CASE STUDIES OF OCEAN TRANSPORTS USING THE SAFETRANS SIMULATOR

Cortis Cooper, Chevron Energy Technology Company Albert Aalbers, Marin

Cees Leenaars, Leenaars BV Stephen Quinn, U. K. Ministry of Defence

Kees-Jan Vermeulen, Jumbo Shipping Sjaak Scholten, Jumbo Shipping

James Vavasour, MathewsDaniel Roel Verwey, BigLift Shipping BV

SUMMARY

SafeTrans is a recently developed software package that calculates motions imposed by winds, waves, and currents on

large vessels, barges, heavy-lift vessels, or towed "wet bodies". Unlike other existing tools, SafeTrans incorporates all

the major factors affecting a transport including weather routing, complicated vessel response, weather forecast error,

human errors, mechanical failures, etc. This paper describes seven case studies ranging from traditional tug-barge and

self-propelled transports, optimization of LNG tanker and containerships routing, and response-based design of an

stationary FPSO (Floating Production Storage Offloading vessel). These case studies illustrate the versatility of

SafeTrans and show its ability to develop less conservative and more realistic criteria than traditional methods.

1 INTRODUCTION

SafeTrans was developed by a consortium of 32

companies involved in various aspects of the heavy-lift

and towing industry. The logic behind the computer

program is briefly described in [1]. SafeTrans has two

modes: the time-invariant Vessel Motion Climate (VMC)

module that uses wave and wind probabilities which is

described in [2], and a Monte Carlo Simulator (MCS)

that generates the time series of individual voyages.

The next section describes the SafeTrans’ MCS since it is

the principal tool used in this paper and it is not

documented in the readily available literature. This is

followed by seven case studies as summarized in Table 1.

The studies span a wide range of vessel and cargo types,

routes, transit speeds, and voyage durations. One case

considers a stationary FPSO. Despite the variations, a

number of common outcomes are apparent and are

summarized in the last section.

Table 1: Summary of case studies included in this paper

Title Route ∆T 1(days)

Spd 2(m/s)

LNG voyage duration

estimate

Australia-

California

20 10

Containership voyage

optimization

France-

New York

6 11.5

Submarine lift

feasibility

Russia 1 NA

Heavy-lift transport of

a crane

Korea-

Boston

30 7.2

Towed barge Dubai-

Gulf of

Mexico

60 3.5

Repeated cargo

transports

Germany-

Iceland

5 5

FPSO design W. Africa NA NA 1approximate voyage duration

2transit speed

2 SAFETRANS MCS DESCRIPTION

MCS mode gathers statistics from many voyages, each

starting on a randomly-selected date within a user-

specified range. Since the MCS considers time it can

include changes in heading and route much as a real-

world transport would. Aalbers and Leenaars [3] found

that the actual waves experienced during repeated

transports was typically 30% less than calculated from

traditional methods that don’t consider weather routing.

Figure 1 shows a flow chart of SafeTrans MCS as

applied to a single voyage for a heavy-lift transport. The

initial step (not shown) is for the user to enter the details

of the voyage including the ship and cargo geometry,

preferred routing, wind and wave weather routing

thresholds, number of MCS simulations, the desired load

monitoring sites (e.g. 6-degree of freedom acceleration at

selected points on the cargo), etc.. At this point the

program starts the first of many MCS voyages (see Block

1 in Figure 1). In Block 2, a Captain’s decision algorithm

consults the forecast weather database and if it shows

winds/waves that are above the user-specified thresholds

then the voyage is delayed (not started). This loop

continues until the forecast shows a few days clear

sailing along the user-specified route. More will be said

about the Captain’s Mimic shortly.

Once the ship has departed its port, it cruises along the

preferred route for three hours (Block 3) at a speed

dictated by the vessel power characteristics which

incorporate weather dependence, i.e. added resistance

due to wind, waves, and current. At the end of the three-

hour step, SafeTrans calculates the ship and cargo

displacements, velocities, and accelerations (Block 4)

based on the nowcast from the weather database and the

pre-calculated vessel-motion look-up tables in the form

of RAO’s and SDA’s. These calculated cargo motions

are archived into the voyage statistics database and can

be later used to develop statistics for cargo acceleration,

wave slam, etc.

Captain’s Mimic

Start Voyage

Clear Forecast

?

Delay

Ship motion database

No

Accident Database

IMDSS Waves winds current

Cruise for 3 hrs

Calculate ship motion

Rare accident?

Update voyage statistics

No

Yes

Yes Final Destination

?

Stop

Adjust

Yes

No

No

In Shelter

?

2

3

4

5

6

7

Figure 1: Flow chart showing the logic used in the

SafeTrans Monte Carlo Simulator (MCS) module.

The next step (Block 5) is to check to see if an accident

has occurred, e.g. engine failure. This is done in a

probabilistic sense by consulting an accident database

that includes many years of transport accident statistics

recorded by insurance underwriters, heavy-lift

transporters, and tow companies. The accident

probability reflects the risks for the transport type being

considered including specific hardware configurations

(e.g. number of engines, propellers, etc.) and qualitative

characteristics such as crew qualifications.

