Exploring the practical application of genetic programming for stormwater drain inlet hydraulic efficiency estimation

Ekmekcioğlu*, E. E. Başakın, M. Özger

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

The hydraulic efficiency of stormwater inlets is generally described as the ratio of the intercepted flow and the approach flow. Thus, determining the approach flow is of paramount importance as well as the captured flow by the grate inlet. To calculate the discharge captured through the inlet, not only parameters related to the flow conditions and representing the grate inlet geometry but also the relevant information regarding the physical properties of the road are required. In this study, a state-of-the-art soft computing method, the genetic programming (GP) was employed to obtain the intercepted flow. The data obtained by the laboratory experiments as well as the datasets collected from the past studies in pertinent literature were utilized to build the proposed model. Eventually, an equation was generated for the determination of drain inlet hydraulic efficiency. It is worth mentioning that the performance of the GP-based model was evaluated according to several performance metrics using the training (70%) and the testing set (30%). Furthermore, the contribution of the current research was also highlighted based on the comparison of the proposed model and empirical equations presented in the literature. In this sense, a new perspective has been introduced to the researchers, engineers, manufacturers, and related professionals by presenting an accurate and robust equation to conduct effective stormwater management strategies.

Original languageEnglish
Pages (from-to)1489-1502
Number of pages14
JournalInternational Journal of Environmental Science and Technology
Volume20
Issue number2
DOIs
Publication statusPublished - Feb 2023

Bibliographical note

Publisher Copyright:
© 2022, The Author(s) under exclusive licence to Iranian Society of Environmentalists (IRSEN) and Science and Research Branch, Islamic Azad University.

Funding

This study was supported by the Scientific Research Projects (BAP) Department of Istanbul Technical University (Project Number: MGA-2019-41864). Therefore, we would like to thank BAP for the financial support of the project. We would also like to thank three anonymous reviewers for improving the quality of the paper with their constructive comments.

FundersFunder number
Istanbul Teknik ÜniversitesiMGA-2019-41864

    Keywords

    • Artificial intelligence
    • Drainage
    • Genetic programming
    • Grate inlet
    • Hydraulic efficiency
    • Laboratory experiment
    • Stormwater discharge

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