On-line ship performance monitoring system for biofouling and its control.

Ph. D. ThesisMarine biofouling has a significant impact on the overall hydrodynamic performance of a vessel. The literature shows that powering penalties for heavy fouled ships may reach up to 80% in the worst-case scenario, clearly resulting in higher operational costs and overall greater CO2 emissions. In the 1920’s, ship performance monitoring emerged as one of the most suitable means of estimating these effects using full-scale on-board measurements coupled with various analysis techniques. The primary difficulty of such method stands in differentiating the effect of biofouling from the effects of such disturbances as waves, wind, change of operating conditions and so forth. A deterministic approach to this problem employs physical laws to estimate the contribution of the most relevant disturbances and hence to ‘deduct’ them from the measured in-service resistance. However, very few deterministic Ship Performance Monitoring Systems (SPMSs) have been successfully implemented to estimate all the effects of hull and propeller performance monitoring with both a scrutinised uncertainty and state of the art standards. The present research investigates this knowledge gap. The main aim of this research is to develop a working on-line SPMS based on the first published deterministic performance analysis method dedicated to the measurement of the effects of hull and propeller fouling on ship performance. In achieving these aims, Newcastle University’s R/V The Princess Royal was employed as a development and testing platform of the prototype SPMS, proving to be one of the few applications on small-size vessels. Four Key Performance Indicators (KPIs) were developed to estimate the impact of biofouling on hull and propeller. A novel method to derive Cf is also proposed. The accuracy of the estimations provided by the SPMS developed on-board The Princess Royal was assessed conducting a comprehensive Uncertainty Analysis, which includes all data treatment stages, from acquisition to performance analysis.Sasaki-SMP fun