84d79a2be00f4c939805d6f69e017bd3.pdf

DNV GL © SAFER, SMARTER, GREENER DNV GL ©

SOFTWARE

Guidance on performing transportation risk analysis of hazardous materials

1

Spend your time reducing transportation risks rather

than spending time producing numbers

DNV GL ©

Contents

The hazards and risks of transporting hazardous materials

Transport Risk Assessment

TRA challenges

Mobile transport unit TRA Case Study

Pipeline TRA Case Study

– Before we get started

– The results

– Risk reduction options

References

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The hazards and risks of transporting hazardous materials

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Pipeline Accidents

Kaohsiung, Taiwan, 2014: Gas pipeline leak and explosions, 25 fatalities, 257

injured

Qingdao, China, 2013: Oil pipeline leak and explosion, 62 fatalities, 136

hospitalized. (Wikipedia - 2013 Qingdao pipeline explosion, 2014)

Dalian, China, 2010: Oil release to sea from port for 90km, covering 946km2.

Fatalities and injuries occurred, number not reported. Extent of environmental

damage also not reported. (Wikipedia - 2010 Xingang Port oil spill, 2013)

San Bruno, California, natural gas pipeline explosion, 8 fatalities. (Wikipedia -

2010 San Bruno pipeline explosion, 2014)

Ghislenghien, Belgium 2004: 24 fatalities, 120+ injuries. (French Ministry of

Sustainable Development, 2009)

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Mobile Transport Accidents

Oil rail tank car

Lac-Mégantic, Canada, 6/6/2013, 42 fatalities, 5 missing presumed dead. 66 of

69 downtown buildings destroyed (30) or to be demolished (36).

West Virginia, USA, 16/2/15, Fireball, Fires, two towns evacuated, no injuries or

fatalities. Using CPC 1232, not DOT 111 tank cars.

Timmins, Ontario, Canada, 14/2/15, 29 tank cars derailed, fires, no reported

injuries or fatalities.

Road

Kannur, India, 27/8/12, 16 tonne road tanker collision with road divider, 41

seriously injured.

Kannur, India, 13/1/14, 18 tonne LPG tanker car collision and overturned, fire, no

injuries.

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Transport Risk Assessment

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Questions TRA can answer

What would an accident from my pipeline look like?

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http://news.nationalgeographic.com/news/2010/09/photogallerie

s/100910-san-bruno-fire-explosion-nation-gas-location-

pictures/#/california-san-bruno-gas-explosion-francisco-

cars_25824_600x450.jpg

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http://news.nationalgeographic.com/news/2010/09/photogallerie

s/100910-san-bruno-fire-explosion-nation-gas-location-

pictures/#/california-san-bruno-gas-explosion-francisco-

cars_25824_600x450.jpg

(Lutostansky, 2013) – 35 kW/m2 Radiation Contour for

San Bruno Pipeline Rupture calculated by Safeti

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What is the risk to people, property and the environment?

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(UK HSC, 1991) Major Hazard Aspects of the Transport of

Dangerous Substances

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Risk Contours with impact on surrounding population

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What are the benefits of prevention measures that I can take?

(EGIG 2015)

10

y = 0.0015e-0.333x

R² = 0.9755

0

0.0001

0.0002

0.0003

0.0004

0.0005

0.0006

0.0007

0 2 4 6 8 10 12 14

Failu

re f

req

uen

cy p

er k

m.y

r

Wall thickness (mm)

Failure frequency and Wall Thickness

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What mode of transport should I use?

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Which route should I take?

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What operating conditions optimise production, reliability and safety?

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Which sections of my route requires most attention?

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Where and how frequently should I place my ESD systems?

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What pipeline design shall I use?

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What is the cost-benefit of risk reductions measures?

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Do I comply with regulations?

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Do I comply with regulations?

Has anybody encroached into my ‘High Consequence Area’?

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DNV GL © 12 TRA Framework (CCPS, 2008)

DNV GL © 12 TRA Framework (CCPS, 2008)

DNV GL © 13 TRA workflow (CCPS, 2008)

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TRA challenges

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Scope is large

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(CCPS, 2008)

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Level of detail needed for accurate modelling is large

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Operating Procedures

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Ignition


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Ignition


Regulations

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Population

Ignition


Regulations

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Population

Ignition


Regulations

Toxicity

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Population

Ignition


Traffic information

Regulations

Toxicity

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Population

Ignition


Traffic information

Regulations

Maps

Toxicity

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Population

Ignition


MSDS

Traffic information

Regulations

Maps

Toxicity

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Population

Ignition


MSDS

Traffic information

Meteorology

Regulations

Maps

Toxicity

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Population

Ignition


MSDS

Traffic information

Meteorology

Regulations

Maps

Failure Rates

Toxicity

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Large x Large = Very Large!

