434-07 Consequence Modelling - OGP

Risk Assessment Data Directory Report No. 434 – 7 March 2010

Consequence modelling International Association of Oil & Gas Producers

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ublications

Global experience Te International Association o Oil & Gas Producers has access to a wealth o technical knowledge and experience with its members operating around the world in many diferent terrains. We collate and distil this valuable knowledge or the industry to use as guidelines or good practice by individual members.

Consistent high quality database dat abase and guidelines Our overall aim is to ensure a consistent approach to training, management and best practice throughout the world. Te oil and gas ga s exploration and production industry recognises the need to develop consistent databases and records in certain elds. Te OGP’s members are encouraged to use the guidelines 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 and saety and environmental bodies. Requests come rom governments and non-government organisations around a round the world as well as rom  rom non-member 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, regardless of its or their negligence, assume liability for any foreseeable or unforeseeable use made thereof, which liability is hereby excluded. Consequently, such use is at the recipient’s own risk on the basis that any use by 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 proide guidance supplemental to the requirements of local legislation. Nothing herein, however, is intended to replace, amend, supersede or otherwise depart om such requirements. In the event of any conict or contradiction between the proisions 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. Permissi Permission on is given to reproduce this report in whole or in part proided (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 goerned by and construed in accordance with the laws of England and Wales. Disputes arising here om shall be exclusively subject to the jurisdiction of the courts of England and Wales.

P

ublications

Global experience Te International Association o Oil & Gas Producers has access to a wealth o technical knowledge and experience with its members operating around the world in many diferent terrains. We collate and distil this valuable knowledge or the industry to use as guidelines or good practice by individual members.

Consistent high quality database dat abase and guidelines Our overall aim is to ensure a consistent approach to training, management and best practice throughout the world. Te oil and gas ga s exploration and production industry recognises the need to develop consistent databases and records in certain elds. Te OGP’s members are encouraged to use the guidelines 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 and saety and environmental bodies. Requests come rom governments and non-government organisations around a round the world as well as rom  rom non-member 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, regardless of its or their negligence, assume liability for any foreseeable or unforeseeable use made thereof, which liability is hereby excluded. Consequently, such use is at the recipient’s own risk on the basis that any use by 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 proide guidance supplemental to the requirements of local legislation. Nothing herein, however, is intended to replace, amend, supersede or otherwise depart om such requirements. In the event of any conict or contradiction between the proisions 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. Permissi Permission on is given to reproduce this report in whole or in part proided (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 goerned by and construed in accordance with the laws of England and Wales. Disputes arising here om shall be exclusively subject to the jurisdiction of the courts of England and Wales.

RADD – Consequence modelling

contents

2.1

Release Release modelling modelling ................ ........................ ................. ................. ................ ................ ................. ................. ................ ................ ........ 3

2.1.1 2.1.2 2.1.3

Simple approaches approa ches to release modelling ................................... .............................. 4 Software for release modelling .............. ..................... ............... ............... .............. .............. ............... ............... .............. .............. ......... .. 6 Modelling Releases from Buried Pipelines.............. Pipelines...................... ............... .............. .............. ............... ............... ........... .... 7

2.2

Dispersion and ventilation modelling ................... ...................... .................. 7

2.2.1 2.2.2 2.2.3

Simple approaches to dispersion modelling.................. modelling......................... .............. .............. .............. ............... ............. ..... 9 Software for dispersion modelling .............. ..................... ............... ............... .............. .............. ............... ............... .............. ......... 11 CFD for ventilation and dispersion modelling.................. modelling......................... .............. ............... ............... .............. ......... 12

2.3

Fire and thermal radiation modelling.................... modelling .................... ...................... ................ 13

2.3.1 2.3.2 2.3.3

Simple approaches to fire and thermal radiation modelling.................. modelling......................... .............. ....... 14 Software for fire and thermal radiation modelling ............... ...................... .............. .............. .............. ............ ..... 20 CFD for fire and thermal radiation modelling .............. ..................... ............... ............... .............. .............. ............. ...... 20

2.4

Explosion modelling...................... modelling ...................... ...................... ...................... ................... 22

2.4.1 2.4.2 2.4.3

Simple approaches to explosion modelling .............. ..................... .............. .............. ............... ............... .............. ......... 23 Software Softwar e for explosion modelling ................................... .................................... .... 23 CFD for explosion modelling ............... ...................... .............. ............... ............... .............. .............. .............. ............... ............... ......... .. 24

2.5

Smoke and gas ingress modelling..................... modelling ..................... ...................... ................... 24

