ChatGPT可以实现岩土工程应用的有限元模型吗?

IF 3.6 2区 工程技术 Q2 ENGINEERING, GEOLOGICAL
Taegu Kim, Tae Sup Yun, Hyoung Suk Suh
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引用次数: 0

摘要

本研究评估ChatGPT从一组提示符生成岩土工程应用的有限元代码的能力。我们使用水力-机械耦合公式测试了三种不同的初始边值问题,包括流体质量在一维空间中的扩散对超孔隙水压力的耗散、条形基础的随时间微分沉降以及重力驱动的渗流。对于每种情况,初始提示都涉及向ChatGPT提供有限元实现所需的信息,例如平衡和本构方程、问题几何、初始和边界条件、材料特性以及时空离散化和求解策略。在ChatGPT生成的有限元代码通过验证/验证测试之前,任何错误和意外结果都将通过及时的增强过程进一步解决。我们的研究结果表明,ChatGPT在使用FEniCS有限元库时需要最少的代码修改,因为它的高级接口可以实现高效的编程。相比之下,ChatGPT生成的MATLAB代码需要大量的提示增强和/或直接的人为干预,因为它涉及有限元分析所需的大量低级编程,例如构造形状函数或组装全局矩阵。考虑到这项任务的快速工程需要对数学公式和数值技术的理解,本研究表明,虽然大型语言模型可能还不能取代人类程序员,但它可以极大地帮助实现数值模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Can ChatGPT Implement Finite Element Models for Geotechnical Engineering Applications?

Can ChatGPT Implement Finite Element Models for Geotechnical Engineering Applications?

This study assesses the capability of ChatGPT to generate finite element code for geotechnical engineering applications from a set of prompts. We tested three different initial boundary value problems using a hydro-mechanically coupled formulation for unsaturated soils, including the dissipation of excess pore water pressure through fluid mass diffusion in one-dimensional space, time-dependent differential settlement of a strip footing, and gravity-driven seepage. For each case, initial prompting involved providing ChatGPT with necessary information for finite element implementation, such as balance and constitutive equations, problem geometry, initial and boundary conditions, material properties, and spatiotemporal discretization and solution strategies. Any errors and unexpected results were further addressed through prompt augmentation processes until the ChatGPT-generated finite element code passed the verification/validation test. Our results demonstrate that ChatGPT required minimal code revisions when using the FEniCS finite element library, owing to its high-level interfaces that enable efficient programming. In contrast, the MATLAB code generated by ChatGPT necessitated extensive prompt augmentations and/or direct human intervention, as it involves a significant amount of low-level programming required for finite element analysis, such as constructing shape functions or assembling global matrices. Given that prompt engineering for this task requires an understanding of the mathematical formulation and numerical techniques, this study suggests that while a large language model may not yet replace human programmers, it can greatly assist in the implementation of numerical models.

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来源期刊
CiteScore
6.40
自引率
12.50%
发文量
160
审稿时长
9 months
期刊介绍: The journal welcomes manuscripts that substantially contribute to the understanding of the complex mechanical behaviour of geomaterials (soils, rocks, concrete, ice, snow, and powders), through innovative experimental techniques, and/or through the development of novel numerical or hybrid experimental/numerical modelling concepts in geomechanics. Topics of interest include instabilities and localization, interface and surface phenomena, fracture and failure, multi-physics and other time-dependent phenomena, micromechanics and multi-scale methods, and inverse analysis and stochastic methods. Papers related to energy and environmental issues are particularly welcome. The illustration of the proposed methods and techniques to engineering problems is encouraged. However, manuscripts dealing with applications of existing methods, or proposing incremental improvements to existing methods – in particular marginal extensions of existing analytical solutions or numerical methods – will not be considered for review.
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