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)
523
minimize the arrival time and minimum energy
requirement.Intheminimumarrivaltimemodel,we
assume that the engine of the selected vessel can
provide constant power output and ship speed can
changed due to weather condition. The ETA
(Estimated Time to Arrival) is used to set a shorter
route
fromdepartureporttodestinationportnodeby
applyingtheweatherforecastdata.Inthismodel,the
pathcost functioncanbe estimatedas asthesailing
time.Intheminimumenergymodel,weassumethat
theshipʹsenergyoutputcanbechangedtokeep the
speed constant. It
can be seen that when a vessel
operatesundertheinfluenceofenvironmentsuchasa
windand wave, more energyshould be supplied to
the vessel than in case the vessel operates in clam
water. Therefore, the path cost function can be
estimated as the minimum energy to maintain a
constantshipspeed.
3.3 Variousspeedreductionparameters
The method for avoiding parametric rolling is
recommendedbyIMOcirc.1228,thecourseandthe
speed of the ship should be chosen avoiding these
condition, encountering period
E
T close to the ship
rollperiod
R
T (
ER
TT )oronehalfoftheshiproll
period
(0.5)
ER
TT .
In ship navigation, the speed reduction of a ship
can be divided into two types, voluntary and
involuntary speed reduction. Involuntary speed
reduction can be estimated from empirical formulae
suggestedbymanyresearchersinthepast.Weused
Kwon’s method (1981, 2005) to predict involuntary
speedreductionunderdifferentweather
condition.In
addition,theeffectoftemperatureisalsoconsidered
intermsofinvoluntaryspeedreduction.
Ontheotherhand,foravoidingacertainexcessive
motion, voluntary speed reduction was reduced the
ship’scaptain in dangeroussea condition. However,
this method depends not only on the caption’s
decisionbutalso
onhislong‐standingexperience.In
this study, the involuntary speed reduction of the
vessel wasmodeled as to avoid slamming and deck
wetness phenomena for avoiding excessive motion.
The probability of slamming and deck wetness is
usually estimated by relative motion and relative
velocityatbow.Inordertoapply
theresultsofmodel
test at various wave heading angle for the optimal
ship,therelativeverticalmotionandrelativevertical
velocity at bow should be calculated from RAOs
motionofthemodeltestinwavesbased onARJM’s
method
4 SIMULATIONANDRESULTS
4.1 Simulation
Weather data sets are
updated every 12 hours and
obtainedfromSAS.Environmentalconditionsthatare
used in the simulation of this study include swell
direction,swellheight,windspeedandtemperature.
Thesampleweatherdataaregivenateachnodewith
gridsizeof0.1degreeinlongitudeand0.1degreein
latitude.
The
weather data at any particular time and
position of the ship are obtained by linear
interpolationofthesurroundingenvironmentaldata.
InordertoconfirmtheabilityoftheA*algorithmin
the OWRSU class, and investigate how the weather
conditions influence the optimal weather route, the
8600 TEU
container ship was selected for this
simulation.
Table 6 shows the route of container ship which
was simulated in this study. Two simulations were
performed to evaluate the effectiveness of the two
models that were suggested in this study for the
optimalshiproute.Incase1,modelofminimumthe
arrival time of the ship is applied and optimization
index is the shortest time under environmental
conditions. In case 2, model of minimum energy is
used,andtheoptimizationindexistheenergyofthe
vessel provided so that the vessel can keep the
constant speed under the influence of
the
environmentalconditions.
Table6.Simulationcondition
_______________________________________________
PortLocation
_______________________________________________
DepartureTokyo,Japan139
o
East,35
o
North.
Destination:SanFrancisco,US 122
o
West,38
o
North.
_______________________________________________
4.2 Results
Figure 17 shows the shipʹs speed comparisons
estimated by both the Great Circles (GC) and the
optimal weather route found by the A * algorithm
duringa shipʹsvoyage.Speedreductionofashipin
the GC’s route has significant difference with that
estimated by the
A* algorithm. Speed reduction is
verysmallincasesofshipfollowsthepathsuggested
by the A * algorithm, whereas speed reduction is
significantinthecasewhentheshipfollowsthepath
suggested by the GC. The reason is that the GC
cannotconsidertheweatherconditionfor
findingthe
optimalshiproute,leading tothe shipbeing ableto
gointodangerousareastoreduceitsapparentspeed.
The shipʹs arrival time can save 9.10% using the A*
algorithmlistedinTable7.A*suggestsshorterroutes,
fasterthanoneissuggestedbyGC.
Figure17.Comparisonofspeedandtimeincaseofconstant
powercondition