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DC Field | Value | Language |
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dc.contributor.author | Panandikar, N. | |
dc.contributor.author | Narayan, K.S.B. | |
dc.date.accessioned | 2020-03-30T09:45:56Z | - |
dc.date.available | 2020-03-30T09:45:56Z | - |
dc.date.issued | 2014 | |
dc.identifier.citation | Vulnerability, Uncertainty, and Risk: Quantification, Mitigation, and Management - Proceedings of the 2nd International Conference on Vulnerability and Risk Analysis and Management, ICVRAM 2014 and the 6th International Symposium on Uncertainty Modeling and Analysis, ISUMA 2014, 2014, Vol., , pp.1311-1320 | en_US |
dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/6648 | - |
dc.description.abstract | The pushover analysis is a nonlinear static procedure wherein monotonically increasing loads are applied to the structure. It is a popular tool for seismic performance evaluation of existing, as well as new, structures. In the literature a lot of research work has been carried out on conventional pushover analysis and, after knowing deficiencies, efforts have been made to improve it. However, actual experimental test results to verify the analytically obtained pushover results are rarely available. Also, the procedure involves certain approximations that some amount of variation is always expected to exist in seismic demand prediction of pushover analysis. In this paper, an ttempt is being made to assess the uncertainty of pushover analysis results to modeling methods and results compared with experimentally obtained results based on tests carried out on a G+2 storied RCC framed structure. Stochastic analysis is carried out by considering uncertain parameters as the strength of concrete, strength of steel, cover to the reinforcement, hinge location and hinge length which are randomly generated and incorporated into the analysis. The hinge lengths are found using various hinge length formulations available in literature. The results are then compared with experimental observations. � 2014 American Society of Civil Engineers. | en_US |
dc.title | Stochastic Analysis to Assess Uncertainty in Pushover Analysis to Modeling Methods | en_US |
dc.type | Book chapter | en_US |
Appears in Collections: | 2. Conference Papers |
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