Sort by:
Publication Type:
Open access:
Publication Date:
Periodicals:
Search results
Online since: June 2012
Authors: Zhen Zhe Li, Gui Ying Shen, Mei Qin Li, Ming Ren, Xiao Ming Pan
Hu has studied the temperature distribution of battery pack using CFD (computational fluid dynamics), and recommended a new cooling strategy for battery pack[11].
In this study, the steady simulations were carried out using a commercial CFD code – FLUENT.
The standard k-ε turbulence model was used for the simulation of convection, and 3 dimensional heat conduction was included.
In this study, the steady simulations were carried out using a commercial CFD code – FLUENT.
The standard k-ε turbulence model was used for the simulation of convection, and 3 dimensional heat conduction was included.
Online since: September 2010
Authors: János Ginsztler, Zsolt Puskás, Árpád I. Toldy
We also
used CFD (computational fluid dynamics) simulation to verify the flow conditions for the new
geometry.
We then used CFD simulation (Ansys CFX) to verify the flow conditions.
We then used CFD simulation (Ansys CFX) to verify the flow conditions.
Online since: August 2013
Authors: Oronzio Manca, Alina Adriana Minea, Razvan Silviu Luciu
Investigations into the thermal properties of nanofluids, based on experiments and molecular dynamics simulations, have been much more extensive than discussions involving microflow.
Many studies have been conducted in the field of computational fluid dynamics (CFD), and numerical simulations have proven to be an effective way to understand nanofluids.
The CFD code Fluent 13.1 was employed to solve the present problem [10].
Bhattacharya, Brownian Dynamics Simulation to Determine the Effective Thermal Conductivity of Nanofluids, J.
Wang, Analyses of Physical Mechanism and Numerical Simulation for micro-convection Enhancement in the Solid-Liquid Two Phase Flow, J.
Many studies have been conducted in the field of computational fluid dynamics (CFD), and numerical simulations have proven to be an effective way to understand nanofluids.
The CFD code Fluent 13.1 was employed to solve the present problem [10].
Bhattacharya, Brownian Dynamics Simulation to Determine the Effective Thermal Conductivity of Nanofluids, J.
Wang, Analyses of Physical Mechanism and Numerical Simulation for micro-convection Enhancement in the Solid-Liquid Two Phase Flow, J.
Online since: October 2011
Authors: Zhi Jun Xu, Zeng Xin Yu
The authors used ANSYSTM program in simulation [3].
The authors used the second coupling method for simulation of dynamic characteristics of hydraulic mount.
Fig.6 shows finite element simulation of dynamic stiffness curve and Lag angle curve.
There is satisfactory coincidence degree between the simulation curve and the test values .
Dynamic Simulation of Engine-Mount Systems .
The authors used the second coupling method for simulation of dynamic characteristics of hydraulic mount.
Fig.6 shows finite element simulation of dynamic stiffness curve and Lag angle curve.
There is satisfactory coincidence degree between the simulation curve and the test values .
Dynamic Simulation of Engine-Mount Systems .
Online since: January 2014
Authors: Tian Qi Cheng, Tian Zhai, Jian Yong Lei, Hui Di Hao, Yong Fang Zhang, Na Zhu
And finally the FLOTRAN CFD software is used to simulate the complex flow field and flow pattern according to the multiple reference frame method.
The advantages[7] of multiple reference frame is to achieve the whole numerical simulation of flow field in stirred tank, and not to need to have experiment; Secondly, it is a kind of steady algorithm ,with small workload.
Stirring reactor in computational fluid dynamics simulation technology progress [J].
Study on Numerical Simulation of the flow field and temperature field of polystyrene reactor [J], Petroleum and Chemical Equipment Technology, 2005,26(4): 44-49
Numerical simulation of flow field of Impeller Stirred Tank [J].
The advantages[7] of multiple reference frame is to achieve the whole numerical simulation of flow field in stirred tank, and not to need to have experiment; Secondly, it is a kind of steady algorithm ,with small workload.
