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Setting Target Reliabilities by Marginal Safety Returns

Rolf SkjongStrategic Research

Det Norske Veritas

Rolf.Skjong @dnv.com

JCSS Workshop on Code Calibration, March 21-22 2002

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Traditional Approach - SRA

Typical Example:DNV Classification Note 30.6 (1992) on Structural Reliability Analysis of Maritime Structures

Explains why SRA does not produce Probabilities with a frequency interpretation– No gross error– Epistemic uncertainty & model uncertainties

included– SRA talk of “notional” reliabilities

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Traditional Approach - SRA

Target should depend on consequence Calibration against known cases (that are acceptable

good/best practices in the industry) Calibration against similar cases with similar

consequences Based on accepted decision analysis techniques Based on tabular values (presented as a last resort)

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Traditional Approach - SRA

Target should depend on consequence Calibration against known cases (that are acceptable

good/best practices in the industry) Calibration against similar cases with similar

consequences Based on accepted decision analysis techniques Based on tabular values (presented as a last resort)

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Traditional Approach - SRA

Based on tabular values (presented as a last resort)

Annual Target Probabilities (and Target βT) from DNV Classification Note 30.6Consequence of FailureClass of Failure

Less serious SeriousI- Redundant Structure PF = 10-3, βT = 3.09 PF = 10-4, βT = 3.71II - Significant warning before the occurrence offailure in a non-redundant structure

PF = 10-4, βT = 3.71 PF = 10-5, βT = 4.26

III - No warning before the occurrence of failure ina non-redundant structure

PF = 10-5, β T = 4.26 PF = 10-6, β T = 4.75

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Traditional Approach - QRA

Quantitative risk assessment is the basis for regulations in many industries– PSA/PRA - Nuclear– Hazardous Industries (Seveso I/II)– Offshore (Safety Case)– Shipping (FSA)– Etc.

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Quantitative Risk Assessment

Two uses of Risk assessment Use as a basis for receiving and maintaining a licence

to operate (the plant, platform etc.)– Safety Case

Use as a basis for implementing risk reducing measures for “populations (all cars, all ships, all planes etc.)– Formal Safety Assessment

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Traditional Approach - QRA

Present Risk Results in terms of– Individual risk (fatalities)– Individual risk (Health and Injuries)– Societal Risk (group Risk)– Environmental risk– Economic risk (not necessarily a regulatory issue)

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Traditional Approach - QRA

Example Individual risk

1.00E-07

1.00E-06

1.00E-05

1.00E-04

1.00E-03

1.00E-02

Ind

ivid

ual

risk Intolerable Risk

ALARP

Negligible Risk

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Traditional Approach - QRA

Example Health Risk

Time (years)

Health index

1Perfecthealth

Death 0

A

C

A’ B’

BExpected Health index, when RCO implemented

Expected Health index,when RCO not implemented

Quality Adjusted Life Years gainedby implementing the RCO

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Traditional Approach - QRA

Example Societal Risk

1.0E-06

1.0E-05

1.0E-04

1.0E-03

1.0E-02

1 10 100

Fatalities (N)

Fre

qu

en

cy

of

N o

r m

ore

fa

taliti

es

(p

er

sh

ip

ye

ar)

Oil tankers

Chem. tankers

Oil/Chemicaltankers

Gas tanker

Negligible

Intolerable

ALARP

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Traditional Approach - QRA

Low Risk

High Risk Intolerable

ALARP

Negligible

Not acceptable

Acceptable

Acceptable if made ALARP

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Traditional Approach - QRA

The As Low As Reasonably Practicable Area implies that cost effectiveness assessment may be used

Risk is made As Low As Reasonably Practicable, when all cost effective safety measures have been implemented

Implies that a decision criteria for cost effectiveness will be required

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Methods for deriving criteria

Human capital approach Willingness to pay Comparing to well informed (risk informed) decisions in

democratic forum (a willingness to pay) Comparing to previous decision (a willingness to pay) Societal Indicators (a willingness to pay) Individual decisions

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Human capital approach

Value of man as a resource in economic production Has discredited cost effectiveness & cost benefit

assessment Contradicts ethical principle (Protagoras: “Homo

mensura” and later formulations, e.g. Kant) Same reason as many governments ban research on

human stem-cells

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Willingness to pay

Many forms of willingness to pay studies– Questionnaires– Observed behaviour (e.g. insurance)– Implicit in previous decisions– Implicit in existing regulations– Etc.

