Fire risk analysis of structures and infrastructures: theory and application in highway tunnels.

Fire risk analysis of structures and
infrastructures: theory and
application in highway tunnels
CORSO DI PROGETTAZIONE STRUTTURALE ANTINCENDIO, AA: 2015-’16
1November 10 2015www.francobontempi.org
Konstantinos Gkoumas, PhD, PE
Facoltà di Ingegneria
Sapienza Università di Roma
Corso di Progettazione Strutturale Antincendio
Docente: Prof. Ing. Franco Bontempi

Outline
• System approach to fire safety design
• Risk/fire risk/risk analysis
• Risk assessment process
• Risk analysis
• Hazard analysis
• Risk acceptance
• Risk reduction
• Risk assessment of road tunnels using PIARC/OECD QRAM
• Case study: risk assessment of a long highway tunnel
• References
www.francobontempi.org
CORSO DI PROGETTAZIONE STRUTTURALE ANTINCENDIO
2
Fire risk analysis of structures
and infrastructures: theory and

3

• System approach to fire safety design
• Risk
- fire risk
- risk types
- risk analysis
4

System approach to fire safety design
MINOR
SPREAD
FIRE SPREADSTOP FIRE
suppression
Y
MAJOR
SPREAD
STRUCTURAL
INTEGRITY
AVOID
CASUALITIES
LOCALISED
DAMAGE
STRUCTURAL
FAILURES
N
mitigation
Y
N
fire safe design
Y
N
FIRE
robust design
Y
N
MAJOR
COLLAPSE
AVOID
DIRECT
DAMAGE
AVOID
COLLAPSE
1
2
3
4
0 preventionOBJECTIVE
fire safety design -
structural
fire safety design -
non structural
GLOBAL
SAFETY
LOSS OF
GLOBAL
SAFETY
AVOID
INDIRECT
DAMAGE
NY
The fire safety is framed in different
“safety levels”, corresponding to
different safety objectives.
5

(Fire) Risk Estimation*
*(following SFPE Handbook of Fire Protection Engineering)
Provide answer to the following questions
1. What could happen?
2. How bad would it be if it did happen?
3. How likely is it to happen
6

What is risk?
Risk can be defined as the probability that the harm or damage from a particular
hazard is realized.
Risk is measured in terms of consequences and likelihood (a qualitative description
of probability or frequency). In mathematical terms risk can be defined as:
risk = f (frequency or probability, consequence) (1)
In the case of an activity with only one event with potential consequences, a risk (R)
is the probability (P) that this event will occur multiplied with the consequences (C)
given the event occurs:
R = PC (2)
The risk of a system is the sum of the risks of all harmful events of that system:
(3)
𝑅𝑆 = 𝑅𝑖
𝑛
𝑖=1
7

Risk types
• Life safety risks are normally presented in two ways:
- Individual risk and
- Societal risk
• Individual risk:
The purpose of the individual risk is to ensure that individuals in the society
are not exposed to unacceptably high risks. It can be defined as the risk to any
occupant on the scene for the event/hazard scenario i.e. it is the risk to an
individual and not to a group of people.
• Societal risk:
Societal risk is not looking at one individual but is concerned with the risk of
multiple fatalities. People are treated as a group, there are no considerations
taken to the individuals within the group i.e. the definition of the risk is from a
societal point of view.
Source: Jönsson, 2007
8

What is risk analysis?
• A big family of different approaches, methods
and complex models combining various
methododical components for specific tasks
• Systematic analysis of sequences and interaction
effects in potential accidents, thereby identifying
weak points in the system and recognizing
possible improvement measures
• Risk analysis makes the quantification of risks
feasible
9

The risk assessment process
10

The risk assessment process
Start
Definition of the system
Hazard identification
Probability analysis Consequence analysis
Additional safety
measures
Risk estimation
Risk evaluation Risk criteria
Acceptable
risk?
Stop
Risk analysis
Risk evaluation
YES
NO
Risk reduction
11

Definition of the system (context establishment)
Define the operational environment and the context of the risk assessment
process
– Definition of the scope or the risk assessment process
• This includes determining the timeframe (e.g. from planning to dismantling), the
required resources and the depth of analysis required.
– Definition of the strategic and organizational context
• The nature of the organization in charge of the risk management and the
environment in which it operates is established
– Identification of the stakeholders (portatori di interesse) and objectives
• The relationships that are interdependent with the organization are defined, the
impacts that might occur are accounted for, as well as and what each is wanting
out of the relationship
– Determination of the evaluation criteria
• Decide what level of risk the organization is prepared to accept
12

a. What can happen
b. How can it happen
Means for hazard identification:
• Decomposition of the system into a number of
components and/or subsystems
• Identification of possible states of failure for the
considered system and sub-systems
• Identification of how the hazards might be realized
for the considered system and subsystems
Source: Faber, 2008
13

Hazard identification – system decomposition
A. Structure
1. Main components
(d) Foundations
(c) Towers
(b) Anchor systems
(a) Main cables
(h) Cable saddle
(e) Railway girder
(f) Highway girders
(g) Expansion joints
(e) Non str.elements
(a) Steel
(b) Concrete
(c) Prestressed c.
(d) Alluminium/iron
3. Materials
(f) Coating
4. Systems
(a) Electrical
(c) Hydraulics
(b) Mechanical
(e) Bitumen
(e) Plastic
2. Secondary comp.
(d) H.R. attachments
(c) TMD
(b) Buffers
(a) Hanger ropes
B. Users
1. Highway traffic
(b) Commercial
(a) Private
2. Railway traffic
(b) Commercial
(a) Private
(a) Heavy
(b) Hazard mat.
(c) Military
3. Exceptional traffic
C. Facilities
1. Over the bridge
(b) Railway
(a) Highway
2. By the bridge
(a) Highway
(b) Railway
(c) Toll booths
(d) Control center
(e) Parking
(a) Maritime traffic
3. Under the bridge
D. Dependencies
1. Power
3. Financial
2. Communications
4. Supplies
5. Emerg. Responce
(a) First aid
(b) Police
(c) Fire brigade
(d) Hospitals
6. Ext. Contractors
E. Linkage
1. Economy
3. Military
2. Social
F. Operation
1. Authorities
(b) Management
2. Aspects
(a) Bridge authorities
(b) Goverment
(c) Region
5. Personnel
(c) Maintenance
(a) Financial
(b) Other
(a) Technical
G. Technology
(a) GPS
(b) Accelerometers
(c) Strain gauges
(e) Thermometers
(g) CCTV
(f) WIM
(d) Seismographs
(h) Field equipment
1. Monitoring
2. Control
(a) Cable control
(d) Railway traffic
(c) Highway traffic
(b) TMD
3. Data transmission
(b) Wireless
(a) Cable
4. Computer center
(b) Software
(a) Hardware
(d) Internet/LAN
(c) Data bases
4. Regulations
3. Policies
4. Location
(c) External
HierarchicalHolographicModels(HHM)
(DefinedinHaimes,1981)
14

