Special issue on Data science for geotechnics

Introduction:

Geotechnical engineering is characterised by numerous uncertainties, which bring significant challenges into the planning, design and construction of geotechnical structures. Rapid advances in sensing technologies provide unprecedented opportunities to reduce uncertainties and transform traditional geotechnical engineering. However, the technologies for geotechnical data sensing, mining and integration in engineering practice require further development. The purpose of this special issue is to communicate the latest theories, methods and applications that consider how geotechnical data can be acquired and analysed, and how it can be used to improve geotechnical practice.

Topics covered:

Subject areas include, but are not limited to:

• Data-driven analysis methods
• Data-based geohazards assessment (individual andregional)
• Geological uncertainty
• Geotechnical bigdata base
• Geotechnical designs considering data uncertainty
• Geotechnical reliability analysis
• Impact of geotechnical data on uncertainty reduction
• Innovative geotechnical sensing technologies
• Machine learning feature selection
• Methods for analysing geotechnical data
• Probabilistic characterisation
• Statistical approach
• Value of information analysis of geotechnical data

Important deadlines:

• Submissions close: 30 November 2022
• Decision on all papers: 28 February 2023

Submission instructions:

Please read the Guide for Authors before submitting. All articles should be submitted online; please select SI: Data-science-geotech on submission. All submissions will undergo a normal peer-review process. If the manuscript is accepted, the article will be published open access with no fee payable by the author.

Guest Editors:

• Limin Zhang, Hong Kong University of Science & Technology, Hong Kong, China. Email: cezhangl@ust.hk 
• Lulu Zhang, Shanghai Jiaotong University, China. Email:lulu_zhang@sjtu.edu.cn 
• Jie Zhang, Tongji University, China. Email: cezhangjie@tongji.edu.cn