Performance Assessment of Davit-Launched · PDF fileThe Human Health Status calculation follows a step-by-step approach for both the human and the hardware as ... davit-launched lifeboat

Proceedings of the ASME 27th International Conference on Offshore Mechanics and Arctic Engineering OMAE2008

June 15-20, 2008, Estoril, Portugal

OMAE2008-57734

PERFORMANCE ASSESSMENT OF DAVIT-LAUNCHED LIFEBOAT

Laurent Prat Bureau Veritas

Paris La Défense, France

Leo de Vries Alex W. Vredeveldt

TNO Delft, The Netherlands

Omar Khattab Ship Stability Research Centre

Glasgow, UK

Jean-Jacques Maisonneuve SIREHNA

Nantes, France

Thomas Boekholt Fassmer

Berne/Motzen, Germany

Ole Andersen Viking

Esbjerg, Denmark

David Cummings Carnival plc London, UK

Jan Block MARIN

Wageningen, The Netherlands

ABSTRACT In response to the recent changes to SOLAS, which further encourage the alternative design of life-saving appliances, the European Union has funded a Framework Programme 6 (FP6) project called SAFECRAFTS that was initiated by the Netherlands Research Organisation TNO. The aims of the project are two fold: to develop a methodology for assessing the performance of life saving systems (made up of life saving appliances or LSA); and to develop novel concepts. This paper focuses on the first objective and presents the results for conventional davit-launched lifeboats. The proposed performance indicator is the Success Rate of the evacuation process, which compares the final Human Health Status (the number of persons in good health, injured or deceased at the end of the process) with the initial Human Health Status (number of persons in good health onboard the mother ship). The Human Health Status calculation follows a step-by-step approach for both the human and the hardware as they progress along an obstacle course, which represents the evacuation sequence specific to the design. Associated to each obstacle is a transformation function that characterises the degradation of the Human Health Status. The determination of the transformation functions is based on first principle methods, risk analysis methods, and human factor methods some of which are inspired by the automotive industry. A scenario-based approach is applied to account for increasingly severe environmental and damaged ship conditions. In addition, the systems performance is represented along the evacuation and rescue route, so that it is possible to identify and quantify the contribution of individual obstacles to the overall degradation. This is essential to select the critical areas for improvement and support the development of innovative designs. Finally, the paper advocates that the set of scenarios and their associated Success Rates represent performance criteria for LSA which can be used for approving alternative designs and arrangements.

- 1 -

1. GENERAL

1.1. Context In December 2006, the Maritime Safety Committee of IMO adopted a new regulation of the SOLAS convention [1] which provides for “Alternative design and arrangements for life-saving appliances”. It allows operators and manufacturers to equip a ship with LSA that deviate from the prescribed requirements. This demands specific engineering studies and comprehensive evaluations to demonstrate their “equivalency” with prescribed designs. In view of the growing market for large cruise ships, the new regulation creates an opportunity for innovation in the field of survival crafts. This also paves the way for an in-depth investigation of the performance of current LSA.

1.2. Challenges and Objectives To demonstrate the equivalent performance of novel concepts with prescriptive designs, the methodology should include a quantitative assessment in line with IMO guidelines [3]. In particular, it is needed to apply the methodology to at least one existing conventional design in order to derive the baseline performance or the acceptance criteria against which alternative designs are to be assessed. In the case of LSA, novel concepts are not precisely novel features because the function (saving lives) is not changed. However, a novel concept or an alternative design may largely deviate from the prescriptive requirements, so that a global assessment is required to effectively address the principle of equivalence. Thus, the methodology aims to derive the global performance of LSA using a functional perspective that is not design specific. In addition, input calculation data are mostly supported by first-principle models. This paper presents the basics of the assessment methodology as well as the assessment results for a generic conventional davit-launched lifeboat.

Copyright © ASME 2008

2. METHODOLOGY This methodology was developed by Bureau Veritas and TNO in the course of the SAFECRAFTS project [2].

2.1. Conceptual Background Life-Saving System: An evacuation and rescue system is more than just one category of LSA. Two or more different types of LSA can be fitted on a ship. The capacity of each LSA unit, the location on the ship, and the means of transfer from the survival craft to the rescue ship are critical to characterise a Life Saving System (LSS). The proposed approach focuses on the system as a whole, because we deem it necessary to tackle the rescue of the entire population being evacuated. The global performance of a LSS is also the level of analysis that allows objective comparison between conventional systems and novel concepts. Rescue Route: It is the sequence of actions required to evacuate safely the entire population from the embarkation station to a safe haven. It involves the passengers, the crew and the hardware components of the LSS. Each LSS is associated with a specific rescue route. Conventional existing systems have similar rescue routes but novel concepts can differ radically in this respect. The rescue route elements (deployment, boarding, etc) that are identified for each LSA type can be grouped together within three generic phases: (1) Leaving the vessel; (2) Surviving at sea; (3) Being rescued from the survival craft. Obstacles: As the hardware systems and the humans proceed along the rescue route, they may face hazards and subsequent damages. Thus, the rescue route can also be considered the series of obstacles that the hardware and humans must overcome for the rescue to be completed. An obstacle is characterized by the hazard generated when the system meets with it. Some hazards directly affect the human body (like seasickness), whereas some primarily affect the hardware system (like mechanical failure). Human Health Status: It is a metric of the state of health of the population being evacuated: for each obstacle along the route a proportion of the population will succeed without any trauma whereas others will be injured, perhaps fatally. The Human Health Status (HHS) is therefore a variable representing the distribution of population (in %) in the following four categories: Good Health, Moderately Injured, Severely Injured and Dead (Table 1). The HSS of a particular population can be seen as a 4-dimensional vector that is transformed step-by-step. The comparison between the initial and final HHS characterises the HHS degradation (Figure 1). Design Casualty Scenarios: A set of assessment scenarios is defined that account for the increasingly precarious situation of the mother ship and severe weather conditions. This approach follows the IMO guidelines [3] that refer to Design Casualty Scenarios against which prescriptive and trial alternative designs must be assessed. In the SAFECRAFTS project, Design Casualty Scenarios represent the sequence of obstacles ranging the assessment scenarios (Figure 2).

- 2 -

HHS categories Description Related mobility

Good Health (GH)

Good physical and mental health Good mobility

Moderate Injury (MI)

Moderate bleeding No fracture, no trauma Mobility impaired

Severe Injury (SI) Fractures and/or trauma Mobility requiring

assistance

Deceased (D) Fatal injury No mobility

Table 1: Categories of Human Health Status (HHS)

Figure 1: Transformation of the Human Health Status

along the Rescue Route

Figure 2: Design Casualty Scenarios

2.2. Risk Model Assumptions and Limits: Firstly, we look at the HHS degradation along the rescue for one use corresponding to one evacuation and rescue process. The risk is therefore characterised by the expected degradation of the HHS, provided the conditional event “evacuation is required” is realised. Secondly, the model does not deal with timeline for the evacuation and rescue aspects. Only the period of survival at sea is set as a benchmark. Thirdly, we consider the sequence of obstacles is linear: they come one after the other. This assumption can be questioned if several obstacles act simultaneously, for instance during the phase of survival at sea. In this case, we compared the matrix products in different orders and found no significant difference in the results, so that we eventually chose the average sum of the different combination of matrix products. As we focused on design

Sc 1 Sc 2

Sc k

- - -

Ob.1 Ob.2

[Assessment scenarios of increasing severity]

Design casualty scenarios

Ob.N [Obstacles along the rescue route]

Rescue Route

Initial HHS

⎥⎥⎥⎥⎥

⎦

⎤

⎢⎢⎢⎢⎢

⎣

⎡

N

N

N

N

δχβα

Final HHS

Obs

tacl

e A

Obs

tacl

e B

Obs

tacl

e N

GH MI SI D

GH MI SI D ⎥

⎥⎥⎥⎥

⎦

⎤

⎢⎢⎢⎢⎢

⎣

⎡

0

0

0

0

δχβα

10000 =+++ δχβα 1=+++ NNNN δχβα


Success Rate: Considering that the primary function of a

ed as the percentage of the

performance, first-principle methods were preferred. Thus maintenance and training were generally not considered. In some cases however, historical data were used that may incorporate some maintenance and training shortages.

