Statistical Characteristics and Calculation Methods of Reinforcement Ratio in Overall Structures and Substructures of Hydropower Plant Buildings

Accurately estimating the steel reinforcement volume in hydropower plant structures requires a clear understanding of the statistical patterns of reinforcement ratios. Based on engineering data from 11 completed hydropower plant buildings, this study employs mathematical statistical methods to systematically analyze the reinforcement ratios of the overall plant structure and its sub-structures (main and auxiliary buildings). The results indicate significant differences in reinforcement ratios among substructures, which exhibit weak correlations with one another. In contrast, the overall plant reinforcement ratio demonstrates clear statistical regularity, following a normal distribution (mean 78 kg/m3, standard deviation 13 kg/m3). The study further identifies the concrete proportion in main and auxiliary buildings, plant type, and hydraulic turbine type as key influencing factors. Based on these findings, a practical formula for estimating the overall reinforcement ratio was developed. Validation demonstrated that this formula yields estimation errors below 5% in most cases. This study not only reveals the statistical distribution patterns of reinforcement ratios but also establishes a theory-based estimation formula that addresses the limitations of existing empirical methods. The proposed approach provides a unified reference framework for preliminary design, filling the gap in systematic statistical analysis of reinforcement ratios in hydropower plant buildings.

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Publication Details

Journal
Applied Sciences
Published
2026-03-02
DOI
https://doi.org/10.3390/app16052411
Primary Topic
Dam Engineering and Safety
Type
article
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article

Statistical Characteristics and Calculation Methods of Reinforcement Ratio in Overall Structures and Substructures of Hydropower Plant Buildings

Xin He, Naifei Liu, Zijian Xiong, Chunyou Hao
Applied Sciences
Dam Engineering and Safety
article

Statistical Characteristics and Calculation Methods of Reinforcement Ratio in Overall Structures and Substructures of Hydropower Plant Buildings

Xin He, Naifei Liu, Zijian Xiong, Chunyou Hao
article en

Abstract

Accurately estimating the steel reinforcement volume in hydropower plant structures requires a clear understanding of the statistical patterns of reinforcement ratios. Based on engineering data from 11 completed hydropower plant buildings, this study employs mathematical statistical methods to systematically analyze the reinforcement ratios of the overall plant structure and its sub-structures (main and auxiliary buildings). The results indicate significant differences in reinforcement ratios among substructures, which exhibit weak correlations with one another. In contrast, the overall plant reinforcement ratio demonstrates clear statistical regularity, following a normal distribution (mean 78 kg/m3, standard deviation 13 kg/m3). The study further identifies the concrete proportion in main and auxiliary buildings, plant type, and hydraulic turbine type as key influencing factors. Based on these findings, a practical formula for estimating the overall reinforcement ratio was developed. Validation demonstrated that this formula yields estimation errors below 5% in most cases. This study not only reveals the statistical distribution patterns of reinforcement ratios but also establishes a theory-based estimation formula that addresses the limitations of existing empirical methods. The proposed approach provides a unified reference framework for preliminary design, filling the gap in systematic statistical analysis of reinforcement ratios in hydropower plant buildings.

Applied SciencesVol. 16(5)
Xi'an University of Architecture and Technology (CN), PowerChina (China) (CN)
Openalex Percentile: Top 39%
Dam Engineering and Safety
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Statistical Characteristics and Calculation Methods of Reinforcement Ratio in Overall Structures and Substructures of Hydropower Plant Buildings — Xin He, Naifei Liu, et al. · Applied Sciences (2026) | TGRS Research Map | TGRS