pipeline transportation of hazardous materials...434-7, consequence modelling (ogp, 2010 - 434-7)....
TRANSCRIPT
SAFER, SMARTER, GREENER
Authors: Colin Hickey
DNV GL, 200 Great Dover Street, London, SE1 4YB, [email protected] Adeyemi Oke DNV GL. 200 Great Dover Street, London, SE1 4YB, [email protected]
WHITEPAPER
PIPELINE TRANSPORTATION
OF HAZARDOUS MATERIALS An updated quantitative risk assessment methodology with Safeti
Reference to part of this report which may lead to misinterpretation is not permissible.
No. Date Reason for Issue Prepared by Verified by Approved by
0 2014-08-28 First issue
Prepared for presentation at:
American Institute of Chemical Engineers, 2nd CCPS China Conference on Process Safety Qingdao, China
August 28 – 29, 2014 AIChE shall not be responsible for statements or opinions contained in papers or printed in its publication.
© DNV GL AS. All rights reserved
This publication or parts thereof may not be reproduced or transmitted in any form or by any means,
including copying or recording, without the prior written consent of DNV GL AS
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1 ABSTRACT
Pipeline transportation of hazardous materials is increasing globally. Major accidents involving pipelines
continue to occur. A wide range of guidance is available from various sources for robust quantitative risk
assessment (QRA) of mobile and pipeline transportation of hazardous materials. Derived from the
aforementioned sources, this paper describes new hazardous pipeline risk assessment capabilities
implemented in the Safeti QRA software package. The methodology includes automatic loss of
containment case generation based on pipeline construction, topography and operating parameters. The
geometrical nature of pipelines and their associated risk footprint relating to people, surrounding assets
and the environment are often long and relatively narrow. Creation of risk contours around such
geometries requires use of high aspect ratio grids. The calculation algorithm required for high aspect
ratio hazard and risk zones such as those presented by pipelines is a challenge to traditional risk contour
based risk assessment techniques for process plants. The new methodology introduces a method for
adaptive grid solution for long pipelines for optimal computation and result accuracy. The new adopted
risk analysis method also introduces a time-varying fire simulation to account for the time-varying flow
phenomenon typically experienced with pipeline breaches. In summary this paper demonstrates how
these QRA methodology enhancements provide analysts with the tools necessary to perform rigorous
assessment and management of pipeline risks in a consistent and efficient manner using validated
models.
Keywords: QRA, Pipeline, Transportation risk analysis and assessment, Safeti, Phast
2 INTRODUCTION
Safeti was developed in the 1980s for quantitative risk analysis of major accident hazards associated
with process facilities. Safeti has since been continuously developed and has been adopted by a global
user base in a range of applications through the process industry including oil and gas, pharmaceuticals,
insurance, chemicals and petrochemicals. Positive change is evident in the process industry – process
safety is becoming common parlance amongst process engineers, while hazard and risk analysis are
becoming part of the standard engineering skill-set. Hazard and Risk analysis has moved from a
legislation driven, land use planning requirement to a standard practice in risk based design and risk
based operation. This change is coupled with an increase in transportation of hazardous materials and
declining tolerance of risk to the public, property and the environment. It is evident that a standard, best
practice method is required for consistent analysis of transportation risks.
Accidents highlighting the need for thorough analysis, communication and management of pipeline risks
include:
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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The scope of transportation risk analysis (TRA) can move through three dimensions, as advised by CPPS
(CCPS, 1995) and shown in Figure 1. You can choose to cover a limited, generalized or detailed set of
failure cases. You can perform qualitative, semi-quantitative or quantitative analysis. Finally you can
perform consequence, frequency or risk analysis. Primarily it is not feasible to be at the deepest extent
of this cube, and a pragmatic process is required whereby transport hazards across the enterprise are
screened and increased depth and focus given to areas identified as being of significant hazard.
Figure 1 - CCPS TRA study cube
This paper describes enhancements to the Safeti software, used to accurately model consequences
arising from loss of containment events from pipelines and their associated risks. The paper then
describes how Safeti supports the CCPS TRA methodology. This new approach will be available in Safeti
7.2.