2.5.1 2.5.2 2.5.3

Simple approaches to smoke and gas ingress modelling ............... ...................... .............. ............. ...... 25 Software for smoke and gas ingress modelling................ modelling....................... ............... ............... .............. .............. ....... 26 CFD for smoke and gas ingress modelling ............... ...................... .............. .............. ............... ............... .............. ......... 27

2.6

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

2.6.1 2.6.2 2.6.3

Simple approaches to toxicity modelling .............. ..................... .............. ............... ............... .............. .............. ............ ..... 29 Software Softwar e for toxicity modelling ................................. .................................... .......... 29 CFD for toxicity modelling ................................... .................................... ................ 29

3.1 3.2 3.3 3.4

General validity ................... ...................... ...................... ..................... ......... 29 Uncertainties .................... ..................... ...................... ...................... ............ 30 Choosing the right approach approach for consequence modelling ...................... . 30 Geometry modelling for CFD ................... ...................... ..................... ......... 31

6.1 6.2

References for Sections 2.0 to 4.0 ................ ......................... ................. ................ ................ ................. ............. .... 32 References for other data sources..................... sources........................................... ...................... ................... 34

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Abbreviations:: Abbreviations BLEVE CFD CHRIS CSTR CV DAL DNV EU FV HSE HVAC IDLH JIP LDx LFL LPG MSDS PDR QRA SLOD SLOT SVP TNO Onderzoek TR UVCE VCE

Boiling Liquid Expanding Vapour Explosion Computational Fluid Dynamics Chemical Hazards Reference Information System Continuous Stirred Tank Reactor Control Volume Design Accidental Load Det Norske Veritas European Union Finite Volume (UK) Health and Safety Executive Heating, Ventilation and Air Conditioning Immediate Danger to Life and Health Joint Industry Project Lethal Dose resulting in fatalities to x% of population Lower Flammable Limit (also known as Lower Explosive Limit, LEL) Liquefied Petroleum Gas Material Safety Data Sheet Porosity, Distributed Resistance Quantitative Risk Assessment (sometimes Analysis) Significant Likelihood of Death Specified Level Of Toxicity Saturated Vapour Pressure Nederlandse Organisatie voor Toegepast Natuurwetenschappelij Natuurwetenschappelijk k (Netherlands Organization for Applied Scientific Research) Temporary Refuge Unconfined Vapour Cloud Explosion Vapour Cloud Explosion

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Consequence modelling refers to the calculation or estimation of numerical values (or graphical representations of these) that describe the credible physical outcomes of loss of containment scenarios involving flammable, explosive and toxic materials with respect to their potential impact on people, assets, or safety functions. This datasheet presents (Section 2.0) recommended approaches to consequence modelling for accidental releases of hazardous materials, with the potential to cause harm to people, damage to assets and impairment of safety functions, from offshore and onshore installations. Consideration of environmental impacts is excluded, although the recommended approaches to release modelling (in particular for liquids) may be applied to estimate potential quantities of hydrocarbon spilt. This datasheet is not intended to be a textbook of consequence modelling theory but rather to indicate the consequence phenomena that need to be considered and to provide guidance on modelling that is fit for purpose.

This 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 of validity, its limitations, the input data required, the valid results that can be obtained, the results’ sensitivity to the different input data, and how the results can be verified.

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The 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.a sp) TRACE, from Safer Systems (www.safersystem.com)

These model most of the consequences set out above apart from smoke. However, they are designed for onshore studies and not all of the models included will be appropriate for 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 but these do not come with any training or support, or with any guarantee of code quality; 2

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the commercial packages listed above do include these and come from reputable organizations 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 consequence modelling.

Computational Fluid Dynamics (CFD) can be used to obtain numerical solutions for ventilation, dispersion and explosion problems for both offshore platforms and onshore plants. CFD simulations are becoming increasingly common as the computing power of standard desktop computers grows. The NORSOK standard Z-013 [21] specifies use of CFD in its probabilistic approach to explosion risk assessment. The objective of the probabilistic assessment is to generate realistic (representative) overpressures for an area based on probabilistic arguments. Ventilation, gas leaks, dispersion as well as gas explosions are considered by establishing probable explosion scenarios, performing explosion simulations and establishing probability of exceedance curves. The application of CFD for gas explosion studies is common for offshore platforms and is 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 of the risk. CFD simulations essentially solve the conservation equations for mass, momentum and enthalpy in addition to the equations for concentration and flammable gas effects. The equations are generally closed using the κ−ε 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 of which lies a computational node where the variable values are calculated. The conservation equations are applied to each CV and interpolation is used to express variable 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 to determine the rate at which a fluid is released to the environment in a loss of containment 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 over time. This is often used for studies of onshore facilities, especially where the offsite risk is the motivation for the study.

