Sanjay Mittal

Bio: Sanjay Mittal is an academic researcher from Indian Institute of Technology Kanpur. The author has contributed to research in topics: Reynolds number & Vortex shedding. The author has an hindex of 39, co-authored 167 publications receiving 6713 citations. Previous affiliations of Sanjay Mittal include University of Minnesota & Indian Institutes of Technology.

Incompressible flow computations with stabilized bilinear and linear equal-order-interpolation velocity-pressure elements

Abstract: Finite element formulations based on stabilized bilinear and linear equal-order-interpolation velocity-pressure elements are presented for computation of steady and unsteady incompressible flows. The stabilization procedure involves a slightly modified Galerkin/least-squares formulation of the steady-state equations. The pressure field is interpolated by continuous functions for both the quadrilateral and triangular elements used. These elements are employed in conjunction with the one-step and multi-step time integration of the Navier-Stokes equations. The three test cases chosen for the performance evaluation of these formulations are the standing vortex problem, the lid-driven cavity flow at Reynolds number 400, and flow past a cylinder at Reynolds number 100.

A new strategy for finite element computations involving moving boundaries and interfaces—the deforming-spatial-domain/space-time procedure. II: Computation of free-surface flows, two-liquid flows, and flows with drifting cylinders

Abstract: New finite element computational strategies for free-surface flows, two-liquid flows, and flows with drifting cylinders are presented. These strategies are based on the deforming spatial-domain/spacetime (DSD/ST) procedure. In the DSD/ST approach, the stabilized variational formulations for these types of flow problem are written over their space-time domains. One of the important features of the approach is that it enables one to circumvent the difficulty involved in remeshing every time step and thus reduces the projection errors introduced by such frequent remeshings. Computations are performed for various test problems mainly for the purpose of demonstrating the computational capability developed for this class of problems. In some of the test cases, such as the liquid drop problem, surface tension is taken into account. For flows involving drifting cylinders, the mesh moving and remeshing schemes proposed are convenient and reduce the frequency of remeshing.

Parallel finite-element computation of 3D flows

Abstract: The authors describe their work on the massively parallel finite-element computation of compressible and incompressible flows with the CM-200 and CM-5 Connection Machines. Their computations are based on implicit methods, and their parallel implementations are based on the assumption that the mesh is unstructured. Computations for flow problems involving moving boundaries and interfaces are achieved by using the deformable-spatial-domain/stabilized-space-time method. Using special mesh update schemes, the frequency of remeshing is minimized to reduce the projection errors involved and also to make parallelizing the computations easier. This method and its implementation on massively parallel supercomputers provide a capability for solving a large class of practical problems involving free surfaces, two-liquid interfaces, and fluid-structure interactions. >

Computation of unsteady incompressible flows with the stabilized finite element methods: Space-time formulations, iterative strategies and massively parallel implementations

Abstract: We discuss the stabilized finite element computation of unsteady incompressible flows, with emphasis on the space-time formulations, iterative solution techniques and implementations on the massively parallel architectures such as the Connection Machines. The stabilization technique employed in this paper is the Galerkin/least-squares (GLS) method. The Deformable-Spatial-Domain/Stabilized-Space-Time (DSD/SST) formulation was developed for computation of unsteady viscous incompressible flows which involve moving boundaries and interfaces. In this approach, the stabilized finite element formulations of the governing equations are written over the space-time domain of the problem, and therefore the deformation of the spatial domain with respect to time is taken into account automatically. This approach gives us the capability to solve a large class of problems with free surfaces, moving interfaces, and fluid-structure and fluid-particle interactions. In the DSD/SST approach the frequency of remeshing is minimized to minimize the projection errors involved in remeshing and also to increase the parallelization potential of the computations. We present a new mesh moving scheme that minimizes the need for remeshing; in this scheme the motion of the mesh is governed by the modified equations of linear homogeneous elasticity. The implicit equation systems arising from the finite element discretizations are solved iteratively by using the GMRES search technique with the clustered element-by-element, diagonal and nodal-block-diagonal preconditioners. Formulations with diagonal and nodal-block-diagonal preconditioners have been implemented on the Connection Machines CM-200 and CM-5. We also describe a new mixed preconditioning method we developed recently, and discuss the extension of this method to totally unstructured meshes. This mixed preconditioning method is similar, in philosophy, to multi-grid methods, but does not need any intermediate grid levels, and therefore is applicable to unstructured meshes and is simple to implement. The application problems considered include various free-surface flows and simple fluid-structure interaction problems such as vortex-induced oscillations of a cylinder and flow past a pitching airfoil.

Boundary Layer Theory

Abstract: The boundary layer equations for plane, incompressible, and steady flow are $$\matrix{ {u{{\partial u} \over {\partial x}} + v{{\partial u} \over {\partial y}} = - {1 \over \varrho }{{\partial p} \over {\partial x}} + v{{{\partial ^2}u} \over {\partial {y^2}}},} \cr {0 = {{\partial p} \over {\partial y}},} \cr {{{\partial u} \over {\partial x}} + {{\partial v} \over {\partial y}} = 0.} \cr }$$

ACC/AHA/SCAI 2005 Guideline Update for Percutaneous Coronary Intervention-summary article : A report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (ACC/AHA/SCAI Writing Committee to Update the 2001 Guidelines for Percutaneous Coronary Intervention)

Abstract: The American College of Cardiology/American Heart Association/Society for Cardiovascular Angiography and Interventions (ACC/AHA/SCAI) 2005 Guideline Update for Percutaneous Coronary Intervention (PCI) contains changes in the recommendations, along with supporting text. For the purpose of comparison

Artificial neural networks for solving ordinary and partial differential equations

Abstract: We present a method to solve initial and boundary value problems using artificial neural networks. A trial solution of the differential equation is written as a sum of two parts. The first part satisfies the initial/boundary conditions and contains no adjustable parameters. The second part is constructed so as not to affect the initial/boundary conditions. This part involves a feedforward neural network containing adjustable parameters (the weights). Hence by construction the initial/boundary conditions are satisfied and the network is trained to satisfy the differential equation. The applicability of this approach ranges from single ordinary differential equations (ODE), to systems of coupled ODE and also to partial differential equations (PDE). In this article, we illustrate the method by solving a variety of model problems and present comparisons with solutions obtained using the Galerkin finite element method for several cases of partial differential equations. With the advent of neuroprocessors and digital signal processors the method becomes particularly interesting due to the expected essential gains in the execution speed.

Total quality management.

Abstract: THE NEED FOR QUALITY The first thing that we need to consider, in any organization, is that quality is the most important thing. The quality of your work defines you.  Whoever you are,  Whatever you do,  I can find the same products and services cheaper somewhere else. But your quality is your signature. Developing and delivering high quality products and services means that you are doing things correctly from the beginning. As a consequence, you are reducing the need for additional services, from verification to warranty.