Elements of risk analysis for collision and grounding of a RoRo passenger ferry

Marine Structures 15 (2002) 461–474

Elements of risk analysis for collision andgrounding of a RoRo passenger ferry

Sven Ottoa, Preben T. Pedersenb, Manolis Samuelidesc,Pierre C. Samesd,*

aGermanischer Lloyd Offshore and Industrial Services, Johannisbollwerk 6–8, D-20459 Hamburg, GermanybDepartment of Mechanical Engineering, Technical University of Denmark, Building 101E, DK-2800 Kgs.

Lyngby, DenmarkcDepartment of Naval Architecture and Marine Engineering, National Technical University of Athens,

9 Heroon Polytechniou, GR-15773 Zografou, Athens, GreecedResearch and Advanced Engineering Division, Germanischer Lloyd, Vorsetzen 35, D-20459 Hamburg,

Germany

Received 15 April 2001; accepted 12 December 2001

Abstract

Newly developed software was applied to study the effects of damages due to collision and

grounding. The annual risk of collision and grounding was computed for an example RoRo

passenger ferry. Collision frequency was evaluated for a specified route taking into account

traffic data. Grounding frequency was calculated for an artificial obstacle located close to the

traffic route. The consequences of collision and grounding scenarios were estimated by

introducing damage criteria that link the calculated distribution of damage size and damage

location to monetary units. Loss of human life and reputation was not considered. It was

shown that the main part of the calculated annual risk is caused by capsize of the vessel after

severe damage. r 2002 Elsevier Science Ltd. All rights reserved.

Keywords: Collision; Grounding; Risk analysis; RoRo; Ferry; Passenger ship

1. Introduction

Risk assessment in the maritime industry (slowly) follows the routes that otherindustries have gone before, e.g., the nuclear industry, the hazardous industry and

*Corresponding author. Tel.: +49-40-36149-113; fax: +49-40-361-49-7320.

E-mail address: [email protected] (P.C. Sames).

0951-8339/02/$ - see front matter r 2002 Elsevier Science Ltd. All rights reserved.

PII: S 0 9 5 1 - 8 3 3 9 ( 0 2 ) 0 0 0 1 4 - X

the offshore industry. In shipping, Formal Safety Assessment started in 1993 withthe United Kingdom proposal to IMO. The IMO adapted formal safety assessment(FSA) to use it in the rule making process. Like other risk assessment methods, it canalso be applied in design and operation. Few risk assessments were published latelyand it seems that more experience must be gathered before the usefulness of riskassessment will become obvious. The objective of the European research projectDEXTREMEL [1] was to contribute to this base of experience. The thematicnetwork SAFER EURORO [2] was initiated to monitor research projects related toRoRo passenger ferry safety and to promote the idea of ‘‘Design for Safety’’ that isto integrate safety aspects into the (early) design phase. Research related to riskassessment was also monitored by the concerted action FSEA [3] and the effort isongoing within the thematic network THEMES [4].Within the project DEXTREMEL, four hazards were identified: (1) collision, (2)

grounding, (3) bow door failure, and (4) front bulkhead of superstructure failure.Other hazards like fire were not investigated, nor were fire, loss of human life andenvironmental pollution taking into account as possible consequences. Here, wefocus on a method that enables the estimation of the collision and grounding risk ina quantitative manner taking into account technical properties of ships and the shiptraffic in a certain sea area. The risk for a sample RoRo passenger vessel will becalculated as the frequency when undesirable events occur multiplied with theconsequences resulting from these events, and the risk is finally expressed inmonetary units.

2. Scenario

2.1. Technical properties of the example ship

The example ship is a fast conventional RoRo passenger ferry. The maindimensions of the reference ship are listed in Table 1. The ship was designed as atwo-compartment vessel to meet the requirements made in SOLAS [5]. The SOLASconvention, released by the International Maritime Organization, defines the lengthDL and depth DD of damages that the ship can suffer without the loss of stability.

