| Popis: |
The Department of Defense's proposed Range Rule greatly increases the number of unexploded ordnance (UXO) contaminated sites that the services must decontaminate. Existing models for estimating the cost of UXO removal often require a high level of expertise and provide only a point estimate for the costs; they do not provide a probability distribution of the potential costs. This thesis presents a probabilistic cost estimation model created as an "add- in" for Microsoft Excel. A test database consisting of descriptive and cost information on the historic cleanup of nineteen contaminated areas is created. To demonstrate the model, the thesis filters the database to find eight historic records characteristically similar to a fictitious cleanup scenario, and uses information from these historic records to build probability distributions for six cost elements. The model applies Monte Carlo simulation to these probability distributions to build a probability distribution for the total cleanup cost. The resulting distribution shows that for this cleanup scenario the most likely per acre cost is $8,400, but there is a 75% chance that costs fall between $8, 500 and $26,000. Results for a scenario composed of three cleanups predicts a most likely total cost of $ 1.7 million with a 50% probability of costs falling between $1.7 million and $2.2 million. |
