Search results

Numerical Simulation of 3-D Unsteady Flows in Flow Passage on Spiral Case of Hydro-turbine Ze Li 1,a Zhilin Liang1,b 1 Engineering Mechanics Department of Kunming University of Science and Technology, Kunming 650500, China alize666@yahoo.com.cn, bliangzhilin001@126.com Keywords: Hydro-turbine, Flow passage, Spiral case, computational fluid dynamics.
Abstract: Based on the Reynolds averaged Navier-Stokes equations, numerical simulation of unsteady flows in the flow passage in spiral case of a hydro-turbine was conducted.
Introduction As the size of water turbine is becoming bigger and bigger and the water head is higher and higher, it is necessary to do the numerical simulation of the flowing number of the water substance in the water turbine runner.
At present, the calculation of three-dimensional flowing in water turbine runner has developed from steady simulation to unsteady simulation.
Numerical calculation model This paper takes the water turbine volute of a large hydropower as the research subject to do the three-dimensional numerical simulation of the water substance flowing in volute runner.

In this paper, the three-dimensional wind field characteristics of thunderstorm microbursts were studied using computational simulation method.
Computational simulation method Wind field model.
The governing equations of computational simulation study on thunderstorm microburst-induced high intensity winds are given by:
The three-dimensional wind field of thunderstorm microbursts was conducted using time-filtered Reynolds Averaged Navier-Stokes (RANS) numerical simulation method.
Numerical Simulations of an Isolated Microburst.

Then, by giving the size parameters and shape parameters of the blades, the simulation has been done and the corresponding simulation results have been obtained.
It is necessary to construct the simulated model in order to obtain the simulation results of the fluid dynamics of the wind turbine [5-6].
Therefore, the simulation study shows that blade A is superior to blade B in terms of torque and energy conversion efficiency.
Similar simulation works can be done for the other wind turbines with the different diameter, radius curvature, or/and number of blades.
Conclusions In this paper, the simulation model for the computational fluid dynamics analysis has been constructed.

The simulation results were represented graphically in a coating window plot.
This work adopts simulation in this area of research for the first time.
Simulation Conditions.
Simulation Results and Defect Types.
Table 1 summarizes the simulation results.

Tay et al. [11] by the use of finned & pinned tubes in thermal energy storage apparatus performance is analyzed with the help of CFD representation, the performance of finned tubes was finer than pinned tubes.
[13] A.Ebrahimi, A.Dadvand, Simulation of melting of a nano-enchanted phase change material in a squa recavity with two heat source-sink pairs, Alex.

In the following simulation, we compare the effect of diffusion and disaggregation in the two structure designs, observing the velocity, turbulent kinetic energy and shear strain rate of airflow in them, and add drug particles in the better one to achieve particles path, and superficial velocity, volume fraction, shear stress of particles.
Fig. 4 Structure 1 Fig. 5 Structure 2 Turbulence Simulation In the following simulation, we assume that boundary conditions include: airflow velocity at the inlet is 30m/s, static pressure at the outlet is 0Pa relative to the standard atmospheric pressure, wall roughness is ignored; the short process is considered as a steady-state process, and the temperature is constant (because of no heat transfer, energy equation is not to be solved); gravity and buoyancy effects are not taken into account.
Fig. 10 Turbulent kinetic energy curve in Fig. 11 Turbulent kinetic energy curve in Structure 1 Structure 2 Fig. 12 Shear strain stress curve in Structure 1 Fig. 13 Shear strain stress curve in Structure 2 Particle Tracking Simulation In the following simulation, we add drug particles to the disaggregation pipe of Structure 2.
We preset these parameters as follow: particle density is 0.25g/cm3, average particle diameter is 80μm, particle molar mass is 600kg/mol, heap volume is 10mm3, particle dynamic viscosity is 8.899×10-6kg/ms, simulation time is 0.002s, inlet airflow velocity is 30m/s (it is regarded as a constant value).
Take the simulation results of 0.001s.

