14 citations · 14 across the 7 of their papers we have counts for
8 papers
Agentic Large Language Models for Automated Structural Analysis of 3D Frame Systems
Ziheng Geng, Ian Franklin, Santiago Martinez +3
Large language models (LLMs) have emerged as powerful foundation models with strong reasoning capabilities across domains. Beyond reactive text generation, agentic LLMs enable auto…
Automating Structural Analysis Across Multiple Software Platforms Using Large Language Models
Ziheng Geng, Jiachen Liu, Ian Franklin +3
Recent advances in large language models (LLMs) have shown the promise to significantly accelerate the workflow by automating structural modeling and analysis. However, existing st…
A Novel Multi-Agent Architecture to Reduce Hallucinations of Large Language Models in Multi-Step Structural Modeling
Ziheng Geng, Jiachen Liu, Ran Cao +3
Large language models (LLMs) such as GPT and Gemini have demonstrated remarkable capabilities in contextual understanding and reasoning. The strong performance of LLMs has sparked…
InsurAgent: A Large Language Model-Empowered Agent for Simulating Individual Behavior in Purchasing Flood Insurance
Ziheng Geng, Jiachen Liu, Ran Cao +3
Flood insurance is an effective strategy for individuals to mitigate disaster-related losses. However, participation rates among at-risk populations in the United States remain str…
A Lightweight Large Language Model-Based Multi-Agent System for 2D Frame Structural Analysis
Ziheng Geng, Jiachen Liu, Ran Cao +3
Large language models (LLMs) have recently been used to empower autonomous agents in engineering, significantly improving automation and efficiency in labor-intensive workflows. Ho…
SoM-1K: A Thousand-Problem Benchmark Dataset for Strength of Materials
Qixin Wan, Zilong Wang, Jingwen Zhou +5
Foundation models have shown remarkable capabilities in various domains, but their performance on complex, multimodal engineering problems remains largely unexplored. We introduce…
A Large Language Model-Empowered Agent for Reliable and Robust Structural Analysis
Jiachen Liu, Ziheng Geng, Ran Cao +3
Large language models (LLMs) have exhibited remarkable capabilities across diverse open-domain tasks, yet their application in specialized domains such as civil engineering remains…
A Kriging-Random Forest Hybrid Model for Real-time Ground Property Prediction during Earth Pressure Balance Shield Tunneling
Ziheng Geng, Chao Zhang, Yuhao Ren +3
A kriging-random forest hybrid model is developed for real-time ground property prediction ahead of the earth pressure balanced shield by integrating Kriging extrapolation and rand…