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General numerical solvers such as FEM and CFD can be used in most situations, but may suffer from solving difficulties with some problems, which are conventionally called numerical noisy. [10] Thus, the numerical noisy is a shortcoming for MDF because the strategy largely depends on the MDA.
Comparison of optimization procedures on the MDF, MDF-RSM and MDF-update-RSM Optimization procedure Search strategy of design space iteration result （x1，x2，f） Precise on result (1,1,0) outer inner MDF NLPQL 57 —— 0.988,0.976, 0.000152 0.015% MDF-RSM NLPQL —— 17 -0.0150,2.647, 6052.970 Not converge MDF-update-RSM NLPQL 8 96 0.977, 0.952, 0.000560 0.056% In addition, it is worth mentioning that the quadric approximate function is smooth up to avoid the numerical noise for engineering problem involving the numerical simulation.
Consequently, facing the numerical simulation used by FEM and CFD, the MDF-update-RSM can gain better result than the MDF procedure.
Consequently, the MDA uses the loosely coupling method in the FEM in which the aerodynamics and temperature will be boundary condition on the pressure and suction of blade interpolated from the CFD result.

There are several methods employed for the calculation of propeller static thrust which include experimental formula method, computational fluid dynamics numerical simulation and experiment.
The propeller performance CFD method[4] is developed from strip theory.
References [1] Ying Nie, Sheng Wang and Yanchu Yang: Computer Simulation Vol. 26 (2009), p.103-107 (In Chinese) [2] Hamilton Standard: Generalized Method of Propeller Performance Estimation, PDB 6101 (1967) [3] Peiqing Liu: Air Propeller Theory and Application (Press of BUAA, Beijing 2006) (In Chinese) [4] Dawei Wu, Hanbing Li and Shu Li: J.

Flutter Optimized Design for a Aircraft Horizontal Tail Base on Optimus Software Da-Qian ZHANG1,a*, Xiao-Dong TAN1,b, Zi-Lei ZHANG2,c and Xin-Ping FU1,d 1Key Laboratory of Liaoning Province for Composite Structural Analysis of Aircraft and Simulation, Shenyang Aerospace University, Shenyang, 110136, China 2 School of Economy and Management, Shenyang Aerospace University, Shenyang 110136, China azhangdaqian65@163.com, btan4362285@126.com, c 2534451919@qq.com, dyyfuxinping@163.com Keywords: Horizontal Tail, Scale Model, Flutter, Optimus, Optimized Design.
Cheng Mulin[1] analyzed the characteristics of the wing flutter using CFD Loosely coupled approach.
Numerical simulation of plane wing vibration in transonic flows ,J.Journalof Hydrodynamics,2004,19 (Supp1):871-876

Salcedo et al. [9] they carried out a numerical simulation of mixed convection heat transfer from a downward flow of Newtonian fluid around a tandem circular cylinder, the simulation are performed at Re = 200 and the governing equations are solved in unsteady laminar regime, Ri = -1 to 4, Pr = 0.7 and Blockage ratio = 0.2.
The numerical simulations are done for the range of these conditions as: Re = 5 to 40, Ri = 1, Pr = 1, β = 0.2 and distance between the cylinders S = 0 to 5d (d is the diameter of the cylinder).
(10) Numerical Details The numerical simulation is carried out by using the commercial CFD package ANSYS-CFX.
Results and Discussion Numerical simulations are represented mainly in term of streamlines and isotherm contours for the following range of conditions: Re = 5 to 40, distance between cylinders, S = 0 to 5d at fixed values of Richardson number Ri = 1, Prandtl number, Pr = 1 and blockage ratio, β = 0.2.
Summary The numerical simulations of incompressible fluid around a tandem of confined circular cylinders exposed to downward flow are studied under the effect of opposing thermal buoyancy in order to understand and to determine the combined effect of buoyancy strength and the distance between the cylinders on fluid flow and heat transfer rate in the range of these conditions: Re = 5 to 40, S = 0 to 5d at fixed values of Ri = 1, Pr = 1 and β = 1/5.

To simplify the model, this study use two-dimensional numerical simulation to reflect the conditions inside foam chamber instead.
In this paper, the commercial software Fluent is used to calculate model based on the finite volume method of CFD.
Namely, the coupled field average data from the numerical simulation shows a monotonic trend as the increasing of the foamability.
Therefore, there is a clear correlation between the experimental results and numerical simulations results.
To evaluate the merits of the two models, the numerical simulations of the two models is going to be compared as follows based on the experimental results.

