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Online since: August 2013
Authors: Jun Sheng Chen, Shu Zhuo Liu, Hai Hong Mo, Ying Guang Fang
Three-dimensional computational fluid dynamics simulation
Determination of computing parameters. 1.Outdoor meteorological parameters
The site for simulation computation is Guangzhou city.
Material of tunnel masonry structures In this simulation computation, the tunnel masonry material is reinforced concrete with a thickness of 300 mm; the concrete’s thermophysical properties are as follows: 1.547 w/m2•℃ (coefficient of thermal conductivity), 0.00277 m2/h (coefficient of thermal diffusivity), 2500 kg/m3 (density), and 1170 J/kg•K (specific heat). 3.
Stratum temperature In this simulation computation, the object is sandy clay with a moisture content of 15 %, and its thermophysical parameters are as follows: 2.559 W/m•°C (thermal conductivity), 1.386 kJ/kg•°C (specific heat), 0.0037 m2/h (coefficient of thermal diffusivity), and 1780 kg/m3 (unit weight).
Convection heat transfer coefficient In this simulation, the computation was carried out according to a computing formula of a convection heat transfer coefficient generalized from engineering test data.
Numerical 3D simulation of a longitudinal ventilation system: Memorial tunnel case.
Material of tunnel masonry structures In this simulation computation, the tunnel masonry material is reinforced concrete with a thickness of 300 mm; the concrete’s thermophysical properties are as follows: 1.547 w/m2•℃ (coefficient of thermal conductivity), 0.00277 m2/h (coefficient of thermal diffusivity), 2500 kg/m3 (density), and 1170 J/kg•K (specific heat). 3.
Stratum temperature In this simulation computation, the object is sandy clay with a moisture content of 15 %, and its thermophysical parameters are as follows: 2.559 W/m•°C (thermal conductivity), 1.386 kJ/kg•°C (specific heat), 0.0037 m2/h (coefficient of thermal diffusivity), and 1780 kg/m3 (unit weight).
Convection heat transfer coefficient In this simulation, the computation was carried out according to a computing formula of a convection heat transfer coefficient generalized from engineering test data.
Numerical 3D simulation of a longitudinal ventilation system: Memorial tunnel case.
Online since: April 2012
Authors: Xing Huang, Wei Qian
China
ahuangxing19811015@163.com, bqianwei@ustb.edu.cn
Keywords: Blast furnace, Wood bellow, Computational Fluid Dynamics, Numerical simulation, Liao dynasty
Abstract.
There is no friction between the lid and box, and no leakage of air in the simulation process.
Numerical simulation for the blast effect In this section, the software FLUENT is applied to simulate the process at constant temperature.
And the simulation results are depicted in Fig.8.
With numerical simulation, the model can meet the requirement of drum wind in smelting.
There is no friction between the lid and box, and no leakage of air in the simulation process.
Numerical simulation for the blast effect In this section, the software FLUENT is applied to simulate the process at constant temperature.
And the simulation results are depicted in Fig.8.
With numerical simulation, the model can meet the requirement of drum wind in smelting.
Online since: May 2014
Authors: Jatuporn Thongsri, Vana Pongkom
The simulation revealed the results of airflow, particle trajectories and efficiency of a circulating filter.
The simulation result reveals that some particles were trapped by the circulating filter, as seen in the marked area, but most of the particles continued to flow and crash into the HDD cover.
Applying the cloud model [10] to predict the particle trajectory, together with our simulation based on the random walk available in the DPM, these can enhance the reliability of this research.
This simulation can be used as fundamental information for designing a higher efficiency circulating filter and for reducing particle contamination.
Sundaravadivelu, A numerical simulation of particle trajectory in thin hard disk drive, IEEE Trans.
The simulation result reveals that some particles were trapped by the circulating filter, as seen in the marked area, but most of the particles continued to flow and crash into the HDD cover.
Applying the cloud model [10] to predict the particle trajectory, together with our simulation based on the random walk available in the DPM, these can enhance the reliability of this research.
This simulation can be used as fundamental information for designing a higher efficiency circulating filter and for reducing particle contamination.
Sundaravadivelu, A numerical simulation of particle trajectory in thin hard disk drive, IEEE Trans.
Online since: June 2014
Authors: Muhammad Ismail, Shahid Latif, Zhou Hong
In our numerical simulation the heavy rain effects have been studied on the aerodynamic performance of 2D cambered NACA 23015 airfoil landing configuration with 20°.
We compared the simulation results the previous experimental results.
The increase in lift coefficient in our simulation results is less than the experimental results.
While in our simulation the percentage decrease in lift coefficient reaches up to 14% for LWC 23 g/m3.
For our simulation the decrease in lift and increase in drag in heavy rain is less than the experimental results for NACA 23015 for rain rate of LWC 0, 12 and 23 g/m3 but the trends are similar.
We compared the simulation results the previous experimental results.
The increase in lift coefficient in our simulation results is less than the experimental results.
While in our simulation the percentage decrease in lift coefficient reaches up to 14% for LWC 23 g/m3.
For our simulation the decrease in lift and increase in drag in heavy rain is less than the experimental results for NACA 23015 for rain rate of LWC 0, 12 and 23 g/m3 but the trends are similar.
