TY - GEN
T1 - Real-time implementation of contamination source identification method for water distribution systems
AU - De Sanctis, Annamaria E.
AU - Hachett, Sam
AU - Uber, James G.
AU - Boccelli, Dominic L.
AU - Shang, Feng
PY - 2009
Y1 - 2009
N2 - A contamination source identification methodology should be continuously run in real time to provide timely information about contamination event status. The method should be robust with respect to uncertainty and variability in factors affecting the network hydraulic model. This work assesses the impact of hydraulic modeling errors on the performance of a source identification algorithm. Preliminary results evaluate the effect of demand estimation errors on the performance of the identification algorithm. Results suggest the source identification method can be robust to the types of errors investigated. It is stressed, however, that broader conclusions can not be drawn, because the tests consider only one network test case, and the true statistical characteristics of stochastic demands are unknown. Furthermore, the particular example chosen assumes optimistic scenarios for demand estimation. The results provide a methodology and motivation for continuing to investigate the true performance characteristics of real-time contamination source identification algorithms.
AB - A contamination source identification methodology should be continuously run in real time to provide timely information about contamination event status. The method should be robust with respect to uncertainty and variability in factors affecting the network hydraulic model. This work assesses the impact of hydraulic modeling errors on the performance of a source identification algorithm. Preliminary results evaluate the effect of demand estimation errors on the performance of the identification algorithm. Results suggest the source identification method can be robust to the types of errors investigated. It is stressed, however, that broader conclusions can not be drawn, because the tests consider only one network test case, and the true statistical characteristics of stochastic demands are unknown. Furthermore, the particular example chosen assumes optimistic scenarios for demand estimation. The results provide a methodology and motivation for continuing to investigate the true performance characteristics of real-time contamination source identification algorithms.
KW - Contamination source identification
KW - Real-time calibration model
UR - http://www.scopus.com/inward/record.url?scp=70350158091&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70350158091&partnerID=8YFLogxK
U2 - 10.1061/41036(342)53
DO - 10.1061/41036(342)53
M3 - Conference contribution
AN - SCOPUS:70350158091
SN - 9780784410363
T3 - Proceedings of World Environmental and Water Resources Congress 2009 - World Environmental and Water Resources Congress 2009: Great Rivers
SP - 544
EP - 553
BT - Proceedings of World Environmental and Water Resources Congress 2009 - World Environmental and Water Resources Congress 2009
T2 - World Environmental and Water Resources Congress 2009: Great Rivers
Y2 - 17 May 2009 through 21 May 2009
ER -