434-07 consequence modelling - ogp

8/2/2019 434-07 Consequence Modelling - OGP

1/40

Risk Assessment Data Directory

Report No. 434 7

March 2010

I n t e r n a t i o n a l A s s o c i a t i o n o f O i l & G a s P r o d u c e r s

Consequencemodelling


2/40

Publications

Global experience

Te International Association o Oil & Gas Producers has access to a wealth o technicalknowledge and experience with its members operating around the world in many diferentterrains. We collate and distil this valuable knowledge or the industry to use as guidelines

or good practice by individual members.

Consistent high quality database and guidelines

Our overall aim is to ensure a consistent approach to training, management and best prac-tice throughout the world.

Te oil and gas exploration and production industry recognises the need to develop consist-ent databases and records in certain elds. Te OGPs members are encouraged to use theguidelines as a starting point or their operations or to supplement their own policies and

regulations which may apply locally.

Internationally recognised source of industry information

Many o our guidelines have been recognised and used by international authorities andsaety and environmental bodies. Requests come rom governments and non-governmentorganisations around the world as well as rom non-member companies.

Disclaimer

Whilst every e ort has been made to ensure the accuracy of the information contained in this publication,neither the OGP nor any of its members past present or future warrants its accuracy or will, regardlessof its or their negligence, assume liability for any foreseeable or unforeseeable use made thereof, whichliability is hereby excluded. Consequently, such use is at the recipients own risk on the basis that any useby the recipient constitutes agreement to the terms of this disclaimer. e recipient is obliged to inform

any subsequent recipient of such terms.

is document may proide guidance supplemental to the requirements of local legislation. Nothingherein, however, is intended to replace, amend, supersede or otherwise depart om such requirements. Inthe event of any conict or contradiction between the proisions of this document and local legislation,

applicable laws shall prevail.

Copyright notice

e contents of these pages are e International Association of Oil and Gas Producers. Permission

is given to reproduce this report in whole or in part proided (i) that the copyright of OGP and (ii)the source are acknowledged. All other rights are reserved. Any other use requires the prior written

permission of the OGP.

ese Terms and Conditions shall be goerned by and construed in accordance with the laws of Eng-land and Wales. Disputes arising here om shall be exclusively subject to the jurisdiction of the courts of

England and Wales.


3/40

RADD Consequence modelling

OGP

contents

1.0 Scope and Definitions ........................................................... 1 2.0 Summary of Recommended Approaches ................................ 1 2.1 Release modelling ..........................................................................................32.1.1 Simple approaches to release modelling................................................................. 42.1.2 Software for release modelling................................................................................. 62.1.3 Modelling Releases from Buried Pipelines.............................................................. 7

2.2 Dispersion and ventilation modelling ........................................................... 72.2.1 Simple approaches to dispersion modelling...........................................................92.2.2 Software for dispersion modelling ......................................................................... 112.2.3 CFD for ventilation and dispersion modelling....................................................... 12

2.3 Fire and thermal radiation modelling.......................................................... 132.3.1 Simple approaches to fire and thermal radiation modelling................................142.3.2 Software for fire and thermal radiation modelling ................................................ 202.3.3 CFD for fire and thermal radiation modelling........................................................202.4 Explosion modelling..................................................................................... 222.4.1 Simple approaches to explosion modelling .......................................................... 232.4.2 Software for explosion modelling........................................................................... 232.4.3 CFD for explosion modelling .................................................................................. 24

2.5 Smoke and gas ingress modelling.............................................................. 242.5.1 Simple approaches to smoke and gas ingress modelling ...................................252.5.2 Software for smoke and gas ingress modelling....................................................262.5.3 CFD for smoke and gas ingress modelling ........................................................... 27

2.6 Toxicity modelling ........................................................................................27

2.6.1 Simple approaches to toxicity modelling .............................................................. 292.6.2 Software for toxicity modelling ............................................................................... 292.6.3 CFD for toxicity modelling....................................................................................... 29

3.0 Guidance on use of approaches........................................... 293.1 General validity ............................................................................................. 293.2 Uncertainties ................................................................................................. 303.3 Choosing the right approach for consequence modelling ....................... 303.4 Geometry modelling for CFD....................................................................... 31

4.0 Review of data sources ....................................................... 325.0 Recommended data sources for further information ............ 326.0 References .......................................................................... 326.1 References for Sections 2.0 to 4.0 ..............................................................326.2 References for other data sources.............................................................. 34


4/40


OGP

Abbreviations:

BLEVE Boiling Liquid Expanding Vapour Explosion

CFD Computational Fluid DynamicsCHRIS Chemical Hazards Reference Information System

CSTR Continuous Stirred Tank ReactorCV Control Volume

DAL Design Accidental LoadDNV Det Norske VeritasEU European UnionFV Finite VolumeHSE (UK) Health and Safety Executive

HVAC Heating, Ventilation and Air ConditioningIDLH Immediate Danger to Life and Health

JIP Joint Industry Project

LDx Lethal Dose resulting in fatalities to x% of populationLFL Lower Flammable Limit (also known as Lower Explosive Limit, LEL)LPG Liquefied Petroleum GasMSDS Material Safety Data Sheet

PDR Porosity, Distributed ResistanceQRA Quantitative Risk Assessment (sometimes Analysis)

SLOD Significant Likelihood of DeathSLOT Specified Level Of ToxicitySVP Saturated Vapour PressureTNO Nederlandse Organisatie voor Toegepast NatuurwetenschappelijkOnderzoek

(Netherlands Organization for Applied Scientific Research)TR Temporary Refuge

UVCE Unconfined Vapour Cloud ExplosionVCE Vapour Cloud Explosion


5/40


OGP 1

1.0 Scope and DefinitionsConsequence modelling refers to the calculation or estimation of numerical values (or

graphical representations of these) that describe the credible physical outcomes of lossof containment scenarios involving flammable, explosive and toxic materials withrespect to their potential impact on people, assets, or safety functions.

This datasheet presents (Section 2.0) recommended approaches to consequencemodelling for accidental releases of hazardous materials, with the potential to causeharm to people, damage to assets and impairment of safety functions, from offshoreand onshore installations.

Consideration of environmental impacts is excluded, although the recommendedapproaches to release modelling (in particular for liquids) may be applied to estimatepotential quantities of hydrocarbon spilt.

This datasheet is not intended to be a textbook of consequence modelling theory butrather to indicate the consequence phenomena that need to be considered and toprovide guidance on modelling that is fit for purpose.

2.0 Summary of Recommended ApproachesThis section addresses the following consequences of a loss of containment incident:

1. Release (discharge)

2. Dispersion in air and water

3. Fire and thermal radiation

4. Explosion

5. Smoke and gas ingress

6. Toxicity

Figure 2.1 illustrates and develops the relationship between many of these.

For each topic, guidance is given on some or all of the following possible approaches:

Simple correlations or formulae

General purpose consequence modelling software (see below)

CFD (Computational Fluid Dynamics see below)

Whichever approach is adopted, it should be used with an understanding of its range ofvalidity, its limitations, the input data required, the valid results that can be obtained, theresults sensitivity to the different input data, and how the results can be verified.


6/40


OGP2

Figure 2.1 Consequence Phenomena and their Interrelationship

General Purpose Consequence Modell ing SoftwareThe main commercial general purpose consequence modelling packages are:

CANARY, from Quest (http://www.questconsult.com/canary.html)

EFFECTS, from TNO

(www.tno.nl/content.cfm?context=markten&content=product&laag1=186&laag2=267

&item_id=739)

PHAST, from DNV(http://www.dnv.com/services/software/products/safeti/SafetiHazardAnalysis/index.asp)

TRACE, from Safer Systems (www.safersystem.com)

These model most of the consequences set out above apart from smoke. However, theyare designed for onshore studies and not all of the models included will be appropriatefor offshore use, in particular in enclosed modules. The sections below give guidance

on the appropriate use of these models.

