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Real-Time Water Distribution System Hydraulic Modeling Using Prior Demand Information by Formal Bayesian Approach
Citation:
Shao, Y., S. Chu, T. Zhang, J. Yang, AND T. Yu. Real-Time Water Distribution System Hydraulic Modeling Using Prior Demand Information by Formal Bayesian Approach. JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT. American Society of Civil Engineers (ASCE), Reston, VA, 145(12):04019059, (2019). https://doi.org/10.1061/(ASCE)WR.1943-5452.0001137
Impact/Purpose:
This article conveys the newest research on how to calibrate water distribution model using EPANET and to minimize the number of sensors required because of a more efficient algorithm to best use prior water demand information. The advances can be used by water professionals to better conduct water distribution system modeling, and thus manage water quality in distribution.
Description:
Real-time water distribution system (WDS) hydraulic models is being used in water utilities. The hydraulic models must be calibrated carefully before they are in use. Most existing calibration methods either require substantial computation resources or lack flexibility to link the real-time information, thus hindering their popular usage for real-time calibration. To address the issue, this study proposes an approach for WDS hydraulic model calibration. Nodal demands are estimated by a formal Bayesian method that explicitly takes prior consumer demand information into account. The goal is to make the estimated values satisfy WDS measurements and prior consumer demand. Application of the approach on a simple WDS and a real city WDS demonstrates that by adding prior information, the ill-posed problem can be transformed into a well-posed one and the model calibration result can meet both measured value and prior consumer demand. Results indicate that the proposed method is not only efficient in relation to evolutionary algorithm-based calibration approaches, but also accurate for calibration compared with previous methods.
URLs/Downloads:
DOI: Real-Time Water Distribution System Hydraulic Modeling Using Prior Demand Information by Formal Bayesian Approach
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