Ruddy Branka

Guy Marlair

Brigitte Nedelec

Risk analysis of fireworks transport in cargo container ships

The study deals with the analysis of the most suitable configuration for positioning the fireworks containers in the cargo ship in order to minimize the risks for the ship in case of an accident (transmission of fire or deflagration originating from containers filled with fireworks devices to other containers or arising from other containers to the those containing fireworks).

The analysis has been done in a three steps process 1) What are the hazards coming from a fireworks container in case of fire? 2) How to fill the containers it in order to minimize the outer effects? 3) Where to place them on the ship from a safety management viewpoint?

In this paper, we present;  The most dangerous fireworks,  Some incidents that occurred in the past and lessons learnt  The problems linked to inappropriate classification of the fireworks,  The hazards linked to confinement and the propagation issues,  Some proposals for safe filling of the containers in terms of types of fireworks under consideration, quantities, segregation rules and training of operators  Some proposals for safe filling and packing of fireworks articles in inner packaging according to their types,  A proposal for optimizing the position selection of the containers in the cargo ship.

INTRODUCTION

Most fireworks used in the European market are produced and imported from CHINA. As a consequence, maritime transport of those articles (as dangerous goods) is quite common and important. Approximately 8000 (equivalent twenty feet) containers are imported each year in Europe, representing 30% of the world fireworks market for maritime transportation of such products by cargo ships.

As some serious accidents have been observed in the past years (see accidentology section of this paper), we have developed a risk based approach to define the best packing configurations inside the boxes, the best lay-out for boxes of fireworks inside the containers and ultimately the best positioning of maritime containers containing fireworks articles inside the cargo ship in order to reduce the risk of propagation of a fire coming from the fireworks containers or from another container.

In the following sections, we present:  The most dangerous fireworks and the main risks affecting them  Some issues arising from past accidentology and handling instructions  The default fireworks classification table for transport and associated problems with inappropriate risk division classification  The hazards and risks presented by a container full of fireworks in boxes, probabilities, propagation and possible protection  Safe instructions during the container's filing, operator's training  General recommendations for transportation of fireworks on a cargo ship

MAIN RISKS AND HAZARDS AFFECTING THE FIREWORKS

Within the new 2007/23/EC European Directive, fireworks are classified into 4 categories (designated as F1 to F4) according to their powder weight and operational effects when functioning. But the main risks cannot be ranked simply accordingly to this individual classification scheme. Indeed, main risks are caused by  The type of pyrotechnic compositions inside the fireworks and their degree of confinement: all fireworks are made with an assembly of different inert elements, each containing one or more different pyrotechnic compositions, in charge of one effect during the functioning of the firework (igniting, ejection, delay, exploding, colours, other visual or sound effects,...). Each composition is a mixture of powders which enables the composition to ensure its function (oxidizing carrier, fuel carrier, colorant, binder,..). These compositions can be classified according to their sensitivity to external aggressions and according to their effect on the environment. The following charts present the percentages of accidents induced by pyrotechnic compositions in function of the type of aggression, and the main causes of accident are clearly the mechanic aggressions (shocks, friction, indentation, drops, crushing, ...)

Figure 1 :Accidents per causes

If we classify the composition according to their actual hazards (as quantified by a severity index), the most dangerous reveal to be those containing chlorate or perchlorate /metal based compositions (metal elements are generally magnesium, aluminium, or titanium, in fine powders)

Some findings from past incidents/accidents

The following table below contains an inventory of major accidents listed worldwide from 1996 to 2004 (various sources; French inspection of explosives, incident log, ARIA database, ...). This list is not exhaustive, the number of accidents in China appears as the highest as compared to incident numbers in other quoted countries, but this looks consistent with the very large number of manufacturers existing in this country and settled in 26 provinces (estimated to range from 4000 to 7000). The following table gives the number of fatalities listed by country and year worldwide (known accidents for which information is available). Among these accidents, very few deal with transport or storage of fireworks. The only known accident in a container ship is the HYUNDAI FORTUNE in 2006, 64 000 tonnes, bearing 5100 containers (in equivalent 20 feet), when an explosion near the YEMEN coast caused a fire that lasted several days. The ship had a cargo of 7 fireworks containers located in the area of the fire, but the actual cause of the incident remains poorly identified. From the analysis of the accidental database, it comes out that:  accidents occurring during a sleeping fireworks storage are limited  key factors of accidents are products handling in unsuitable packaging (cardboard boxes containing fireworks in bulk for example),  the main causes of accidents are due to mechanical stresses on products, i.e. shock during transfers (shocks, drops, violent friction), or when manipulations violate security policies. The effect of temperature on shock sensitivity is also a factor to be taken into account.

The default fireworks classification table and associated problems with inappropriate risk division classification

Among explosive products, fireworks form a specific category, characterized:  by the diversity of products existing on the market (hundreds of them), from the simple banger to shells deploying their effects during functioning at altitudes up to 800 metres,  by their partial use on the consumer market (therefore inducing possible sale by retail stores),  by specific legislations (European Directive 2007/23/EC, TDGs legislation).

The Fireworks do not derogate from the pyrotechnic products classification rule. However, given the diversity of products and their packaging, an individual ranking of these products is not always possible in practice. To address this point a default classification has been set by the legislator (primarily as a recommendation in the UN model regulation for the transport of dangerous goodsthe so-called orange book [START_REF]Recommendations on the Transport of Dangerous Goods[END_REF]), this classification is supposed to correspond to a worse case situation in terms of hazard ranking of the given fireworks. Fireworks assignment under N ° UN 0333, 0334, 0335, 0336 and 0337 can be done accordingly by analogy without having to run the test series 6 of the UN Manual of test and criteria [START_REF]Recommendations on the Transport of Dangerous Goods -Manual of Tests and Criteria -Fifth revised edition[END_REF]. The applicant, in the event of disagreement with the classification given to the products by default, may request other classification through testing (according to test series 6 procedure).

This "by default" classification system scheme has been adopted in the IMDG as can be seen in its last edition 2009: see IMDG sections. 2.2.3.5.5, Amdt. 34-08). The classification in this table only applies to objects packed in cardboard boxes. The classification in risks division is intimately linked to the product packaging. Thus, for example, separation of fireworks in a box by the mean of bulkhead may change classification from division 1. 1 G to division 1. 3 G or even to divisions from 1. 3 G to 1. 4 G.

Problems coming from the "by default" classification

Because of the relatively low possibilities of maritime transport of class 1 products, and because of the lack of clear regulations concerning the classification of fireworks products (international rules said that such products should be classified using the same principles as for conventional explosive materials which had revealed to be largely enforceable in practice, because of the infinite variety of existing Fireworks), many exporters had tendency in the past to underestimate actual hazard ranking of such articles by using categories 1.3 or 1.4 instead of 1.1 and 1.3 or 1.2 categories. This has led in Europe to large capacity storages where lower risk category group than actually pertinent was in current use. This ended up with the occurrence of a few but extremely serious accidents that killed or endangered many people (Enschede in Netherlands, Kölding in Denmark...).

These accidents have caused a violent reaction of authorities;

 Establishment of a fireworks classification by default table for international transport,  Directive 2007/23/EC giving essential safety requirements for the placing on the European market of such articles,  Reconsider and upgrade security requirements of fireworks by re-labelling to appropriate risk level on arrival at the first European harbour (to be implemented by the importer, considering that the first hazard ranking performed in China is valid until the first storage place in Europe).  Currently in Amendment No 34-08 the IMDG, a commitment exists in the framework for multimodal transport of dangerous goods (5.4.5.1) formula in which the sender declares that cargo content is described as complete and accurate by the official designation of transport and that it is properly classified, packed, marked, labelled, affixed and in all respects well conditioned to be transported in accordance with international and national regulations apply.

Despite of this commitment, the findings provided by audits carried out in harbours of Hamburg and Felixstowe by the competent authorities before unloading the ships showed that these fireworks either had not been classified at all or had been labelled as presenting the lowest risk level (1. 4 G) while in reality they belonged to a class of higher risk [3]. Law enforcement authorities in these ports have had to take the necessary measures to ensure that these products were properly classified to be delivered to their final destination. The classification was entrusted to European authorities and a large number of fireworks which had been declared belonging to class 1. 4 G or 1-3 G were then reclassified

(1. 3 G, 1. 2 G / 1. 1 G).
Furthermore, another common distortion to actual regulations constraints consists simply in not considering classification of fireworks as hazard material of class 1, but to declare them as toys articles.

Most of fireworks containers contain less than 8 tons Fireworks (5 tons net weight) splitting in between 5 and 20 different products. The additional information required for classification, as they are proposed above, should not impose an additional burden to the sender.

The hazards and related risks presented by a container full of fireworks packed in boxes

The probability of occurrence of an accident can be determined by three different methods: semi-quantitative, qualitative or quantitative type. The qualitative or intuitive method is based on a meaningful and representative feedback. The following data values were determined according to this method from the analysis of the available information on past accidents. The semi-quantitative or empirical method is based on statistical data driven from accident databases. Quantitative or analytical method seeks to identify exhaustively possible causes (basic events) that lead to the feared hazardous event. The probability of the feared hazardous event is determined based on the probabilities of occurrence of the various causes that lead to this phenomenon (see The above values are determined starting from the available accidentology.

