Open AccessDesign Optimization of Reinforced Concrete Beams by Genetically Optimized Neural Network Technique
Author(s) -
Eshanya Tongper gsiej,
Karthiga Shenbagam Natarajan,
S. Murugesan
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/955/1/012021
Subject(s) - serviceability (structure) , structural engineering , limit state design , reinforced concrete , optimal design , artificial neural network , computer science , engineering , artificial intelligence , machine learning
An approach to find the accurate optimal solution for structural elements such as beams, columns, footings etc. has been studied by huge researches in the current situation. As an addition in this research paper optimal design of two different types of reinforced concrete beams with different loading conditions one with concentrated load and another with UDL has been considered in addition to its self-weight, live load, equilibrium and serviceability constraints. Manual design of beams has been done in order to verify with the optimization technique limit state approach with accordance to the Indian standard codal provisions, classical and non-traditional optimization technique are done and the results are tabulated.