Date of Award

3-2000

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Systems Engineering and Management

First Advisor

Mark N. Goltz, PhD

Abstract

In this work, genetic algorithms (GAs) were used to help interpret tracer breakthrough curves from partitioning interwell tracer tests (PITTs) conducted at Hill AFB, Utah by researchers from the University of Florida. Two transport models were developed to simulate tracer transport in the test cells. One model assumed the cell consisted of multiple layers, and that transport in each layer could he described by the one-dimensional advective/dispersive equation. The second model also assumed multiple layers, and modeled transport in the individual layers as advective transport through 100 tubes. Transport times were represented by a stochastic (lognormal) distribution. The model solutions were coded into Microsoft Excel. Model parameters were optimized using Evolutionary Solver, a GA developed by Froutline Systems. The optimized parameters were used to estimate pre-and post-flushing NAPL saturations, as well as cleanup efficiency. Results were compared to estimates obtained through moment analysis of me PITT data. Results demonstrated that GAS are a tool that may be useful in interpreting PITT data for the characterization of NAPL source areas. In particular, using the GAs to interpret PITT data provided more information than could he obtained from moment analysis.

AFIT Designator

AFIT-GEE-ENV-00M-17

DTIC Accession Number

ADA377108

Comments

The author's Vita page is omitted.

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