Online since: October 2014
Authors: Yong Tao, Ting Ting Yu, Hong Xia Cai, Yu Jie Bai
The parameters for simulation are shown in Table 1.
Fluent fluid analysis and simulation practical tutorial [M].Beijing: People Post Press, 2010
Solid-liquid two-phase flow model and pressure characteristics simulation of abrasive flow machining [J].Chinese Mechanical Engineering, pp.17-19, April 2008
[9] G.J.Jiang, G.Z.Gao, H.Wen.Diesel fuel injector flow within the three-dimensional numerical simulation [J].Nanchang University Journal, pp.13-16, January 2008
Simulation and Analysis of diesel-hole nozzle hole flow [J].Journal of internal combustion engine, pp.21-23, June 2006.
Fluent fluid analysis and simulation practical tutorial [M].Beijing: People Post Press, 2010
Solid-liquid two-phase flow model and pressure characteristics simulation of abrasive flow machining [J].Chinese Mechanical Engineering, pp.17-19, April 2008
[9] G.J.Jiang, G.Z.Gao, H.Wen.Diesel fuel injector flow within the three-dimensional numerical simulation [J].Nanchang University Journal, pp.13-16, January 2008
Simulation and Analysis of diesel-hole nozzle hole flow [J].Journal of internal combustion engine, pp.21-23, June 2006.
Online since: September 2013
Authors: Shu Nan Liu, Xing Zhu He, Yan Li Chen, Chun Xue Wang, Song Yang
Research the complex flow field of the ducted fan by numerical simulation to analyze its hover characteristics.
So this paper analyzes the hover characteristics of ducted fan with coaxial rotors by numerical simulation.
Computational Model and Numerical Simulation Simulation Model Fig.1 shows the computational model of ducted fan with coaxial rotors, whose propellers use the NACA 2412 as aerofoil and linear torsion is used.
So this paper analyzes the hover characteristics of ducted fan with coaxial rotors by numerical simulation.
Computational Model and Numerical Simulation Simulation Model Fig.1 shows the computational model of ducted fan with coaxial rotors, whose propellers use the NACA 2412 as aerofoil and linear torsion is used.
Online since: February 2013
Edited by: Ching Kuo Wang, Jing Guo
The papers are grouped as follows:
Chapter 1: Manufacturing Technology and Processes, Design, Modelling, Simulation and Mechanical Engineering;
Chapter 2: Robotic, Automation, Sensors, Detection and Monitoring Technologies;
Chapter 3: Development Elecrtonics, Networks, Information Technology and Algorithms in Systems Applications;
Chapter 4: Mechanics, Thermal and Dynamics Systems, Vibration, Noise, Applied Mechanics and Numerical Simulation Applications;
Chapter 5: Materials Science and Technology, Material Manufacturing Processes;
Chapter 6: Control System Modeling and Applications;
Chapter 7: Developments in Medical Technologies and Images Processing Technologies.
Online since: August 2010
Edited by: Hong Hua Tan
The 477 peer-reviewed papers are grouped into 12 chapters: Session One: Computational Mechanics and Applied Mechanics, Session Two: Mechanical Design, Session Three: Materials Science and Processing, Session Four: System Dynamics and Simulation, Session Five: PC Guided Design and Manufacture, Session Six: Other Related Topics, Session Seven: Computational Mechanics and Applied Mechanics, Session Eight: Mechanical Design, Session Nine: Materials Science and Processing, Session Ten: System Dynamics and Simulation, Session Eleven: PC-Guided Design and Manufacture, Session Twelve: Other Topics.
Online since: December 2012
Authors: Wei Jie Li, Ji Xin Yin, Li Hong Zhang
Numerical Simulation of Bionic Wing for Drag Reduction
Lihong Zhang 1, a, Weijie Li 2,b and Jixin Yin 3,c
1 Basic Course Department of Aviation University of Air Force,Changchun,China
2 Scientific research department of Aviation University of Air Force,Changchun,China
3 Aviation Theory Department of Aviation University of Air Force,Changchun,China
azhlhjj@163.com, b58116492@qq.com, c25010511@qq.com
Keywords: Airfoil; Computational fluid dynamics; Bionic; Drag reduction
Abstract: According to the presence of the rounded protuberances or tubercles located on the leading edge, a similar leading edge of humpback whale pectoral fin with the “paraganglioma” has been made on the leading edge of NACA63-210 wing, an bionic NACA63-210 airfoil is designed with convex-concaved leading edges, and the 3-dimensional flows around the bionic wing are simulated for the drag reduction purpose.
The 3-D Numerical Simulations for the Standard and Bionic Wing The chord length of standard wing is 0.2m and wingspan is 0.4m( see Fig. 1), the wingspan of bionic wing is 0.4m, the maximum chord length is at the point 0.12m and 0.28m of the wingspan, which is 0.11m; the minimum chord length is at the point 0.04m, 0.2m and 0.36m of the wingspan, which is 0.09m(see Fig. 2).
The 3-D Numerical Simulations for the Standard and Bionic Wing The chord length of standard wing is 0.2m and wingspan is 0.4m( see Fig. 1), the wingspan of bionic wing is 0.4m, the maximum chord length is at the point 0.12m and 0.28m of the wingspan, which is 0.11m; the minimum chord length is at the point 0.04m, 0.2m and 0.36m of the wingspan, which is 0.09m(see Fig. 2).