Table 2 below gives for each operation the probability of an accidental event during logistics operations regardless of the relevant division.

Logistics operation Annual possibility of an accidental event

Container loading 10 -3

Charging/discharging in the cargo ship 10 -4

Transportation 10 -5

Table 3

Risk of fire/explosion propagation (domino effect)

First case -reaction by influence of initial detonation (division 1.1)

In the current state of knowledge, it is acceptable to say that the detonation of a given mass Q in kg  causes within 0.5 Q 1/3 (expressed in metres) around this mass, the instantaneous detonation of any mass able to explode (by Shockwave)  can lead to a distance (in meters) between 0.5 Q 1/3 and 2.4 Q 1/3 , the almost simultaneous detonation of any load which may explode (boot that often impact projections).  does not lead to simultaneous detonation:

-beyond a distance in meters of 2.4 Q 1/3 , in this case, the remaining risk of initiating is always due to projections but it does not create enough pressure to ensure the transition to detonation; -beyond a distance in meters of 0.5 Q 1/3 , if the load exploding initially is separated from any other likely to explode by a screen or a sufficiently thick protection wall able to stop any projection

Second case -materials or objects generating intense thermal effects (division 1. 3 a)

1.3 Division products have propagation risks by thermal radiation and heat transfer that depend on:  Nature, weight and moisture of these products.  Their speed of combustion and therefore the duration of the initial accidental phenomenon.

 The nature of their packaging.  The degree of containment.

If they are placed in buildings covered with Earth and fitted with a discharge pressure door, these products involve risks of spreading very strongly increased in a zone of conical shape with their centre of gravity coinciding with the cone summit. This interpretation can be considered as valid for a container when the door opens as a result of the pressure.

Third case -materials or objects with lower thermal radiation (division 1. 3b)

A mass Q (expressed in kg) of products within division 1.3 (b) placed in a lightweight building or a container presents a risk of spreading up to one of the following distances: -0.22 Q 1/2 metres if Q is more than 13 000 kg -25 metres if Q is less than 13 000 kg; for a small mass this distance may be reduced on justification -10 metres if the mass Q is surrounded by a screen resistant to the effects of pressure and projections as well as thermal radiation. The above distances must be increased if substances or articles 1.3 Division are located in the presence of a significant quantity of flammable products (solvents, fuels...) which, by burning, emit a strong heat radiation, and are likely to encourage fire spread. Fireworks generally belong to the division 1.3b.

Fourth case -materials or objects whose effects are limited (division 1.4)

In this case, propagation of the accident beyond the original location of the initial event is always sufficiently slow so that people at risk can shelter.

Conclusions concerning the fireworks behaviour

As concerning summary regarding fireworks hazardous behaviour, let us state they may be classified into 3 categories of behaviour for which specific recommendations can be made;  Fireworks experiencing explosive behaviour, even in limited quantities and in the absence of containment : the probability can be reduced by measures addressing adequate filling of the containers (special containers with compartments, with limited quantities and/or separation by 1.4 division fireworks (or inert or a double wall) corresponding to a minimum distance of 0.5 Q 1/3 between each 1.1 pallet,  Fireworks with behaviour that may become explosive if certain prevention measures are not taken (e.g. by limiting confinement and quantities to 50% of containers overall capacity)  Fireworks with intrinsic safer behavior (but that may render more severe the consequences of a fire coming from the outside) Annual probability of an accident can be estimated at 10 -5 during transport, 10 -4 during loading or unloading and 10 -3 for filing.

SAFE INSTRUCTIONS DURING THE CONTAINER'S FILING, OPERATOR'S TRAINING

Beyond the intrinsic danger from products and explosive objects previously exposed, and taking account of fireworks behaviour in confined environment, it is important:

to limit the quantities loaded in order to limit the potential effects, to choose packages as appropriate, to wedge and store the fireworks inside the packages in order to limit all movement which could result in mechanical shock and/or thermal contact which could lead to an accidental event to avoid the co-storage of incompatible materials. We present below existing regulatory demands as well as possible recommendations on the quantities to be loaded, type of packing preferred as well as the bulkhead which could be envisaged to limit the effects in the event of an accidental event occurrence in a container

Accordance with IMDG AMdt 34-8

Unless otherwise provided, the packs containing substances of class 1 shall comply with the provisions applicable to the Group of moderately hazardous materials (packing group II) (4.1.1.16)

The table 3 below mentions (4.14.1) packing instruction required for each firework UN number which can be assigned to fireworks articles for their maritime transport. Table 3 Packaging must comply with the General provisions of 4.1.1 (holding of shock to the usual demands on transport, packaging must not react dangerously with dangerous goods ….) and 4.1.3 (Special packing provisions) as well as the provisions particular relating to the packaging of goods of class 1 mentioned in Chapter 4.1.5 of the IMDG code.

Packing instruction P135 shows the type of internal and external packaging that are allowed for maritime transport.

Segregation of materials in the containers

Incompatible materials must be separated from each other. Two materials or objects are considered incompatible when their stowage joint can cause excessive risks in the event of a leak or spill or other accident.

This segregation may be obtained by separating incompatible materials in accordance with certain distances between dangerous goods or by requiring the presence among them one or more steel bulkheads or one or more steel bridges, or a combination of both. The intermediate spaces between these dangerous goods may be filled by another compatible with hazardous materials concerned cargo.

The G and S compatibility groups can be loaded in the same container. Segregation rules concerning the loading of the fireworks in a container together with other dangerous goods is not permitted for divisions 1.1, 1.2, 1.3 because the words "away from" are not listed in the table of contents separation for any class, nor in the list of dangerous goods.

On the other hand, as a general rule, non-dangerous goods can be loaded together with fireworks. Beyond regulatory IMDG, type of packing preferred is proposed below.

Maximum quantity in a container

Aiming at limiting the overpressure effects of Fireworks Division 1.1 :

To limit the overpressure effects, it is necessary to limit the quantity of products counted as net mass of explosives. If the fireworks container is surrounded by empty containers on each of its six sides, this corresponds to take a distance effect of 2.40 m (width of a container) and from the formula 0.5 Q 1/3 it comes that the appropriate net weight limiting quantity for such a distance is Q = 110 kg.

Limiting the thermal effects of Fireworks Division 1.3 :

To limit the heating effects and if we limit the container loaded of fireworks by empty containers on each of its six sides, this corresponds to take a distance effect of 2.40 m (width of a container), and from the formula 0.22 Q 1/2 to it comes that the appropriate net weight for such a distance is Q = 118 kg.

To limit the Fireworks Division 1.3 behaviour to thermal effects, it is recommended to load the container at half of its overall capacity. A full load of the container could lead to a division 1.1 with mass explosion behaviour and overpressure effects. Tests that confirm this statement were performed by CHAF (quantification and Control of the Hazards Associated with the transport and Bulk Storage of Fireworks)

on a 20 feet container containing 4 tons of 1.3G fireworks. A loud bang was observed with overpressure effects.

-Containing 2 tons of 1.3 G fireworks with results limited to fire, and thermal effects. Test videos are online www.chaf.info site.

We recommend the following combinations based on divisions with an indication of the maximum loading. The total quantity in net mass of fireworks by container 20 feet does not exceed 2 tons if containing 1.1G or 1.2G or 1.3G products (to multiply by 2 for 40 feet containers).

Loading Division Maximum per load (net weight of pyrotechnic composition)

Loading type 1

Types of packaging preferred

To avoid any movement of substances of class 1 inside the ship, storing packages in containers is an important element which will help limit unwanted event occurrences -Big size rockets should not be arranged in parallel rows inside the packages, but tumbled and layered perpendicular (to be sure all rockets heads are not located near each other) -Density of active material in boxes must be limited to 35 kg/m 3 for the most sensitive fireworks (low confinement and high vivacity) and 90 kg/m3 for less sensitive fireworks (high confinement and medium vivacity), which determines the fill factor mass of active material (with the boundaries of the table above) -Spherical form fireworks (bombs, maroons) should be strictly compartmentalized with a housing for each fireworks, so that they cannot move and this also help to comply with the permitted maximum density -The fuses must be protected by a cover and arranged to avoid friction -The most sensitive fireworks may be transported either by bringing together and coping with non-propagation distances or by mixing with low sensitive fireworks (very high confinement and low vivacity) boxes or boxes filled with inert elements which may be considered as elements of bulkhead, or by using compartmentalized containers.

Permissible amount of fireworks on a container ship

No limit appears in the IMDG [START_REF]3.5.5 fireworks default classification[END_REF] about maximum quantities of dangerous goods that can be embedded on a ship that has less than 12 passengers. Limitation of the quantities of fireworks to load the container door therefore comes from ; -Restrictions on the limited quantities of explosives for temporary parking on land, which can be different in each harbour and ship loading docks -The ship document of compliance -The Dangerous Goods loading plan and safety distances corresponding to segregation rules as well as the distribution loads and stowage categories.