3 MODELLING ENHANCEMENTS
Whether performing hazard analysis of a single loss of containment scenario or a holistic risk analysis
across an entire enterprise involving several sites interconnected by different transport modes, accurate
modelling of the loss of containment scenario is fundamental. For this reason, Safeti has been reviewed
and areas of improvement identified to more accurately simulate hazardous outcomes resulting from
breaches from pipelines.
The sequence of events that occurs when there is a release from a pipeline is: discharge, pool formation
(if liquid present and rainout occurs), and vapour cloud dispersion. At each of these stages people may
be exposed to toxicity if the material is toxic. If the material can act as an asphyxiant (such as CO2,
Nitrogen) then hazard from displacement of oxygen will occur. If the material is flammable, upon breach
immediate ignition may occur resulting in a fireball which transitions to a jet fire, in a two period
phenomenon, as observed by Lutostansky (Lutostansky, Modeling of Underground Hydrogen Pipelines,
2012). If the released flammable material experiences delayed ignition a flash fire or explosion may
occur. If a liquid pool has formed, a pool fire may occur. Each of these current capabilities in Safeti have
been assessed for their suitability to pipeline modelling and the following improvements have been
identified and implemented.
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3.1 Discharge source term
The work by Lutostansky (Lutostansky, Modeling of Underground Hydrogen Pipelines, 2012) presented
validation of Phast and Safeti’s models against gas (Hydrogen) pipeline rupture experiments. The
discharge rate from Phast and Safeti’s pipeline release model was found to give good results. For buried
pipelines a momentum modification factor of 0.25 should be used and for non-buried pipelines, no
modification factor need be applied.
Phast and Safeti have pipeline release models for gas (Webber & Witlox, Gaspipe Theory, 2010) and two
phase (Webber & Witlox, Pipebreak Theory, 2010) containment. No model is currently available for sub-
cooled liquids.
Best practice guidance for definition of pipeline release source terms have been taken from OGP report
434-7, Consequence Modelling (OGP, 2010 - 434-7). This guidance recommends size category and
orientation of releases.
Recommendations from OGP 434-7 have been combined with experimental findings and valve closure
logic. From this it is possible to establish a set of standard failures to be used at a single location on a
pipeline, as shown in Table 1. These would be accompanied by cases in which upstream and downstream
valves close, and where only the upstream valve succeeds in closing and finally where only the
downstream valve succeeds in closing. Releases are governed by:
Hole size
Elevation (below or above ground)
Release direction
Valve behaviour
Safeti contains inputs for controlling each of the above factors.
Hole size considerations
Hole sizes are an input to Safeti as they are pipeline specific. Information from organisations such as
EGIG (EGIG, 2011) can help to define typical hole sizes.
The definition provided by EGIG on the size of the breaches for their data is:
Pinhole crack: diameter of defect equal to or less than 2 cm
Hole: diameter of defect more than 2 cm and equal to or less than the diameter of the pipe
Rupture: diameter of defect more than the pipe diameter
In Safeti un-isolated small and medium leaks are represented by steady state orifice model calculations
and not the time-varying long pipeline (gas-pipe and two-phase pipe-break) models. Isolated small,
isolated medium and all full-bore rupture releases are calculated using the time-varying pipeline release
models. This application of steady state and time-varying approaches balances the need for accurate
modelling of the disturbance zone within the pipeline (for which the un-isolated small and medium cases
have less need) and the computation time of time-varying discharge calculations.
Elevation considerations
When pipelines are buried, upon release there is interaction with the over-burden. When the over-
burden is removed a crater remains. Safeti takes account of interaction with the over-burden and crater
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by offering a momentum adjustment factor. This reduces the velocity of the release whilst maintaining
the mass flowrate. Lutostansky found that 0.25 aligns with experimental findings for a hydrogen pipeline
for discharge rate and consequent jet fire behavior (Lutostansky, Modeling of Underground Hydrogen
Pipelines, 2012). A release angle of +45° is also applied to horizontal releases from buried pipeline to
account for interaction with the crater.