With the improvement of laboratory equipment and development of computer technology, a large number of experiments and numerical simulations have been made since 1970s..
A large number of experiments show that the method of setting elasticity artificially also could get the same result by simulation based on accurate elasticity.
Tab.2 Parameter of PFC2d calculation Particle parameters Calculation step Partice size range （mm） Surface friction coefficient Particle density （kg/m 3） Wears stiffness Tangential stiffness DEM CFD 0.80~12.0 0.3~0.5 2.65E3 1.00E6 1.00E6 2.00E-7 2.00E-5 size（mm） Wall parameter Fluid parameters L H Wears stiffness Tangential stiffness Surface friction coefficient density （kg/m 3） Dynamic viscosity （Pa.s） Fluid cells 300 500 1.00E8 1.00E8 0.3 1.00E3 1.00E-3 1×1 In order to change hydraulic gradient into velocity recognized by PFC2D software, firstly, using the method of getting permeability though porosity obtains the estimating permeability coefficient of permeability of filter layer.
Strack: A Discrete Numerical Model for Granular Assemblies, Géotechnique Vol.29 (1979), p.47-65 [3] Zhang Gang: Researches on Meso-scale Mechanism of Piping Failure by Means of Model Test and PFC Numerical Simulation, Shanghai: Tongji University, 2007 [4] Mindlin, R.D., and H.Deresiewiez: Elastic Spheres in Contact under Varying Oblique Forces, J.APPI.Meeh., 1953，Vol.20 (1953), p.327-344 [5] Cundall, P.
Tanata: Discrete Particle Simulation of Two-Dimensional FluidizedBed, Powder Tech., Vol77, (1993), p.79-87 [9] Kawaguchi, T.: Discrete Particle Simulations of Gas-Fluidized Bed, Osaka University, 2003

The commercial CFD software ANSYS-FLUENT© was used to solve this numerical problem with the governing differential equations discretized by a control volume approach.
Simulations found that by increasing the nanoparticle volume fraction, heat transfer can be increased.
Hooman, Numerical simulation of natural convection and mixed convection of the nanofluid in a square cavity using Buongiorno model, Powder Technology, 268 (2014) 279-292

Numerical Simulations of the Fluid Flow and Heat Transfer during a Solidification Phase Change of a Polymer in a Die Shixiong RenaP, Shasha DangPbP, Tao LuPc, TF∗FPT, Kuisheng WangPd PPSchool of Mechanical and Electricial Engineering, Beijing University of Chemical Technology, Beijing 100029, China PaPrenshx@mail.buct.edu.cn, PbPdangshas@163.com, PcPlikesurge@sina.com, PdPwangks@mail.buct.edu .cn Keywords: Numerical Simulation, Fluid Flow, Heat Transfer, Solidifying Phase Change, Polymer, Die Abstract.
Numerical simulation provides a reliable method to optimize the design of the die, the choice of metallic material for the die, and the operating conditions of the polymer pelletizing under water.
In recent years, a considerable amount of progress has been made in the analysis and simulations of polymer flow for non-Newtonian fluids undergoing solidification, in order to optimize the process and improve the product quality.
In this work, the temperatures, velocity distributions and phase changes for dies with different temperatures of the inlet polymer and the cooling water, and different convection heat transfer coefficients of the thermal oil were obtained by numerical simulation with the CFD software, Fluent.
Governing equations Figure 2 Heat transfer in the die Simulations of the heat transfer in the die shown in Figure 2 are described.

Simulation results show that the introduction of seed bubbles improves the heat transfer performance and suppresses the flow instability simultaneously.
Numerical simulations of bubble growth rate coupled with heat transfer rate was observed to increased significantly by W.
A numerical simulation was performed to analyze the wall heat transfer mechanisms during growth of a vapor bubble inside a microchannel by A.
Figure 2 A section of the computational mesh used in the CFD simulations Figure 3 Comparison of the present work with experiment results [1] Results and discussion Figure 3 shows a comparison of the experimental results obtained by Xu et al. [1] with the simulations.
As can be seen from Fig. 3, the simulation result shows a shift to wall temperature no more than 3 K as compared to the experiment data.

Numerical Simulation of the Oscillating Water Column inside a Vertical Cylinder in Regular Waves Using IHFOAM J.M.P.
In simulations without porous zone solves only the RANS equations.
In the simulation presented was used the version 2.2.2 of OpenFOAM®, installed in the Ubuntu 14.04LTS operating system.
For this, in future work, simulations will be conducted contemplated that influence.
[16] OpenFOAM, The Open Source CFD Tollbox – User Guide v.2.2.2, OpenCFD, 2013