Guy Marlair

) Jean-Pierre

Sylvain

USE OF THE ASTM E 2058 FIRE PROPAGATION APPARATUS FOR THE EVALUATION OF UNDER-VENTILATED FIRES

 and Tewarson apparatus in Europe ' 3 is a polyvalent fire calorimeter that was recently described in its updated version in ASTM E 2058, under the name of Fire Propagation Apparatus (FPA). This paper deals with the use of such a fire calorimeter implemented by INERIS in year 1997, and which has now been used for both research and services to private customers, in a routine manner since 1998. The paper focuses on the experience achieved so far by the Institute with this apparatus for the detailed characterization of ventilation controlled fires of industrial products that are likely to govern the accidental fire scenarios in fire resistant enclosures. Such hazardous confined spaces can be frequently encountered in industry and transportation infrastructures.

In particular, relevant testing procedures and potential technical problems are discussed based on inlet air flow restriction or use of oxidizing flows diluted by nitrogen or carbon dioxide. Results regarding under-ventilated fires of a variety of products not belonging to polymers are presented to illustrate the capability of the apparatus to qualify such types of fires. Eventually, the ability of the equipment to provide detailed characterization of the fire chemistry of the combustion gases and related influence of ventilation rate, using specific additional sampling and chemical analysis is pointed out through examples.

INTRODUCTION

It is well known that ventilation controlled fires may result from accidental fire scenarios occurring in conventional buildings devoted to Public assembly. In such fires involving building materials or pieces of furniture, lack of oxygen and CO poisoning are considered the main chemical threats liable to cause escape impairment or fire deaths. Such types of fires may also occur in other particular enclosures that can be found in industrial premises (e.g. fire resistant warehouses used for the storage of dangerous goods) or underground infrastructures used for transportation (e.g. road and rail traffic tunnels, subways). In those environments, the description of related physical hazards is less well known. In particular, due to the presence of hetero-atoms in the hydrocarbon cores of combustible products, or due to potential thermal decomposition of mineral materials in the case of fires, the toxicity of those fires is more complex to evaluate than for conventional fires.

The original FMRC lab-scale flammability apparatus belongs to the family of fire calorimeters (like the cone calorimeter, or the OSU apparatus). The equipment, now known as the Fire Propagation Apparatus in ASTM E 20584 and also in the new NFPA code # 287 s , has been in continuous use for more than two decades in the USA to study the flammability parameters of polymers in various application contexts 6 ' 7 . The ability of the equipment to study the effect of under-ventilation on the combusiion of natural and synthetic polymers, at lab-scale, was pioneered by the inventor of the equipment as early as 1993 [START_REF] Tewarson | Ventilation controlled Combustion of Polymers[END_REF] . In Europe and more precisely in France, the advantages presented by this equipment to learn about the fire behavior of chemicals and electrical components were recognized very early after its design, as reported by Marlair and co-authors in Poitiers [START_REF] Marlair | On Going Experimental Fire Research and Testing in France using Test Rigs Derived from the 'Tewarson Apparatus[END_REF] .

Initiated from the European programmes MISTRAL [START_REF] Malet | Main results of the MISTRAL programme. Application to real accident cases and R&D needs for the safety of industrial facilities[END_REF] , INERIS federated new collaborations between French early users of the equipment (namely Rhône-Poulenc, LCEE, EdF) and FM Global. The Institute decided to complete its large-scale testing facilities [START_REF] Marlair | Experimental Approach of the Fire Hazard in Closed Spaces : Laboratory and Fullscale Tests[END_REF] by implementing in its turn a lab-scale fire calorimeter meeting latest design of the American FPA. The work was carried out in tight collaboration with the research division of FM Global at the origin of the concept. As a result, INERIS commissioned its own fire calorimeter end of 1997, which shall now be considered as the most modern equipment that meets all requirements of new standards previously mentioned. The Institute is now exploring 'non conventional' use of the apparatus in Europe. The INERJS calorimeter was built with the leading goal of supporting needed research in relation with industrial safety on behalf of and with the financial support of the French Ministry of the Environment. Currently, the equipment is considered as a key tool for evaluating the overall consequences of ventilation controlled industrial fires.

THE INERIS FIRE CALORIMETER

Presentation of the apparatus

To take profit of recent developments carried out by FMRC, INERIS made up its mind to adopt for its lab-scale equipment all essential technical features of the equipment now described as Fire Propagation Apparatus as described in current versions of the above mentioned American standards. The modified version of the Tewarson apparatus operated by Rhône-Poulenc (now split intoAventis and Rho did) was also examined, in terms of selection of additional measuring equipment.

Figure 1 : view ofthe INERIS FPA and associated control board

Figure 1 shows a picture ofthe INERJS calorimeter implemented in a purpose-built section of INERIS reaction to fire laboratory. The INERIS FPA is a carbon copy ofthe apparatus as described in ASTM E 2058. In particular, the INERIS calorimeter strictly follows the requirements ofthe standard for : the overall sizing of lower and upper parts ofthe system, the design and operation of external heat flux provider, -the fundamental basic measurements capabilities, including on-line gas analysis devices allowing accurate fire calorimetry measurements based on carbon dioxide generation (CDG) or oxygen consumption (OC) principles (see for instance paper of Janssens [START_REF] Janssens | Fire calorimetry[END_REF] for basic information on those techniques).

Additional features enlarging the domain of use and measuring capabilities of lNERIS FPA

In addition to technical features resulting from strict application of ASTM E 2058, INERIS has fitted its FPA with further components and complementary measuring equipment that have strictly no impact on routine use of the apparatus as shown by recent round robin tests on polymer samples 13 (e.g. approvals of materials according to FM standard requirements). Since a basic requirement for INERIS was the ability of using the apparatus to study the fire behavior of potentially toxic products, a key safety issue regarding staff security was considered, in relation with potential accidental release (very unlikely to happen !) of toxic smoke in the lab. This led to the integration of an optional system at the hood level which, when used, ensures the dilution step of the combustion gases in an air tight manifold using ambient air from outside the lab. In practice, the safety components provide the alternative possibility of using the equipment in the so-called closed mode.

DEVELOPING PROCEDURES FOR TESTING CHEMICALS BURNING IN FUEL RICH CONDITIONS General

A key advantage of the FPA in the field comes directly from the original design. Indeed, the quartz tube that creates a physical delimitation of the combustion zone allows perfect control of the global air-to-fuel ratio in any combustion test. Moreover, it also provides a perfect observation of the flame structure and relevant visual effects of under-ventilation.