Table 1

Main dimensions of the example RoRo passenger ferry

Ship parameter Value

Length between perpendiculars Lpp (m) 173.00

Breadth B (m) 26.00

Depth D (m) 15.70

Draught d (m) 6.50

Block coefficient cB 0.56

Displacement D (tons) 16,073

Service speed (kn) 27

S. Otto et al. / Marine Structures 15 (2002) 461–474462

Applying these SOLAS requirements, given in Eqs. (1) and (2), to the reference shipgive the maximum damage length DL;max ¼ 16:38 (m) and the maximum damagedepth DD;max ¼ 5:2 (m) that the ship can suffer. The calculation of damages requiredthe analysis of internal mechanics that describe the response of the ship structure dueto the loads induced by collision and grounding. Fig. 1 shows the midship section ofthe example ship that was used to compute the structural response.

DL;SOLAS ¼ minf3þ 0:03Lpp; 11g ðmÞ; ð1Þ

DD;SOLAS ¼B

5ðmÞ: ð2Þ

2.2. Traffic conditions

The traffic conditions are only relevant for collision scenarios. The presentedmethod is able to take into account arbitrary traffic conditions. The traffic is dividedinto traffic streams representing traffic lanes that group ships by type. Thus,statistical data are necessary comprising number and kind of ships that operate inthe considered sea area. As an example route we selected the existing route between

Fig. 1. Midship section of the example ship.

S. Otto et al. / Marine Structures 15 (2002) 461–474 463

Cadiz and the Canary Islands, see Fig. 2. The route length is 700 nm and the voyagetime is assumed 25 h per trip. We assumed nv ¼ 240 voyages per year.

2.3. Environmental conditions

The danger of collision and grounding is influenced by the environmentalconditions in the considered sea area. For example, the visibility that depends onrain and fog must be taken into account. The presented method includes these effectsusing the so-called causation factors computed by Bayesian Networks [6]. It isgenerally accepted that most collisions between ships can be attributed to humanfailure. In the present analysis it is assumed that the machinery and the steering gearare functioning. Therefore, an analysis of collision rates must be based on a study ofthe navigator’s role in resolving critical situations. We selected a Bayesian Networkto describe the tasks of the Officer of the Watch (OOW). The network is a graphicalrepresentation of influence factors (nodes) and explicitly reveals their probabilisticdependence and the flow of information between the nodes. Table 2 lists the nodes ofthe network and summarizes the principal source of input to model the behavior ofeach node.

3. Risk due to collision

3.1. Assessment of collision frequencies

The presented method is based on probabilistic calculations published in Pedersen[7]. The traffic in the considered sea area is subdivided into traffic streams. Eachtraffic stream is characterized by the number, type and size of ships. The mean valueand the standard deviation define a Gaussian distribution that is assumed torepresent the distribution of ships across the shipping lane. Three collision scenarioswere taken into account:

Fig. 2. Example route.


Crossing waterways. Crossing routes are defined to have one-way traffic only, seeFig. 3. Thus, if two-way traffic exists in the crossing route, the route must beincluded twice, one for each direction of the traffic. This strategy is adopted to allowfor different traffic distribution in the two directions.

Intersecting waterways. Another kind of collision occurs at bends where twostraight route segments intersects, see Fig. 4. At the intersection a ship can become acollision candidate if the course is not changed at the intersection. This probability ofomission P0 is taken as 0.01.

Table 2

Nodes of Bayesian network to determine causation factor

Node Statistics Math. Subjective Node Statistics Mathe. Subjective

Weather O Time for visual OVisibility O (O) Time for radar OObject type O Other alarms (O) ODaylight O OOW training OVisual distance O Stress level ORadar status O OOW task ORadar distance O Alarm transfer O (O)

Vessel speed O Looking frequency OObject relative speed O (O) Radar frequency OVisual time O OOW visual ORadar time O OOW radar OTraffic intensity O OOW acts OManoeuvring time O

Fig. 3. Crossing waterways.


Parallel waterways. The third kind of collision scenario is a head-on inducedcollision due to two way traffic in the straight waterway segments, see Fig. 5.We used statistical data from Spanish port statistics to generate the traffic data for

this analysis. According to these statistics the total annual traffic to the harbors inTenerife and in Las Palmas is 8647 and 8012 ships per year, respectively. The shiptraffic out of and into the Gibraltar Straight was 11,659 ships per year in 1987. Thisinformation and the composition of the ship traffic between Cadiz and the CanaryIslands and the Gibraltar Straight according to vessel type and size was taken fromthe traffic database COAST [8]. The number of collision candidates related to head-on, intersections, and crossing situations is calculated for each segment of the routeand for each vessel type and vessel size. The probabilities of collision are thenestimated by multiplication with causation factors. The causation factors representthe probability that actions to prevent collisions like the change of course or speedreduction are insufficient or not taken, Table 3. The number of collisions was

Fig. 4. Typical intersecting waterways.