Numerical simulation of the starting characteristics is carried out in this study.
The simulation results tend to qualitatively agree with the experimental results for steadily rotating wind turbines in terms of two aspects: (1) the optimal shape has an 20% overlap of the turbine radius, and (2) the larger the gap, the lower the efficiency.
We performed numerical simulations of time-varying rotations to investigate the characteristics of a wind turbine as it starts to rotate.
The simulation was carried out on 18 wind turbines of different shapes.
Table 2 Simulation conditions (non-dimensional length) No. 1 (Original) 2 3 4 5 6 7 8 9 10 11 Radius of turbine 1.00 0.50 1.50 0.50 1.00 1.00 1.00 1.00 1.00 1.00 1.00 Blade length 1.00 1.50 0.50 0.50 1.00 1.00 1.00 1.00 1.00 1.00 1.00 Thickness 0.20 0.20 0.20 0.40 0.20 0.20 0.20 0.20 0.20 0.20 0.20 Overlap 0.00 0.00 0.00 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 Gap 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 No. 12 13 14 15 16 17 18 Radius of turbine 1.00 1.00 1.00 1.00 1.00 1.00 1.00 Blade length 1.00 1.00 1.00 1.00 1.00 1.00 1.00 Thickness 0.20 0.20 0.20 0.20 0.20 0.20 0.20 Overlap 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Gap 0.05 0.10 0.15 0.20 0.25 0.30 0.35 Fig. 11 Simulation results; the optimal shape was found by comparing the normalized torque coefficients The optimal shape in this simulation (radius of turbine = 1.0, blade length = 1.0, thickness = 0.2, overlap = 0.2, and gap = 0.0) is shown in Fig. 12.

Relevant topics in category "Thermodynamics" include: cooling and heating systems, cryogenics, refrigeration, combustion, energy conversion, thermal stresses, computational fluid dynamics (CFD) and etc.
Oxley, Corecive journal self citations, impact factor, Journal Influence and Article Influence, Mathematics and Computers in Simulation 93 (2013) 190-197

Simulation the environment pollution evolution with Lattice Boltzmann Method Yanchao Qiao1,2,a,* , Ziqi Guo2,b,Yaolin Shi1,c , 1 Key Laboratory of Computational Geodynamics, Graduate University of Chinese Academy of Science, Beijing 100049, China 2 Institute of Remote Sensing Applications of Chinese Academy of Sciences, Beijing 100101, China aoliver.qiao@gmail.com, bguozq@irsa.ac.cn, cshiyl@gucas.ac.cn (corresponding author) * Author to whom correspondence should be addressed.
In this paper, we focus on the need for forecast the contamination propagation by numerical simulation.
Table1 illustrate some of important parameters used in this simulation.
Swift, Lattice Boltzmann Simulation of Nonideal Fluids, Phys.

Fluid Dynamic Simulation of a Wall-jet-flow Loaded with Solid Particles Using the Finite Analytic/Grid Method of PDF Model Ying Tiana, Jiangrong XU,b, Sujuan Huc and Weiwei Yed Insititute of Energy Science and Engineering, Hangzhou Dianzi University, Hangzhou 310018, China a842898633@qq.com, bjrxu@hdu.edu.cn, clh7421@126.com, d179058616@qq.com Keywords: two-phase flow PDF transport equation Computational fluid dynamic finite analysis/particle method finite analysis/grid method Abstract.
In this paper, a classical wall-jet-flow loaded with particles is simulated by the finite analysis /grid method using the particle PDF transport equation, as well as by the finite analysis / particle method, and then the simulation results obtained by the two methods are compared with the experimental results.
solve the reduced PDF equation in velocity space by solving method of the Fokker-Planck equation[7], and the solution of the equation include the average velocity and variance, which is expressed by a set of ordinary differential equations as follows: , , , (5) Second step, integral to the particle velocity - position joint PDF transport equation for , we get the reduced PDF equation in position space, (6) where The above equation is the unsteady form, the reduced steady PDF equation in position space in the two dimensional Cartesian system is: (7) Using the finite difference method, we set the j-th step as on the direction, the m-th step as on the direction, is used to solve above equation, and get the difference format of the equation (8) 3.Numerical simulation
for wall-jet of two-phase flow using finite analysis/grid method Fig.1 Geometry of the wall-jet test case In this paper, the simulation object is a wall-jet-flow loaded with particles, the geometry and the flow conditions are represented in Fig.1, the flow field characteristic parameters are shown in Table 1.
The difference between the simulation results of finite analysis/particle method with the experimental results is smaller in the upstream, and the results by finite analysis/grid method is obviously superior to that by the finite analysis/particle method in the downstream.