In addition, there are freeware packages that can be downloaded for the internet butthese do not come with any training or support, or with any guarantee of code quality;


7/40


OGP 3

the commercial packages listed above do include these and come from reputableorganizations with quality management systems.

In addition, freeware calculators may be found for specific consequences (e.g.

BLEVE) but these suffer the same disadvantages listed above for general consequencemodelling.

Computational Fluid DynamicsComputational Fluid Dynamics (CFD) can be used to obtain numerical solutions forventilation, dispersion and explosion problems for both offshore platforms and onshoreplants. CFD simulations are becoming increasingly common as the computing power ofstandard desktop computers grows. The NORSOK standard Z-013 [21] specifies use ofCFD in its probabilistic approach to explosion risk assessment. The objective of theprobabilistic assessment is to generate realistic (representative) overpressures for anarea based on probabilistic arguments. Ventilation, gas leaks, dispersion as well as gas

explosions are considered by establishing probable explosion scenarios, performingexplosion simulations and establishing probability of exceedance curves.

The application of CFD for gas explosion studies is common for offshore platforms andis increasingly used onshore in cases where the explosion risk is significant and a

better description of the physics is required in order to give a more robust estimate ofthe risk.

CFD simulations essentially solve the conservation equations for mass, momentum and

enthalpy in addition to the equations for concentration and flammable gas effects. Theequations are generally closed using the turbulence model. Most of the

commercially available CFD packages (see below) are based on the Finite Volume (FV)method which uses an integral form of the conservation equations. Essentially, the

solution domain is subdivided into a number of control volumes (CV) at the centroid ofwhich lies a computational node where the variable values are calculated. The

conservation equations are applied to each CV and interpolation is used to expressvariable values at the CV surface in terms of the centre values.

The most widely used commercially available CFD packages are:

AutoReaGas, from Century Dynamics(http://www.ansys.com/Products/autoreagas.asp)

CFX, from ANSYS, Inc. (http://www.ansys.com/products/cfx.asp)

FLUENT, now also from ANSYS, Inc. (http://www.fluent.com/)

EXSIM, from EXSIM Consultants AS (http://www.exsim-consultants.com/)

FLACS, from GexCon (http://www.gexcon.com/index.php?src=flacs/overview.html)

Kameleon FireEx, from ComputIT (http://www.computit.no/)

2.1 Release modelling

Release modelling also called discharge or source term modelling is mainly used todetermine the rate at which a fluid is released to the environment in a loss ofcontainment incident, together with the associated physical properties (e.g.temperature, momentum).

A simple approach is to calculate the initial rate and to assume that this is constant overtime. This is often used for studies of onshore facilities, especially where the offsite

risk is the motivation for the study.


8/40


OGP4

A more sophisticated approach is to model the time dependence of the release rate.This is often used for studies of offshore facilities, where the time dependence has asignificant impact on the likelihood, in particular, of the initial event escalating. Themodelling required is more complex but avoids certain issues that arise when initial rate

modelling is used:

Initial rate modelling can lead to over-prediction of the flammable/explosive mass in

a vapour cloud

Initial rate modelling can lead to over-prediction of the size of a jet fire over time butunder-predict its duration or the time for which it exceeds a critical length (e.g. toother equipment)

Initial rate modelling can lead to over-prediction of the impact of toxic gas or smokeeffects

In general, time dependence should be explicitly modelled in offshore studies, wherethe impacts over relatively short distances (tens of metres) and over time periods up tothe required endurance times of the TR (Temporary Refuge) and other safety functions,which may be of the order of 1 hour, are of concern. Time dependence is less oftenmodelled in onshore studies, where the impacts over relatively long distances

(hundreds of metres to a few kilometres) and over time periods up to that required foreffective emergency action to commence. An exception to this is the modelling of

cross-country pipeline ruptures, for which time dependence may be important.

2.1.1 Simple approaches to release modelling

Where gas or non-flashing liquid would be released from an orifice, simple formulaeexist to calculate the initial rate, in particular Bernoullis equation for liquids (strictly,incompressible fluids).

Some example release rates are shown in Figure 2.2, Figure 2.3 and Figure 2.4 for

selected representative materials. These were obtained using DNVs PHAST software.

Equations for modelling time-varying releases of gas, including blowdown, are given inthe CMPT Guide to quantitative risk assessment for offshore installations [1]. This alsoincludes a simple method for calculating the flash fraction of a liquid such as

unstabilized crude.

Modelling releases from ruptured pipelines is rather more complex as the pipelinepressure decreases away from the release point over time and so the flow rate

decreases with time, especially for gases. It is therefore normal to use software toolsfor discharge modelling.


9/40


OGP 5

Figure 2.2 Release Rates for Natural Gas at 20C

Figure 2.3 Release Rates for Propane at 20C

Note: at 1 barg and 5 barg the releases are vapour; at higher pressures they are two-phase.


10/40


OGP6

Figure 2.4 Release Rates for Kerosene-type Liquid at 20C (density = 714kg/m3)

2.1.2 Software for release modelling

There is a range of software tools available that include release modelling. As with all

software, its range of validity and limitations need to be understood. For example, thethermodynamics of mixtures may be modelled by an average equivalent purecomponent. However, as computer power increases, this limitation is increasinglybeing eliminated in favour of full multicomponent thermodynamics.

Software can model some or all of the following:

Time-dependent releases, including inflow, isolation and blowdown

Flashing liquid releases

Releases that flash in the atmosphere as they are released

Releases from vessels containing liquid that flashes as the pressure decreases

Releases from vessels of different shapes and orientations

Releases from long pipelines

These models are generally appropriate for use onshore and offshore.

When the fluid after release is two-phase, the modelling needs to predict the liquiddroplet size so that the amount of liquid that rains out (falls to the ground or watersurface) can be calculated as part of the dispersion modelling (Section 2.2).

SPT Groups OLGA software (http://www.sptgroup.com/products/olga) can be used to

model time dependent releases from pipeline networks and includes multiphase flowcapability.

It should be noted that a release from a high pressure reservoir will normally be quitecomplex with sonic flow, expansion and compression shocks. In safety studies, this


11/40


OGP 7

complex outflow is often not calculated and the boundary conditions for the jet aregiven at surrounding pressure. Both the specified momentum and the temperature(density) of this jet may be important for the dispersion simulation and thereby theresulting gas cloud size. Often this boundary condition is specified as pure gas at sonic

velocity at surrounding pressure or lower. This is not conserving momentum andshould not be used when momentum is important for dispersion.

2.1.3 Modelling Releases from Buried Pipelines

Following a full bore rupture there will be flow from both sides of the break. Theconsequences of a full bore rupture of a buried pipeline can be modelled as follows:

1. Initial high flow rate: consider immediate ignition as a fireball, using mass releasedup to the time when this mass equals the fireball mass giving the same fireballduration.

2. Ensuing lower flow rate(s): model dispersion and delayed ignition with low

momentum (velocity) as the flows from both sides of the break are likely to interact.

The following figure illustrates a possible simplification into quadrants of releasedirections for a leak from a buried pipeline. The text beside suggests an approach tomodelling these for medium and large leaks, based on these having sufficient force tothrow out the overburden (and even concrete slabs, if placed on top).

1. Vertical release. Model as vertical release

(upwards) without modification of normal dischargemodelling output, i.e. full discharge velocity.

2, 3. Horizontal release. Model at angle of 45upwards with velocity of 70 m/s.4. Downward release. Model as vertical release(upwards) with low (e.g. 5 m/s) velocity to reflect loss of

momentum on impact with ground beneath.

For small horizontal or downward leaks, the force exerted by the flow is unlikely tothrow out the overburden, hence the flow will only slowly percolate to the surface. Thefollowing approach is suggested for all release directions:

Calculate discharge rate as normal.

Remodel release with a very low pipeline pressure (1 barg for operating pressure

>10 barg, 0.1 barg for operating pressure < 10 barg), to simulate diffusion throughthe soil, with the hole size modified to obtain the same discharge rate as above.