This allows the user to adjust the fire ventilation of the test in terms of fuel enrichment of the combustion process. This is done in practice quantitatively through the measurement of the parameter called the equivalence ratio <j ) (actual fuel-to air ratio normalized by the stoichiometric value of same ratio) commonly adopted by fire scientists to report on ventilation control [START_REF] Pitts | The Global Equivalence Ratio Concept and the Formation Mechanisms of Carbon Monoxide in Enclosures Fires[END_REF] . In any experiment, the equivalence ratio may be targeted at any desired level to feature well ventilated or under-ventilated fire conditions, simply by varying the air inlet flowrate. However, some cautions are needed when very low air flowrates are considered, due to technical limitations of the procedure in terms of flow patterns, related pressure profiles inside the quartz tube and air tightness at the level of the quartz junction with the bottom part of the system. Furthermore, theoretical considerations not developed here for reasons of size restraint shall be regarded to select the proper calorimetry laws that will lead to an accurate diagnostic of thermal fire parameters (rate of heat release, overall combustion efficiency, etc) regardless of the ventilation rate, in all cases. The reader is referred to other publications 1 5' [START_REF] Brohez | The Measurement of Heat Release from Oxygen Consumption in Sooty Fires[END_REF] ' [START_REF] Lônnemark | TOXFIRE -Fire characteristics and smoke gas analyses in underventilated large-scale combustion experiments .Theoretical Background and Calculations[END_REF] to learn more on this aspect

Procedure relying on the restriction of combustion air supply

From the fundamental reason explained above, fire ventilation conditions can be first adjusted by acting on the air co-flow inlet rate. This is the easiest way to overview how the burning behavior can be affected by a reduction in air supply at the level of the combustion zone. In practice, the procedure was explored by INERIS using a series of different chemicals (such as heptane, adiponitrile (C$H8N2), atrazine (CgHnClNs), pyridine, isoproturon (Cj2Hi g N 2 O), toluene diisocyanate (TDI : C6H9O2N2), PMMA, thiophene, 1-chlorobutane) selected according to different technical or economic criteria. Figure 3 illustrates this routine procedure applied for a common liquid (heptane) and a solid powder named isoproturon, in terms of CO yields. Two things are worth mentioning about the use of this technique. First, reducing the air inlet flow leads to ventilation controlled conditions (when fuel rich conditions start to prevail) that tends globally to reduce the mean combustion rate, if any counter-measure is taken, such as an increasing value of the applied external heat flux or an increased size of material sample. Secondly, when external heat flux is applied, time-varying conditions are generally observed in terms of measured parameters in a single test, including the equivalence ratio itself, as far as the experimental fire goes on. This is attributed to transient heating processes and related heat loss responses and requires that the rough data obtained in a single experiment be reprocessed systematically for the analysis of results according to the actual time-related equivalence ratio. Globally, using this technique, it must be stressed that 4 to 8 single runs, depending on the chemical tested, are generally enough to cover the full spectrum of ventilation conditions equivalent to a range of equivalence ratios between 0,2 and 3 or more. During the commissioning period of the equipment INERIS identified conditions requiring a careful control of oxygen flows to determine the true equivalence ratio pertaining to one test when very low air flowrate is adjusted. In such a case, it may happen that Û2 consumed as taken from heat release data reveals to be more important than air supply available by normal air distribution system in the bottom part of the FPA. Figure 4 illustrates such a situation in the case of heptane, a highly flammable hydrocarbon where a control of the actual oxygen consumption by the fire process reveals that an extra supply of air other than normal inlet flow occurred in that experiment. Such a case shall lead the user to correct the apparent <f > factor by integrating in some way the additional oxygen which was artificially made available for combustion. Indeed, afterburning of test products beyond the combustion was recently reported by users of a modified cone calorimeter, which led them to correct the equivalence ratio values in that way [START_REF] Hietaniemi | Burning characteristics of Selected Substances : Production of Heat, Smoke, and Chemical Species[END_REF] . Our experience is that with the FPA, very flammable products (like heptane) may lead to visible afterburning outside the quartz tube only if overly high external heat fluxes or overly large samples are used. Besides, two other different ways of possible unexpected additional air interactions have been identified by INERIS. One is linked to a tightness performance at the junction of the quartz tube to its bottom support that may be rendered partially ineffective when very low air flowrates are used. This may be corrected by conventional ways of reinforcing air-tightness (use of adhesive aluminum paper) and monitored through pressure drop measurements between ambient air and the inner part of the quartz tube. The second possible unexpected entrance of air, which is less easily detectable, is located at the top of the quartz tube, where some air may enter in opposite direction of main gas flow close to the inner walls of the quartz tube (convective movement induced by cold wall effect). As a result of open discussions between users 19 , it was found that same analysis led to the same technical solution consisting in putting an orifice plate made of mineral material at the top of the quartz tube, when such a situation is expected. This procedure proves to be a good solution as shown by comparison of the graphs plotted in figure 4. The figure shows the time evolution of oxygen mass flow rates in heptane burn tests on a comparative basis (before use of the technical countermeasure basei on the use of an orifice plate above the quartz tube, on the left hand site-and after use of it, on the right hand side). The comparison clearly shows that using such a component to prevent any counter flow of air from the top part of the quartz tube is efficient. The curve shows that the actual oxygen consumption derived from the oxygen mass balance is i. this configuration consistent with air availability by the inlet flow all over the test duration.

Procedure simulating air vitiated conditions

Fuel rich conditions characterizing steady under-ventilated fires may either result from simple air access limitation to the combustion zone in a similar way that the testing procedure mentioned above, or alternatively result from air vitiation, that is to say from recirculation in a given enclosure of air progressively vitiated by the combustion gases. Such a situation can also be very easily investigated by use of the standard FPA apparatus, as the oxidizing flow may be adjusted according to operator's requirement, by use of a combination of different mass flowmeters connected to normal air, 62, orN2.