Table 2 summarizes the major accident types, when they

can occur, and their possible consequences. A few of

the accidents in this step (e.g. capsize) would end that

voyage. It is far more likely that the “accident” if it

occurs would result only in voyage delays.

If the voyage is not terminated by an accident nor

reached its final destination (Block 6) then it goes to the

top of the loop and starts the next three-hour cycle.

The most unique and complicated aspect of SafeTrans is

the “Captain’s Mimic” (yellow block in Figure 1). It

uses a probability matrix to weight the input factors in

the first column of Table 2 and derive the most likely

action shown in the second column. In essence the

“adjustment” referred to in Block 7 of Figure 1, can be

any of the actions in Column 2 of Table 3. The

probability matrix was derived by carefully surveying the

response of experienced captains when confronted with

various scenarios.

Table 2: Summary of accident types, when they occur,

and their possible consequences.

Initial Event Conditions Consequences

Capsize Extreme weather Total Loss

Collision Constant Sinking,

Drifting

Fire/Explosion Constant likelihood Damage,

Drifting

Foundering Extreme weather Total Loss

Grounding

(powered)

Proximity to shore Damage

Stability Weather/Constant Total Loss

Machinery

Failure

Constant Likelihood Drifting

Out of Control Extreme weather Slow Drifting

Structural Extreme weather Damage, Total

Loss

Sea Fastening Extreme Weather Damage, Total

Loss

Towline

Breakage

Shock-load / bottom

contact

Drifting

Towline

entangled

Shelter /

Manoeuvring

Drifting

Other Constant Likelihood Damage

Table 3: Possible captain’s actions and the factors upon

which those actions are based.

Input Factors Possible Actions

Forecast on route

Sheltering potential

Rerouting potential

Comfort situation

Delay risk

Crew quality

Value of consequences

Vulnerability

Capsize risk

Shipping green water

Tow line break risk

Tow line bottoming risk

Hurricane hit risk

Continue to destination

Seek shelter/head for open

sea

Change route

Change power/heading

Go to survival mode

Shorten tow line length

Reduce tow line tension

Apply Rendering

Avoid hurricane

Wait for weather (when in

shelter)

Another innovative aspect of SafeTrans is the wind and

wave database that includes 6-day forecasts. By

including the forecasts, SafeTrans can quantitatively include the impact of the poorer forecasts found in some

regions of the world, e.g. much of the Southern Ocean.

Winds and waves are based on a 10-yr nowcast/forecast

model from Oceanweather known as IMDSS.

IMDSS uses a 2.5° grid size which is far too large to

resolve tropical cyclones. In addition, a 10-yr database is

too short to resolve multidecadal variations in tropical

cyclones. To overcome these limitations, SafeTrans

overlays hurricane wind and wave fields using a simple

parametric model and the storm tracks from the NOAA

Climatic Atlas for 1972-1995. SafeTrans also includes

currents from the Ocean Drifter database. These are

seasonal and averaged over the 2.5° grid size on 8 main

directions (45° bins)

Ship response can be calculated using vessel-specific

RAO’s if available, or with a linearized strip-theory, 2-D

diffraction module in SafeTrans.

Individual modules of SafeTrans have been extensively

validated including the ship motion and wave/wind

forecasts. Overall, it has proven difficult to validate

SafeTrans because of the lack of comprehensive data

collected during repeated transits of the same route.

Aalbers et al. [1] do show some excellent comparisons

for individual voyages which were well instrumented.

3 TRANSIT TIME FOR LNG TANKERS

TRANSITING AUSTRALIA TO CALIFORNIA

A study was made to estimate the transit time of time-

critical cargo (LNG) from Western Australia to southern

California. Unexpected delays during transit can result

in stiff financial penalties imposed by LNG buyers.

Conversely, quicker than expected voyages will

underutilize expensive tankers. Since there was no prior

experience along the route using the proposed new-build

vessels, the SafeTrans computer simulation program was

used to calculate the voyage duration. Monte Carlo

(MC) mode was used because it captures the potentially

important influence of weather routing.

The route started on the NW Shelf of Australia, went

west-northwest between Papua New Guinea and

Queensland Australia and then proceeded along a great-

circle route to southern California The vessels had a

displacement of roughly 100,000 tonnes transiting at

roughly 10 m/s with a loaded draft of 11.5 m and length

of approximately 300 m. An average of several voyages

a week is expected. Ma and Cooper [4] described these

simulations in more detail and included results for

another route; Australia to Japan.

3.1 METHODOLOGY

The goal of the study was to estimate the statistics of the

voyage duration (e.g. mean, standard deviation) AND to

understand how potentially important parameters might

affect that duration. Factors considered included:

1. Weather avoidance - no avoidance, aggressive, and

moderate. For aggressive avoidance, Hs=3.7 m,

while for moderate avoidance, Hs=6.1 m. A case

with no-avoidance was also analyzed.

2. Seasonality - winter, spring, summer and fall (using

Northern Hemisphere convention).

3. Transit direction and loading condition - outgoing

(from Australia) or returning (toward Australia).