REGULATIONS FOR LOADING FIREWORKS IN A CARGO SHIP

The table below lists, for each UN numbers that can be assigned to fireworks, the stowage category allowed to ships having on board a maximum of 12 passengers.

Table 5 In addition to these requirements, the IMDG lays down the following stowage provisions for class 1:

-With the exception of goods Division 1.4, the class 1 goods must not be stowed on the rank the more outdoors, -The class 1 goods must be stowed in a fresh portion of the ship and kept cool as far as possible while they are on board, -They must be at least 3 m from any source of heat.

-Compartments where they were strapped under deck must be dry.

-Containers should be loaded and stowed securely to prevent moving during transport.

-The class 1 goods must be stowed as far as possible of the accommodation zone and machinery rooms and must not be stowed directly above or below these premises. -They must be separated from those premises by a metallic partition.

-Divisions 1.1, 1.2, 1.3 must not be stowed within 3 m of bulkhead. Idem on the deck, they must be stowed at 3 m from the vertical projection of the houses. -The class 1 goods must not be stowed in a horizontal distance of less than 6 metres of any fire, machines, kitchens, ventilation ducts, exhaust pipes of any other source of ignition. -These goods must always be stowed so as to not clutter up passages and be at least 3 m from all facilities necessary for safe operation of the ship and at least 8 m from gateway and salvation craft. -As a general rule, cables and electrical equipment must not be installed in the compartments to hold class 1. If they are present, however they must be isolated from the power source in order that no part of the circuit located in compartment is powered. -A lightning protection must be installed. -Compartments must be locked.

-Instructions must be given to freight operators on the possible risks that may be presented by the class It is possible to intervene as soon as a fire event starts, if the fire fighting means are available and if it begins far from the explosive products. Regardless of the outcome of this original intervention that must keep of short duration, one must then evacuate. Generally, it is recommended not to intervene on a pyrotechnic facility on fire but;

-to alarm, to warn the crew and to evacuate the area concerned or neighbour of the place of the disaster -to go away as soon as possible of the area and go to a rally point -In any case, staff members don't have to fight a fire of explosive products. Only provisions to avoid a possible extension of the fire can be taken. Where this extension cannot be prevented, the secure zone must be maximized Pyrotechnic products decompose without additional oxygen carrier from outside their formulation. This is what differentiates them with ordinary combustibles like oil and other flammable products; in addition they continue to react the same way under water which can sometimes even be a factor worsening if there is presence of fine metal powders.

Water can be effective on small amounts of explosive products, in the case of a workshop for example but not in case of a storage fire. Water can also play a shield role so that the intervention teams specially equipped to intervene to save people; it also allows you to cool the surrounding installations to avoid rapid extension of the fire.

History has also shown that even if the fire appears to be mastered, extreme caution is still needed to allow for enough cooling time and be ready to cope with side reactions like cookoff (initiation and violent breakdown of neighbouring explosive products by slow heating).

Automatic (sprinklers or inert gases such as CO2) fire extinguishing systems are not effective on fireworks in boxes in a container, the fire may smouldering and pyrotechnic compositions do not need oxygen to work.

Only a complete flooding of the fireworks can be effective, which is possible in a cargo ship but very long compared to the reactivity of a fireworks fire, once detected.

CONCLUSIONS IN TERMS OF SAFE PRINCIPLES FOR TRANSPORTATION OF FIREWORKS ON A CARGO SHIP

Recommendations target both filling fireworks in maritime containers and container loading and stowing on the container ship.

1/ proceed to pertinent fireworks classification regarding Transportation of Dangerous Goods: the first recommendation concerns the classification of the fireworks. The only way to get a secured classification is asking to the sender the risk division of fireworks issued by the transmitting competent authority (which is for the time being only required by the ADR and not by the IMDG).

2/ limit the quantities: the second recommendation is then to limit the quantities loaded to limit the effects in the event of accidental scenarios, 3/ select an adequate packaging: the third recommendation is to ensure the quality uploads by choosing a type of packaging adapted to avoid moving material goods during stowage. These actions will help to reduce the probability of an accidental event and therefore limit related risks.

4/ make use of suitable containers: a possibility is to use containers with fire walls able to contain a Fireworks fire. To our knowledge, there are no such containers that are in current use for maritime transportation, this type of fire resistant container is however in use for the storage of dangerous goods.

5/ define a safe position for stowage fireworks containers on ship: in order to limit the thermal effects, we recommend to position the fireworks containers onside the deck and far from accommodation areas, and enclosed as far as possible with empty containers to limit the spread of the thermal effects (or to use special containers). Another possibility is the stowage below deck inside the first dock, if equipped with a rapid flooding system and fire detectors (inside containers).

Figure 2 :

 2 Figure 2: Severity of accidents per type of composition  The density of composition inside the packaging, and consequently the confinement inside the packaging: fireworks, according to their type, confinement or quantities, can have different behaviours; mass explosion (maroons, big shells or roman candles), heavy thermal effect (fountains, Bengal, rockets) with a possibility of transition to a mass explosion in case of high storage density (see CHAF project results [1]), or light thermal effect only located in the immediate vicinity.

Figure 3 :

 3 Figure 3: Fire in the Hyundai Fortune cargo ship Among recent accidents involving containers, the best-known is the one in the port of Changsha in 2006 where 200 containers have caused a significant fire after an explosion as initial event.

Figure 4 :

 4 Figure 4: Fire in the Changsha harbour

Figure 5 :

 5 Figure 5: Containers above and below deck

Table 1

 1

Table 2

 2 table 1 below).

	Probability	Example of accidental event with fireworks
	P 0	Accidental functioning in package accepted for transportation, during operations
		of loading/unloading, from time to time outside period of high activity
	P 1	Accidental functioning in package accepted for transportation, during operations
		of loading/unloading and handling (package leakage, friction, shocks, drops, …)
		Accidental functioning of fireworks during operations of handling, sampling or
		dividing
	P 2	Accidental functioning during linking of fireworks without any modification of
		product
	P 3	Accidental functioning of igniters during electric testing or checking

Table 4

 4

		1.1G	Maximum 110 kg to avoid overpressure effects
			if surrounded by empty containers
		1.4G and/or 1.4S	1890 kg
			Or more if 1.1G is less than 110 kg
		1.3G or 1.2G	< or equal to 2 tons max
	Loading type 2	1.4G and/or 1.4S	The remaining according to the quantity of 1.3G
			or 1.2G, until 2 tons max.

  1 goods and related necessary precautions. -Containers loaded with fireworks from different divisions can be transported together in a same compartment and next to each other in deck because groups G and S compatibility allow it.

	UN Number	Designation	Division	Stowage category	Meaning
	0333	Fireworks	1.1G	Category 7	In closed containers above or below deck
	0334	Fireworks	1.2G	Category 7	In closed containers above or below deck
	0335	Fireworks	1.3G	Category 7	In closed containers above or below deck
	0336	Fireworks	1.4G	Category 6	In closed containers above or below deck
	0337	Fireworks	1.4S	Category 5	In closed containers above or below deck


Truchot Benjamin

Duplantier Stéphane

Dispersion in Confined Building: a Coupled Approach

Keywords: toxic dispersion, critical infrastructure, large eddy simulation, coupled approach

Modelling gas dispersion in mechanically ventilated building is a challenge for safety engineers. A leak in such an infrastructure can generate two different consequences: toxic effect or blast effect after a flammable vapour cloud ignition. In both case, it is important to be able to predict the gas behaviour using numerical tools in order to be able to design adapted ventilation systems. Gaseous products are generally stored under pressure that induces high velocity in case of release from the tank or following a line rupture. Considering this important pressure, the jet zone is a highly complex zone with a Mach number higher than 1 that induces shock waves. These waves correspond to discontinuity of the flow. After this jet zone, a transition region (air entrainment) is observed and can be characterised by the beginning mixture of the gas with air. This also corresponds to an expansion of the jet diameter inducing a velocity decrease. Finally, after this zone, the flow becomes governed by the ventilation system where the Mach number is lower than 1. To model gas dispersion in closed enclosure, CFD models can be used. Such codes enable to predict the different physical quantities in the whole domain along time. However, most of these codes are not able to model complex phenomena such as ones that characterised the jet region. CFD codes are able to capture such a complex physic require mesh in the jet zone that is not in accordance with the objective to model the whole infrastructure considering current computing limitations. To overcome this and making achievable such modelling, a coupled approach between a 1D jet model and a CFD code is proposed. The 1D model predicts gas behaviour in the jet zone while the CFD code describes the concentration and velocity in the whole domain. The FDS CFD code was used. This code is based on the LES approach for turbulence modelling. Such an approach is highly interesting for safety because it enables not to predict an average configuration but a realistic one. Because of the well known capability of this code for predicting smoke behaviour considering ventilation, it is useful to wonder about its capability to model gas dispersion in buildings. A comparison between FDS, coupled with the 1D model, results and experimental ones are given. The experimental results were obtained in an 80 m 3 room equipped with a ventilation system in which ammoniac was injected. Two different ventilation regimes were used and concentrations were measured in several locations inside the room at different heights. Comparisons between experimental and numerical values shows a great agreement and leads to the conclusion that the FDS code is a pertinent tool for gas dispersion modelling in confined building when coupling this code with a 1D jet model.