Risk analysis: hazard identification
• Qualitative methods
Studies based on the generic experience of personnel and do not
involve mathematical estimations.
• Quantitative methods
Mathematical estimations that rely upon historical evidence or
estimates of failures to predict the occurrence of an event.
• Semi-quantitative methods
Combination of the above (mostly, qualitative methods with
applied numerical values).
Source: Nolan, D. P. Handbook of Fire and Explosion Protection
Engineering Principles for Oil, Gas, Chemical, and Related Facilities, 1986
15

Source: Aven, T. Risk Analysis: Assessing Uncertainties beyond Expected Values and Probabilities.
John Wiley & Sons, 2008
Risk analysis: hazard identification
16

Hazard identification. Qualitative Methods
Checklist or Worksheet
A standardized listing which identifies common protection features required for typical
facilities is compared against the facility design and operation. Risks are expressed by
the omission of safety systems or system features.
Preliminary Hazard Analysis (PHA)
Each hazard is identified with potential causes and effects. Recommendations or known
protective measures are listed.
What-If analysis
A safety study which by which “What-If’ investigative questions (brainstorming
approach) are asked by an experienced team of a hydrocarbon system or components
under examination. Risks are normally expressed in a qualitative numerical series (e.g., 1
to 5).
HAZOP - HAZard and OPerability analysis (analisi di pericolo e operabilità)
A formal systematic critical safety study where deviations of design intent of each
component are formulated and analyzed from a standardized list. Risks are typically
expressed in a qualitative numerical series (e.g., 1 to 5) relative to one another.
Source: Nolan, D.P. 1986. Handbook of Fire and Explosion Protection Engineering Principles for …. Noyes, New Jersey
17

Hazard identification. Qualitative Methods
Event Trees (ET) –albero degli eventi
A mathematical logic model that mathematically and graphically
portrays the combination of events and circumstances in an
accident sequence, expressed in an annual estimation.
Fault Trees (FT) – alberi dei guasti
A mathematical logic model that mathematically and graphically
portrays the combination of failures that can lead to a specific main
failure or accident of interest, expressed in an annual estimation.
Failure Modes and Effects Analysis (FMEA)
A systematic, tabular method of evaluating the causes and effects
of known types of component failures, expressed in an annual
estimation.
Source: Nolan, D.P. 1986. Handbook of Fire and Explosion Protection Engineering Principles for …. Noyes, New Jersey
18

• Risk analysis
• Qualitative risk analysis
• Quantitative risk analysis
19

Risk analysis
• Risk analysis
– Probability- as the likelihood of the risk occurrence
– Impact - consequences if the risk occurs
• risk proximity, meant as the point in time during which
a risk will impact
• Risk analysis - methods
– Qualitative Risk Analysis, in which numbers and
probabilities are used not extensively or at all
– Quantified Risk Analysis (QRA)
– Probabilistic Risk Analysis (PRA), in which the system risk
is represented as a probability distribution
20

Risk analysis and system complexity
High-Probability/
Low-Consequences
(HPLC)
Low-Probability/
High-Consequences
(LPHC)
High-Probability/
Low-Consequences
(HPLC)
Low-Probability/
High-Consequences
(LPHC)
High-Probability/
Low-Consequences
(HPLC)
Low-Probability/
High-Consequences
(LPHC)
High-Probability/
Low-Consequences
(HPLC)
Stochastic
Complexity
Deterministic
Analysis
Methods
Qualitative
Risk
Analysis
Quantitative/Probabilistic
Risk
Analysis
Pragmatic
Risk
Scenarios
Stochastic
Complexity
Deterministic
Analysis
Methods
Qualitative
Risk
Analysis
Quantitative/Probabilistic
Risk
Analysis
Pragmatic
Risk
Scenarios
21

Qualitative Risk analysis
• Qualitative Risk Analysis is the simplest method of risk analysis, and
generally is used during the preliminary analysis phases.
• It consists in using subjective assessments of risks, and consequently, in
ranking them in a subjective manner.
• Sources for information to be used in the analysis can be drown from
previous experiences, history of events and consultation of experts.
• The ranking of risks is qualitative, e.g. risk (1) > risk (2) > risk (3),
while a description can be added. Eventually, a likelihood-consequence
matrix can be constructed.
• The biggest drawback of QRA is that there is neither a clear indication
of the risk’s magnitude nor an absolute scale of how serious the risk
might be, so, for a comprehensive risk analysis of more complex
systems, quantitative methods should be preferred.
22

Qualitative risk analysis methods: risk matrix
• A risk matrix typically provides a discrete partitioning of relative consequences
along one dimension and relative likelihood along the other.
• The entry in each matrix cell may include a description of hazards known or
believed to have that combination of consequence severity and likelihood.
Source: NFPA, SFPE Handbook of
Fire Protection Engineering,
3rd edition, 2002
Source: Furness, A., Muckett, M.
Introduction to Fire Safety
Management. Elsevier, 2007.
23

Qualitative risk analysis methods: SWOT analysis
24
Strengths (forza): characteristics of
the business or project that give it
an advantage over others.
Weaknesses (debolezza):
characteristics that place the
business or project at a
disadvantage relative to others
Opportunities (opportunità):
elements that the project could
exploit to its advantage
Threats (minacce): elements in the
environment that could cause
trouble for the business or project

