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A Review of Optimal Design for Large-Scale Micro-Irrigation Pipe Network Systems.

Authors :
Wang, Yafei
Zhang, Yangkai
Wang, Wenjuan
Liu, Zhengguang
Yu, Xingjiao
Li, Henan
Wang, Wene
Hu, Xiaotao
Source :
Agronomy; Dec2023, Vol. 13 Issue 12, p2966, 24p
Publication Year :
2023

Abstract

Micro-irrigation pipe network systems are commonly utilized for water transmission and distribution in agricultural irrigation. They effectively transport and distribute water to crops, aiming to achieve water and energy conservation, increased yield, and improved quality. This paper presents a model for the scaled micro-irrigation pipeline network system and provides a comprehensive review of the fundamental concepts and practical applications of optimization techniques in the field of pipeline network design. This paper is divided into four main sections: Firstly, it covers the background and theoretical foundations of optimal design for scaled micro-irrigation pipeline network systems. Secondly, the paper presents an optimal design model specifically tailored for scaled micro-irrigation pipeline networks. And then, it discusses various optimization solution techniques employed for addressing the design challenges of scaled micro-irrigation pipeline networks, along with real-world case studies. Finally, this paper concludes with an outlook on the ongoing research and development efforts in the field of scaled micro-irrigation pipeline network systems. In addition, this paper establishes a fundamental model for optimizing pipeline networks, to achieve minimum safe operation and total cost reduction. It considers constraints such as pipeline pressure-bearing capacity, maximum flow rate, and diameter. The decision-making variables include pipeline diameter, length, internal roughness, node pressure, future demand, and valve placement. Additionally, this paper provides an extensive overview of deterministic methods and heuristic algorithms utilized in the optimal design of micro-irrigation pipeline networks. Finally, this paper presents future research directions for pipeline network optimization and explores the potential for algorithmic improvements, integration of machine learning techniques, and wider adoption of EPANET 2.0 software. These endeavors aim to lay a strong foundation for effectively solving complex and challenging optimization problems in micro-irrigation pipeline network systems in the future. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20734395
Volume :
13
Issue :
12
Database :
Complementary Index
Journal :
Agronomy
Publication Type :
Academic Journal
Accession number :
174402675
Full Text :
https://doi.org/10.3390/agronomy13122966