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A numerical simulation for the model is carried out by using Polyflow.
It can be used to guide oil exploitation and enhance oil recovery by using the method of software simulation with computational fluid dynamics software, having the aid of computer’s numerical computing power, to study the rules of water flooding.
Polyflow is a kind of computer fluid dynamics software (CFD) based on the finite element method, used in flow simulation for viscoelastic material.
Fig.2 Polyflow calculating block diagram Numerical Calculation and Analysis of Result Velocity Field Simulation.

The feasibility of the demonstration project of boiler flue gas treating wastewater on 4# boiler in Changshu Power Company limited was analyzed; the computational fluid dynamics (CFD) software FLUENT was adopted to simulated the pressure field and velocity field in the outlet flue pipes of air pre-heater.
Schedule of the droplet size and the settling velocity droplet size（μm） settling velocity（m/s） 10 — 30 — 60 0.09 100 0.21 137.5 0.32 171.4 0.54 Simulation of the Flue Gas Flow Conditions In the process where the wastewater is atomized and sprayed into the flue gas, the mixture of the droplet and gas is the prerequisite of the effect of waste water evaporation, which is also the basis of the nozzle arrangement.
In preliminary studies, combination with the research of the mixing process of our group and the experience in the process of desulfurization denitration development, The large commercial computational fluid dynamics (CFD) software FLUENT was adopted to simulated the flue gas flow conditions in the outlet flue pipes of air pre-heater.

Three combustor performance of difference ER were compared applied CFD simulated.
Combined with the CFD simulation, it were compared that three different gas-oil ratio the combustor performance parameters.

Two dimensional CFD analysis of micro patterned surfaces in hydrodynamic lubrication.
CFD model for turbocharger journal bearing performances.
CFD simulation of magnetorheological fluid journal bearings.
Simulation Modelling Practice and Theory 19 (2011) 1035–1060
Output maximization of a CIM system: Simulation and statistical approach.

Simulation of the MOCVD Reactor for ZnO Growth S.
The simulation results are useful for the practical growth of ZnO.
However, computer simulation has many advantages over experiment method.
In this paper, we utilize a computer-modeling tool, which bases on computational fluid dynamics (CFD) called FLUENT, to solve the various transport equations in the growth process.
In the simulations, the mole fraction remained constant.

In this paper, the distribution of temperature field and velocity field of the multi-temperature refrigerated trucks were simulated by using Computational Fluid Dynamics (CFD) software Fluent.
Numerical simulation of multi-temperature refrigerated trucks Computational Fluid Dynamics is a numerical simulation tool based on computer technology for solving fluid flow and heat transfer problems.
CFD application is related to the heat transfer problems in the process of food frozen, refrigerated and vacuum cooling[7,8,9].
According to the simulation in the cooling zone and the normal temperature zone, this region can better meet the temperature requirements than that in Fig.3(a).
When the air outlet was placed in position B and the wind speed was set as 3m/s, the numerical simulation results for velocity field were obtained and analyzed.

The simulations reveal show that cancer cells generally experience higher levels of deformation than normal cells.
(a) (b) Figure 1: Schematics of: (a) Cell deformation model used in CFD simulation and (b) Bending of cell-ECM interface adopted for FEM. 3.2.
Also the simulations of crack growth involved the release of nodes in the vicinity of the crack-tip, once the critical crack driving forces were reached.
Table 1 Values of the parameters used in two models for deformation and detachments single cell Definition Value Reference Normal Cell Young’s modulus of nucleus 8000 Pa [46] Young’s modulus of cytoplasm 500Pa,1.97kPa [46,52] Young’s modulus of extracellular matrix 105± 14 Pa [45] Density of normal cell 1E-6 kg/m3 [50] Breast Cancer Cell (MDA-MB 231) Young’s modulus of nucleus 400 Pa [48] Young’s modulus of cytoplasm 2204 Pa,0.53kPa [49,50] Young’s modulus of extracellular matrix 100 k Pa [45] Density of tumor cell 1.08 E-3 kg/m3 [50] Fluid Properties Density of fluid used in CFD simulation 1000 kg/m3 [22] Viscosity of fluid used in CFD simulation 0.001 Pa*s [22] 4.
The simulations of cell deformation and detachment revealed that breast cancer cells deform.

Using ANSYS－FLOTRAN CFD program, the temperature field and the stream field in sensing element of three wire structure and two wire structure under the effect of the different tilt state, has been obtained by a series of procedure, such as model building, meshing, loads applying and equation solving.
Finite element method ANSYS－FLOTRAN CFD is an advanced tool used to analyze the two and three dimensional flowing fields[2].
“Practical Engineering Numerical Simulation and Practice in ANSYS,” Northwest Polytechnical University of Technology Press, Xian, pp. 221, 1999.

Simulation Study on Indoor Pollen Removal with Variable Exhaust Angle of an Air Purifier Akinori Hashimoto1,a and Toshiki Takahashi2,b 1Human Resources Cultivation Center (HRCC), Gunma University, 1-5-1 Tenjin-Cho, Kiryu 376-8515, Japan 2Faculty of Science and Technology, Gunma University, 1-5-1 Tenjin-Cho, Kiryu 376-8515, Japan at10802401@gunma-u.ac.jp, bt-tak@gunma-u.ac.jp Keywords: Pollen removal, Air purifier, CFD, LES, GPGPU Abstract.
The present simulation model is schematically drawn in Fig. 1.
We carry out the LPT simulation and LES by GPGPU based on CUDA.
Therefore we have accelerated the simulations using GPGPU to increase simulation research efficiency.
The LPT-LES coupling simulation using GPGPU (NVIDIA GTX 780 based on CUDA) has become 18 times faster than the same simulation on the CPU.

But their results are without the simulation of air core.
The numerical solutions were carried out using commercial CFD code FLUENT 6.1.
The simulation was realized using a large eddy simulation (LES) for turbulent modeling and discrete phase model (DPM) for particle trahectories calculation.
This study drop 1470 particles at inlet at simulation time 1.9 s.
Fig. 2 shows the particle movement simulation from 1.98 s to 2.50 s.