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The efficiency and performance of the HVAC system in the isolation room can be improved by using CFD simulation, as shown by several studies [10], [13], [14].
Sikarwar, Design and simulation of isolation room for a hospital, no.
Biswas, “A novel CFD analysis to minimize the spread of COVID-19 virus in hospital isolation room,” Chaos, Solitons and Fractals, vol. 139, p. 110294, 2020, doi: 10.1016/j.chaos.2020.110294

The numerical representation of transient temperature fields within the coating process may be calculated by computational fluid dynamics simulations (CFD) as well as by empirical equivalent models.
However, an efficient simulation process requires the identification of significant process parameters in order to avoid additional costs caused by oversized simulation time.
Fig. 6: Diagram of simulation process chain To transfer the upstream generated material- and part characteristics to the thermo mechanical simulation, a result mapping algorithm is used.
Therefore, the simulation process is supplemented by a springback calculation following the former deep drawing simulation.
The upstream performed deep drawing simulation generates significant part characteristics and defines the yield point in the thermo mechanical simulation due to strain hardening.

For our analysis, CFD method and preprocessing grid generator are used as our main analytical tools, and the simulation of rain is accomplished via two phase flow approach named as Discrete Phase Model (DPM).
An over head rain simulation system was constructed along a 525 ft section of the track.
In 2003, Wan and Wu [6] also conducted the numerical simulation of heavy rain effects on airfoil.
The simulation results are compared with the experimental results done earlier.
In our simulation we used LWC 0 g/m3, 30 g/m3 and 39 g/m3 rain rate cases.

In 1980, Hwang and Stoehr [1-4], for the first time, applied the MAC (marker and cell), and SMAC (simplified MAC) methods in the numerical simulation of the casting process using a computational fluid dynamics (CFD) approach.
Joseph et al. [10] designed two runners through experiments and the CAE simulations, and to compare the actual finished products and the corresponding simulation results.
These models were recently performed in the commercial simulation software ProCAST.
Figure 6 shows the simulation results of solidification evolution of the modified pouring system.
Niyama, in: Quasi Three-Dimensional Mold Filling Simulation System for Prediction of Defects in Die Castings, Conf.

This book covers these topics: Acoustics and Noise Control, Aerodynamics, Applied Mechanics, Automation, Mechatronics and Robotics, Automobiles, Automotive Engineering, Ballistics, Biomechanics, Biomedical Engineering, CAD/CAM/CIM, CFD, Composite and Smart Materials, Compressible Flows, Computational Mechanics, Computational Techniques, Dynamics and Vibration, Energy Engineering and Management, Engineering Materials, Fatigue and Fracture, Fluid Dynamics, Fluid Mechanics and Machinery, Fracture, Fuels and Combustion, General mechanics, Geomechanics, Health and Safety, Heat and Mass Transfer, HVAC, Instrumentation and Control, Internal Combustion Engines, Machinery and Machine Design, Manufacturing and Production Processes, Marine System Design, Material Engineering, Material Science and Processing, Mechanical Design, Mechanical Power Engineering, Mechatronics, MEMS and Nano Technology, Multibody Dynamics, Nanomaterial Engineering, New and Renewable Energy, Noise
and Vibration, Noise Control, Non-destructive Evaluation, Nonlinear Dynamics, PC guided design and manufacture, Plasticity Mechanics, Pollution and Environmental Engineering, Precision mechanics, Mechatronics, Production Technology, Quality assurance and environment protection, Resistance and Propulsion, Robotic Automation and Control, Solid Mechanics, Structural Dynamics, System Dynamics and Simulation, Tribology, Turbulence and Vibrations.

Design and analysis of water turbine that used for wave energy power generation Shi Ming Wang1,a, Ya Nan Wang2,b and Ka Tian3,c 1Room301, College of Engineering, Shanghai Ocean University, No.999, Hu cheng huan Road, Lin gang new city, Shanghai, P.R.China 2,3Room402, College of Engineering, Shanghai Ocean University, No.999, Hu cheng huan Road, Lin gang new city, Shanghai, P.R.China asmwang@shou.edu.cn, bwangyananzc@126.com,c 799496533@qq.com Keywords: water turbine; wave energy; wave energy generation; simulation; analysis Abstract: In view of the current global energy shortage crisis, ocean wave energy is development potential renewable energy, which is gaining more and more attention.
It focus on the compose and generate mechanism of water turbine, and design structure of water turbine, and combine ocean wave theory and the flow control equation to analysis, through the method of machine design and FLUENT simulation, finally proved the water turbine had a high efficiency and has good application prospect.
Mesh generation is very important in CFD calculation.
Numerical modeling water velocity is 1 m/s, 1.5 m/s, 2 m/s respectively in simulation process, and blade rotate speed is 75 rpm, 110 rpm, 150 rpm corresponding.

Numerical model and grid distribution The 3D model was built by CATIA.The grid was generated using ANSYS/ICEM CFD.The solution was calculated by ANSYS/FLUENT 12.0.
All grid has been smoothed before numerical simulation.
The ralative errors between the results for simulation and the results calculated from the Gnielinski and Filonenko equations were both below 10%.
So, the grid is fine enough for simulation between Reynolds number from 1.2×104 and 5×104.
The grid arrangement with 386241 elements was used for the simulation with Reynolds numbers between 1.2×104 and 5×104. 2.3.

Heat transfer performance is investigated using Fluent computational fluid dynamics (CFD) package.
The computational fluid dynamics (CFD) software Fluent is used in this study.
In their simulation, a low-Reynolds number turbulence model was used for the fluid layer, while two different turbulence models modified from [10] and a laminar flow model were tested.
Figure 10 - Comparison of simulation and experiments for varying dj/dh.

For mass transfer applications, CFD codes need the turbulent Schmidt number .
In order to analyse both equations (3) and (6 with 7), we will use accurate analytical formulations for TKE and eddy viscosity calibrated by direct numerical simulation (DNS) data.

For this, numerical computer simulation was used with the aid of the Ansys Fluent software, in which simulations of water flow in a steady state occurred.
The simulations were performed considering the steady state and isothermal state.
After the execution of these models, the simulations were performed in the Ansys Fluent.
Sketch of distributor flap profiles used for simulation The numerical simulation was performed in the four models outlined in Fig. 4, from the results obtained in the simulation the two best ones were selected.
CFD Based Analysis of Combined Effect of Cavitation and Silt Erosion on Kaplan Turbine.