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

Published: 17 October 2022Hydraulic 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.Qi Zhao, Wenyan Wu, Angus R. Simpson and Ailsa Willi

Enrichment of Wind Turbine Health History for Condition-Based Maintenance

This research develops a methodology for and shows the benefit of linking records of wind turbine maintenance. It analyses commercially sensitive real-world maintenance records with the aim of improving the productivity of offshore wind farms. The novel achievements of this research are that it applies multi-feature record linkage techniques to maintenance data, that it applies statistical techniques for the interval estimation of a binomial proportion to record linkage techniques and that it estimates the distribution of the coverage error of statistical techniques for the interval estimation of a binomial proportion. The main contribution of this research is a process for the enrichment of offshore wind turbine health history. The economic productivity of a wind farm depends on the price of electricity and on the suitability of the weather, both of which are beyond the control of a maintenance team, but also on the cost of operating the wind farm, on the cost of maintaining the wind turbines and on how much of the wind farm’s potential production of electricity is lost to outages. Improvements in maintenance scheduling, in condition-based maintenance, in troubleshooting and in the measurement of maintenance effectiveness all require knowledge of the health history of the plant. To this end, this thesis presents new techniques for linking together existing records of offshore wind turbine health history. Multi-feature record linkage techniques are used to link records of maintenance data together. Both the quality of record linkage and the uncertainty of that quality are assessed. The quality of record linkage was measured by comparing the generated set of linked records to a gold standard set of linked records identified in collaboration with offshore wind turbine maintenance experts. The process for the enrichment of offshore wind turbine health history developed in this research requires a vector of weights and thresholds. The agreement and disagreement weights for each feature indicate the importance of the feature to the quality of record linkage. This research uses differential evolution to globally optimise this vector of weights and thresholds. There is inevitably some uncertainty associated with the measurement of the quality of record linkage, and consequently with the optimum values for the weights and thresholds; this research not only measures the quality of record linkage but also identifies robust techniques for the estimation of its uncertainty.