Modeling of modular limit of arc porous weirs using soft computing models

Subject Areas : watere sciences

Mehrdad Pirzad ¹ , Mohammad hossein purmohammadi ² , hossein ghorbanizadeh kharazi ³ , Mohsen Solimani Babarsad ⁴ , ehsan derikvand ⁵

1 - rDepartment of Civil Engineering, Water Resources Engineering and Management, Shoushtar Branch, Islamic Azad University, Shoushta
2 - گروه آب دانشگاه شوشتر
3 - Assistant professor
4 - عضو هیات علمی گروه آبیاری دانشگاه آزاد اسلامی واحد شوشتر
5 - Department of Water Science, Shoushtar Branch, Islamic Azad University, Shoushtar, Iran

Received: 2024-04-23 Accepted : 2024-08-10 Published : 2024-09-20

Keywords: flow measurement, free flow, submerged flow, experimental modeling, soft compute analysis,

Abstract :

Porous weirs, as environmentally friendly structures, are a suitable alternative to solid weirs commonly used in the water industry. One of the challenges in measuring flow in weirs is determining whether the flow is free or submerged. The modular limit index is used to distinguish between these two types of flow. This research evaluates the ability of an artificial neural network and combination with a optimization model to predict the modular limit index. To achieve this, a laboratory dataset was utilized. The experiments were conducted in a flume with dimensions of 20 m in length, 0.6 m in width, and 0.5 m in height. In total, 20 weir models were tested at various flow rates, resulting in 175 tests being performed. The modeling results indicated that the MLP model, with an average error of 7%, and the combined MLP-GNDO model, with an average error of 4%, successfully predicted the modular limit index value.

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