Life-Saving System is to save lives, the comparison between the final and the initial HHS should be an adequate measure of the LSS performance. To ease the assessment, it is also useful to convert injuries into “equivalent fatalities” using the IMO index [4] reproduced in Table 2. Hence, the success rate is defininitial ship’s population in “equivalent Good Health” which is still in “equivalent Good Health” at the end of the rescue process. It reflects the global degradation of the HHS along the rescue route and therefore the global performance of the LSS. The formal expression of the success rate is given below in Eq. (1) with reference to one assessment scenario “k”.

Effects on human safety Equivalent fatalities Single or minor injuries 0.01

M ultiple or severe injuries 0.1 Single fatality 1

Table 2: Equivalent Fatalities

( )( )000 01.01.01

01.01.01βχδβχδ

++−++−

=kN

kN

kNkSR (1)

lobal Degradation Function: The overall HHS Gdegradation can be seen as a 4-dimensional function f: [0 ; 1]4 → [0 ; 1]4 that is applied to the initial HHS vector. The transformation can be written using matrix format in the standard basis ),,,( 4321 uuuuB rrrr

=

⎥⎥⎥⎥

⎦

⎤

⎢⎢⎢⎢

⎣

⎡

=

⎥⎥⎥⎥

⎦

⎤

⎢⎢⎢⎢

⎣

⎡

⎥⎥⎥⎥

⎦

⎤

⎢⎢⎢⎢

⎣

⎡

N

N

N

N

plhdokgcnjfbmiea

δχβα

δχβα

0

0

0

0

*

s the population cannot get healthier in the course of the

(2)

he global degradation function is a risk assessment tool

Aevacuation and rescue process, the global degradation function can be simplified in Eq. (2):

⎥⎥⎥⎥

⎦

⎤

⎢⎢⎢⎢

⎣

⎡

=

1000000

lhdkgc

fba

f⎪⎩

⎪⎨

⎧

=+=++

=+++

11

1

lkhgf

dcba

Tbecause the coefficients of the matrix are determined according to the expected degradation of the HHS through the sequence of obstacle and the likelihood of such degradation. Yet, the global degradation function can only be derived from the determination of the local degradation functions associated with individual obstacles.

- 3 -

ocal Degradation Functions: Local degradation

ractically, one characterises each obstacle to determine the

/ Hardware obstacles

Lfunctions account for the local degradation of the HHS when passing through one single obstacle and have identical structure as global degradation functions. Given the model’s assumptions, the global degradation is equivalent to the successive degradations caused by the local degradations – in mathematical terms, the matrix product of the local degradation functions. Pcoefficients of the matrix by means of engineering methods and models. As a result, the global degradation matrix is calculated as the product of the local degradation matrixes Eq. (3). There are two types of local degradation functions associated with two categories of obstacles: 1 refer to a failure or a hazard that

2/ an factor obstacles

directly affects the hardware components of the system, for instance a mechanical failure in the deployment system. The effect is binary with respect to the HHS of the people “inside” the hardware. If the hardware fails all occupants are deemed lost and furthermore the phenomenon does not depend of the HHS before the obstacle;

Hum are associated with a number of

phenomena that degrade HHS while the hardware part of the system remains operational. This includes impacts forces, accelerations, seasickness, and other mobility failures. Subsequently, the HSS before the obstacle is relevant because an injured person is more likely to “fail” the next obstacle than a healthy person.

⎥⎥⎦

⎤

⎢⎢⎣

⎡

⎥⎥⎦

⎤

⎢⎢⎣

⎡

⎥⎥⎦

⎤

⎢⎢⎣

⎡=

⎥⎥⎦

⎤

⎢⎢⎣

⎡ABN ffff **...*

(3)

plemented Methodology: On Table 3 hereunder is the Imbasic scheme of the implemented methodology. It includes a phase of definition based on technical documentation and brainstorming, followed by a phase of analytical work to set up and perform the relevant analyses, and finally a phase of consolidation and exploitation of the results.

Main steps Description

Documentation System definition ving appliances, : ship, life-sapopulation, scenarios

Brainstorming cue route and stacles

Description of the Rescharacterisation of the sequence of ob

Analysis Selection of relevant methods and risk criteriafor each obstacle

Assessment al degradation matrixes

Determination of locthrough direct calculation, tests or simulations

Consolidation Calculation of Global degradation functions, final HHS and Success Rates

Exploitation proval of Identification of critical areas, apalternative design and arrangements

Table 3: I p mplemented method step by ste


3. PERFORMANCE ASSESSMENT OF DAVIT-LAUNCHED LIFEBOAT

3.1. System definition Abandoned Vessel: the mother ship model is a large cruise ship whose main features are given in Table 4.

Ship type Cruise liner Displacement 43,000 T

Passenger capacity 2,900 Crew members 900

LOA 294 m LDWL 265 m

Moulded Breadth B 32.2 m Moulded Draught T 7.8 m

KG 15.1 m LCG 123.3 m

Table 4: Features of the abandoned vessel Life-Saving System: The LSS that is assessed here is made up of three hardware components that are (1) the davit system, (2) the lifeboats, and (3) the pilot ladder that is used for disembarkation. In our model, only the lifeboat is specified in details because it is the most complex and important element among the three. Also, we do not model spare capacities, so that LSS capacity corresponds exactly to the population being evacuated. We then consider that the entire population to evacuate “P” is distributed in “N” lifeboats of full capacity “p”. Since all lifeboats are identical, the risk of fatality or injury expressed as a percentage of the total population is calculated as if the entire population was evacuating on one “big lifeboat”:

( )∑ ×=

Nfailure plifeboatTotalRisk )(Pr

PlifeboatplifeboatNTotalRisk failurefailure ×=××= )(Pr)(Pr

Survival Craft: Only one type of LSA is considered that is a standard 150pax partially enclosed davit-launched lifeboat, based on Fassmer’s SEL 8.8 design (Table 5 and Figure 3).

LWL (m) 8.69 BWL (m) 4.09 Draft T 1.05

Sinkage (m) 1.06 Trim (°) -1.35

Volume displacement (m^3) 17.58 Displacement (kg) 18 050

LCG (m) 4.16 VCG (m) 0.66 LCF (m) 4.25

Wetted surface area (m^2) 41.04

Table 5: Features of the lifeboat in fully loaded condition (150pax)

- 4 -

Figure 3: General view of the lifeboat design

Population Features: People’s age is an important aspect to consider because the elderly are generally more vulnerable to harsh conditions and unexpected physical stress. The population used for analysis is distributed as in Table 6 on the basis of internal data and IMO guidelines [5].

