Zobrazeno 1 - 10
of 32
pro vyhledávání: '"Itoi, Tatsuya"'
Model updating of engineering systems inevitably involves handling both aleatory or inherent randomness and epistemic uncertainties or uncertainities arising from a lack of knowledge or information about the system. Addressing these uncertainties pos
Externí odkaz:
http://arxiv.org/abs/2410.03150
Publikováno v:
Computer Methods in Applied Mechanics and Engineering,Volume 429, 1 September 2024, 117148
A novel framework for Bayesian structural model updating is presented in this study. The proposed method utilizes the surrogate unimodal encoders of a multimodal variational autoencoder (VAE). The method facilitates an approximation of the likelihood
Externí odkaz:
http://arxiv.org/abs/2406.09051
We develop a site-specific ground-motion model (GMM) for crustal earthquakes in Japan that can directly model the probability distribution of ground motion acceleration time histories based on generative adversarial networks (GANs). The proposed mode
Externí odkaz:
http://arxiv.org/abs/2404.15640
Publikováno v:
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, Vol. 10, No. 4, pp. 04024072, 2024
This study presents a novel approach to quantifying uncertainties in Bayesian model updating, which is effective in sparse or single observations. Conventional uncertainty quantification metrics such as the Euclidean and Bhattacharyya distance-based
Externí odkaz:
http://arxiv.org/abs/2404.03871
Publikováno v:
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 10 (2024), 04024055
Bayesian model updating facilitates the calibration of analytical models based on observations and the quantification of uncertainties in model parameters such as stiffness and mass. This process significantly enhances damage assessment and response
Externí odkaz:
http://arxiv.org/abs/2401.17932
Publikováno v:
Structural Safety 108 (2024) 102442
This paper proposes a multitask learning framework for probabilistic model updating by jointly using strain and acceleration measurements. This framework can enhance the structural damage assessment and response prediction of existing steel frame str
Externí odkaz:
http://arxiv.org/abs/2401.17888
Publikováno v:
Japan Architectural Review; Jan2024, Vol. 7 Issue 1, p1-16, 16p
Publikováno v:
Japan Architectural Review; Jan2023, Vol. 6 Issue 1, p1-19, 19p
Publikováno v:
Proceedings of The Seventh Asian-Pacific Symposium on Structural Reliability and Its Applications (APSSRA2020).
会議名/ Conference Name : APSSRA2020
回次 / Conference Sequence : 7
開催期間 / Conference Date : October 4-7, 2020
開催会場 / Conference Venue : The University of Tokyo
開催地 / Conference Place : Tokyo
開催
回次 / Conference Sequence : 7
開催期間 / Conference Date : October 4-7, 2020
開催会場 / Conference Venue : The University of Tokyo
開催地 / Conference Place : Tokyo
開催
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=jairo_______::42c8a9424545fcdf3e0f3cee996ab00a
https://repository.dl.itc.u-tokyo.ac.jp/records/54688
https://repository.dl.itc.u-tokyo.ac.jp/records/54688
Autor:
Itoi, Tatsuya
Publikováno v:
Proceedings of The Seventh Asian-Pacific Symposium on Structural Reliability and Its Applications (APSSRA2020).
会議名/ Conference Name : APSSRA2020
回次 / Conference Sequence : 7
開催期間 / Conference Date : October 4-7, 2020
開催会場 / Conference Venue : The University of Tokyo
開催地 / Conference Place : Tokyo
開催
回次 / Conference Sequence : 7
開催期間 / Conference Date : October 4-7, 2020
開催会場 / Conference Venue : The University of Tokyo
開催地 / Conference Place : Tokyo
開催
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=jairo_______::d7d7dbe810668d3accc0810f31ee5749
https://repository.dl.itc.u-tokyo.ac.jp/records/54723
https://repository.dl.itc.u-tokyo.ac.jp/records/54723