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Performing Structural Analysis and Design of 3D Space Frame in STAAD.Pro Using LLM’s: A Practical Framework for Automated Structural Engineering Workflows


Authors : Syed Munawar Ali

Volume/Issue : Volume 11 - 2026, Issue 10 - October


DOI : https://doi.org/10.38124/ijisrt/26Oct831

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.


Abstract : Generative artificial intelligence has moved quickly into text and software work, but its place in everyday structural engineering is still poorly defined. This paper sets out a practical framework in which a large language model (LLM), Claude, takes a steel structure from natural-language prompts and existing calculation documents to a complete STAAD.

Keywords : Large Language Models; Claude AI; Structural Engineering; STAAD.Pro; Artificial Intelligence; Structural Analysis; Steel Design; Foundation Design; Engineering Automation.

References :

  1. R. Sacks, C. Eastman, G. Lee, and P. Teicholz, BIM Handbook: A Guide to Building Information Modeling for Owners, Designers, Engineers, Contractors, and Facility Managers, 3rd ed. Hoboken, NJ, USA: Wiley, 2018.
  2. Y. Pan and L. Zhang, “Roles of artificial intelligence in construction engineering and management: A critical review and future trends,” Automation in Construction, vol. 122, Art. no. 103517, 2021.
  3. H. Adeli, “Neural networks in civil engineering: 1989–2000,” Computer-Aided Civil and Infrastructure Engineering, vol. 16, no. 2, pp. 126–142, 2001.
  4. H. Salehi and R. Burgueño, “Emerging artificial intelligence methods in structural engineering,” Engineering Structures, vol. 171, pp. 170–189, 2018.
  5. H.-T. Thai, “Machine learning for structural engineering: A state-of-the-art review,” Structures, vol. 38, pp. 448–491, 2022.
  6. C. V. Camp and B. J. Bichon, “Design of space trusses using ant colony optimization,” Journal of Structural Engineering, vol. 130, no. 5, pp. 741–751, 2004.
  7. A. Kaveh, Applications of Metaheuristic Optimization Algorithms in Civil Engineering. Cham, Switzerland: Springer, 2017.
  8. A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin, “Attention is all you need,” in Advances in Neural Information Processing Systems, vol. 30, 2017, pp. 5998–6008.
  9. T. B. Brown et al., “Language models are few-shot learners,” in Advances in Neural Information Processing Systems, vol. 33, 2020, pp. 1877–1901.
  10. S. Noy and W. Zhang, “Experimental evidence on the productivity effects of generative artificial intelligence,” Science, vol. 381, no. 6654, pp. 187–192, 2023.
  11. H. Liang, M. Talebi Kalaleh, and Q. Mei, “Integrating large language models for automated structural analysis,” arXiv:2504.09754, 2025.
  12. J. Liu, Z. Geng, R. Cao, L. Cheng, P. Bocchini, and M. Cheng, “A large language model-empowered agent for reliable and robust structural analysis,” arXiv:2507.02938, 2025.
  13. H. Sun, H. V. Burton, and H. Huang, “Machine learning applications for building structural design and performance assessment: State-of-the-art review,” Journal of Building Engineering, vol. 33, Art. no. 101816, 2021.
  14. J. Zheng and M. Fischer, “BIM-GPT: A prompt-based virtual assistant framework for BIM information retrieval,” arXiv:2304.09333, 2023.
  15. R. Parasuraman and D. H. Manzey, “Complacency and bias in human use of automation: An attentional integration,” Human Factors, vol. 52, no. 3, pp. 381–410, 2010.
  16. American Society of Civil Engineers, Minimum Design Loads for Buildings and Other Structures, ASCE/SEI 7-10. Reston, VA, USA: ASCE, 2010.
  17. American Institute of Steel Construction, Specification for Structural Steel Buildings, ANSI/AISC 360-16. Chicago, IL, USA: AISC, 2016.
  18. ACI Committee 318, Building Code Requirements for Structural Concrete (ACI 318-14) and Commentary (ACI 318R-14). Farmington Hills, MI, USA: American Concrete Institute, 2014.
  19. J. M. Fisher and L. A. Kloiber, Base Plate and Anchor Rod Design, AISC Design Guide 1, 2nd ed. Chicago, IL, USA: American Institute of Steel Construction, 2006.
  20. C. Boje, A. Guerriero, S. Kubicki, and Y. Rezgui, “Towards a semantic construction digital twin: Directions for future research,” Automation in Construction, vol. 114, Art. no. 103179, 2020.

Generative artificial intelligence has moved quickly into text and software work, but its place in everyday structural engineering is still poorly defined. This paper sets out a practical framework in which a large language model (LLM), Claude, takes a steel structure from natural-language prompts and existing calculation documents to a complete STAAD.

Keywords : Large Language Models; Claude AI; Structural Engineering; STAAD.Pro; Artificial Intelligence; Structural Analysis; Steel Design; Foundation Design; Engineering Automation.

Paper Submission Last Date
31 - October - 2026

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