Introduction

Toxic releases in large enclosure are a topic of interest regarding both accidental risk and intentional threat. On the first hand, toxic gases are commonly used in industrial facilities and that can generate, in case of release, catastrophic consequences. Several gases must be considered in such a configuration, ammonia, chlorine, hydrogen cyanide, ... To provide an example, ammonia, which is commonly used for cooling is generally stored at its critical pressure will be at 8 bars. Such a pressure will generate, in case of release, important velocities and the jet can, in some configurations, become sonic.

On the other hand, toxic gases can also be used for terrorism. In such a case, not only industrial chemicals can be used but military ones too. For the first ones, they could be introduced using pressurised containers that induce the same problematic as accidental release. For the second, i.e. the military toxic gases, they are liquid under atmospheric conditions and consequently, they could be release as a pool. This second case is out of the topic of the present paper that focuses on the link between a pressurised gaseous release and the dispersion in a large enclosure. So, as mentioned above, the objective of this paper consists in modelling a high pressure gaseous release in a large enclosure. This enclosure can be either an industrial building or a critical installation as airport or train station for example. In both cases, dimensions of the domain will be strongly larger than the characteristic of the jet. So, two different zones must consequently be distinguished with own properties to be discussed, Fig. 1 and Table 1. As represented on this figure, dimension of the infrastructure can be larger than hundreds meters while the jet characteristic size is of about of cm. Consequently, characteristics dimensionless numbers for the two flows can be highly different. To keep this in mind, summarize characteristic dimensions and dimensionless numbers for a ventilated infrastructure, industrial or critical one, and for the release jet. Fr 0.01 to 0.5 5e6 to 15e6

Ma << 1 ≈ 1 to > 1
Before going any further in the physical requirement, the dimensionless numbers must be clarified. The Reynolds number, Re=(ρUL)/µ, represents the ratio between inertia and viscous effects and is characteristics of the turbulence. Higher is the Reynolds more important the turbulence is. It appears that, even if the velocity, and consequently the shear, are lower in the infrastructure without the jet, characteristic dimensions of the room governs because this allows a large range of possible turbulent scales.

Consequently, it should be considered that turbulent phenomena are mainly attached to the ventilated infrastructure. The Froude number, Fr=U²/(gL), represents the relative effects of velocity induced forces and gravity ones. It appears clearly that, for the present case, the jet flow is governs by velocity forces in the near field. The Mach number, Ma=U/C, represents the ratio between motion forces and fluid compressibility. A low Mach number, <<1, means a weak compressibility while an important Mach number signifies that compressible effects must be accounted for.

Those three numbers enable to make a clear distinction between the physic associated to the jet zone and the one of the whole ventilated infrastructure, without this jet. It appears through these dimensionless number that velocity effects governs a highly compressible flow for the jet zone but that turbulence is moderate considering that the Reynolds number is around the transition criteria. On the opposite, the flow in the ventilated infrastructure is characterized by an important turbulence level but a weakly compressible flow with a great influence of gravity. So, it appears that physical issues are different depending on the interest zone.

Two next paragraphs discuss respectively on jet modelling regarding the physical characteristics and existing techniques and on flow modelling for the whole infrastructure.

Gases Jet Modelling

Several ways are available to model jet flows. Because a CFD approach is used for modelling dispersion in the whole domain, it is legitimate to wonder about its capability to be used from the release to the exhaust.

CFD Capability for Jet Modelling

If modelling high pressure jet for liquid or gas is a challenge for the CFD approach considering the complexity of the associated phenomena, some approaches were developed for particular configurations [START_REF] Truchot | Modelling of turbulence in the context of an eulerian approach for simulating two-phase flow in internal combustion engines[END_REF] . Because of the characteristic size of the injection jet, suitable mesh is required to model the different phenomena even if turbulence is quite low. Considering this characteristic size, in the order of mm up to cm, this implies mesh to respect those characteristics with cell size in the order of mm or minus. On top of that, considering a 1mm cell with 300m/s velocity, it is possible to evaluate the order of the time step for such a modelling based on the CFL criteria. This CFL condition means a relation between velocity, spatial discretization and time step: U∆t/∆x < 1 [START_REF]Numerical computation of internal and external flows[END_REF] .

Consequently, for the above mentioned characteristics of the jet, the time step has to be in the order of 10 -6 s. Furthermore, solving such a physic requires particular numerical techniques to be able to compute highly compressible flow. So, it appears that computing such thin important gradients requires a fine mesh. Because of the size of the domain to be model in the context of accidental gas dispersion, using such a mesh is not realistic and it is required to couple a jet flow model with the CFD simulation tool.

In the context of our study, that consists in modelling the jet inside a large infrastructure during quite long period that can reach one hour, this leads to unrealistic configuration. It then appears that the jet zone cannot be modelled, in the whole geometry, using a CFD approach. This implies introducing a coupling technique between two approaches. Consequently, a 1D jet model that enables to describe the leak behaviour from the hole to a low velocity zone is used to predict the jet evolution in the first centimetres.

2D Jet Model

Physic that occurs inside a high pressure release jet is highly complex and several studies were achieved to improve this phenomena description [START_REF] Beer | Combustion aerodynamics[END_REF] . Mainly a complex sequence of shock waves can be produced. These shock waves will of course influence the flow and consequently the jet expansion. As shown in previous studies [START_REF] Donaldson C D | A study of free jet impingement. Part 1: mean properties of free and impinging jets[END_REF] , a high pressure jet can be split into three zones: (1) A shock area with flow instabilities; (2) A transition zone; (3) A fully developed region.

This can be schemed, following [START_REF] Donaldson C D | A study of free jet impingement. Part 1: mean properties of free and impinging jets[END_REF] as reproduced on Fig. 2 for weakly under relaxed jet with oblique shocks. In this case, the jet relaxed in the ambient to the atmospheric pressure through a series of shock waves.

Fig.2 Schematic representation of the jet zone

Such a configuration is very complex to model and several works were achieved to obtain a description of the near filed, mainly [12][13] or, more recently [START_REF] Harstadt | Global analysis and parametric dependencies for potential unintended hydrogen-fuel releases[END_REF] . It consists in computing a "pseudo-source" with an equivalent diameter that aims representing the jet flow after this complex wave's zone. The Birch's model was used to describe the first zone of the jet and computed equivalent diameter based on an isotropic approach, equation (1).

      -   =               (1)
After having computed this equivalent diameter and characteristics at this diameter, a classic 2D analytical method for jet velocity and concentration evolution can be used. Some studies [START_REF] Beer | Combustion aerodynamics[END_REF] have shown that velocity and concentration profiles can be approximate using Gaussian curves function of the centreline value. The centreline values are proportional to d 0 /x. Then, a full set of equations is available to compute the 2D jet expansion, (2) and (3).

0 0 ( ) / ( / ) m u u x U k d x = (2) 0 0 ( ) / ( / ) m c c x C k d x = (3)
And then the Gaussian profiles are given by equation ( 4) and (5).

( ) / exp

m u r u r u K x       = -        (4) 2 ( ) / exp m c r c r c K x       = -        (5)

Identified limitation

This model of course induces some simplification in terms of solved physical phenomena. The jet evolution from the hole to the equivalent diameter can be assumed as well reproduced considering in this zone exchanges with ambient are weak. In the following mixing region, if the jet is well solved considering the air entrainment inside with the concentration and velocity distribution, the momentum transfer from the jet to the ambient is not modelled as the air well term due to jet entrainment. Of course this induces approximations about the velocity distribution close to the jet region. It must be however kept in mind that the objective of this work is not the jet prediction but the evaluation of the concentration distribution in large infrastructures. For this objective, it is considered as first approach that this momentum transfer can be neglected.

The second drawback of this model is that jet turbulence is not taken into account. Considering the characteristics of this zone, mainly the Reynolds number, it appears that turbulence of this zone is not as important as the one of the whole domain. This means that the turbulence source term form the jet to the domain can be neglected and consequently it is not modelled with this approach.

CFD Modelling of the Infrastructure

Computational Fluid dynamics (CFD) is a powerful tool to design safety measures but it must be kept in mind that such an approach still has some limits that must be known before achieving some modelling. The aim of this section is to provide a short overview of the CFD approach centred on the limits for gas dispersion modelling. The CFD general basis is the set of continuity equations: mass, momentum and energy. These equations cannot be solved explicitly, excepted for some ideal cases, and some sub models are required. The main one concerned the turbulence modelling. This model is detail in the first paragraph of this section because it impacts directly the dispersion modelling. Finally, the second paragraph of this section concerns the numerical solver. The one describes in this paper is the FDS one because of the available LES model of this code. The main interest of this numerical description is the underlining of the limits induced by this numerical approach.

