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China ajdgaofeng@163.com, bWeiyanzh@163.com Keywords: Multi-blade Centrifugal Fan, Unsteady Flow, Pressure Pulsation, Aerodynamic Noise, Numerical simulation Abstract.
Numerical simulation of the three-dimensional steady and unsteady turbulent flow in the whole flow field of a multi-blade centrifugal fan is performed.
Along with the development of the computer technology and the computational fluid dynamics, the CFD technology is replacing part of the experiment gradually.
In order to make sure the stability of the unsteady simulation, the steady numerical simulation is done at first based on the same mesh subdivision, after that, the results of the steady simulation are used as the beginning field to proceed with the whole passage unsteady simulation inside the multi-blade centrifugal fan.
Simulation results and analysis Velocity field.

The mesh of negative area of cylinder cavity was divided by ANSYS ICEM CFD and the flow field was simulated by ANSYS FLUENT.
Establishment the simulation model Structure and working principle.
ANSYS ICEM CFD is a pre-processing software professional CAE, providing efficient and reliable analysis model for all the world popular software of CAE.
Simulation calculation and analysis Introduction of the dimensionless parameter.
CFD simulation optimization of cooling water jacket structure for 2D25 horizontal diesel engine[J].

Fig.1.Mesh used in the simulations and the system dimensions The fluid dynamic simulation was accomplished in the software Fluent® and the main contour conditions: air feeding velocity (1.56 m/s), permeability (4.69x10-10 m2), porosity (82%), thickness (2.5x10-3 m), relative humidity of the air (20%) and temperature (300 K), were derived from [4].
It was a two-dimensional fluid dynamic simulation with approximately 530.000 computational cells.
Results and debates As indicated in the fluid dynamics simulations in [3], the pressure drop in the studied filtering system was dependent on the position of feeding gas, and this dependence was confirmed in the simulation with the feeding in the bottom of the filtering box, according to the Figure 2.
These authors’ fluid dynamics simulations indicated that the bag “1” was the one that provided a higher rate of filtered element among all bags.
In the Figure 3, you can examine the results of the [3] work, and the results of the simulation with a feeding in the bottom of the filtering box.

(a): CFD NWT model.
Goggins, Numerical simulation of linear water waves and wave-structure interaction.
Elangovan, CFD Simulation and Validation of Flap Type Wave-Maker.
Li, Numerical Simulation of Irregular Wave-Simulating Irregular Wave Train.
Elangovan, Simulation of Irregular Waves by CFD.

Through the indoor temperature, meteorological data, walls, roof, vent, vent and other structural elements, air conditioning load simulation.
Fig.2 Energy consumption simulation-Jin Yule residential area This Fig.2 chart displays average and total simulation data for the current building.To study the building of the year temperature,heat gains and energy consumption,the first chart shows room electricity and heating（gas）with the trend of the month.the second shows the temperature trends over the month, the third shows a thermal equilibrium with the changing trend of month. 3.Heat load data If the user can define in less than 1 hours of time step, using integrated synchronous load / system / device simulation method, heat balance method was used to simulate the load, muti-regional air flow, thermal comfort and photovoltaic system.
Wind field simulation, the indoor air quality analysis software is not limited to outdoor, it can help us to the outdoor heat simulation analysis, considering the HVAC systems Fig.4, solar radiation, surface structure on the indoor thermal environment simulation analysis of the influence of double glass curtain wall, inner heat flow analysis, environment on human comfort simulation.
Fig.4 CFD-Jin Yule residential area Fig.5 The amount of sunlight-Jin Yule residential area 5.The lighting calculation and report The amount of sunlight on the lighting control system model of computation, save electrical lighting.
Conclusion In this paper, through analyzing the simulation method of environmental performance of building systems, combining Jin Yule residential building as an example, through the construction of the environment simulation, performance prediction after the completion of the construction environment, emphasizes significance to the further study on the construction of the building environment performance.

Simulation of methanol steam reforming heated by waste heat for hydrogen production in a microreactor Feng Wang 1, a, Jing Zhou 2, b, Guoqiang Wang 2, c, and Xinjing Zhou 2, d 1Key Laboratory of Low-grade Energy Utilization Technologies and Systems (Chongqing University), Ministry of Education, Chongqing, 400030, PR China 2College of Power Engineering, Chongqing University, Chongqing, 400030, PR China a wangfeng@cqu.edu.cn, b 646108160@qq.com, c 513715507@qq.com, d 497314155@qq.com Keywords: waste heat; methanol steam reforming; hydrogen production; simulation Abstract.
With the application of general finite reaction rate model in CFD software of FLUENT, we carried out 3-D simulation of this process.
Physical, mathematical and kinetic model The physical model used by simulation is shown in Fig.1.
With application of general finite reaction rate model in CFD software of FLUENT, the governing equations for analysis of the reacting flow in methanol steam reforming reaction channel of the reactor are: Mass balance: (1) Species balance: (2) Momentum balance: (3) Energy balance: (4) Ideal gas law: (5) Since CO content in the products of methanol steam reforming is very small on copper based catalyst, single rate kinetics of methanol reacting with water

Along with the development of fluid dynamics research, it is feasible and has obvious advantages to adopt simulation study with the CFD simulation software for attrition of sewage pump.
Model parameter of centrifugal sewage pump The paper took type of 50W15 centrifugal sewage pumps as research object for simulation.
Simulation results and analysis The simulation was done under different working condition with different particle size which diameter is from 1mm, 2mm, 3mm, 4mm and 5mm, and different granule concentration which is 1%,2%,3% and 4%.
Simulation results show that wear degree is not uniform in different part of impeller.
[3]Fu-jun Wang: in:Computational fluid dynamics (CFD) software analysis: principles and applications.

