Modelling the dynamics of treadle pump for its design optimization.
Published In: Sādhanā: Academy Proceedings in Engineering Sciences, 2025, v. 50, n. 3. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: HONKALASKAR, VIJAY; MEVADA, HET; DEO, ANIKET; CHAVAN, SUSHANT; MARLA, DEEPAK 3 of 3
Abstract
Treadle pumps are promising manual pumping alternatives for low gravitational suction and delivery head conditions. The operation of a treadle pump comprises dynamics of the motions of the centre of mass of the operator, treadles, pistons with piston rods and fluid columns. The present article presents a comprehensive steady-state analytical model for the operation of a treadle pump, with the aim of designing key pump parameters and achieving maximum discharge for the given farm field conditions. The analytical model of the pump was developed by formulating the equations of motions of the centre of mass of the operator, treadles and pistons with piston rods. The model integrates the dynamics of the operator's motion with the treadle pump system, making it a uniquely comprehensive model. The validation of the discharge flow rate of the numerical model confirms good agreement with experimental results, with a deviation of 5–10% for different pump parameters. Parametric analysis of different treadle pump parameters using the numerical model showed an increase in flow rate with suction and discharge diameters, and stroke length, while an optimum value of mechanical advantage exists for different field conditions. Lastly, the model is used to optimize the design parameters of the treadle pump for different field conditions to deliver maximum flow rate. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Sādhanā: Academy Proceedings in Engineering Sciences. 2025/09, Vol. 50, Issue 3, p1
- Document Type:Article
- Subject Area:Engineering
- Publication Date:2025
- ISSN:0256-2499
- DOI:10.1007/s12046-025-02827-6
- Accession Number:186909521
- Copyright Statement:Copyright of Sādhanā: Academy Proceedings in Engineering Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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