2.2 Dispersion and ventilation modelling

Dispersion modelling is used to determine how the fluid released spreads in theenvironment: usually air but also water1.

Onshore, dispersion is usually modelled for releases into the open air

Offshore, modelling dispersion within an enclosed module is usually required;

modelling underwater releases (e.g. pipeline and flowline failures) is often alsoneeded.

1Dispersion in soil is considered in environmental rather than safety risk studies and is outside

the scope of this datasheet.


12/40


OGP8

When a release is in the open air, several mechanisms may cause it to disperse. Theseare illustrated in Figure 2.5. Not all releases go through all phases. A gas release on anoffshore platform may go directly from turbulent jet to passvie dispersion. A releasefrom a stack may be passive from the stack tip. The vapour in a release of refrigerated

LPG will be dense from the start.

Figure 2.5 Mechanisms of Atmospheric Dispersion of Vapour

A vapour release inside an enclosed volume (a module of an offshore installation or abuilding onshore) will mix with the air flowing through the volume. On offshore facilities

with enclosed modules, what is required for fire and explosion calculations is first of allthe size of the flammable/explosive cloud within the module. Onshore, the vapour cloud

may emerge from a vent or stack, already partially diluted, and then disperse in theenvironment.

When the release is wholly or partially liquid, typically this will fall onto a solid surfaceor through a grated deck to the sea below; on a solid surface it will spread out to form apool. At the same time, some of this liquid may vaporize, adding to any vapour in theinitial release, and will disperse in the atmosphere, as illustrated in Figure 2.6.

Dispersion modelling thus frequently has to be able to model all of these phenomena, in

addition to addressing the different mechanisms of atmospheric dispersion. The


13/40


OGP 9

relationship between many of these phenomena and mechanisms is illustrated in Figure2.1.

Figure 2.6 Pool Vaporisation

2.2.1 Simple approaches to dispersion modelling

Very little dispersion modelling can validly be done using simple formulae. That which

can is as follows:

1. Passive (Gaussian) dispersion

2. Gas build-up in enclosed volumes

Using a Continuous Stirred Tank Reactor (CSTR) model, when it is acceptable to

assume a uniform concentration throughout the volume (e.g. as source term for arelease from a vent or stack, or calculating toxic impact for people indoors)

To calculate the quantity of flammable gas, for explosion modelling (see Section2.4)

3. Oil pool spreading

4. Gas releases subsea.

The equations for passive dispersion, 1, can be found in standard texts on atmospheric

dispersion. The equations for 2 (CSTR model) and 3 are given in [1].

Two simplified methods have been developed to calculate the quantity of flammable gasin an enclosed volume such as an offshore module (2). Section 4.2.3.1 of [2] presents asimple equation valid when the ventilation flow field is close to uniform. A workbookapproach to estimating the flammable volume produced by a gas release [3, 4] has beendeveloped as part of the JIP on Gas Build Up from High Pressure Natural Gas Releases in

Naturally Ventilated Offshore Modules, sponsored by 10 operators and the UK HSE.

For gas releases subsea (4), a common assumption is that the diameter of the plume at

the sea surface is 20% of the water depth at the release point, regardless of the gas flow


14/40


OGP10

rate. This diameter together with the gas flow rate can then be used as input to aGaussian plume model.

Some example dispersion modelling results (distances to LFL) are given in Figure 2.7

and Figure 2.8. These were obtained using DNVs PHAST software.

Figure 2.7 Dispersion Distances to LFL for Vapour Releases at 20C

Note: F1.5 refers to F stability, 1.5 m/s wind speed; D5 refers to D stability, 5 m/swind speed.


15/40


OGP 11

Figure 2.8 Dispersion Distances to LFL for Two-Phase Propane Releases at20C

Note: F1.5 refers to F stability, 1.5 m/s wind speed; D5 refers to D stability, 5 m/swind speed.

2.2.2 Software for dispersion modelling

Atmospheric dispersion modelling software mainly divides into:

Box models, which calculate vapour cloud dimensions and concentrations frombulk properties.

CFD models, which divide the computational domain representing the space

through which the fluid disperses, into small volume elements where physicalproperties are calculated explicitly.

In general, plume models do not allow for the influence of terrain, assuming a flat,unobstructed surface. Plume models cannot model well the near field characteristics of

dispersion within a congested or confined area such as an offshore module or themiddle of a process unit. However, for far field (i.e. in open areas) dispersion and

when numerous release cases need to be run, plume models are ideal.

The software used needs to be selected with an understanding of the phenomena(identified in Section 2.2) likely to occur for the cases being modelled, to ensure that the

software can adequately model them. For example:

A Gaussian plume model would not be appropriate for a gas release under pressure,

which will initially disperse as a turbulent jet (see Figure 2.5)

For releases of pressurised LPG, rain-out and re-evaporation may need to bemodelled.

The results from dispersion modelling need to be examined to ensure they are sensible,i.e. that they match expectations about their behaviour.


16/40


OGP12

FLOWSTAR, a model developed by CERC (www.cerc.co.uk/software/flowstar.htm) forcalculating profiles of the mean airflow and turbulence in the atmospheric boundarylayer, can calculate plume trajectory and spread in complex terrain and over variablesurface roughness. It is limited to passive dispersion (i.e. it cannot be used when fluid

momentum or density is significant) but its ability to model air flow over hilly terrainmay be useful. It is part of the widely accepted ADMS (Atmospheric Dispersion

Modelling System) suite of programs for air pollution modelling.Other software packages such as CALPUFF and INPUFF are available, which are

especially suitable for mid- and far-field applications and for long (> 1 hour duration)releases, however potential users should be aware of their limitations. HGSYSTEM

(www.hgsystem.com) is also well known as a freely available set of DOS-baseddispersion models.

2.2.3 CFD for ventilation and dispersion modelling

CFDs main application in dispersion modelling for QRA is in explosion analysis, ofwhich ventilation and dispersion simulations are an important part.

In explosion analysis for offshore installations, the objective of the ventilationsimulations is to generate a ventilation distribution in terms of rate, direction and

probability. Based on this information, representative wind conditions are selected forthe dispersion simulations. The NORSOK Z-013 standard [21] recommends that at least

8 wind directions are considered for the ventilation simulations. Only one wind speed isnecessary as it is generally assumed that the ventilation rate for a wind direction isproportional to the wind speed so that ventilation rates can be linearly scaled with windspeeds. Also, the number of simulations may be reduced from symmetry

considerations.

The objective of the dispersion simulations in explosion analysis is to identify crediblesize, concentration and location of gas clouds and establish how the flammable gas

clouds varies with the hazardous leak location, external wind speed and direction andleak direction. Those representative gas clouds are subsequently used in the explosionstudies.

Generally, the number of parameters that can be varied is high (leaklocations/rates/directions, wind conditions) and it is unrealistic to simulate all possible

combinations so that a selection must be made. The NORSOK probabilistic approach[21] recommends that at least 3 leak points with 6 jet directions and 1 diffuse leak

should be evaluated. At least one of the scenarios needs to consider leak orientationagainst prevailing ventilation direction. It is, however, possible to reduce the number ofdispersion simulations based on symmetry considerations and the physics of theproblem.

Additionally, not all the identified scenarios (after consideration of symmetry andengineering judgement) need to be simulated. The frozen cloud concept can be used toestimate the results of the scenarios not simulated. This is an assumption that gasconcentration scales with the leak rate and the inverse of the ventilation. The results

from the scenarios not simulated can then be obtained by altering the gas concentrationfield in all control volumes by a constant factor. It is expected [26] that this assumption

will be reasonable in a ventilation dominated region (as opposed to a fuel dominatedregion).


17/40


OGP 13

Although the NORSOK approach is for offshore installations, a similar approach can beapplied to explosion analysis for onshore installations. CFD modelling of ventilationand dispersion is also useful for evaluating optimal geometry layout and location of gasdetectors [22,23]. CFD has also found some application in modelling dispersion in

complex topography (e.g. along a pipeline route), although it is not cost-effective to useit routinely to model explicitly all scenarios typically represented in a QRA.