A first series of tests was thus performed with pyridine (CsH5N) as the burning material, and inlet flows of air progressively diluted with N 2 and with COa as the oxidising stream. It must be pointed out that only free burn conditions up to the transition conditions leading to ventilation controlled fires have been explored so far in such a manner. During the whole experimental program using pyridine as a fuel, external heat flux of 15 kW/m2 was applied only until ignition of fuel vapor occurred, than stopped. A constant inlet flowrate of some 250 Nl/min was set. It was observed that yields of CO were clearly dependent of oxygen molar fractions in the inlet flow stream, regardless the global burning mode in terms of ventilation rate. Besides, vitiation of air clearly diminishes the combustion rate. As the oxygen concentration is decreased from 21 % to a value near the extinction limit of the fire, the fuel mass loss rate decreases by a factor of about 2.5 from 21 g.m" .s" 1 to about 8 g.m^.s" 1 (see figure 5). The fuel mass loss rate decreases slightly more rapidly when CÛ2 is used as diluent. In both cases, the relationship between mass loss rate and Û2 concentration in the oxidising flow is clearly linear.

20

Figure 6: normalized mass Iocs rate of pvridine versus O-> concentration (% vol)

This observation is consistent with experimental results published by Tewarson et al. [START_REF] Tewarson | The Influence of Oxygen Concentration on Fuel Parameters for Fire Modeling[END_REF] , Santo et al. [START_REF] Santo | Influence of Oxygen Depletion on the Radiative Properties of PMMA Flames[END_REF] and Mulholland et al. [START_REF] Mulholland | The Effect of Oxygen Concentration on CO and Smoke Produced by Flames[END_REF] (e.g. PMMA, 15kW.m" 2 ). More recently, Nikitin [START_REF] Nikitin | Variations of Mass Combustion Rate with Oxygen Concentration and Gas Pressure of a Milieu[END_REF] also deduced from theoretical considerations that the fuel mass loss rate is directly proportional to oxygen concentration. In figure 6, normalized fuel mass loss rate (which is defined here as the ratio of fuel mass loss rate to the fuel mass loss rate in normal air) is plotted as function of Û2 concentration. The correlation proposed by Peatross and Beyler [START_REF] Peatross | Ventilation Effects on Compartment Fire Characterization[END_REF] is also plotted. As can be seen, there is good agreement between our results and the proposed correlation.

Another series of tests was carried out using diluted flows of air at a fairly constant equivalence ratio of 1.06 (transition regime) that allows comparison in terms of yields of CO and soot with results obtained for the well ventilated regime (0.1 < <j >< 0.25) . To make the comparison more instructive, we have plotted the CO yield versus the 02 concentration for well-ventilated and ventilated controlled (transition regime) conditions using non dimensional values (see figure 7). Here a normalized value is used by dividing the respective effective yields of CO by their values for normal air conditions (O2 =21%). It must be noticed that CO yields of 0.02 g/g, (respectively 0.09 g/g) were obtained in pyridine burn tests for < } > values of 0.2 (respectively 1.06) for normal air conditions (oxidizing flow having 21% of O2). It may be seen that the resulting curves look more or less identical.

The same observation can be made with the soot yields (see figure 8). We assume that the reason is O2 depletion in the oxidizing flow and global air inlet flow limitation act as independent variables on the variation in the combustion product releases. Indeed, both air limitation and air vitiation may effect the product yields in a cumulative way. Thus, both parameters should probably be taken into account in order to accurately predict fire gas composition produced by ventilation controlled fires in enclosures, as assumed from some experiments conducted at a larger scale on pyridine by the authors [START_REF] Brohez | A zone model for predicting the burning rate of liquid pool fires, and gas temperatures and composition in forced ventilated enclosures[END_REF] .

SOME FINDINGS REGARDING THE FIRE BEHAVIOUR OF TEST PRODUCTS IN FUEL RICH CONDITIONS

General observations

For all the materials that were used in this study, all general trends are similar and are in fairly good agreement with the work carried out in the field by previous workers. As far as the equivalence ratio increases, the following combustion product releases systematically increase : CO, TUHC (total unburnt hydrocarbons), soot, cyanhydric acid (HCN), for N-containing fuels. By contrast, CO: but also (where relevant), NO and NO:, SO: yields generally decrease.

Following the data processing procedure proposed by Tewarson et al [START_REF] Tewarson | Ventilation controlled Combustion of Polymers[END_REF] to relate ventilation controlled fire properties to those applying for well-ventilated conditions in the case of polymers using generalized relationships of the form indicated by equation ( 1), _ 1+ (1) with / fire property valid for any ventilation rate determined by the equivalence ratio value ($) ,/. , the same fire property applying for well ventilated fires (<| > « 1), and a,P4 experimental correlation parameters.

we have examined the influence of the fire ventilation when industrial products other than polymers are dealt with. Our primary finding is that the use of such correlations is statistically consistent with the experimental data that we have collected on under-ventilated fires of TDI, pyridine, adiponitrile, isoproturon, heptane, and some other tested chemicals. A variety of thermal and chemical issues of those fires were indeed well described by this kind of relationship. Our results, like to some extent those recently obtained by Hietaniemi and co-workers [START_REF] Hietaniemi | Burning characteristics of Selected Substances : Production of Heat, Smoke, and Chemical Species[END_REF] thus show that the initial results obtained by Tewarson et al can be extrapolated to products other than solid polymers. As examples, table 2 gives the a, P and \ parameters of equation ( 1) derived from experimental data regression analysis relevant to chemical yields of products released by combustion of the commercially-important liquid chemical named toluene diisocyanate (known as TDI), whereas table 3 gives the practical values of the same parameters in the case of isoproturon, a heavy weight solid pesticide substance. As other examples, HCN (cyanhydric acid) and TUHC (Total unbumt Hydrocarbons) yields are presented in a graphical way, as a function of the equivalence ratio in figure 9 (respectively figure 10) for the solvent adiponitrile. The correlations obtained by least square fits using the form of equation ( 1) is also presented in these figures. It can be emphasized from the latter figures that the toxicant HCN can be increased by at least one order of magnitude as a result of ventilation control of the fires involving N-containing fuels. The increase of total unburnt hydrocarbons and soot can also be very significant. Therefore the analysis of fire toxicity for ventilation controlled fires requires careful evaluation especially when non conventional fuels with N-S-Cl-atoms in their structure are feeding the combustion processes.