In this study, numerical simulations of the two-dimension hill over smooth and roof surface have been done using three different turbulence model :standard k ε− model and other revised models ,and the simulation results have been prepared with wind tunnel experiments ,in order to obtain the best turbulence model .
Currently,the location of wind power plant or wind turbine is mostly selected by using standard linear model software WAsP.Now more and more designers of wind power plant find that WAsP software is not suitable for wind power plant over complex terrain.So calculated fluid dynamics(CFD)begins gradually to be applied in the research of complex wind power plant.CFD simulation can fully consider the impact of terrain,roughness and barrier on orographic wind,establish numerical wind tunnel test,and calculate the flow field of orographic wind.
This model is given by Ishihara and others in 2001 when they made wind tunnel test,figure 1 describes the length and the heigth of the hill clearly,then compares the result of the simulation with this test.The mesh generation is showm in figure 1(b),the mesh of the surface layer of the hill is refined.
2 shows the results abtained from the simulation of three models on the hill with smooth surface,figure 2 (a) expresses the distribution of standardized turbulent kinetic energy, (b) represents the distribution of the average wind speed vector,and part 1,2,3 are respectively corresponding to standard k ε− model,RNG k ε− model and realizable k ε− model;The value of standard k ε− model is much larger than that of RGN k ε− model and realizable k ε− model in the distribution of standardized turbulent kinetic energy 2 Hk u in the position of the hill top compared results of three models.
The simulated results of realizable kε− model Fig. 3 shows the results abtained from the simulation of three models on the hill with rough surface,obviously, standardized turbulent kinetic energy 2 Hk u is in the position of the hill top,and the value of standard k ε− model is much larger than that of RNG k ε− model and realizable k ε− model;In the flow region in front of the hill,when 11.25 / 0X H − < < ,the standardized value of k abtained from RNG k ε− model is more close to testing value,the standard k ε− model and the realizable k ε− model both overestimate the value of k in this region,but after pasing the hill top,RNG k ε− model underestimates the value of k,however the value of realizable k ε− model and test is most approach.

To obtain the design criterion ofcurve regression equations and area ratio,Wan Peisun conducted tests on the jet-mixing apparatus and discussed the relationship between its structure parameters[2].He Peijie chose different jet nozzle diameters and different jet nozzle distances and some other parameters to determine the pressure ratio and the flow ratio of jet-mixing apparatus[3].To analyze and compare the mixing performance of different kinds of jet mixing apparatus, Xu Youlin designed 4 forms of jet-mixing apparatus and carried out numerical simulation by using CFD software Fluent flow[4].Meanwhile.Qiu Baijing studied pipe distance, area ratio and inlet angle on the effects of mixing performance of the mixing device by CFD, he obtained some rules between the three structural parameters and the jet mixing properties[5].
At present, the research on jet mixing was limited to the flow field simulation of jet mixing apparatus and experimental analysis, but the jet-mixing device and spray system to integrate a large system for the research didn’t be taken.Therefore, this text studies working state of jet mixing apparatus used in spray system based on the bench test. 1 Working state of jet-mixing apparatus 1.1 The structure and parameters of jet-mixing apparatus A jet-mixing apparatus is mainly composed of jet nozzle, medicine sucking mouth, suction chamber, mixing tube and diffusion tube, its structure is schematically shown in figure1.And the structural parameters of jet-mixing apparatus could be divided into fixed parameters and variable parameters, fixed parameter is a constant parameter in the optimization design and variable parameter refers to changing parameters values in order to explore an optimized parameter in the effects of flow jet to jet-mixing apparatus in simulation design.
The apparatus may appears reflux and cavitation that are thought as failed condition, to avoid back flow and cavitation state, the current research on reflux state of jet-mixing apparatus is less, this paper will study the working state of the jet-mixing apparatus from numerical simulation and experimental study. 2 Bench test 2.1 The bench test device The main parts of the test device are: online mixing test platform, it consists of dynamic liquid pump, water tank, pesticide tank, jet mixer, spraying system and the measuring elements, the structure and the test bench of online automatic mixing test platform are both shown in figure 2.
[4] Xu Youlin,Zhou Fengfang,Guo Jingkun.Flow Field Simulation of Chemical Mixing Process for Direct Injection System based on CFD[C].2008:ASABE International Meeting,Rhode [5] Qiu Baijing,Xu Xichao,Yang Ning.The simulation analysis of the influence of structure paraments on the mixing performance of jet mixing device[J],Transaction of the Chinese Society for Agricultural Machinery,2011, 42(6): 172~174.

The experimental findings are compared to numerical results obtained with a computational fluid dynamics (CFD) package using a finite volume approach and its ability for the prediction of fibre movement in molten matrix during forming processes is evaluated.
Therefore, viscous and viscoelastic material models are used in calculations and numerical simulations of composite forming processes [6, 7].
In addition, numerical flow simulations were set-up to model the experiment.
Numerical simulations have been assessed for the prediction of the resistance force.
Additionally, this could be the result of neglecting elastic material properties in the simulation.