2.3 Fire and thermal radiation modelling

Fire modelling is typically used to calculate the flame dimensions for 2 purposes:

As input to a thermal radiation model

To determine whether a flame can reach a target for escalation (e.g. otherequipment)

It is important to understand the type of fire that can occur:

Flash fire an ignited vapour plume, whose dimensions are typically determineddirectly from the dispersion modelling as the distance to LFL

Jet fire an intense, highly directional fire resulting from ignition of a vapour ortwo-phase release with significant momentum

Pool fire from an ignited liquid pool2 or sea surface gas pool resulting from asubsea gas release (e.g. from a pipeline or wellhead)

Offshore installations often have grated decks, so a liquid spill will fall through thegrating onto the sea surface. If ignited, the resulting sea fire may engulf one or more

legs of the installation as well as risers and conductors.

Boilover when a full surface fire occurs in an oil storage tank, heat will slowlyconduct downwards to any layer of water in the bottom of the tank; this will then

vaporise and the resulting expansion will hurl boiling oil upwards out of the tank. Fireball/BLEVE

Strictly, a BLEVE (Boiling Liquid Expanding Vapour Explosion) is simply explosivelyexpanding vapour or two-phase fluid. A BLEVE results from a hot rupture of avessel typically containing hydrocarbons such as LPG3, stored and maintained as aliquid under pressure, due to an impinging or engulfing fire. A flammable materialwill be ignited immediately upon rupture by the impinging/engulfing fire and willburn as a fireball.

A fireball would also result from immediate ignition of a release resulting from coldcatastrophic rupture of a pressurised vessel.

The initial phase of a gas pipeline rupture should also be modelled as a fireball.

Crater Fire from ignition of a release from a buried pipeline. For vertical andhorizontal releases (see Section 2.1.3), the corresponding jet fire can be modelled.

For downward releases, the hole size corresponding to the low release velocity canbe taken as the diameter of a gas pool burning as a pool fire.

2Note that it is not the liquid that burns but rather the vapour above it. The heat of the flame

vaporises the liquid beneath to provide the fuel supply.3

BLEVEs of hydrocarbons up to butane or perhaps pentane are credible. A BLEVE of a vessel

containing a toxic material such as chlorine stored as a liquid under pressure is also credibleand should be considered if relevant. BLEVEs of heavier hydrocarbons such as crude oil orpetroleum do not occur.


18/40


OGP14

An appropriate model for the type of fire that could result from ignition of the releasebeing considered can be selected. This will also depend on the time/location of ignition:for example, for a high momentum vapour release, ignition close to the source willresult in a jet fire; ignition at a point away from the source will result in a flash fire or

explosion (see Section 2.4), which may also burn back to a jet fire.

Whatever model is selected, the following parameters of the flame have to be

calculated:

Flame dimensions

Surface emissive power (not for a flash fire)

Fireball only: duration (and possibly lift-off)

2.3.1 Simple approaches to fire and thermal radiation modelling

Some simple models for calculating flame dimensions are given in the sub-sections

below. Calculation of thermal radiation received by a target (e.g. a person) is notstraightforward, although an approximation can be used for a fireball due to itsspherical symmetry (see Section 0), and is best done using software. The simple flamesize models below are therefore best used either when only the flame dimensions arerequired or to provide direct input to a flame radiation model.

2.3.1.1 Jet Fire

A simple correlation for the length L (m) of a jet flame due to Wertenbach [5]:

L = 18.5 Q0.41 [Q = mass release rate (kg/s)]

A generalised formula for different fuel types is [6]:

L = 0.00326 (Q Hc)0.478 [Hc = heat of combustion (J/kg)]

Based on calculations using the Chamberlain model [7], the following roughrelationships for distance along the flame axis to various thermal radiation levels havebeen calculated:

37.5 kW/m2: 13.37 Q0.447

12.5 kW/m2: 16.15 Q0.447

5.0 kW/m2: 19.50 Q0.447

Some example jet fire thermal radiation results for horizontal releases are presented in

Figure 2.9 and Figure 2.10. These were obtained using DNVs PHAST software, whichused the Chamberlain model [7].


19/40


OGP 15

Figure 2.9 Jet Fire Thermal Radiation Distances at Ground Level forPropane Releases at 1 m Elevation

Figure 2.10 Jet Fire Thermal Radiation Distances at Ground Level forReleases at 10 m Elevation


20/40


OGP16

2.3.1.2 Pool Fire

The diameter of an equilibrium pool fire (i.e. where all the fuel is being consumed as it isreleased) is easily calculated by equating the mass release rate over the pool surface

with the burning rate. Burning rates for typical materials are given in Table 2.1.

The pool diameter D (m) is given by:

(assuming constant thickness of the pool)

Table 2.1 Mass Burning Rates for Selected Materials (29] unless indicated)Material Mass BurningRate (kg/m2s) Burning velocity(mm/s)Gasoline 0.05 0.07

Kerosene 0.06 0.07Crude oil 0.05 0.07

Hexane1 0.08 0.11

Butane 0.08 0.13

LNG 0.14 on land [30]0.24 on water [30]

0.242

0.422

LPG 0.11 on land

0.22 on water

0.21

0.42

Notes

1. Condensate may be taken as similar to hexane.2. Calculated from mass burning rate using typical density of 450 kg/m3

Note that a pool fires size may be constrained by a bund (dike) or drainage, and alsothat process areas are often constructed with the floor sloping towards a drain. In bothcases, the resulting pool will not be circular. For modelling thermal radiation from the

fire, most models assume the pool is circular with the diameter of the fire correspondingto the surface area of the pool.

The flame length and tilt angle of a pool fire can be simply calculated using the Thomas

correlation [8]. Other models are referred to in [1].

Some example pool fire thermal radiation results are presented in Figure 2.11 andFigure 2.12. These were obtained using DNVs PHAST software.


21/40


OGP 17

Figure 2.11 Liquid Propane Pool Fire Thermal Radiation Distances atGround Level

Figure 2.12 Kerosene-type Liquid Pool Fire Thermal Radiation Distances atGround Level

Note: The shape of the curves for 12.5 kW/m2

is explained by the decreasing flame surfaceemissive power with increasing pool diameter.


22/40


OGP18

2.3.1.3 Boilover

Boilover can be modelled as a pool fire with:

Diameter equal to the tank diameter

A height of 5 times the tank diameter

Flame thermal emissive power = 150 kW/m

2

However, a boilover also results in considerable rainout of burning hydrocarbon liquid

over a wide area, posing additional risk to people; this may also ignite hydrocarbonvapours above neighbouring tanks.

2.3.1.4 Compartment Fire

For a fire inside an enclosed volume such as an offshore module, the fire size andproperties (in particular, smoke toxicity) depend on two factors:

Whether the fire is large enough to impinge on a wall or ceiling

Whether the fire is fuel- or ventilation-controlled

4

.Figure 2.13 shows a procedure to determine the model required for a gas or 2-phaserelease. A similar approach can be taken for a liquid release.

Lees [9, pp16/286ff] suggests possible approaches and other models for compartment

fires. Although written as applying to fires inside buildings, the text can also be appliedoffshore.

4In the former case there is an adequate supply of air to ensure complete combustion of the fuel;

in the latter case the ventilation is limited and the fuel is not fully combusted.


23/40


OGP 19

Figure 2.13 Procedure for Fire Model Selection (Gas or 2-phase Release)

Note: in a highly confined volume with limited ventilation (e.g. a platform leg), even a small fire

may be ventilation controlled.