Age groups (years) Percentage of passengers (%) a ≤ 50 28%

50 ≤ a ≤ 75 58% 75 ≤ a 14% Total X + Y + Z = 100 %

Table 6: Age distribution among typical cruise population Initial Human Health Status: In realistic conditions, the typical population onboard cruise ship cannot be considered 100% in Good Health according to the model’s assumptions. In particular, people with impaired mobility are deemed more vulnerable to the physical stress and efforts required by the evacuation and rescue process. Based on IMO guidelines for evacuation analysis [5], it is estimated that about 55% of the population older than 50 years old has impaired mobility. With reference to Table 1, we then obtain the initial HHS as input for the calculation (Table 7):

Age groups (years) Initial HHS

a ≤ 50 ⎥⎥⎥⎥

⎦

⎤

⎢⎢⎢⎢

⎣

⎡

00.000.000.000.1

50 ≤ a ≤ 75

75 ≤ a ⎥⎥⎥⎥

⎦

⎤

⎢⎢⎢⎢

⎣

⎡

00.000.055.045.0

Table 7: Initial Human Health Status Assessment Scenarios: The selected scenarios have been derived from the damaged ship and environmental requirements that are currently in force with respect to the operability of LSA. The scenario parameters are independent from LSS design and arrangement and shall reflect the increasing difficulty of the evacuation and rescue process. The selection of relevant parameters may however depend on LSA specificities: for instance low temperature was identified as a relevant parameter for assessing the risk of hypothermia for life rafts, whereas it was not deemed relevant for lifeboats. Beam sea situation would correspond to the typical “dead ship” that has lost its manoeuvring capacity; sea states influence the motions of the abandoned ship and survival crafts; and the period of time at sea is 24 hours as a reference


to LSA Code requirements [6]. In order to limit the number of calculations, we have selected five assessment scenarios (Table 8). The environmental parameters are also described in Table 9; the ITTC spectrum with two parameters was used for seakeeping and ship motions calculation.

Abandoned ship

Scenario Sea state

Period at sea

Heading angle

List (°)

Trim (°)

Sc 1 0-1 ../. 0 0 Sc 2 3 Beam 0 0 Sc 3 5 Head 10 5 Sc 4 5 Beam 20 10 Sc 5 6

24 h

Beam 20 10

Table 8: Five Assessment Scenarios

Sea state

Beaufort scale

Mean wind speed

(knots)

Significant wave height

Hs (m)

Wave peak period Tp (s)

0-1 0 0.0 0.00 ../. 3 3 11.5 0.88 7.5 5 6 24.5 3.25 9.7 6 7 37.5 5.00 12.4 7 10 51.5 7.50 15.0

Table 9: Description of Sea States codes (source NATO)

3.2. Rescue Route For each LSA type, the rescue route in Table 10 was determined during brainstorming exercises through hazard identification and the contributions of experts from various backgrounds including classification, naval architects, LSA manufacturers, ship owners, shipyards and research institutes in both marine science and human health.

Phases Elements Obstacles Type Malfunction Hardware

Deployment Engine failure to start Hardware

Boarding Mobility failure Human factor Premature release Hardware Failure /impact hull Hardware Lowering Injuries / impact hull Human factor Fail to release Hardware

1

Release Injuries / Slamming Human factor

Clear ship Fail manoeuvring Hardware Capsizing Hardware Seasickness Human factor

2 At sea

Tossed around Human factor 3 Recovery Climbing pilot ladder Human factor

Table 10: Rescue Route for Davit-Launched Lifeboat

- 5 -

3.3. Obstacles and Degradation Functions Malfunction: From stowed to lowered position before disconnection, the failure probability is estimated based on historical data available within the project. Over two years and a half, a fleet of passenger ships has experienced 13,692 launches of lifeboats. Problem occurrences relevant to the deployment phase are reported and turned into a failure rate per launch of one lifeboat (Table 11). Due to the lack of details regarding the events actually reported, it is ensure that every occurrence actually prevented the use. Our approach is therefore conservative in this respect. We further consider that these basic events are independent one from each other, and that “Malfunction” can occur because of at least one of these causes. Using a simple fault tree model (Figure 4), we eventually obtain an estimate of the overall probability of failure associated with the obstacle “Malfunction” that is to say 3.2×10-03 per launch or about 1 malfunction every 300 launches. Since the event is independent from age groups and scenarios, there is only one degradation function to derive.

Failure type Occurrences Failure rate per use

Brake mechanism 8 5.84×10-04

Davit mechanism 12 8.76×10-04

Falls 7 5.11×10-04

Winch failure 17 1.24×10-03

Table 11: Failure rate per launch of davit-launched lifeboat

Figure 4: Fault Tree analysis of the obstacle "Malfunction"

0.9968 0.0000 0.0000 0.0000 0.0000 0.9968 0.0000 0.0000 0.0000 0.0000 0.9968 0.0000

“Malfunction”

All scenarios 0.0032 0.0032 0.0032 1.0000


Engine Failure to Start: Passenger ship disasters’ reports [7-9], suggest that lifeboat engine may fail to start, hence preventing the survival craft to clear the ship as required. The associated failure probability per use was derived from historical data available in the offshore industry [10]. The estimate is 0.01 per use which was considered reasonably applicable to passenger ships’ lifeboats. Since this failure is independent from age groups and scenarios, only one degradation function is derived.

0.9900 0.0000 0.0000 0.0000 0.0000 0.9900 0.0000 0.0000 0.0000 0.0000 0.9900 0.0000

“Engine failure”

All scenarios 0.0100 0.0100 0.0100 1.0000

Mobility Failure: Boarding lifeboat and move to final seat may be an obstacle for elderly people. However, if crew assistance is provided, the probability of falling is deemed negligible, so that the obstacle does not degrade HHS.

Premature Release: There are evidences that some on/off-load release hooks currently in use may be instable even with adequate maintenance [8, 11]. This concern in particular so-called “flat contact area cam” designs reproduced hereunder in Figure 5 and Figure 6, taken from [8]. Although many lifeboats are equipped with safer hook designs, we found it interesting to deal with this particular design in order to evaluate the contribution of this hazard to the overall performance of the system.

Figure 5: Mechanical description of flat contact area cam

hook design

- 6 -

Figure 6: Description of hook opening sequence

The contact surface between hook lever and cam is flat. The end of the hook lever pushes the cam open, which is prevented by the release cable attached to the cam lever. When the release cable is removed, the hook will open instantaneously. A simple mechanical model was developed to determine the relationship between the retaining moment in the cam and the cam angle. The following geometrical relations hold.

( ) ( )202 cossin)( ϕϕα vxvvx −++=

⎟⎟⎠

⎞⎜⎜⎝

⎛=

)(sinarcsinαϕα

xv

)(αx Distance cam contact force from cam hinge

v Lever cam contact force related to hook hinge

ϕ Hook angle with respect to the “vertical”

0x Lever cam contact force related to hook hinge, at cam angle 0.0

α Cam angle with respect to the “vertical”

Considering equilibrium of moments about the swivel pin:

vFhF cpvh =

cpvcpc FF)cos(

1ϕα +

=


hF Hook load [N]

h Lever hook load related to hook hinge

cpvF Cam contact force perpendicular to lever v [N]

cpcF Cam contact force perpendicular to cam plane [N]

In line with other experiments [11], the graph in Figure 7 shows the retaining moment is always negative, meaning that the hook will open freely if, for whatever reasons, the retaining control cable is removed or disconnected. More importantly, if the cam is not properly reset, flat against the hook tail, the opening moment is big enough to make the mechanism open at any moment. Assuming a human error probability that the control release cable is improperly reset, the model goes on investigating the problem of premature release. If improperly reset, the control release cable will still apply a retaining force due to the frictional resistance of the cable in the mechanism. As the lifeboat is hoisted empty, back to its stowed position the model help calculate the probability that the frictional resistance of the control cable overcome the opening moment. Considering a 150 persons partially enclosed lifeboat, its typical total weight would be 17.70 tonnes. One hook would carry 8.85 tonnes. The associated cam retaining moment would be about 150 Nm. With a typical relative cam lever length of 0.085, the required retaining force in the mechanical operating cable (release cable) would be about 1760 N. A typical travel of the cable would be 100 mm. A suitable cable would then be a Heavy Duty cable with a travel of 5 inch and push/pull loads 1780/4450 N (400/1000 lbs). For this cable the manufacturer specifies an internal friction of , where cb stands for the total degrees of bend in the cable (in a boat often 180 degrees) and F

cableFcb0015.0

cable stands for the maximum control force. Therefore a typical internal friction would be 481 N (0.0015 × 180 × 1780) in the push mode. When a boat is retrieved after a launching exercise, the hooks will only have to carry the weigh of the empty boat and perhaps six crews. In case of a 150 persons life boat this will be about 6.18 tonnes. One hook has to carry 3.09 tonnes. The associated cam retaining moment is shown in Figure 8.