Fig. 5. Typical parallel waterways.

Table 3

Computed causation factors with respect to collision types

Collision type Causation factor

Head on 4.9E-05

Intersection 1.3E-04

Crossing 1.3E-04


calculated by multiplying the number of collision candidates with the relatedcausation factor for each collision scenario. The summation of all collision scenariosyielded the total number of collisions per year or the annual collision frequency, seeTable 4. The frequency of collision fcoll contains two cases. In the first case theexample ship is the struck ship where large damages can occur at each ship location.In the second case, where the example ship is the striking ship, only damages in thebow region are expected that should not yield to severe damage. The probability thatthe example ship is the struck ship was taken as Pstruck ¼ 0:4985:

3.2. Assessment of collision consequences

For each individual collision scenario, the analysis of the external dynamics andthe internal mechanics must be performed which can be treated as independent.Therefore, a simplified method was developed and validated with model tests andfinite element computations. The external dynamics deal with the energy released forcrushing of the involved ship structures and the impact impulse of the collision byanalyzing the rigid body motions of the colliding ships taking into account the effectof the surrounding water. The procedure was published by Pedersen and Zhang [9].The internal mechanics deal with the structural response and damage caused by thereleased energy and its dissipation by crushing of ship structures during the collision.The applied procedure was published by Simonsen [10] and Zhang [11]. Bothprocedures were included in the computer program ‘‘Collide’’. The results were theprobability density functions of the length PDLðdLÞ; depth PDDðdDÞ; height PDH ðdH Þof damages that result from the collision impact, see Fig. 6 that shows thedistribution of the damage length as an example. Using these damage densityfunctions a joint density function Dcoll of damages was calculated with Eq. (3) underthe assumption that the damage parameters were not correlated to each other

Dcoll ¼ PDLðdLÞPDDðdDÞPDH ðdH Þ: ð3Þ

3.3. Calculation of collision risk

The evaluation of the collision-induced risk requires the rating of the damageswith respect to costs (monetary units). We derived our criteria based on currentSOLAS requirements [5] as a simple and easy to implement measure.

Table 4

Computed annual frequencies for different kinds of collision

Collision type Annual collision frequency fcoll

Head on 3.90E-02

Intersection 1.50E-05

Crossing 3.84E-03

Total 4.29E-02


Probability and costs due to capsizing. It was assumed that the ship capsizes if thedamage size simultaneously exceeds the SOLAS limits DL;max and DD;max: Theprobability that the ship capsizes can be computed by integrating the joint densityfunction Dcoll using Eq. (4). With respect to the example of RoRo passenger ferrythis probability yields Pcap ¼ 0:0419 per collision. The resulting costs of this scenariois the new building price of the ship, Cship ¼ 115 million (EUR). The expected costsof collision due to capsizing is the product of the probability of capsizing and thecosts for the ship Ccap ¼ 4:82 million (EUR/collision)

Pcap ¼ Pstruck

ZN

dL;max

ZN

dD;max

ZN

0

Dcoll ddL ddD ddH ; ð4Þ

Ccap ¼ PcapCship: ð5Þ

Probability and costs due to repair. If the damage does not exceed the SOLASlimits DL;max and DD;max costs only result from repair of the damage. The probabilityof this case was 0.958 according to Eq. (6). Repair costs depend on damage location,damage size, repair yard, etc., and can be estimated using the amount of (ruptured)steel that has to be repaired. The price of a typical repair job is assumed as crep;1 ¼6000 (EUR/t) with respect to the mass of steel that has to be repaired. This priceincludes the full repair process i.e., cutting–building–fitting of the damaged area. Themass of ruptured steel was calculated with respect to the damage size and the relatedprobability as well as the density of steel rFe ¼ 7:85 (t/m3) and the ratio of the shipsteel volume Vsteel and ship volume Vship: For the example RoRo passenger ferry, theheight was taken to be H ¼ 15:7 (m), the block coefficient of the submerged ship,cB1 ¼ 0:56 and the block coefficient of the ship above the waterline, cB2 ¼ 0:8: Theapplication of Eq. (7) yields a ship volume of Vship ¼ 49; 700 (m3). We neglected thesuperstructure for this estimate. The ship steel volume VSteel is the ratio of the lightship weight mSteel (excluding non-load carrying parts, e.g., machinery, propeller, etc.)and the steel density rFe: The ship steel volume of the vessel is calculated with Eq. (8)

