In EDS ansehen

Automating the Seismic Design of Reinforced Concrete Rectangular Columns Employing Multi-Expression Programming: Towards the Automated Design of Reinforced Concrete Structures

Gespeichert in:
Bibliographische Detailangaben
Titel: Automating the Seismic Design of Reinforced Concrete Rectangular Columns Employing Multi-Expression Programming: Towards the Automated Design of Reinforced Concrete Structures
Autoren: Muhammad Faisal Javed, Raheel Asghar, Sardar Kashir Ur Rehman
Quelle: Advances in Mechatronics and Mechanical Engineering ISBN: 9798369321614
Verlagsinformationen: IGI Global, 2024.
Publikationsjahr: 2024
Beschreibung: This chapter explores an AI-powered approach for predicting the seismic capacity of RC rectangular columns using multi-expression programming (MEP). Leveraging a database of 250 RC column specimens tested under seismic loads from the Pacific Earthquake Engineering Research (PEER) Centre, two distinct MEP models were developed for flexural and shear capacity prediction. These models, trained with five key input variables using MEPX software, achieved high accuracy (R2 > 0.96) exceeding the performance of ACI 318-19 code provisions. Additionally, the models captured the underlying physical processes of seismic behavior in columns. These findings suggest the potential of MEP-based models for practical application in seismic design automation of RC structures.
Publikationsart: Part of book or chapter of book
DOI: 10.4018/979-8-3693-2161-4.ch009
Dokumentencode: edsair.doi...........7e7c0fa4b04e9549f1e1d5c7eecb2f1b
Datenbank: OpenAIRE
Beschreibung
Abstract:This chapter explores an AI-powered approach for predicting the seismic capacity of RC rectangular columns using multi-expression programming (MEP). Leveraging a database of 250 RC column specimens tested under seismic loads from the Pacific Earthquake Engineering Research (PEER) Centre, two distinct MEP models were developed for flexural and shear capacity prediction. These models, trained with five key input variables using MEPX software, achieved high accuracy (R2 > 0.96) exceeding the performance of ACI 318-19 code provisions. Additionally, the models captured the underlying physical processes of seismic behavior in columns. These findings suggest the potential of MEP-based models for practical application in seismic design automation of RC structures.
DOI:10.4018/979-8-3693-2161-4.ch009