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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 a significant impact on the likelihood, in particular, of the initial event escalating. The modelling 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 but under-predict its duration or the time for which it exceeds a critical length (e.g. to other equipment) Initial rate modelling can lead to over-prediction of the impact of toxic gas or smoke effects

In general, time dependence should be explicitly modelled in offshore studies, where the impacts over relatively short distances (tens of metres) and over time periods up to the 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 often modelled 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 for effective 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 formulae exist to calculate the initial rate, in particular Bernoulli’s 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 DNV’s PHAST software. Equations for modelling time-varying releases of gas, including blowdown, are given in the CMPT Guide to quantitative risk assessment for offshore installations [1]. This also includes 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 pipeline pressure 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 tools for discharge modelling.

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

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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, the thermodynamics of mixtures may be modelled by an “average” equivalent pure component. However, as computer power increases, this limitation is increasingly being 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 a re 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 liquid droplet size so that the amount of liquid that rains out (falls to the ground or water surface) can be ca lculated as part of the dispersion modelling (Section 2.2). SPT Group’s OLGA software (http://www.sptgroup.com/products/olga) can be used to model time dependent releases from pipeline networks and includes multiphase flow capability. It should be noted that a release from a high pressure reservoir will normally be quite complex with sonic flow, expansion and compression shocks. In safety studies, this

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complex outflow is often not calculated and the boundary conditions for the jet are given at surrounding pressure. Both the specified momentum and the temperature (density) of this jet may be important for the dispersion simulation and thereby the resulting 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 and should 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. The consequences 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 released up to the time when this mass equals the fireball mass giving the same fireball duration. 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 release directions for a leak from a buried pipeline. The text beside suggests an approach to modelling these for medium and large leaks, based on these having sufficient force to throw out the overburden (and even c oncrete slabs, if placed on top). 1. Vertical release. Model as vertical release (upwards) without modification of normal discharge modelling output, i.e. full discharge velocity. 2, 3. Horizontal release. Model at angle of 45° upwards 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 to throw out the overburden, hence the flow will only slowly percolate to the surface. The following approach is suggested for all release directions: •

•

2.2

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 through the soil, with the hole size modified to obtain the same discharge rate as above.

Dispersion and ventilation modelling

Dispersion modelling is used to determine how the fluid released spreads in the environment: usually air but also water 1. •

•

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 also needed.

1

Dispersion in soil is considered in environmental rather than safety risk studies and is outside the scope of this datasheet.

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

A vapour release inside an enclosed volume (a module of an offshore installation or a building 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 all the 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 the environment. When the release is wholly or partially liquid, typically this will fall onto a solid surface or through a grated deck to the sea below; on a solid surface it will spread out to form a pool. At the same time, some of this liquid may vaporize, adding to any vapour in the initial release, and will disperse in the atmosphere, as illustrated in Figure 2.6. Dispersion modelling thus frequently has to be able to model a ll of these phenomena, in addition to addressing the different mechanisms of atmospheric dispersion. The

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relationship between many of these phenomena and mechanisms is illustrated in Figure 2.1.

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 a release from a vent or stack, or calculating toxic impact for people indoors) To calculate the quantity of flammable gas, for explosion modelling (see Section 2.4)

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 gas in an enclosed volume such as an offshore module (2). Section 4.2.3.1 of [2] presents a simple equation valid when the ventilation flow field is close to uniform. A workbook approach to estimating the flammable volume produced by a gas release [3, 4] has been developed 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

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rate. This diameter together with the gas flow rate can then be used as input to a Gaussian plume model. Some example dispersion modelling results (distances to LFL) are given in Figure 2.7 and Figure 2.8. These were obtained using DNV’s PHAST software.

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

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

2.2.2

Software for dispersion modelling

Atmospheric dispersion modelling software mainly divides into: •

•

“Box” models, which calculate vapour cloud dimensions and concentrations from bulk properties. CFD models, which divide the “computational domain” representing the space through which the fluid disperses, into small volume elements where physical properties 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 the middle 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 c ases 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 be modelled.

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

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FLOWSTAR, a model developed by CERC ( www.cerc.co.uk/software/flowstar.htm) for calculating profiles of the mean airflow and turbulence in the atmospheric boundary layer, can calculate plume trajectory and spread in complex terrain and over variable surface 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 terrain may 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-based dispersion models.