Product

It is expected that generalized correlations of the type mentioned above obtained from tests on the FPA could be tabulated in the soon future to complete input data of new generation zone models aiming at calculating a compartment fire, and depicting the fire source in a more accurate way than through a simple heat release curve. Such an attempt was recently initiated by Brohez and co-workers and presented at the last international combustion symposium held in Edinburgh [START_REF] Brohez | A zone model for predicting the burning rate of liquid pool fires, and gas temperatures and composition in forced ventilated enclosures[END_REF] . A few experiments at a larger scale have however revealed that the prediction of outlet flows of combustion products (such as CO, TUHC) according to our model still gives values lower than those measured. This is thought to be a consequence of air vitiation, not yet taken into account in the zone model.

A further graphical illustration of the ventilation effect on heat and products releases acting in the opposite way compared with yields of products dealt with in previous graphs is presented in figures 11 and 12. Both graphs refer to the combustion of the product TDI.

EXPLORING CAPABILITY OF THE FPA TO PROVIDE MORE DETAILED INFORMATION ON THE CHEMISTRY OF VENTILATION CONTROLLED FIRES

Methodology

As sub-lethal concentrations of minor species produced by fires is of growing interest at the European level according to the precaution principle, INERIS started to explore the ability of the FPA to obtain more detailed information of the composition of fire gases through additional sampling techniques and a posteriori analysis in dedicated laboratories. Therefore, three chemicals were selected, i.e. pyridine (CsH5N), a ring compound containing one atom of nitrogen in the molecule, a chlorinated aliphatic hydrocarbon, chlorobutane (C4H9C1) and one ring hydrocarbon containing one atom of sulfur called thiophene (C4H4S). For the purpose of this specific study, additional gas sampling lines were implemented on the measuring section of the FPA, in order to identify unburned hydrocarbon species (using, according to relevant trapping techniques, either impingers, or vacuum flasks or dry adsorbant tubes).

Components with high molecular weight were preferably trapped on Carbotrap tubes as a first step of qualitative analysis. Identification of species found in the combustion gases was carried out by coupled Gas Chromatography (GC) and Mass Spectrometry (MS) from thermal desorption of Carkotrap tubes. In a second series of tests (after identification of products of interest), new experiments by use of activated carbon and silica gel tubes were carried out with the aim of performing some more quantitative analysis of major compounds identified in the first stage. Components of light molecular weight (HC < C 4 ) were preferably sampled using vacuum flask (volume = 0.3 1) and then analyzed quantitatively by gas chromatography.

Figure 13 : Global >'esponse oftotal unburnt hydrocarbons as given by the THC anah-erin the case ofthiophene,(\y.G[lr)&Btfi&te4ftt:çl

Complementary techniques were also used to analyze some additional species linked to the presence of hetero-atoms in the test molecules (e.g. NH* by ion exchange chromatography in the case of pyridine burn tests ; H2S by colorimetric method using méthylène blue in the case of thiophene burn tests. For each product selected, both well ventilated (<| > « 0.2) and ventilation controlled conditions ( <J> « 1.5) were considered in the experimental programme. Clearly, the sampling trains were monitored in order that samples be representative of the combustion zone, and not the preheating phase of the test, since the response, in terms ofTUHC may be totally different (see figure 13).

Results

Table 4 -respectively table 5-compare the substances clearly identified in the flue-gas from combustion of pyridine and thiophene, according to ventilation conditions prevailing in the experiments. Discrimination between well and low ventilation conditions, already possible from qualitative analysis, becomes very clear from information issued from quantitative analysis, not reported in detail here. For instance, light hydrocarbon (IC2) were found in quantities 10 times higher in the case of fuel rich test configuration compared to fuel lean configuration.

Well ventilatedfire

Ventilation controlledfire The results regarding the product chlorobutane also provide clear discrimination between wellventilated and ventilation controlled fire conditions. However, in comparison with pyridine or thiophene, a much larger number of chemical species were identified by CG/SM, including many chlorinated hydrocarbons in both well and under-ventilated conditions. Therefore, we plan to deal with the experiments carried out on three substances in a future paper allowing relevant development and making comparisons with related works undertaken recently in Europe by other researchers.

Eventually, another global result is very encouraging. The total amount of hydrocarbons product by product after the identification step and relevant detailed chemical analysis procedure performed for all the three test chemicals (pyridine, thiophene and chlorobutane) leads to fairly good consistency with the value of the total hydrocarbon value derived from on-line measurements. Moreover, relevancy of the equipment to measure dioxins and furanesfrom industrial fires was also verified in the recent past by INERIS and Rhône-Poulenc laboratories 27 .

The authors intend in the near future to implement a FTIR instrument in addition to already existing on-line gas measurement devices, as this latter technique seems very promising, as outlined elsewhere in this conference. An evaluation step of such equipment is however planned to test relevancy for qualifying the chemical issues of well and under-ventilated fires in connection with the use of the FPA. This will be done in a new series of tests using the three above-mentioned chemicals for which we have obtained detailed information as reported in this section by conventional analytical techniques.

SUMMARY

The use of the FPA for the prediction of thermal and chemical impacts of fires when controlled by the ventilation is really pertinent, provided that careful control of testing procedures is ensured by the operator.

By design, the equipment allows easily manageable adequate procedures simulating ventilation control either resulting from simple lack of combustion air or recirculation of vitiated atmospheres. Both phenomena seem to act independently but can result in a cumulative effect for the case of unerventilated fires.

Generalized relationships proposed by Tewarson and co-workers to correlate ventilation controlled to well-ventilated fire parameters for polymers are extrapolable to other liquid or solid chemicals for a wide -ange of parameters including the yields of CO:, CO, TUHC, HCN, NOX, SOa and soot, with appropriate values of the parameters a, (3 and Ç. Those experimental coefficients can be determined by 4 to 8 single runs of the FPA fitted with relevant additional measuring equipment.

It can also be concluded that the FPA apparatus, fitted like ours with appropriate additional sampling and analytical techniques, is a useful tool to provide detailed information on the composition of the flue-gas for products burning in fire conditions.

Identification and/or quantification of minor species by CG/SM techniques in fire experiments carried out by use of the FPA also provide ways of further discrimination between well and under-ventilated fire, from the chemical point ofview.

