The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Predicting and Monitoring the Failure of Steel Structures Using Artificial Neural Networks
|
|
Author(s): Ratna Sunil Buradagunta (Prince Mohammad bin Fahd University, Saudi Arabia), P. Sundara Kumar (Vignan's Foundation for Science, Technology, and Research, India), K. Kamala Devi (Bapatla Engineering College, India)and I. M. R. Fattah (University of Technology Sydney, Australia)
Copyright: 2025
Pages: 16
Source title:
Expert Artificial Neural Network Applications for Science and Engineering
Source Author(s)/Editor(s): Lingala Syam Sundar (Prince Mohamamd Bin Fahd University, Saudia Arabia), Deepanraj Balakrishnan (Prince Mohammad Bin Fahd University, Saudi Arabia)and Antonio C.M. Sousa (University of Aveiro, Portugal)
DOI: 10.4018/979-8-3693-7250-0.ch016
Purchase
|
Abstract
Artificial neural networks (ANN) have emerged as powerful tool to compute, assess, predict and understand the structural system behavior subjected to combination of complex input variables such as mechanical loads, extreme environmental conditions, seismic conditions etc. The existing experimental and simulation methods may not completely predict the structure response under combination of different input variables. In this context, assessing the failure of the steel structures by using ANN techniques ease the efforts of engineers in structure health monitoring. Compared with the available traditional methods, using ANN enables to assess the failure of the structures with more accuracy and reliability. The present chapter provides a summary of using ANNs in predicting different failures usually observed in steel structures. Additionally, the challenges and future perspectives are also discussed.
Related Content
|
Dankan Gowda V., Anjali Sandeep Gaikwad, Pilli Lalitha Kumari, Erdal Buyukbicakci, Sengul Ibrahimoglu.
© 2025.
32 pages.
|
|
Debasish Banerjee, Ranjit Barua, Sudipto Datta, Dileep Pathote.
© 2025.
18 pages.
|
|
Kok Yeow You, Man Seng Sim.
© 2025.
96 pages.
|
|
Man Seng Sim, Kok Yeow You, Fahmiruddin Esa, Raimi Dewan, DiviyaDevi Paramasivam, Rozeha A. Rashid.
© 2025.
38 pages.
|
|
Mandeep Kaur.
© 2025.
24 pages.
|
|
Ganesh Khekare, Priya Dasarwar, Ajay Kumar Phulre, Urvashi Khekare, Gaurav Kumar Ameta, Shashi Kant Gupta.
© 2025.
22 pages.
|
|
Manoj Kumar Elipey, P. S. Kishore, Ratna Sunil Buradagunta.
© 2025.
14 pages.
|
|
|