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dc.contributor.authorPanwar, Dinesh
dc.contributor.authorTiwari, Nand Kumar
dc.date.accessioned2026-08-20T11:10:23Z
dc.date.available2026-08-20T11:10:23Z
dc.date.copyright2026/03/25
dc.date.issued2026
dc.identifier.otherJIDEDH.IRENG-10716.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4311793
dc.description.abstractAbstractThis study introduces a machine learning (ML) framework to optimize Venturi flume design for improved aeration efficiency (E20) and discharge coefficient (Cd) for sustainable water management. Six flume geometries: three fundamental Venturi flumes ...Practical ApplicationsVenturi flumes play a crucial role in both aeration and accurate flow measurement, distinguishing themselves from traditional drop structures such as weirs, cascades, and spillways through their low head loss and high precision under ...
dc.publisherAmerican Society of Civil Engineers
dc.titleOptimizing Venturi Flume Design for Sustainable Water Management: Bridging Flow Accuracy and Aeration Efficiency through Experimental and Machine-Learning Approaches
dc.typeJournal Article
dc.journal.volume152
dc.journal.issue3
dc.journal.titleJournal of Irrigation and Drainage Engineering
dc.identifier.doi10.1061/JIDEDH.IRENG-10716
dc.journal.fristpage04026003-1
dc.journal.lastpage04026003-20
dc.page20
dc.treeJournal of Irrigation and Drainage Engineering:;2026:;Volume ( 152 ):;issue: 003
dc.contenttypeFulltext


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