Quantitative Risk analysis
• Quantified (or quantitative) Risk Analysis (QRA) combines
the consequences and frequencies of accident scenarios to
estimate the level of risk.
• In respect to the Qualitative method, QRA implicates the
acquaintance of probabilities that describe the likelihood of
the outcomes and their consequences.
• QRA started with the chemical industries from the 70s and
the offshore industry from the 80s.
• QRA is traditionally expressed through the decomposition
of the system. This frequently is done by the use of event
trees and fault trees.
25

FTA and ETA
• ETA (event tree analysis – albero degli eventi)
provides a structure for postulating an initiating
event and analyzing the potential outcomes
• FTA (fault tree analysis – albero dei guasti)
begins with a failure and provides a structure to
look for potential causes
26

Event tree analysis
• Event trees pictorially represent the logical order in which
events in a system can occur. Event trees begin with an
initiating event, and then the consequences of the event are
followed through a series of possible paths.
• Each path is assigned a probability of occurrence. Therefore,
the probability of the various possible outcomes can be
calculated.
• Event tree analysis is based on binary logic, in which an
event has either happened or not, or a component has failed
or has not.
• It is valuable to analyze the consequences arising from a
failure or undesired event.
27

Event tree analysis: illustration (1)
28
Event trees are helpful in
considering all the possible
outcomes (on the right-hand side)
from an initiating event (on the
left-hand side), which is usually
ignition for fire risks.
The frequency of the initiating
event can be estimated from fire
report data, and the conditional
probabilities of the sub-events can
be quantified from fire report data
or fault trees.

Event tree analysis: illustration (2)
Source: Fire Risk in Metro Tunnels and Stations Hyder Consulting
29

Fault tree analysis
30
Fault trees are helpful in
quantifying the
probability of a top
event of concern (such
as the failure of a fire
protection system) from
all the potential root
causes (at the bottom),
again quantified from fire
report data.

Fault tree analysis
general conclusion (event)
• Fault trees look like a complement
to event trees.
• The idea is to begin with a general
conclusion (event) and, using a
top-down approach, to generate a
logic model that provides for both
qualitative and quantitative
evaluation of the system
reliability.
Source: google pictures search “Fault tree”
31

Fault tree analysis - symbols
Basic event - failure or error in a system component or element
(example: switch stuck in open position)
Initiating event - an external event (example: bird strike to aircraft)
Undeveloped event - an event about which insufficient information is
available, or which is of no consequence
Conditioning event - conditions that restrict or affect logic gates
(example: mode of operation in effect)
Intermediate event: can be used immediately above a primary event to
provide more room to type the event description.
Source: Fault Tree Handbook. Nuclear Regulatory Commission. NUREG–0492
32

Fault tree analysis – gate symbols
OR gate - the output occurs if any input occurs
AND gate - the output occurs only if all inputs occur (inputs are
independent)
Exclusive OR gate - the output occurs if exactly one input occurs
Priority AND gate - the output occurs if the inputs occur in a specific
sequence specified by a conditioning event
Inhibit gate - the output occurs if the input occurs under an enabling
condition specified by a conditioning event
Source: Fault Tree Handbook. Nuclear Regulatory Commission. NUREG–0492
33

Advantages and disadvantages of FTA
• Disadvantages
1. There is a possibility of oversight and omission of significant failure
modes.
2. It is difficult to apply Boolean logic to describe failures of system
components that can be partially successful in operation and thereby
affect the operation of the system, e.g. leakage through a valve.
3. For the quantitative analysis there is usually a lack of pertinent failure
data. Even when there are data they may have been obtained from a
different environment.
• Advantages
1. It provides a systematic procedure for identifying faults that can exist
within a system.
2. It forces the analyst to understand the system thoroughly.
Source: Hasofer et al. 2007, Risk Analysis in Building Fire Safety Engineering
34

Cause – consequence diagrams
• The combination of fault trees and event trees leads to the creation of
cause-consequence diagrams.
Time
Revealed from the
Monitoring system
S3
S2
S1
Consequences
Infraction of traffic law
Improper speed
Road condition
Vehicle flow
blocked
YES
YES
NO
NO
Other
Iniziative event
Road
Accident
35

SCENARIO PROBABILITY
A1 PA*P1
A2 PA*(1-P1) *P2 *P3
A3 PA*(1-P1) *P2*(1-P3 )
A4 PA*(1-P1) *(1-P2)*P3
A5 PA*(1-P1) *(1-P2)*(1-P3)
B1 PB*P1
B2 PB*(1-P1) *P2 *P3
B3 PB*(1-P1) *P2*(1-P3 )
B4 PB*(1-P1) *(1-P2)*P3
B5 PB*(1-P1) *(1-P2)*(1-P3)
C1 PC*P1
C2 PC*(1-P1) *P2 *P3
C3 PC*(1-P1) *P2*(1-P3 )
C4 PC*(1-P1) *(1-P2)*P3
C5 PC*(1-P1) *(1-P2)*(1-P3)
Triggering
event
Fire
ignition
1. Fire
extinguished
by personnel
2. Intrusion of
fire fighters
Arson
Explosion
Short
circuit
Cigarette
fire
YES (P1)
NO (1-P1) YES (P2)
NO (1-P2)
Scenario
Other
A1
A2
A3
A4
A5
3. Fire
suppression
YES (P3)
NO (1-P3)
YES (P3)
NO (1-P3)
Fire
location
AREA A
(PA)
YES (P1)
NO (1-P1) YES (P2)
NO (1-P2)
B1
B2
B3
B4
B5
YES (P3)
NO (1-P3)
YES (P3)
NO (1-P3)
AREA B
(PB)
YES (P1)
NO (1-P1) YES (P2)
NO (1-P2)
C1
C2
C3
C4
C5
YES (P3)
NO (1-P3)
YES (P3)
NO (1-P3)
AREA C
(PC)
Quantified Risk Analysis: cause – effect diagrams
36

