Please use this identifier to cite or link to this item:
https://idr.l4.nitk.ac.in/jspui/handle/123456789/15860Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Ramkrishnan R. | |
| dc.contributor.author | Sreevalsa K. | |
| dc.contributor.author | Sitharam T.G. | |
| dc.date.accessioned | 2021-05-05T10:28:17Z | - |
| dc.date.available | 2021-05-05T10:28:17Z | - |
| dc.date.issued | 2020 | |
| dc.identifier.citation | Journal of Earthquake Engineering Vol. , , p. - | en_US |
| dc.identifier.uri | https://doi.org/10.1080/13632469.2020.1778586 | |
| dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/15860 | - |
| dc.description.abstract | Existing Ground Motion Prediction Equations (GMPE) in practice for North East India have been developed using limited or simulated datasets of recorded ground motions. The current study presents the development of a new GMPE based on a well-established model considering actual recorded ground motion data comprising of acceleration, magnitude, and hypocentral distances. A larger dataset with magnitudes ranging from 4.2 to 6.9 and up to 640 kms, with a total of 204 recordings is used in non-linear multiple-regression. The newly developed GMPE could predict ground acceleration realistically over larger ranges of distance and magnitudes, compared to existing GMPEs. © 2020, © 2020 Taylor & Francis Group, LLC. | en_US |
| dc.title | Strong Motion Data Based Regional Ground Motion Prediction Equations for North East India Based on Non-Linear Regression Models | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | 1. Journal Articles | |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.