Suhas V. Patankar

Bio: Suhas V. Patankar is an academic researcher from University of Minnesota. The author has contributed to research in topics: Heat transfer & Turbulence. The author has an hindex of 42, co-authored 135 publications receiving 7165 citations. Previous affiliations of Suhas V. Patankar include Innovative Research Inc..

Simulating Boundary Layer Transition With Low-Reynolds-Number k–ε Turbulence Models: Part 2—An Approach to Improving the Predictions

Abstract: An approach for improving the prediction of boundary layer transition with k−e type low-Reynolds-number turbulence models is developed and tested. A modification is proposed that limits the production term in the turbulent kinetic energy equation and is based on a simple stability criterion and correlated to the free-stream turbulence level

Block-correction-based multigrid method for fluid flow problems

Abstract: A coupled-point solution procedure employing a multilevel correction strategy is developed and test results are presented in this article. The method is based on the principle of deriving the coarse-grid discretization equations from the fine-grid discretization equations. The adaptive scheme is applied to the sample problems of laminar flow in lid-driven square and cubic cavities and flow over a backward-facing step. The study demonstrates that the multigrid method is robust and rapidly convergent, resulting in improvement in CPU requirements by a factor of approximately S to 15 compared to the sequential signal-grid SIMPLER procedure. The performance of procedure improves, in comparison to the SIMPLER, as the number of grid points increases.

Enhancements of the simple method for predicting incompressible fluid flows

Abstract: Variations of the SIMPLE method of Patankar and Spalding have been widely used over the past decade to obtain numerical solutions to problems involving incompressible flows. The present paper shows several modifications to the method which both simplify its implementation and reduce solution costs. The performances of SIMPLE, SIMPLER, and SIMPLEC (the present method) are compared for two recirculating flow problems. The paper is addressed to readers who already have experience with SIMPLE or its variants.

Numerical solution of saddle point problems

Abstract: Large linear systems of saddle point type arise in a wide variety of applications throughout computational science and engineering. Due to their indefiniteness and often poor spectral properties, such linear systems represent a significant challenge for solver developers. In recent years there has been a surge of interest in saddle point problems, and numerous solution techniques have been proposed for this type of system. The aim of this paper is to present and discuss a large selection of solution methods for linear systems in saddle point form, with an emphasis on iterative methods for large and sparse problems.

Error analysis and estimation for the finite volume method with applications to fluid flows

Abstract: The accuracy of numerical simulation algorithms is one of main concerns in modern Computational Fluid Dynamics. Development of new and more accurate mathematical models requires an insight into the problem of numerical errors. In order to construct an estimate of the solution error in Finite Volume calculations, it is first necessary to examine its sources. Discretisation errors can be divided into two groups: errors caused by the discretisation of the solution domain and equation discretisation errors. The first group includes insufficient mesh resolution, mesh skewness and non-orthogonality. In the case of the second order Finite Volume method, equation discretisation errors are represented through numerical diffusion. Numerical diffusion coefficients from the discretisation of the convection term and the temporal derivative are derived. In an attempt to reduce numerical diffusion from the convection term, a new stabilised and bounded second-order differencing scheme is proposed. Three new methods of error estimation are presented. The Direct Taylor Series Error estimate is based on the Taylor series truncation error analysis. It is set up to enable single-mesh single-run error estimation. The Moment Error estimate derives the solution error from the cell imbalance in higher moments of the solution. A suitable normalisation is used to estimate the error magnitude. The Residual Error estimate is based on the local inconsistency between face interpolation and volume integration. Extensions of the method to transient flows and the Local Residual Problem error estimate are also given. Finally, an automatic error-controlled adaptive mesh refinement algorithm is set up in order to automatically produce a solution of pre-determined accuracy. It uses mesh refinement and unrefinement to control the local error magnitude. The method is tested on several characteristic flow situations, ranging from incompressible to supersonic flows, for both steady-state and transient problems.