LITERATURE

24 Figure 3

 243 Figure 3 yields of CO versus equivalence ratio determined by use of the INERISFPA using simple qir inletflow control : heptane (liquid-no external heat flux, left hand side} : isoproturon (use qfexternal heatflux, right hand side)

  figure 4 : heptane test burns presenting (left) actuql oxygen consumption by fire overwhelming the oxygen supply from bottom inlet flow : (right) : with oxygen consumption lower than bottom oxygen yupply qfteryse of an orifice plate serving cfs section restriçtor at top of quartz tube,

Figure 8 :Figure 7 :

 87 Figure 8: Ratio of soot yield to soot yield in ambient air as function of Oiconcentration . (pyridine asfuel. COi as diluent)

Figure 9 :

 9 Figure 9 : yield of HCN (g/g) as a function of equivalence rafio for adiponitrile

Figure 10 :

 10 Figure 10 : yield of TUHC (g/g) as a function of equivalence ratio for adiponitrile

Figure 11 :Figure 12 :

 1112 Figure 11 : overall thermal combustion Efficiency(°/ty versus equivalence ratiç for TDI

ppm/0-100 ppm 0-1000 ppm 0-10 ppm 70-100 ppm 0-1000 ppm

  By contrast to all conventional fire calorimeters which allow air dilution at the smoke collector in an open way, the INERIS calorimeter in the closed mode, introduces dilution air before the mixing duct by use of a lateral pipe connected to the toric distributor mounted at the base of the hood (see figure2). A movable cover fixed in closed mode at the bottom of the hood completes the system. It has a central hole letting the upper part of the quartz tube enter slightly into the conical section of the hood.

	Air dilution coming
	from outside the lab
		movable cover
		Quartz tube
	component	type of equipment	measuring range
	C0 2	NDIR analyzer MAHIAK model UNOR 610	0-0.3%adj.to0-6%
	CO	NDIR analyzer MAHIAK model UNOR 610	0-200 ppm adj. to
	uz	paramagnetic analyzer MAHIAK UNOR 610	0-4000ppm 0-25%
	NOx(NO,NO 2 ) THC	analyzer COSMA model TOPAZE 2020 (chemiluminescence analysis) analyzer COSMA model GRAPHITE 655 FID (flame ionization detector) discriminates methane from other HCs	0-10 0-10000 ppm
	H2O	two channel Rosemount IR analyzer model BINOS	0-20%
	SO 2	NDIR analyzer MAHATK model UNOR 610	0-200 ppm adj. to
			0-2000 ppm
	HCN	prototype two channels heated Rosemount IR analyzer &	0-500 ppm
		automatic titrimetry, using AgNO j (potentiometric principle)	detecting limit 1 ppm
	HC1	automatic titrimetry, using AgNO s (potentiometric principle)	detecting limit 1 ppm
	soot	optical measurements, use of 4 monochromatic wavelengths	(nd)
	TableI : on-line measuring devices implemented to the INERIS FPA,
	Standard characterization of fire gases and smoke composition by use of the INERIS FPA relies on the
	routine use of the set of on-line gas equipment listed in table 1. It is useful to notice that the additional
	instrumentation devices incorporated into the INERIS FPA provide a considerable enrichment of
	equipment compared to strict requirements from ASTM E2058.

Figure 2 : details of system allowing INERIS FPA to operate in the closed mode configuration

O N2 as dfluert (Equiv. Rjtio <U) • C02 as ffluent (Equiv. Rjt» = 0,2)

* C02 as diluent (Equiv. fade =1,06)

14 16 17 IS 02 Concentration (%) 20 21

	0
	Figure 5 : mass loss rate ofpyritfinc(g/m2/s)
	versus Q concentration (% vol

N2 as diluent (Equiv. Ratio = <U) • C02 as diluent

(Equiv. Ratio * (U) A C02 as diluent (

Equiv. Ratif ' %) -Correlation of Peatross and • • + • 16 17 IS 02 Concentration (%)

Table 2 :

 2 parametersfor TDI Table 3 : parameters for ISOPROTURON


Air Quality Department INERIS Jean Poulleau

INTERLABORATORY TESTS OF EMISSION MEASUREMENTS IN FRANCE USING A TESTING BENCH

It is well known that interlaboratory tests are a powerful tool to improve the quality of measurements. However they are difficult and costly to organise in the framework of emission measurements because of several reasons (too small measuring platforms, access to industrial plants...). In order to facilitate these tests, French authorities asked INERIS to built a testing bench, which could simulate industrial gaseous emissions of easily modified composition. The bench was originally designed mainly for having a constant concentration of gaseous pollutants (SO2, NO X , HC1, VOC). Work is in progress for semi-volatile pollutants injection. The bench is designed and equipped in such a way that five teams may work in parallel, which allows having statistical comparison. For the time being, it is mainly used for: validation of measurement methods before their standardisation proficiency testing for laboratories in view of their accreditation/approval A description of the bench and examples of results will be given.

INTRODUCTION

To be accredited, the laboratories which are involved in emission measurements have to provide the uncertainty attached to their measuring values. They can find some information in the most recent CEN standard, but they still do not know if they are implementing the standardised procedure properly unless they participate to interlaboratory campaigns. Thus, interlaboratory tests are a powerful tool to improve the quality of measurements. These campaigns are not so easy to organise on a plant and are expensive. Only very few teams can be simultaneously involved and the range of concentrations covered by one plant is quite often very narrow.

Therefore, in order to make these tests easier and more frequent, French authorities asked INERIS to design and build a testing bench, which could simulate varied industrial gaseous effluents.

The bench, which is a horizontal loop, was originally designed mainly for measuring concentrations of gaseous pollutants (SO2, NO X , HC1, VOC) but some studies are in progress for semi-volatile pollutants injection.

Up to now, six interlaboratory campaigns with French bodies and one with European laboratories have been organised, measuring O2, CO, SO2, NO X , H2O. Some interlaboratory campaigns are also under way for mercury and for PAH generated by a wood stove.

The bench is designed and equipped in such a way that five teams may work in parallel, which allows having statistical comparisons.

For the time being, it is mainly used for:

• validation of measurement methods before their standardisation • proficiency testing for laboratories in view of their accreditation/approval This presentation gives the main results and statistical evaluation of six campaigns for the determination of O 2 , SO 2 , NO X , CO, TOC and H 2 O.

PRESENTATION OF THE TESTING BENCH

A bench loop has been drawn up and built in 1998 in INERIS, which has the capacity to generate dynamically gaseous effluents from exhaust gases of a gas boiler or a fuel-oil boiler. These exhaust gases can be humidified and doped by pollutants coming from pure gases in cylinders: CO, CH 4 , NO, NO 2 , HC1 or liquids (specific VOC). Generated gases are injected into a stainless steel loop (150 mm internal diameter) coated with PTFE, where 300 kg/h gases are circulating. This horizontal loop is temperature controlled by mean of electric heating resistances. This bench is equipped to receive 5 different teams. Each team has at its disposal:

-a rectangular sampling port (100 x 400 mm) situated at 1.20 m height with the possibility to have 2 or 3 holes in it.