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How do we handle a very large scope?

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How do we handle a very large scope?

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TRA study cube (CCPS, 1995)

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What does this mean?

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We can’t do everything at once, we need to be strategic

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We need to systematically screen a broad study set and then zoom-in

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“Zoom in” means:

– Use more quantitative methods

– Get more accurate local information

– Smaller “step sizes” in the calculations

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When should we zoom in?

– Sensitive area

– Uncertain of the results

– When we have detailed data available

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When should we zoom in?

– Sensitive area

– Uncertain of the results

– When we have detailed data available

We need to be efficient and systematic using consistent, validated models

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Mobile Transport Unit TRA Case Study

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Mobile transport unit releases

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We can think of rail cars and tank trucks as vessels which move along a route

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We can assess the reasons why the containment can fail due to:

– Operation

– Accident initiated event (collision, allision, overturn, derailment)

– Non-accident initiated event (corrosion crack, overpressure, valve/fitting leaks)

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– Operation



This means we can define a fixed set of cases and then move them along the

route

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– Operation



This means we can define a fixed set of cases and then move them along the

route

We can supplement the route releases with fixed point rest stops or high risk

locations such as cross roads

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Route modelling schematic

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Route

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Route

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Route

Effect Zone

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Route

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Route

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Route

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Route

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Route Model Capabilities

Safeti contains a Route model

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We define a folder of potential

accidents

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accidents

We define routes along which the

vehicle may travel

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accidents


vehicle may travel

This can be used for road tankers, rail

cars, barges, ships

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accidents


vehicle may travel


cars, barges, ships

The hazard zones are calculated and

then the risk model spreads them

along the routes

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accidents


vehicle may travel


cars, barges, ships

The hazard zones are calculated and

then the risk model spreads them

along the routes

The failure frequency/distance is

applied to the hazard zone when it is

placed in each location

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Route Model Example - CCPS TRA Guidance 1995 Case Study

From ‘Here’ To ‘Eternity’

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Along either Route 27 or Route 46

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Population changes along each

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Which is the best risk option?

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Which is the best risk option?

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Lets look at this in Safeti

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CCPS TRA 1995 Case Study - Safeti Results Summary

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Route 27 PLL: 30/yr

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Route 27 PLL: 30/yr

Route 46 PLL: 0.011/yr

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Route 27 PLL: 30/yr


Who is being impacted and where?

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Route 27 PLL: 30/yr



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Route 27 section 1 7.21



Total PLL/yr 30.19

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Route 27 PLL: 30/yr



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distance? pop density?

frequency?

consequence?




Total PLL/yr 30.19

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How is this helping you to overcome TRA challenges?

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You can define a large, coarse route and get an overview based on semi-

quantified parameters

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For example

– Put in broad population locations

– Put in broad ignition values

– Put in different routing with different failure frequencies

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For example




Zoom in and apply more details when you see risks are getting relatively larger or

when hazards are near populations

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For example






Phast and Safeti’s discharge, dispersion, pool, fire and explosion models are

validated against a wide range of experiments

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For example






Phast and Safeti’s discharge, dispersion, pool, fire and explosion models are

validated against a wide range of experiments

By systematically approaching this problem you are saving time to apply your

skills to managing safety, not crunching numbers

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Pipeline TRA Case Study (adapted from CCPS 1995 case study 7.1)

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Pipeline releases

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Pipeline releases

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Release

Pressure Front Pressure Front

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Pipeline releases

Pipelines are continuously variable along their length

– Friction causes pressure drop

– Pipe construction may be variable

– Proximity to ESD

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Release


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Pipeline releases

Pipelines are continuously variable along their length

– Friction causes pressure drop

– Pipe construction may be variable

– Proximity to ESD

Long distances to consider

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Release


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New pipeline risk modelling capabilities in Safeti 7.2

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Define your pipeline

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– Draw it on a map

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– Specify where valves are and the valve properties

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– Define sections of the pipeline which differ:

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– Elevation

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– Elevation

– Pipe wall thickness

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– Elevation


– Diameter differences

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– Elevation



Safeti creates a complete pipeline definition containing segments to be modelled

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– Elevation




Create breaches of interest (small, medium, large etc.) which will be modelled for

all sections along the pipeline

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– Elevation




Create breaches of interest (small, medium, large etc.) which will be modelled for

all sections along the pipeline

In addition to the systematic breaches you can produce detailed results from a

location of interest along the pipeline

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Pipeline Case Study – adapted from CCPS 1995

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(adapted)

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Sour Gas transported 50 miles, past populations from Facility A to Facility B

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(adapted)

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Releases:

– One inch holes

– Full bore rupture

– Pinholes are omitted

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(adapted)

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Releases:

– One inch holes

– Full bore rupture

– Pinholes are omitted

What level of protection

do we need?