4. Weather forecast accuracy. SafeTrans allows the

Captain’s mimic to weight the importance of the

longer term weather forecast. A “low” means the

captain puts little faith into the longer term forecast

and will tend to make fewer route changes.

5. Engine Power Setting. For most cases the vessel is

assumed to be powered at 90% MCR (Maximum

Continuous Rating) plus a 20% sea margin (or 75%

MCR equivalent). At the time of our study,

SafeTrans would not allow the MCR setting to

change during simulations. This was unfortunate

because a real-world captain can and will increase

power during some voyages to avoid severe weather

and/or to make up time. An estimate of the effect of

variable MCR on the mean voyage time was made

by making a set of runs at a high MCR.

The MCS was set up to run 200 voyages in each season.

More voyages would have been preferred but at the time

SafeTrans only included a 4-yr global wave hindcast (25-

yr hurricane). With such a limited database, using more

than 200 voyages would mean individual voyages

become increasingly correlated as discussed in more

detail in [4].

3.2 RESULTS

3.2.1 Weather Avoidance

Figure 2 shows the voyage duration by season (northern

Hemisphere convention) for the three weather avoidance

scenarios. They assume a fully laden tanker departing

from Australia.

The figures suggest some dependence on the weather

strategy taken by the captain. If avoidance is aggressive

then the voyage is slowed considerably. During the

winter and fall when waves are largest, the delay

averages about 1 day but drops to less then ½ day by

summer (as compared to the no-weather avoidance case).

Recall that for the aggressive case, the captain is trying to

avoid waves exceeding Hs=3.7 m. The delays suggest

that meeting this threshold is a challenge especially

during the winter.

Figure 2 also shows the standard deviation (σ) by season

(vertical bars). This is an important measure of the

uncertainty of arrival time. Assuming the voyages are

normally distributed, roughly 80% of the voyages would

arrive within ±1σ. The figures show that aggressive

weather avoidance again has serious consequences in

terms of the ability to consistently make it to the

destination on time. The σ is about 1 day for the winter

and fall and nearly a ½ day for the spring and summer.

A σ=1 means that roughly 20% of the voyages will differ

by more then 4 days – a substantial variability to deal

with. More will be said about the implications of this

on shipping strategy in the final section.

18

19

20

21

22

0.5

Vo

ya

ge

du

rati

on

(d

ay

s)

Aggressive

None

M oderate

Winter Spring Summer FallWinter Spring Fall

Figure 2: Mean voyage duration by season for three

weather avoidance scenario. Vertical bars show one

standard deviation.

3.2.2 Seasonality

This issue is already discussed to a large degree in

previous subsections. To summarize, the voyage

duration is clearly affected by the season for the

aggressive weather avoidance case. There is no seasonal

effect seen for the other two weather routing cases. The

seasonal dependence is clearly caused by storms in the

Northern Pacific during the Northern Hemisphere winter.

3.2.3 Transit direction

“Returning” simulations were made for the fall season

for the most likely weather routing scenario (moderate

weather avoidance, Hs=6.1m). The mean duration for the

returning trip is 17.3 days. This is 1.6 (8.4%) days faster

than the mean for the equivalent outbound voyage (18.9

days). There is also a significant drop in variability – the

return is roughly 1/3 of the outbound.

There are two obvious causes for changes in voyage

duration. First, the draft of the vessel is roughly 2 m less

for the return (9.5 m vs. 11.5 m). This means the hull

resistance will generally be less so the ship’s speed will

be higher under the same engine power settings. Second,

a close look at the SafeTrans database for currents

reveals that there is a favourable current on the return trip

which averages 25 cm/s over the route. Thus the relative

speed of the water past the ship is 25 cm/s less on the

return trip. Conversely, during the outbound trip, the

ship must oppose the current. If the mean speed of the

vessel is 9.4 m/s for the outbound (Fall, moderate

avoidance case), it is 9.9 m/s for the returning. This

results in a 5.4% difference in voyage duration between

outbound and return legs. That is slightly less than the

8.4% difference calculated by SafeTrans but well within

the range of uncertainty of the various assumptions made

including the wave added resistance and the contribution

from ship draft.

3.2.4 Weather forecast accuracy

SafeTrans allows the user to specify how much

credibility the captain should give to the longer-term

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

0.5 1.5 2.5 3.5

Long-term Forecast Confidence

Sta

nd

ard

De

via

tio

n (

da

ys

)

Moderate

Aggressive

High Medium Low

Figure 3: Variability of the voyage duration during

winter as a function of the captain’s confidence in the

longer-term weather forecast.

forecast. If the factor is “high” then the longer-term

forecast (> 5 day) is given relatively high impact on the

captain’s decisions. Conversely if the user specifies a

“low” factor, the captain is to take the longer term

forecast less seriously.

Figure 3 shows the impact of this parameter on duration

variability for winter. It shows no effect for the moderate

weather avoidance case – a result consistent with the lack

of importance of weather routing for this case.

More interestingly, the figure shows a sharp increase in

the variability of the voyage duration when the longer-

term forecast is heavily weighted. One possible

explanation for this is that the accuracy of weather

forecasts is known to become unreliable after 7 days in

regions where they have been well studied such as the

North Atlantic. It is likely that along the Australia-U.S.

route the forecast deteriorates more rapidly because of

the well known Pacific weather “data void”. Hence, by

weighting the longer-term forecast too heavily, the

captain is making moves based on statistically unreliable

data that results in wasted miles traveled.

