A Comparison of Response Surface Methodology and a One-Factor-At-A-Time Approach as Calibration Techniques for the Bioplume-II Simulation Model of Contaminant Biodegradation

Abstract

This thesis compared Response Surface Methodology (RSM) to the one-factor-at-a-time approach for calibrating the Bioplume-II simulation model of contaminant biodegradation. The MADE-2 data set from Columbus Air Force Base, Mississippi was used. The one-factor-at-a-time approach reduced the root-mean-squared (RMS) error for the flow to 0.921225 feet in a total of 36 runs of Bioplume-II. The RSM approach reduced the error criterion to 0.918875 in a total of 47 runs. The one-factor-at-a-time approach was unable to reduce the error below 67.1831 parts per billion (ppb) after 21 runs. The RSM approach reduced the RMS error to 67.0327 ppb after 47 runs. The RSM approach allows the modeler to identify parametric regions of improved response in a systematic way that would be extremely difficult to find using the one-factor-at-a-time approach. Limitations of this work included the use of inefficient full factorial designs and the poor assumption of homogeneous parameter values.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1995
Accession Number
ADA305879

Entities

People

  • Benjamin Shuman

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Air Force
  • Biodegradation
  • Calibration
  • Cyclic Hydrocarbons
  • Data Science
  • Data Sets
  • Engineering
  • Factorial Design
  • Fungi
  • Groundwater
  • Information Science
  • Microbiology
  • Microorganisms
  • Operations Research
  • Regression Analysis
  • Simulations
  • United States

Fields of Study

  • Agricultural and Food sciences

Readers

  • Computational Modeling and Simulation
  • Groundwater Contamination Remediation.