2.3.1.5 Fireball/BLEVE

Several models for fireball duration and diameter have been developed. Most are simplecorrelations between these quantities and fireball mass5. One model is due to Prugh

[10]:

Diameter, D (m): D = 6.48 M0.325 [M = fireball mass (kg)]

Duration, td (s): td = 0.825 M0.26

Height of fireball centre, h (m): h = 0.75 D

Surface emissive power, q (kW/m2):

[P < 6 MPa; P is vapour pressure (MPa) at which failure occurs.]

5

When the release is two-phase, the fireball may not consume all the liquid. One possibleassumption is that the fireball mass is calculated assuming 3 the adiabatic flash fraction at theburst pressure, constraining this to be 1.0.


24/40


OGP20

Radiation received, I (kW/m2): I = q F

F = view factor: [x = distance (m) along ground]

= transmissivity:

2.3.2 Software for fire and thermal radiation modelling

The software packages listed in Section 2.0 model the fire types listed in Section 2.3,apart from compartment fires. They will model the flame dimensions and orientation,and thence the thermal radiation received.

For a compartment fire, if the fire inside the module is a diffusive fire smaller in volume

than the module, it can be modelled as a pool fire with the dimensions suggested inSection 2.3.1.4; the surface emissive power can be taken to be the same as that of the

unimpinged jet fire.

2.3.3 CFD for fire and thermal radiation modelling

CFD models can be used to determine the fire loading on critical areas on both offshorestructures and onshore plants. The Oil and Gas UK guidance [24] provides a state-of-the-art review of CFD fire modelling. In particular, it is stated that although CFD modelsprovide a more realistic representation of the flow physics, there are uncertaintiesassociated with modelling turbulent flow and combustion as well as in definition of fire

source and ambient conditions. Commonly used software for fire modelling includeKameleon FireEx and CFX. Kameleon FireEx is typically used for fire modelling onoffshore platforms and onshore plants; CFX is more commonly for low geometryscenarios, e.g. fire and smoke modelling in tunnels.

For CFD fire modelling, it may be best to reduce the size of the problem by modellingonly a subset of the installation. Otherwise, the run times for the analyses would be very

long. The procedure for running the fire analyses can be summarised in the followingsteps:

1. Define leak size and select realistic leak locations;

2. Select leak directions. Typically, the analyses are run for up to 6 leak directions;

3. Run the fire simulations for different leak rates for each leak location and directionuntil steady state conditions are reached.

Huser [25] describes a probabilistic procedure for the design of process against fires

using CFD modelling. The probabilistic assessment provides a Dimensioning AccidentalLoad (DAL) fire that is used for design of the structure and allows for the developmentof a consistent methodology (similar to explosion approach) for calculating fire loads.The methodology is illustrated in Figure 2.14.


25/40


OGP 21

Figure 2.14 Probabilistic Procedure for Establishing DimensioningAccidental Load (DAL) Fire and Mitigating Measures (from [25])

[25] has shown that for CFD simulations of jet fires the following parameters areimportant (i.e. resulting in more than 20% variation in the heat loads when all otherparameters are kept constant):

Initial leak rate and leak profile Leak and fire location


26/40


OGP22

Jet direction

Dynamic development of fire

Geometry layout and

Deluge

The probabilistic approach can be used to generate a fire exceedance curve from whichthe DAL fire can be obtained.

2.4 Explosion modelling

For QRA and associated studies, explosions are usually taken to mean vapour cloud

explosions (VCEs). However, other types of explosion are possible (see Figure 2.1):

Condensed phase explosions

Dust explosions

Runaway reactions

In addition, BLEVEs and vessel bursts generate overpressures that may be significant.However, this section focuses on VCEs.

Huge advances in understanding and modelling of VCEs have been made in the lastdecade since the Spadeadam tests. For offshore, the NORSOK standard Z-013 [11] hasestablished a comprehensive but computationally demanding approach to explosionmodelling, requiring use of an advanced CFD tool. Whilst originally developedspecifically for platforms in Norwegian waters, this approach is being adopted in other

areas of the North Sea. Although CFD models cannot yet be incorporated directly within(offshore) QRAs, output from QRA is increasingly expected to be used in them.

Onshore, CFD is less well established in QRA whilst the application of simpler modelsavailable in general purpose software is becoming more sophisticated and considered

fit for purpose. However, where design or layout decisions may critically depend onexplosion risks, use of CFD for specific scenarios would give additional robustness to,

and confidence in, the results. Another issue where CFD would assist is where terraineffects are important, for example if a facility is built on a slope or at the foot of a hill: inthis case dispersion would be significantly modified compared with that which wouldresult over flat ground.

The recent advances in understand of explosions referred to above mean that theprevious classification of VCEs as unconfined, semi-confined or confined can now beconsidered over-simplistic. It would be better to talk about degrees of confinement andcongestion6. TNOs Multi-Energy model [12], discussed further in Section 2.4.2, allows

for 10 levels of confinement/congestion, ranging from the equivalent of a UVCE

(Unconfined Vapour Cloud Explosion) through to highly confined/ congested volumessuch as can be found in a densely packed process area of an onshore plant. In this andsimilar models, some assessment or assumption needs to be made outside of themodel as to the maximum overpressure. In CFD modelling, the distinction betweenlevels of confinement/ congestion disappears since the geometry is defined and thesoftware itself calculates the maximum overpressure.

6

Confinement should be thought of as a solid barrier preventing flame acceleration in a certaindirection; congestion as a porous barrier, or set of discrete obstructions, inducing turbulence inthe flow and modifying (increasing) flame acceleration in a certain direction.


27/40


OGP 23

2.4.1 Simple approaches to explosion modelling

Historically, simple TNT equivalence models have been used for modelling explosionoverpressures from unconfined VCEs (UVCE) onshore. However, these require the

explosive mass to be calculated: as this is an output from dispersion modelling, manualcalculation of explosion overpressures is not likely to be undertaken.

Another old approach for onshore QRA [13] calculates the distance to specified levelsof damage directly from the explosion energy by a simple correlation. Again, this

requires the explosive mass to be calculated.

2.4.2 Software for explosion modelling

2.4.2.1 Onshore explosions

General purpose consequence modelling software (see list in Section 2.0) includeseither of both of two well established explosion models: the TNO Multi Energy model[12] and the Baker Strehlow or Baker Strehlow Tang model [14].

In the Multi Energy model , a vapour cloud is divided into the regions of congestion,or blast sources, they may enter and fill (or partially fill). Each of these blast sourcesis treated independently of the others. The material and the volume of the cloud withinthe blast source are used to calculate the explosion energy. A confined explosion

strength is assigned to the blast source by the analyst: this strength corresponds oneof 10 lines on a graph of peak side-on overpressure vs. scaled distance from the source.

The 10 lines represent a range of maximum overpressures (at the source) ranging from0.01 to 13 bar. Selecting the correct confined explosion strength for a given situation(e.g. a specific process unit on a refinery) is far from straightforward, although generallyno. 7 or 8 is used for process units. Guidance [15] has been developed to assist this,although even with this it is strongly recommended to call upon experienced personnel

to make the assessment.

In the Baker Strehlow Tang model the analyst selects instead the material reactivity(high, medium, or low), flame expansion (number of directions in which the flame can

expand), obstacle density (high, medium, or low), and ground reflection factor (1 for airburst, 2 for ground burst and hence ground reflection). This has two advantages over

the Multi Energy model:

Materials of different reactivities can be adequately represented

Selection of flame expansion and obstacle density is simpler

As in the Multi Energy model, the overpressure vs. scaled distance is a set of curves (in

this case 11) that span the range of input selections.

These models are appropriate for use in studies of onshore facilities including marine

terminals.

2.4.2.2 Offshore explosions

For offshore installations, non-CFD software has been used to estimate maximumoverpressures in modules using relatively simplified methods that nevertheless take

account of the broad features of module geometry. For example, DNV have used theirprograms COMEX and NVBANG in numerous studies, however these programs are notavailable commercially and are not recommended for non-specialists in explosion

modelling.

