| contributor author | Panwar, Dinesh | |
| contributor author | Tiwari, Nand Kumar | |
| date accessioned | 2026-08-20T11:10:23Z | |
| date available | 2026-08-20T11:10:23Z | |
| date copyright | 2026/03/25 | |
| date issued | 2026 | |
| identifier other | JIDEDH.IRENG-10716.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl1/handle/yetl/4311793 | |
| description abstract | AbstractThis 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 ... | |
| publisher | American Society of Civil Engineers | |
| title | Optimizing Venturi Flume Design for Sustainable Water Management: Bridging Flow Accuracy and Aeration Efficiency through Experimental and Machine-Learning Approaches | |
| type | Journal Article | |
| journal volume | 152 | |
| journal issue | 3 | |
| journal title | Journal of Irrigation and Drainage Engineering | |
| identifier doi | 10.1061/JIDEDH.IRENG-10716 | |
| journal fristpage | 04026003-1 | |
| journal lastpage | 04026003-20 | |
| page | 20 | |
| tree | Journal of Irrigation and Drainage Engineering:;2026:;Volume ( 152 ):;issue: 003 | |
| contenttype | Fulltext | |