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(adapted)

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Case Study Data

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Case Study Data

Pipe: 5 inch OD, 0.337 wall, 4.663 ID

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Case Study Data


Flowrate 0.2 kg/s

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Case Study Data


Flowrate 0.2 kg/s

Pressure: 80 barg

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Case Study Data


Flowrate 0.2 kg/s

Pressure: 80 barg

Product temperature: 30°C

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Case Study Data


Flowrate 0.2 kg/s

Pressure: 80 barg


Valve stations: 7 (evenly distributed)

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Case Study Data


Flowrate 0.2 kg/s

Pressure: 80 barg


Valve stations: 7 (evenly distributed)

Consequence scenario inputs:

– Elevation 0 ft

– Angle 10° from horizontal

– Weather conditions: 12°C, D11mph, F4.5mph

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Frequency Estimation

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Using (EGIG 2015) we can obtain

failure frequency information

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It is a very sophisticated data

source which allows us to analyse

the frequency of events in detail

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We can look at total failure rates

per breach size

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per breach size

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per breach size

Or we can look at rates for pipe

diameters

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per breach size


diameters

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per breach size


diameters

Given that around 5 inch diameters

sees a peak we should use those

values for our case

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per breach size


diameters



values for our case

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per breach size


diameters



values for our case

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before we get started…

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The problems with modelling pipelines

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For the reasons discussed above, every outcome location has different

consequences

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consequences

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Pipeline

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consequences

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Pipeline

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Village



consequences

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Pipeline

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Village



consequences

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Pipeline

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Village



consequences

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Pipeline

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Village



consequences

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Pipeline

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Village



consequences

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Pipeline

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Village



consequences

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Pipeline

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Village



consequences

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Pipeline

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Village



consequences

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Pipeline

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Village



consequences

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Pipeline

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Village



consequences

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Pipeline

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Village



consequences

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Pipeline

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We need to create individual scenarios for continuously changing release locations

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This requires:

– Pipeline pressure at the release location

– Distance to closure valves

– Local pipe wall thickness

– Local burial depth

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This requires:

– Pipeline pressure at the release location

– Distance to closure valves

– Local pipe wall thickness

– Local burial depth

The solution in Safeti is to automate this process

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Manually sectioning the pipeline…

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Pipeline

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Section 1

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ESD Valves

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Section 1 Section 2 Section 3 Section 4

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Local wall thickness


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Culverted section


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Automatically Sub-sectioning the pipeline

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Δ pressure drop

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Δ pressure drop

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Δ pressure drop

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Δ pressure drop

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Δ pressure drop

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Δ pressure drop

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Δ pressure drop

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Δ pressure drop

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Δ pressure drop

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Δ pressure drop

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Δ pressure drop

Sub s

ection 1

Sub s

ection 2

Sub s

ection 3

Sub s

ection 4

Sub s

ection 5

Sub s

ection 6

Sub s

ection 7

Sub s

ection 8

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Δ pressure drop

Δ mass flowrate

Sub s

ection 1

Sub s

ection 2

Sub s

ection 3

Sub s

ection 4

Sub s

ection 5

Sub s

ection 6

Sub s

ection 7

Sub s

ection 8

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Continuously variable scenarios

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Sub s

ection 1

Sub s

ection 2

Sub s

ection 3

Sub s

ection 4

Sub s

ection 5

Sub s

ection 6

Sub s

ection 7

Sub s

ection 8

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We can now calculate release scenarios for every sub-section

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Sub s

ection 1

Sub s

ection 2

Sub s

ection 3

Sub s

ection 4

Sub s

ection 5

Sub s

ection 6

Sub s

ection 7

Sub s

ection 8

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Each sub-section will comprise location specific properties

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Sub s

ection 1

Sub s

ection 2

Sub s

ection 3

Sub s

ection 4

Sub s

ection 5

Sub s

ection 6

Sub s

ection 7

Sub s

ection 8

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Each sub-section will comprise location specific properties

Safety systems are modelled, giving rise to cases for:

– Valves close

– Upstream valve fails to close

– Downstream valve fails to close

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Sub s

ection 1

Sub s

ection 2

Sub s

ection 3

Sub s

ection 4

Sub s

ection 5

Sub s

ection 6

Sub s

ection 7

Sub s

ection 8

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Lets take a look at the results…

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Study set up

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Pipeline construction

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Pipeline construction

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Lets look at this in Safeti

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Auto sectioning results

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Pressure drop along pipeline

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1 Inch Breach

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0

200

400

600

800

1000

1200

1400

1600

1800

0 10000 20000 30000 40000 50000 60000 70000 80000

Averag

e R

ele

ase D

urati

on

(s)

Downstream distance (m)

Average Release Duration vs Downstream Distance

No Isolation

Full Isolation

Successful Upstream Isolation

Successful Downstream Isolation

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1 Inch Breach

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0

2

4

6

8

10

12

14

16

18

20

0 10000 20000 30000 40000 50000 60000 70000 80000

Mass f

low

rate

(kg

/s)

Downstream Distance (m)

Average Mass Flowrate vs Downstream Distance

No Isolation

Full Isolation



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Full Bore Rupture

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0

100

200

300

400

500

600

700

0 10000 20000 30000 40000 50000 60000 70000 80000

Rele

ase D

urati

on

(s)


Release Duration vs Downstream Distance

No Isolation

Full Isolation



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Full Bore Rupture

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0

10

20

30

40

50

60

70

80

90

100

0 10000 20000 30000 40000 50000 60000 70000 80000

Averag

e R

ele

ase R

ate

(kg

/s)


Average Release Rate vs Downstream Distance

No Isolation

Full Isolation



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Risk Contours

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FN Curve

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FN Curve

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Is this as low

as reasonably

practicable?

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Risk reduction options

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Failure frequency effects of pipe wall thickness (EGIG 2015)

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Failure frequency correlations

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Failure frequency correlations Discrete

Wall thickness (mm) Failure Frequency

(/km.yr)

wt<5 0.00056

5<wt<10 0.000167

10<wt<15 0.00002

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(/km.yr)

wt<5 0.00056

5<wt<10 0.000167

10<wt<15 0.00002

54

0

0.0001

0.0002

0.0003

0.0004

0.0005

0.0006

0 5 10 15 20

Failu

re F

req

uen

cy (

/km

.yr)

Wall Thickness (mm)

Discrete Failure Frequency and Wall Thickness

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(/km.yr)

wt<5 0.00056

5<wt<10 0.000167

10<wt<15 0.00002

Exponential interpolation

54

0

0.0001

0.0002

0.0003

0.0004

0.0005

0.0006

0 5 10 15 20

Failu

re F

req

uen

cy (

/km

.yr)

Wall Thickness (mm)


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(/km.yr)

wt<5 0.00056

5<wt<10 0.000167

10<wt<15 0.00002


0

0.0001

0.0002

0.0003

0.0004

0.0005

0.0006

0.0007

0 5 10 15

Failu

re f

req

uen

cy (

/km

.yr)

Wall thickness (mm)


54

0

0.0001

0.0002

0.0003

0.0004

0.0005

0.0006

0 5 10 15 20

Failu

re F

req

uen

cy (

/km

.yr)

Wall Thickness (mm)


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(/km.yr)

wt<5 0.00056

5<wt<10 0.000167

10<wt<15 0.00002


0

0.0001

0.0002

0.0003

0.0004

0.0005

0.0006

0.0007

0 5 10 15

Failu

re f

req

uen

cy (

/km

.yr)

Wall thickness (mm)


54

F = 0.0015e-0.333t

0

0.0001

0.0002

0.0003

0.0004

0.0005

0.0006

0 5 10 15 20

Failu

re F

req

uen

cy (

/km

.yr)

Wall Thickness (mm)


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(/km.yr)

wt<5 0.00056

5<wt<10 0.000167

10<wt<15 0.00002


0

0.0001

0.0002

0.0003

0.0004

0.0005

0.0006

0.0007

0 5 10 15

Failu

re f

req

uen

cy (

/km

.yr)

Wall thickness (mm)


54

F = 0.0015e-0.333t

0

0.0001

0.0002

0.0003

0.0004

0.0005

0.0006

0 5 10 15 20

Failu

re F

req

uen

cy (

/km

.yr)

Wall Thickness (mm)


DNV GL ©



(/km.yr)

wt<5 0.00056

5<wt<10 0.000167

10<wt<15 0.00002


0

0.0001

0.0002

0.0003

0.0004

0.0005

0.0006

0.0007

0 5 10 15

Failu

re f

req

uen

cy (

/km

.yr)

Wall thickness (mm)


