Linked Life Data

16889871

Source:http://linkedlifedata.com/resource/pubmed/id/16889871

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3-4
pubmed:dateCreated
2006-11-29
pubmed:abstractText
Contamination source identification is a crucial step in environmental remediation. The exact contaminant source locations and release histories are often unknown due to lack of records and therefore must be identified through inversion. Coupled source location and release history identification is a complex nonlinear optimization problem. Existing strategies for contaminant source identification have important practical limitations. In many studies, analytical solutions for point sources are used; the problem is often formulated and solved via nonlinear optimization; and model uncertainty is seldom considered. In practice, model uncertainty can be significant because of the uncertainty in model structure and parameters, and the error in numerical solutions. An inaccurate model can lead to erroneous inversion of contaminant sources. In this work, a constrained robust least squares (CRLS) estimator is combined with a branch-and-bound global optimization solver for iteratively identifying source release histories and source locations. CRLS is used for source release history recovery and the global optimization solver is used for location search. CRLS is a robust estimator that was developed to incorporate directly a modeler's prior knowledge of model uncertainty and measurement error. The robustness of CRLS is essential for systems that are ill-conditioned. Because of this decoupling, the total solution time can be reduced significantly. Our numerical experiments show that the combination of CRLS with the global optimization solver achieved better performance than the combination of a non-robust estimator, i.e., the nonnegative least squares (NNLS) method, with the same solver.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
0169-7722
pubmed:author
pubmed:issnType
Print
pubmed:day
15
pubmed:volume
88
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
181-96
pubmed:meshHeading
pubmed:year
2006
pubmed:articleTitle
A robust approach for iterative contaminant source location and release history recovery.
pubmed:affiliation
Geosciences and Engineering Division, Southwest Research Institute, 6220 Culebra Road, San Antonio, TX 78238, USA. asun@swri.org
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't