Drag on an ellipsoid particle in free-molecular plasma flow

Based on the analysis of molecular gas dynamics, the drag and moment acting on an ellipsoid particle of revolution X-2/a(2) + Y-2/a(2) + Z(2)/c(2) = 1, as an example of nonspherical particles, are studied under the condition of free-molecular plasma flow with thin plasma sheaths. A nonzero moment which causes nonspherical particle self-oscillation and self-rotation around its own axis in the plasma flow-similar to the pitching moment in aerodynamics-is discovered for the first time. When the ratio of axis length c/a is unity, the moment is zero and the drag formula are reduced to the well-known results of spherical particles. The effects of the particle-plasma relative velocity, the plasma temperature, and the particle materials on the drag and moment are also investigated.

Triple-region structure for turbulent-flow in a square duct - a finite-element approach

The Reynolds-averaged Navier-Stokes equations for describing the turbulent flow in a straight square duct are formulated with two different turbulence models. The governing equations are then expanded as a multi-deck structure in a plane perpendicular to the streamwise direction, with each deck characterized by its dominant physical forces as commonly carried out in analytical work using triple-deck expansion. The resulting equations are numerically integrated using higher polynomial (H-P) finite element technique for each cross-sectional plane to be followed by finite difference representation in the streamwise direction until a fully developed state is reached. The computed results using the two different turbulence models show fair agreement with each other, and concur with the vast body of available experimental data. There is also general agreement between our results and the recent numerical works anisotropic k-epsilon turbulence model.

Computation of turbulent-flow in a square duct - aspects of the secondary flow and its origin

A numerical study of turbulent flow in a straight duct of square cross-section is made. An order-of-magnitude analysis of the 3-D, time-averaged Navier-Stokes equations resulted in a parabolic form of the Navier-Stokes equations. The governing equations, expressed in terms of a new vector-potential formulation, are expanded as a multi-deck structure with each deck characterized by its dominant physical forces. The resulting equations are solved using a finite-element approach with a bicubic element representation on each cross-sectional plane. The numerical integration along the streamwise direction is carried out with finite-difference approximations until a fully-developed state is reached. The computed results agree well with other numerical studies and compare very favorably with the available experimental data. One important outcome of the current investigation is the interpretation analytically that the driving force of the secondary flow in a square duct comes mainly from the second-order terms of the difference in the gradients of the normal and transverse Reynolds stresses in the axial vorticity equation.

Multiscale Method for Turbulent-Flow Computations

A main method of predicting turbulent flows is to solve LES equations, which was called traditional LES method. The traditional LES method solves the motions of large eddies of size larger than filtering scale An while modeling unresolved scales less than Delta_n. Hughes et al argued that many shortcomings of the traditional LES approaches were associated with their inabilities to successfully differentiate between large and small scales. One may guess that a priori scale-separation would be better, because it can predict scale-interaction well compared with posteriori scale-separation. To this end, a multi-scale method was suggested to perform scale-separation computation. The primary contents of the multiscale method are l) A space average is used to differentiate scale. 2) The basic equations include the large scale equations and fluctuation equations. 3) The large-scale equations and fluctuation equations are coupled through turbulent stress terms. We use the multiscale equations of n=2, i.e., the large and small scale (LSS) equations, to simulate 3-D evolutions of a channel flow and a planar mixing layer flow Some interesting results are given.

Some characteristics of thin shear layers in homogeneous turbulent flow.

Tomographic particle image velocimetry measurements of homogeneous isotropic turbulence that have been made in a large mixing tank facility at Cambridge are analysed in order to characterize thin highly sheared regions that have been observed. The results indicate that such regions coincide with regions of high enstrophy, dissipation and stretching. Large velocity jumps are observed across the width of these regions. The thickness of the shear layers seems to scale with the Taylor microscale, as has been suggested previously. The results discussed here concentrate on examining individual realizations rather than statistics of these regions.

Laminar to turbulent flow transition measurements using an array of SOI-CMOS MEMS wall shear stress sensors

The successful utilization of an array of silicon on insulator complementary metal oxide semiconductor (SOICMOS) micro thermal shear stress sensors for flow measurements at macro-scale is demonstrated. The sensors use CMOS aluminum metallization as the sensing material and are embedded in low thermal conductivity silicon oxide membranes. They have been fabricated using a commercial 1 μm SOI-CMOS process and a post-CMOS DRIE back etch. The sensors with two different sizes were evaluated. The small sensors (18.5 ×18.5 μm2 sensing area on 266 × 266 μm2 oxide membrane) have an ultra low power (100 °C temperature rise at 6mW) and a small time constant of only 5.46 μs which corresponds to a cut-off frequency of 122 kHz. The large sensors (130 × 130 μm2 sensing area on 500 × 500 μm2 membrane) have a time constant of 9.82 μs (cut-off frequency of 67.9 kHz). The sensors' performance has proven to be robust under transonic and supersonic flow conditions. Also, they have successfully identified laminar, separated, transitional and turbulent boundary layers in a low speed flow. © 2008 IEEE.

A FEniCS-based programming framework for modeling turbulent flow by the Reynolds-averaged Navier-Stokes equations

Finding an appropriate turbulence model for a given flow case usually calls for extensive experimentation with both models and numerical solution methods. This work presents the design and implementation of a flexible, programmable software framework for assisting with numerical experiments in computational turbulence. The framework targets Reynolds-averaged Navier-Stokes models, discretized by finite element methods. The novel implementation makes use of Python and the FEniCS package, the combination of which leads to compact and reusable code, where model- and solver-specific code resemble closely the mathematical formulation of equations and algorithms. The presented ideas and programming techniques are also applicable to other fields that involve systems of nonlinear partial differential equations. We demonstrate the framework in two applications and investigate the impact of various linearizations on the convergence properties of nonlinear solvers for a Reynolds-averaged Navier-Stokes model. © 2011 Elsevier Ltd.

A numerical investigation of the flow structures and losses for turbulent flow in 90 degrees elbow bends

Computational fluid dynamic modelling was carried out on a series of pipe bends having R/r values of 1.3, 5, and 20, with the purpose of determining the accuracy of numerical models in predicting pressure loss data from which to inform one-dimensional loss models. Four separate turbulence models were studied: the standard k-epsilon model, realizable k-epsilon model, k-omega model, and a Reynolds stress model (RSM). The results are presented for each bend in the form of upstream and downstream pressure profiles, pressure distributions along the inner and outer walls, detailed pressure and velocity fields as well as overall loss values. In each case, measured data were presented to evaluate the predictive ability of each model. The RSM was found to perform the best, producing accurate pressure loss data for bends with R/r values of 5 and 20. For the tightest bend with an R/r value of 1.3, however, predictions were significantly worse due to the presence of flow separation, stronger pressure gradients, and high streamline curvature.