Multi-source data integration modeling and spatial analysis for optimal design of high-level radioactive waste geological repository (original) (raw)

Abstract

In the site evaluation, design, and construction of high-level radioactive waste (HLW) geological repositories, clear insight expression and reliable geological models are indispensable, while the spatial relationships between tunnel structures and affected zones are equally crucial for construction safety. However, traditional geological modeling methods using scarce preliminary data often suffer from loss of precision, and subsequent spatial analysis is frequently neglected. This paper presents a comprehensive methodological framework for refined modeling of the repository geological environment and tunnel structures, with particular emphasis on tunnel safety planning that incorporates spatial analysis of unfavorable geological bodies/interfaces. The geological potential prediction based on Universal Cokriging gradient field interpolation is developed using multi-source data derived from regional surveys. Safety control standards and optimization design processes are established to address the spatial layout of repository tunnels within geological bodies. The proposed framework is applied to China’s Beishan HLW repository project. Results demonstrate that data integration and modeling methods effectively enhance structural refinement. Modeling robustness is validated through systematic 10% incremental reductions in input data. Overall repository planning and layout incorporating geographic information system (GIS) principles enhance tunnel design safety and operational performance.

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Acknowledgements

This work was supported by Shanghai “Science and Technology Innovation Action Plan” Outstanding Academic/Technical Leaders Program (Project No. 23XD1431200), Shanghai “Science and Technology Innovation Action Plan” Social Development Science and Technology Research Project (Project No. 21DZ1201100), and Key Laboratory of Geotechnical and Underground Engineering of Ministry of Education, Tongji University (KLE-TJGE-B2206)”.

Funding

This work was supported by Shanghai “Science and Technology Innovation Action Plan” Outstanding Academic/Technical Leaders Program (Project No. 23XD1431200), Shanghai “Science and Technology Innovation Action Plan” Social Development Science and Technology Research Project (Project No. 21DZ1201100), and Key Laboratory of Geotechnical and Underground Engineering of Ministry of Education, Tongji University (KLE-TJGE-B2206)”.

Author information

Authors and Affiliations

1. College of Environmental Science and Engineering, Donghua University, Shanghai, 201620, China
   Peinan Li & Qingyan Tan
2. Department of Geotechnical Engineering, College of Civil Engineering, Tongji University, Shanghai, 200092, China
   Jingxiao Wang
3. Beijing Research Institute of Uranium Geology, CNNC, Beijing, 100029, China
   Yong Ye
4. Shanghai Tunnel Engineering Co., Ltd, Shanghai, 200032, China
   Jie Fan & Yan Qiu

Authors

1. Peinan Li
2. Qingyan Tan
3. Jingxiao Wang
4. Yong Ye
5. Jie Fan
6. Yan Qiu

Contributions

P.L.: Conceptualization, Methodology, Investigation, Data curation, Formal analysis. Q.T.: Conceptualization, Methodology, Data curation, Formal analysis, Visualization, Validation, Writing– original draft. J. W.: Visualization, Writing– review & editing. Y.Y.: Funding acquisition, Writing– review & editing. J.F.: Writing– review & editing. Y.Q.: Funding acquisition, Writing– review & editing.

Corresponding author

Correspondence toPeinan Li.

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The authors declare no competing interests.

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Communicated by Hassan Babaie

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Li, P., Tan, Q., Wang, J. et al. Multi-source data integration modeling and spatial analysis for optimal design of high-level radioactive waste geological repository.Earth Sci Inform 18, 469 (2025). https://doi.org/10.1007/s12145-025-01972-0

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• Received: 08 January 2025
• Accepted: 06 July 2025
• Published: 16 July 2025
• Version of record: 16 July 2025
• DOI: https://doi.org/10.1007/s12145-025-01972-0

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