Development of environmental modeling methodologies for supporting system simulation, optimization and process control in petroleum waste management

In this dissertation research, a set of environmental modeling methodologies has been developed. They include (i) a DPVE-aided (dual-phase-vacuum-extraction-aided) remediation and contaminant transport modeling system (DRCT), (ii) an interval fuzzy programming method with violation analysis (IFVA), (iii) a hybrid simulation-optimization approach for real-time dynamic modeling and process control (HSOPC), and (iv) an integrated process control system based on numerical modeling, stepwise cluster analysis, and discrete-nonlinear optimization for supporting decisions of remediation practices (IPCS). These methods have been applied to a number of western Canadian cases for petroleum waste management and pollution mitigation planning.;The developed IFVA can deal with systems with high uncertainties (in which the related parameters are of wide intervals) through permitting levels of tolerable violation for environmental constraints. Thus, solutions from the violation analysis will not necessarily satisfy all of the model's original constraints. The IFVA was applied to a petroleum waste management system. The results can help generate a number of decision alternatives under various system conditions, allowing in-depth analyses of tradeoffs between environmental and economic objectives as well as those between system optimality and reliability.;The HSOPC has been developed through combining a 3D multi-phase and multi-component subsurface model with a dual-response surface model (DRSM) and a nonlinear optimization system for generating desired operation conditions under various site conditions. The developed methodology was applied to a real-world case study in western Canada. The results can provide bases for guiding real-time process control of surfactant-enhanced remediation under various site conditions. They are also useful for decision makers to analyze tradeoffs between system cost and treatment efficiency.;The IPCS has been developed based on numerical modeling, stepwise cluster analysis, and nonlinear optimization. Firstly, stepwise cluster analysis was used to establish a bridge between remediation operation practices and respondent benzene concentrations in the groundwater. Secondly, nonlinear and discrete optimization models were developed to determine optimal operating conditions. Finally, process control for enhanced in-situ biodegradation was accomplished through incorporating the developed forecasters and optimizers with methods of genetic algorithm and neural networks modeling. The developed control system can support decisions of operation conditions in a real-time manner.;The DRCT has been developed by combining a three-dimension (3D) multiphase and multicomponent subsurface model and a DPVE process model into a general modeling frame. It was applied to a petroleum-contaminated site in western Canada. The DRCT is effective in simulating effects of free-product recovery and groundwater cleanup through processes of DPVE and groundwater remediation. It represents a unique contribution to the fields of groundwater systems modeling and petroleum waste management.