2.2.3

CFD for ventilation and dispersion modelling

CFD’s main application in dispersion modelling for QRA is in explosion analysis, of which ventilation and dispersion simulations are an important part. In explosion analysis for offshore installations, the objective of the ventilation simulations is to generate a ventilation distribution in terms of rate, direction and probability. Based on this information, representative wind conditions are selected for the 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 is necessary as it is generally assumed that the ventilation rate for a wind direction is proportional to the wind speed so that ventilation rates can be linearly scaled with wind speeds. Also, the number of simulations may be reduced from symmetry considerations. The objective of the dispersion simulations in explosion analysis is to identify credible size, concentration and location of gas clouds and establish how the flammable gas clouds varies with the hazardous leak location, external wind speed and direction and leak direction. Those representative gas clouds are subsequently used in the explosion studies. Generally, the number of parameters that can be varied is high (leak locations/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 orientation against prevailing ventilation direction. It is, however, possible to reduce the number of dispersion simulations based on symmetry considerations and the physics of the problem. Additionally, not all the identified scenarios (after consideration of symmetry and engineering judgement) need to be simulated. The ‘frozen cloud’ concept can be used to estimate the results of the scenarios not simulated. This is an assumption that gas concentration 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 concentration field 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 dominated region).

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Although the NORSOK approach is for offshore installations, a similar approach can be applied to explosion analysis for onshore installations. CFD modelling of ventilation and dispersion is also useful for evaluating optimal geometry layout and location of gas detectors [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 use it 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. other equipment)

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

•

•

– an ignited vapour plume, whose dimensions are typically determined directly from the dispersion modelling as the distance to LFL – an intense, highly directional fire resulting from ignition of a vapour or two-phase release with significant momentum – from an ignited liquid pool 2 or sea surface gas pool resulting from a subsea gas release (e.g. from a pipeline or wellhead) Offshore installations often have grated decks, so a liquid spill will fall through the grating 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.

•

– when a full surface fire occurs in an oil storage tank, heat will slowly conduct 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.

•

Strictly, a BLEVE (Boiling Liquid Expanding Vapour Explosion) is simply explosively expanding vapour or two-phase fluid. A BLEVE results from a “hot rupture” of a vessel typically containing hydrocarbons such as LPG 3, stored and maintained as a liquid under pressure, due to an impinging or engulfing fire. A flammable material will be ignited immediately upon rupture by the impinging/engulfing fire and will burn as a fireball. A fireball would also result from immediate ignition of a release resulting from cold catastrophic rupture of a pressurised vessel. The initial phase of a ga s pipeline rupture should also be modelled as a fireball. •

– from ignition of a release from a buried pipeline. For vertical and horizontal 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 can be taken as the diameter of a gas pool burning as a pool fire.

2

Note 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 credible and should be considered if relevant. BLEVEs of heavier hydrocarbons such as crude oil or petroleum do not occur.

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An appropriate model for the type of fire that could result from ignition of the release being 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 will result 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 not straightforward, although an approximation can be used for a fireball due to its spherical symmetry (see Section 0), and is best done using software. The simple flame size models below are therefore best used either when only the flame dimensions are required 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 H c)0.478

[Hc = heat of combustion (J/kg)]

Based on calculations using the Chamberlain model [7], the following rough relationships for distance along the flame axis to various thermal radiation levels have been calculated: •

37.5 kW/m2:

13.37 Q0.447

•

12.5 kW/m 2:

16.15 Q 0.447

•

5.0 kW/m 2:

19.50 Q 0.447

Some example jet fire thermal radiation results for horizontal releases are presented in Figure 2.9 and Figure 2.10. These were obtained using DNV’s PHAST software, which used the Chamberlain model [7].

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2.3.1.2 Pool Fire The diameter of an equilibrium pool fire (i.e. where all the fuel is being consumed as it is released) 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)

Gasoline

0.05

0.07

Kerosene

0.06

0.07

Crude 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]

0.24 2 0.42 2

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 fire’s size may be constrained by a bund (dike) or drainage, and also that process areas are often constructed with the floor sloping towards a drain. In both cases, 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 corresponding to 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 and Figure 2.12. These were obtained using DNV’s PHAST software.

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2

Note: The shape of the curves for 12.5 kW/m is explained by the decreasing flame surface emissive power with increasing pool diameter.

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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 hydrocarbon vapours above neighbouring tanks.

2.3.1.4 Compartment Fire For a fire inside an enclosed volume such as an offshore module, the fire size and properties (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-phase release. 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 applied offshore.

4

In 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.

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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 simple correlations between these quantities and fireball mass 5. One model is due to Prugh [10]:

Diameter, D (m): D = 6.48 M 0.325

[M = fireball mass (kg)]

Duration, td (s): td = 0.825 M 0.26 Height of fireball centre, h (m): h = 0.75 D Surface emissive power, q (kW/m 2): [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 possible assumption is that the fireball mass is calculated assuming 3 × the adiabatic flash fraction at the burst pressure, constraining this to be ≤ 1.0.

