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A model to optimise the selection of marine dual-fuel low-speed diesel engines

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Abstract

This study aimed to address the state of the art of marine diesel engines computer simulation models and the main computer applications. There are simple models based on transfer function or more complex models based on computational fluid dynamics. The models may be either implemented through basic programming languages or simulated through dedicated packages of internal combustion engine simulation. Owing to the recent interest to reduce the gas emission, dual-fuel engines are increasingly being used as primary propulsion in merchant ships. In this context, a simplified model of marine dual-fuel low-speed diesel engine has been developed. Through the normalisation of specific fuel consumption and exhaust gas data, clear trends approachable by polynomial curves or surfaces were revealed. Thus, by using the proposed model and knowing the characteristics of an engine at its nominal maximum continuous rating, it is possible to predict the engine operation in any design point on the engine layout diagram, even at part load. The maximum deviations regarding the two simulated engines did not exceed −3.4%. Summarising, the developed model is a simple and effective tool for optimising the selection of dual-fuel low-speed diesel engines to be applied in ship propulsion systems.

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Fig. 1

(adapted from MAN Diesel and Turbo [18])

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Authors and Affiliations

  1. Federal University of Rio Grande – FURG, Rio Grande, Brazil

    Crístofer Hood Marques

  2. Federal University of Rio de Janeiro – COPPE/UFRJ, Rio de Janeiro, Brazil

    Crístofer Hood Marques, Carlos Rodrigues Pereira Belchior & Jean David Job Emmanuel Marie Caprace

Authors
  1. Crístofer Hood Marques
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  2. Carlos Rodrigues Pereira Belchior
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  3. Jean David Job Emmanuel Marie Caprace
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Correspondence to Crístofer Hood Marques.

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Marques, C.H., Belchior, C.R.P. & Caprace, J.D.J.E.M. A model to optimise the selection of marine dual-fuel low-speed diesel engines. Mar Syst Ocean Technol 12, 138–149 (2017). https://doi.org/10.1007/s40868-017-0030-6

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  • DOI: https://doi.org/10.1007/s40868-017-0030-6

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