The CHyPS project (“Clean Hydrogen Propulsion for Ships”) will develop essential building blocks in the roadmap to a comprehensive modelling suite to enable simulation of the powertrains of the vessels of the future. Within CHyPS, the focus will be on detailed modelling of green and clean ship engines on hydrogen and methanol, and the storage system for e-fuels, with a focus on liquid hydrogen. The models will be written in a way that allows their implementation in either open source or commercial system simulation software. Their integration in specific software will be demonstrated within the project, for case studies that will be defined in consultation with the Industrial Advisory Board (IAB).

Specifically, the project will realize the following objectives:

1. Develop and validate a comprehensive two-phase CFD model based on existing and newly developed tools in OpenFOAM® to simulate the thermo-fluid-dynamics behavior of e-fuel in the tank with particular emphasis on cryogenic e-fuel (e.g. liquid hydrogen) and on transient conditions (e.g. bunkering, sloshing…).
2. This will allow to create a high-fidelity numerical database of representative cases to support model calibration and better understand the relative importance of the different physical phenomena governing the pressure dynamics inside the fuel tank for specific tank architectures and specific external excitations faced during an operation profile.
3. Develop and implement a modeling strategy based on a transient thermodynamic fuel tank model to simulate the pressure dynamics inside the tank and the boil-off rate for a full operation profile combining different sequences (bunkering, harbor, maneuvering and navigation).
4. Develop and extend the suite of alternative fuel building blocks: burning velocity of hydrogen and methanol, in-cylinder heat transfer model, emissions models, models for abnormal combustion phenomena in spark ignition and dual fuel engines;  
5. Develop integrated models for the potential combinations of fuels and engine technologies: e.g. spark ignition with port or direct injection, or pre-chambers; dual-fuel with port or direct injection; for hydrogen and methanol; including validation
6. Develop a general framework for a self-calibrating modeling architecture open to online and transfer learning, and apply a self-calibrating machine learning architecture to fuel tank model calibration and engine model calibration.