An inverse design method for determining the optimal tributary flow into a main stream in a rainstorm period

To ensure water quality at the control cross-section of main streams (CCMS) in a rainstorm period, an inverse design method was proposed to determine the optimal discharge flow of tributary rivers. The design variables are tributary discharges and the target variables are the required concentrations...

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Autores principales:	Lei Liu, Huimin Chen, Xue-Yi You
Formato:	article
Lenguaje:	EN
Publicado:	IWA Publishing 2021
Materias:	artificial neural network genetic algorithm inverse design method optimization stormwater tributary flow Water supply for domestic and industrial purposes TD201-500 River, lake, and water-supply engineering (General) TC401-506
Acceso en línea:	https://doaj.org/article/9bfdf18b629a4b94b4b99ff7e52e754c
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spelling	oai:doaj.org-article:9bfdf18b629a4b94b4b99ff7e52e754c2021-11-06T10:08:53ZAn inverse design method for determining the optimal tributary flow into a main stream in a rainstorm period1606-97491607-079810.2166/ws.2021.089https://doaj.org/article/9bfdf18b629a4b94b4b99ff7e52e754c2021-09-01T00:00:00Zhttp://ws.iwaponline.com/content/21/6/3180https://doaj.org/toc/1606-9749https://doaj.org/toc/1607-0798To ensure water quality at the control cross-section of main streams (CCMS) in a rainstorm period, an inverse design method was proposed to determine the optimal discharge flow of tributary rivers. The design variables are tributary discharges and the target variables are the required concentrations of chemical oxygen demand (COD), dissolved oxygen (DO) and ammonia nitrogen (NH3-N) at CCMS. The relationship between target variables and design variables was identified using an artificial neural network (ANN). The database was obtained by Environmental Fluid Dynamics Code (EFDC) and the optimal tributary discharges were obtained by a genetic algorithm (GA) coupled with well trained ANN. The results showed the following results: (a) The relative prediction errors of ANN are mostly less than 5%. (b) When the inlet flow rate is 0 m3/s, 30 m3/s, 50 m3/s, 100 m3/s and 200 m3/s, the optimization total discharges of tributaries are 5.7 m3/s, 12.5 m3/s, 18.6 m3/s, 33.4 m3/s and 61.8 m3/s, respectively. (c) Most of optimization plans entirely satisfy the water quality requirements at CCMS except a few plans, in which the relative errors between optimized results and required values of COD and DO are less than 0.4% and 0.1%, respectively. The study showed that the inverse design method is efficient for determining the optimal discharges of multiple tributaries. HIGHLIGHTS An inverse design method of Environmental Fluid Dynamics Code, artificial neural network and genetic algorithm is proposed.; The optimal discharge of multiple tributaries into mainstream is obtained.; The optimal discharge schemes satisfy the water quality requirement of a main stream.; The inverse design method is proved to be highly efficient.;Lei LiuHuimin ChenXue-Yi YouIWA Publishingarticleartificial neural networkgenetic algorithminverse design methodoptimizationstormwatertributary flowWater supply for domestic and industrial purposesTD201-500River, lake, and water-supply engineering (General)TC401-506ENWater Supply, Vol 21, Iss 6, Pp 3180-3192 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	artificial neural network genetic algorithm inverse design method optimization stormwater tributary flow Water supply for domestic and industrial purposes TD201-500 River, lake, and water-supply engineering (General) TC401-506
spellingShingle	artificial neural network genetic algorithm inverse design method optimization stormwater tributary flow Water supply for domestic and industrial purposes TD201-500 River, lake, and water-supply engineering (General) TC401-506 Lei Liu Huimin Chen Xue-Yi You An inverse design method for determining the optimal tributary flow into a main stream in a rainstorm period
description	To ensure water quality at the control cross-section of main streams (CCMS) in a rainstorm period, an inverse design method was proposed to determine the optimal discharge flow of tributary rivers. The design variables are tributary discharges and the target variables are the required concentrations of chemical oxygen demand (COD), dissolved oxygen (DO) and ammonia nitrogen (NH3-N) at CCMS. The relationship between target variables and design variables was identified using an artificial neural network (ANN). The database was obtained by Environmental Fluid Dynamics Code (EFDC) and the optimal tributary discharges were obtained by a genetic algorithm (GA) coupled with well trained ANN. The results showed the following results: (a) The relative prediction errors of ANN are mostly less than 5%. (b) When the inlet flow rate is 0 m3/s, 30 m3/s, 50 m3/s, 100 m3/s and 200 m3/s, the optimization total discharges of tributaries are 5.7 m3/s, 12.5 m3/s, 18.6 m3/s, 33.4 m3/s and 61.8 m3/s, respectively. (c) Most of optimization plans entirely satisfy the water quality requirements at CCMS except a few plans, in which the relative errors between optimized results and required values of COD and DO are less than 0.4% and 0.1%, respectively. The study showed that the inverse design method is efficient for determining the optimal discharges of multiple tributaries. HIGHLIGHTS An inverse design method of Environmental Fluid Dynamics Code, artificial neural network and genetic algorithm is proposed.; The optimal discharge of multiple tributaries into mainstream is obtained.; The optimal discharge schemes satisfy the water quality requirement of a main stream.; The inverse design method is proved to be highly efficient.;
format	article
author	Lei Liu Huimin Chen Xue-Yi You
author_facet	Lei Liu Huimin Chen Xue-Yi You
author_sort	Lei Liu
title	An inverse design method for determining the optimal tributary flow into a main stream in a rainstorm period
title_short	An inverse design method for determining the optimal tributary flow into a main stream in a rainstorm period
title_full	An inverse design method for determining the optimal tributary flow into a main stream in a rainstorm period
title_fullStr	An inverse design method for determining the optimal tributary flow into a main stream in a rainstorm period
title_full_unstemmed	An inverse design method for determining the optimal tributary flow into a main stream in a rainstorm period
title_sort	inverse design method for determining the optimal tributary flow into a main stream in a rainstorm period
publisher	IWA Publishing
publishDate	2021
url	https://doaj.org/article/9bfdf18b629a4b94b4b99ff7e52e754c
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An inverse design method for determining the optimal tributary flow into a main stream in a rainstorm period

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