3.2.5 Engine Power Setting (MCR)

Additional simulations were made using MCR settings of

80, 85, 90, and 95% for the fall season. It was found that

there was essentially no change in the variability of the

voyage duration or the MPM Hs. It was also found that

the mean travel time dependence on MCR can be

explained by a nearly linear relationship between MCR

and ship speed. From this it is concluded that the captain

can reduce his voyage time by as much as 5% by

increasing power. This is roughly double the variance on

travel time for the moderate and no weather avoidance

cases likely to be used. That means that the captain has

the power to overcome weather delays for virtually all

runs and still meet the mean travel time.

3.3 DISCUSSION

The results above show that there are significant

penalties if a low weather threshold (Hs ≤ 3.7 m) is used

in routing. If a more moderate threshold of 6.1 m is used

then weather routing does not change the voyage

duration appreciably compared to simply ignoring the

weather (no avoidance). We conclude that aggressive

weather avoidance would have significant negative

impacts with little obvious benefits for ships of the size

being considered. On the other hand, moderate weather

routing (Hs=6.1 m) has little substantial impact on

voyage duration and would almost certainly enhance

safety and fuel economy.

Another interesting finding is that the captain should not

give much weight to the long-term (> 5 day) weather

forecasts. It is conjectured that the forecasts are so

uncertain that a captain who considers them will simply

waste time with unnecessary avoidance.

Finally, the sensitivity studies suggest that the captain

will be able to meet the mean voyage duration for

virtually all runs by increasing engine power when facing

adverse weather.

4 TRANSIT TIME FOR CONTAINER SHIPS

TRAVELLING ACROSS THE N. ATLANTIC

SafeTrans MCS simulations were used to optimize the

voyage duration and economic risks of a westbound

trans-Atlantic crossing of container ships (Le Havre,

France to New York). The ship had a length of roughly

200 m, beam of 32 m, and mean travel speed of 11.5 m/s.

4.1 METHODOLOGY

Several scenarios regarding seamanship were examined:

• None. No re-routing or other changes.

• Limited. No re-routing but changes in ship heading

and speed.

• Full. Weather routing and seamanship.

The key factor when specifying weather routing is the

wave height above which the captain tries to re-route. In

this study, 4 thresholds for Hs were tested: 8, 7, 6, and 4

m. The resulting simulations were analysed to obtain

voyage duration (90% bandwidth), fuel consumption, 10-

voyage return maximum wave, and risk of damage

(economic risk).

4.2 RESULTS

The results of the simulations are summarized in Table 4.

Most of the columns are self-explanatory with the help of

the footnotes. The last column is a measure of the

damage risk. Damage is expected to occur if a given

acceleration level is exceeded, leading to sea-fastening

loads above Ultimate Limit State (ULS).

A number of trade-offs are readily implied by the Table.

For example as the Hs threshold goes down, the voyage

duration increases but the level of risk and most probable

maximum Hs goes down. The optimal scenario will

depend upon the owners risk aversion. The table also

shows that the Hs threshold is always exceeded. This is

primarily because of forecast uncertainty and/or

‘unavoidable’ bad weather. Another reason is that re-

routing involves human decision making processes and

these are obviously less than perfect [5].

Table 4: Summary of simulation results.

Sea-

manship Hs

1(m)

∆T 2(hrs)

Fuel

(t) Hs

3(m)

Risk 4(%)

None NA 149 (+45/-13) 570 9.3 0.94

Ltd NA 150 (+48/-14) 576 9.3 0.94

Full 4 188 (+110/-40) 675 6.9 0.63

Full 6 155 (+61/-20) 590 7.9 0.78

Full 7 151 (+45/-15) 574 8.3 0.83

Full 8 150 (+42/-14) 572 8.7 0.86 1Target threshold Hs. “NA” means “Not Applicable”; no weather

routing was used in this scenario. 2∆T is the voyage duration. Within this column, the 1st number

is the mean, the 2nd number is the increment added to the mean to reach

the 95% nonexceedence probability, and the 3rd number is the increment for the 5% probability. 3Most probable maximum Hs experienced during the 500 voyages. 4Damage criterion (ULS) assumed at 0.5 g vertical acceleration at bow

Figure 4 shows histograms of the sea states encountered

during the 500 voyages. From these one can conclude

that weather routing reduces the occurrence of the high

sea states by about a factor three.

Figure 4: Distribution of MPM Hmax for weather routed

(a) and non-routed voyages (b)

An example of the effect of weather routing during one

of the 500 simulated voyages is shown Figures 5 and 6.

The route actually sailed in 2004 is shown by the solid

thin line while the weather-routed, simulated voyage of

the same departure day is shown by the dashed line.

