Retrofits to alternative fuels like methanol represent a strong candidate for complying with current and upcoming environmental regulations. The decision to retrofit to methanol power, propulsion and energy systems introduces uncertainties linked to technology integration, conversion costs, and environmental performance. This paper proposes a bi-objective Markov decision process as the foundation of a design tool aimed to support retrofit decisions within a vessel’s lifecycle. This approach aims to quantify the trade-off between the conflicting objectives of (a) emissions reduction and (b) retrofit costs minimization. The bi-objective formulation is evaluated against the equivalent single-objective formulations of the problem to assess the effect on the feasible design pathways. Depending on the initial vessel preparation level for a retrofit, this paper quantifies the uncertainty in the retrofit pathways during the lifecycle through the metrics of optimal state and optimal action. A case study has been applied to a notional short-sea vessel. Results indicate differing solutions when comparing the bi-objective to two individual single-objective scenarios. Preparation for a retrofit and the selection and usage of a methanol dual fuel configuration indicate a promising strategy to satisfy both objectives for the vessel’s lifecycle timespan.

The integration of methanol power, propulsion and energy systems (PPE) generates uncertainties linked to the selection and sizing of systems, layout design and compliance with strict safety regulations. This paper argues that alternative fuels, such as methanol, should be treated as disruptive innovations, in part due to the uncertainties linked to their implementation. These uncertainties strongly connect to the PPE dimensions and the dependencies among the systems because of integration requirements. Through a model based system engineering inspired approach, the uncertainties are elucidated into relevant inputs for the proposed framework. The authors introduce an uncertainty evaluation framework that uses Monte Carlo simulations to generate the layout design space under uncertainty. The impact of uncertainty on the design is examined through a case study on the layout of a notional engine room. Multiple probability distributions for the PPE dimensions and varied logical architectures – reflecting systems dependencies – are applied to identify patterns in the generated design space. The varied logical architectures influence drastically the dominating solutions of the design space regarding the length. For a 1000-kW notional vessel, under the varied scenarios, the length of the engine room clustered in specific values while the connection costs produced wide value spectrum.

Requirements elucidation is a significant part of early-stage ship design, especially in naval architecture for complex ships. During a vessel’s acquisition process, the stakeholders propose requirements in statements, regulations, Concepts of Operations (CONOPS), vignettes, and Minutes of Meetings, all expressed in natural language. However, bridging these natural language requirements and their impact on the final design remains an open research problem. This research proposes a framework that utilizes semantics interpretation to map the natural language requirements (R) to the layers of the systems architecture: Functional (F), Logical (L), and Physical (P). This paper proposes to use semantics to better understand the effect of requirements on design change occurring in the logical and physical architecture layers of the system architecture. This research also introduces the classification of the requirements on a two-dimensional axis system, with one axis being their importance to the stakeholders and the other axis evaluating their elasticity (i.e., if they can be interpreted in more than one way). This classification provides insights into the characteristics of requirements that may impact the physical design. The proposed framework shows potential for identifying and tracing the propagation of changes and uncertainties stemming from the requirements to the other layers of the systems architecture. This paper showcases the framework through a case study on the semantic interpretation of redundancy and safety regulations for the design of a short-sea vessel’s engine room. The results show that hard” and ”elastic” safety requirements are more influential on the layout arrangement and
thus the shape of the generated design space.

The ongoing technological development of methanol energy converters (EC) towards decarbonization means that their dimensions and performance characteristics will be continually updated during the lifecycle of vessels currently designed. These advancements influence the ease of EC integration within the general arrangement of the vessel. The decision to switch from an internal combustion engine to a fuel cell or a hybrid configuration depends both (1) the technology adoption costs (i.e. CAPEX, OPEX) of the EC and (2)
on the effect of EC on the actual engine room layout. The state-of-the-art literature has typically addressed these two challenges separately. This study proposes a design method to bridge these two fields by combining the use of (1) Markov decision processes to assess uncertain future methanol EC developments during the vessel lifecycle and (2) a generative probabilistic layout algorithm to quantify the risks associated with the EC systems layout integration. The case study identifies the drivers behind the EC technology choice during the lifecycle of a notional yacht vessel.

This article examines the potential implications of using iron powder as an alternative fuel on the design and performance of container ships. Iron powder is a relatively new alternative energy carrier and one in which little research has been done into the application on-board vessels as part of the maritime energy transition. The key benefits of iron powder are that it is a circular energy carrier and the combustion process emits no greenhouse gases. Transitioning to iron powder is expected to have far reaching implications for the design and performance of ships. Thus, this paper aims to perform the first study assessing the potential of this concept applied to container ships. To do so, a preliminary design space was explored with a custom parametric design model developed to generate preliminary designs of iron fuelled container ships as a function of the operational profile. Using this parametric design model, it was identified that iron fuelled container ships are weight limited, unlike conventionally fuelled container vessels. Furthermore, iron fuelled container ships are best suited for short voyages at low cruising speed. For these voyages, it was concluded that iron fuelled ships are economically feasible; however, other alternative marine fuels are likely more profitable than iron due to the low efficiency of iron fuelled ships and the high cost of iron per unit energy.

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.