-500.00

-400.00

-300.00

-200.00

-100.00

0.00

100.00

0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00

CAM angle [deg]

CA

M M

omen

t [N

m]

Figure 7: Cam retaining moment against cam angle with

lifeboat fully loaded

- 7 -

-500.00

-400.00

-300.00

-200.00

-100.00

0.00

100.00

0.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00

CAM angle [deg]

CA

M M

omen

t [N

m]

Figure 8: Cam retaining moment against cam angle with

lifeboat unloaded With a typical effective cam lever length of 0.085, the required retaining force would be as shown in the Figure 9. Up to a cam angle of 20 degrees the required cam retaining force is about 600 N. A probability of undue resetting can now be determined, assuming a normal distribution for the internal friction force, with a mean of 481 N and a deviation of 20%, as depicted in the Figure 10 below.

-7000

-6000

-5000

-4000

-3000

-2000

-1000

00.00 10.00 20.00 30.00 40.00 50.00 60.00 70.00 80.00

CAM angle [deg]

Ret

aini

ng fo

rce

[N]

Figure 9: Retaining force required with lifeboat unloaded

0

0.0005

0.001

0.0015

0.002

0.0025

0.003

0.0035

0.004

0.0045

200 300 400 500 600 700 800

friction force in morse cable [N]

prob

abili

ty d

ensi

ty []

Figure 10: Frictional resistance of the control cable


Undue hook reset is possible when there is sufficient friction in the control cable to provide for a required cam retaining force of 600 N. The cam angle would then be somewhere between 0 and 20 degrees. In this condition the weight of half the boat can be transferred into the release hook without immediate opening of the hook. Assuming the above density function valid, the probability of this being the case is 0.11. Subsequently, the probability of premature release is dramatically high: any additional load can disrupt the fragile equilibrium and trigger the release mechanism. In the worst case scenario, this will happen during a real emergency as people are starting to board the lifeboat. It is however true that this result depends heavily on the average friction force in the release cable and the deviation. The Table 12 below demonstrates this.

Deviation 10% 20% 30%

425 0.00 0.02 0.08 450 0.00 0.05 0.13 475 0.00 0.09 0.19 500 0.02 0.16 0.25 A

rithm

etic

m

ean

525 0.08 0.23 0.32

Table 12: Sensitivity analysis of the control cable frictional resistance model

Additionally we needed to determine the conditional probability that the control cable is improperly reset. This is a typical human error that can occur in the course of drill operations. On the basis of human errors probabilities that are quantified for generic tasks (Hunns & Daniels 1980) we estimated that the control cable is improperly reset once every 20 times (0.05). As a result, the overall failure rate associated with this obstacle is 0.0055.

0.9945 0.0000 0.0000 0.0000 0.0000 0.9945 0.0000 0.0000 0.0000 0.0000 0.9945 0.0000

“Premature release”

All scenarios

0.0055 0.0055 0.0055 1.0000

Structural Failure due to Impact against the Hull: As lifeboats are lowered from the embarkation deck to water level, their relative motions with the mother ship generate a pendulum effects so that lifeboats may impact the hull of the vessel. Apart from injuries induced by impact forces and accelerations, a lifeboat can undergo structural failures that put all occupants in danger irrespective of age or HHS. The aim was to analyse the structural response of a lifeboat during its lowering alongside the mother ship and with reference to the five assessment scenarios. The model has been implemented in Adams software which is dedicated to poly-articulated mechanical systems with large displacements and non-linearity. The mechanical system studied consists of two main parts: the vessel hull and the lifeboat. The davits are rigidly fixed to the hull. Shocks are detected and analysed to extract the velocity of impacts against the hull (Figure 11).

- 8 -

The mother ship’s hull is modelled by a parallelepiped rigid body (265m × 32m × 23m). The six degrees of freedom motions of the vessel are obtained with a 3D-linear seakeeping frequential code (AQUA+), and post-processed to take into account irregular waves (ALEA+). Motions are imposed at the vessel centre of gravity. The lifeboat’s geometry is inspired by Fassmer’s partially enclosed lifeboats SEL 8.8 type.

Figure 11: Setting-up of the lifeboat descent model

As risk criterion, we focused on the velocity of impacts against the hull, which is a relevant indicator with respect to the structural integrity of lifeboats. Indeed, one of the testing requirements for davit-launched lifeboats requires the lifeboat’s structure to withstand a minimum impact velocity of 3.5m/s against a fixed vertical rigid surface [12]. From a regulatory point of view, this requirement means that a lifeboat is approved to withstand impacts up to 3.5m/s. As a result, we deem the “regulatory lifeboat design” would not withstand higher impact velocity – even if a particular lifeboat could actually withstand beyond the regulatory level. This gives us a criterion to analyse the results of the simulations. We consider that a structural failure would occur for each recorded peak of impact velocity above 3.5m/s. The frequency analysis is based on simulated motions over 1700s for two lengths of the davit falls 7.5m (half way) and 12.5m (lifeboat at waterline). This provides an insight of the likelihoods of impacts against the hull. As the amplitude of the pendulum effect increases with the falls’ length, these two positions provides two reference values for estimating the risk of structural failure due to impacts during the descent. The results show that many impacts would occur in Beam Seas, even for medium weather conditions (sea state 3). Yet, most impacts would remain below the threshold of 3.5 m/s. When the ship is listing, there are two aspects: on the positive listing side, lifeboats would supposedly glide down along the ship’s hull; on the other side, the distance to the hull increases as the lifeboat is lowered, but impacts could occur with some of them above the threshold.


The only hazardous situation reported by the simulation is represented in Figure 12 with reference to Scenario 5. Over the time of the simulation (1700s), one dangerous impact is reported for cable length 7.5m whereas height impacts are reported for cable length 12.5m. At constant speed, for a typical descent time of 30 seconds, this would give a probability of respectively 0.017647 and 0.141176 of at least one dangerous impact. At this stage, we can make use of these reference values to approximate the overall probability of structural failure during a descent of 30 seconds. To do so, we have fitted an analytical function Eq. (4) thanks to the three points of reference: [0;0]; [7.5;0.017647] and [12.5;0.141176]. The function F represented in Figure 13 is a probability function associated to the event “at least one impact against the hull with velocity in excess of 3.5 m/s during the descent”.

Figure 12: Simulated impact velocity of the lifeboat against

the mother ship's hull

with (4) XbeXaXF ...)( =1

4

10137.310237.2

−

−

×≈

×≈

ba

0,141

0,018

0,0000,000

0,050

0,100

0,150

0,0 2,5 5,0 7,5 10,0 12,5Cable length (m)

Prob

. at l

east

one

impa

ct w

ith v

eloc

ity

> 3,

5 m

/s d

urin

g de

scen

t 30

s

Figure 13: Probability function associated with dangerous

impacts of the lifeboat against the mother ship's hull

At constant speed, we can calculate the expected value with a simple integration. The overall approximated probability that at least one dangerous impact occurs is 2.7×10-02 for a descent time of 30 s and with reference to Scenario 5.

25.12

0

107.2)(5.12

1 −×=∫ dXXF

- 9 -

The consequence analysis is that impacts against the hull can produce a failure in a lifeboat’s structure if the impact velocity exceeds the prescribed level. As we have explained earlier in the methodology, this kind of failure is considered as a “Hardware obstacle” which is binary in nature with respect to the human health status. In other words, when a structural failure occurs to a lifeboat due to impacts against the hull, all occupants are deemed lost. This is the worst case scenario, but the approach is for an approval process and it is designed to promote robust LSS. Age and HHS before the obstacle have no influence on the results. This is reflected in the simplified structure of the associated degradation function.

