AI-driven predication of concrete beam size, design and capacity for gravity loads (Record no. 3385)

MARC details
000 -LEADER
fixed length control field 02820nas a2200409 a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20260817162000.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 260202s20259999th u ms t 000 eng d
035 ## - SYSTEM CONTROL NUMBER
System control number .b12473972
099 #9 - LOCAL FREE-TEXT CALL NUMBER (OCLC)
Classification number AIT Thesis no.ST-25-05
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Zwe Yan Naing
245 10 - TITLE STATEMENT
Title AI-driven predication of concrete beam size, design and capacity for gravity loads
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Pathum Thani, Thailand :
Name of publisher, distributor, etc. Asian Institute of Technology,
Date of publication, distribution, etc. 2025
300 ## - PHYSICAL DESCRIPTION
Extent 80 leaves :
Other physical details ill.+
Accompanying material 1 online resource
490 1# - SERIES STATEMENT
Series statement Thesis ;
Volume/sequential designation no. ST-25-05
500 ## - GENERAL NOTE
General note A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Structural Engineering
502 ## - DISSERTATION NOTE
Dissertation note Thesis (M. Eng.) - Asian Institute of Technology, 2025
520 ## - SUMMARY, ETC.
Summary, etc. 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.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Structural design
General subdivision Data processing
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Sturctural Engineering
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Artificial intelligence
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Deep learning (Machine learning)
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Krishna, Chaitanya,
Relator term Chairperson
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Anwar, Naveed,
Relator term (Co-chairperson)
700 0# - ADDED ENTRY--PERSONAL NAME
Personal name Pennung Warnitchai,
Relator term Examination Committee
700 0# - ADDED ENTRY--PERSONAL NAME
Personal name Punchet Thammarak,
Relator term Examination Committee
700 0# - ADDED ENTRY--PERSONAL NAME
Personal name Panon Latcharote,
Relator term Examination Committee
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element AIT Fellowship,
Relator term Scholarship Donor
810 2# - SERIES ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element Asian Institute of Technology.
Title of a work Thesis ;
Volume/sequential designation no. ST-25-05
856 40 - ELECTRONIC LOCATION AND ACCESS
Materials specified Full-Text
Uniform Resource Identifier <a href="http://203.159.5.9/ait-thesis/Viewer/viewer.php?id=B23406">http://203.159.5.9/ait-thesis/Viewer/viewer.php?id=B23406</a>
907 ## - LOCAL DATA ELEMENT G, LDG (RLIN)
a .b12473972
b mnarc
c a
902 ## - LOCAL DATA ELEMENT B, LDB (RLIN)
a 260209
998 ## - LOCAL CONTROL INFORMATION (RLIN)
Operator's initials, OID (RLIN) 0
Cataloger's initials, CIN (RLIN) 260204
First date, FD (RLIN) m
-- h
-- a
-- 0
945 ## - LOCAL PROCESSING INFORMATION (OCLC)
l mnarc
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type 67-Electronic Resource
909 ## - LOCAL ITEMS USED
Barcode Barcode : -
CREATED CREATED : 2026-02-02
RECORD Id RECORD # : i13570584
LPATRON LPATRON : 0
LCHKIN LCHKIN : -
RENEWALS # RENEWALS : 0
-- # OVERDUE : 0
-- IUSE3 : 0
-- TOT CHKOUT : 0
-- TOT RENEW : 0
Holdings
Withdrawn status Lost status Damaged status Not for loan Home library Current library Shelving location Date acquired Total checkouts Full call number Date last seen Copy number Price effective from Koha item type
      Available for Loans Asian Institute of Technology Library Asian Institute of Technology Library Archives 17/08/2026   AIT Thesis no.ST-25-05 17/08/2026 1 17/08/2026 67-Electronic Resource
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