F (frequency) – N (number of fatalities) curve
• An F–N curve is an alternative way of describing the
risk associated with loss of lives.
• An F–N curve shows the frequency (i.e. the expected
number) of accident events with at least N fatalities,
where the axes normally are Logarithmic.
• The F–N curve describes risk related to large-scale
accidents, and is thus especially suited for
characterizing societal risk.
Source: Aven, T. Risk Analysis: Assessing Uncertainties beyond Expected Values and Probabilities. John Wiley & Sons, 2008
37

Source: Aven, T. Risk Analysis: Assessing Uncertainties beyond Expected Values and Probabilities. John Wiley & Sons, 2008
38

Source: NFPA, SFPE Handbook of Fire Protection Engineering, 3rd edition, 2002
39

Index
• Risk acceptance
- ALARP
- Human life (!)
40

Risk acceptance
Source: Persson, M. Quantitative Risk Analysis Procedure for the Fire Evacuation of a Road Tunnel -An Illustrative Example. Lund, 2002
41

Risk acceptance – ALARP (1)
RISK MAGNITUDE
INTOLERABLE
REGION
As
Low
As
Reasonably
Practicable
BROADLY ACCEPTABLE
REGION
Risk cannot be justified
in any circumstances
Tolerable only if risk
reduction is impracticable
or if its cost is greatly
disproportionate to the
improvement gained
Tolerable if cost of
reduction would exceed
the improvements gained
Necessary to maintain
assurance that the risk
remains at this level
As
Low
As
Reasonably
Achievable
RISK MAGNITUDE
INTOLERABLE
REGION
As
Low
As
Reasonably
Practicable
BROADLY ACCEPTABLE
REGION
Risk cannot be justified
in any circumstances
Tolerable only if risk
reduction is impracticable
or if its cost is greatly
disproportionate to the
improvement gained
Tolerable if cost of
reduction would exceed
the improvements gained
Necessary to maintain
assurance that the risk
remains at this level
As
Low
As
Reasonably
Achievable
42

Risk acceptance – ALARP (2)
Source: google pictures search “ALARP”
43

Monetary values – cost of human life (!)
• What is the maximum amount the society (or the decision-maker) is willing
to pay to reduce the expected number of fatalities by 1?
• Typical numbers for the value of a statistical life used in cost-benefit analysis
are 1–10 million euros. The Ministry of Finance in Norway has arrived at a
value at approximately 2 million euros.
Guideline values for the cost to
avert a statistical life (euros), used
by an oil company
Source: Aven, T. Risk Analysis: Assessing
Uncertainties beyond Expected Values and
Probabilities. John Wiley & Sons, 2008
44

Risk reduction
45

Risk reduction
Source: Brussaard et al. 2004. The Dutch Model for the Quantitative Risk Analysis of Road Tunnels.
46

Risk reduction (2) - monitoring and system response
Time
1
3
2
Accident Accident evolution
Pre-accident
situation
Pre-accident
Monitoring
Pre-accident
System Response
Accident
Localization
Evolution of System Response
Accident evolution Monitoring
System
Response
47

48
Parte 2a: Analisi del rischio di gallerie stradali
Source:
"Risk analysis for severe traffic accidents in road tunnels". “Laurea Magistrale”
(M.Sc.) Thesis at the Sapienza University of Rome, Faculty of Civil and Industrial
Engineering. Candidate: Carmine Di Santo. Final grade: 110/110 “Summa cum
Laude”. Advisor: Prof. Franco Bontempi, co-advisor: Konstantinos Gkoumas, PhD.
Defended in January 2015.

www.francobontempi.org 49
The issue of SAFETY in tunnels
Mont Blanc Tunnel Fire (1999)
39 Fatalities
Italia (Courmayer) – France (Chamonix)
single – bore, bidirectional tunnel
Length = 11.6 km
St. Gotthard Tunnel Fire (2001)
11 Fatalities
Switzerland (Göschenen) – Switzerland (Airolo)
Length = 16,9 km
Frejus Tunnel Fire (2005)
2 Fatalities
Italia (Bardonecchia) – France (Modane)
Length = 12,9 km

The issue of SAFETY in tunnels
Directive
2004/54/EC
Quantitative Risk
Analysis
Objectives
Parameters
Requirements
Transport of Dangerous Goods through road tunnels
OECD/PIARC/EU
Quantitative Risk Assessment Model
• OECD (Organisation of Economic Co-
operation and Development)
• PIARC (World Road Association)
• European Commission
• France (INERIS), Canada (WS Atkins),
UK (IRR)

PIARC/OECD QRAM OUTPUTS
𝑅 = 𝐹 ∙ 𝐶
F probability of occurrence / frequency
C extent of damage / consequences
• Fatalities
• Injured
• Destruction of buildings and structures
• Environmental Damage
PIARC/OECD
QRAM
Societal Risk
Individual Risk F[1/year]
N [Fat]
𝐸𝑉𝑠 =
𝑖=0
∞
𝐹 𝑁𝑖 ∙ 𝑁𝑖
The risk to which a group of people
is subjected in case a scenario s
occurs.
Prob. that a person (among local
population and within a certain
distance from the road) dies due to
the scenario s.