With reference to the scenarios defined in the methodology, the results indicate no risk of structural failure due to impacts against the hull for the first four scenarios. For Scenario 5, we have derived the failure rate for lifeboats launched on the negative listing side. On the positive listing side, it is assumed no impacts during the descent. Hence, the overall failure rate is half of 2.7×10-02, that is to say 0.0135.

1.0000 0.0000 0.0000 0.0000 0.0000 1.0000 0.0000 0.0000 0.0000 0.0000 1.0000 0.0000

“Impacts / structural failure”

Scenario 1 to 4

0.0000 0.0000 0.0000 1.0000 0.9865 0.0000 0.0000 0.0000 0.0000 0.9865 0.0000 0.0000 0.0000 0.0000 0.9865 0.0000

“Impacts / structural failure”

Scenario 5

0.0135 0.0135 0.0135 1.0000

Injuries due to impacts against the hull: Provided that no structural failures occur due to impacts against the hull, we then considered the problem of injuries for the lifeboat’s occupants. In short, lateral impact accelerations taken from the previous simulation were converted into biomechanical injuries in a way that is similar to a car crash accident using the Abbreviated Injury Scale (AIS) [13].

Injury is estimated on the basis of maximum acceleration that is scaled relative to a “tolerable acceleration limit” which is 5g for lateral impact. This value holds for cars where occupants have a sort of bucket seat. In a lifeboat with absolute flat benches and no armrests at all, we lowered the limit to 4g, and 3g for the oldest group of people. The conversion to AIS was based on a regression formula. Furthermore, a fatality was assumed for AIS 5 or beyond (“critical” or “fatal”); severe injury for AIS 2.5 to 4.99 (“serious” or “severe”); and moderate injury was assumed for AIS 1.0 to 2.5. Only Scenario 4 & 5 gave peak accelerations greater than 3g or 4g. Figure 14 below show the simulation results in scenario 5 conditions for the two cable lengths.


Figure 14: Simulated impact accelerations of the lifeboat

against the mother ship’s hull As with the previous obstacle, impacts and associated injuries are only considered on the negative listing side. Considering both sides, the overall degradation is as follows:

AGE ≤ 75

1.0000 0.0000 0.0000 0.0000 0.0000 1.0000 0.0000 0.0000 0.0000 0.0000 1.0000 0.0000

“Impacts / injuries”

Scenario 1 to 4

0.0000 0.0000 0.0000 1.0000 0.9445 0.0000 0.0000 0.0000 0.0472 0.9898 0.0000 0.0000 0.0083 0.0103 1.0000 0.0000


Scenario 5

0.0000 0.0000 0.0000 1.0000

75 ≤ AGE 1.0000 0.0000 0.0000 0.0000 0.0000 1.0000 0.0000 0.0000 0.0000 0.0000 1.0000 0.0000


Scenarios 1 to 3

0.0000 0.0000 0.0000 1.0000 0.9584 0.0000 0.0000 0.0000 0.0417 1.0000 0.0000 0.0000 0.0000 0.0000 1.0000 0.0000


Scenario 4

0.0000 0.0000 0.0000 1.0000 0.8234 0.0000 0.0000 0.0000 0.1322 0.9479 0.0000 0.0000 0.0361 0.0419 0.9800 0.0000


Scenario 5

0.0084 0.0103 0.0201 1.0000

- 10 -

Fail to release: In addition to the risk of premature release, there exist a risk that the release system fails when it is required, hence preventing lifeboats to sail away from the touchdown area. There are certainly various causes that contribute to such event including poor maintenance. For the purpose of the assessment, we used historical data from within the project as well as from the offshore industry [8] (Table 13). For all age groups, the degradation functions are thus provided hereunder.

Environmental conditions Calm Moderate Severe Internal data 9.49×10-04 ./.. ./.. CMPT report 1999 0.000 0.015 0.140 SAFECRAFTS Data 0.001 0.01 0.1

Table 13: Release failure rate per use

0.9990 0.0000 0.0000 0.0000 0.0000 0.9990 0.0000 0.0000 0.0000 0.0000 0.9990 0.0000

“Fail to release”

Scenario 1 0.0010 0.0010 0.0010 1.0000 0.9900 0.0000 0.0000 0.0000 0.0000 0.9900 0.0000 0.0000 0.0000 0.0000 0.9900 0.0000


Scenario 2 0.0100 0.0100 0.0100 1.0000 0.9000 0.0000 0.0000 0.0000 0.0000 0.9000 0.0000 0.0000 0.0000 0.0000 0.9000 0.0000


Scenario 3, 4 & 5 0.1000 0.1000 0.1000 1.0000

Slamming: As the lifeboat is disconnected from the falls, it may drop in water due to the relative vertical motions with the surface of the sea. Slamming may then cause impact accelerations leading to injuries for the occupants. This aspect was investigated in the project but the results were not sufficiently reliable to use them in the overall assessment. As a result, we do not account for the degradation induced by the obstacle “Slamming”.


Fail Manoeuvring: This analysis was performed to derive the operational limits of a conventional lifeboat while clearing from the mother ship. Wind exposure may prevent lifeboats to sail away from the touchdown area close to the vessel’s hull. Lifeboats unable to clear are deemed lost because of the dangerous vicinity with the hull. The model ignores the influence of waves and does not account for several unsuccessful trials before successful clearing. Manoeuvring model of the lifeboat was generated from the main boat data (Table 14) using the manoeuvring suite SIMX [14].The lifeboat handling was done by the engine and rudder. The lifeboat is steered away from the ship by using a combination of engine and rudder setting. The handling criterion was set for a limit of two boat lengths along the side of the mother ship. Clearing from the bow or from the stern was considered for five different wind directions and height wind speeds ranging from 15 to 50 knots. If the trajectory was outside the defined lanes or the boat was pushed away by the environment in the direction of the mother ship, the manoeuvre was considered unsuccessful. The simulation results are reported in Table 15, whereas Figure 15 shows an example of graphical representation. Against the assessment scenarios, the results indicate that lifeboats in windward side should be able to clear in the first four scenarios. In Scenario 5, lifeboats in windward side could not sail away. This conclusion is dramatically conservative because some lifeboats could certainly withstand a few impacts while sailing alongside the hull to escape from aft or stern. However, it is very difficult to address such a complex situation, so that the degradation function was set in accordance with the simulation results. The authors believe the simulation is yet quite informative regarding the operational limits of conventional lifeboats.