Release direction considerations
As discussed by OGP 434-7, releases can be vertical, horizontal and downward. Some special
considerations can be applied to some circumstances such as small releases from buried pipelines, which
are unlikely to have sufficient energy to displace the over-burden. They can therefore be modelled as
vertical with reduced velocity to represent permeation through the substrate. An example of an approach
is given in Table 1 for the buried small horizontal case.
Valve behaviour
Valves will be present upstream and downstream of breach locations. Emergency shut-down (ESD), non-
return, excess flow and manual valves may be present on the pipeline. Safeti can take account of ESD,
non-return and excess flow valves. The inputs to control valve behaviour in Safeti are the valve location,
valve type and for closure valves the closure time. When a breach occurs the control system is designed
to isolate the breached section to minimise outflow of the hazardous material. A change of operating
conditions would be detected and this could instigate automatic closure of ESD valves. The distance from
the breach to detectors and isolation valves will impact the response time. The closure time is not
provided automatically by Safeti as this is scenario specific. A useful reference for closure times can be
found in the UK HSE contract research report 206/1999 (UK HSE, 1999). For excess flow valves the
input of mass flow set point is required by Safeti. Reverse flow from pipeline downstream of the breach
will be limited by non-return valves in Safeti.
The variation on accidental release source terms is governed by the event tree shown in Figure 2. In this
way Safeti can provide support for decisions about effectiveness on investment and location of pipeline
control systems.
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Figure 2 - Event tree of valve success/failure for immediate and delayed ignition
Size Horizontal Vertical Downward
Buried
Small
1.Calculate as normal
2. Remodel to match flowrate by adjusting hole size for: 0.1barg for <10bar and 1bar for >10bar
3.Vertical
Same as small, buried, horizontal
Same as small, buried, horizontal
Medium +45° release direction, 0.25 momentum
Vertical Vertical @ 5m/s
Rupture +45° release direction, 0.25 momentum
Vertical Vertical @ 5m/s
Above ground
Small Horizontal Vertical Downward
Medium Horizontal Vertical Downward
Rupture Horizontal Vertical Downward
Table 1 – Suggested failure cases at pipeline breach location for above/below ground
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3.2 Failure frequency
Using information from the European Gas Pipeline Incident Group (EGIG, 2011) it is possible to derive
the failure frequency of pipeline breaches per length of pipeline. As shown in Table 2. Due to the useful
format in which the EGIG data is reported, with information on cause of breach and size of breach
(column and row in Table 2 respectively) it is also possible to determine the relative probability and
therefore the frequency of the various breach sizes. The inputs to Safeti are failure rate per distance.
Sections of pipeline can be assigned specific failure rates per distance. In this way it is possible to
account for local factors such as burial depth, pipe wall thickness. Breach categories in Safeti are
assigned relative probabilities. Referring to data shown in Table 2 one might assign small, medium and
rupture breaches with relative probabilities of 49%, 36.5% and 14.5% respectively.
External
interference
Corrosion Construction
Defect or
Material Failure
Hot tap
made by
error
Ground
movement
Total
Frequency
Relative
probability
(/1000km.yr)
Pinhole
crack
0.045 0.054 0.041 0.012 0.006 0.158 0.490
Hole 0.09 0.002 0.013 0.005 0.008 0.118 0.365
Rupture 0.033 0 0.004 0 0.01 0.047 0.145
Table 2 - Frequency of breach type, EGIG 2011
Total = 0.323
Using the information from EGIG and the class of “secondary failure frequencies” (EGIG, 2011 p.25) it is
possible to investigate the effect of variation of pipeline design on risk. For example, using the
relationship between cover depth and failure frequency it is possible to perform sensitivity analysis in a
QRA to see the risk reduction achieved by increasing the burial depth of a pipeline. The same process
could be applied to see the effect of wall thickness on risk. In this way, Safeti can take the inputs in the
best-practice format discussed above, but does not offer default values, as these may be misleading for
any given pipeline configuration.
3.3 Automatic failure case generation
With the above methods defining the source term, how it behaves after release and its likelihood, it is
possible to define rules for automatic creation of failure cases. Continuously variable events are too
computationally onerous to perform. Therefore the pipeline is broken into segments, and mid-point
representative release cases are used per segment. The choice to use representative release cases is to
gain efficiency at an acceptable cost of accuracy.