PIARC/OECD QRAM OUTPUTS
𝑅 = 𝐹 ∙ 𝐶
F probability of occurrence / frequency
C extent of damage / consequences
• Fatalities
• Injured
• Destruction of buildings and structures
• Environmental Damage
PIARC/OECD
QRAM
Societal Risk
F[1/year]
N [Fat]
𝐸𝑉𝑠 =
𝑖=0
∞
𝐹 𝑁𝑖 ∙ 𝑁𝑖
The risk to which a group of
people is subjected in case a
scenario s occurs.
SR = F(N) ∙ N
The F-N diagrams may be
applied to illustrate the risk
profile for a specific hazard
such as a fire in a road tunnel.
Expected amount of victims
in a certain time period

F-N curve construction process flow
1 – Dangerous Goods and
Accident Scenarios selection
2 – Effect j (due to the scenario s )
and its Range from the epicentre
Ej=f(d) Rj
3 – Mortality Rate within the range Rj
%LETHj
4 – Mortality Rate corrected
considering the possibility of escape
%LETHj=f(tevac)
5 – Scenario s Probability of
occurrence fs
6 – Number of victims due to the
scenario s
N= jNj=f(Rj, Dru, Ljam, %LETHj)
7 – F-N curve for the scenario s and
its relative Expected Value

Tunnel risk assessment procedure
Data Collection
Data Preparation
Risk Calculation
Using QRAM
Is Risk
acceptable?
NO
Additional risk
reduction
measures
YES
End
Mean Data:
• Traffic
• Accident Frequencies
• Tunnel Geometry
• Tunnel Equipment
• .....
Risk Acceptability:
• Absolute criteria
• Relative criteria
Risk
Analysis
Prevention Measures:
• Signs and road markings
• Lighting
• Traffic control
• Route geometry
• Prohibition of access to
certain types of vehicles
Protection Measures:
• Monitoring
• Fires/Accident Detection
system
• Ventilation system
• Emergency lighting
• Protection of escape routes
• System of emergency
management
• Emergency Procedures

Societal Risk Acceptability criteria
Absolute
Criteria
𝐸𝑉𝑠 ≤ 𝐸𝑉𝑙𝑖𝑚𝑖𝑡 (𝐸𝑉𝑠: Expected Value of Victims)
0,000001
0,00001
0,0001
0,001
0,01
0,1
1
1 10 100
F(N)[1/year]
N
Tollerable Risk Line Acceptable Risk Line
Not Acceptable area
ALARP
Acceptable area
As Low As Reasonably Practicable
ALARP area:
• prevention and/or
mitigation actions must be
taken to reduce the risk, as
far as reasonably
practicable
• Cost – Benefit Analysis

Societal Risk Acceptability criteria
Relative Criteria 𝐸𝑉𝑠 ≤ 𝐸𝑉𝑠,𝑟𝑒𝑓
1,00E-06
1,00E-05
1,00E-04
1,00E-03
1,00E-02
1,00E-01
1,00E+00
1,00 10,00 100,00 1000,00
Tunnel Tunnel Reference
Applying the same calculation method, compare the examined risk with:
• the risk of an alternative route
• that calculated for a reference tunnel, which must have characteristics similar to the one
examined, but with all the safety requirements required by the relevant regulations

Probit analysis
Is a type of regression used to analysing the relationsheep between a stimulus
(dose) and “all or nothing” (such as death) response
The following items must be identified:
• The toxicant
• The target
• The effect or response to be monitored
• The dose range
• The period of the test
Biological organisms respond differently
to the same dose of a toxicant.
Each individual is exposed to the same
dose and the response is recorded.
Curves are frequently represented by a
normal or Gaussian distribution
A Gaussian or normal distribution
representing the biological response to
exposure to a toxicant.
𝑓 𝑥 =
1
𝜎 2𝜋
𝑒
−
𝑥−𝜇 2
2𝜎2
probability (or fraction) of individuals
experiencing a specific response
x is the response, σ is the standard
deviation, and μ is the mean.
σ determines the shape and μ characterize the location of the curve with respect to the x axis
the percentage
of individuals
affected for a
specified
response interval
• The toxicological experiment is repeated for a number
of different doses, and normal curves are drawn.
• The standard deviation and mean response are
determined from the data for each dose.
FINNEY 1971

Probit analysis
A complete dose-response curve is produced
by plotting the cumulative mean response at
each dose.
The response is plotted versus the logarithm of the
dose, to provide a much straighter line in the
middle of the response curve
For comparison purposes the dose that results
in 50% lethality of the subjects is frequently
reported. This is called the LD50 dose
(lethal dose for 50% of the subjects).
For computational purposes the response
versus dose curve is not convenient.
For single exposures the probit method is
particularly suited, providing a straight-line
equivalent to the response-dose curve.
P or RATIO =
1
2𝜋
−∞
Pr−5
𝑒−
1
2
𝑢2
𝑑𝑢
provides a relationship between the
probability P and the probit variable Pr.
Many methods exist for representing the
response-dose curve.

Probit analysis
Transformation from Percentages to Probits
The probit relationship transforms the sigmoid shape of the normal response versus
dose curve into a straight line when plotted using a linear probit scale
The probit variable Pr is computed from
𝑃𝑟 = 𝑎 + 𝑏 ln 𝐷
P or RATIO =
1
2𝜋
−∞
Pr−5
𝑒−
1
2 𝑢2
𝑑𝑢

1) Dangerous goods and accident scenarios
Liquefied
Petroleum Gas
(LPG)
Motor Spirit
Acrolein
(Toxic Liquid)
Chlorine
(Toxic Gas)
Ammonia
(Toxic Gas)
Liquified CO2
Boiling Liquid Expanding
Vapor Explosion (BLEVE)
Toxic Release in the air
Torch Fire
Pool Fire
Vapor Cloud Explosion (VCE)
Vapor Cloud Explosion
BLEVE
No DGs 20MW Fire
100 MW Fire

0
20
40
60
80
100
120
140
0,00 10,00 20,00 30,00 40,00 50,00 60,00 70,00
qr[kW/m2]
d [m]
2) scenario physical effects
Thermal Effects Pressure Effects Toxicity Effects
• Fires
• VCEs
• BLEVEs
• VCEs
• BLEVEs
• Fires (smokes)
• Toxis Releases in
air
qr [kW/m2] = f(d)
Radiative Heat Flux
which is experienced
by the receiver per
unit area
Side-on Blast Overpressure
∆Ps [bar] = f(d)
Wave Positive-phase
t+[bar] = f(d)
Concentration
C [ppmv] = f(d)
Effect
Intensity
Distance from
the epicentre

