{"title":"GeoLLM: A specialized large language model framework for intelligent geotechnical design","authors":"","doi":"10.1016/j.compgeo.2024.106849","DOIUrl":null,"url":null,"abstract":"<div><div>Large language models (LLMs) have achieved remarkable success in various industrial and research fields, enhancing work efficiency by assisting machines in comprehending human language. In geotechnical design where extensive repetitive cross-checking of design codes consumes considerable time and labour, the utilization of LLMs to enhance design procedures has not been explored before. The challenge is to ensure that LLMs accurately comprehend professional geotechnical information from text and execute mathematical calculations correctly. This study makes the first attempt at developing a specialized LLM framework, GeoLLM, integrated with an innovative prompt engineering strategy to extract professional information from text and enable accurate mathematical calculations. GeoLLM is applied to the design of single piles involving bearing capacity and settlement calculations. The results reveal that GeoLLM exhibits excellent performance in single pile cases. Additionally, compared with LLMs of varying architectures and sizes, commercial LLMs with over 100 billion parameters presented outstanding comprehensive capacities, while those with 1.8 ∼ 72 billion parameters degraded relatively. These findings indicate the promising capacity of GeoLLM to address professional tasks in geotechnical design.</div></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":null,"pages":null},"PeriodicalIF":5.3000,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers and Geotechnics","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0266352X24007882","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Large language models (LLMs) have achieved remarkable success in various industrial and research fields, enhancing work efficiency by assisting machines in comprehending human language. In geotechnical design where extensive repetitive cross-checking of design codes consumes considerable time and labour, the utilization of LLMs to enhance design procedures has not been explored before. The challenge is to ensure that LLMs accurately comprehend professional geotechnical information from text and execute mathematical calculations correctly. This study makes the first attempt at developing a specialized LLM framework, GeoLLM, integrated with an innovative prompt engineering strategy to extract professional information from text and enable accurate mathematical calculations. GeoLLM is applied to the design of single piles involving bearing capacity and settlement calculations. The results reveal that GeoLLM exhibits excellent performance in single pile cases. Additionally, compared with LLMs of varying architectures and sizes, commercial LLMs with over 100 billion parameters presented outstanding comprehensive capacities, while those with 1.8 ∼ 72 billion parameters degraded relatively. These findings indicate the promising capacity of GeoLLM to address professional tasks in geotechnical design.
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.