Assembly Fault-Tolerant Interval Inversion Method for Cable-Stayed Bridge Based on Bilayer Surrogate Model
Lecture Notes in Civil Engineering, ISSN: 2366-2565, Vol: 302 LNCE, Page: 959-974
2023
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Conference Paper Description
Focusing on the assembly accuracy control problem of practical engineering and installation tolerance ability under uncertain interference, this paper presents an interval inversion method derived from reliability-based optimization design (RBDO) scheme. The proposed method is applied to the tolerance planning of cable tensioning process of an example cable-stayed bridge. In this paper, the midpoint and radius of the controllable parameters are taken as the optimization variables, and a decoupling evaluation framework based on bilayer surrogate model is established to quantify uncertainty, and then the maximum tolerance range is efficiently extracted from the highly coupled design objectives. The results illustrates that the proposed method not only effectively saves calculation resources, but also ensures high accuracy. The application of tolerance interval to guide engineering decision-making process has shown better inclusiveness to the error accumulation during construction, which improves the construction resilience under the influence of manufacturing and assembly errors.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85151149602&origin=inward; http://dx.doi.org/10.1007/978-981-19-7331-4_79; https://link.springer.com/10.1007/978-981-19-7331-4_79; https://dx.doi.org/10.1007/978-981-19-7331-4_79; https://link.springer.com/chapter/10.1007/978-981-19-7331-4_79
Springer Science and Business Media LLC
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