3) Physiological effects
𝐹𝑖𝑛𝑛𝑒𝑦,1971
𝑅𝑎𝑡𝑖𝑜 = 𝑓(Pr) =
−∞
𝑃𝑟−5
𝑒
−
1
2
𝑢2
𝑑𝑢
𝑃𝑟𝑜𝑏𝑖𝑡 𝑇𝑟𝑎𝑛𝑠𝑓𝑜𝑟𝑚𝑎𝑡𝑖𝑜𝑛
𝑃𝑟𝑗 = 𝑎 + 𝑏 ln 𝐸𝑗 ∙ 𝑡 𝑒𝑥𝑝,𝑗
Thermal
Pressure
Toxicity

4) probability of occurrence of the scenarios
𝑓𝑠,𝑖 = 𝑃𝑠,𝑖 ∙ 𝑓𝑎𝑐𝑐,𝑖 ∙ 𝑇𝐻𝑖 ∙ 𝐿𝑖 ∙ 24 ∙ 365 ∙ 10−6
Frequency of occurrence of the scenario s on the section i in a year [scen/year]
Conditional probability
that scenario j occurs
once an accident
implying an HGV has
taken place on the
section i
Annual frequency of accidents involving HGVs on the section i
[acc/(MVkm*year)]
Traffic of HGVs passing through the section i in one hour
[veh/h]
𝑓𝑎𝑐𝑐,𝑖 =
𝐻𝐺𝑉𝑎𝑐𝑐,𝑖
𝑇𝐻𝑖 ∙ 𝐿𝑖
FaultTreeAnalysis
• HGV/h
• % DG-HGV
• DGs types
• Accidents/year
𝐏 = 𝐏𝟏. 𝟏 ∙ 𝐏𝟏. 𝟐 + 𝐏𝟐. 𝟏 ∙ 𝐏𝟐. 𝟐

5) Possibility of escape or of finding shelter
𝐷𝑖𝑗 =
𝑡 𝑖𝑛
𝑡 𝑜𝑢𝑡
𝐷𝑗 𝑡 𝑑𝑡
Dose of physical effect j
that affects a man
crossing the segment i
𝐷𝑗,𝑇𝑂𝑇 =
𝑖
𝐷𝑖𝑗
Total dose
received during
the escape
𝑃𝑟𝑗 = 𝑎 + 𝑏 ∙ ln 𝐸𝑗 ∙ 𝑡 𝑒𝑥𝑝,𝑗
𝐷𝑗,𝑇𝑂𝑇
𝑡 𝑒𝑣𝑎𝑐
𝑡 𝑝𝑟𝑒 𝑡 𝑚𝑜𝑣
Pre-movement
time
Movement
time
𝑣
𝑑 𝑠𝑎𝑓𝑒𝑡𝑦
𝑡 𝑝𝑟𝑒 = 𝑡 𝑝𝑟𝑒−𝑏𝑝𝑠 ∙ 𝑤 𝑒𝑓𝑓
𝑤 𝑒𝑓𝑓 =
5
𝑎𝑣𝑒𝑟𝑎𝑔𝑒 𝑟𝑎𝑡𝑖𝑛𝑔 𝑜𝑓 𝑝𝑎𝑟𝑎𝑚𝑒𝑡𝑒𝑟𝑠
• Alertness (4)
• Mobility (4)
• Social Affiliation (3)
• Commitment (3)
• Familiarity (2)
• Distance from the accident (by calc)
• Perceived severity (4)
Occupant
Response Model
𝑡 𝑟𝑒𝑐 + 𝑡 𝑟𝑒𝑠

6) Societal risk indicators
Number of Victims
tsce Occurs the accident
scenario
tbarr Delay for stopping
approaching traffic
tjam min (tsce, tbarr).
N = 𝑅 ∙ 𝐷 𝑅𝑈𝐽 + 𝑅 − 𝐿𝑗𝑎𝑚 ∙ 𝐷 𝑅𝑈𝐹 ∙ %𝐿𝐸𝑇𝐻
Road Users Density in a Traffic Jam [users/m]
Road Users Density in a Fluid Traffic [users/m]

7) Societal risk indicators
F-N curve construction
Each scenario s may appear as different events Ei depending on:
 the section of the path being considered (section i)
 the accident location on the section
 the traffic direction (A, B)
 the reference period of the day (QUIET, NORMAL, PEAK)
 ....
Event Event Frequency Fatalities Cumulative Frequency
Ei fi Ni Fi
[-] [1/year] [Fat] [1/year]
E1 f1 N1 F1 = f1
E2 f2 N2 F2 = f1+f2
E3 f3 N3 F3 = f1+f2+f3
E4 f4 N4 F4 = f1+f2+f3+f4
... ... ... ...
En fn Nn Fn = f1+f2+f3+f4+...+fn
Scenario "s"
F[1/year] N [Fat]
𝐸𝑉𝑠 =
1
+∞
)𝐹(𝑁 𝑑𝑁

Parte 2b: Analisi del rischio della galleria St. Demetrio

Tunnel St. Demetrio
Motorway Catania – Syracuse
(European route E45)
ANAS s.p.a.
Construction:
2007-2009
Pizzarotti & C. S.p.A. Parma
Courtesy of Dr. Luigi Carrarini
(ANAS S.p.A.)
Courtesy of Ing. Alessandra Lo Cane
(M.I.T.)

Tunnel St. Demetrio
(Central Design Management ANAS S.p.A.)
Height from the Roadway to the Inner Wall 8.06 [m]
Road Platform Width 11.2 [m]
Cross Sectional Area 87.31 [m
2
]
Natural Tunnel
TWIN BORE TUNNEL,
ONE DIRECTION PER BORE
Polycentric Circular Section
Traditional Excavation
Bore in direction SOUTH (Syracuse)
portal of entry [km] 4+800
portal altitude above sea level [m] 10642
portal of exit [km] 7+695
Length [km] 2895
maximum longitudinal slope [%] 0.32
minimum longitudinal slope [%] 0.32
average longitudinal slope [%] 0.32
Bore in direction NORTH (Catania)
portal of entry [km] 7+698
portal of exit [km] 4+750
Length [km] 2949
maximum longitudinal slope [%] -0.32
minimum longitudinal slope [%] -0.32
average longitudinal slope [%] -0.32
Catania – Syracuse (E45), ANAS s.p.a.
2007-2009, Pizzarotti & C. S.p.A. Parma

