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The use of inverse methods for response estimation of long-span suspension bridges with uncertain wind loading conditions

Practical implementation and results for the Hardanger Bridge

Autor(en):


Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Journal of Civil Structural Health Monitoring, , n. 1, v. 9
Seite(n): 21-36
DOI: 10.1007/s13349-018-0319-y
Abstrakt: Structural health monitoring seeks to assess the condition or behavior of the structure from measurement data, which for long-span bridges typically are wind velocities and/or structural vibrations. However, in the assessment of the wind-induced response effects, models for the loads must be adopted, which introduces uncertainties. An alternative is to apply model-based inverse methods that consider the actual input forces unknown, and estimate these forces jointly together with the system states using limited vibration data. This article presents a case study of implementing Kalman-type inverse methods to a long-span suspension bridge in complex terrain, with the objective of estimating the full-field response. Previous studies have shown the local wind field is complicated, leading to uncertain load effects. We discuss the key challenges faced in the use of the methodology for the long-span bridges and present the results for a 6 h storm event. The analysis show that the dynamic response contribution from the 14 lowermost bridge modes (up to 3 rad/s or 0.5 Hz) can be reconstructed with decent accuracy. The estimated response magnitude differs from the predicted response from design specifications, pointing to load-related uncertainties that can be reduced to give greater confidence in the assessment of wind-induced fatigue, wind-resistant performance and other response effects.
Stichwörter:
Hängebrücke inverse Methoden Bauwerksmonitoring

Bauwerke und Projekte

Bauwerkstypen

Structurae kann Ihnen derzeit diese Veröffentlichung nicht im Volltext zur Verfügung stellen. Der Volltext ist beim Verlag erhältlich über die DOI: 10.1007/s13349-018-0319-y.
  • Über diese
    Datenseite
  • Reference-ID
    10249453
  • Veröffentlicht am:
    28.06.2019
  • Geändert am:
    28.06.2019
 
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