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August 5, 2026Energy Science & Engineering0 citationsOpen Access

Optimizing Gravitational Water Vortex Power Plant Runners Using Genetic Algorithms

Genetic Algorithm‐Driven Analysis of Gravitational Water Vortex Power Plant Runner Performance: A Comparative Study Integrating Experimental and Computational Fluid Dynamics

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Authors

ZMZakaria. A. MwakitwangeAFAdam Faraji

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Overview

Randomized trial analyzes performance optimization of GWVPP runners, suggesting improved efficiency and power outcomes.

Key Points

  • This investigation aims to optimize the performance of gravitational water vortex power plant runners using genetic algorithms and computational fluid dynamics.
  • Utilized genetic algorithm predictions alongside experimental data and computational fluid dynamics simulations for analysis.
  • Assessed performance parameters such as power, torque, and efficiency over a rotational speed range of 1.91–3.26 rad/s.
  • Conducted sensitivity analysis on factors influencing performance, including rotational speed, hub-blade angle, and blade number.
  • Performance improves with rotational speed, peaking around 2.6–2.7 rad/s, after which it declines.
  • GA predictions align closely with CFD simulations, validating the effectiveness of the GA in optimization.
  • Experimental results indicated lower efficiency at higher rotational speeds due to practical losses and measurement uncertainties.
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Cite This Study

Mwakitwange et al. (2026) studied this question.

synapsesocial.com/papers/6a72e831226790f370657e23https://doi.org/10.1002/ese3.70604
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