Artificial intelligence transformations in geotechnics: progress, challenges and future enablers

IF 6.2 1区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers and Geotechnics Pub Date : 2025-09-08 DOI:10.1016/j.compgeo.2025.107604

Brian Sheil , Christos Anagnostopoulos , Róisín Buckley , Matteo Oryem Ciantia , Eky Febrianto , Jinlong Fu , Zhiwei Gao , Xueyu Geng , Bin Gong , Kevin Hanley , Pengpeng He , Kostas Kolomvatsos , Bruna de C.F.L. Lopes , Jelena Ninic , Marco Previtali , Mohammad Rezania , Agustin Ruiz-Lopez , Jin Sun , Stephen Suryasentana , David Taborda , Pin Zhang

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引用次数: 0

Abstract

Our reliance on the underground space to deliver critical civil engineering infrastructure is growing: to accommodate utility and transport infrastructure in urban environments, to provide innovative housing and commercial solutions, and to support proliferating renewable energy infrastructure, particularly offshore. Artificial intelligence (AI) is arguably the most promising enabler to transform geotechnical engineering by extracting knowledge from data to achieve step-change increases in efficiency, sustainability, reliability and safety. This paper seeks to develop a shared understanding of the state of the art of AI in geotechnics and to explore future developments. By way of example, specific popular use cases in geotechnics are considered to highlight current progress in AI applications including intelligent site investigation, predictive modelling for soil behaviour, and optimisation of design and construction processes. The paper then addresses key research challenges, such as data scarcity and interpretability, and discusses the opportunities that lie ahead in the integration of AI with geotechnical engineering. Finally, priority technological enablers are identified for future transformations.

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岩土工程中的人工智能转型：进展、挑战和未来推动者

我们越来越依赖地下空间来提供关键的土木工程基础设施：在城市环境中容纳公用事业和交通基础设施，提供创新的住房和商业解决方案，并支持不断增加的可再生能源基础设施，特别是海上基础设施。人工智能（AI）可以说是最有前途的推动者，它可以从数据中提取知识，从而实现效率、可持续性、可靠性和安全性的逐步提高。本文旨在对人工智能在岩土工程领域的发展现状达成共识，并探讨其未来的发展。举例来说，岩土工程中特定的流行用例被认为突出了人工智能应用的当前进展，包括智能现场调查，土壤行为的预测建模，以及设计和施工过程的优化。然后，本文解决了关键的研究挑战，如数据稀缺性和可解释性，并讨论了人工智能与岩土工程集成的未来机遇。最后，确定未来转换的优先技术使能因素。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Computers and Geotechnics 地学-地球科学综合

CiteScore

9.10

自引率

15.10%

发文量

438

审稿时长

45 days

期刊介绍： The use of computers is firmly established in geotechnical engineering and continues to grow rapidly in both engineering practice and academe. The development of advanced numerical techniques and constitutive modeling, in conjunction with rapid developments in computer hardware, enables problems to be tackled that were unthinkable even a few years ago. Computers and Geotechnics provides an up-to-date reference for engineers and researchers engaged in computer aided analysis and research in geotechnical engineering. The journal is intended for an expeditious dissemination of advanced computer applications across a broad range of geotechnical topics. Contributions on advances in numerical algorithms, computer implementation of new constitutive models and probabilistic methods are especially encouraged.