# Estimating RQD for Rock Masses Based on a Comprehensive Approach
## 6 Conclusions  
Commonly used methods for calculating the RQD leverage fracture network simulation technology. Typically, the number of virtual boreholes selected is based more on empirical selection rather than a quantitative analysis. Furthermore, repeated Monte Carlo stochastic simulations often yield varying RQD results. Considering the influence of the borehole count and model numbers on RQD simulations, this paper introduces a novel methodology for quantitatively determining the threshold of the number of virtual boreholes and the number of models. This approach relies on the CNNCV and class ratio analysis methods. By employing the threshold number of boreholes and models, our method yields a representative RQD for a specific size. Simultaneously, acknowledging the impact of the model size on RQD simulations, we propose a class-ratio-analysis-based method for determining the model size threshold. The representative RQD corresponding to this size threshold is then considered as the representative RQD for the rock mass. A case study at the Lamping Lead-Zinc Mine, China, demonstrates the practicality and efficiency of the proposed method. The results show that, as the number of simulation models of the same size increases, fluctuations in the lower and upper confidence limits, as well as the mean value of the RQD samples, decrease before stabilizing. Furthermore, an increased number of models leads to a reduced width of the confidence interval for the RQD, indicating higher precision in the estimation. Ensuring a reliable RQD(\(D\)) requires restricting the width of the confidence interval within 0.02 through an adequate number of RQD samples. The RQD calculation results between the proposed method and the traditional single-model approach exhibit a difference that diminishes with increasing model sizes. At the 95% confidence level, the stable size of the RQD determined using the proposed method is 13 m, compared to 25 m for the single-model approach. This method enhances the accuracy of the representative elementary volume prediction by accounting for the diversity in the simulation results of RQDs for the same size. Although the proposed approach offers an efficient way to obtain RQDs for geotechnical engineering, acquiring representative RQD values necessitates a large number of RQD samples, resulting in inefficiency. Future research will focus on exploring influencing factors on the threshold for the number of virtual boreholes and the number of models to develop estimation formulas that ease the application process, facilitating effective implementation for practitioners. Conceptualization, J.Y. and R.Y. ; methodology, R.Y., J.Y. and L.H. ; software, W.S. ; validation, W.S. ; formal analysis, W.N. ; investigation, W.S. and R.Y. ; resources, W.N. and R.Y. ; data curation, W.S. ; writing--original draft preparation, W.S., L.H. and R.Y. ; writing--review and editing, W.S., L.H. and R.Y. ; visualization, W.S., R.Y. and L.H. ; supervision, W.N., R.Y. and Z.L. ; project administration, W.N., Z.L. and S.D. ; funding acquisition, W.N., R.Y. and S.D. All authors have read and agreed to the published version of the manuscript. **Funding:** This research was funded by the National Natural Science Foundation of China, grant No. 42177117 and No. 42277147, and the Zhejiang Collaborative Innovation Center for the Prevention and Control of Mountain Geological Hazards, grant No. PCMGH-2017-Z03. **Informed Consent Statement:** Not applicable. **Data Availability Statement:** The data presented in this study are available on request from the corresponding author. The data are not publicly available due to the dataset includes private information that could potentially identify participants or organizations involved in the research. **Acknowledgments:** The authors would like to thank all who participated in this study, with their best wishes going out to their rigorous academic teachers. The authors would also like to express gratitude to their parents for their silent support.