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Radiation received, I (kW/m 2): I = q F

τ

F = view factor: τ

2.3.2

[x = distance (m) along ground] =

transmissivity:

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 in Section 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 offshore structures and onshore plants. The Oil and Gas UK guidance [24] provides a state-ofthe-art review of CFD fire modelling. In particular, it is stated that although CFD models provide a more realistic representation of the flow physics, there are uncertainties associated with modelling turbulent flow and combustion as well as in definition of fire source and ambient conditions. Commonly used software for fire modelling include Kameleon FireEx and CFX. Kameleon FireEx is typically used for fire modelling on offshore platforms and onshore plants; CFX is more commonly for low geometry scenarios, e.g. fire and smoke modelling in tunnels. For CFD fire modelling, it may be best to reduce the size of the problem by modelling only 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 following steps: 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 direction until 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 Accidental Load (DAL) fire that is used for design of the structure and allows for the development of a consistent methodology (similar to explosion approach) for calculating fire loads. The methodology is illustrated in Figure 2.14.

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

Initial leak rate and leak profile

•

Leak and fire location

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RADD – Consequence modelling •

Jet direction

•

Dynamic development of fire

•

Geometry layout and

•

Deluge

The probabilistic approach can be used to generate a fire exceedance curve from which the 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 last decade since the Spadeadam tests. For offshore, the NORSOK standard Z-013 [11] has established a comprehensive but computationally demanding approach to explosion modelling, requiring use of an advanced CFD tool. Whilst originally developed specifically 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 models available in general purpose software is becoming more sophisticated and considered fit for purpose. However, where design or layout decisions may critically depend on explosion 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 terrain effects are important, for example if a fac ility is built on a slope or at the foot of a hill: in this case dispersion would be significantly modified compared with that which would result over flat ground. The recent advances in understand of explosions referred to above mean that the previous classification of VCEs as unconfined, semi-confined or confined can now be considered over-simplistic. It would be better to talk about degrees of confinement and congestion6. TNO’s 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 volumes such as can be found in a densely packed process area of an onshore plant. In this and similar models, some assessment or assumption needs to be made outside of the model as to the maximum overpressure. In CFD modelling, the distinction between levels of confinement/ congestion disappears since the geometry is defined and the software itself calculates the maximum overpressure.

6

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

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2.4.1

Simple approaches to explosion modelling

Historically, simple “TNT equivalence” models have been used for modelling explosion overpressures from unconfined VCEs (UVCE) onshore. However, these require the explosive mass to be calculated: as this is an output from dispersion modelling, manual calculation of explosion overpressures is not likely to be undertaken. Another old approach for onshore QRA [13] calculates the distance to specified levels of 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) includes either 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 , 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 sources is treated independently of the others. The material and the volume of the cloud within the 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 one of 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 from 0.01 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 generally no. 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 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 air burst, 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 maximum overpressures in modules using relatively simplified methods that nevertheless take account of the broad features of module geometry. For example, DNV have used their programs COMEX and NVBANG in numerous studies, however these programs are not available commercially and are not recommended for non-specialists in explosion modelling. However, in offshore applications the maximum overpressure itself is usually not used directly 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

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unlikely to be achieved and a lower overpressure will be reached. Of direct concern is the likelihood of an explosion that will result in equipment escalation or breaching of the TR wall, for example. This requires a probabilistic approach to estimate the likelihood of 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 model explosion 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. DNV’s EXPRESS) to develop overpressure exceedence probability curves for use in the QRA. The same approach can be used for more specific design problems, for example designing an ESD or deluge system to withstand the drag forces likely to result from an explosion. This approach requires considerable investment of effort to obtain useful and robust results. Previous, more simplified methods have the appearance of being less costly to achieve the same end. However, the initially more costly NORSOK approach [11] can be used to cost-optimise the design of a module for explosions, eliminating the need for excessive 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) can be ignited and explosion analysis carried out. The Oil and Gas UK guidance [24] reports that 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 this application. Instead, an equivalent quiescent stoichiometric gas cloud, that gives similar overpressures to the non-homogeneous and turbulent clouds, has to be ca lculated. As an example of how this can be done, the FLACS software automatically calculates a parameter (referred to as “Q5”) that converts the non-homogeneous cloud into an equivalent 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 in the 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 gas cloud location and ignition location should be varied. In particular, it is important to locate the clouds close to c ritical 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 centre of cloud and at edge of cloud. Depending on the geometry and layout, edge ignition will sometimes produce the higher (than central ignition) explosion overpressures due to the increased flame distance. Results in terms of explosion overpressures can be output at monitor points at predefined locations and drag forces can be obtained for design of critical equipment and piping.

