AWWA WQTC60606

AWWA WQTC60606 A Markov Chain Monte Carlo Approach to Network Model Calibration Using Tracer Tests
Conference Proceeding by American Water Works Association, 11/15/2004

Boccelli, Dominic L.; Uber, James G.

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A preliminary Markov chain Monte Carlo (MCMC) calibration algorithm is presented forestimating the demand pattern multipliers of a distribution system network model utilizingtracer test data. A simple 35 node distribution system network is used to generate a synthetictracer study data set over a 55-hour simulation time. The MCMC calibration algorithm isable to reproduce the 55-hour demand pattern multipliers from an initial guess absent of anytemporal information. This preliminary study for the MCMC calibration algorithm providesthe basis for extending the capabilities to include spatial correlation of user demands. Includes 5 references, figures.