Figure 7 illustrates how SafeTrans can be used to

quantify the consequences of weather routing. If for

example the total economic risk is valued at 100m€, the

cost per ton HFO at 250€ and the cost of delay at 10k€

per hour, an optimum can be derived by calculating the

cost function:

Total merit = Risk*(100m€+FuelUse)*250€+delay*10k€

and plotting this cost function against decreasing weather

routing criteria settings as shown in Fig 7. The optimum

lies at lowest total merit; in this case with weather

routing criterion between 6 and 7 m Hs.

5 HEAVYLIFT OF A SUBMARINE

The SafeTrans MCS was used to assess the probability of

obtaining a suitable weather window within a specified

timeframe in order to undertake the heavy lift of a

Russian Nuclear Fuelled Submarine of about 3000T

displacement. The operation started with a 1-hour tow of

the submarine from the storage area to the loading site,

then a 3-hour operation to load the submarine onto the

Tranself which is 34,000T DWT, followed by a 12-hour

period to install seafasteners. Table 5 summarizes the

pre-determined thresholds for the operations. Figure 8

shows the submarine aboard the Tranself.

Figure 5: Actual historic route (solid) and weather

routed simulation (dashed).

.

Figure 6: Waves encountered on weather-routed (Hs=7

m, solid) and actual voyages (dashed line).

€0

€50,000

€100,000

€150,000

€200,000

€250,000

€300,000

€350,000

€400,000

€450,000

All Deci

sions

4m

All Deci

sions

6m

All Deci

sions

7m

All Deci

sions

8m

No R

e-ro

utin

g

No A

ctio

ns

DELAY COST

FUEL COST

ECONOMIC RISK

TOTAL MERIT

Figure 7: SafeTrans results can be used to optimize the

voyage by accounting for risk, fuel and delays.

5.1 METHODOLOGY

A start and completion date of 20 and 31 Aug 07 as per

the Charter Party and random years and days within the

timeframe were selected. A set of simulations totalling

40 and 400 voyages were utilised, the lower figure being

used initially to assess the feasibility of the task until the

full scale analysis could be performed. The location of

the offshore operation, the hull definition of the heavy-

lift vessel including its resistance curve, current and wind

forces and wind coefficients as well as the wind

coefficients of the cargo, roll and pitch motion, amount

of fuel and number of personnel onboard and the

allowable criteria for the operation below were selected.

The vessel response parameters that were analyzed were

the roll angle and pitch velocity of the centre of gravity

of the submarine.

Figure 8: Russian sub shortly after lift aboard the

Transhelf.

Table 5: Allowable criteria for the operation

Task Duration

(hrs)

Max Hs

(m)

Wind

(m/s)

Tow 1 0.6 10.3

Loading 3 0.4 8.7

Sea-

Fastening

12 1.0 12.9

5.2 RESULTS

The results indicated that there was a high probability of

experiencing a suitable weather window with the

necessary characteristics particularly when used in

conjunction with the daily and 5-day weather forecast for

the area. More specifically the results showed that:

• The pitching of the center of gravity of the vessel and

cargo could range from 0º to 7.5º, with those values

below 2º occurring within the suitable weather

window for the task.

• The number of occurrences where the maximum

wave-height was less than or equal to 1.2 m was met

our criteria. Additionally the probability of Hs less

than 1 m was 0.3 while that below 0.5 m was 0.7.

• Despite differing distributions of suitable conditions

within the 10 year period analyzed there was

indication that suitable conditions would occur at least

once within the specified timeframe in each year.

• Weather conditions were more likely to be favourable

within the first 4½ days of the allocated period.

The environmental conditions experienced during the

operation were at par with those predicted by the

SafeTrans computer programme. On this occasion the

actual operation was carried out successfully within the

allowable criteria in the first 4 days of the 10-day given

timeframe without effecting the charter of the heavy-lift

vessel. This demonstrates the usefulness of the program

to provide an enhanced assessment of the viability of the

operation; due to a better understanding of the

probability of suitable weather criteria occurring within a

specific timeframe; thereby enabling a more informed

decision to be made about reliance on the operational

outcome and the commitment of funds.

6 TRANSPORT OF A CRANE FROM S. KOREA

TO US EAST COAST

SafeTrans was used to study the transport of a crane

between South Korea and the U. S. East Coast during the

Northern Hemisphere winter. Figure 9 shows the vessel

loaded with the crane. The ship was 110 m long, had a

beam of 20 m and was capable of 7.5 m/s in calm seas.

Two routes were considered. Both went through the

Panama Canal. The shortest route is a more northern one

that travels along a great circle through the North Pacific

passing just south of the Aleutians (48ºN). The second

route takes a more sheltered southern route passing near

Hawaii and never going further north than the latitude of

Soul (35ºN).

6.1 METHODOLOGY

Three methods were used to analyze the loads at the

crane. SafeTrans provided two of those; one based on

VMC and the other based on the MCS with weather

routing. The third method is based on DnV [6] and uses

a wave factor for the North Atlantic portion of the

transport with an exposure period of 30 days.

Figure 9: Side view of heavy-lift ship with crane (cargo).

The results for the three methods and two routes are

summarized in Table 6. MCS mode is based on 250

voyages. Figure 10 defines the various forces and

motions used in the table. The “z” axis is aligned with

the vertical axis of the center of gravity (CoG) of the

crane. The blue plane represents the ship’s deck with

the y-axis is aligned along the ship’s beam. SafeTrans

results are based on the expected value for the 10-voyage

extreme.

