Comprehensive Regression‐Based Sensitivity Analysis of Geometric Parameter Effects on Gas Turbine Nozzle Performance and Stage Characteristics

The global rise in electrical energy demand is placing strain on conventional power generation methods, such as thermal, hydroelectric, and nuclear plants. These sources are often insufficient to meet increasing demand, particularly in remote areas where grid connectivity is economically unfeasible. One potential solution is the implementation of localized power generation systems, such as low‐flow turbines, which are highly suitable for small‐scale energy production. These turbines offer an efficient means of supplying power to isolated regions, bypassing the need for large capital investments in new infrastructure. This study focuses on improving the efficiency of low‐flow turbines by analyzing the geometric characteristics of their critical components, particularly the nozzle apparatus. The nozzle plays a pivotal role in shaping flow dynamics, which significantly influences the turbine’s overall performance. Using regression analysis, the research evaluates the impact of various geometric parameters on turbine efficiency, identifying key empirical relationships and sensitivity factors. The results provide a comprehensive understanding of how geometric modifications can affect flow processes within the turbine stage, ultimately enhancing performance. This work contributes to optimizing low‐flow turbines for small‐scale power generation, addressing energy challenges in remote and underserved regions.

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Publication Details

Journal
International Journal of Energy Research
Published
2025-01-01
DOI
https://doi.org/10.1155/er/7548518
Primary Topic
Turbomachinery Performance and Optimization
Type
article
Field-Weighted Citation Impact
0.00

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article

Comprehensive Regression‐Based Sensitivity Analysis of Geometric Parameter Effects on Gas Turbine Nozzle Performance and Stage Characteristics

Kseniia Iurevna Usanova, Mikhail A. Laptev, A P Shirokikh, Viktor Barskov et al.
International Journal of Energy Research
Turbomachinery Performance and Optimization
article

Comprehensive Regression‐Based Sensitivity Analysis of Geometric Parameter Effects on Gas Turbine Nozzle Performance and Stage Characteristics

Kseniia Iurevna Usanova, Mikhail A. Laptev, A P Shirokikh, Viktor Barskov, Mehdi Basati Panah, В. А. Рассохин, Kirill Alisov, Ivan Talabira, A. Y. Balakin, Mikhail Kanakin, Anton Pulin, Gleb Roshchenko
article en

Abstract

The global rise in electrical energy demand is placing strain on conventional power generation methods, such as thermal, hydroelectric, and nuclear plants. These sources are often insufficient to meet increasing demand, particularly in remote areas where grid connectivity is economically unfeasible. One potential solution is the implementation of localized power generation systems, such as low‐flow turbines, which are highly suitable for small‐scale energy production. These turbines offer an efficient means of supplying power to isolated regions, bypassing the need for large capital investments in new infrastructure. This study focuses on improving the efficiency of low‐flow turbines by analyzing the geometric characteristics of their critical components, particularly the nozzle apparatus. The nozzle plays a pivotal role in shaping flow dynamics, which significantly influences the turbine’s overall performance. Using regression analysis, the research evaluates the impact of various geometric parameters on turbine efficiency, identifying key empirical relationships and sensitivity factors. The results provide a comprehensive understanding of how geometric modifications can affect flow processes within the turbine stage, ultimately enhancing performance. This work contributes to optimizing low‐flow turbines for small‐scale power generation, addressing energy challenges in remote and underserved regions.

International Journal of Energy ResearchVol. 2025(1)
Peter the Great St. Petersburg Polytechnic University (RU), Russian New University (RU), Iran University of Science and Technology (IR)
Ministry of Science and Higher Education of the Russian Federation
Openalex Percentile: Top 75%
Turbomachinery Performance and Optimization
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