Virtual hull monitoring using hindcast and motion data to assess frigate-size vessel stress response
The structural response of a frigate-type hull is assessed using virtual hull monitoring. For this approach, wave conditions were retrieved from two wave hindcast models and a ship as a wave buoy assessment using motion data. The stress response calculated using the numerical model of the vessel and...
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Veröffentlicht in: | Ocean engineering 2022-02, Vol.245, p.110338, Article 110338 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | The structural response of a frigate-type hull is assessed using virtual hull monitoring. For this approach, wave conditions were retrieved from two wave hindcast models and a ship as a wave buoy assessment using motion data. The stress response calculated using the numerical model of the vessel and the three wave datasets is compared to strain measurements. Further comparisons include estimates of the accumulated fatigue damage at a midship bracket based on the same data sources. Sensitivity of the fatigue accumulation to the wave spectrum description and input errors in the wave data are assessed. Results show fatigue damage estimates calculated using wave hindcast data are in good agreement with values derived from strain measurements. However, in storm conditions, the agreement is poor. In contrast, damage estimates calculated using the wave data from ship as a wave buoy procedures better represent responses in storm conditions but significantly over-estimate damage accumulation in milder seaways. Sensitivity analyses show that uncertainty in hindcast wave parameters has a limited effect on fatigue damage calculations while wave spectrum shape is more significant.
•Fatigue estimates from wave hindcast and numerical models agree with measurements•Ship-as-a-wave buoy sea state estimates better reflect fatigue damage during a storm•Random uncertainty in hindcast statistics causes minor differences in fatigue•Short-term wave definitions produce differences in fatigue accumulation up to 30% |
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ISSN: | 0029-8018 1873-5258 |
DOI: | 10.1016/j.oceaneng.2021.110338 |