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<p>This study focuses on characterizing the rock mass at the Pare Hydroelectric Power&#xa0;Project Site in Papumpare district, Arunachal Pradesh, India, using multiple classification systems. Accurately assessing rock mass strength is crucial for the safe construction of key project components, including the dam foundation, headrace tunnel, powerhouse pit, and surge shaft. This evaluation is conducted through comprehensive classification systems, utilizing data from geological and geotechnical investigations, such as drill holes, drifts, and Triaxial Compression tests. These investigations provide essential parameters for assessing rock mass quality. The rock mass at Pare is classified using Indian Standard (IS) Codes alongside various Classification systems. The study presents a range of rock mass index values, which play a vital role in designing the necessary support structures at any power project sites. Furthermore, the back-calculated tunneling quality index, derived from the specified support systems, is compared with the&#xa0;values obtained&#xa0;from IS Codes. The results&#xa0;thus obtained from&#xa0;the process of Characterization in terms of rock mass indices are used to develop empirical correlations through regression analysis, which are validated using performance indicators. The findings indicate that the empirical correlations between rock mass indices provide a better fit than previously established models.</p>

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Characterization of Pare Rock Mass in North East India using Various Classification systems

  • 期刊论文

  • 发表日期：

    2025年6月24日

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  • Pawan Kumar Singh,
  • Diganta Goswami

摘要

This study focuses on characterizing the rock mass at the Pare Hydroelectric Power Project Site in Papumpare district, Arunachal Pradesh, India, using multiple classification systems. Accurately assessing rock mass strength is crucial for the safe construction of key project components, including the dam foundation, headrace tunnel, powerhouse pit, and surge shaft. This evaluation is conducted through comprehensive classification systems, utilizing data from geological and geotechnical investigations, such as drill holes, drifts, and Triaxial Compression tests. These investigations provide essential parameters for assessing rock mass quality. The rock mass at Pare is classified using Indian Standard (IS) Codes alongside various Classification systems. The study presents a range of rock mass index values, which play a vital role in designing the necessary support structures at any power project sites. Furthermore, the back-calculated tunneling quality index, derived from the specified support systems, is compared with the values obtained from IS Codes. The results thus obtained from the process of Characterization in terms of rock mass indices are used to develop empirical correlations through regression analysis, which are validated using performance indicators. The findings indicate that the empirical correlations between rock mass indices provide a better fit than previously established models.