Turbulence Modelling: LES Approach

These instantaneous equations require to be solved with a very fine mesh because their resolution implies to capture all the turbulent scale of the flow from the integral to the Kolmogorov one. Turbulent scales are going from integral scale to Kolmogorov one. Integral scale, l t , is given by: ' Re . u l t t ν = while the Kolmogorov one is:

1/4 3 k ν η ε   =    
, corresponding to a unity Reynolds number. Of course, solving the whole turbulence spectrum is not realistic for industrial configuration. Modelling the whole scales requires the mesh to be fine enough to capture all those length, consequently, the number of cells requires in such a case is in the order of Re 9/4 [START_REF]Numerical computation of internal and external flows[END_REF] . For the present case, considering a 10 6 Reynolds number, this requires more than 3.10 13 cells. It is then possible to deduce that, this commonly called DNS (Direct Numerical Simulation) approach, cannot be used for dispersion modelling. Some approximations have to be made. It also must be considered that large scales contain the major part of the turbulent energy, which means that they govern the flow. On the opposite, smaller scales are responsible of the turbulent energy dissipation. On top of that, if large scales are not isotropic, small scales becomes isotropic and consequently can be modelled.

Two approaches are available: the first consists in averaging the equation using a statistical tool (RANS: Reynolds Average Navier Stokes), the second consists in filtering equation to solve large scale and model the small ones (LES: Large Eddy Simulation).

Because of the importance of the time dependence for such a phenomenon and the importance of large structure in the gaseous species transport, the LES approach was chosen.

The LES approach requires introducing a filter on the equation [START_REF] Sagaut | Large eddy simulation for Incompressible flows: an introduction[END_REF] . This filter consists in a cut off length in spatial space or in a cut off frequency in the energy diagram. Applying such a filter on the flow equation lets appear some cross correlation to be modelled while large scale quantity can be solved.

Solving the opened cross correlation means determining the turbulent energy transfers from large to small scale. Several approaches exist from static to dynamic ones. The objectives of this paper is not to detail the LES approach that can be find in [1] but to examine the limitation that can be generated by such an approach for dispersion modelling. For both modelling approach, the sub grid viscosity is written as a function of the Smagorinsky constant, C s and the width of the filter ) 2 ( . ) 3

t ij ij C S S u ν ∆ = -∇ (6)
The filter size is directly governed by the mesh but the Smagorinsky constant have then a real impact. Let first consider the static approach that is commonly used. In this case, the C s value is fixed before the simulation. So, this means that the energy transfer from large to small scales must be evaluated a priori. If this value is well known for an homogeneous isotropic turbulence, the value for a complex industrial flow is highly difficult to predict. Furthermore, this value is flow dependant and consequently, its value will vary along time and space. This is the objective of dynamic model to compute its value. However, the complexity of those models is higher and such a model was not used in this paper. So, the limitation of the LES approach appears clearly and mainly concerns the choice in terms of C s value. However, this description lets appear the mesh size importance considering that, if the cut off frequency is not in the inertial zone, the model is not consistent. Those two problems must be referred both for numerical model construction and results exploitation.

FDS Description: Numerical Method

The numerical description of above mentioned equation is one key parameter for CFD. Depending of the numerical scheme that is retained, some limitation should appear. The CFD tool that was used in the present study is the Fire Dynamic Simulator (FDS) [5][6] .

This code is especially dedicated to fire modelling and consequently contains some hypothesis about the flow that enables to simplify the numerical approach. The main one is a low Mach number hypothesis that induces incompressible flow. This hypothesis enables to separate pressure in an average part and a fluctuating one. This numerical approach induces that high release velocity cannot be capture using the CFD code.

To complete the description, it must highlight that FDS is based on a first order finite difference spatial numerical scheme coupled with a two step predictor corrector temporal solver.

Synthesis of CFD Benefits and Limits

The brief CFD description given in this paragraph has highlighted several limits for accidental gas release in an enclosure. First of all, it was discussed the utility of the LES approach for turbulence modelling because of the importance in solving the unsteady phenomena with peak values instead of the average ones. However, using LES induces some constrains, mainly on the mesh that governs the filter size. This size must be in the inertial zone to have a correct numerical model. The second limit concern the Smagorinsky constant that is well known for a Homogeneous Isotropic Turbulence but a priori unknown for other flows. It must be considered however that, in the case of a large infrastructure, the turbulence can be assumed as quite isotropic and homogeneous and that the constant is around 0.2.

The last hypothesis is more specific to the CFD code used in this study, FDS and concerns the law Mach number hypothesis.

This hypothesis is in accordance with the choice of using an algebraic model for the jet. The results of the jet model are used as boundary condition in the CFD code by creating a source with a dimension as computed by the model with given velocity and concentration distribution. As discussed previously, this approach does not make possible to account for momentum transfer along the jet zone, from the hole to the virtual source and for turbulence transfer from jet area to ambient.

Confined Dispersion: a Experimental Validation

The aim of this paper is to discuss about the LES capability for dispersion of toxic gases inside building equipped with a ventilation system. To validate this capability, CFD results is compared with experimental measurement obtained in an 80 m 3 room of INERIS.

Experiment Description

The INERIS 80m 3 room is a 5m long, 4m width and 4m height and is equipped with a ventilation system that enables to control the flow rate through the room. This room is schemed on Fig. 3 where photography is also given.

This scheme shows the operational room located upstream the building. This operational room enable to install the measurement apparatus and all other control system. In order to homogenise ventilation inside the building, a wall is positioned near the entrance in order to prevent from a fresh air jet formation. This aims to have a well distributed flow inside the building. A large series of experiment were achieved but, for the present source model, only gas release can be modelled. The above described jet model is not yet able to deal with two phase flow and consequently, only two experimental configurations can be modelled. These two configurations correspond to different releases and different ventilation regimes. The first configuration is a 4.4g/s gaseous ammoniac release with a 2000m 3 /h ventilation rate. For the second configuration, the ventilation flow is only 500m 3 /h for a 2.2g/s ammoniac release. So, ventilation flow rate fore the second case is divided by 4 while the ammonia injection rate is only divided by 2. This release is achieved in both cases through a 2mm hole. (1/Re) 3/4 , is in the order of 1.6*10 -4 m. The Integral scale is in the order of half the room width, i.e. 2m, that represents the larger scale than can be encountered in the domain. It must be important to keep in mind that the objective is not in reproducing the jet dynamics but the ammonia dispersion inside the room. Considering that 1/20 of the integral scale is in the inertial zone, this implies cells to be lower than 0.1 m. This value was used to define the mesh with 0,1 m cells. This size enables to filter the fluid equations in the inertial zone and consequently respects the LES requirements with 120000 cells.

The second point to be checked in the numerical model is the Smagorinsky constant. Considering that, because of the ventilation coupled with the injection, turbulence is 3D, the 0,2 standard value was kept. This will be discussed according the results. The results for the two ventilation configurations are described next.

Comparison Between Experimental and Numerical Results: 4,4g/s Release

As mentioned above, the fist experiment that was modelled corresponds to a 4,4 g/s release with a ventilation flow rate of 2 000 m 3 /h. Fig. 5 shows the ammonia distribution inside the room 240 s after the release start. This figure is interesting because it shows the position of the virtual source and the dynamic of the ammonia jet that impinging the wall. As shown on this picture, the virtual release is quite far from the real source and consequently bigger than the real hole. However, according the jet sub model, the characteristics of the jet is maintained and enables to achieve a realistic computation.

Concentration at the top and at the bottom of positions 1, 3, 4 and 6 are presented on Figs. 6 and7. This part corresponds to a quick increase of the concentration in this domain that can be due to the dynamic of the jet. This dynamic cannot be reproduced by the CFD code and consequently, this first phase is not well reproduced. The important increase is however quite surprising because this is the only one sensor that shows this increase. On top of that, the concentration after those 250 s is quick well reproduced.

Finally, considering the importance of a ventilation system in such an equipment and the impact that a gas can have on this system, the prediction of the concentration at the entrance of the ventilation system was compared with the experimental value.

According this first series of comparison that seems encouraging, it is interesting to go any further with the second configuration experimental and numerical comparison (Fig. 8).

This curve shows that the value at the entrance of the ventilation system is quite correctly predicted using the simulation code FDS. The difference observed in the 250 first seconds can be explained by the sensor dynamic and the discrete measurement. Once again, it is important to note that the sensor error is around 30%.

Comparison Between Experimental and Numerical Results: 2.2 g/s release

The difference between the previous case and the present one is the ventilation flow rate and the injection rate. The injection is, for this case, 2.2 g/s while the ventilation flow rate is diminished to 500 m3/h. The dynamic of the flow is quite not modified and, mainly, the integral scale can be still estimated to the half size of the room. As for the previous case, the evolution of concentration for the upper and lower sensor for each corner of the room is plotted again the predicted value, Figs. 9 and 10.

This second series of comparison curve show again a god agreement between experimental results and numerical ones. Only the prediction of concentration on the lower sensor of position 4 is far from measurements. It is important to note that, on this curve, the first part of the experimental curve is not plotted because values are negative, around -0.2. This may indicated either a sensor default or a concentration out of the range. Conclusion is the same and this point cannot be exploited placidly. This second series of comparison shows a great agreement between experimental values and numerical predictions. The simulation FDS code is able, not only to predict the steady values but the unsteady evolution to. In the introduction of this paper, two main criteria were identified as critical for CFD modelling. First and second concern the turbulence modelling: filter size and Smagorinsky constant. Finally, the jet model influence must be discussed.

