In DNV GL, we believe that: “energy efficiency is an inherent and fundamental aspect for shipping through the ages”. Whether we want faster ships, like the first Athenian triremes (fastest ships of their time), whether we want endurance, capacity, fuel efficiency, or better environmental performance, the key aspect is efficiency. And what in fact changes in todays’ market needs, is the challenges and the questions we pose, in terms of the efficiency of vessels. We can briefly summarize what we currently mean by energy efficiency and what we want from our vessels in these 5 questions:
- How to reveal the biggest sources of losses?
- How to priorities efficiency improvement measures?
- How to provide a common way of quantifying efficiency?
- How to change behavior of shore and vessel teams towards more efficient operations?
- How to demonstrate control and transparency to customers and other industry stakeholders?
We want for sure to reveal our biggest sources of losses on board in order to be able to prioritize, to focus on specific areas and to propose solutions. Another problem that we certainly face is how to quantify efficiency in a common, formal and consistent manner. And of course how to use all that knowledge and information in order to change the behavior of shore and vessel teams towards more efficient operations. This is a key aspect, because ships are operated by crews and in turn, shipping companies that need to adapt to a more energy efficiency mentality. And also, it is important to remember that the focus is not always on emissions and on reduction of fuel cost. The focus sometimes is on demonstrating that a company has control and transparent to affect its business viability.
In particular, when we come to ships systems, we see that the main challenge is that systems and operations become increasingly complex. Quantification is the key. In order to have quantification, all the digital data that comes for our ships can help us. But it’s only a part of the puzzle. What we also need is analytics. What we see under the term analytics is the ability to model and simulate the behavior of our system (see picture 1). Quantifiable metrics of efficiency lead to:
- Actionable knowledge
- Prioritization focus areas and
- Prioritization of investments.
In DNV GL, we address this through our in house model and simulation framework called COSSMOS. Through this, we are able to connect data from existing ships or information regarding new build ships, with a complete modelling of the ship machinery system. So, we build models of ship systems and then we use them to analyze and interpret data both for new-buildings and ships in operation. In particular, we also use this tool to assess new technologies.
Two indicative examples demonstrate how we apply this model and simulation approach in order to improve efficiency in practice; the first involves new build ships and the other involves ships in operation. Both these examples deal with existing projects within the shipping industry - with our customers that lead to practical and tangible efficiency improvements.
The first example considers: how we improve decision support in the design of modern LNG carriers and how we approach the overall efficiency or fuel consumption reduction problematic, with a design by a trade approach. The key aspect is the consideration of the operational profile and the trading pattern of the vessel early in our decision making process. Our idea is to be able to compare alternative machinery configurations and various energy improvement variants, early in the design process (at the pre-contract phase), and to be able, through modelling and simulation, to identify promising alternatives, quantify their behavior and result in a techno-economically viable improvement of efficiency. One such recent example is the LNGreen concept design, in which DNV GL in cooperation with Hyundai Heavy Industries, GasLog and GTT, arrived in a design that improves total efficiency of the vessel for the trade routes and operational profiles, considered by the ship-owner by 8.5%. This includes all aspects of efficiency improvement areas; from hydrodynamic performance, to engines and systems. Other similar studies include the techno economic comparison of different configuration alternatives that we do in pre-contract face for different solutions, proposed by the shipyards to a ship owner. Again, by being able to quantify efficiency, fuel consumption and in turn fuel cost, we are able to compare alternatives and provide rigorous decision support, comparing in a common basis different solutions. We are in a position to also dive deeper and having information for the entire operating envelope of the vessel so as to provide insight regarding the possible sailing modes and possible conditions that may encounter in its service life. By having quantifiable information, we are able to support the decision making process even better.
The second set of examples, involves ships in operation (fleet already in service). Here again, we face complex operations and complex systems, that may have potential for improvement. Again, we use our model and simulation capabilities to assess the energy efficiency of certain operations, like the cargo discharge operation on board crude oil tankers. Here, we fuse data with a process model of the complete discharge system of a vessel, that we have calibrated and customized to represent the exact system on board, and then we ask for the crew to gather data, during the discharge process. We process them, we fit them to our model, we do simulations and as a result we obtain improvement strategies that can be translated to practical advice to the crew.
In this type of projects, after an initial advice face, we try to educate the crew by giving them feedback on how their actions influenced fuel consumption and efficiency. It is evident that the crew learns and adapts. The office learns to monitor more efficiently this process and we have tangible efficiency improvements with respect to the efficiency of that particular process. This is more evident when we see a crew change, when the new crew has to be re-aligned with new practices and advices. After an initial calibration period, the performance improves as well. Therefore, through quantification and being able to demonstrate to personnel on board what their actions mean, we are in a position to improve efficiency in practice.
In conclusion, I would like to highlight the importance of quantifying efficiency and different technology alternatives, capturing all the aspects that are relevant to our system behavior and hence its efficiency, and the importance to examine the integrated system. We are currently in a transition phase in shipping with data smart and innovative solutions that are coming. We may tend to believe that these are things for the future. I don’t believe that, as one of my professors used to say “future is here but is not evenly distributed”.
Above article is an edited version of Mr. George Dimopoulos presentation during the 2016 SMART4SEA Forum
Please click here to view his video presentation
The views presented hereabove are only those of the author and not necessarily those of SAFETY4SEA and are for information sharing and discussion purposes only.
About George Dimopoulos
George Dimopoulos is a Naval Architect & Marine Engineer, holding a PhD in Marine Engineering from NTUA. His field of expertise is the modelling and optimization of complex ship machinery systems. His professional experience, both in the academia and in DNVGL’s R&D units, is in the application of computer and process modelling techniques and advanced thermodynamic analysis methodologies in order to optimize ship systems for improved performance, safety, fuel savings, emissions reductions and cost-effectiveness. He is lead researcher or project manager in various R&D and commercial projects fusing forefront research methods and new technologies with the modern shipping industry environment. As a researcher, he has authored or co-authored more than 30 peer-reviewed papers in scientific conferences and journals.