2.5

Smoke and gas ingress modelling

Modelling of smoke and gas ingress to the TR or living quarters usually forms part of an offshore 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 escape routes being impaired or of people out-of-doors being overcome by smoke. Smoke and gas ingress modelling has up to 4 stages: Source Term

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→

Dispersion → Ingress → Effects

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The source term comes from the release rate modelling (Section 2.1): directly for gas and from suitable ratios of (mass of smoke) / (mass of hydrocarbon released). Dispersion can be modelled as suggested in Section 2.2. Since smoke’s largest constituent 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 a molecular weight and temperature equal to those estimated for the combustion gases. However, the high temperature invariably results in a rapidly rising smoke plume that doesn’t match experience. For example, photographs of smoke from the Piper Alpha disaster show the plume travelling almost horizontally. One possible reason is that the soot particles in the smoke increase the plume’s density. Hence this approach is not recommended for 3D results. However, it may be used to determine the smoke concentration at a given distance horizontally from the release point, assuming as a worst 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 data and 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.

a) Fuel Controlled

Carbon Monoxide (ppm) 400 800 Carbon Dioxide (%) 10.9 11.8 Oxygen (%) 0 0 Smoke Temperature (°C) 1,000 1,000 Particulates (dB/m) 15 47 b) Ventilation Controlled Carbon Monoxide (ppm) 30,000 31,000 Carbon Dioxide (%) 8.2 9.2 Oxygen (%) 0 0 Smoke Temperature (°C) 600 600 Particulates (dB/m) 29 70 * The light composition is used for gas jet fires. The heavy composition is used for condensate 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 of barriers). •

•

Figure 2.15 shows dilution factors, based on calculations using FLACS [17], for different release rates. Smoke Ingress:

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−

−

−

•

CO and CO2 build-up in the module are calculated using a CSTR model, taking as input the smoke concentration immediately outside the TR and the TR’s ventilation rate The CO2 concentration calculation also includes exhaled CO 2 from personnel inside The internal temperature is also calculated based on heat generated by TR occupants

Smoke effects/toxicity −

−

Based on dose relationships given in [18] Considers toxicity of CO; effects of CO 2, lack of oxygen and high air temperature; visibility reduction

For gas ingress a set of dilution factors is used, equivalent to but different from those used for smoke. A CSTR model is used for gas ingress, and fatalities in the TR are assumed 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 software such as the packages listed in Section 2.0 is sometimes used. However, the validity of this 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 be used. 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 in buildings, but they are also capable of predicting the transient transport of

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contaminants such as smoke. The method is applied by considering a building as being divided into a number of zones (typically rooms) that are physically separated from one another. As with the CSTR model, each zone is treated as fully mixed. The rate at which air 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 of the 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 in TR or living quarters. The effect of heat sources due to people and computing equipment can be included in the analysis. However, smoke modelling using CFD can be quite difficult due to the variability and uncertainty in the boundary conditions [26]. A recent article by O’Donnell et. al. [27] provides a comparison of different approaches to smoke 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 were determined 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 in Section 2.2.3 for gas dispersion modelling in general. However, the approach described in 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 on the 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 a high concentration over a short period of time) or chronic (resulting from continuous exposure 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 different physiological effects: they may inhibit respiration (causing asphyxiation) through inhalation, they may affect the central nervous system, they may be ingested or absorbed through the skin. For the purposes of this datasheet, the discussion is limited to 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. H 2S. Onshore, besides H 2S (in onshore hydrocarbon production, transport and processing), other toxic materials are potentially of concern. Toxic consequences are invariably bound 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: specified concentrations such as the IDLH (Immediate Danger to Life and Health), or concentration-lethality levels for different species such as rats. Such data can be found in Material Safety Data Sheets (MSDS) or online reference sources such as CHRIS www.chrismanual.com.

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For QRA, a dose-response relationship is often used that relates the lethality to the dose received 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 in highly susceptible people being killed and a substantial portion of the exposed

population requiring medical attention and severe distress to the remainder exposed. It represents the dose that will result in the onset of fatality for an exposed population (commonly referred to as LD 1 or LD1-5) •

SLOD (Significant Likelihood Of Death): is defined as the dose to typically result in

50% fatality (LD 50) 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 be seen in the final column, values of “n” for these materials range from 1 to 4.

Ammonia Carbon monoxide Chlorine Hydrogen sulphide Sulphur dioxide Hydrogen fluoride Oxides of nitrogen

3.78 × 10

8

40125

1.09

×

9

10

57000

1.08 × 10

5

12

2.0 × 10

4.66 × 10

6

12000 96000

4.84

×

1 5

2

13

4

7

2

10

1.5 × 10 7.45

×

2

10

41000

1 5

6.24 × 10

2

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

As stated above, the LD 50 is often used in risk calculations. The HSE’s approach allows for calculation of the LD 50 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 concentration and duration of exposure. This is the “probit”. A probit value Pr is calculated (for a constant release rate and hence concentration 7) 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 in many places e.g. [9].