To evaluate the first, a simulation was achieved with a finer mesh, 420 000 cells and a highly finer mesh, with 2 250 000. Those two simulations have shown a weak influence of this parameter on the predicted concentration. However, the finest mesh has shown the LES ability in capturing small turbulent scale. Consequently, the concentration evolution curve is noisy; this can be explained by the fact that smaller cell size implies smaller scale to be captured with a smaller characteristic time. Such high frequency cannot be captured by gas sensor that gives an averaged value.

The second parameter is the Smagorinsky constant that was kept to the 0.2 standard value considering a 3D flow, and consequently, a 3D turbulence decrease. Because the lack of data concerning velocity fluctuation, it is not possible to construct the experimental turbulence spectra that can confirm this value. The concentration comparison on the different position confirms that the flow is correctly reproduced because values are correct in the four corners of the room both in the upper part and in the lower part of the room. Consequently, for the present dispersion case, this choice appears to be valid. Simulations achieved with lower values have

shown that this has, as assumed, a weak influence on the result, which signified that resolved scales are responsible of the mixing.

Finally, as discussed above, the jet sub model induces a momentum loss because one part of the kinetic energy to be transfer to the ambient air before the virtual release. It appears that, this part of the momentum is not crucial for gas dispersion prediction in a ventilated enclosure. Finally, it appears that, even if some approximation are made for computing high pressure gas release in an enclosure, FDS is quite correctly able to predict concentration distribution inside the whole room.

Conclusions

This paper describes a methodology to model gaseous release in large infrastructure, from the source to the whole domain.

Because of the complexity and characteristics of jet near the release, CFD cannot be applied to the whole domain. An algebraic model form the literature is used before introducing the results in the FDS CFD code to model the dispersion inside the infrastructure.

The jet model enable to predict the concentration and velocity in accordance with the CFD model limits while keeping the major information: velocity and concentration. After introducing this in the CFD code, turbulence phenomena in the domain is model using a LES approach to capture the large scale effect and obtain the unsteady characteristics of the flow.

This coupled methodology was compared with experimental data for two cases of ammonia release in a ventilated 80 m 3 room.

Sensors were distributed inside the room to follow the concentration evolution along time. The comparisons have shown that, for both case, a great agreement between experimental measurements and numerical prediction. This signifies that, while some phenomena are not accounted for, the global behaviour of the gas dispersion inside the domain is correctly predicted. These comparisons have also shown that, even the uncertainties on several parameters as Smagorinsky constant, the flow is sufficiently well reproduced to have a correct prediction of the concentration field in the domain.

Finally, the proposed approach seems valid for such an application and can be extended to real configurations for both accidental hazards and intentional threats.

Several perspectives are identified for future work to improve this approach. The first concerns the jet part for which turbulence, momentum and air transfer with the ambient can be introduced in order to evaluate the influence. Concerning turbulence, because LES is used, turbulence is not just boundary conditions on certain quantities as for RANS approaches but it consists in the time fluctuation of the different physical values. Doing this requires to be able to determine the characteristic frequencies of the flow, through for example a Strouhal number. For the momentum and air transfer, it consists in a boundary condition on the mass and momentum equation through a well term of air function of the entrainment characteristic of the jet and a shear velocity determined using the algebraic law.

Then, because not only gaseous toxic can be release, a two phase sub model must be evaluated. However, in this case, the momentum quantity transfer to the gas will probably not be neglected and such an improvement will come later.

The second perspective aims in improving the CFD modelling and mainly turbulence. This can be done, for example with the dynamic LES model that enable to compute the energy transfer from large to small scale as a function of the flow. Such an approach is more realistic than a constant in the whole domain.

Finally, if this approach was developed for confined dispersion, it is also suitable for atmospheric dispersion. In such a configuration, the domain characteristic dimensions are not on the order of hundred meters but in the order of kilometres. The problematic is next quite similar considering the main part of the turbulent energy is the atmospheric turbulence that governs the gas dispersion. However, some other problems have to be solved before achieving such a computation: atmospheric turbulence description, influence of the roughness and the LES wall law problematic.

Notations

Fig. 1

 1 Fig.1 Schematic representation of nested physics

Fig. 4 (

 4 Fig.4(b) presents the sensors distribution inside the room. Six vertical measurement lines are distributed inside the building, each line is equipped with three gas detectors and 5 thermocouples located at different height, Fig.4(a).

Fig. 3 Fig. 4 Sensors distribution in the building 4 . 2

 3442 Fig.3 Scheme and photography of the INERIS 80 m 3 room

Fig. 5 Fig. 6 Fig. 7

 567 Fig.5 Visualization of the results: ammonia mass concentration 240 s after the release start

Fig. 8 Fig. 9 6 4. 5

 8965 Fig.8 Evolution of the concentration at the entrance of the ventilation system

  Fig.10 Evolution of ammonia concentration versus time for lower of position 1, 3, 4 and 6

Table 1 Characteristic of the infrastructure and jet

 1

	Characteristic	Infrastructure (grey on Fig.1)	Jet (black on Fig.1)
	L	Decades to hundreds m	Some mm to cm
	U	≈ 1 m/s	> 300 m/s
	C	10 2 to 10 6	1 near the hole
	Re	1×10 6 to 1×10 7	1×10 4 to 5×10 6


Benjamin Truchot

T Durussel

Stéphane Duplantier

Combustion Rate of Medium Scale Pool Fire, an Unsteady Parameter

Keywords: combustion rate, medium scale, pool fire

Pool fire is a classical dangerous phenomenon that can occur in various infrastructures and generates different consequences. Several investigations were achieved to improve the understanding of this phenomenon from theoretical to experimental. Experimental studies have lead to a classification of fuel as a function of combustion rate. These tests are generally based on constant level fire with fuel feed at the bottom of the sample. Theoretical studies have detailed the fire heat release distribution and the impact on the liquid fuel. Based on these results, the expected evolution of the fire includes three main parts: the fire increase, a constant maximal heat release period and the fire decrease. If this evolution suits with external pool fire, behaviour of the liquid can be impacted by contextual configuration. In confined infrastructures, such as building or tunnels, the liquid fuel combustion velocity becomes an unsteady parameter and the heat release rate from the fire varies, and often a runaway phase of the reaction is observed. Because such fires could be used for demonstrating the efficiency of a ventilation system, the power release must be controlled. This may have an important impact on the design of a mechanical ventilation system or the fire resistance of the infrastructure. To control the released power of such a fire, it is important to have a good understanding of this diffusion flame influenced by the environment. Then, understanding the phenomena that occur in the fire region means characterizing: the radiative fraction, the thermal exchanges and the impact of the flow on the fire. Using the results obtain along several experimental campaigns, both confined and unconfined, that were achieved in INERIS concerning pool fire, the different physical parameters are discussed and confronted with theoretical one. This paper proposed a physical characterization that finally leads to a power control strategy for pool fire.

Introduction

Pool fire is not only an important dangerous phenomena but a useful one. Such a phenomenon can occur in different industries as petroleum, chemical plants and generate dramatic consequences. However, such a phenomenon is useful for fire safety because it can be used easily, for example to validate a tunnel ventilation system. Liquid pool fires were studied through different ways in the Literature, theoretical, numerical and experimental. However, most part of these studies refers to steady state pool fires that are not in accordance with long pool fires experiment in tunnels. In such a configuration, not only the physic of the pool fire governs the phenomenon but the tunnel specificities too. On top of that, the objective of long time pool fire adds some complexity.

On the one hand, accidental pool fires can occur in the retention pool of highly important fuel storage that means very long pool fire. On the other hand, because pool fire can be used for checking the ventilation design, the heat release must be controlled during a period as long enough as vehicle fire, for example. Consequently, studying long pool fire is a major interest for safety engineers.

This study is based on an experimental approach. Heptane pool fires were achieved in a third scale tunnel in order to determinate evolution of the heat release of such a fire during a long period that can reach more than one hour. This evolution shows that a runaway occurs instead of a constant heat release rate. Understanding the occurrence of such a runaway is crucial because it reveals that classical approach of constant heat release rate cannot be considered as an adjutant approach. The present study refers only to confined pool fire, i.e. it mainly concerns fire in tunnels, and cannot of course be extrapolated to atmospheric pool fire. In that second case, the heat exchanges are quite different. This paper presents first the theoretical and experimental heat release curve for a heptane pool fire. Next, on the basis of temperature evolution in the liquid, the different phases that were observed are explained. Finally, some experiments enable to validate these explanations.

