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May 29, 2026Renewable Energy1 citationsOpen Access

Performance Optimization and Prediction Model of Pump as Turbine Using Latin Hypercube Sampling

Performance optimization and prediction model of pump as turbine based on Latin hypercube sampling

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Authors

YZYu-Liang ZhangHHHui-Fan HuangYZYan-Juan Zhao

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Overview

Randomized trial explores geometric parameters' impact on pump efficiency, indicating optimization opportunities.

Key Points

  • This research aims to understand how specific geometric parameters of pumps as turbines influence their performance. It identifies optimization strategies for improving efficiency.
  • Used three correlation analysis methods: Pearson, Spearman, and standardized linear regression.
  • Established 60 numerical calculation models based on Latin hypercube sampling.
  • Analyzed the influence of 4 key geometric parameters on turbine performance.
  • The blade wrap angle shows a strong negative correlation with efficiency (Pearson r = -0.85).
  • The impeller outlet width has a strong positive correlation with efficiency (Pearson r = 0.90).
  • The constructed regression models show goodness of fit between 0.92 and 0.941.

Cite This Study

Zhang et al. (2026) studied this question.

synapsesocial.com/papers/6a192e18fab5b468c44171f2https://doi.org/10.1016/j.renene.2026.126004
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