-electric supply (230V 16A) and compressed air (6-7 bars).

The static pressure inside the duct is maintained between 1 and 4 mmCE in order to avoid interferences from one team to the others.

Characteristics of exhaust gases can be quickly modified. Ten to fifteen minutes only are necessary to reach a new steady configuration.

THE PARTICIPANTS

THE TESTS

Tests performed between French laboratories were focusing on automatic measurements of O 2 (5-13%), CO 2 , CO (10 -500 mg/m 3 ), NO X (75 -1000 mg/m 3 ), SO 2 (40 -1000 mg/m 3 ) and COVT (0 -50 mgC/m 3 ). The choice of analytical techniques were left open.

For the European test performed for CEN standard validation purposes, the institutes had to use reference method in the following concentrations:

-SO 2 (0-2000 mg/m 3 ) Thorin and Ionic Chromatography Method -NO X (0-1300 mg/m 3 NO2 equiv.) Chemiluminescence -O2 (3 -12 %) Paramagnetism -CO (0-400 mg/m 3 ) Infra-Red Absorption

-H2O Absorption and condensation

For each campaign, 10 to 12 half-hour tests were carried out, mostly at steady concentrations. Furthermore, FNERIS has checked the calibration bottles of each participant with its own instruments.

RESULTS

CALIBRATION BOTTLES

The uncertainties attached to the concentration values, given by the manufacturer, are often small: +/-1 to 2% relative, even smaller in some cases.

To perform good measurements, we noticed that we could give the following advice: use a automatic instrument whose range corresponds approximately to twice the Emission Limit Value (ELV) and whose sensitivity may be adjusted with a calibration bottle whose concentration is approximately equal to the ELV.

For NO X , we have two possibilities:

To use one bottle with a mixture of NO and NO2. In that case we suppose that both channel (NO and NOx) give an equivalent signal when injecting NO (it isn't always true). And we must have also enough NO2 in NO in order to check the efficiency of the conversion oven.

to use two separate bottles, the first one with NO in order to adjust both NO and NO X channels, the second one with NO2 in order to calculate the efficiency of the conversion oven.

It's a pity to see some laboratories that have only a NO bottle and don't control NO2. Moreover some are measuring NO and add 5% to give NO X values! Even if the French standard and the new CEN Standard for TOC measurement demand to adjust the sensitivity of the FID with propane, half of French bodies still use methane. This can induce quite high deviations because the ratio of response factor between propane and methane is not always equal to 3 on every FID.

The comparison of calibration gases has been made on INERIS analysers who were previously adjusted. The linearity of these analysers has been previously checked according to internal quality assurance procedures. The results have been considered as abnormal when the deviation between the reading and the expected value was larger than the square root of the sum of the square value of the uncertainties given by the manufacturers.

We found that one fourth of the checks gave anomalies.

ANALYSERS ZERO AND SENSITIVITY ADJUSTMENTS AND CHECKS

The tests forecast an adjustment at the beginning of each day and a check at the end in order to detect possible zero and sensitivity drift.

Only a few laboratories, except the European bodies involved in CEN are correcting their values for drift when it is necessary. Some laboratories don't respect the warming time of their instruments, which induce a rather high drift in measurements.

MAIN RESULTS FOR EACH COMPONENT

For each component the average value obtained by the laboratories with the confidence interval attached to this average value has been calculated. This value gives an idea of the dispersion of results. (1) Ic : 95% confidence interval attached to the average results

(2) half an hour limit values given by the European directive on wastes

Table n°l : confidence intervals attached to the average results

This table shows that the results obtained during the European campaign with recognised bodies are much better than those obtained by common French labs.

Several explanations can be given:

For the same pollutant, all European labs implemented the same measurement principles, in this case: the reference method.

The recognised laboratories do perform the measurements with more expertise. They actually do know their instruments and have control procedures to follow their instruments up. Furthermore, they have a better knowledge of standards and regulation requirements. Leak tests of the sampling lines are generally done. Drifts are calculated and results are corrected when it is necessary.

The concentration ranges and the calibration gases are well adapted to the measuring task.

For the European tests, the test programme has been modified in order to calculate repeatability and reproducibility according to ISO 5725-2 procedure. The reproducibility confidence interval is quite useful because each laboratory, performing the same method, has the possibility to give an uncertainty attached to its results.

Table n°2: European interlaboratory tests results

This table shows that :

The uncertainty budget made according to ISO 14956 often lead to figures lower than those given by ISO 5725-T.SR approach. We should observe the opposite because this approach is supposed to sum up all the possible sources of uncertainty. Therefore, it shows that either all sources have not been taken into account or the estimation has not been correctly managed.

A factor 1.5 to 4 exists between repeatability and reproducibility, except for Thorin method where a factor 12 has been reached. This large dispersion may be due to the bad control of this rarely used method.

In the last column we see that we fulfil the uncertainty requirements of the European Directive on Waste. Half confidence interval requirements are: 10% for CO, 20% for SO 2 and NO X , and 30% for COVT.

OBSERVATIONS AND RECOMMENDATIONS

In conclusion, we can draw the following observations and recommendations:

Anomalies met with some calibration gases have a rather limited influence on deviations between labs, except for TOC, where propane has to be used for adjustment of the sensitivity. Deviation between laboratories are not always constant from one day to another, for the same level of concentrations, which seems to show that some labs carry untidy adjustments. We have to remind that it is better to inject calibration gases at the inlet of the sampling line, in order to take into account possible loses in the line, above all with SO2 or NO2, to check that the analyser gives the same signal on calibration mode and on measurement mode. Moreover, because final results are given by the recording system, it seems important to calibrate referring to data logging and recording system.

For some components, confidence intervals are rapidly increasing at low concentrations, because of a lack of sensitivity of the instrument, of cross interferents, of instrument adjustment (for FID), parameters whose influence on the results are known only when the performance characteristics have been previously determined. It would be useful for laboratories to have assessment or type approval reports from TUV, MCERTS, INERIS... If these reports are not available, laboratories will have to perform linearity check, calculation of quantification limit and so on according to ISO 9169. At last, it's quite easy, when adjusting the sensitivity of one analyser to inject the calibration gas not only to the analyser but also to all the others in order to detect possible interference.

