Assessment of added resistance estimates based on monitoring data from a fleet of container vessels. (15th March 2023)

• Record Type: Journal Article
• Authors: Mittendorf, Malte; Nielsen, Ulrik Dam; Bingham, Harry B.; Dietz, Jesper
• Is Part Of: Ocean engineering. Volume 272(2023)
• Publication Date: 2023-03-15
• Subjects: Added resistance -- Spectral calculation -- Parametric wave spectrum -- Resistance decomposition -- Fleet performance data -- Metocean hindcast data; Ocean engineering -- Periodicals; Ocean engineering; Periodicals; 620.4162
• DOI: 10.1016/j.oceaneng.2023.113892
• Languages: English
• ISSNs: 0029-8018

Abstract

Abstract: A practical estimation methodology of the mean added resistance in irregular waves is shown, and the present paper provides statistical analyses of estimates for ships in actual conditions. The study merges telemetry data of more than 200 in-service container vessels with ocean re-analysis data from ERA5. Theoretical estimates relying on spectral calculations of added resistance are made for both long- and short-crested waves and are based on a combination of a parametric expression for the wave spectrum and a semi-empirical formula for the added resistance transfer function. The theoretical estimates are compared to predictions from an indirect calculation of added resistance relying on shaft power measurements and empirical estimates of the remaining resistance components. Overall, the comparison reveals a bias in bow oblique waves and higher sea states of the spectral estimates as well as a large variance of the empirically derived predictions — particularly in beam-to-following waves. One of the study's main findings, confirming previous studies but based on a much larger dataset than in earlier similar studies, is that added resistance assessment based on in-service data is complex due to significant associated uncertainties. Highlights: Monitoring data of 228 container ships in worldwide service is analyzed. Added resistance in waves is calculated using a spectral and empirical method. The spectral method is based on a semi-empirical formula and wave hindcast data. Estimates in long- and short-crested waves are determined and compared. Empirical predictions rely on shaft power measurements and resistance decomposition.