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0 - 1

.5

1.5

- 3.0

3.0

- 4.5

4.5

- 6.0

6.0

- 7.5

7.5

- 9.0

9.0

- 10.

5

10.5

- 12

.0

12.0

- 13

.5

13.5

- 15

.0

15.0

- 16

.5

16.5

- 18

.0

18.5

- 20

.0

20.0

- 21

.5

damage length DL [m]

prob

abili

ty o

f occ

urra

nce

Fig. 6. Damage length distribution of the example of RoRo passenger ferry.


that yields Vsteel ¼ 1105 (m3).

Prep ¼ 1� Pcap; ð6Þ

Vship ¼ LppBðdcB1 þ ðH � dÞcB2Þ; ð7Þ

VSteel ¼mSteel

rSteel: ð8Þ

The application of (9), below, gives the expected mass of steel EðmrupÞ that will beruptured per collision in the case where the damage does not exceed the SOLAScriteria. It is further assumed that the amount of steel per unit volume is constant.For the example of RoRo passenger ferry, we obtained EðmrupÞ ¼ 1:65 (t/collision)based on an expected damage volume of 9.46 (m3/collision). With respect to thevoyage to the shipyard, costs of crep;2 ¼ 50; 000 (EUR/repair) were assumed. Thesecosts include fuel consumption, crew payment and possible support by tugs. Usingthe probability that the ship does not capsize, expected mass of ruptured steelEðmrupÞ and the repair costs per ton of steel crep;1 as well as the costs for the voyage tothe ship yard crep;2 the total costs for an expected average ship repair were Crep ¼57; 380 (EUR/collision),

EðmrupÞ ¼ rFeVSteel

VShip

Z dL;max

0

Z dD;max

0

ZN

0

dLdDdHDcoll ddL ddD ddH ; ð9Þ

Crep ¼ Prepðcrep;1E½mrup þ crep;2Þ: ð10Þ

Although the probability for capsizing is much smaller than the case of repair, theexpected costs for the total loss of the ship is significantly higher than the expectedcosts for ship repair. The annual risk for ship–ship collisions was computed bymultiplying the expected costs per collision with the annual frequency of collisions,see Eq. (11). Considering the example of RoRo passenger ferry, the annual risk dueto collision was Qcoll ¼ 0:209 million (EUR/year).

Qcoll ¼ fcollðCcap þ CrepÞ: ð11Þ

4. Risk due to grounding

The risk calculation for grounding scenarios is again subdivided into two parts. Inthe first part, the frequency of a possible grounding event will be calculated. In thesecond part, the consequences are expressed as repair or new building costs. Thepresented procedure is only applicable to hard-groundings like, e.g., a collision withrocks or coral-reefs. Such groundings induce high local loads in the ship structurethat can result in large damages in the bottom area of the ships.


4.1. Assessment of grounding frequencies

Computation of grounding probability followed a method that was presented byPedersen [7]. Often groundings are caused by the failure of the main engine or therudder engine. Then the crew is unable to avoid the obstacle and the ship groundsdue to drift motions of wind, wave and current forces. Here, we focus on agrounding scenario that is shown in Fig. 7. The distribution of routes over the trafficlane was assumed to be normal distributed with a mean value of 900 (m) and astandard deviation of 900 (m). In a distance of 1800 (m) from the center of the trafficlane an obstacle (reef) with a diameter of 300 (m) was located. Integration of routeprobability distributions that overlapped with the obstacle yielded the probabilityper voyage that the vessels grounds if no aversive maneuvers will be done. In theconsidered example these values are PG1 ¼ 0:132 and PG2 ¼ 0:0182 for route nos. 1and 2, respectively. Causation factors were introduced to reflect the influence of thecrew to avoid the grounding by changing the course. The causation factor Pcg ¼1:59E � 04 was taken from Pedersen [7]. Assuming nv ¼ 240 voyages per year anannual frequency of grounding fG ¼ 5:78E � 03 was computed,