In addition to accelerations, the forces at deck level are

calculated with SafeTrans. With the DnV approach, the

phasing between the acceleration components is not

known so conservative assumptions would have to be

made (not done in this paper) in order to calculate the

design deck loads.

6.2 RESULTS

Table 6 shows the SafeTrans estimates are always less

than the DnV estimates with the exception of pitch on the

northern route.

The largest difference is found for the cross-beam

accelerations which are nearly a factor of two different.

The two SafeTrans approaches are quite consistent; the

�

Figure 10: Definition of responses used in Table 6.

Table 6: Summary of results (units are mks).

Northern Southern

Signal DNV VMC MCS DNV VMC MCS

Hs NA 10.6 10 9.0 6.6

Roll 25.5 25 24 25.5 24.1 17.9

Pitch 10.2 12 11 10.2 9.2 9.2

Ax 6.2 3.8 3.1 6.2 3.2 3.1

Ay 5.9 5.2 4.7 5.9 4.9 3.6

Az 4.9 4.4 3.3 4.9 3.4 3.1

FxA 1170 865 920 856

FxB 1090 898 960 930

FyR 2780 2497 2600 1942

FzA 3260 2974 3060 2270

FzB 6600 5836 6050 4535

FzC 3350 3022 3130 2389

VMC results being slightly higher than MCS. This is

predictable given the effect of weather routing (missing

in VMC; present in MCS).

SafeTrans MCS provides considerable insight into the

tradeoffs involved in taking the northern and southern

routes. Figures 11 and 12 show the probability

distributions for voyage duration. The most probable

duration for the northern route is about 2 days shorter

than the southern route, and the northern route shows

considerably less variability. On the other hand, Table 6

shows the northern route exposes the crane to

considerably higher motions. Obviously, the final choice

for the route would depend on how close allowable loads

and motions are to the calculated values (accounting for

inherent safety factors) , and to the owner’s risk aversion.

7 BARGE TRANSPORT OF A SPAR FROM

DUBAI TO GULF OF MEXICO

SafeTrans was used to study the transport of a large

production spar from Dubai (UAE) to the Gulf of Mexico

routed via the Suez Canal starting in October. The spar

was mounted on a large heavy-lift barge which was

towed by a tug as depicted in Figure 13.

Figure 11: Histogram of voyage duration from

SafeTrans MCS for the southern route.

Figure 12: Histogram of voyage duration from

SafeTrans MCS for the northern route.

7.1 METHODOLOGY

Three methods were used to estimate the 10-yr Hs during

the voyage: SafeTrans MCS and VMC modes and the

traditional 10-yr Hs [6]. The ship transit speed was

determined from MCS and VMC. For the more

traditional approach, the speed must be specified so two

values were used.

Figure 13: Front Runner spar loaded on the Zhong Ren

3 being pulled by a tug.

7.2 RESULTS

Table 7 summarizes the results. The 10-yr return-period

Hs from the VMC analysis correlates well with the

conventional 10-yr criteria based on the slower speed

while the Hs from the MCS analysis is considerably

lower. MCS runs were based on 100 voyages. The latter

is consistent with MCS’s ability to incorporate weather

routing and safehavens. It is important to remember that

MCS provides encountered wave values, meaning they

are an average of the waves encountered within

simulated voyages. Given the above conclusion on MCS

statistics, one can understand that, for weather routed

transports and tows, the most probable maximum value is

not the design value.

Table 7: Comparison of traditional method and

SafeTrans.

Method Transit Spd

(m/s)

10-yr Hs (m)

Traditional 1 3.1 8.0

Traditional 2 3.3 7.0

MCS 3.6 5.7

VMC 3.4 8.0

7.3 DISCUSSION

Both SafeTrans MCS and VMC indicated a vessel speed

of roughly 3.5 m/s, about 10% higher than the design

team’s collective intuition had suggested. Initially, the

team had considered 3.5 m/s but dismissed it as too

optimistic. The team were concerned that a spar had

never been towed on a barge and believed 3.1 m/s would

be more appropriate. However, SafeTrans results

prompted a reassessment. Subsequently, SafeTrans was

used to investigate the risks involved using a restricted

tow with a design sea state of 7 m. Restrictions were

imposed by at three hold points along the route where a

shipboard evaluation of the current weather condition

and forecast was performed by the captain before

proceeding forward. Specifically, the hold points were:

1. Jebel Ali yard just prior to entering the Indian Ocean.

2. Suez Canal just prior to entering the Mediterranean.

3. Gibraltar just prior to entering the Atlantic.

SafeTrans MCS was used to study the consequences of

using a threshold of Hs of 7 m to make a go/no-go

decision at each hold point. During the 100’s of MCS

voyages, Hs never exceeded 7 m.

With the insight gained from this further analysis, the

tow proceeded with the above strategy. In October 2003,

the Front Runner spar left Dubai loaded on the barge. It

arrived in Mississippi, USA without incident on

December. Daily reports from the vessel showed that at

no point during the voyage was the cargo exposed to seas

greater than the 7 m threshold.