Length Overall 8.80 Length between Perpendiculars 8.75 Beam (m) 4.26 Mean Draught (m) 0.85 Block Coefficient 0.5130 Position of LCB from Midship (m) 0.00 Trim (m) 0.00 Lateral Windage Area (m^2 23.76

Life

boat

dat

a

Transverse Windage Area (m^2) 18.90 Propeller Type FPP Number of Propellers 1 Propeller Diameter (m) 0.50 Propeller Pitch (m) 0.45 Propeller Shaft rev/s 14.10 Pr

opel

ler d

ata

Engine Delay Time 1.00 Number of Rudders 1 Rudder Area (m^2) 0.12 Rudder Height (m) 0.50 Rudder Aspect Ratio 1.67

Rud

der d

ata

Rudder Turning Rate (deg/sec) 2.25

Table 14: Input data for the lifeboat manoeuvring model

- 11 -

Wind direction (deg)

Head Quarter bow Beam Quarter

stern Stern

15 Stern or Bow Stern Bow Bow Stern or

Bow

20 Stern or Bow Stern Bow Bow Stern or

Bow

25 Stern or Bow

Stern or Bow Bow Bow Stern or

Bow

30 Stern or Bow Stern N Bow Stern

35 Stern or Bow N N N Stern

40 Stern or Bow N N N Stern

45 Stern or Bow N N N Bow

Win

d sp

eed

(kno

ts)

50 Stern or Bow N N N Bow

Lifeboat can clear away Lifeboat can clear away with difficulties Lifeboat can not clear away

Table 15: Lifeboat clearing manoeuvre simulation results

Figure 15: (Up) Successful manoeuvre by the stern (wind direction: Quarter bow / wind speed: 20 knots); (Down) Unsuccessful manoeuvre by the stern (wind direction:

beam / wind speed: 35 knots)

1.0000 0.0000 0.0000 0.0000 0.0000 1.0000 0.0000 0.0000 0.0000 0.0000 1.0000 0.0000

“Fail manoeuvring”

Scenario 1 to 4

0.0000 0.0000 0.0000 1.0000 0.5000 0.0000 0.0000 0.0000 0.0000 0.5000 0.0000 0.0000 0.0000 0.0000 0.5000 0.0000

“Fail manoeuvring”

Scenario 5

0.5000 0.5000 0.5000 1.0000


Capsizing: After disconnection, lifeboats have to sail until they can safely use a sea anchor and drift head-on. During this phase, dangerous wave incidences such as stern to beam waves will be encountered. The risk is higher in beam waves, and it is considered realistic that a lifeboat could be exposed for a maximum cumulated time of ten minutes. If capsized, a lifeboat is deemed lost with its occupants. Two main events are considered that contribute to capsizing the lifeboat: excessive roll motions and flooding – as the ship is partially enclosed. For excessive roll motions, risk criterion is roll angle in excess of 30.5° that corresponds to the maximum of the Gz curve. For flooding, risk criterion is vertical relative motion at mid-ship in excess of freeboard fully loaded: 0.78m. The assessment draws on seakeeping analysis for lifeboat afloat with minimum speed. Lifeboat motions and accelerations were calculated with AQUA+ and ALEA+ in the same way as for the mother ship. The simulation results reported on Figure 16 first indicate that the risk is negligible in moderate sea conditions. For sea state 5 and 6, the risk is substantially higher, in particular for flooding. In this respect, it is true that a canopy should protect the openings from water entry. However, in a real gale the canopy was deemed insufficient to prevent water entry, so that we considered the openings “opened”. In addition, we adapted the risk criterion by “adding” 20cm to the freeboard that means vertical relative motions should be as high as 0.98 to effectively cause flooding Eq. (5). Hence, for a period of ten minutes in Beam Sea, it is possible to derive the associated probability, assuming that it is proportional to the time of exposure. We then used a simple fault tree analysis to combine the two event using a “OR” gate as represented in Figure 17. The probabilities of capsizing (Table 16) for sea states 5 or 6 are quite closed, so that we rounded up to the upper value that is to say 0.0006. The corresponding degradation functions are then derived.

Figure 16: Seakeeping simulation results of free-floating

lifeboat

- 12 -

( )⎟⎟⎠

⎞⎜⎜⎝

⎛−=

2/98.0exp)(

2

98.0RMSfloodingP (5)

Figure 17: Capsizing probability using fault tree analysis Sea states P (roll > 30.5°) P (flooding)0.98 P(capsizing)

3 4.43×10-33 6.01×10-31 Negligible 5 2.09×10-04 3.86×10-04 5.95×10-04

6 2.74×10-04 8.41×10-05 3.58×10-04

Table 16: Capsizing probability of lifeboat for 600s exposure in Beam Sea

0.9994 0.0000 0.0000 0.0000 0.0000 0.9994 0.0000 0.0000 0.0000 0.0000 0.9994 0.0000

“Capsizing”

Scenario 3, 4 & 5 0.0006 0.0006 0.0006 1.0000

Seasickness: In real emergency cases, lifeboat’s occupants may spend hours at sea before they can get rescued. Among the difficulties that an individual may face in such situation, seasickness is by far the most problematic. Seasickness would generally only create discomfort but it can also escalate to vomiting, headache, apathy, lack of appetite, etc. The most dangerous impacts on human health are dehydration and Loss Of Will To Survive (LOWTS). Especially for the elderly, additional dangers of continued vomiting are heart failure and suffocation in unexpelled vomit. Physically motion sickness occurs when sensed motions and accelerations differ strongly and continuously from what is expected or anticipated in the inner ear organ. Typical provocative motions include low-frequency1 linear and angular motions with special negative influence of vertical motions and accelerations.

Within the project, the analysis was conducted by specialists in motion sickness and human factors. The model is based on the core concept of Motion Sickness Incidence [15] that depends on the RMS of the vertical acceleration, the frequency, and the exposure duration (Figure 18). The model

1 Between 0.01 Hz and 1 Hz, with most sickness observed around 0.17 Hz (McCauley et al., 1976)


used in SAFECRAFTS is somewhat more sophisticated as it also accounts for lateral accelerations and variations related to people’s age. In this model, vomiting is taken as criterion of being seasick. The sickness incidence is then so-called Vomiting Incidence

As input data, we used lifeboat’s motions and accelerations simulated for lifeboats floating free with minimum speed for a constant incidence of waves on quarter bow (Table 17). The Vomiting Incidence was estimated for different age groups exposed for 24 hours (Table 18). The Vomiting Incidence values were further interpreted to derive the actual percentage in the HHS categories. The calculations do not include the effect of seasickness pills, which are available on board ships and LSA; however it is possible for these to be taken into account.

Figure 18: Illustration of the Motion Sickness Incidence

model

Input data at Centre of Gravity X acc Y acc Z acc Free

floating lifeboat

RMS (m/s2)

T2 (s)

RMS (m/s2)

T2 (s)

RMS (m/s2)

T2 (s)

Sea state 3 0.22 4.28 0.12 4.50 0.27 4.20 Sea state 5 0.57 4.72 0.32 4.96 0.71 4.59 Sea state 6 0.61 5.15 0.34 5.41 0.75 4.98

Table 17: Lifeboat motions input data for the calculation of seasickness

Exposure Age groups (years) Vomiting Incidence (%) SS3 SS5 SS6

a < 50 6 13.6 12.3 50 < a < 75 4.1 9.3 8.4 24h

75 < a 2.7 6.2 5.6

Table 18: Vomiting incidence for the three age groups for 24 hours at sea

- 13 -

AGE ≤ 50 1.0000 0.0000 0.0000 0.0000 0.0000 0.9950 0.0000 0.0000 0.0000 0.0030 0.9968 0.0000

“Seasickness”

Scenario 2 0.0000 0.0020 0.0032 1.0000 1.0000 0.0000 0.0000 0.0000 0.0000 0.9895 0.0000 0.0000 0.0000 0.0070 0.9930 0.0000

“Seasickness”

Scenario 3 & 4 0.0000 0.0035 0.0070 1.0000 1.0000 0.0000 0.0000 0.0000 0.0000 0.9906 0.0000 0.0000 0.0000 0.0063 0.9938 0.0000

“Seasickness”

Scenario 5 0.0000 0.0031 0.0062 1.0000

50 ≤ AGE ≤ 75

0.9981 0.0000 0.0000 0.0000 0.0000 0.9953 0.0000 0.0000 0.0016 0.0032 0.9968 0.0000

“Seasickness”

Scenario 2 0.0003 0.0016 0.0032 1.0000 0.9958 0.0000 0.0000 0.0000 0.0000 0.9878 0.0000 0.0000 0.0035 0.0070 0.9930 0.0000

“Seasickness”

Scenario 3 & 4 0.0007 0.0052 0.0070 1.0000 0.9963 0.0000 0.0000 0.0000 0.0000 0.9906 0.0000 0.0000 0.0031 0.0063 0.9938 0.0000

“Seasickness”

Scenario 5 0.0006 0.0031 0.0062 1.0000

75 ≤ AGE

0.9953 0.0000 0.0000 0.0000 0.0000 0.9945 0.0000 0.0000 0.0032 0.0032 0.9953 0.0000

“Seasickness”

Scenario 2 0.0016 0.0024 0.0047 1.0000 0.9895 0.0000 0.0000 0.0000 0.0000 0.9878 0.0000 0.0000 0.0070 0.0070 0.9896 0.0000

“Seasickness”

Scenario 3 & 4 0.0035 0.0052 0.0104 1.0000 0.9906 0.0000 0.0000 0.0000 0.0000 0.9890 0.0000 0.0000 0.0063 0.0063 0.9907 0.0000

“Seasickness”

Scenario 5 0.0031 0.0047 0.0093 1.0000

Tossed around: In view of the relatively rough seating arrangement inside a lifeboat, people may glide or fall down due to motions that may cause injuries. However, no data was available on this issue to estimate the risk associated with this obstacle.