Experimental Heptane Pool Fire

Experimental Apparatus

Experiments were achieved in the INERIS fire gallery. This experimental device is a tunnel with a third scale section compare to a real one with 3 m in width and 1.85 m height. This tunnel is 50 m long and is equipped with ventilation and air treatment system,

Ideal Heptane Pool Fire

The apparatus used to generate the fire is a round container of heptane with a section of 0.25 m² and 0.20 m height. Such an installation may enable to obtain a constant power. Following theoretical knowledge about liquid pool fire, the fire power and duration can be evaluated using the combustion velocity and the heat of combustion. Using the classical values for heptane [START_REF] Babrauskas | Estimating large pool fire burning rate[END_REF][2] , i.e. a combustion velocity of 44 g/(m²⋅s) (i.e. 11 g/s for a 0.25 m² pool) and a heat release of 44.6 MJ/kg, the power that has to be reached by a 0.25 m² heptane pool fire is of about 500 kW. This correspond to the theoretical fire and, for such a theoretical approach, the initial power increase phase can be described using a t² law [START_REF] Cajot | Thermal and Mechanical actions[END_REF] . For a heptane pool fire, the corresponding phase is a very fast fire increase. This enables to evaluate the theoretical time for a 0.25 m² and the theoretical evolution in time of the fire power. The estimate time for this fire is about 40 minutes with a 20 minutes long period of steady state which corresponds quite to the standard curve for a vehicle in tunnel, as described in the first section. This theoretical approach predicts a three phases curve for heat release along time, Fig. 2. This theoretical approach shows that fire duration must be higher than half an hour with a very fast heat release rate increase and 22 minutes of constant heat release. On the basis of this approach, experiments were achieved for a 0.25 m² heptane pool fire.

Experimental Heptane Pool Fire

After this theoretical description of the heptane pool fire, it is important to check the compatibility between a theoretical pool fire and a real one. Long heptane pool fire were achieved, the total duration of the fire was longer than 30 minutes. This induces enough time to equilibrate the different thermal exchanges. The experimental release rate is reproduced on Fig. 3. Of course, this curve must be compared with the theoretical one. It appears that the heat release during phase II is in quite good accordance with theoretical value, around 500 kW. It however appears that this value is not the peak value reached by the fire. The heat release maximum value is quite the double of this theoretical value and the decrease phase, starting from this important peak value decrease to the theoretical maximum before the extinction phase. On top of that, it must be noticed that the second phase is quite longer than the first constant phase II. Finally, a surprising decrease appears in the middle of this heat release rate evolution before the important rise. Consequently, all these six phases must be explained and understood. Before going any further in the explanation for each phase, the physical behaviour of a pool fire must be described.

Liquid Fuel Pool Fire Physical Description

It must be first kept in mind that pool fire is nothing else than a self-sustaining diffusion flame. This implies two main characteristics: first, the flame position is governed by the mixing with air and second, the flame governs the combustible gas production. So, the above mentioned problem of obtaining a long steady fire means obtaining a steady exchanges between the flame and the liquid in order to feed the fire with a constant combustible flow rate.

Overview of Heat Exchanges

Several studies were achieved to improve the understanding of the pool fire behaviour. However, a large number of experimental tests were done at small scale either for space or in time. In both case, the involved phenomena are not representative of a large and long pool fire. Furthermore, the confined configuration in tunnel adds some complexity.

The thermal transfers were studied by different authors [START_REF] Nakakuki A | Heat Transfer in Hot-zone forming pool fire[END_REF][START_REF] Nakakuki | Heat transfer in small scale pool fires[END_REF] and can be simplified to the scheme that represented this equilibrium, Fig. 4.

Flame

Radiation from flame to the liquid surface

Liquid fuel

Heat exchanges between fuel and surronding air Liquid fuel evaporation

Fig. 4 Thermal exchange for a pool fire

This scheme represents a simple view of the thermal exchange between the air, the flammable liquid and the flame. It must be consider however that, in a tunnel configuration, the ventilation flow has an influence on the flame behaviour. The ventilation velocity will move the flame downstream the pool, as represented on Fig. 5.

Flame

Liquid fuel

Fresh air

Fig. 5 Thermal exchange for a pool fire in tunnel configuration

The principle consists in heating the fuel by the energy emitted by the fuel combustion till it reaches a sufficient temperature to provide fuel vapour. Two cases should be distinguished. The first consists in a liquid boiling with emission of fuel without air. In that case, liquid behaviour will be quite chaotic because of the boiling effect. The second is equilibrium at a temperature that induces a high enough vapour pressure on the liquid surface. On that second case, some air will be present in the initial mixture. For the studied pool fire, the temperature seems to be of about 90°C (Fig. 6) that corresponds to a vapour pressure of 7.8.10 4 Pa, which induces a fuel concentration of 78%.

The configuration of the heat reception and heat losses induces the creation of a temperature gradient inside the liquid. This means that keeping a steady evaporation rate requires a steady heat exchanges.

Having this behaviour in mind, analysis of the temperature evolution curves can be achieved.

To improve the understanding of the six above described phases, thermocouples were introduced inside the pool to follow temperatures during the fire, Fig. 6.

This curve must be read keeping in mind the heat release rate evolution. This comparison between the two curves shows clearly that the beginning of rapid heat release increase corresponds to the instant when the liquid temperature at the pool bottom reaches the heptane boiling temperature. Based on these elements, an explanation of the heat release evolution is discussed in the following. The strong temperature rising on this graph reveals that the flame reaches the thermocouple.

Initial Growth and Constant Phase -Phase I and II

The first two periods, i.e. the initial power growth and the steady period, are typical of pool fire. However, it must be noticed on the heat release rate that the increase is slower than expected. The rising curve does not follow a t² classical curve as discussed by [START_REF] Cajot | Thermal and Mechanical actions[END_REF] .

The main consequence of this is that using a t² heat release rising is not realistic but induced an adjutant position for safety study.

During the initial growth phase energy received by liquid heptane is used to produce more fuel vapour till equilibrium is reached.

During this equilibrium phase, as discussed above, flame energy radiated to the liquid is divided into two parts:

• Evaporation of fuel,
• Energy conduction inside the liquid.

Considering that evaporated part of the liquid was previously preheated and knowing the mass loss rate, it is possible to evaluate the energy consumed for evaporation. The mass loss rate is around 10 g/s, which mean an energy consumption of 3.21 kW with a 321 kJ/kg for the evaporation enthalpy. Having assumed that this part of liquid was previously preheat, it imposes that the same quantity is preheat during this time from the ambient, around 10°C, to the boiling temperature, 99°C that corresponds approximately to 2 kW.

This flux is distributed inside the liquid that generates the creation of the thermal gradient.

Then, the liquid temperature evolution is governs by the equation for energy conservation that can be written, for such a pool fire geometric configuration [START_REF]Heat transfer mechanisms and boilover in burning oil-water systems[END_REF] :

) exp( ) ( kz q C k z T V z T z t T r p a - + ∂ ∂ + ∂ ∂ ∂ ∂ = ∂ ∂ ρ α (1)
where T is the temperature, t, the time, z, the vertical position, α, thermal diffusivity, V a , regression velocity, k, radiative absorption coefficient, r, the density, C p , specific heat and q r the incident radiative flux. Solving this equation will enable determining the temperature evolution at the bottom of the pool.

In the a first approach, the steady thermal gradient thickness can be determined. Considering that this gradient is steady and moves with the regression velocity, i.e. a virtual z is attached with the liquid surface; it is possible to simplify this:

z T V kz q C k z T z a r p ∂ ∂ + - = ∂ ∂ ∂ ∂ ) exp( ) ( ρ α (2) ) ( ) exp( 1 z T V kz q C z T a r p + - - = ∂ ∂ α ρ (3)
This theoretical basis will be used to develop a model to predict liquid fuel behaviour.

A First Decrease -Phase III

As mentioned above, a surprising decrease is observed in the middle of the heat release rate evolution curve. Considering that the fire is linked to both combustible and oxidant, it is legitimate to wonder about those two aspects: a modification of the heat exchange equilibrium or a transition to a ventilation control fire. Those two ways are developed and experimental validation configurations are proposed for each one.

(1) Fire controlled by heat exchange?

The first reason that can be developed concerns the fire itself or, more precisely, the heat exchange equilibrium between the fuel and the air. A rate decrease means that the evaporation fuel rate is diminishing which signifies that, one part of the energy is lost by the fuel due to a modification of the thermal exchanges equilibrium. Considering that this heat release reduction occurs just before the liquid reached its boiling temperature at the bottom of the pool, it is relevant to wonder about the heat transfer between the fuel and the surrounding air in this phase. To have a better understanding of these exchanges, photography of the experimental set up and a scheme of this installation are reproduced on Fig. 7. The heat exchange between the air flow under the pool and the liquid, or more precisely the steel at the bottom of the pool, is a convective exchange that can be written as follow, equation (2).

2 air d ( )d d p Q h T T S t = - ( 4
)
where d²Q is the heat quantity that go through the surface element dS during dt. T p and T air are respectively the steel and the air temperature. This equation shows that increasing the steel temperature will induce a heat exchange increase. To highlight this, the parallel evolution of bottom pool temperature and heat release rate is given on Fig. 8.

This figure clearly shows the quick increase of the temperature at the bottom of the pool due to the temperature gradient propagation inside the liquid. Consequently, this induces an increase of the heat exchange with the ambient air that flows under the pool and can consequently generate a decrease of the evaporation rate.

To check whether the heat exchange equilibrium modification influences the heat release or not, this experiment was achieved with insulation at the pool bottom, Fig. 9.

This figure shows that, for such a configuration, heat exchange are not possible at the bottom of the pool between incident air and the liquid. Then, the heat release rate for such a configuration was plotted on Fig. 10.