8 REPEATED VOYAGES OF CARGO SHIPS

FROM WESTERN EUROPE TO ICELAND

Over the span of 1.5 years, 12 voyages were made to

transport large equipment from western Europe to new

smelter on Iceland. Mean speed for the large cargo

vessels varied between 4.5-6 m/s depending on the

vessel and the time of year. This translated to a voyage

duration ranging from four days in the summer to over

six days in the winter. Figure 14 shows a photo of the

vessel loaded with some of the modules.

8.1 METHODOLOGY

Two voyages were considered both departing from

Wilhelmshaven, Germany. The first voyage involved the

transport of 6 modules in December and the second

voyage transported a large 660 tons vacuum ship

unloader during June. Six safehavens were specified in

SafeTrans along the route.

Figure 14: Picture of cargo vessel loaded with smelter

modules.

SafeTrans’ MCS (200 runs) was used to determine the

acceleration level at predetermined locations. For the

first voyage the center of gravities of the six modules

were added manually and for the second voyage the

center of gravity of the large unloader was selected. Both

voyages were carried out with the same ship type and

with weather avoidance thresholds set to Hs 7 m and

wind speed 15 m/s.

In addition to the SafeTrans calculations the maximum

accelerations at the same locations to be expected

according to DNV rules [6, Part 3, Chapter 1, Section 4]

for ships were calculated as well. These rules are based

on a North Atlantic voyage during wintertime that give

values for the maximum acceleration level at a selected

spot based on parameters of the ship and the loading

condition.

8.2 RESULTS

Table 8 shows the results. For the December voyage only

2 modules are included: module 1, which is the most

forward upper-deck module, and module 2, also an

upper-deck module stowed near the ship’s longitudinal

CoG. It was interesting to discover that the DNV results

for the transversal and vertical acceleration for all cargo

locations are exceeded during the December voyage. In

Table 8: Comparison of voyage results from SafeTrans

and DNV All units are mks unless otherwise stated.

DNV

WINTER SUMMER

Hs 5.0 5.0

Wind Spd 15 15

G'M (m) 1.20 1.40

Time frame Dec June

Distance, speed

duration (hrs) - 130 89

mean distance - 1618 1589

mean speed - 4.6 6.1

Accelerations (m/s2)

x COG Module 3.1 2.2

y COG Crane 1 3.8 4.2

z COG Crane 1 3.1 3.7

x COG Crane 2 3.1 2.2

y COG Crane 2 3.8 3.9

z COG Crane 2 2.2 3.1

x COG Vacuum Ship 3.5 1.9

y COG Vacuum Ship 4.6 1.9

z COG Vacuum Ship 2.2 2.0

Motions (m and º )

x COG ship - 7.0 3.5

y COG ship - 6.2 3.6

z COG ship - 7.5 3.2

roll COG ship - 15.8 7.7

pitch COG ship - 8.3 4.8

yaw COG ship - 6.7 4.1

SafeTrans

contrast, SafeTrans results for the summer voyage are

well below those of the DNV method. Also note the

difference in mean voyage duration between the summer

and winter voyage.

8.3 DISCUSSION

The results suggest that a more thorough evaluation of a

particular voyage using a tool like SafeTrans can yield

significant differences from a standard engineering

method. Furthermore it suggests that the DnV method

may yield unconservative results in some cases.

9 FPSO DESIGN OFF W. AFRICA

The SafeTrans MCS was used to estimate probability

distributions for various response parameters for a FPSO

(Floating Production Storage Offloading vessel) turret-

moored in deep water about 500 km south of Ghana,

West Africa. Figure 15 shows a front view of the FSO.

9.1 METHODOLOGY

The RAO's of the FPSO were specified and then the

MCS was run for 10 years with a departure day every

three days. The voyage route was essentially “no

movement”. Weather routing was turned off.

The peak responses from the simulated time series were

extracted from the SafeTrans runs and fit with a Weibull

distribution.

9.2 RESULTS

Figure 16 shows an example of the peaks of vessel pitch

fitted to a Weibull distribution. Table 9 shows the design

values at various return intervals which were extracted

from the Weibull plots.

9.3 DISCUSSION

Historically, most offshore facilities have been designed

with a two-step process. First, the metocean specialist

derived the n-yr wind , wave, etc. Then the response

Figure 15: Front view of FPSO

Weibull graph

0.00E+00

5.00E-01

1.00E+00

1.50E+00

2.00E+00

2.50E+00

3.00E+00

3.50E+00

4.00E+00

0.1 1 10 100

Signal Amplitude

Pro

ba

bil

ity

of

exc

ee

de

nc

e

[L

n(-

Ln

(pro

ba

bil

ity

))]

motion pitch COG [MCSid = 0-121]

Figure 16: Weibull for Pitch

The results of the simulations are presented in Table 9.