fG ¼ nvPcgðPG1 þ PG2Þ: ð12Þ

4.2. Assessment of grounding consequences

Damage size in case of grounding is mainly influenced by ship speed. We selected aprobability density function for the ship speed that corresponded to operation inopen waters. The chosen beta distributed density function is presented in Fig. 8. Ofcourse, a different shape of the distribution would result if we select coastal wateroperations. Within the project DEXTREMEL, various methods were integrated intoa computer program to compute the damage size of a grounding event in relation tothe ship speed or kinetic energy. The program is limited to grounding scenarioswhere damages are located in the area of the bottom and double bottom of the ship.The damage size varies depending on the calculation method, the location of thedamage and the geometry of the obstacle. Fig. 9 shows the average damage sizes ofthe reference ship grounded on the obstacle using a method by Minorsky [12]. Thetop of the obstacle (reef) is located 5.0 (m) below still water level. With respect to aship draft of T ¼ 6:5 (m) there is a possible damage height of up to 1.5 (m). For eachship speed, a damage volume was computed. Thus, a joint density function DGr ofthe damage parameter damage length DL; damage depth DD and damage height DH

was constructed assuming that the damage parameters were not correlated to eachother.

4.3. Calculation of grounding risk

Similar to the collision case, a damage stability criterion was introduced to rate theseverity of the damages. If the damage exceeds certain limits the ship was consideredto capsize. At present no rules or guidelines exist for RoRo vessels with respect to


0.00

0.02

0.04

0.06

0.08

0.10

0 5 10 15 20 25 30 35ship speed [Kn]

prob

abili

ty

Fig. 8. Probability distribution for RoRo ferry velocity in open waters.

0

2

4

6

8

10

12

0 10 20 30ship speed [Kn]

dept

h an

d he

ight

of d

amag

e [m

]

020406080100120140160180200

dam

age

leng

th [m

]

damage depthdamage heightdamage length

Fig. 9. Damage sizes depending on the ship speed.

routedistribution 2

300 m900 m

1800 m routedistribution 1

obstacle

Center of theTraffic Lane

Fig. 7. Sample grounding scenario.


groundings. Therefore, we used the ‘‘International Convention for the Prevention ofPollution from Ships’’ MARPOL [13] that defines damage limitations for tankers.Eqs. (13)–(15) show the dependency of the damage criteria on the ship dimensions.Applied to our RoRo passenger ferry the criteria yielded dL;max ¼ 69:2 (m), dD;max ¼8:67 (m) and dH;max ¼ 1:48 (m).

DL;MARPOLþ ¼ 0:4Lpp ðmÞ; ð13Þ

DD;MARPOL ¼ B=3 ðmÞ; ð14Þ

DH;MARPOL ¼ height of the double bottom ðmÞ: ð15Þ

Probability and costs due to capsizing. Considering one grounding event, theprobability of capsizing can be calculated with (16). For the example of RoRopassenger ferry, (16) gives a value of Pcap ¼ 0:5: Like in the collision scenario, thecosts of the lost ship was assumed as Cship ¼ 115 million (EUR). The expected costsper grounding in case of capsizing is computed with Eq. (17), Ccap ¼ 57:5 million(EUR/collision).

