ExpectedOutcome:Project outputs and results are expected to contribute to all of the following expected outcomes:
Reduced emissions and improved efficiency enabled through development of digital models and tools for a wide range of vessel types, ship systems and operational environments.Prove and quantify the impact regarding emissions reductions and improved efficiency through productivity and performance increases based on a proven and efficient environmental impact assessment methodology.Ensuring the wider applicability of digital models for different ship types, both for new constructions and for retrofitting, through a comprehensive methodology and a transferable system architecture.Proving the interoperability of data models between different ship types and regarding the link with port digital twin models.Benchmarking efficiency improvements against other industry sectors.Increase the confidence of investors concerning the expected improvements in energy efficiency and reduced emissions resulting from upgrades and modifications for both new designs and retrofitting.In the medium term, enable the development of the “zero emission decision support system” as a cont...
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ExpectedOutcome:Project outputs and results are expected to contribute to all of the following expected outcomes:
Reduced emissions and improved efficiency enabled through development of digital models and tools for a wide range of vessel types, ship systems and operational environments.Prove and quantify the impact regarding emissions reductions and improved efficiency through productivity and performance increases based on a proven and efficient environmental impact assessment methodology.Ensuring the wider applicability of digital models for different ship types, both for new constructions and for retrofitting, through a comprehensive methodology and a transferable system architecture.Proving the interoperability of data models between different ship types and regarding the link with port digital twin models.Benchmarking efficiency improvements against other industry sectors.Increase the confidence of investors concerning the expected improvements in energy efficiency and reduced emissions resulting from upgrades and modifications for both new designs and retrofitting.In the medium term, enable the development of the “zero emission decision support system” as a contribution to the 55% reduction goals of fuel consumption in 2030.
Scope:The digital revolution is affecting most industrial sectors, enabling the digital modelling of designs, manufacturing processes and operations. A wider and better development of Digital Twin (DT) models enables new functionalities for the design and operation of vessels to improve operational efficiency to be developed and validated with increased confidence without resorting to more costly physical testing. DT modelling can be founded and validated using sensor data, data mining and merging, big data, AI and self-learning to improve efficiency on all levels. Such developments increase owner confidence in the expected performance when procuring innovative green systems as well as providing operational feedback to the manufacturer which can be used to further improve energy efficiency. In this respect DT models are understood as wide-ranging tools with known application areas and those still to be explored.
The waterborne (transport) sector is characterised by very diverse requirements and market realities. Ships, their systems and related technical and commercial processes are already widely using digital technologies including virtual models but those are generally developed individually and with significant overlaps. Capital expenditure is often very high. The wider implementation and integration of digital technologies into more coherent Digital Twins on-board and onshore supporting user oriented decisions is still in its infancy.
Whilst simulation environments are relatively mature maritime system tools, development to enable full exploitation of the potential functionalities is still lacking.
Activities will address the DT concept in order to improve energy efficiency and environmental performance from the early design phase of vessels to the end of the life cycle, thus providing assurance to the owner or operator concerning the expected improvements resulting from upgrades and modifications. This will be a key factor to achieve the zero-emission targets for waterborne transport, while increasing the understanding of vessel performance in a wide range of operations, in particular in the view of the parallel uptake of a multitude of innovative technologies for on-board energy storage, distribution and conversion as well as those for voyage optimisation and manoeuvring. A methodology to assess environmental impacts and performance improvements through the DT model should be developed and validated, with the definition of KPIs orienting the design choices and manufacturing processes.
Project(s) will develop DT models, preferably based on existing specifications and simulation environments, addressing different ship systems (e.g. engine and machinery operations, hull/propeller performance and interaction models, electric network management including in particular HVAC, cargo handling) in order to have a significant impact on energy efficiency as well as on operational performance, both in maritime transport and IWT and with regard to newbuildings and existing vessels. To this end the dynamic use of real life data (feedback loop) is expected to be addressed as well.
This topic implements the co-programmed European Partnership on ‘Zero Emission Waterborne Transport’ (ZEWT).
Specific Topic Conditions:Activities are expected to achieve TRL 5 by the end of the project – see General Annex B.
Cross-cutting Priorities:Co-programmed European PartnershipsOcean sustainability and blue economy
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