Table 9: Summary of simulation results

Return Period Heave

(m)

Pitch/Roll

(deg)

1 year 5.10 2.4

10 year 5.75 3.0

100 year 6.40 3.5

Expert made a single run with a response model to

determine the presumed n-yr motions and loads. Of

course, the preferred approach is to determine the n-yr

response directly, and this is what SafeTrans

conveniently provides. However, a word of caution is in

order – the uncertainty of the longer return periods such

as 100-yrs or greater may be quite large in some parts of

the world given that SafeTrans only includes a 10-yr

wind-wave database (24-yr hurricane).

10 SUMMARY AND CONCLUSIONS

This paper describes six case studies of SafeTrans

applications ranging from tug-barge and self-propelled

transports to the design of a stationary FPSO. These

applications also cover a wide range of routes, durations,

and transit speeds.

One of the unique capabilities of the SafeTrans MCS is

its ability to mimic the weather-routing that is now

routinely employed by the shipping industry. Results

from the case studies consistently show that including

weather-routing will reduce the expected cargo/vessel

motions (or it’s proxy, Hs) below those calculated using

methods that don’t consider weather routing. The degree

of reduction depends greatly on the route, time of year,

distance to safe havens, and transport speed. For

example in one of our case studies, the barge transport of

a spar, the reduction in the 10-yr Hs was roughly 20%.

The value of including weather routing in the analysis is

not limited to reductions in motions. One can also use

SafeTrans to investigate the effect of different weather

routing restrictions on the risk of achieving a successful

transport or voyage. At least four of the case studies

illustrate this benefit: the LNG, containership, barge-

spar, and submarine transports. In these four cases,

SafeTrans was used to find an Hs threshold for weather

routing that was easily met with no substantial adverse

impacts on the transport’s duration. In the other case

study, the transport of cranes, SafeTrans provided the

basic inputs that could be used in a further benefit-cost

analysis to optimize the route.

It should also be remembered that SafeTrans MCS

provides the ability to do fairly complicated frequency-

domain motion analysis using time series of

simultaneous Hs, Tp, wind speed, etc. Such analysis will

account for joint statistics of these parameters and will

almost certainly be more accurate than traditional

estimates using probabilities. The differences in

calculated motions can be substantial, e.g. in the case of

the transport of cranes, the expected value for the cross-

beam acceleration was a factor of two less than a

traditional analysis would suggest. SafeTrans also

provides an interesting new tool to do a thorough

response-based design of stationary floating facilities like

FPSO's.

Overall, these case studies illustrate the versatility of

SafeTrans and demonstrate its ability to develop less

conservative and more comprehensive criteria than

traditional methods.

11 REFERENCES

1. Aalbers, et al., ‘SafeTrans: A new software system

for safer rig moves’ Proc. Jackup Symposium, Imperial

College, 2001.

2. Aalbers, et al., ‘Voyage acceleration climate: a new

method to come to realistic design values for ship

motions based on the full motion climate for a particular

transport’, 5th

Jack-up Symposium, London, 1995

3. Aalbers, A. B. and C. E. J. Leenaars, ‘Two years of

acceleration measurements on Dock Express heavy-lift

vessels compared with predicted values for several

design methods’, RINA Spring Meeting, London, 1987.

4. Ma, W. and C. Cooper, ‘Estimating the Voyage

Duration of Transoceanic LNG transports’, Offshore

Marine & Arctic Engr. Conf., 67398, 2005.

5. Aalbers and Van Dongen, Weather routing:

uncertainties and the effect of decision support systems,

Paper 0041, MOSS conference Singapore, 2008

6. DNV Rules for Classification of Ships, Part 3, Chapter

1, Section 4, January, 2005

12 AUTHORS’ BIOGRAPHIES

Albert B. Aalbers is a Senior Researcher at the

Maritime Research Institute Netherlands (MARIN)

where he manages the Maritime Innovation Programme

and is responsible for co-ordination of R&D initiatives in

the maritime construction and offshore service industry.

Cortis Cooper is a Fellow at Chevron Energy

Technology Company where he is responsible for

developing metocean criteria for Chevron’s world-wide

operations.

Stephen Quinn, OBE, is Assistant Director Mooring,

Towing & Plans within the Salvage and Marine

Operations Integrated Project Team, U. K. Ministry of

Defence (MoD). He is responsible for all MoD heavy-

lift, coastal and ocean towing and all strategic fleet

moorings worldwide.

Cees Leenaars, is managing director of Leenaars Marine

and Offshore Design. His previous positions included

R&D manager at Dockwise and engineering operations

manager at Dock Express Shipping.

Sjaak Scholten, is a Naval Architect and has worked for

Jumbo Shipping since 2002 as a Project Engineer where

he is responsible for the technical preparation of heavy-

lift transports and installation projects.

James Vavasour is a Naval Architect who has worked

for MatthewsDaniel since 2002 as a Lead Project

Engineer where he is responsible for the technical and

procedural review of heavy-lift transports and major

offshore installation projects in the Gulf of Mexico

Kees Jan Vermeulen is a Naval Architect who works as

a Senior Project Engineer for Jumbo Shipping where he

is responsible for the technical preparation of heavy-lift

transports and technical feasibility analyses of offshore

projects.

Roel Verwey is Manager of the Engineering Department

at BigLift Shipping BV where he is responsible for the

development of engineering methods and for the

technical preparations of heavy lift transports.