Introduction
Ships are traditionally optimized for operation in calm water, at design draught. Wind and waves are important for the operation of the ships, and might mean that the ships should be designed differently to be optimal in their actual operation. In addition comes the need to design for safety and operability in really harsh weather conditions. Both purposes require methods for reliable prediction of the performance in a seaway. To predict the powering performance of ships in a seaway, one need to predict the added resistance due to wind and waves, and the change of propulsive efficiency. Furthermore, the prediction methods must be computationally efficient, something that currently rules out complete RANS CFD simulations. With respect to computation of added resistance, the main shortcomings of existing practical computational methods are:
• following seas,
• effect of above-water geometry,
• accuracy in general
• added resistance due to steering and manoeuvring
With respect to prediction of speed loss and power increase, in addition to predicting the added resistance, main challenges are related to:
• Voluntary speed reduction – criteria and typical practice
• Effect of use of rudder, related to course-keeping, which makes it difficult to predict.
• Change of propulsive efficiency – the effect of change of propulsion point depends on added resistance and is well-known, but the effect on hull interaction factors like thrust deduction and wake is less well known.
• Propeller-engine interaction, impacting both propeller efficiency and engine specific fuel consumption
There is a general need for end-to-end validation of speed loss and power increase due to wind and waves, since there are so many inter-related effects, each of them being quite complicated.
Currently, speed loss due to wind and waves is accounted for in the design by use of a sea margin on power, which is routinely set to 15%. However, the trend to make ships with less power in order to gain a good EEDI ranking probably means that the sea margin should be set higher. Effectively the same problem is related to predicting expected sea margin in slow steaming operation (Eco and SuperEco). Thus, there is a need for establishing methods and guidelines for rational determination of sea margin.
Objective:
• To obtain full scale data for validation of computational methods
• Learn more about factors that are important for speed loss and added power due to operation in waves
• Validation of computational methods for speed loss and power increase due to wind and waves
• Review the current practice with respect to sea margin, and propose improved approach
• Investigate the effect of waves and off-design operation on Energy Saving Devices
Expected impact
• competitiveness through increased knowledge and guidelines wrt hull design, weather routing and application of Energy Saving Devices
• Potential fuel savings 10-15%
Contributions from industry partners:
• Experience and/or data from operation of ships with ESD. Before-after experiences are particularly welcome
• Model tests of ESD at MARINTEK. The project can only finance the extra tests in waves. It relies on an influx of new project(s). Alternatively, allowing use of still existing models from previous test campaigns, can be acceptable.
Deliverables:
• Method and tool for full scale data monitoring of speed loss and power in-crease
• Computational methods for speed loss and power increase
• Effect of waves on Energy Saving Devices.
WP – involvement
WP 2 Hull and Propeller: Hydrodynamic simulation modelling
WP 3 Power Systems and Fuel: Power system simulation modelling
WP 4 Ship system integration, validation and monitoring: Integration of simulation models
and validation of virtual prototypes against full-scale data
Schedule:
2016
Participants and resources
SP leader: Sverre Anders Alterskjær, MARINTEK (now SINTEF OCean)
Research partners: MARINTEK, NTNU
Industry partners: Wallenius Wilhelmsen, KG Jebsen Skipsrederi, Grieg Star, Vard Design, Havyard, DNV GL, Jotun, Rolls-Royce Marine
The sub-project was finalized in 2016 and the Gymir simulation tool was further developed and tested through business cases in a new Sub-project SP7, integrating the results of 2016- sub-projects SP2, SP3 and SP4.