Simpler Is Better—Calibration of Pipe Roughness in Water Distribution Systems

Abstract

Hydraulic models of water distribution systems (WDSs) need to be calibrated, so they can be used to help to make informed decisions. Usually, hydraulic model calibration follows an iterative process of comparing the simulation results from the model with field observations and making adjustments to model parameters to make sure an acceptable level of agreement between predicted and measured values (e.g., water pressure) has been achieved. However, the manual process can be time-consuming, and the termination criterion relies on the modeler’s judgment. Therefore, various optimization-based calibration methods have been developed. In this study, three different optimization methods, i.e., Sequential Least Squares Programming (SLSQP), a Genetic Algorithm (GA) and Differential Evolution (DE), are compared for calibrating the pipe roughness of WDS models. Their performance is investigated over four different decision variable set formulations with different levels of discretization of the search space. Results obtained from a real-world case study demonstrate that compared to traditional engineering practice, optimization is effective for hydraulic model calibration. However, a finer search space discretization does not necessarily guarantee better results; and when multiple methods lead to similar performance, a simpler method is better. This study provides guidance on method and formulation selection for calibrating WDS models.

Two Iterative Methods for Sizing Pipe Diameters in Gas Distribution Networks with Loops

“…(A) Classical flow distribution problem in already existing networks of pipe with loops: A network for gas distribution is typically assumed to be predefined with an established topology (route [81]), including the pipe dimensions (length and diameter) and their characteristics (mostly the roughness of the inner pipe surface, which is a function of the material and age [82]), as well as the predetermined maximum gas consumption at network nodes (with gas income in the network treated as negative consumption). For such a network, assuming that pressure drops cannot compress the gas significantly, the flow distribution through the pipes of the network can be calculated for the steady state and usually for the working condition designed for the maximal load, i.e., for the largest possible consumption.…”

Symbolic Regression Approaches for the Direct Calculation of Pipe Diameter

“…Uncertainty of measurement: Some parameters, such as the roughness of the inner surface of pipes ε cannot be easily measured [56][57][58][59]. The values of physical roughness measured in dry pipes cannot always be used directly in hydraulic calculations under certain flow conditions due to the existence of a viscose sublayer near the inner wall of the pipe wall (e.g., all types of pipes, new or used, are treated as smooth during laminar flow [60]).…”

A Review of Sources of Uncertainty in Optimization Objectives of Water Distribution Systems

“…Model structure uncertainty refers to the discrepancy between the mathematical representation of reality and the reality itself [6]. Model parameter uncertainty is the uncertainty in model parameter values, for example, pipe roughness factors, which cannot be directly measured and therefore need to be determined in a model calibration process [6,7]. Model parameters for WDS optimization can also include other variables when additional models are used for specific purposes.…”