The pipeline route should be divided into sections along which the pipeline conditions are “approximately
constant”. To achieve this, the following rules are applied:
Sections upstream and downstream of valves that could be closed (including Excess Flow Valves
but excluding manual valves) following a release should be modelled separately.
The absolute pressure should change by no more than 20% over the length of a section.
Section lengths should be at least 500 m and no more than 20% of the total pipeline length.
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Releases from the section should be modelled using conditions (pressure, temperature) at the
mid-point of each section.
Using the above rules, it is possible for a user to draw a pipeline route, define process conditions, insert
valves and then click to automatically create the array of failure cases.
3.4 Results to grid
Due to the traditional risk analyses’ location specific individual risk and societal impact calculations, it
has been necessary to perform the calculations of risk to an area using a cellular grid method. This
requirement comes at some cost to computation and requires some new logic for optimal calculation of
transport risks. The two issues related to optimization of transport risk on grids are that of failure event
spacing and efficient grid use.
3.4.1 Failure event spacing
In the existing mobile transportation risk model within Safeti 6.7 the user is required to define event
spacing along the route. If the spacing between events is larger than the release’s hazard zones the risk
summation will contain gaps between the events. If the spacing between events is much smaller than
the hazard zones then extraneous calculations are being performed by Safeti’s risk summation model.
While the latter problem only wastes time, the former problem can lead to incorrect results. For this
reason the pipeline route model in Safeti will determine the optimum failure spacing automatically. The
algorithm will look at a distance to lethality from flammable and toxic hazards. Different failure event
spacing is applied to different size breaches modelled along the pipeline in a manner which optimizes
results resolution and computation time.
3.4.2 Grid area optimization
Safeti, by default, uses a 200 x 200 cell grid for calculation of risks. This approach is ideal for process
plants. Pipelines and mobile transportation routes will, by their nature, have high length to width ratio.
This results in sub-optimal usage of grid cells when risk summation calculations are being performed. A
(multi-)linear transport risk grid method has been added to Safeti. This approach will support adaptive
(with finer grid resolution close to the pipeline), multi-layered, non-rectangular (radial) irregular grids.
This results in higher resolution results in the near field around the pipeline and follows the route of the
pipeline over its length. It is envisaged that this enhancement will add further broad benefits in the
future in Safeti for other cases (including non-transport) such as flammable and toxic materials where
near-field and far-field effects must be accounted for in the same release and would cause problems for
the non-adaptive grid based method.
3.5 Fireballs and jet fires
In earlier versions of Phast and Safeti, the impulsive fireball / jet fire generated following immediate
ignition of a pipeline release may be represented by a short duration fireball and a time-averaged jet fire.
The jet fire contribution to this approach has a limitation in that the jet fire is represented by the time-
averaged mass flowrate over 20 seconds (or the release duration, whichever is shorter). This under-
predicts the maximum hazard zone size and may under-predict the radiation dose at various locations.
The approach has therefore been improved by introduction of a time-varying fire model.
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Experimental/field evidence (Cracknell & Carsley, 1997), (Hirst, 1986) suggests that upon immediate
ignition of a flammable release from a pipeline a buoyant fireball is formed shortly after ignition followed
by a quasi-steady state jet fire. The new time-varying fire model (TVFM) developed for Phast and Safeti
makes use of the existing efficient, flame, radiation and numerical integration calculations. Radiation
effects are calculated for multiple mass flowrates during the time-varying release; this leads to different
flames and associated radiation intensities, while radiation dose, probit and lethality at various observer
locations over a given duration of interest are determined using established numerical integration
methods. Figure 3 shows a transect of radiation intensity versus upwind and downwind distance from the
release. The transect is shown for several times of interest as the flame develops. The time-dependent
dose at various locations of interest along the transect are determined via numerical integration as
illustrated in Figure 4. Figure 4 also shows the predicted radiation dose along the transect for the
scenario illustrated in Figure 3 using the “20 second” time-averaged steady-state fire analysis (with and
without an initial fireball) implemented in earlier versions of Safeti as compared against the time-varying
fire and radiation analysis (with an initial fireball) introduced within Safeti 7.2. Note how in Figure 3 that
the radiation intensity starts at a peak level and is centered around 0m downwind distance. This is due
to the flame being at maximum mass flowrate with high momentum modelled starting as a fireball
centered at the point of release. As time progresses and the mass flowrate to the fire decreases, the
flame decays and the resulting radiation field decreases in size for a given level of radiation intensity.