A special attention has to be paid for SO2 measurements by an automatic instrument:

-By choosing the right gas treatment to get rid of moisture -By choosing the length and material of the sampling line (Viton will be banned) -In adjustment procedure (wait enough time to reach stability and if possible, inject in the inlet of the line) -In the choice of the analytical technique (we have to know interferents and instrument behaviour at low concentrations).

Some important deviations at low concentrations seem to be due to the choice of a too high concentration range and calibration gas (see the recommendation of calibration gases above)

These tests revealed erratic instruments functioning which have been sent back to manufacturers.

Dispersion of humidity measurements are rather high: the efficiency of the condensation should be checked and leak test performed before sampling.

• For TOC measurements, the uncertainties on the measurements are very large. The gas burner geometry and adjustments are influential parameters. Therefore it is essential to know the response factor of all commercial FID according to the CEN requirements even if CEN requirements seem unrealistic.

These interlaboratory campaigns had the advantage to reveal the state of the uncertainty at the level of reference level and at the level of common practice in one country. The participants have drawn a lot of information on their own practice and will improve the quality of their measurements.

But these exercises must be periodically repeated to follow the progress in the management of measurement procedures.

About the author

Jean Poulleau has many years experience working as a development engineer in the field of combustion techniques then in air pollution measurements: evaluation of the performance characteristics of gas analysers, stack sampling and analysis. He is strongly involved in standardisation activities, at the french, european and international levels. E-mail adress: jean.poulleau@ineris.fr

Table 1

 1 below gives the confidence intervals for the first five tests between common French bodies and the European test performed with what we can consider as recognised laboratories.

Table 2

 2 below gives the main results of the European campaign. We can find the results of different approaches to calculate the uncertainty of the measurement:

		Reproducibility confidence interval according to ISO 5725: t.S
			Confidence	Confidence	Repeatability	Reproducibility
		Concentration	Interval	Interval attached	Confidence	Confidence interval
				to the mean	interval
			ISO 14956		ISO 5725-2	ISO 5725-2
			2*u	t.s/vn	t.s r	ts R
			%rel	%rel	%rel	%rel
	O 2	3		1.1	0.8		1.7
	%	6		0.9	0.5		1.3
		9	2.9	0.8	0.4	0.3	1.3
		12		0.6			1.0
	CO	20		8.7	2.6	14.9
	mg/m 3	60		4	1.1	6.9
		100	2.5	2.1	0.8	3.6
		350		0.9	0.6		1.5
	NO	25		2.4	3.3	4.0
	mg/m 3	100	1.7	2.5	1.9	3.7
	as NO 2	450		2.8	1.5	4.2
		1300		3.6	1.4	5.1
	NO X	30		2.6	3.0	4.0
	mg/m J	100	1.7	1.4	1.9	2.3
	asNO 2	450		1.6	1.5	2.5
		1300		1.8	1.4	2.9
	SO 2 Thorin	20		19	3.0	36.8
	mg/m J	50		11	4.2	29.0
		200		10	4.8	13.3
		2000		9	5.0	17.3
	SO 2 IEC	20		27	27.6	38.9
	mg/m 3	50		21	12.0	26.2
		200		9.1	4.4	13.2
		2000		8.8	9.2	13.1
	H 2 O	8		12	8.5	17.7
	%	12		9	9.2	13.4
		14		10	9.6	14.1
		22		10	10.3	14.9

ISO 14956 approach: 2.u. It's a GUM approach, calculating the overall uncertainty from all the individual sources of uncertainty.

Confidence interval attached to the average result t.s/vn Repeatability confidence interval according to ISO 5725: t.s r .


Source location estimation using single three-component seismic station M. Abdul-wahed (1 ' 2) ; G. Senfaute (1) ; J. P. Piguet (1) .

(1) Institut National de l'Environnement Industriel et des Risques (INERIS) & Laboratoire Environnement, Géomécanique et Ouvrage (LAEGO), Ecole des Mines de Nancy. 54042 Nancy (2) CEA de Syrie, Damas B.P. 6091. Syrie ABSTRACT: An experimental microseismic monitoring system composed of one three component station has been set up overlying the last iron mine in France. This experiment consisted of recording the seismic signals corresponding to the localised underground roof fall following the blasting of some small pillars 300 meters deep. The a priori knowledge of the position sources allows the application and validation of the seismic wave rotation technique to estimate the position of the microseismic events recorded at a single three component station. The method used is based on the calculation of the covariance matrix in a time window. However the length of this window significantly affects the precision of the calculations. The method used involves a new approach in which the length of the time window was optimised on the basis of the dominant frequency in the seismic signal. This article describes the approach to optimise the convergence process between numerical results and geometrical field assessment of experiment.

INTRODUCTION

The technique of seismic wave rotation can be used to determine the direction of polarisation of the seismic signal, in other words to calculate azimuth and incidence angle of the signal emerging at a threecomponent seismic station. Thus, the technique is used to estimate the position of a seismic event recorded at a single measuring station. The location will of course be cruder than those achievable with data from several stations surrounding the sources. However the seismic wave rotation technique is a big interest for microseismic systems monitoring areas that are affected by dynamic instabilities, and which are often limited initially to a single seismic measuring station.

The aim of this study was to test and validate the technique of seismic wave rotation for estimating the location of the seismic source from one threecomponent seismic station in the particular encountered field conditions.

A number of wave rotation techniques -whether in time or frequency domains -have been developed [START_REF] Kanasewich | Time sequence analysis in geophysics[END_REF], Vidale 1986[START_REF] Magotra | Seismic event detection and source location using single station, three component seismic data[END_REF][START_REF] Jurkevics | Polarization analysis of three component array data[END_REF], Christofferson et al 1988[START_REF] Bataille | Polarization analysis of highfrequency, three-component seismic data[END_REF]. The method used in this study is based on calculating the covariance matrix in a given time window [START_REF]Signal analysis using rectilinearity and direction of particle motion[END_REF]. However the length of this window has a significant effect on the precision of the signal rotation [START_REF] Roberts | Realtime event detection, phase identification and source location estimation using single station three component seismic data[END_REF]. This problem was examined by [START_REF] Cichowicz | An automatic S-phase picker[END_REF] who proposed a new technique consisting in optimising the length of the time window on the basis of the dominant signal frequency.