Tunnel St. Demetrio: equipment & traffic data
• Pedestrian Bypass every 300m
• Bypass Carriageable every 900m
• Control Centre → Catania
• CCTV cameras placed every 282m
• CO sensors
• Smoke Meters (Opacimeters)
• Linear Thermal Sensors (heat sensing
cable)
• Variable Message Panels every 300m
• SOS stations every 200m
9 Jet Fan
10 Jet Fan 9 Jet Fan
9 Jet Fan
Equipment Emergency Ventilation System
Longitudinal Ventilation
average speed (on the cross section) of
3 m/s in the direction of traffic
time of fire detection (via thermo sensitive
cable) of 3 minutes from the ignition
a time of 5 minutes for the emergency
ventilation establishment

Tunnel St. Demetrio: equipment & traffic data
Traffic
QUIET NORMAL PEAK
AADT = 21190 veh/day
(1 direction)
22÷07
325 veh/h
HGV-ratio = 2%
vcar = 126.4 km/h
vHGV = 90.5 km/h
1050 veh/h
HGV-ratio = 10%
vcar = 126.4 km/h
vHGV = 90.5 km/h
1553 veh/h
HGV-ratio = 11.7%
vcar = 114.5 km/h
vHGV = 82 km/h
SOUTH NORTH
QUIET 1 1
NORMAL 7 3
PEAK 12 5
DG-HGV / h
63% Flammable Liquids (motor spirit, diesel oil, etc.)
31% LPG
6% Others
[acc /(MVkm*year)] [acc /(veh*km*year)]
SOUTH 0.161 0.000000161
NORTH 0.160 0.000000160
facc

21 - TUNNEL 3
2 3 - TUNNEL1
SOUTH (Syracuse)
NORTH (Catania)
x
Tunnel St. Demetrio: QRAM input data
Accident Scenarios
Tunnel
QRAM Model
Average number of people in a light vehicle [-] 2
Average number of people in a HGV [-] 1.1
Average number of people in a Bus/Coach [-] 40
Bus/Coaches ratio [-] 0.01
Delay for stopping approaching traffic [s] 9000
Area (Urban/Rural) [-] urban
Average density of population [hab/km2
] 0.01
DG transport correction factor [-] 1.00E+00
Traffic & Population Data
W (effective width) [m] 11
H (effective height) [m] 7.9
A (open cross sectional area) [m
2
] 86.9
Cam (camber) [%] 0
Gs (Segment gradient) [%] 0.32
VnN (volume flow rate along tunnel at nodes) [m3
/s] 0
VnE (volume flow rate along tunnel at nodes) [m3
/s] 261
Ad (open area of discrete drains) [m2
] 0.075
Xd (interval between drains) [m] 20
Xe (average spacing between emergency exits) [m] 300
Ecom (emergency coms) → 1, 2 o 3 [-] 3
Tunnel Data

Tunnel St. Demetrio: F-N curve in the south direction
1,00E-06
1,00E-05
1,00E-04
1,00E-03
1,00E-02
1,00E-01
1,00E+00
1,00 10,00 100,00 1000,00
FCUM[acc/year]
N [FAT]
Tollerable Risk Line
Acceptable Risk Line
EV [Fat/year] 1.68E-02

Tunnel St. Demetrio: QRAM Sensitivity analysis
input parameter Variation Initial Value Final Value Initial Value Final Value
0 0.01 0.00 0.01 0.00
equal to HGV ratio 0.01 0.02; 0.1; 0.117 0.01 0.02; 0.1; 0.117
0.15 - 0.15 0.30 ; 0.00 0.15 ; 0.15 0.30 ; 0.00 0.15 ; 0.15
0 - 0.30 0.30 ; 0.00 0.00 ; 0.30 0.30 ; 0.00 0.00 ; 0.30
1 2 1 2 1
1.5 2 1.5 2 1.5
2.5 2 2.5 2 2.5
3 2 3 2 3
1.5 1.1 1.5 1.1 1.5
2 1.1 2 1.1 2
3 1.1 3 1.1 3
x 10 1.61E-07 1.61E-06 1.60E-07 1.60E-06
x 10-1
1.61E-07 1.61E-08 1.60E-07 1.60E-08
x 10-1
1.00 0.10 1.00 0.10
x 10 1.00 10.00 1.00 10.00
2.5 0.00 2.50 0.00 2.50
4.12 0.00 4.12 0.00 4.12
1 3 1 3 1
2 3 2 3 2
A,B: 0 0.32 0.00 0.32 0.00
A,B: 3 0.32 3.00 0.32 3.00
A: -0.32 0.32 -0.32 - -
B: -0.32 - - 0.32 -0.32
A,B: -3 0.32 -3.00 0.32 -3.00
1 2 1 2 1
3 2 3 2 3
XI Type of Construction (1 Circular, 2 Rectangualar cross-section) 2 [-] 1 2 1 2
105 0.00 105.00 0.00 -105.00
210 0.00 210.00 0.00 -210.00
200 261.00 200.00 -261.00 -200.00
300 261.00 300.00 -261.00 -300.00
REVERSE 261.00 -261.00 -261.00 261.00
0 0.075 0.00 0.075 0.00
0.15 0.075 0.15 0.075 0.15
1 3 1 3 1
2 3 2 3 2
200 300.00 200.00 300.00 200.00
400 300.00 400.00 300.00 400.00
1 150 1 150 1
2 150 2 150 2
3 150 3 150 3
4 150 4 150 4
5 150 5 150 5
10 150 10 150 10
XVII
Safety
equipment
XII
XIII
XIV
XV
XVI
VII
VIII
IX
X
Changes to
the
structure
Frequency
of
Accidents
I
II
Bus Coaches Ratio (for each period: QUIET, NORMAL, PEAK)
Propane in Bulk ratio - Propane in Cylinder ratio
Average Number of People in a Light Vehicle
Average Number of People in a HGV
III
IV
TRAFFIC
V
VI
Average Spacing between Emergency Exits
Delay for Stopping Approaching Traffic
Accidents Frequency (facc)
DG-HGV transport correction factor
Camber (transversal slope)
Ground Type: 1 (Bedrock), 2 (Fragmented), 3 (Fragmented and
Under Water
Segments Gradient
Number of Lanes
[m3/s]
Normal Longitudinal Ventilation, Volume Flow Rate along tunnel (at
each node)
Emergency Longitudinal Ventilation, Volume Flow Rate along tunnel
(at each node)
Open Area of discrete Drains
Emergency Coms: 1 (bell/siren), 2 (Public Address system)
[min]
[-]
[-]
[m2
]
[m3
/s]
Societal Risk A - SOUTH Syr B - NORTH Cat
[-]
[%]
[-]
[%]
[-]
[-]
[acc/(veh*
km*year)]
[pass]
[pass]
[-]

