Year: 2016
Type: dissertation
Abstract: The calibration of water distribution systems networks (WDN) is a complex non-linear problem that \nhas traditionally been solved using manual trial-and-error methods. Over the past few decades, \nautomated calibration techniques have been the subject of a great deal of research, and significant \nadvancements in the field of WDN calibration have been achieved. Despite these advancements in \ncalibration techniques, and the development and application of automated tools in numerous research \nsettings, most practitioners still rely on engineering judgment and traditional calibration methods for \nWDN calibration. In an effort to bridge the gap between practitioners and researchers, the value of \nthese advanced calibration approaches relative to traditional methods is validated and quantified in a \nreal world scenario. \nCity X’s WDN model has been manually calibrated by engineers familiar with the system. Their \ncalibration procedure was mainly an expert-based approach using judgment and trial-and-error and \ndid not rely on automated optimization tools. The purpose of this study is to resolve the \ncorresponding calibration problem with optimization tools and compare the calibration solutions in \nterms of quality (closeness to measured data) and calibration parameter values. The calibration \nproblem is posed as a multi-objective optimization problem and solved with the PA-DDS algorithm. \nThe precise calibration objectives are roughly matched to the manual calibration objectives specified \nby the engineers who calibrated the model. Multi-objective optimization results are compared against \nthe manually calibrated model, and the potential benefit of applying an automated approach is \nassessed. The utilization of automated calibration methods is shown to clearly assist in parameter \nerror detection and model quality improvement. \nTo further improve the quality of the calibrated model, the initial results from the automated \ncalibration are used to guide a manual calibration effort. Upon the manual adjustment of macrocalibration parameters, the automated calibration tools are used again to quantify the parameter \nuncertainty. As such, the calibration approach is iterative, and based upon the effective application of \nautomated calibration tools coupled with traditional trial-and-error methods. Several thousand unique \nsolutions of approximately equal or greater quality than the existing manually calibrated model are \ngenerated. 89 of the most robust solutions are identified in an effort to parsimoniously capture the \nmodel parameter uncertainty. Ideally, this list of candidate solutions can be used in future operational \nstudies to ensure that operational decisions are robust to a wide range of potential network conditions. \nMoreover, particularly uncertain model parameters are identified so as to focus future field studies, \nand data collection efforts.
Source: UWSpace (University of Waterloo)
Author: Ayman E. Khedr
Language: English
Subfield: Civil and Structural Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2296132707