mlsanityData to 7 Oct 2026

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

arXiv 2607.16580 ↗First posted 18 Jul 2026stat.AP cs.CE cs.SEcited by 0

On the map: LLM agents and tool use → Multimodal and embodied agents

Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Multimodal and embodied agents, one of 16 directions in LLM agents and tool use. Builds on 14 of its 45 references that are in the map. First posted on arXiv 18 Jul 2026.

Builds on

14 of 45 references.

Closest ancestors · 6

Same direction, newest first

  1. 2026Agentic Large Language Models for Automated Structural Analysis of 3D Frame Systems2 Jun
  2. 2026A Novel Multi-Agent Architecture to Reduce Hallucinations of Large Language Models in Multi-Step Structural Modeling8 Mar
  3. 2025Automating Structural Engineering Workflows with Large Language Model Agents13 Oct
  4. 2025A Lightweight Large Language Model-Based Multi-Agent System for 2D Frame Structural Analysis6 Oct
  5. 2025Large Language Model Agent for Structural Drawing Generation Using ReAct Prompt Engineering and Retrieval Augmented Generation26 Jul
  6. 2025A Large Language Model-Empowered Agent for Reliable and Robust Structural Analysis27 Jun

Other references · 8

  1. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,084
  2. 2023QLoRA: Efficient Finetuning of Quantized LLMscited by 3,355
  3. 2021A Survey of Human-in-the-loop for Machine Learningcited by 214
  4. 2025Fine-tuning a Large Language Model for Automating Computational Fluid Dynamics Simulationscited by 18
  5. 2025Integrating Large Language Models for Automated Structural Analysiscited by 12
  6. 2025Can ChatGPT implement finite element models for geotechnical engineering applications?cited by 5
  7. 2021Rare event estimation using stochastic spectral embeddingcited by 2
  8. 2025Fine-Tuning Large Language Models and Evaluating Retrieval Methods for Improved Question Answering on Building Codescited by 2

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  2. 2024Collaboration Dynamics and Reliability Challenges of Multi-Agent LLM Systems in Finite Element Analysis
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  4. 2025Automatic Building Code Review: A Case Study
  5. 2026A Multi-AI-agent Framework Enabling End-to-end Finite Element Analysis for Solid Mechanics Problems
  6. 2026Verication-driven closed-loop multi-agent large language modelframework for code-compliant structural design
  7. 2025A Multidisciplinary Design and Optimization (MDO) Agent Driven by Large Language Models
  8. 2026Rethinking Scientific Modeling: Toward Physically Consistent and Simulation-Executable Programmatic Generation