Prediction of normalized modulus reduction curve based on limited measurement data
Prediction of normalized modulus reduction curve based on limited measurement data
The precision and reliability of the normalized modulus reduction curve in laboratory tests can be significantly compromised by the scarcity of specimens as well as variations among them, which can further impact the accuracy of seismic response analysis. In this paper, a Bayesian updating framework is proposed to predict the normalized modulus reduction curve with limited measurement data. Different prior distributions and measurement errors are investigated. Results show that the proposed technique is effective and efficient in handling limited data, reducing the uncertainty of variables through measurements, and improving the accuracy of the normalized modulus reduction curve with the acquisition of more measurements.
578–586
Zhang, Yuting
821b7687-fe98-4525-b641-2ea503797319
Huang, Bin
dbc73278-0b9b-4142-b816-4a8ca4d527cd
Fu, Xudong
e7127978-da7a-4ea0-9ddb-55d243917ac0
Zou, Di
44b46143-b364-4489-8864-00a654b878ef
Zhang, Yuting
821b7687-fe98-4525-b641-2ea503797319
Huang, Bin
dbc73278-0b9b-4142-b816-4a8ca4d527cd
Fu, Xudong
e7127978-da7a-4ea0-9ddb-55d243917ac0
Zou, Di
44b46143-b364-4489-8864-00a654b878ef
Zhang, Yuting, Huang, Bin, Fu, Xudong and Zou, Di
(2024)
Prediction of normalized modulus reduction curve based on limited measurement data.
In,
Ha-Minh, Cuong, Hung Pham, Cao, Vu, Hanh T.H. and Huynh, Dat Vu Khoa
(eds.)
Proceedings of the 7th International Conference on Geotechnics, Civil Engineering and Structures, CIGOS 2024, 4-5 April, Ho Chi Minh City, Vietnam.
Springer, .
(doi:10.1007/978-981-97-1972-3_64).
Record type:
Book Section
Abstract
The precision and reliability of the normalized modulus reduction curve in laboratory tests can be significantly compromised by the scarcity of specimens as well as variations among them, which can further impact the accuracy of seismic response analysis. In this paper, a Bayesian updating framework is proposed to predict the normalized modulus reduction curve with limited measurement data. Different prior distributions and measurement errors are investigated. Results show that the proposed technique is effective and efficient in handling limited data, reducing the uncertainty of variables through measurements, and improving the accuracy of the normalized modulus reduction curve with the acquisition of more measurements.
Text
978-981-97-1972-3_64
- Version of Record
Restricted to Repository staff only
Request a copy
More information
e-pub ahead of print date: 1 June 2024
Identifiers
Local EPrints ID: 496233
URI: http://eprints.soton.ac.uk/id/eprint/496233
PURE UUID: 5dcf9175-8096-4c4a-9a63-b3f3fd3ed2f6
Catalogue record
Date deposited: 09 Dec 2024 17:45
Last modified: 10 Dec 2024 03:11
Export record
Altmetrics
Contributors
Author:
Yuting Zhang
Author:
Bin Huang
Author:
Xudong Fu
Author:
Di Zou
Editor:
Cuong Ha-Minh
Editor:
Cao Hung Pham
Editor:
Hanh T.H. Vu
Editor:
Dat Vu Khoa Huynh
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics