Experimental design and model parameter estimation for locating a dissolving dense nonaqueous phase liquid pool in groundwater

摘要: [1] This paper investigates the experimental design problem in context of estimating location and dimensions a dissolving dense nonaqueous phase liquid (DNAPL) pool an aquifer. The deals with selection number observation wells that minimizes parameter uncertainty while minimizing installation sampling costs. solution this multiobjective optimization is achieved by solving series combinatorial problems which, for each imposed budget constraint, optimal combination found. are solved genetic algorithm two different strategies: one where prior estimates not updated updating performed at end stage (sequential design). In latter case, obtained executing inverse model based on concentration values collected locations specified previous design. algorithms tested controlled, bench-scale dissolution experiment. results demonstrate sequential performs better terms final estimates. Three optimality criteria associated estimation compared: A optimality, D E optimality. Among three criteria, optimalities produce size, which justified appreciably variances parameters their high degree correlation.