Don Kulasiri

Lincoln University New Zealand

Professor Don Kulasiri is a professor (personal chair) and has been head of the Centre for Advanced Computational Solutions (C-fACS) at Lincoln University since 1999. His research theme is to understand the mathematical basis for biological and environmental phenomena based on physics broadly construed to assimilate data-driven machine learning and AI in phenomenological models. He has been a visiting professor at the Mathematical Institute, Oxford University, the UK, since 2008; Princeton University, USA (2004, 2006); and the Mechanics and Computation Division, Stanford University, USA (1998) and a fellow of the New Zealand Centre at Peking University (2018) and of the Modelling and Simulation Society of Australia and New Zealand (MSSANZ). He has published over 190 publications and authored six research monographs on his research with leading international publishers.

Don Kulasiri

1books edited

11chapters 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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