Simulation of thermal transpiration flow using a high-order moment method

2014 ◽  
Vol 25 (11) ◽  
pp. 1450061 ◽  
Author(s):  
Qiang Sheng ◽  
Gui-Hua Tang ◽  
Xiao-Jun Gu ◽  
David R. Emerson ◽  
Yong-Hao Zhang

Nonequilibrium thermal transpiration flow is numerically analyzed by an extended thermodynamic approach, a high-order moment method. The captured velocity profiles of temperature-driven flow in a parallel microchannel and in a micro-chamber are compared with available kinetic data or direct simulation Monte Carlo (DSMC) results. The advantages of the high-order moment method are shown as a combination of more accuracy than the Navier–Stokes–Fourier (NSF) equations and less computation cost than the DSMC method. In addition, the high-order moment method is also employed to simulate the thermal transpiration flow in complex geometries in two types of Knudsen pumps. One is based on micro-mechanized channels, where the effect of different wall temperature distributions on thermal transpiration flow is studied. The other relies on porous structures, where the variation of flow rate with a changing porosity or pore surface area ratio is investigated. These simulations can help to optimize the design of a real Knudsen pump.

2006 ◽  
Vol 55 (5) ◽  
pp. 2657
Author(s):  
Zhang Wen ◽  
Gao Xin-Quan ◽  
Dong Wen-Jie ◽  
Li Jian-Ping

2011 ◽  
Vol 261-263 ◽  
pp. 873-877
Author(s):  
Wei Li

Normal transformation technique is often used in practical probabilistic analysis in structural or civil engineering especially when multivariate random variables with the probabilistic characteristics expressed using only statistical moments are involved. In this paper, a modified high-order moment method(MHOM) is given based on the polynomial coefficients of a third-order normal transformation polynomial (NTP) using the first four central moments of random variables having unknown distributions. The present high-order moment method is introduced into several typical test problems having unknown distributions are available. Since it needs neither the computation of derivatives nor iteration, and since it is unnecessary to know the probability distribution of the basic random variables, the present method should be practical in actual reliability problems. Applications to several typical examples have helped to elucidate the successful working of the present MHOM.


2013 ◽  
Vol 341 (1-2) ◽  
pp. 55-64 ◽  
Author(s):  
Aymeric Vié ◽  
Frédérique Laurent ◽  
Marc Massot

1993 ◽  
Author(s):  
K. T. Tsang ◽  
C. Kostas ◽  
A. Mondelli

Sign in / Sign up

Export Citation Format

Share Document