Stirring reactor in computational fluid dynamics simulation technology progress [J].
Study on Numerical Simulation of the flow field and temperature field of polystyrene reactor [J], Petroleum and Chemical Equipment Technology, 2005,26(4): 44-49
Numerical simulation of flow field of Impeller Stirred Tank [J].
Online since: September 2013
Authors: Faizal W.M. Wan Mohd, Mohamad Shukri Zakaria, A. Roslizar, Mohd Hafidzal Mohd Hanafi, Mohd Noor Asril Saadun, Abdul Rafeq Saleman
Previous researchers investigated on soot distribution in a diesel engine by using the CFD software, Kiva-3v.
Kiva-3v implements a two stage of Hiroyasu soot model in the simulation.
The data that were obtained from the Kiva-3v simulation were velocity vectors of the soot, fuel, temperature, pressure and others [6].
In this study, the drag force equation is included in the simulation to determine soot movement.
[13] Hong, S., Wooldridge, M.S., Im, H.G., Assanis, D.N. and Pitsch, H., Development and application of a comprehensive soot model for 3D CFD reacting flow studies in a diesel engine.
Kiva-3v implements a two stage of Hiroyasu soot model in the simulation.
The data that were obtained from the Kiva-3v simulation were velocity vectors of the soot, fuel, temperature, pressure and others [6].
In this study, the drag force equation is included in the simulation to determine soot movement.
[13] Hong, S., Wooldridge, M.S., Im, H.G., Assanis, D.N. and Pitsch, H., Development and application of a comprehensive soot model for 3D CFD reacting flow studies in a diesel engine.
Online since: January 2012
Authors: Wen Juan Wang, Xiao Qing Yu, Mao Lin, Yu Zhang, Li Jia
Simulation of Design and Optimization of Local Oil Gas Ventilation Equipments with CFX
Li Jia1, , Wenjuan Wang1, Xiaoqing Yu1, Mao Lin1, Yu Zhang1
1 XuZhou Air Force College, XuZhou, JiangSu, China, jiayuanzi@163.com
Keywords: oil gas; ventilation equipments; design; optimization; CFX; simulation
Abstract.
Under a given refueling condition, the diameter parameter value of cover mouth of suction hood is defined through Computational Fluid Dynamics (CFD) code CFX.
The parameters of simulation model Parameter Value 0.06 0.04 0.12 0.04 0.05 Fig.2.Layout and parameters of oil gas control system parameters 3 The Simulation Models In order to observe the diffusion control of the oil gas,taking the semicircular which centres the oil filling port and the radius of which is 1.5m as the viewing area of simulation mode.
Left: Simulation model Right: Simulation model after meshing 3.1 Pretreatment of Simulation Model The fuel velocity is supposed to be 340L/min,environmental temperature maintains normal (25℃), the pressure is standard atmospheric pressure(1atm).
For small-scale simulation of oil gas diffusion, the convergence accuracy is set as 10-4.
Under a given refueling condition, the diameter parameter value of cover mouth of suction hood is defined through Computational Fluid Dynamics (CFD) code CFX.
The parameters of simulation model Parameter Value 0.06 0.04 0.12 0.04 0.05 Fig.2.Layout and parameters of oil gas control system parameters 3 The Simulation Models In order to observe the diffusion control of the oil gas,taking the semicircular which centres the oil filling port and the radius of which is 1.5m as the viewing area of simulation mode.
Left: Simulation model Right: Simulation model after meshing 3.1 Pretreatment of Simulation Model The fuel velocity is supposed to be 340L/min,environmental temperature maintains normal (25℃), the pressure is standard atmospheric pressure(1atm).
For small-scale simulation of oil gas diffusion, the convergence accuracy is set as 10-4.
Online since: September 2016
Authors: D. Davidson Jebaseelan, C.P. Karthikeyan, Joseph Stokes, Vaibhav Gawaji Shelar
Simulation of HVOF coating is extremely complex to analyze, since its properties and microstructure depend on numerous processing parameters.
