) was lower than any other three operative strategies at all predetermined LPA/RPA flow split distribution ratios. The CV-PL achieved a minimal value of 23.60 mW at the ratio of 50/50. Conclusions For Fontan operations, it may be the optimal operative strategy to anastomose bilateral SVCs to the homolateral PA separately and to connect the IVC in the middle of the SVC-PA anastomotic sites. Key words: Computational fluid dynamics; Fontan procedure; Virtual operation; Energy me-tabolism

Optimal Pressure in Bypass Graft to Prevent Failure Bypass Graft in Carotid Artery to Middle Cerebral Artery Bypass using Computational Fluid Dynamic Method