Climbing pilot ladder: Contrary to the evacuation phase that takes place on one specific vessel in some given environmental conditions, the final rescue may be more heterogeneous. Various means of rescue may be involved, and to some extent, it is possible to postpone the final operations if the weather conditions are too severe. In this assessment, we have only considered pilot ladder as final means of rescue because (1) it is likely to be the first means of rescue available, and (2) we wanted to put emphasis on its drawbacks. Full-scale experiments performed within the project showed that age and gender have little influence on the ability to climb if the volunteers are in good physical condition. Alternately, the relative motions between the survival craft and the rescue vessel were considered the most impairing factor. In this context, it is assumed that rescue operations with ships would only occur in calm or moderate sea conditions (Scenario 1 & 2). Thus, climbing a pilot ladder is possible and ship-to-ship impacts should be limited. Only healthy people at that stage of the process might be able to effectively climb the ladder. In severe weather conditions (Scenario 3, 4 & 5), it is assumed that no one would take the chance to climb a pilot ladder. At this stage of the analysis, we present two alternatives: 1/ “Case A”: pilot ladder is the only means of rescue available; therefore those unable to climb are deemed lost.

1.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

“Climbing pilot ladder” Case A

Scenario 1 & 2 0.0000 1.0000 1.0000 1.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000

“Climbing pilot ladder” Case A

Scenario 3, 4 & 5 1.0000 1.0000 1.0000 1.0000

2/ “Case B”: the other people onboard the lifeboat wait for other means of rescue – helicopter for instance. To account for this drawback, we “assigned” these people at sea for another period of 24h, facing the risk of seasickness and capsizing.

AGE ≤ 50 1.0000 0.0000 0.0000 0.0000 0.0000 1.0000 0.0000 0.0000 0.0000 0.0000 1.0000 0.0000

“Climbing pilot ladder” Case B

Scenario 1 0.0000 0.0000 0.0000 1.0000 1.0000 0.0000 0.0000 0.0000 0.0000 0.9950 0.0000 0.0000 0.0000 0.0030 0.9968 0.0000


Scenario 2 0.0000 0.0020 0.0032 1.0000 0.9994 0.0000 0.0000 0.0000 0.0000 0.9889 0.0000 0.0000 0.0000 0.0070 0.9924 0.0000


Scenario 3 & 4 0.0006 0.0041 0.0076 1.0000

- 14 -

0.9996 0.0000 0.0000 0.0000 0.0000 0.9902 0.0000 0.0000 0.0000 0.0063 0.9934 0.0000


Scenario 5 0.0004 0.0035 0.0066 1.0000

50 ≤ AGE ≤ 75

1.0000 0.0000 0.0000 0.0000 0.0000 1.0000 0.0000 0.0000 0.0000 0.0000 1.0000 0.0000


Scenario 1 0.0000 0.0000 0.0000 1.0000 1.0000 0.0000 0.0000 0.0000 0.0000 0.9953 0.0000 0.0000 0.0000 0.0032 0.9968 0.0000


Scenario 2 0.0000 0.0016 0.0032 1.0000 0.9952 0.0000 0.0000 0.0000 0.0000 0.9872 0.0000 0.0000 0.0035 0.0070 0.9924 0.0000


Scenario 3 & 4 0.0013 0.0058 0.0076 1.0000 0.9959 0.0000 0.0000 0.0000 0.0000 0.9902 0.0000 0.0000 0.0031 0.0063 0.9934 0.0000


Scenario 5 0.0010 0.0035 0.0066 1.0000

75 ≤ AGE

1.0000 0.0000 0.0000 0.0000 0.0000 1.0000 0.0000 0.0000 0.0000 0.0000 1.0000 0.0000


Scenario 1 0.0000 0.0000 0.0000 1.0000 1.0000 0.0000 0.0000 0.0000 0.0000 0.9945 0.0000 0.0000 0.0000 0.0032 0.9953 0.0000


Scenario 2 0.0000 0.0024 0.0047 1.0000 0.9889 0.0000 0.0000 0.0000 0.0000 0.9872 0.0000 0.0000 0.0070 0.0070 0.9890 0.0000


Scenario 3 & 4 0.0041 0.0058 0.0110 1.0000 0.9902 0.0000 0.0000 0.0000 0.0000 0.9886 0.0000 0.0000 0.0063 0.0063 0.9903 0.0000


Scenario 5 0.0035 0.0051 0.0097 1.0000


3.4. Success Rate and Identification of Critical Areas for Improvements

Success Rates: Once local degradation functions are determined, it is possible to calculate the global degradation functions for each scenario and each age category. Given the initial HHS presented in section 3.1, one obtains the corresponding final HHS that are required to derive the Success Rates for each scenario and each age category. Eventually, the overall results are obtained (Table 19) using a weighted sum of the three age categories (Table 6). The results for “Case A” show that scenarios 3, 4 & 5 are not practicable if only pilot ladders are used for the final rescue. Climbing the pilot ladder is clearly a showstopper. Even in drill conditions (Scenario 1), only 60% of the initial population is able to complete the process. The results for “Case B” show that the system performs rather well in the four first scenarios. Scenario 5 has a very low performance due to the obstacle “Fail manoeuvring” that accounts for 50% of the degradation. However, even when lifeboats are able to clear away from the wrecked vessel (Scenarios 1 to 4), many fatalities are predicted in this assessment. For instance, if 4,000 people would be considered in this evacuation and rescue process as modelled here, there would be around 80 fatalities in Scenario 1, and 480 fatalities in Scenario 3.

Success Rates Scenario Case A Case B

Scenario 1 59% 98% Scenario 2 59% 97% Scenario 3 0% 88% Scenario 4 0% 88% Scenario 5 0% 43%

Table 19: Estimated Success Rates for LSS using conventional lifeboats

Identification of critical areas: It is possible to calculate the Success Rate step-by-step and determine the actual contribution of individual obstacles to the overall degradation associated with the rescue route. Critical obstacles were selected if their contribution was higher than 1% of the total degradation of the Success Rate (Figure 19). For “Case A”, the obstacle “Climbing pilot ladder” is by far the most critical obstacle in the first two scenarios. More dedicated equipment should therefore be available on every merchant ship to effectively address this issue. For “Case B”, the contribution of the obstacle “Climbing pilot ladder” is significantly smaller due to the availability of other means of rescue. As a result, the relative contribution of the other obstacles is highlighted: hardware obstacles are the most contributing obstacles, whereas the two main human factor obstacles are “Seasickness” and “Climbing pilot ladder”. If we ignore “Fail start engine” and “Fail to release” that are based on historical data, “Premature release” is the main contributor. This confirms the feedback that the “flat contact area cam” hook design has been at the origin of numerous accidents. However, the vast majority of modern hook designs are radically different and this problem would not occur on brand new lifeboats using failsafe hook designs.

