pipeline transportation of hazardous materials...434-7, consequence modelling (ogp, 2010 - 434-7)....

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

| WHITEPAPER | Safeti | www.dnvgl.com/software Page 1

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)


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.


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


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.


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


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.


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.


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


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.


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


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.


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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