Technical Papers
Feb 22, 2021

State Estimation for Prediction of Fatigue Life for a Rollercoaster Connection Subjected to Operational Multiaxial Nonproportional Loading

Publication: Journal of Structural Engineering
Volume 147, Issue 5

Abstract

Recent research on structural health monitoring has shown the applicability of Kalman filtering for fusion of models and data of dynamic systems. In this study, the augmented Kalman filter (AKF) is combined with a substructuring approach for the estimation of strain time histories at unmeasured locations of a rollercoaster connection, with the purpose of predicting remaining fatigue life. The AKF allows for response estimation in the absence of direct measurements of operational loads and in the presence of noisy measurements at limited locations of the instrumented system. The proposed research implements for the first time the AKF and a substructure with exclusively in-service strain measurements from a full-scale structure. Given that uniaxial fatigue life assessment methods often prove insufficient for large in-service structures with complex geometry and subjected to multiaxial nonproportional loadings, the critical plane method is here employed for estimation of fatigue life. The applicability of a substructuring approach combined with strain estimates from the AKF is demonstrated and evaluated with operational strain measurements obtained from an in-service rollercoaster support structure. It is shown that the proposed methodology and fine-tuning of the AKF parameters result in a close match of predicted and measured strains.

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Data Availability Statement

Strain, acceleration, and optical sensor data collected from the rollercoaster support bracket and used during this research are available from the corresponding author by request.

Acknowledgments

The writers are grateful for the funding of this research by NSF Division of Industrial Innovation & Partnership (IIP) Grant No. IIP-1640693. PFI: AIR-TT: Real-Time Fatigue Life Prediction for Decision-making and Asset Management. Additional funding was provided by the ThinkSwiss Research Scholarship Program by the Embassy of Switzerland in the United States of America, Office of Science, Technology, and Higher Education (OSTHE). Any opinions, findings, and conclusions or recommendations expressed in this research paper are those of the authors and do not necessarily reflect the views of the National Science Foundation or the Embassy of Switzerland in the United States of America.

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Go to Journal of Structural Engineering
Journal of Structural Engineering
Volume 147Issue 5May 2021

History

Received: Sep 19, 2019
Accepted: Nov 16, 2020
Published online: Feb 22, 2021
Published in print: May 1, 2021
Discussion open until: Jul 22, 2021

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Authors

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Sofia Puerto Tchemodanova [email protected]
P.E.
Doctoral Candidate, Dept. of Civil and Environmental Engineering, Tufts Univ., Medford, MA 02155. Email: [email protected]
Konstantinos Tatsis [email protected]
Doctoral Candidate, Dept. of Civil, Environmental and Geomatic Engineering, ETH Zurich, Zurich 8092, Switzerland. Email: [email protected]
Professor, Dept. of Civil and Environmental Engineering, Tufts Univ., Medford, MA 02155 (corresponding author). ORCID: https://orcid.org/0000-0002-7033-4562. Email: [email protected]
Eleni Chatzi, Ph.D. [email protected]
Associate Professor, Dept. of Civil, Environmental and Geomatic Engineering, ETH Zurich, Zurich 8092, Switzerland. Email: [email protected]
Vasilis Dertimanis, Ph.D. [email protected]
Research Scientist, Dept. of Civil, Environmental and Geomatic Engineering, ETH Zurich, Zurich 8092, Switzerland. Email: [email protected]

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