However, in offshore applications the maximum overpressure itself is usually not useddirectly in the risk calculations. Rather, it represents the worst case combination of

module fill, release location and ignition location. In a real situation, this combination is


28/40


OGP24

unlikely to be achieved and a lower overpressure will be reached. Of direct concern isthe likelihood of an explosion that will result in equipment escalation or breaching of theTR wall, for example. This requires a probabilistic approach to estimate the likelihoodof any given explosion overpressure being exceeded at a specific location. This is the

approach set out in the NORSOK standard Z-013 [11]. CFD modelling is used to modelexplosion overpressures for a number of scenarios. The results are then combined with

leak frequencies, ignition data and wind probabilities in another software package (e.g.DNVs EXPRESS) to develop overpressure exceedence probability curves for use in theQRA. The same approach can be used for more specific design problems, for exampledesigning an ESD or deluge system to withstand the drag forces likely to result from anexplosion.

This approach requires considerable investment of effort to obtain useful and robustresults. Previous, more simplified methods have the appearance of being less costly toachieve the same end. However, the initially more costly NORSOK approach [11] can beused to cost-optimise the design of a module for explosions, eliminating the need forexcessive and hence costly conservatism (i.e. over-engineering).

2.4.3 CFD for explosion modelling

The representative gas clouds from the CFD dispersion analysis (see Section 2.2.3) canbe ignited and explosion analysis carried out. The Oil and Gas UK guidance [24] reportsthat it is not recommended to use dispersed non-homogeneous and turbulent gas

clouds in CFD explosion simulations due to the lack of testing/validation for thisapplication. Instead, an equivalent quiescent stoichiometric gas cloud, that gives similar

overpressures to the non-homogeneous and turbulent clouds, has to be calculated.

As an example of how this can be done, the FLACS software automatically calculates aparameter (referred to as Q5) that converts the non-homogeneous cloud into anequivalent quiescent gas cloud. It should be noted that the duration of the equivalent

gas cloud may be shorter than the non-homogeneous one resulting in a difference inthe structural response.

The explosion simulations should be carried out for various gas cloud sizes and

shapes, gas cloud locations and ignition locations. For each gas cloud size, the gascloud location and ignition location should be varied. In particular, it is important tolocate the clouds close to critical and congested areas of equipment and piping.

The ignition location will also have a strong impact on the explosion loads. Generally,

the CFD analyses are run with two different locations namely ignition location at centreof cloud and at edge of cloud. Depending on the geometry and layout, edge ignition willsometimes produce the higher (than central ignition) explosion overpressures due tothe increased flame distance.

Results in terms of explosion overpressures can be output at monitor points at pre-defined locations and drag forces can be obtained for design of critical equipment andpiping.

2.5 Smoke and gas ingress modelling

Modelling of smoke and gas ingress to the TR or living quarters usually forms part of anoffshore QRA and could also be used in onshore studies. More generally, modelling of

smoke generation and dispersion can be useful to determine the likelihood of escaperoutes being impaired or of people out-of-doors being overcome by smoke.

Smoke and gas ingress modelling has up to 4 stages:

Source Term

Dispersion

Ingress

Effects


29/40


OGP 25

The source term comes from the release rate modelling (Section 2.1): directly for gasand from suitable ratios of (mass of smoke) / (mass of hydrocarbon released).Dispersion can be modelled as suggested in Section 2.2. Since smokes largestconstituent is nitrogen (i.e. the unburnt part of the air involved in combustion), one

approach used has been to model the smoke as hot, dense nitrogen, giving it amolecular weight and temperature equal to those estimated for the combustion gases.

However, the high temperature invariably results in a rapidly rising smoke plume thatdoesnt match experience. For example, photographs of smoke from the Piper Alphadisaster show the plume travelling almost horizontally. One possible reason is that thesoot particles in the smoke increase the plumes density. Hence this approach is notrecommended for 3D results. However, it may be used to determine the smoke

concentration at a given distance horizontally from the release point, assuming as aworst case that this is the centreline concentration.

2.5.1 Simple approaches to smoke and gas ingress modelling

The CMPT Guide to quantitative risk assessment for offshore installations [1] provides dataand references on smoke generation, composition, dispersion, visibility reduction,

ingress to TR and impact.

A series of linked models has been used in offshore QRAs for BP and other operators:

Smoke generation:

Composition from [16]: see Table 2.2

Depends on fuel (light = gas, heavy = condensate/oil)

Depends on whether fire is fuel-controlled, ventilation-controlled or in between

these.

Table 2.2 Smoke Composition DataFuel Type*Fire Area Type Component Light Heavy

a) Fuel Controlled Carbon Monoxide (ppm)Carbon Dioxide (%)Oxygen (%)Smoke Temperature (C)Particulates (dB/m)

40010.90

1,00015

80011.80

1,00047

b) Ventilation Controlled Carbon Monoxide (ppm)Carbon Dioxide (%)Oxygen (%)Smoke Temperature (C)

Particulates (dB/m)

30,0008.20

600

29

31,0009.20

600

70* The light composition is used for gas jet fires. The heavy composition is used forcondensate fires.

Dispersion: based on a dilution factor, which is a function of fuel burn rate and of

distance from source (does not take into account wind speed or the presence ofbarriers).

Figure 2.15 shows dilution factors, based on calculations using FLACS [17], for

different release rates.

Smoke Ingress:


30/40


OGP26

CO and CO2 build-up in the module are calculated using a CSTR model, taking asinput the smoke concentration immediately outside the TR and the TRsventilation rate

The CO2 concentration calculation also includes exhaled CO2 from personnelinside

The internal temperature is also calculated based on heat generated by TRoccupants

Figure 2.15 Smoke Dilution Factors

Smoke effects/toxicity

Based on dose relationships given in [18]

Considers toxicity of CO; effects of CO2, lack of oxygen and high air temperature;visibility reduction

For gas ingress a set of dilution factors is used, equivalent to but different from thoseused for smoke. A CSTR model is used for gas ingress, and fatalities in the TR areassumed to occur if the gas concentration exceeds 60% of LFL.

2.5.2 Software for smoke and gas ingress modelling

For smoke dispersion in the open, general purpose consequence modelling softwaresuch as the packages listed in Section 2.0 is sometimes used. However, the validity ofthis approach and its superiority to the simple approach described in Section 2.5.1 are

uncertain.

For smoke and gas build-up within modules, multizone models such as COMIS can beused. Multizone modelling involves solving mass balance equations for the flow

between different zones, thus allowing for partitioning due to smoke barriers, walls

between rooms, etc. Multizone models were developed primarily to predict airflow inbuildings, but they are also capable of predicting the transient transport of


31/40


OGP 27

contaminants such as smoke. The method is applied by considering a building as beingdivided into a number of zones (typically rooms) that are physically separated from oneanother. As with the CSTR model, each zone is treated as fully mixed. The rate at whichair flows between zones is governed by the pressure difference and the modelled

connection (i.e. doors, ducts etc.) between the rooms. Multizone models have some ofthe characteristics of both CFD and the CSTR model; conceptually the approach lies

between the two in terms of resolution and complexity.2.5.3 CFD for smoke and gas ingress modelling

CFD modelling can be used to provide a detailed prediction of the smoke distribution inTR or living quarters. The effect of heat sources due to people and computingequipment can be included in the analysis. However, smoke modelling using CFD canbe quite difficult due to the variability and uncertainty in the boundary conditions [26]. Arecent article by ODonnell et. al. [27] provides a comparison of different approaches tosmoke modelling namely the CSTR model, a multizone model and a CFD model. CFX

and Kameleon FireEx can be used to carry out detailed CFD smoke modelling.

The smoke and gas dilution factors used in the models described in Section 2.5.1 weredetermined using FLACS, a CFD package. This or another CFD package could be used

directly to model smoke dispersion from a source in the same way as described inSection 2.2.3 for gas dispersion modelling in general. However, the approach describedin Section 2.5.1 has generally been accepted as fit for purpose in QRAs.