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Comparing to well informed decisions

Example from IMO: UN Organisation for maritime safety and environmental protection regulations

Cost of averting fatalities in actual decisions

Decision DecisionMaker

Value

Strengthening Bulkheads on Existing BulkCarriers

IACS andIMO (1)

> $ 1.5 million

Helicopter Landing Area on non-Ro/RoPassenger Ships

IMO(2) < $ 37 million($ 12 million to $ 73

billion)3 bulkheads on car deck IMO(3) < $ 5 million3 bulkheads on car deck NMD(3) > $ 5 million3 bulkheads + sponsons IMO(3) < 7.8 millionExtended sponsons only IMO(3) < $ 11 millionCollision Avoidance Training Owner(3) > $ 0.7 millionExtra Deck Officer IMO(3) < $ 5.5 millionRe: (1) Mathisen et al.(1997), (2) Skjong et al.(1997), (3) DNV(1997)

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Comparing to previous decision

Results from Tengs et al. (1995)“Five Hundred Life-Saving Interventions and their Cost Effectiveness”

Number of measures studied 587Range of cost effectiveness Negative to $10 billion/life year

savedMedian Value $ 42.000/life yearMedian for Medical Interventions $ 19.000/life yearMedian for Injury Prevention $ 48.000/life yearMedian for toxic control $2.8 million/life year

•By reallocation 40.000 lives could be saved annually in the US•$ 42.000 •35 = $ 1.5 million

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Societal Indicators

Societal Indicators used to rate “quality of life” in countries

Published by UN (UNDP) Many different indictors exist Include such parameters as: GDP/Capita, Life

Expectancy at Birth, literacy etc.HDI (1999)

1 Norway 0.9392 Australia 0.9363 Canada 0.9364 Sweden 0.9365 Belgium 0.9356 United States 0.9347 Iceland 0.9328 Netherlands 0.9319 Japan 0.92810 Finland 0.92511 Switzerland 0.924

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Social Indicators

e

dew

g

dgw

L

dL)1(

wwegL 1

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Societal Indicators

CAF for OECD Countries ( $ million )

0

0,5

1

1,5

2

2,5

3

3,5

4

4,5

Aus

tral

ia

Aus

tria

Bel

gium

Can

ada

Cze

ch R

epub

lic

Den

mar

k

Fin

land

Fra

nce

Ger

man

y

Gre

ece

Hun

gary

Icel

and

Irel

and

Italy

Japa

n

Kor

ea

Luxe

mbo

urg

Mex

ico

Net

herla

nds

New

Zea

land

Nor

way

Pol

and

Por

tuga

l

Spa

in

Sw

eden

Sw

itzer

land

Tur

key

Uni

ted

Kin

gdom

Uni

ted

Sta

tes

Ave

rage

OE

CD

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Individual Decisions

Also individuals take decision that increase life expectancy and reduces accident frequencies

For example:– Buy safer cars– Buy more healthy food– Go to the doctor more frequently– Etc.

How much increase in purchasing power is necessary to increase the life expectancy in a population by “e”

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Individual Decisions

0

10

20

30

40

50

60

70

80

90

0 5000 10000 15000 20000 25000 30000 35000 40000

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Societal Indicators

0

2

4

6

8

10

12

14

16

18

Austra

lia

Austri

a

Belgium

Canad

a

Czech

Rep

ublic

Denm

ark

Finlan

d

Franc

e

Ger

man

y

Gre

ece

Hunga

ry

Icela

nd

Irelan

dIta

ly

Japa

n

Korea

Luxe

mbo

urg

Mex

ico

Nethe

rland

s

New Z

ealan

d

Norway

Poland

Portu

gal

Spain

Sweden

Switzer

land

Turk

ey

United

King

dom

United

Sta

tes

Avera

ge O

ECD

$U

S m

illi

on

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Published Numbers

Published NCAF values in use in acceptance criteriaORGANISATION SUBJECT NCAF SOURCE

US Federal HighwayAdministration

Road Transport $2.5m (£1.6m) FHWA (1994)

UK Department ofTransport

Road transport £1.0 m (1998, uprated withGDP per capita)

DETR (1998)

UK Health & SafetyExecutive

Industrial safety As above or higher HSE (1999)

Railtrack (UK railinfrastructure controller)

Overground railways As above to £2.65m Railtrack (1998)

London Underground Ltd. Underground railways £2m ($2.9 m) Rose (1994)EU Road Transport € 1 million ($0.89m) Evans (1998)Norway All hazards NOK 10m ($1.1m) Norway (1996)

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Criterion?

For an OECD member country (excluding the newest members) the criteria is somewhere in the range $ 1.5 -3.0 million

Some uncertainties relates to: Fatalities as indicator or actual fatalities NCAF or GCAF Despite uncertainty different methods give surprisingly

consistent results In a QRA a factor of 2 is not much compared to the

uncertainty in the analysis In SRA the design variables are continuos, and we do not

know how sensitive the resulting dimensions are to the criterion

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Advantages in SRA

Consistency with QRA The decision is based on the derivative of PF with

respect to design variables only Not reliant on probability (the absolute number) Example: Mid ship bending moment

Table 1: GCAF/NCAF in US$ million for increases ofthe reliability index

Flat Bar L-Profile

2.53.09 0.402/-2.80 0.128/-3.073.093.50 1.76/-1.74 2.46/-0.7433.503.72 4.44/1.24 9.93/6.73