Figure 3 also shows that at later times as the flame decays the radiation versus time profiles move
downwind, indicative of the flame losing vertical momentum and therefore being tilted by the wind. This
leads to a very dynamic picture for the received dose at locations upwind and downwind from the release
point. In all the results are significantly more accurate for flammable pipeline releases.
Figure 2 - Example time varying fire results
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Figure 3 - Example thermal dose transect for time-varying pipeline release scenario illustrated in Figure 2: comparison of Safeti 7.2 time varying fire and radiation analysis results against the “20 second” time-
averaged fire analysis (with and without an initial fireball) as implemented in earlier versions of Safeti.
4 RISK ASSESSMENT METHODOLOGY
The purpose of the pipeline hazard and risk assessment methodology is to understand the nature of a
hazard from a phenomenological perspective and to include the event at the correct level of priority
amongst the many other risks that are managed by an enterprise. As discussed above, detailed, risk
analysis of all transportation risks is unlikely to be possible in a single project. Note that the underlined
terms here represent the axes of the CCPS TRA study cube shown in Figure 1. CCPS’ transport safety,
security and risk management guidance offers a systematic approach to managing enterprise transport
risks (CCPS, 2008). The process begins with mapping out all plants, transport routes, their hazardous
materials and modes of transport. Figure 5 illustrates how transportation of a range of feed and product
materials can be organised for qualitative risk screening on a large geographical and operational scale.
This process recommends that one considers the conditions of roads, the performance of 3rd party
service providers and other practical factors which may influence the likelihood and consequence of a
hazardous event. This screening process will highlight segments which require more detailed semi-
quantitative and quantitative analysis. For segments of this network which are supported by pipeline one
can move onto the next step with the new Safeti pipeline risk model.
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Figure 4 - CCPS network of transport operations with chemicals and modes of concern
The large geographical area covered by pipelines can lead to large amounts of input information being
required. It is impractical to provide detailed information on population and delayed ignition sources for
the entire pipeline length. This infers that we need to perform a relatively coarse pipeline QRA for the
overall pipeline route as a first step. One can do this by using coarse blocks of population and delayed
ignition along the route. The variable nature of the pipeline process and release cases (governed by
process pressure, elevation, proximity to valves and hole sizes) result in various failure cases interacting
with the population and ignition. The results from a coarse analysis can be considered to be semi-
quantitative. However, the failure cases which have been automatically generated are full, detailed
simulations of the hazard phenomenon – this is a large step forward for the analyst, freeing up their time
to where it is best spent: reducing and managing the identified risks. It also helps the analyst move on
to the next step, focusing the analysis on areas of concern which have been identified.
Detailed information is required around the pipeline when there are factors which may increase the risk.
These may be:
Significantly vulnerable population
High population density
Increased likelihood of ignition
Large hazard zones
Areas with potential for escalation (e.g. near process plant)
Within the broad study of the entire pipeline, one can zoom in on areas of concern and add information
on population, ignition and any other local factors. This will then provide more detailed results around
these locations. One can then identify risk prevention and mitigation options. For example we might
choose re-routing, or culverting at vulnerable locations such as road or rail crossings or human activity.
One may choose to increase wall thickness, introduce more proximate detection and emergency
shutdown measures or work with construction and access exclusion zones around the pipeline corridor.
One can very efficiently make changes to the Safeti study reflecting the suggested prevention measures
and perform repeated analyses to see what benefits these return in terms of risk reduction.