CFD is more likely to be useful in design, for example in locating HVAC air intakes to

minimise the likelihood of smoke ingress. Although best practice is to place them onthe TR face away from potential smoke sources (i.e. fires), flow around bluff bodies

results in zones of recirculation and hence of enhanced smoke concentration.

2.6 Toxicity modelling

The toxic effects of a material may be acute (resulting from accidental exposure to ahigh concentration over a short period of time) or chronic (resulting from continuousexposure to a lower concentration over a long period of time, as a result of routine

emissions or a small, undetected leak). Different toxic materials have differentphysiological effects: they may inhibit respiration (causing asphyxiation) through

inhalation, they may affect the central nervous system, they may be ingested orabsorbed through the skin. For the purposes of this datasheet, the discussion is limitedto acute effects and it is not necessary to consider the nature of the physiological

effects. The discussion addresses toxicity on the basis of dose-response relationships(see below).

Offshore, besides smoke (as discussed in Section 2.5), toxic modelling is usually limited

to the effects of sour gas, i.e. H2S.

Onshore, besides H2S (in onshore hydrocarbon production, transport and processing),other toxic materials are potentially of concern. Toxic consequences are invariablybound up with toxic effects: that is, a model for toxicity is a model for lethality or lesser

effects.

Toxicity data is typically encountered in two forms when required for QRA: specifiedconcentrations such as the IDLH (Immediate Danger to Life and Health), or

concentration-lethality levels for different species such as rats. Such data can be foundin Material Safety Data Sheets (MSDS) or online reference sources such as CHRISwww.chrismanual.com.


32/40


OGP28

For QRA, a dose-response relationship is often used that relates the lethality to the dosereceived at a point. At its simplest, the dose is given by (concentration time),assuming the concentration remains constant over time. However, for many materials,the effect of concentration is magnified and, for concentration C and exposure time t,

the relevant dose A is given by:

Note that the exponent n is not necessarily an integer.

In its regulatory work the UK HSE (e.g. 19] uses two values of A:

SLOT (Specified Level Of Toxicity) Dangerous Toxic Load: the dose that results inhighly susceptible people being killed and a substantial portion of the exposed

population requiring medical attention and severe distress to the remainderexposed. It represents the dose that will result in the onset of fatality for anexposed population (commonly referred to as LD1 or LD1-5)

SLOD (Significant Likelihood Of Death): is defined as the dose to typically result in50% fatality (LD50) of an exposed population and is the value typically used for

group risk of death calculation onshore.

Values of the SLOT and SLOD for selected materials are given in Table 2.3. As can beseen in the final column, values of n for these materials range from 1 to 4.

Table 2.3 SLOT & SLOD Values for Selected MaterialsSubstance SLOT SLOD nAmmonia 3.78 10

81.09 10

92

Carbon monoxide 40125 57000 1

Chlorine 1.08 105

4.84 105

2

Hydrogen sulphide 2.0 1012 1.5 1013 4Sulphur dioxide 4.66 10

67.45 10

72

Hydrogen fluoride 12000

41000 1

Oxides of nitrogen 96000 6.24 105

2

Note: these values are based on concentration in ppm, time in minutes.

As stated above, the LD50 is often used in risk calculations. The HSEs approach allowsfor calculation of the LD50 for any exposure duration.

The most sophisticated approach to determining toxicity adopts the same approach to

calculating the dose but allows the lethality to be calculated for any given concentrationand duration of exposure. This is the probit. A probit value Pr is calculated (for aconstant release rate and hence concentration7) as:

where a, b and n are all material specific constants (n is the same as above).These constants have been published for many commonly encountered materials in a

number of sources [e.g. 9,20]. A table relating lethalities to probits can be found inmany places e.g. [9].

7For a time varying release rate and hence concentration, the (C

nt) can be replaced by an integral

over time.


33/40


OGP 29

2.6.1 Simple approaches to toxicity modelling

The toxic dose should always be calculated using the relationship discussed in

the text preceding this sub-section. It therefore requires results from dispersionmodelling (Section 2.2) together with the exposure time. Calculation of the LD50 usingthe HSE approach described in the text preceding this sub-section is recommended as

the best simple approach and will be sufficient for many purposes.

2.6.2 Software for toxicity modelling

The software listed in Section 2.0 will calculate probits for toxic materials and thencethe lethality level as a function of distance from the release point or as contours ofdifferent lethalities overlaid on a plan or map. In this way the lethality at any point canbe determined for a given wind direction.

2.6.3 CFD for toxicity modelling

CFD will provide as output the concentration at any point. This could be used togetherwith a SLOT/SLOD value or probit to calculate lethality at that point. Contour plots oftoxic lethality are not available from CFD software but could probably be generated fromtabular output.

3.0 Guidance on use of approaches3.1 General validity

The approaches described in Section 2.0 are based on published sources that arewidely known and accepted.

All modelling of physical phenomena is imperfect. Any use of software must be withinthe limitations set out for the software, and even then the analyst must carry out areality check on the results. For example: a jet fire model applied to a large, highpressure gas release will predict a jet flame several hundreds of metres long; theanalyst must consider whether this is credible, or whether the flame will impinge on an

obstruction within this distance.

Depending on the application, a simple model may be fit for purpose, or detailedmodelling (e.g. using CFD) may be required. Whilst it may be considered desirable touse CFD as much as possible, the resources (time, trained personnel, and budget)required to use it effectively are rarely available; hence it is usually used to addressspecific problems or to provide results for a limited set of scenarios that can be applied

or extrapolated to all the scenarios being modelled in a QRA.

In the early stages of design, the detailed design information required for CFD to giveaccurate predictions of overpressures is not available and hence decisions based on

CFD results may result in under-design for the potential overpressures.


34/40


OGP30

3.2 Uncertainties

All modelling suffers from uncertainties. For a given set of input (initial) conditions, it isunlikely exactly to match the physical outcome that would result in reality from the

same initial conditions. Indeed, numerous physical realisations of the same releasewould give different results, whereas consequence modelling software gives the same

result each time8. Sources of uncertainty in consequence modelling for QRA includethe following:

A QRA only models a limited range of cases, so the conditions of an actual releaseare unlikely to match exactly any of the cases modelled in a QRA

Ambient conditions (wind speed, wind direction) do not stay constant over the

duration of a release as is modelled

Box models for dispersion, and models of equivalent complexity for otherphenomena, cannot deal with solid or porous barriers (buildings, process units,bund walls, etc.)

CFD cannot model sub grid scale turbulence (see Section 0)

3.3 Choosing the right approach for consequence modelling

As set out in Section 2.0, whilst simple models are available for some consequences,

and a range of numerical results for some consequences are given there, someconsequence modelling requires the use of either general purpose or CFD software. Todecide which is the best approach it is necessary to decide:

What is the scope of the study?

What is the required depth of the study?

How many release scenarios will be modelled?

Who will carry out the study?

Will the analysis need to be updated in the future, or the results interrogated? If so,who will do this?

If the scope is a full, detailed QRA, then most or all of the 6 steps described in Section2.0 will need to be undertaken. This means that the output from one step of the analysiswill become the input to the next step, and it is important to make the links between the

steps as straightforward and robust as possible. This in turn suggests that generalpurpose consequence modelling software where the transitions from one model to thenext are automated is preferable to using a mixture of models from different sources

(perhaps with some implemented in spreadsheets, others coded). However, in this casethe automated transitions may be black box-like and so the analyst needs tounderstand fully how these work to ensure that the results represent physical reality.(For example, that a modelled jet fire is a credible outcome.)

If a coarse QRA of a simple installation is to be undertaken, a simpler approach may beacceptable. This could use the correlations given or referred to in Section 2.0, or theconsequence results presented in that section.

8

Monte Carlo modelling could be used to vary slightly the input parameters but this does notappear to be done routinely. Another type of dispersion modelling, random walk modelling,likewise does not appear to be used for QRA.