Powder Composition[7] 88%WC-12%CO Particle shape[7] Angular Young’s Modulus(GPa)[6] 185 Poisson’s ratio[6] 0.278 Yield stress(MPa)[6] 60 Density(Kg/m3)[8] 14000 Tangent modulus(GPa) )[8] 184 Specific Heat(Cp)(J/kg k)[7] 295 Latent heat(J/kg)[7] 420000 The substrate is Steel material with Young’s Modulus of 200GPa [6], density of 8000kg/m3 and Poisson’s ratio of 0.3[6].Zahra Shahbazian [7] conducted CFD simulation and plotted graphs between velocity and spraying distance[7].The particle is heated to 1000K and having 100m/s velocity at 1mm distance away from the substrate[7].
Ireland (2003) [7] Zahra Shahbazian, CFD analysis of the HVOF diamond Jet Gun.
Powder Composition[7] 88%WC-12%CO Particle shape[7] Angular Young’s Modulus(GPa)[6] 185 Poisson’s ratio[6] 0.278 Yield stress(MPa)[6] 60 Density(Kg/m3)[8] 14000 Tangent modulus(GPa) )[8] 184 Specific Heat(Cp)(J/kg k)[7] 295 Latent heat(J/kg)[7] 420000 The substrate is Steel material with Young’s Modulus of 200GPa [6], density of 8000kg/m3 and Poisson’s ratio of 0.3[6].Zahra Shahbazian [7] conducted CFD simulation and plotted graphs between velocity and spraying distance[7].The particle is heated to 1000K and having 100m/s velocity at 1mm distance away from the substrate[7].
Ireland (2003) [7] Zahra Shahbazian, CFD analysis of the HVOF diamond Jet Gun.
Online since: October 2011
Authors: Yi Zhou, Yuan Qi Li, Zu Yan Shen
Determination of the fluid loading
Significant progress in the field of CFD(computational fluid dynamics) has been made, and it has been used as an efficient tool for the prediction of fluid loads.
Because Reynolds-averaged Navier–Stokes (RANS) modeling can reasonably simulate mean wind characteristics and require less computing time than other CFD methods, it is the most widely used method in many industrial applications.
For the numerical simulation, the governing equations of the incompressible turbulent wind flow around circular membrane presented by the RANS equations as follows: (4) (5) Using the dynamic mesh model in FLUENT allows for the arbitrary motion of fluid boundaries and in doing so, captures the response of the fluid to the prescribed boundary motion.
Because Reynolds-averaged Navier–Stokes (RANS) modeling can reasonably simulate mean wind characteristics and require less computing time than other CFD methods, it is the most widely used method in many industrial applications.
For the numerical simulation, the governing equations of the incompressible turbulent wind flow around circular membrane presented by the RANS equations as follows: (4) (5) Using the dynamic mesh model in FLUENT allows for the arbitrary motion of fluid boundaries and in doing so, captures the response of the fluid to the prescribed boundary motion.
Online since: January 2013
Authors: Chun Lin Zhang, Nian Su Hu, Wen Yang, Jian Mei Wang, Min Li, Cheng Ma
The flow and heat transfer inside the steam seal is controlled by the following equations [6]:
Continuity equation: (1)
Momentum equation: (2)
Energy equation: (3)
The CFD model of the steam seal and steam is showed in Fig. 5.
Fig. 5 The CFD model of the steam seal The flow inside the steam seal is assumed to be incompressible flow, controlled by the Reynolds averaging Navier-Stokes equations together with the continuity equation.
(3) In order to have a rapid convergence, the calculation for these simulations involve the liquid should have the calculation of the steady state first
Fig. 5 The CFD model of the steam seal The flow inside the steam seal is assumed to be incompressible flow, controlled by the Reynolds averaging Navier-Stokes equations together with the continuity equation.
(3) In order to have a rapid convergence, the calculation for these simulations involve the liquid should have the calculation of the steady state first