Amazon.com: Optimizing of In Situ Bioremediation Technology to Manage Perchlorate- Contaminated Groundwater (9781423502609): Mark R. Knarr: Books

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Optimizing of In Situ Bioremediation Technology to Manage Perchlorate- Contaminated Groundwater
 
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Optimizing of In Situ Bioremediation Technology to Manage Perchlorate- Contaminated Groundwater [Spiral-bound]

Mark R. Knarr (Author)


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Book Description

2003
This is a AIR FORCE INST OF TECH WRIGHT-PATTERSONAFB OH SCHOOL OF ENGINEERING report procured by the Pentagon and made available for public release. It has been reproduced in the best form available to the Pentagon. It is not spiral-bound, but rather assembled with Velobinding in a soft, white linen cover. The Storming Media report number is A023514. The abstract provided by the Pentagon follows: Combining horizontal flow treatment wells (HFTWs) with in situ biodegradation is an innovative approach with the potential to remediate perchlorate-contaminated groundwater. A technology model was recently developed that combines the groundwater flow induced by HFTWs with in situ biodegradation processes that result from using the HFTWs to mix electron donor into perchlorate-contaminated groundwater. A field demonstration of this approach is planned to begin this year. In order to apply the technology in the field, project managers need to understand how contaminated site conditions and technology design parameters impact technology performance. One way to gain this understanding is to use the technology model to select engineering design parameters that optimize performance under given site conditions. In particular, a project manager desires to design a system that: 1) maximizes perchlorate destruction; 2) minimizes treatment expense; and 3) attains regulatory limits on down gradient contaminant concentrations. Unfortunately, for a relatively complex technology with a number of engineering design parameters to determine, as well as multiple objectives, system optimization is not straightforward. In this study, a multi-objective genetic algorithm (MOGA) is used to determine design parameter values (flow rate, well spacing, concentration of injected electron donor, and injection schedule) that optimize the first two objectives noted; to maximize perchlorate destruction while minimizing cost.

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