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Sudarshan Tiwari

Researcher at Kaiserslautern University of Technology

Publications -  68
Citations -  1016

Sudarshan Tiwari is an academic researcher from Kaiserslautern University of Technology. The author has contributed to research in topics: Boltzmann equation & Knudsen number. The author has an hindex of 16, co-authored 67 publications receiving 906 citations. Previous affiliations of Sudarshan Tiwari include Fraunhofer Society & Daimler AG.

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Journal ArticleDOI

Self-propelled interacting particle systems with roosting force

TL;DR: This work considers a self-propelled interacting particle system for the collective behavior of swarms of animals, and extends it with an attraction term called roosting force, as it has been suggested in Ref. 30, which models the tendency of birds to overfly a fixed preferred location, e.g. a nest or a food source.
Book ChapterDOI

Finite Pointset Method Based on the Projection Method for Simulations of the Incompressible Navier-Stokes Equations

TL;DR: In this paper, a Lagrangian particle scheme is applied to the projection method for the incompressible Navier-Stokes equations, and the approximation of spatial derivatives is obtained by the weighted least squares method.
Journal ArticleDOI

Modeling of two-phase flows with surface tension by finite pointset method (FPM)

TL;DR: In this paper, a mesh-free method for two-phase immiscible incompressible flows including surface tension is presented, where the Navier-Stokes equation is considered as the mathematical model and implicit projection method results in linear second-order partial differential equations for velocities and pressure.
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An adaptive domain decomposition procedure for Boltzmann and Euler equations

TL;DR: In this article, a domain decomposition approach for the coupling of Boltzmann and Euler equations is presented, which leads to a simple implementation of the coupling procedure and to natural interface conditions between the two domains.
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Finite pointset method for simulation of the liquid–liquid flow field in an extractor

TL;DR: The results show that FPM can predict the one- and two-phase flow field in the RDC, whereas the predicted velocities are in good agreement with the experimental ones.