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(a) rectangular acvity (b) streamlined acvity 1 (c) streamlined acvity 2 Fig. 2 Two-dimonsional simplified models of sensitive cavity of three structures Solve with Finite Element Method The FLOTRAN CFD analysis of ANSYS software is an advanced tool used to study two-dimensional and three-dimensional flow field, which can be used to analyze the movement of air in cavity [4].
This simulation typically comprises modeling, loading and solution
Summary ANSYS-FLOTRAN CFD software is used to calculate two-dimensional flow field distribution of different thermal wires position in fluidic gyroscope sensitive element with rectangular cavity and two streamlined cavity structures.
Wang: Numerical Simulation Technology of Practical Engineering and its Practice (Northwestern Polytechnical University Press, Xi’an 1999).

The theoretical calculation and numerical simulation for the effective thermal conductivity of Li2TiO3 pebble bed are performed in this paper.
The results show that the effective thermal conductivity of Li2TiO3 pebble bed can be preliminarily obtained by numerical simulation and theoretical calculation.
But the construction of experimental apparatus for the pebble bed is still being planned and prepared now, so it might be a feasible way to theoretical calculate and model the thermal conductivity of pebble bed with the heat transfer law and CFD simulation.
Conclusion In this paper, theoretical equations and 3D numerical simulation model used to evaluate the effective thermal conduction of Li2TiO3 pebble bed were obtained.
Therefore, numerical simulation might be a more feasible way to assess the effective thermal conduction of Li2TiO3 pebble bed when there is no experimental data.

Non-Isothermal Enhanced Recovery of Heavy Oils by Numerical Simulation A.
aactolimacunha@yahoo.com.br, bfariasn@deq.ufcg.edu.br, cgilson@dem.ufcg.edu.br, denivaldo.sb@gmail.com Key words: Heavy oil, flow, porous media, recovery factor, numerical simulation.
Results and Discussions Fig. 3 illustrates the mesh representing the study domain, which was crafted with the support of ICEM-CFD 11.0, this mesh was obtained after various refinements and resulted in a non structured mesh of 760.786 tetrahedral elements.
The simulations were performed on a Quad Core 2.66 GHz, 8 GB RAM and 1 TB physical memory (HD) computer.
The simulation time of the studied cases ranged from 43 to 46 hours.

Zhang[5] has studied the heading control of AUV using ADRC with the semi-physical simulation, and Yan[6] has researched path following control of AUV using SVR-ADRC.
The depth model of AUV The simulations used in this paper adopt a nonlinear 6 degrees of freedom (DOF) model to give a representation of the real system as accurate as possible.
To achieve a precise depth model, the hydrodynamic coefficients are usually obtained through tow-tank experiments or by employing computational fluid dynamics (CFD) tools in a general way.
However, the effective load of AUV and hydrodynamics could be affected by the frequently changed mission requirement, which limits the achievement of parameters by the experiment time, expensive tow-tank experiments or CFD simulations.
Journal of Applied Mathematics, 2014, [7] Timothy Prestreo.Verification of a Six-Degree of Freedom Simulation Model for the REMUS Autonomous Underwater Vehicle:[D].Massachusetts Institute Of Technology and the Woods Hole Oceanographic Institution,2001 [8] Fossen T.

The plume model used in the paper was simulated using a computation fluid dynamic (CFD) software package, FLUENT (Fluent, Inc.).
Compared with the static plume model, the simulated plume in CFD is more precise because the airflow velocity and odor concentrations are estimated throughout the space of interest [7].
Fig. 1 shows the dynamic CH4 plume model of two sources in simulation environment.
In the simulation experiment, we need to reproduce the plume model.
Lu, “A simulation framework for plume-tracing research,” Proceedings of ACRA.

Simulation Analysis on Industrial Wastewater Adjust Pool Stench in Collecting Hood with Properties of Environmental Materials Zhao Du1,2,a,Jing Han2,b,Bin Guo2,c,Shao Zuo Meng2,d 1School of Environmental Science and Engineering, Tianjin University, Tianjin 300072, People’s Republic of China 2School of Environmental Science and Engineering, Hebei University of Science and Technology, Shijiazhuang Hebei 050018, People’s Republic of China aduzhao12@163.com,bhgxhjj@163.com,cgbin69@163.com, d563868878@qq.com Keywords: Wastewater, Gas-collecting Hood, CFD Abstract.
Using fluent software module to the model of flow field simulation, Speziale, studies have shown that [6], the standard kappa epsilon - predominate turbulence model is a simulation indoor 3 d gas turbulence model is good.
Method adopted standards kappa epsilon model predominate is a semi-empirical formula, wide applicable scope, economic and reasonable accuracy, the model put forward by Launder, a default after a lot of experimental summary, is now widely used in industrial flow field simulation.
Simulation results At z = 0.9 m above the liquid level of the static pressure contours (Fig.3) and velocity contours (Fig.4), the concentration of cloud image (Fig.5), the concentration of x = 10 m cloud image (Fig.6).
From simulation report, regulating pool gas-collecting hood distribution of pressure in the range 0.652~0.144 Pa, the velocity distribution range 0~0.617 m/s, hydrogen sulfide molar concentration of 0 ~ 0.040 kmol/m3, can take a breath when induced air negative pressure is 600 Pa 472 m3/h.

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.

,Ltd,Dalian 116028,China a43665222@qq.com,bdlminghai@vip.sina.com Keywords: FLUENT; boundary conditions; computerized simulation; diesel engine; injector nozzle Abstract.
Research on Locomotive Diesel Engine Nozzle three-dimensional Flow Field Numerical Simulation and Improvement[J].
Numerical Simulation on Optimization of Diesel Nozzle[J].
Research on Numerical Simulation Analysis of Flow Field in the Diesel Engine Nozzle[J].
Research on CFD analysis of the Flow in Diesel Nozzle[J].

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.

In terms of proper initial and boundary conditions, a simultaneous iterated solution process coupling governing equations and compensatory terms is carried out within the SIMPLEC algorithm in the CFD (Computational Fluid Dynamics) program FLUENT.
The program FLUENT, which is an excellent flow modeling simulation tool, allows us to obtain valuable information during casting process of the molten Al-alloy within the mould.
The initial conditions in this simulation are presented as: the temperature of the mould and the molten Al-alloy are 620 °C and 720 °C, respectively.
Fig.3 (b) shows the simulations of molten Al-alloy infiltrating throughout the mould at time t=0.2 s and t=0.5s.
Summary The considered examples of simulation indicate that CFD program (Fluent) can be treated as an attractive and useful tool for modelling the pressure infiltration casting process to produce open-cell metal foam.