题目：A Multivariate Markovian Arrival Process for Modeling Contaminant Transport through Porous Media

报告人：Professor P Patrick Wang，Department of
Mathematics，University of Alabama

时间：6月16日上午10-12点
地点：方正301会议室
主持人：郑春苗 教授

摘要：
A multivariate Markovian arrival process (MMAP) is presented to model a variety of solute transport phenomena in porous media. MMAP is based on a stochastic model that generalizes many counting processes, including Poisson processes, Markov
modulated Poisson processes, and phase-type renewal processes. In the MMAP model, each site in the aquifer is decomposed into a number of conceptual modules. Mass transfers occurs between the modules. The overall governing equations are vector-formed, first-order differential equations. The resulting probability distributions from MMAP are shown to exhibit both normal Gaussian-type behaviors and long-tailed breakthrough curves, depending on the MMAP
structure. In addition, this study also shows the relationship between the parameters in the MMAP model and those in solute transport equations so
that these probability distribution functions from MMAP can be interpreted as solute concentrations in heterogeneous aquifers. MMAP is shown to be a general formulation that includes the traditional advection-dispersion model, dual-domain and multiple-rate mass transfer models, and continuous-time random walk models
(CTRW). Numerical examples are used to demonstrate the flexibility and efficiency of the MMAP models.

报告人简介：
Dr. Patrick Wang is a professor in the Department of Mathematics at the University of Alabama.  He is an applied mathematician with research interests in stochastic modeling and its applications to groundwater transport.  His publications have addressed transport solution techniques, groundwater remediation system
optimization, and stochastic uncertainty analysis. He is co-author with Chunmiao Zheng of the widely used MT3D transport model. He received a Ph.D. in industrial engineering in 1990 from Lehigh University.

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