When installing a data collection platform onboard new
liquefied natural gas (LNG) carriers, the first step is to
gather as much knowledge as possible about onboard operations.
The results of this data collection help determine vessel
efficiency, which, in turn, assists owners in maximizing ship
efficiency and operations.
Todays LNG carriers are amazing feats of engineering
(Fig. 1). The ship cargo is extremely
dangerous because of its highly flammable properties.
Furthermore, the dual-fuel/tri-fuel engines used, as well as
the occasional presence of reliquefication plants, make these
vessels among the most complex floating engineering projects in the world.
1. Todays LNG carriers represent
of engineering. Photo courtesy of Eniram.
The transport of LNG can be compared to running with a full
soft drink can in a backpack. When the can is shaken, some of
its contents will vaporize as CO2, which increases
the cans internal pressure. A similar process occurs in a
tank filled with LNG, although the somewhat inert gas is
replaced with a variety of different natural gases [i.e.,
boiloff gas (BOG)]. The increasing pressure must be relieved by
releasing gas from the tank.
LNG tank design
LNG tanks are extremely well insulated to limit the BOG that
naturally occurs after a cargo is loaded. Typically, the cargo
is loaded at an approximate temperature of −170°C.
However, despite the insulation, a small percentage of the LNG
cargo is converted to gas during each day of a sea voyage. The
size of the percentage will depend on the efficiency of the
insulation and the weather patterns en route.
Improvements in insulation and clever engineering have
increased storage effectiveness. A small number of LNG vessels
are now equipped with reliquefication plants that are able to
reliquefy the excess BOG and return it to the tanks, making
these ships more environmentally efficient. For the
majority of vessels not equipped with reliquefication plants,
the excess gas can be used for running vessel engines or
boilers. In practice, however, LNG carrier operations are more
complicated than this description suggests.
Rough seas are part of the scenario. These types of sea
states can behave exactly like the example of a soft drink can
in a backpack, jostling the cargo about and increasing the
pressure in the tanks. On one of the authors recent LNG
carrier trips, the ship encountered not one but two typhoons.
Typhoons Francisco and Lekima kept the officers and crew on
alert, but the ship was able to sail through the storms without
any problems. Some of the excess gas was used in the engines;
the rest was reliquefied. In this type of situation, older LNG
ships may have been forced to burn the fuel without using
Complex vessels should be matched with sophisticated, yet
easily understood, data-gathering solutions. The first step of
the process is data integration. Data is collected from
the various automated systems already installed onboard, as
well as from proprietary sensors. Readings are also received
from other equipment located on the bridge or in the cargo
Monitoring carrier operation
This deep integration is necessary to obtain the highest
level of accuracy regarding the ships physical behavior.
Essentially, all of the information being gathered must be
validated. Sensors are attempting to analyze real phenomena,
and trusting such devices should be done with caution before a
proper calibration is performed.
This data can be used to observe how offset a speed log is
(Fig. 2), or to monitor the reading errors of
an anemometer, for example. These actions are essential to
understanding the actual performance of a carrier. They also
aid in the modeling of ship energy usage and in mapping the
breakdown of where energy is consumed. On an LNG vessel,
numerous systems are the source of hundreds of variables. The
initial target of a data collection platform is to make sense
of this information, and to present it in a normalized
2. Speed log device errors can be assessed
A clear offset is seen on the vertical axis, which
the difference between speed through water and
After the integration of all sensors and
variables, both the onboard and onshore systems are
automatically synchronized. This is the second step of the
process. Modeling takes into account a wide variety of
variables, such as fuel flowmeters, navigation equipment,
engines and reliquefication plant usage. The speed profile, for
example, requires automatic updates based on the latest sea
current and wind data available onshore. No additional work is
required from the navigation officer to import the data, and
yet it is achievable in real time.
Measurements performed onboard will also be taken into
account to better reflect the forecast measurements provided
from onshore. Forecast and data share one simple fact: taken
alone, the flow coming out of a device or data source is only
as reliable as the device or the forecast itself. Ship-wide
integration of a platform can help put into context all of that
information, as in the speed log example.
The third step of the process is the actual data crunching
to provide the optimum guidelines typically seen on the
display. Onboard and onshore dedicated calculation servers are
provided to improve the accuracy of the optimums.
During the installation of the system described earlier, the
weather threatened to delay the carriers arrival to the
next port. However, the integrated system enabled the rapid
approximation of an estimated time of arrival, taking into
account all of the effects of the rough weather and its energy
cost. Engineers could then use the prediction regarding the
required energy necessary to reach the next port as close to
the original schedule as possible.
Officers and engineers aboard an LNG carrier are extremely
busy. They require real-time, user-friendly data derived from
the vessels systems, as well as accurate individual
metrics. Maximizing fuel efficiency should not trump other
tactical, on-the-spot decisions needed to ensure that the ship
continues to sail as safely as possible with its strategic
Guillemin leads the development team for Enirams onshore and
onboard platforms. As an enthusiast builder, he has a
broad experience in converting ideas into usable,
concrete technologies. Prior to Eniram, Mr. Guillemin spent
most of his career in startup companies in the data
crunching field, from search engine development to
crowdsourcing services. He holds an MEng degree in
computer science from ESIEA Paris in France.