7

n

For a time varying release rate and hence concentration, the (C t) can be replaced by an integral over time.

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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 dispersion modelling (Section 2.2) together with the exposure time. Calculation of the LD 50 using the 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 thence the lethality level as a function of distance from the release point or as contours of different lethalities overlaid on a plan or map. In this way the lethality at any point can be 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 together with a SLOT/SLOD value or probit to calculate lethality at that point. Contour plots of toxic lethality are not available from CFD software but could probably be generated from tabular output.

3.1

General validity

The approaches described in Section 2.0 are based on published sources that are widely known and accepted. All modelling of physical phenomena is imperfect. Any use of software must be within the limitations set out for the software, and even then the analyst must carry out a reality check on the results. For example: a jet fire model applied to a large, high pressure gas release will predict a jet flame several hundreds of metres long; the analyst 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 detailed modelling (e.g. using CFD) may be required. Whilst it may be considered desirable to use 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 address specific 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 give accurate predictions of overpressures is not available and hence decisions based on CFD results may result in under-design for the potential overpressures.

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3.2

Uncertainties

All modelling suffers from uncertainties. For a given set of input (initial) conditions, it is unlikely exactly to match the physical outcome that would result in reality from the same initial conditions. Indeed, numerous physical realisations of the same release would give different results, whereas consequence modelling software gives the same result each time 8. Sources of uncertainty in consequence modelling for QRA include the following: •

•

•

•

3.3

A QRA only models a limited range of cases, so the conditions of an actual release are 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 other phenomena, cannot deal with solid or porous barriers (buildings, process units, bund walls, etc.) CFD cannot model sub grid scale turbulence (see Section 0)

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, some consequence modelling requires the use of either general purpose or CFD software. To decide 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 Section 2.0 will need to be undertaken. This means that the output from one step of the analysis will 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 general purpose consequence modelling software where the transitions from one model to the next are automated is preferable to using a mixture of models from different sources (perhaps with some implemented in spreadsheets, others coded). However, in this case the automated transitions may be “black box”-like and so the analyst needs to understand 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 be acceptable. This could use the correlations given or referred to in Section 2.0, or the consequence results presented in that section.

8

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

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For a QRA of an offshore installation with enclosed modules, use of CFD for explosion modelling is now routinely used. For a new installation, it will almost certainly have to be used in order to design for explosions. For an existing installation, explosion modelling 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 will have 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 earlier VCE models. For problems of a more limited nature, in particular decisions about significant investment in relation to fire or explosion and especially in relation to offshore structures, it is advisable to use CFD in order to maximise the robustness of the analysis 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 to personnel 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 the turbulence generated during an explosion. Most of the software (FLACS, EXSIM, AutoReaGas) uses a so-called distributed porosity concept (Porosity, Distributed Resistance (PDR) model) to account for the objects which cannot be represented by the grid. 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 grid wake. Explosion relief panels and yielding walls can also be represented by modifying the porosity 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 explosion analyses 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 a problem 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 and by 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 is required. In addition, it is important to define the CFD grid to extend quite a large distance from the area of interest to avoid too strong influence from open boundaries.

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Key general sources for suitable consequence modelling methods are the Guide to quantitative risk assessment for offshore installations [1] and Lees’ Loss Prevention in the Process Industries [9]. These have been supplemented by more specific published papers 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 software providers. 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 the boilover 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, and were partly obscured by smoke. Hence a height of 5 times tank diameter appears reasonable. For explosion modelling, FLACS and AutoReaGas have been extensively validated against experimental data, in particular from the Phase 2 and Phase 3 JIP Blast and Fire Engineering for Topside Structures experiments carried out at Spadeadam and elsewhere. FLACS is also currently being validated for hydrogen as part of the EU HySafe programme. Details of FLACS and AutoReaGas validation are available on their respective websites (see Section 2.0).

For further information, the data sources referenced in Sections 2.0 to 4.0 should be consulted. Some additional references are given in Section 6.2. On the subject of subsea releases, two major reports 32], [33] were published in 2007 and 2008 and should be consulted if detailed information is required (i.e. if subsea releases appear to pose a significant risk).

6.1

References for Sections 2.0 to 4.0

1. Spouge, J, 1999. A guide to quantitative risk assessment for offshore installations , CMPT publication no. 99/100, ISBN 978-1-870553-36-0 / 1 870553 36 5. Now available from the 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 a Confined and Congested Area, Joint Industry Project Gas Build Up from High Pressure Natural Gas Releases in Naturally Ventilated Offshore Modules. [Believed to be available 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.

