Automating structural reliability analysis with a multi-agent large language model framework

2026-07-17

AI Summary

Structural reliability analysis heavily relies on specialized expertise, which limits its broader engineering application. This work proposes a multi-agent large language model framework that, for the first time, integrates a fine-tuned Method Planner with a multi-agent architecture to automate the entire component-level reliability analysis pipeline—from natural language problem descriptions through modeling, method planning, code generation, execution, and result interpretation—while incorporating human verification at critical decision points. By delegating computations to validated deterministic solvers rather than relying on the LLM to generate numerical results directly, the system significantly enhances reproducibility and mitigates hallucination. Experimental results demonstrate that the proposed approach lowers the expertise barrier while preserving the accuracy and trustworthiness of the computational outcomes.

Abstract

Structural reliability analysis supports the design and safety assessment of buildings and civil infrastructure but requires specialized expertise throughout the workflow. This study presents a multi-agent large language model framework that automates component-level reliability analysis from a natural-language problem statement to interpreted estimates of the reliability index and failure probability. Specialized agents handle problem formulation, method planning, code generation, execution, and result interpretation, with human confirmation at key decision points. The Method Planner is fine-tuned using QLoRA for a priori reliability-method category selection. Analysis results are not generated directly by an LLM; instead, validated deterministic solvers compute the reliability estimates, improving reproducibility and reducing hallucination risk. The framework uses open-weight models and supports local execution without closed APIs. Results show that it lowers the expertise barrier to structural reliability assessment while preserving computational trustworthiness.

Problem

• structural reliability analysis
• expertise barrier
• automation
• reliability assessment
• civil infrastructure

Innovation

• multi-agent LLM
• structural reliability analysis
• QLoRA fine-tuning
• deterministic solvers
• automated engineering workflow