TY - GEN

T1 - Sequential estimation of demand and roughness in water distribution system

AU - Kang, Doosun

AU - Lansey, Kevin

PY - 2012/1/30

Y1 - 2012/1/30

N2 - Pipe roughness and water consumption at a demand node are the most uncertain input variables in a simulation model because they are not typically directly measurable. Instead, information provided from field measurements are used to estimate them indirect way. Parameter estimation is the process of adjusting model parameters so that the simulation model represents the real system adequately by fitting the model output to the field data. To provide more accurate estimates and account for all associated uncertainties, the two variables, i.e., demand and roughness, must be estimated simultaneously. This study proposes a two-step sequential method for dual estimation of demand and roughness coefficient based on a weighted least squares (WLS) scheme using field measurements of pipe flow rates and nodal pressure heads under multiple demand loading conditions. The algorithm is applied to a simple hypothetical system using synthetically generated field data. The proposed two-step sequential model provides accurate estimates with little effort in terms of simulation time.

AB - Pipe roughness and water consumption at a demand node are the most uncertain input variables in a simulation model because they are not typically directly measurable. Instead, information provided from field measurements are used to estimate them indirect way. Parameter estimation is the process of adjusting model parameters so that the simulation model represents the real system adequately by fitting the model output to the field data. To provide more accurate estimates and account for all associated uncertainties, the two variables, i.e., demand and roughness, must be estimated simultaneously. This study proposes a two-step sequential method for dual estimation of demand and roughness coefficient based on a weighted least squares (WLS) scheme using field measurements of pipe flow rates and nodal pressure heads under multiple demand loading conditions. The algorithm is applied to a simple hypothetical system using synthetically generated field data. The proposed two-step sequential model provides accurate estimates with little effort in terms of simulation time.

KW - demand estimation

KW - roughness coefficient

KW - sequential method

KW - weighted least squares

UR - http://www.scopus.com/inward/record.url?scp=84856170129&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84856170129&partnerID=8YFLogxK

U2 - 10.1061/41203(425)115

DO - 10.1061/41203(425)115

M3 - Conference contribution

AN - SCOPUS:84856170129

SN - 9780784412039

T3 - Water Distribution Systems Analysis 2010 - Proceedings of the 12th International Conference, WDSA 2010

SP - 1279

EP - 1286

BT - Water Distribution Systems Analysis 2010 - Proceedings of the 12th International Conference, WDSA 2010

T2 - 12th Annual International Conference on Water Distribution Systems Analysis 2010, WDSA 2010

Y2 - 12 September 2010 through 15 September 2010

ER -