02820nas a2200409 a 4500 20260817162000.0 260202s20259999th u ms t 000 eng d .b12473972 AIT Thesis no.ST-25-05 Zwe Yan Naing AI-driven predication of concrete beam size, design and capacity for gravity loads Pathum Thani, Thailand : Asian Institute of Technology, 2025 80 leaves : ill.+ 1 online resource Thesis ; no. ST-25-05 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 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. Structural design Data processing Sturctural Engineering Artificial intelligence Deep learning (Machine learning) Krishna, Chaitanya, Chairperson Anwar, Naveed, (Co-chairperson) Pennung Warnitchai, Examination Committee Punchet Thammarak, Examination Committee Panon Latcharote, Examination Committee AIT Fellowship, Scholarship Donor Asian Institute of Technology. Thesis ; no. ST-25-05 Full-Text http://203.159.5.9/ait-thesis/Viewer/viewer.php?id=B23406 .b12473972 mnarc a 260209 0 260204 m h a 0 mnarc 67 Barcode : - CREATED : 2026-02-02 RECORD # : i13570584 LPATRON : 0 LCHKIN : - # RENEWALS : 0 # OVERDUE : 0 IUSE3 : 0 TOT CHKOUT : 0 TOT RENEW : 0 3385 3385 0 0 0 0 MAIN MAIN mnarc 2026-08-17 0 AIT Thesis no.ST-25-05 2026-08-17 16:20:00 1 2026-08-17 67