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Uncertainty Analysis of full-scale ship performance monitoring onboard The Princess Royal

Lookup NU author(s): Alessandro Carchen, Dr Serkan Turkmen, Dr Kayvan Pazouki, Dr Alan J Murphy, Batuhan Aktas, Professor Mehmet Atlar

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Abstract

The increasing attention towards ship operational optimization and maintenance strategy over the past decades has become a driving force for performance data retrieval and analysis as primary decision tools. Continuous monitoring, big data analysis and mathematical modelling are commonly employed by nearly all the applications, not seldom targeting for small changes or degradation in hull hydrodynamic performance such are those caused by biofouling growth. In as much as every measurement retains an uncertainty, the complex models employed in ship performance monitoring also require estimation of the total uncertainty to ensure the targeted result lays outside the uncertainty range.Newcastle University’s Research Vessel, The Princess Royal, is used as a platform to develop an in-house Ship Performance Monitoring System to analyse the effect of biofouling growth on the hull and propeller performance. Periodical dedicated service trials were carried out to establish a performance database and then used to calibrate and validate the model. Different experimental and computational techniques have been employed to outline the behaviour of the R/V in off-design conditions. A deterministic approach was also adopted as core of the analysis. The total uncertainty of the system is calculated using Monte Carlo Methods for Uncertainty Analysis using the measured data.This paper presents the results of the Uncertainty Analysis carried out on the full-scale Ship Performance Monitoring together with results of performance monitoring carried out over the years.The increasing attention towards ship operational optimization and maintenance strategy over the past decades has become a driving force for performance data retrieval and analysis as primary decision tools. Continuous monitoring, big data analysis and mathematical modelling are commonly employed by nearly all the applications, not seldom targeting for small changes or degradation in hull hydrodynamic performance such are those caused by biofouling growth. In as much as every measurement retains an uncertainty, the complex models employed in ship performance monitoring also require estimation of the total uncertainty to ensure the targeted result lays outside the uncertainty range.Newcastle University’s Research Vessel, The Princess Royal, is used as a platform to develop an in-house Ship Performance Monitoring System to analyse the effect of biofouling growth on the hull and propeller performance. Periodical dedicated service trials were carried out to establish a performance database and then used to calibrate and validate the model. Different experimental and computational techniques have been employed to outline the behaviour of the R/V in off-design conditions. A deterministic approach was also adopted as core of the analysis. The total uncertainty of the system is calculated using Monte Carlo Methods for Uncertainty Analysis using the measured data.This paper presents the results of the Uncertainty Analysis carried out on the full-scale Ship Performance Monitoring together with results of performance monitoring carried out over the years.The increasing attention towards ship operational optimization and maintenance strategy over the past decades has become a driving force for performance data retrieval and analysis as primary decision tools. Continuous monitoring, big data analysis and mathematical modelling are commonly employed by nearly all the applications, not seldom targeting for small changes or degradation in hull hydrodynamic performance such are those caused by biofouling growth. In as much as every measurement retains an uncertainty, the complex models employed in ship performance monitoring also require estimation of the total uncertainty to ensure the targeted result lays outside the uncertainty range. Newcastle University's Research Vessel, The Princess Royal, is used as a platform to develop an in-house Ship Performance Monitoring System to analyse the effect of biofouling growth on the hull and propeller performance. Periodical dedicated service trials were carried out to establish a performance database and then used to calibrate and validate the model. Different experimental and computational techniques have been employed to outline the behaviour of the R/V in off-design conditions. A deterministic approach was also adopted as core of the analysis. The total uncertainty of the system is calculated using Monte Carlo Methods for Uncertainty Analysis using the measured data. This paper presents the results of the Uncertainty Analysis carried out on the full-scale Ship Performance Monitoring together with results of performance monitoring carried out over the years.


Publication metadata

Author(s): Carchen A, Turkmen S, Pazouki K, Murphy AJ, Aktas B, Atlar M

Publication type: Conference Proceedings (inc. Abstract)

Conference Name: The 5th International Conference on Advanced Model Measurement Technology for The Maritime Industry

Year of Conference: 2017

Acceptance date: 14/08/2017

Print publication date: 13/10/2017


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