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5. Wertenbach, H G, 1971. Spread of Flames on Cylindrical Tanks for Hydrocarbon Fluids, Gas and Erdgas . 6. API, 1982. Guide for Pressure Relieving and Depressuring Systems , American Petroleum Institute, Recommended Practice RP 521, 2 nd ed. 7. Chamberlain, G A, 1987. Developments in Design Methods for Predicting Thermal Radiation from Flares, Chem Eng Res Des . 8. Thomas, P H, 1963. The Size of Flames from Natural Fires, 9th Intl. Combustion Symposium, Combs Inst. Pittsburgh, PA, pp.844-859. 9. 2005. Lees’ Loss Prevention in the Process Industries , 3 rd. ed., Mannan, S, ed., Oxford: Elsevier Butterworth – Heinemann. 10. Prugh, R W, 1994. Quantitative evaluation of fireball hazards, Process Safety Progress 83-91. 11. Procedure for probabilistic explosion simulation, NORSOK Standard Z-013 Rev.2 Annex G. 12. TNO 1997. Methods for the calculation of physical effects due to releases of hazardous materials (liquids and gases) [the “Yellow Book”], eds: van den Bosch, C J H and Weterings, R A P M, Chapter 5: Vapor Cloud Explosions, Mercx, W P M and van den Berg, A C. 13. TNO 1979. Methods for the Calculation of the Physical Effects of the Escape of Dangerous Material, [the “Yellow Book”], Chapter 4: Vapour Cloud Explosions, Wiekema, B J. 14. Tang, M J, and Baker, Q A, 1999. A New Set of Blast Curves from Vapour Cloud Explosion, Proc. Safety Progress , 235-240. 15. Mercx, W P M et al., 1998. Application of correlations to quantify the source strength of vapour cloud explosions in realistic situations. Final report for the project: ‘GAMES’ , HSE and TNO, http://www.hse.gov.uk/research/crr_pdf/2001/crr01318.pdf . 16. SINTEF 1992. Handbook for Fire Calculations and Fire Risk Assessment in the Process Industry. 17. FLACS, V8 (version 8), 2003, see www.gexcon.com. 18. Purser, D, 1992. Toxic Effects of Fire Cases, Conf. on Offshore Fire and Smoke Hazards, Aberdeen. 19. HSE 2006. Indicative Human Vulnerability to the Hazardous Agents Present Offshore for Application in Risk Assessment Of Major Accidents, SPC/Tech/OSD/30. http://www.hse.gov.uk/foi/internalops/hid/spc/spctosd30.pdf . 20. CPD 1992. Methods for the determination of possible damage to people and objects resulting from releases of hazardous materials [the”Green Book”], Committee for the Prevention of Disasters caused by Dangerous Substances / TNO, The Hague: Directorate-General of Labour of the Ministry of Social Affairs and Employment. 21. Norwegian Technology Centre, 2001. Risk and Emergency preparedness analysis, NORSOK Z-013, http://www.standard.no/imaker.exe?id=1503.# 22. Huser, A., Oliveira, L F, Rasmussen, O, and Dries, J V D, 2002. Explosion risks in large and widespread process areas, ERA Conference, November. 23. Huser, A, Oliveira, L F, and Dalheim, J, 2004. Cost optimisations of gas detector systems, Proc. OMAE04, 23 rd International Conference on Offshore Mechanics and Arctic Engineering , June.

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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 Newsletter . 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 paper available from CMR-Gexcon http://www.gexcon.com/download/ERA_00-Paper.pdf . 27. O’Donnell, K, Deevy, M, and Garrard, A, 2007. Assessment of mathematical models for prediction of smoke ingress and movement in offshore installations, FABIG Newsletter . Available from FABIG www.fabig.com. 28. Daish, N C, Britter, R E, Linden, P F, Jagger, S F, and Carissimo, B, 1999. Scientific Model Evaluation techniques applied to dense gas dispersion models in complex situations, Intl Conf. on Modelling the Consequences of Accidental Releases of Hazardous Materials, CCPS, San Francisco, California, September 28 – October 1. 29. Mudan, K S, and Croce, P A, 1988. Fire Hazard Calculations for Large Open Hydrocarbon Fires, Fire Protection Engineering , Section 2 Chapter 4, Society of Fire Protection 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. Fanneløp, T K, and Bettelini, M, 2007. Very Large Deep-Set Bubble Plumes From Broken 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. Videreføring 2007, Spredning over havet , Petroleum Safety Authority Norway.

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