Accurate experimental benchmark study of a catamaran in regular and irregular head waves including uncertainty quantification. (1st January 2020)

• Record Type: Journal Article
• Authors: Durante, D.; Broglia, R.; Diez, M.; Olivieri, A.; Campana, E.F.; Stern, F.
• Is Part Of: Ocean engineering. Volume 195(2020)
• Publication Date: 2020-01-01
• Subjects: EFD -- Seakeeping -- Regular and irregular waves -- Uncertainty quantification -- Subseries method -- Bootstrap method -- Validation -- Delft catamaran; Ocean engineering -- Periodicals; Ocean engineering; Periodicals; 620.4162
• DOI: 10.1016/j.oceaneng.2019.106685
• Languages: English
• ISSNs: 0029-8018

Abstract

Abstract: Irregular wave experiments are essential to assess the statistics of ship responses in realistic operating conditions and to validate the associated numerical simulations. The cost and time required to achieve statistically-converged results are usually high (both experimentally and computationally). For these reasons, high-quality statistically-converged irregular wave studies are limited in the literature and models to reduce the experimental/computational costs are highly desirable. Here, a statistically-converged experimental benchmark study of a catamaran in irregular waves is presented, along with regular-wave Uncertainty Quantification (UQ) model used to approximate the relevant statistical estimators. The statistical assessment is achieved through recently-developed approaches based on the analysis of the autocovariance function of the ship response, along with block-bootstrap and bootstrap methods. The validation variables are the wave elevation, axial force, heave and pitch motions, vertical acceleration of the bridge and vertical velocity of the flight-deck. Values from the time series are addressed as primary variables, whereas heights associated to mean-crossing waves are referred to as secondary variables. The statistical uncertainty related to Expected Value (EV) and Standard Deviation (SD) of primary variables is evaluated through autocovariance analysis and block-bootstrap methods. The latter are used to assess also the quantile function. EV, SD, and quantile function of secondary variables are then assessed by the bootstrap method. Regular-wave models assess the EV of the axial force, and single significant amplitudes (twice the SD) of pitch, acceleration, and velocity, as relevant merit factors used for design optimization in earlier studies. Highlights: Large experimental campaign in regular and irregular waves for a Delft catamaran was carried out. A regular wave Uncertainty Quantification model was used to approximate relevant statistical estimators. Statistical uncertainty of Expected Value and Standard Deviation evaluated with autocovariance analysis and block-bootstrap.