Multiphase Flow in Porous Media
The development and solution, via numerical analysis, of the equations governing the evolution of non-aqueous phase liquids in the subsurface is the focus of this research. The objective is to develop mathematical models that describe the flow, transport and transformation of non-aqueous phase contaminants, such as trichloroethylene, that constitute a threat to groundwater quality.
Least-cost Groundwater Remediation Design
The use of groundwater simulators in combination with linear and non-linear programming algorithms to obtain the least-cost design of groundwater-remediation systems is the focus of this research effort. Flow and transport models of contaminated groundwater reservoirs are coupled to operations-research programming algorithms. Objective functions (usually based upon cost) are combined with design constraints to obtain the least-cost remediation-design While pump-and-treat systems have been the focus to date, other strategies are also considered. Of particular interest at this time is the study of problems involving non-aqueous phase contaminants and bioremediation.
Least-cost Long-term Groundwater Quality Monitoring
The use of groundwater flow and transport models that exhibit random-field based parameter distributions (for example hydraulic conductivity) in combination with Kalman-Filter algorithms to formulate least-cost strategies for the long-term monitoring of groundwater quality is the focus of this research area. Using these computational tools it is possible to determine where and when to sample groundwater in order to assure that statistical objectives are met at minimal cost.
Latin-hypercube Sampling for Random-field Generation
The use of Latin-hypercube statistical sampling to generate correlated random fields, such as hydraulic conductivity,that are subsequently used in Monte-Carlo analysis of state variables such as hydraulic head or concentration, is the main focus of this work. By using the Latin-hypercube approach it is possible to obtain the target statistical accuracy needed in Monte-Carlo analysis with less computational effort. The proposed approach is being developed as a sub-problem associated with long-term monitoring.
The development of new numerical techniques for the solution of partial-differential equations, such as those that describe the evolution of groundwater contaminants, is the focus of this research area. Finite-element methods, especially those based upon collocation-like methods, are of primary concern. The development of new and more efficient algebraic approaches for the solution of the resulting discrete equations is also of interest. Current efforts focus on the development of a single-degree of freedom strategy for solving transport-like equations and non-linear flow equations arising out of multiphase flow in porous media.
Assessment of Risk using Fuzzy Sets and Fuzzy Logic
The use of fuzzy knowledge-based systems to describe and evaluate risk, especially health risk identified with exposure to toxic chemicals is the focus of this research effort. Using the fuzzy approach expert opinion can be used to formulate a risk-based model that can subsequently be used to determine health risks associated with new levels of exposure or new exposure pathways. The approach specifically avoids the need to explicitly use questionable statistical data on dose-response relationships that have been developed using animal studies and high-dose concentrations.
Intermediate Scale Groundwater Facility
The design and construction of an intermediate-scale model , and the design, fabrication and installation of sophisticated instrumentation for monitoring various state variables for the evaluation of various theoretical concepts, is the goal of this research effort. Experiments designed to evaluate the efficacy of computer generated optimal remediation and optimal monitoring designs will be conducted in the facility. Concentration, pressure, temperature and saturation variables will be monitored using state-of-the art hardware and software.