SOURCE-LINKED INTELLIGENCE
Flexible Tool Environment for Holistic Retrofits and Decarbonization of Ships
total retrofit design space within reasonable time, which means that ship owners cannot be sure that the retrofit solutions are the best for a given vessel. FIT-HORIZONS aims to solve this by using a machine learning-based multi-fidelity approach and combining operational and experimental data series, advanced AI models, and advanced dimensionality techniques to build surrogate models that will then be used to construct 6 synthesis models representing each of the 6 ship types defined by the ZEWT Partnership. Moreover, a cost-benefit model will be integrated with the synthesis models to consider regulatory compliance and LCA metrics across the vessels’ lifetime. Together, this will allow for a flexible and efficient design process in which multiple combinations of retrofit technologies can be analysed at the same time to identify optimal retrofit solutions for a given vessel. Finally, virtual demonstrations will be carried out where ship designers will collaborate with ship owners to design 6 optimised retrofit solutions for vessels from each of the 6 ship types that will be ready to
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- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 3998318.53
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T05:31:32.981Z. This is not the publication date.