- 15 -

2% 2% 1% 1% 0% 0% 0% 0% 0% 0% 0%

93%

0%

20%

40%

60%

80%

100%

Clim

b pi

lot l

adde

r

Fail

star

t eng

ine

Fail

to re

leas

e

Pre

mat

ure

rele

ase

Mal

func

tion

Sea

sick

ness

Mob

ility

failu

re

Stru

ctur

al fa

ilure

Inju

ries-

impa

cts

Fail

man

oeuv

ring

Cap

sizi

ng

Toss

ed a

roun

d

Case A - Scenario 2

33% 32%

18%

11%

3% 3%0% 0% 0% 0% 0% 0%

0%

10%

20%

30%

40%

50%

Fail

star

t eng

ine

Fail

to re

leas

e

Pre

mat

ure

rele

ase

Mal

func

tion

Sea

sick

ness

Clim

b pi

lot l

adde

r

Mob

ility

failu

re

Stru

ctur

al fa

ilure

Inju

ries-

impa

cts

Fail

man

oeuv

ring

Cap

sizi

ng

Toss

ed a

roun

d

Case B - Scenario 2

80%

8% 4% 3% 2% 2% 0% 0% 0% 0% 0% 0%0%

20%

40%

60%

80%

100%

Fail

to re

leas

e

Fail

star

t eng

ine

Pre

mat

ure

rele

ase

Mal

func

tion

Clim

b pi

lot l

adde

r

Sea

sick

ness

Cap

sizi

ng

Inju

ries-

impa

cts

Mob

ility

failu

re

Stru

ctur

al fa

ilure

Fail

man

oeuv

ring

Toss

ed a

roun

d

Case B - Scenario 4

Figure 19: Selected critical areas for LSS using

conventional lifeboats


4. APPLICATION FOR APPROVAL OF

ALTERNATIVE DESIGN In SAFECRAFTS, the proposed methodology was developed with a view to (1) assess the performance of conventional systems, (2) identify critical areas for improvements, and (3) assess the performance of novel LSA concepts. This was achieved by focusing research on the functional performance of LSA, which was expressed as the Success Rate of the evacuation and rescue process in different scenarios. Hence, it is also possible to use it as an evaluation tool within a process of approval of alternative design and arrangements.

4.1. Dealing with a complete Life-Saving System As previously explained in the paper, a ship shall be equipped with a Life-Saving System (LSS) made-up of several LSA types. Hence, given the fact that the proposed methodology is linear in all aspects, it is possible to combine the performance of different LSA types in order to obtain the specific performance of the LSS considered. This provides a great flexibility in the application of the methodology and allows for a global comparison with novel LSS concepts.

4.2. Acceptance Criteria The process flowchart developed in the IMO guidelines for alternative LSA design [3] is reproduced hereunder in Figure 20. It is explicitly requested to “Evaluate performance of prescriptive vs. proposed” design in a quantitative fashion. The methodology presented in this paper provides effectively a conceptual approach to meet this requirement, where Success Rates calculated for the prescriptive design stand for acceptance criteria. When all relevant assessment scenarios are defined, the trial design should score a higher Success Rate than the prescriptive design for all scenarios (Table 20). Thus, the assessment results for a conventional design compliant with prescriptive rules provide a reference baseline for the approval process of alternative LSA designs. However, the results presented in this paper are essentially used to illustrate the methods and validate the identification of critical areas for design improvements. Moreover, if the methodology is generic, the implementation imposes many choices and assumptions in the modelling of the system, the rescue route and the scenario parameters that make every assessment tailor-maid for the purpose of the ship design project, for which alternative LSA design is envisaged.

Scenario #

Success Rate Prescriptive

design

Success Rate Alternative

design

Acceptance criteria

Sc 1 SR1(PD) SR1(AD) SR1(AD) ≥ SR1(PD)

Sc 2 SR2(PD) SR2(AD) SR2(AD) ≥ SR2(PD)

… … … …

Sc k SRk(PD) SRk(AD) SRk(AD) ≥ SRk(PD)

Table 20: Acceptance criteria concept for the approval of alternative LSA designs and novel concepts

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Figure 20: Process flowchart for Alternative design and

arrangement for LSA

5. CONCLUSION AND FUTURE WORK This paper demonstrates how one can practically implement a global assessment of life-saving appliances. The Success Rate of the evacuation and rescue process is recommended as the principal performance indicator of life-saving systems. It reflects the degradation of the Human Health Status as the hardware system and the population faces a sequence of obstacles along the rescue route. Different scenarios are defined to account for increasingly severe environmental and damaged ship conditions enabling the assessment of system robustness. Some obstacles were difficult to quantify such as slamming or being tossed around. Use of historical data also introduced a bias in the quantitative treatment, whereas the problem of premature release is specific to one designated hook design that is not representative of state-of-the-art designs. In the near future, the methodology will be applied on novel concepts developed within the SAFECRAFTS project. It is also intended to further streamline this approach with the IMO framework and contribute to defining a systematic approach for assessing existing and novel LSA concepts.


6. ACKNOWLEDGMENT A major part of this study presented herein, was financially supported by the European Commission under the FP6 Sustainable Surface Transport Programme. The support is given under the scheme of STREP, Contract No. FP6-PLT-506402. The European Community and the authors shall not in any way be liable or responsible for the use of any such knowledge, information or data, or of the consequences thereof.

7. REFERENCES [1] INTERNATIONAL MARITIME ORGANISATION,

SOLAS convention, Chapter III, Part C, Reg. 38, as amended in MSC 82, December 2006.

[2] McGREGOR J., PRAT L., CORRIGNAN P., BOER

L., “Risk-based approval of alternative designs and arrangements for life-saving appliances onboard passenger ships”, Proceedings of the 3rd Design For Safety conference, 2007, Berkeley, CA, USA.

[3] INTERNATIONAL MARITIME ORGANISATION,

MSC.1/Circ.1212, Guidelines on Alternative Design and Arrangements for chapters II-1 and III, December 2006.


MSC/Circ.1023, Formal Safety Assessment Guidelines, 2002.


MSC/Circ.1033, Annex 2, Interim Guidelines for the Advanced Evacuation Analysis of New and Existing Passenger Ships, 2002.


International Life-Saving Appliance Code, Edition 2003, section 4.4.6.8.

[7] BAHAMAS MARITIME AUTHORITY, Report of the

investigation into fire on and sinking of the passenger vessel “Sun Vista” on 20 and 21 May 1999 in the Malacca Straits, November 2000.

[8] LANG J. S. REAR ADMIRAL, “Review of Lifeboat

and Launching Systems’ Accidents, Maritime Accident Investigation Branch, 2001.

[9] PEACHEY J., POLLARD S., Burness Corlett-Three

Quays Ltd for the UK Maritime and Coastguard Agency, MCA Research Project 555: Development of Lifeboat Design, 2006.

[10] CMPT Centre for Marine and Petroleum Technology,

Guide to QRA for Offshore Installations, 1999 [11] INTERNATIONAL MARITIME ORGANISATION,

Measures to Prevent Accidents with Lifeboats (submitted by Canada), FP 50/INF.4, 20 October 2005.

[

[

[ [

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12] INTERNATIONAL MARITIME ORGANISATION, International Life-Saving Appliance Code, Edition 2003, section 4.4.1.7.

13] AIS (1998): Association for the Advancement of Automotive Medicine, The Abbreviated Injury Scale, updated of revision 1990, AAAM Des Plaines, IL-USA.

14] http://hydrosim.mysite.wanadoo-members.co.uk/

15] BOS, J.E., Scheepsbewegingen en “Motion Sickness Incidence” (MSI): Voorspellingen van het percentage bewegingszieken op basis van verticale bewegingen, TNO-TM 1995 A-71, November 1995 (in Dutch)


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