Pcap ¼Z

N

dL;max

ZN

dD;max

ZN

dH ;max

DGr ddL ddD ddH ; ð16Þ

Ccap ¼ PcapCship: ð17Þ

Probability and costs due to repair. The probability that the ship does not capsizeand that it can be repaired is Prep ¼ 0:5; see Eq. (6). The application of Eq. (18) givesthe expected mass of steel that ruptured per grounding event if the ship does notcapsize. For the example ship, Eq. (18) gives EðmrupÞ ¼ 136 (t). Multiplying EðmrupÞwith the repair costs per ton of steel c2 ¼ 6000 (EUR) and adding the costs c3 ¼50; 000 (EUR/repair) for the voyage to the ship yard yielded the costs of repair dueto grounding damages (Crep ¼ 867; 000 (EUR/grounding)) according to Eq. (10).The annual risk QGr ¼ 0:169 million (EUR/year) was then calculated multiplying theannual frequency fG of grounding events with the expected costs from capsizing andship repair according to

EðmrupÞ ¼ rFeVSteel

VShip

Z dL;max

0

Z dD;max

0

Z dH ;max

0

dldddhDðdl; dd ; dhÞddl ddd ddh; ð18Þ

QGr ¼ fGðCcap þ CrepÞ: ð19Þ

5. Summary and conclusions

The annual risk for collision and grounding scenarios was computed andexpressed in terms of monetary units. Based on the SOLAS and MARPOLconventions damage criteria were introduced to rate the seriousness of consequences.The method was applied to an example ship that sails on a route between Cadiz andTenerife. Main part of the risk for both collision and grounding was due to the


capsizing of the ship. Our assumption of a reef close to the traffic lane and the highship speed resulted in a probability of 50 (%) that the vessel will capsize in case ofgrounding. However, resulting annual risk for collision was higher than the annualrisk for grounding events due to higher collision frequency, see Table 5. Weemphasize that our results were sensitive to small changes of the damage criteria.Based on our investigations, we conclude that the applied methods were capable to

predict annual risks for simplified collision and grounding scenarios. We recommendto develop a computational method that has to be incorporated into the presentedprobabilistic framework to accurately predict the ultimate floating position afterdamage. To rationally predict grounding probability, seabed topology along theroute has to be gathered.

Acknowledgements

The research work presented was funded by the European Commission under theBriteEuRam programme, contract BRPR-CT97-0513. Opinions expressed herein arethose of the authors. We thank the partners of DEXTREMEL (GermanischerLloyd, Technical University of Denmark, MARIN, National Technical Universityof Athens, Sirehna, University of Newcastle, IZAR) for their kind permission topublish this work.

References

[1] DEXTREMEL: Design for Structural Safety under Extreme Loads, contract BRPR-CT97-0513,

1997.

[2] SAFER EURORO: Design for Safety: An Integrated Approach to Safe European RoRo Ferry

Design, Thematic Network, ERB BRRT-CT97-5015, 1997.

[3] FSEA: Formal Approaches to Risk Assessment for Seaborne Transport in European Waters,

Concerted Action WA-96-CA1155, 1996.

[4] THEMES: Safety Assessment in Waterborne Transport, Thematic Network, 2000-TN.11080, 2000.

[5] SOLAS: International Convention for the Safety of Life at Sea (SOLAS), 1974.

[6] Jensen FV. An introduction to Bayesian networks. UCL Press, 1996.

Table 5

Annual risk due to collision and grounding

Collision Grounding

PCap 0.0419 0.5

CCap (EUR) 4.82 million 57.5 million

PRep 0.958 0.5

CRep (EUR) 57,380 867,000

Frequency (1/Year) 0.042 0.00578

Annual risk (EUR) 205,000 169,000


[7] Pedersen PT. Collision, grounding mechanics. Proceedings of WEMT ‘95. Copenhagen: The Danish

Society of Naval Architecture and Marine Engineering. 1995.

[8] COAST database, Dovre Safetec Ltd., Development of UKCS Vessel Traffic Database for DOT/

UKOOA/HSE, Report No. DST-95-CR-1110-02, 1996.

[9] Pedersen PT, Zhang S. On impact mechanics in ship collisions. Mar Struct 1998;11:429–49.

[10] Simonsen BC. Ship grounding on rock: I—theory. Mar Struct 1997;10:519–62.

[11] Zhang S. The mechanics of ship collisions. Ph.D. dissertation, Department of Naval Architecture and

Offshore Engineering, Technical University of Denmark, 1999.

[12] Minorsky VU. An analysis of ship collision with reference to protection of nuclear power ships.

J Ship Res 1959;3(2):1–4.

[13] MARPOL: International Convention for the Prevention of Pollution from Ships, 1973/1978.


Elements of risk analysis for collision and grounding of a RoRo passenger ferry

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