First of all a warm thank you to all the partners for active participation at the Smart Maritime Network meeting in Værnes in October. The more you engage in Smart Maritime, the more it can ensure valuable research activity targeting relevant challenges for the Norwegian maritime industry.
A learning point for next meeting will be to have longer workshop-sessions in smaller groups.
Minutes of the Network meeting, as well as documents and presentations, can be downloaded from the website.
Positive feedback from the Norwegian Research Council
On November 3rd, the Norwegian Research Council, represented by Liv Jorunn Jenssen, Sigurd Falch and Kai Mjøsund, carried out a Site Visit of Smart Maritime at MARINTEK. NRC expressed their satisfaction regarding the progress of the Centre and the cooperation between the research team and the Technical Advisory Committee. They noted particularly the engagement from industry partners, and your high expectations and requirements playing a key role for ensuring innovation. The written evaluation and feedback from NRC will be made available when ready.
Planning of 2017 activities
Based on the discussions at the Network meeting in Værnes and dialog with our industry Coordinator, the management team drafted a plan for 2017-activities. This will be presented to the Smart Maritime Board on November 22nd together with a budget proposal to be discussed and finalised.
The priority is to ensure balance between long-term publishable research and shorter-term projects with practical value for industry partners. The focus is put on fewer activities and exploiting synergies across work packages and across sub-projects.
Following the Board meeting and the General Assembly (voting the final decision regarding 2017-budget and activity plan), detailed plans for each sub-projects will be established in cooperation between the research team and industrial partners.
The date for the General Assembly has been re-set to December 20th, 1pm.
The General Assembly consists of one representative of each Consortium partner. The meeting will be organised by Video-conference. A notice of meeting and practical information will be sent tomorrow to the primary contacts of each Consortium partner.
Please find online the list of contact persons from each industry partners, with indication of primary contact person. We kindly ask you to review it and send us corrections if necessary.
Publication & Representation:
Smart Maritime represented at the SNAME Maritime Convention 2016
Haakon-Elizabeth Lindstad and Evert Bouman were present at the SNAME Maritime Convention 2016, held in Seattle from November 1-5. The convention, organized by the society of naval architects and marine engineers (SNAME), was an excellent opportunity to create visibility for the work done in Smart Maritime outside of Norway.
Elizabeth presented the paper Revitalization of short sea shipping through slender, simplified and standardized designs. Assessing several cases, she concluded that significant fuel and cost savings can be achieved, and that these savings might be of a similar magnitude as the traditional Economies of Scale benefits, which are achievable by doubling the vessel size.
Evert presented the paper Life-cycle approaches for bottom-up assessment of environmental impacts of shipping. He outlined the philosophy and motivation behind the life-cycle model developed within the SFI. In addition, he presented a test-case assessing environmental impacts of an Aframax tanker and the benefits of reducing block coefficient and/or operational speed.
Statistical Filter based Sensor and DAQ Fault Detection for Onboard Ship
Prasad Perera's article on Statistical Filter based Sensor and DAQ Fault Detection for Onboard Ship is now available online. Statistical filter based sensor and data acquisition (DAQ) fault detection is presented in this study. The parameters of a large-scale data set of ship performance and navigation information are considered as statistical distributions and principal component analysis (PCA) is used to identify the hidden structure of the same data set.