TY  - SER
AU  - Zwe Yan Naing
AU  - Krishna,Chaitanya
AU  - Anwar,Naveed
AU  - Pennung Warnitchai,
AU  - Punchet Thammarak,
AU  - Panon Latcharote,
ED  - AIT Fellowship,
TI  - AI-driven predication of concrete beam size, design and capacity for gravity loads
T2  - Thesis
PY  - 2025///
CY  - Pathum Thani, Thailand
PB  - Asian Institute of Technology
KW  - Structural design
KW  - Data processing
KW  - Sturctural Engineering
KW  - Artificial intelligence
KW  - Deep learning (Machine learning)
N1  - A thesis submitted in partial fulfillment of the requirements for the  degree of Master of Engineering in Structural Engineering; Thesis (M. Eng.) - Asian Institute of Technology, 2025
N2  - Artificial Intelligence (AI) has emerged as a transformative technology, driving innovation across numerous industries through its ability to process information and data, learn patterns, and make predictions.This research addresses the need for efficiency and innovation in  structural engineering, where traditional design methods involving iterative calculations can be  time-consuming and complex. The study develops an AI-driven framework, utilizing Artificial  Neural Networks (ANNs), to predict cross-section size, rebar area, and loading capacity for  continuous rectangular shaped reinforced concrete beam. The ultimate goal is to deploy these  models as a cloud-based web application, integrating Large Language Models (LLMs) to  enhance accessibility and interaction for civil and structural engineers, as well as students. This  application will provide a practical, code-compliant tool for efficient structural design,streamlining the traditional process especially in preliminary design stage and offering an  intuitive, automated solution in innovative structural design workflow.
UR  - http://203.159.5.9/ait-thesis/Viewer/viewer.php?id=B23406
ER  -