Benjamin Lagemann

PhD student WP4 (2019–2022)

Supervisor: Stein Ove Erikstad

Co-supervisor: Bjørn Egil Asbjørnslett, Sverre Steen





Concept Ship Design for Future Low-Emission Shipping

Research topic

The overarching research question for this project is
How to systematically design innovative, future-proof and low-emission ships at a conceptual level?
The main research question is divided into three different sub-questions:
  • How to rapidly explore different conceptual ship designs?

A large number of different systems and principles for lowering ship emissions are available today. The aim is to find out how these principles can be combined and assessed on a case basis for each new design.

  • How to prepare for uncertain future contexts and operations?

While the focus of the first sub-question is on synthesizing ship systems, this question targets the system response to future contexts and operations. A life-cycle assessment accounting for different scenarios shall be set up and combined with the synthesis model.

  • How to structure the design process?

With tools for synthesis and analysis in place, this question addresses the way to effectively engage and interact with all stakeholders in the conceptual design phase.

Industrial goals

A large fraction of costs and ship life-time emissions are determined by decisions made during the preliminary ship design phase. Thus, the goal of this study is to support ship designers and ship owners in their decisions during this early design phase. An illustrative question to be supported would be: “Should the next newbuilt be prepared for a retrofit with, e.g. Hydrogen storage facilities, during its life-time?”. Since the definite answer is likely to depend on certain scenarios for the future, these shall be effectively included in the design process.

Expected results

  • Methodology and tool to investigate aspects such as Flexibility, Modularity, Infrastructure, Visualization, and Uncertain future contexts on the ship design process and ship life cycle emissions.
  • Prove the tool’s performance in different case studies.