54

F = 0.0015e-0.333t

0

0.0001

0.0002

0.0003

0.0004

0.0005

0.0006

0 5 10 15 20

Failu

re F

req

uen

cy (

/km

.yr)

Wall Thickness (mm)


DNV GL ©



(/km.yr)

wt<5 0.00056

5<wt<10 0.000167

10<wt<15 0.00002


0

0.0001

0.0002

0.0003

0.0004

0.0005

0.0006

0.0007

0 5 10 15

Failu

re f

req

uen

cy (

/km

.yr)

Wall thickness (mm)


54

F = 0.0015e-0.333t

0

0.0001

0.0002

0.0003

0.0004

0.0005

0.0006

0 5 10 15 20

Failu

re F

req

uen

cy (

/km

.yr)

Wall Thickness (mm)


Caution!

DNV GL ©

Translating trends into practical tools

55


(/km.yr)

wt<5 0.00056

5<wt<10 0.000167

10<wt<15 0.00002

DNV GL ©


55


(/km.yr)

wt<5 0.00056

5<wt<10 0.000167

10<wt<15 0.00002

We didn’t use

this failure

frequency for

our base case

DNV GL ©


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(/km.yr)

wt<5 0.00056

5<wt<10 0.000167

10<wt<15 0.00002

We didn’t use

this failure

frequency for

our base case

We used a failure frequency of 0.401/1000 km.yr as per EGIG table 3.

DNV GL ©


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(/km.yr)

wt<5 0.00056

5<wt<10 0.000167

10<wt<15 0.00002

We didn’t use

this failure

frequency for

our base case


This is important as we wanted to account for the adverse influence of our

5” diameter pipeline.

DNV GL ©


55


(/km.yr)

wt<5 0.00056

5<wt<10 0.000167

10<wt<15 0.00002

We didn’t use

this failure

frequency for

our base case



5” diameter pipeline, not including pin holes.

5” pipes are easier to break!

DNV GL ©


55


(/km.yr)

wt<5 0.00056

5<wt<10 0.000167

10<wt<15 0.00002

We didn’t use

this failure

frequency for

our base case





We must therefore use the Wall Thickness failure frequency effect as a

factored influence on our base case, rather than as an absolute frequency.

DNV GL ©


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(/km.yr)

wt<5 0.00056

5<wt<10 0.000167

10<wt<15 0.00002







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(/km.yr)

wt<5 0.00056

5<wt<10 0.000167

10<wt<15 0.00002







Factor

3.35

1

0.12

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(/km.yr)

wt<5 0.00056

5<wt<10 0.000167

10<wt<15 0.00002







Our 0.401/1000km.yr can be factored by 0.12 to 0.04812/1000km.yr

Factor

3.35

1

0.12

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Risk reduction measure 1 – use 12mm pipe wall everywhere

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56

x10 reduction

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Risk reduction measure 2 – use 12mm pipe wall near towns

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Societal Comparison

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Societal Comparison

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Societal Comparison

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Can make a cost

benefit decision

about steel costs

and risk reduction

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Conclusions

TRA is vast and complex

There are excellent resources such as EGIG and OGP reports which can provide us

with guidance on how to model accidents and how to predict the effect of risk

reduction measures

Use caution when applying information sources to your cases (E.g. EGIG is for

steel, methane pipelines)

Software tools exist which can speed up systematic work

Making the laborious parts of a TRA more efficient frees us up to ask “What If?”

and make better risk management decisions, and hence improve safety

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References

CCPS. (1995). Guidelines for Chemical Transportation Risk Analysis. New York:

AIChE.

CCPS. (2008). Guidelines for Chemical Transportation Safety, Security and Risk

Management. Hoboken: Wiley.

Lutostansky, E., Shork, J., Ludwig, K., Creitz, L., & Jung, S. (2013). Release

Scenario Assumptions for Modeling Risk From Underground Gaseous Pipelines.

Global Congress on Process Safety. AIChE CCPS.

EGIG. (2015). 9th Report of the European Gas Pipeline Incident Data Group.

Groningen: European Gas Pipeline Incident Data Group.

OGP. (2010 - 434-7). Consequence Modelling Report - 434-7. London, International

Association of Oil & Gas Producers.

Hickey, C., Oke, A., Pipeline Transportation of Hazardous Materials – an Updated

Quantitative Risk Assessment Methodology, CCPS China, Qingdao, 2014

Safeti. DNV GL. dnvgl.com/safeti

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http://www.dnvgl.com/safeti

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SAFER, SMARTER, GREENER

www.dnvgl.com

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