35/40


OGP 31

For a QRA of an offshore installation with enclosed modules, use of CFD for explosionmodelling is now routinely used. For a new installation, it will almost certainly have tobe used in order to design for explosions. For an existing installation, explosionmodelling predating the Blast and Fire Engineering for Topside Structures JIP will probably

have been revised using CFD. Thus it is likely that the necessary CFD modelling willhave been done, or at least that the geometry model has been built and it will be

relatively straightforward to obtain any additional results required.For QRAs of onshore installations, use of the TNO Multi Energy Model or the Baker

Strehlow Tang model (see Section 2.4.2.1) is strongly recommended over use of earlierVCE models.

For problems of a more limited nature, in particular decisions about significantinvestment in relation to fire or explosion and especially in relation to offshorestructures, it is advisable to use CFD in order to maximise the robustness of theanalysis and the confidence in the results.

CFD modelling requires considerable experience and expertise to use effectively. It is

rare for a risk analyst skilled in all aspects of QRA to possess the required degree of

specialist expertise. CFD analysis should therefore be assigned or contracted topersonnel with the required expertise.

3.4 Geometry modelling for CFD

Generally, the numerical grid in CFD models is not fine enough to resolve the smaller

items of equipment and pipe work which are responsible for a large part of theturbulence generated during an explosion. Most of the software (FLACS, EXSIM,AutoReaGas) uses a so-called distributed porosity concept (Porosity, DistributedResistance (PDR) model) to account for the objects which cannot be represented by thegrid. The porosity model is used to calculate the turbulence source terms due to those

small items and the flame speed enhancement arising from flame folding in the sub gridwake.

Explosion relief panels and yielding walls can also be represented by modifying theporosity in the region where they occur.

It is important that all the geometric details are properly represented in a CFD model due

to their importance in pressure build-up. The particular areas where gas explosionanalyses are carried out must be modelled with a high degree of accuracy. In the early

design stages, no detailed description of the geometry exists and this may pose aproblem with regard overpressure prediction. There are two ways in which this problem

can be circumvented namely by applying a factor for equipment growth to account andby adding anticipated congestion to obtain final expected object density and

distribution.The Oil and Gas UK guidance [24] reports on a detailed investigation of a typical North

Sea integrated deck platform which showed that, for good prediction of overpressures,definition of all major equipment, boundaries (decks, TR), all piping with diameters >

0.2 m, and primary/ secondary structures with cross-section dimensions > 0.13 m isrequired.

In addition, it is important to define the CFD grid to extend quite a large distance fromthe area of interest to avoid too strong influence from open boundaries.


36/40


OGP32

4.0 Review of data sourcesKey general sources for suitable consequence modelling methods are the Guide toquantitative risk assessment for offshore installations [1] and Lees Loss Prevention in the

Process Industries [9]. These have been supplemented by more specific publishedpapers and books as listed in Section 6.1: all of these are believed to have found wide

acceptance in the QRA community including with regulatory authorities.

The general purpose software packages listed in Section 2.0 are all commercially

available. Validation data for them, if required, should be sought from the softwareproviders. The EU SMEDIS project [28] in particular has compared the leading

dispersion models with results from experimental measurements.

The basis of the suggested approach to modelling releases from buried pipelines(Section 2.1.3) is confidential work carried out by DNV on behalf of clients (personal

communication). No published methodology has been found.

The basis of the suggested approach to modelling boilover (Section 2.3.1.3) is the Dyfed

Fire Brigade video of the Amoco Milford Haven refinery tank fire. The flames from theboilover reached a height of 3000 feet, or about 10 times the tank diameter; however,

they were not continuous or constant to this height over a typical period of interest, andwere partly obscured by smoke. Hence a height of 5 times tank diameter appearsreasonable.

For explosion modelling, FLACS and AutoReaGas have been extensively validatedagainst experimental data, in particular from the Phase 2 and Phase 3 JIP Blast and FireEngineering for Topside Structures experiments carried out at Spadeadam and elsewhere.FLACS is also currently being validated for hydrogen as part of the EU HySafeprogramme. Details of FLACS and AutoReaGas validation are available on their

respective websites (see Section 2.0).

5.0 Recommended data sources for further informationFor further information, the data sources referenced in Sections 2.0 to 4.0 should beconsulted. Some additional references are given in Section 6.2.

On the subject of subsea releases, two major reports 32], [33] were published in 2007and 2008 and should be consulted if detailed information is required (i.e. if subseareleases appear to pose a significant risk).

6.0 References6.1 References for Sections 2.0 to 4.0

1. Spouge, J, 1999. A guide to quantitative risk assessment for offshore installations, CMPTpublication no. 99/100, ISBN 978-1-870553-36-0 / 1 870553 36 5. Now available fromthe Energy Institute www.energyinst.org.uk.

2. Czujko, J (ed.), 2001. Design of Offshore Facilities to Resist Gas Explosion Hazard

Engineering Handbook, Sandvika: CorrOcean ASA.

3. BP Amoco, CERC and BG Technology, 2000. Workbook on Gas Accumulation in aConfined and Congested Area, Joint Industry Project Gas Build Up from High PressureNatural Gas Releases in Naturally Ventilated Offshore Modules. [Believed to beavailable only to sponsors but summarised in the following reference.]

4. Cleaver, R P and Britter, R E, 2001. A Workbook Approach to Estimating the Flammable

Volume Produced by a Gas Cloud, Paper R416, FABIG Newsletter: Issue 30, 5-7.


37/40


38/40


OGP34

24. Oil and Gas UK & HSE, 2007. Fire and Explosion Guidance, publication no. EHS24.Available from Oil and Gas UK http://www.ukooa.co.uk/ukooa/.

25. Huser, A, 2006. Probabilistic procedure for design of process areas against fires,

FABIG Newsletter44 . Available from FABIG www.fabig.com.26. Talberg, O, Hansen, O R, Bakke, J R, and Wingerden, K. Application of a CFD-based

probabilistic explosion risk assessment to a gas-handling plant, conference paperavailable from CMR-Gexcon http://www.gexcon.com/download/ERA_00-Paper.pdf.

27. ODonnell, K, Deevy, M, and Garrard, A, 2007. Assessment of mathematical models

for prediction of smoke ingress and movement in offshore installations, FABIGNewsletter48 . Available from FABIG www.fabig.com.

28. Daish, N C, Britter, R E, Linden, P F, Jagger, S F, and Carissimo, B, 1999. ScientificModel Evaluation techniques applied to dense gas dispersion models in complexsituations, Intl Conf. on Modelling the Consequences of Accidental Releases ofHazardous Materials, CCPS, San Francisco, California, September 28 October 1.

29. Mudan, K S, and Croce, P A, 1988. Fire Hazard Calculations for Large OpenHydrocarbon Fires, Fire Protection Engineering, Section 2 Chapter 4, Society of FireProtection Engineers, National Fire Protection Association.

30. Cleaver P, & Johnson, M, 2004. LNG Behaviour, Fire and Blast Issues related to LNG,FABIG Technical Review Meeting, London & Aberdeen, October 6 7.

6.2 References for other data sources

31. CCPS 1994. Guidelines for Evaluating the Characteristics of Vapour Cloud Explosions,Flash Fires and BLEVES, New York: American Institute of Chemical Engineers.

32. Fannelp, T K, and Bettelini, M, 2007. Very Large Deep-Set Bubble Plumes FromBroken Gas Pipelines, Report No. 6201, Project No. 99B43, Petroleum Safety Authority

Norway.33. Tveit, O J, and Huser, A, 2008. Risiko knyttet til gassutslipp under vann. Viderefring

2007, Spredning over havet, Petroleum Safety Authority Norway.


39/40

For further information and publications,please visit our website at

www.ogp.org.uk


40/40

209-215 Blackfriars RoadLondon SE1 8NLUnited KingdomTelephone: +44 (0)20 7633 0272Fax: +44 (0)20 7633 2350

165 Bd du Souverain

434-07 consequence modelling - ogp

Documents