Don Kulasiri

Professor Don Kulasiri obtained B.Sc. (Hons) in Mechanical Engineering (1980) at University of Peradeniya, Sri Lanka, M.S. (1988) and PhD (1990) at Department of Biological Systems Engineering, Virginia Tech, U.S.A. His main research interests are in developing mathematical and computational models of biological and environmental systems to explain the experimental data, and to pursue these interests he has been developing research programmes at Lincoln University, Christchurch, New Zealand since 1991. He was appointed to a personal chair (professorship) in 1999 at Lincoln University, and he has been a visiting professor at the Computation and Mechanics division, Stanford University (6 months in 1998), Department of Mathematics, Princeton University (6 months in 2004) and Mathematical Institute, Oxford University (6 months in 2008 and a month in 2010). He has been a supervisor or co-supervisor of 30 PhD students so far, and co-authored over 100 journal publications and three books. He has been active in Computational Molecular Systems Biology for the last six years.

1books edited

9chapters authored

Latest work with IntechOpen by Don Kulasiri

This research monograph presents a mathematical approach based on stochastic calculus which tackles the “cutting edge” in porous media science and engineering – prediction of dispersivity from covariance of hydraulic conductivity (velocity). The problem is of extreme importance for tracer analysis, for enhanced recovery by injection of miscible gases, etc. This book explains a generalised mathematical model and effective numerical methods that may highly impact the stochastic porous media hydrodynamics. The book starts with a general overview of the problem of scale dependence of the dispersion coefficient in porous media. Then a review of pertinent topics of stochastic calculus that would be useful in the modeling in the subsequent chapters is succinctly presented. The development of a generalised stochastic solute transport model for any given velocity covariance without resorting to Fickian assumptions from laboratory scale to field scale is discussed in detail. The mathematical approaches presented here may be useful for many other problems related to chemical dispersion in porous media.

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