In summary, to conduct the process described by the CCPS TRA study cube as shown in Figure 1 an
approach is to first perform screening of a large subject set, and to then drill down with more detail on
the areas of concern which have been revealed. The process supports efficient analysis of broad subject
matter with the potential for more detailed analysis by adding details to the same study. Such a study
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may appear as shown in Figure 6, where an entire route has been analysed and then a local, vulnerable
location has been investigated in more detail.
Figure 5 – Entire route with detailed segment shown in zoomed area, in Safeti
5 CONCLUSION
Safeti has long had a model for transport risk. This model was suitable for mobile transport units but
required manual work to apply to pipelines. Areas have been identified to improve Safeti for risk analysis
for transportation of hazardous materials through pipelines. Improvements include automatic creation of
failure cases for small, medium and large releases above and below ground. The failure cases are
generated for the entire pipeline length taking account of pressure change within the pipeline and
location of shut-down valves. Safety systems are taken account of by inclusion of a new configurable
event tree that allows improved modelling of safety-system performance by accounting for the impact of
different isolation actions, detection times and probabilities and shutdown probabilities for upstream and
downstream isolation. Time-varying mass flow and flame behavior are simulated by a new model giving
rise to time-varying radiation, dose and lethality. The new methodology includes improved support for
event frequency according to the data format available from EGIG and the OGP methodologies.
In all this takes more accurate account of accidental breaches and presents a more realistic assessment
of major accident hazard risks stemming from transportation of hazardous materials through pipelines
and the improvements introduced to Safeti help better support the CCPS TRA methodology.
The improvements described in this paper allow analysts to more accurately and efficiently identify key
risk drivers and undertake detailed benefit analysis of potential remedial measures for risk based design
/ management and/or decision making.
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6 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. Cracknell, R. F., & Carsley, A. J. (1997). Cloud fires – A methodology for hazard consequence modelling.
ICHEME Symposium Series, No. 141, (pp. 139 -150). EGIG. (2011). 8th Report of the European Gas Pipeline Incident Data Group. Groningen: European Gas
Pipeline Incident Data Group.
French Ministry of Sustainable Development. (2009, 9). Rupture and ignition of a gas pipeline July 30, 2004, Ghislenghien, Belgium, No. 27681. Retrieved 5 1, 2013, from www.aria.developpement-durable.gouv.fr: http://www.aria.developpement-durable.gouv.fr/ressources/fd_27681_ghislengheinv_jfm_anglais.pdf
Hirst, W. J. (1986). Combustion of Large Scale Releases of Pressurized Liquid Propane. Proceedings 3rd Symposium on Heavy Gas Risk Assessment. Dordrecht, Netherlands: Reidel.
Lutostansky, E. (2012). Modeling of Underground Hydrogen Pipelines. Global Congress on Process Safety.
AIChE CCPS. 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.
OGP. (2010 - 434-7). Consequence Modelling Report - 434-7. London: : International Association of Oil & Gas Producers.
UK HSE. (1999). Assessing the risk from gasoline pipelines in the United Kingdom based on a review of historical experience. Norwich: UK HSE.
UK HSE. (1999). Risks from gasoline pipelines in the United Kingdom crr 206/1999. Norwich: Crown. Webber, D., & Witlox, H. (2010). Gaspipe Theory. London: DNV. Webber, D., & Witlox, H. (2010). Pipebreak Theory. London: DNV. Wikipedia - 2010 San Bruno pipeline explosion. (2014, 07 30). 2010 San Bruno pipeline explosion.
Retrieved from http://en.wikipedia.org/:
http://en.wikipedia.org/wiki/2010_San_Bruno_pipeline_explosion Wikipedia - 2010 Xingang Port oil spill. (2013, 5 1). 2010 Xingang Port oil spill. Retrieved 5 1, 2013,
from Wikipedia/Xingang_port_oil_spill: http://en.wikipedia.org/wiki/Xingang_Port_oil_spill Wikipedia - 2013 Qingdao pipeline explosion. (2014, 07 23). 2013 Qingdao oil pipeline explosion.
Retrieved from http://en.wikipedia.org/: http://en.wikipedia.org/wiki/2013_Qingdao_oil_pipeline_explosion
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