Regression Analysis as a Cost Estimation Model for Unexploded Ordnance Cleanup at Former Military Installations

Abstract

Throughout the 1990s, the Department of Defense has undergone numerous changes in an effort to save money and bring the military infrastructure in line with the National Security Strategy. One of the major ways of reducing military infrastructure has been through the Base Realignment and Closure program. Before an installation can be formally turned over to the local community, the military service owning the base has to certify that the land is environmentally safe for reuse. One of the greatest problems discovered on former weapons training installations is the numerous pieces of Unexploded Ordnance that were located either on the surface or just below the surface in soil that will be reworked for land development projects by local city developers. This thesis provides a comprehensive case study of the former Fort Ord installation as the Army goes through the process of cleaning up Unexploded Ordnance so that the property can be given to the City of Seaside, CA and other civilian entities. A mathematical model is developed to better estimate cleanup costs using historical cost data that could be used by the Defense Department prior to placing installations on any future closure lists.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2002
Accession Number
ADA405942

Entities

People

  • Ronald B. Ross

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Biomedical
  • Counter IED
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Ammunition
  • Base Closures
  • Cost Analysis
  • Environment
  • Environmental Protection
  • Environmental Restoration And Remediation
  • Information Science
  • Mathematical Models
  • Munitions
  • National Security
  • Natural Resources
  • Personnel Management
  • Public Health
  • Regression Analysis
  • Statistical Analysis
  • Training
  • Unexploded Ammunition

Readers

  • Emergency Management and Homeland Security.
  • Energy Conservation and Renewable Energy Engineering.
  • Explosive Engineering.