Establishing the Influence of Methanol Fuelled Power Propulsion and Energy Systems on Ship Design

Conference Paper (2023)
Author(s)

A. Souflis-Rigas (TU Delft - Ship Design, Production and Operations)

JFJ Pruijn (TU Delft - Ship Design, Production and Operations)

Austin A. Kana (TU Delft - Ship Design, Production and Operations)

Research Group
Ship Design, Production and Operations
Copyright
© 2023 A.S.R. Souflis-Rigas, J.F.J. Pruyn, A.A. Kana
DOI related publication
https://doi.org/10.59490/moses.2023.658
More Info
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Publication Year
2023
Language
English
Copyright
© 2023 A.S.R. Souflis-Rigas, J.F.J. Pruyn, A.A. Kana
Research Group
Ship Design, Production and Operations
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Abstract

The adoption of alternative energy carriers is one of the key ways to meet the increasingly stricter emission regulations faced by shipping vessels from the international maritime organisation (IMO) and European Commission. To support this objective, this study examines the challenges and uncertainties associated with implementing a methanol power propulsion and energy (PPE) system on the design of a vessel. This paper argues that new fuels, such as methanol, should be treated
as disruptive innovations due, in part, to the uncertainties surrounding their implementation. Their integration causes challenges regarding systems selection, layout design, and maintaining strict safety measures. In the case of methanol, current research treats the fuel as a system conversion based on diesel fuel. This paper provides a review of the state-of-the-art on the design of methanol fuelled vessels, and identifies a research gap related to the need for a new suitable design method for the design of ships integrating future alternatively fuelled PPE systems. A design approach inspired by model-based systems engineering integrating uncertainty modelling is proposed to examine the influence of uncertainty on the design of the vessels. The impact of uncertainty on the design is investigated through a case study of a simplified engine room layout utilizing a genetic algorithm to produce layouts for variable PPE systems dimensions within a Monte
Carlo simulation.