1,00E-03
1,00E-02
1,00E-01
initialcurve
Busratio=0
BusCoachesRatio=HGVRatio
LPGinBulk=LPGinCylinder=0.15
LPGinCylinder=0.30
PeopleinaLightVehicle=1
PeopleinaLightVehicle=1.5
PeopleinaLightVehicle=2.5
PeopleinaLightVehicle=3
PeopleinaHGV=1.5
PeopleinaHGV=2
PeopleinaHGV=3
faccx10
faccx10-1
DG-HGVcorrectionfactor*10-1
DG-HGVtransportcorrectionfactor*10
Camber=2.5
Camber=4.12
Ground(BadRock):1
GroundType(Fragmented):2
SegmentGradient=0
SegmentGradient=3
SegmentGradient(SOUTH)=-0.32
SegmentGradient(NORTH)=-0.32
SegmentGradient=-3
NumberofLanes1
NumberofLanes3
Construction2(Rectangualarcross-section)
NormalLongitudinalVentilation105
NormalLongitudinalVentilation210
OpenAreaofdiscreteDrains=0
OpenAreaofdiscreteDrains*2
EmergencyComs=1(bell/siren)
EmergencyComs=2(PublicAddresssystem)
EmergencyLongitudinalVentilation200
EmergencyLongitudinalVentilation300
EmergencyLongitudinalVentilation→ReverseFlow
AverageSpacingbetweenEmergencyExits=200
AverageSpacingbetweenEmergencyExits=400
DelayforStoppingTraffic=1min
EVs in Direction South
Tunnel St. Demetrio: Sensitivity analysis results
Traffic
Frequency
of accidents
Structure
details
Safety
equipment
Number
of Lanes
facc x
10
DG-HGV
factor x 10
Delay for stopping
approaching trafficBUS ratio

1,00E-07
1,00E-06
1,00E-05
1,00E-04
1,00E-03
1,00E-02
1,00E-01
1,00E+00
1,00 10,00 100,00 1000,00
initial curve
Delayfor Stopping Approaching Traffic = 1 min
Delay for Stopping Approaching Traffic = 5 min
Sensitivity to parameter: “delay for stopping approaching traffic”

1,00E-07
1,00E-06
1,00E-05
1,00E-04
1,00E-03
1,00E-02
1,00E-01
1,00E+00
1,00 10,00 100,00 1000,00
initial curve
Number of Lanes (for every section and in both directions) = 1
Number of Lanes (for every section and in both directions) = 3
𝑁 = 𝑅 ∙ 𝐷 𝑅𝑈𝐽 ∙ %𝐿𝐸𝑇𝐻
Sensitivity to parameter: “number of lanes”

1,00E-07
1,00E-06
1,00E-05
1,00E-04
1,00E-03
1,00E-02
1,00E-01
1,00E+00
1,00 10,00 100,00 1000,00
initial curve
facc x 10
facc x 10-1
𝑓𝑖𝑗 = 𝑃𝑖𝑗 ∙ 𝑓𝑎𝑐𝑐,𝑖 ∙ 𝑇𝐻𝑖 ∙ 𝐿𝑖 ∙ 24 ∙ 365 ∙ 10−6
Sensitivity to parameter: “HGVs accident frequency”

1,00E-07
1,00E-06
1,00E-05
1,00E-04
1,00E-03
1,00E-02
1,00E-01
1,00E+00
1,00 10,00 100,00 1000,00
initial curve
Propane in Bulk ratio =Propane in Cylinder ratio =0.15
Propane in Cylinder ratio = 0.30
Sensitivity to parameter: “LPG (Liquefied Petroleum Gas) ratio”

conclusions
The parameters that most affect the risk curve:
• Density of people on the road
• Traffic (veh/h)
• Bus ratio (%)
• Number of lanes
• Delay for stopping approaching traffic
• Average vehicle occupancy
• Accident scenarios frequency [scen/year]
• facc
• DG-HGV traffic
• HGV traffic
• Proportion of each DG
𝑓𝑖𝑗𝑘 = 𝑃𝑖𝑗𝑘 ∙ 𝑓𝑎𝑐𝑐_𝐷𝐺,𝑖 ∙ 𝑇𝐷𝑖𝑘 ∙ 𝐿𝑖 ∙ 24 ∙ 365 ∙ 10−6
• Further risk mitigation measures (adopted only after a cost benefit analysis)
• The safety margin is high
San Demetrio Tunnel Risk Analysis
General Conclusions on the PIARC/OECD QRA model

CONCLUSIONS: QRAM AND Fluid Dynamics/evacuation models
Data Collection
Data Preparation
Risk Calculation
Using QRAM
Is Risk
acceptable?
NO
Additional
risk reduction
measures
START
YES
End
Idintification of
Critical Scenarios
Single Scenario
Simulation
CFD Simulation
(Fire, Ventilation)
Evacuation Model
(Evacuation, Rescue)
Qualitative Risk
Estimation
Measures
Included
in the model?
YES NO
(Gai et al., Proceedings IF CRASC’ 15)
An operating method to follow can be to
identify the critical scenarios that give the most
significant contribution to the overall risk
through the QRAM, and then to simulate those
scenarios in detail in order to define risk
reduction measures (Petelin S. 2009)

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