This figure clearly shows that introducing insulation at the bottom of the pool does not modify the heat release curve, including the heat release decrease that is kept for such a configuration. Such a result enables to reject the theory based on a modification of the heat exchanges. To evaluate the oxygen lack on the control of the fire, it is first necessary to consider the ideal reaction for heptane written as follow:

C 7 H 16 + 11 (O 2 +3.773 N 2 ) -> 7 CO 2 + 8 H 2 O + 41.5 N 2 (5) This equation shows that, in ideal conditions, 11 moles of oxygen, i.e. 0,352 kg, are required to burn 1 mole of heptane, 0.100 kg.

Considering the ideal value for specific heat of heptane at 44.6 MJ/kg, this implies that a 500 kW fire corresponds to an heptane consumption rate of 0,011 kg/s and consequently requires 0.04 kg/s of oxygen. This corresponds to an air flow of 0.2 kg/s to feed the fire. The forced ventilation in the fire galley is of about 6.5 kg/s for the whole 5.4 m² of the section of the fire gallery. Of course not all this air feed the fire but considering that the flame is located in the middle of the section, most of this air may be used. This course, will be discussed. It important however to consider the restriction due to the smoke layer than can reduced oxygen concentration by mixing with smoke, Fig. 11.

Fig. 11 Photography of the pool fire with the backlayering layer

To validate this, the fire was located at the entrance of the fire gallery to minimise the impact of the smoke layer. This experiment was achieved to minimise the influence of the backlayering layer on the fire. Consequently, its objective was to validate or not the theory based on the ventilation control. The heat release evolution obtained with this configuration is plotted on Fig. 12.

This curve was obtained for a regulated fire; i.e. with water circulation at the bottom. This last curve shows that diminishing the effect of the backlayering induces an elimination of the phase confirm the second developed approach that means a heat release controlled by the lack of oxygen.

A Rapid Increase -Phase IV

As discussed in the introduction of this paragraph, this rapid increase corresponds to the end of liquid preheat inside the pool. At the beginning of this phase, all the liquid is at the boiling temperature and all the energy received from the flame is used for heptane evaporation. Consequently, the gaseous fuel production increases and leads to an important rise in the heat release rate. Then this phenomenon is self sustained till a new equilibrium to be reached. This is shown on Fig. 8.

Of course, such a configuration must be fuel dependant. To evaluate this, an alcohol pool fire was achieved.

Properties of alcohol must be first compared with heptane ones. The boiling temperature is lower for alcohol with 79°C and the vaporisation enthalpy of 855 kJ/kg is higher. The heat of combustion for alcohol is only 28 MJ/kg [2] . Then, a 0.25 m² pool fire was achieved in exactly the same experimental conditions than heptane. The heat release rate evolution along time is plotted on Fig. 13.

This curve shows explicitly differences with the heptane one. On this evolution, it appears the heat release rate to be constant along time on a very long period, longer than one hour. So, considering this heat release evolution, it is legitimate to wonder about the liquid temperature evolution inside the pool, Fig. 14. According the explanation developed in the previous paragraph, the temperature at the bottom of the pool stays lower than the boiling one. curve clearly shows that the liquid temperature at the bottom does not reach the boiling temperature. Consequently, as discussed previously, the fire runaway cannot occur, which is demonstrated on Fig. 13. This curve also shows that the heat propagation inside the liquid is limited for this product.

This fire seems indicating that there exists a criterion, based on some liquid properties as mainly heat of combustion, vaporisation energy, thermal conductivity and boiling temperature that governs the fire as mentioned by [7]. These properties are linked, not only with the combustion velocity, but with the transition to a runaway phase too.

To go any further, it is of course interesting to achieve a fire with a heat sink to prevent from boiling at the bottom of the pool.

So, the second test case consists in a heptane pool fire with a heat sink at the bottom of the pool. A water cooling circuit was introduced at the bottom of the pool to prevent the liquid reaching its boiling temperature at the bottom of the pool. This method leads to the elimination of the runaway of the heat release, Fig. 15. Compared with the initial fire curve, Fig. 3, the runaway phase was replaced with a constant heat release phase. However, it can be noticed on this curve that the decaying period is still observed. It is however legitimate to wonder about the impact of the regulation system on this decaying period. A reduction of the regulation temperature should enable to maintain a constant heat release.

A Slow Decrease -Phase V and VI

After a short stability period at its maximum, some seconds, the heat release rate starts decreasing slowly. This short stability period signifies that the heat release run away is not a stable situation and the required energy to maintain it is higher than the energy received from the flame. Consequently, the energy received is used for evaporating a certain quantity of liquid lower than the required one to produce energy enough to evaporate this quantity. Consequently, the energy release by the fire is diminishing. On top of that, it is relevant to wonder about the combustion properties. Because of the fuel evaporation rising, the combustion will be modified and should become richer with the associated efficiency reduction and the increase of soot production. Of course those two phenomena will act simultaneously during this decrease phase.

It is important to note that this decrease phase follow a t² decreasing law with an asymptote with a value that correspond to the initial steady phase heat release.

Synthesis

This experimental sequence of four configurations has enabled not only to understand the different phases but to reach a configuration of constant fire as described by the theory. First, it was shown that, as mentioned by [START_REF] Chivas | Method to obtain large scale burning rate of liquids with lab scale tests[END_REF] , physical behaviour of the fire is linked with heat of combustion, vaporisation energy and boiling temperature. Second, for a given fuel with an important enough heat of combustion that can leads to a runaway, it is possible to obtain a constant heat release with some adaptations. The first consists in introducing a heat well at the bottom of the pool and in ensuring a sufficient air feed to the fire.

Conclusions and Perspectives

This paper refers to liquid pool fire in confined spaces and their impact. It was first shown that, such a confined pool fire does not behave as theoretical predictions. . It must be first noticed that the first steady heat release value is close to the theoretical one but while three phases are waited, six can be distinguished including a runaway that induces the heat release to be doubled. Of course, this can have a major impact not only on the design checking but on consequences predictions too. On top of this runaway, a first decrease phase was observed just before this runaway. Those two phases are not classical and an explanation was proposed on the basis of temperature measurement inside the liquid.

Concerning the runaway, the explanation is based on the thermal exchanges equilibrium. When the whole liquid reach the boiling temperature, the evaporation rate increase rapidly because energy no more diffuses inside the liquid. That means that all the energy received by the fuel is used to generate vapour. This phase is however not a stable one and, just after this quick increase, a t² decrease is observed and the heat release tends to reduce to the theoretical value. Several reasons are proposed to explain this reduction based on heat exchanges equilibrium or on the combustion properties. Two reasons can explain the decrease phases; the first is based on heat exchanges while the second is based on a combustion control by the ventilation. Experiments were achieved to evaluate both configurations and show that this phase seems due to a transition from fuel control to ventilation control. Because the creation of a backlayering smoke layer, the air feed to the fire is reduced and consequently, the heat release is diminished.

In the last part of this paper, several experimental configurations are proposed for evaluate the explanation. The alcohol pool fire shows that the fire behaviour, not only in terms of combustion rate as proposed previously [START_REF] Chivas | Method to obtain large scale burning rate of liquids with lab scale tests[END_REF] but in terms of thermal gradient inside the liquid too. Considering that this gradient governs the runaway, such a correlation should be used to predict whether or not such a phenomena can occur.

This work was mainly based on experimental confined fires and cannot be generalised to all pool fires. This work must be extended to atmospheric fire in which thermal exchanges are quite different. The comparison between those two configurations of long fire will leads to a better understanding of this phenomena. On top of that, these experimental results will be coupled with numerical simulation to provide more information about the fire behaviour.

Finally, on the basis of the theoretical evolution of temperature inside the liquid, a model will be developed to predict liquid fuel behaviour. This model will be validated on the basis of the numerous experimental data available in INERIS. This model will mainly be based on the product characteristics, latent heat, vapour pressure as a function of temperature, heat of combustion and thermal conductivity in the liquid. The last will be used to predict thermal gradient while other will enable to have estimation of the combustion rate for a given fuel.

Fig. 1 .Fig. 1

 11 Fig. 1. The objective of this series of experiments was to understand long pool fire behaviour. Pool fire behaviour was experimentally studied but experiments are generally short pool fire, less than 10 minutes. The objective of the present campaign was to study more

Fig. 2

 2 Fig. 2 Theoretical heat release curve for heptane pool fire

Fig. 3

 3 Fig. 3 Evolution of the power of a free heptane pool fire

Fig. 6

 6 Fig. 6 Temperature evolution for the two thermocouples in the liquid

Fig. 7

 7 Fig. 7 Photography (left) and scheme (right) of the experimental set-up for fire

Fig. 8 Fig. 10

 810 Fig. 8 Comparative evolution of heat release rate and temperature at the bottom of the pool

Fig. 12

 12 Fig. 12 Heat release rate for a fire at the entrance of the gallery.

Fig. 14

 14 Fig.13 Heat release rate for an alcohol 0.25 m² pool fire

  Fig. 15 Heat release rate a regulated heptane pool fire This figure lets appear 5 phases: I. Initial fire growth period, II. Steady power release phase, III. Power decaying period, IV. Second steady state, V. Power diminishing.