In an experiment carried out in the last iron mine, the microseismic events from fracture and collapses caused deliberately at mine bottom were recorded using a single three-component station at the surface. Since the location of the seismic source was known, the data were used to validate the seismic wave rotation technique for estimating the location of the seismic source recorded by the single three-component seismic station. This article begins with a description of the experimental site, the microseismic monitoring system used, and the events recorded. We then give a summary of the literature on the wave rotation technique, a description of the microseismic events recorded during the experiment, and a sensitivity study of how different parameters influence the precision of the calculations. Finally we reach some conclusions about the validity of the technique and the prospects for its application.

PRESENTATION OF THE EXPERIMENT

monitoring station is a three-component station with sensors of the accelerometer type with pass band 2 to 2300 Hz and a sensitivity of 500 mV/g before post amplification. For signal acquisition a local computer was used with a sampling frequency of 8 kHz par channel (Figure 2).

The mine and the microseismic monitoring system

The microseismic monitoring technique was applied in an experiment carried out in the last working iron mine. The working method in these mines was to cut roadways to divide the deposit into panels, which were themselves cut into square or at least parallelepiped pillars with dimensions of the order of several metres. In the case of total extraction the size of these pillars was gradually reduced until they were finally blasted away with explosive. The experiment involved recording, at the surface, the microseismic events resulting from localised collapse deliberately caused at the mine bottom by destroying pillars with explosive [START_REF] Senfaute | Qualification of the microseismic monitoring technique applied to the risk of collapse in iron ore mines EUROCK[END_REF]. Figure 1 shows the position of the microseismic monitoring station and the working units where the pillars were removed. Three working units carried out the pillar removal operations during the period of microseismic monitoring: unit 57 was located about 300 metres away from the vertical line passing through the microseismic monitoring station, unit 55 at a distance of about 890 metres and unit 58 at about 1250 metres.

THE TERRE ROUGE MME

Microseismic events recorded during the experiment

During the experiment, 265 microseismic events were recorded. They were subdivided into three categories:

• class 1: events directly associated with blasting;

• class 2: events associated with immediate roof fractures, during the collapse process, class 3: events associated with rock fractures not connected with roof collapse.

The events in class 1 were identified by noting the precise time at which the shot was fired and were contemporaneous with the explosions. The events in class 2 are defined as concomitant with localised roof collapses (limited caving) consecutive to the blasting of the pillars. The third class of event corresponds to isolated incidents, i.e., those occurring at different times than those of shotfiring and roof collapse. The table 1 shows the distribution of events throughout the period of microseismic monitoring.

Microseismic events associated with blasting

From an initial spectral analysis of the recordings associated with the shotfiring it was possible to separate the blasting signals into two groups. One group of events was associated with shotfiring at unit 57. This unit at a distance of about 300 metres was the closest to the seismic station. The frequency band of these events is fairly broad, between 200 and 400 Hz (Figure 3). a)

V » & * l -1 i & : Z i > n < ] [ : i I -2 9 2 1 U 11, 1 • O J [P| » « ! • • a OJ L.
- The second group of signals concerns the events resulting from shotfiring by a unit farther away than the previous one. The dominant frequency in these signals is therefore lower than that of the previous events. The frequency band of the signals is between 50 and 200 Hz (Figure 4), typically due to physical attenuation.

The first set of 31 microseismic events associated with the shotfiring operations were then processed using the seismic wave rotation technique because the source location was known precisely, and the signal/noise ratio of the signals was very good.

PRESENTATION OF THE SEISMIC WAVE ROTATION TECHNIQUE

The wave rotation method proposed by [START_REF] Cichowicz | An automatic S-phase picker[END_REF] is based on the calculation of the covariance matrix in a given time window. According several authors, the length of the time window significantly affects the precision of the method used for rotating the signal. A link between the duration of the window and the errors committed has been demonstrated [START_REF] Roberts | Realtime event detection, phase identification and source location estimation using single station three component seismic data[END_REF]. The new approach proposed by [START_REF] Cichowicz | An automatic S-phase picker[END_REF] involves calculating the length of the time window on the basis of the dominant frequency in the seismic signal, which allows the different waves recorded to be processed separately.

According to [START_REF] Cichowicz | An automatic S-phase picker[END_REF], the length of the time window, denoted N fi i ter is given by the formula: Nfiltre =l/(f 0 . At) f 0 : dominant frequency At: sampling interval The method of [START_REF] Cichowicz | An automatic S-phase picker[END_REF] involves several steps:

In order to qualify the calculated angles, we determine the degree of rectangularity from the eigenvalues of the covariance matrix using the formula of [START_REF] Jurkevics | Polarization analysis of three component array data[END_REF]:

Rectangularity = 1-( (X 2 -X3) 12X\)
where X\, X 2 and A,3 are the eigenvalues of the covariance matrix. These eigenvalues are usually in the following order: X\>X 2 > X 3 . The degree of rectangularity is an important parameter that characterises the polarisation of the ground motion. It takes the value "1" if the ground motion is completely polarised or, in other words, linear. In this case the specific value X\ associated with the P wave is dominant.

• Preliminary analysis of the signal to calculate the dominant frequency, • Calculation of the covariance matrix during a time window of length Nfii ter , • Extraction of the parameters characterising the polarisation of the signal using eigenvalues and eigenvectors, • Rotation of the signal to produce the seismogram in the new frame of reference, • Pick up of the S wave arrival time.

The location of the microseismic events is estimated from the azimuth and incidence angle of the seismic signal.

These angles are determined from the eigenvector associated with the P wave using the following formulae: Azimuth = arctan incidence = arcos un : vertical component of the eigenvector associated with the P wave; U21 and U31: horizontal components of the eigenvector (figure 5).

APPLICATION OF THE SEISMIC WAVE ROTATION TECHNIQUE

Comparison between the azimuth and incidence angle calculated from the wave rotation technique and those measured at the known source location makes possible to test, to validate and to determine the precision of the technique in the field context.

Presentation of results

The seismic wave rotation were applied to the 31 selected microseismic events. Applying the rotation technique for each event allowed the determination of the angles (azimuth and incidence) of the seismic signal. These results were used to classify the events into two groups :

• group 1 : events with a mean azimuth N 81 ° and a standard deviation of 11.7°; a mean incidence of 54° and a standard deviation of 8.5°; • group 2: events with a mean azimuth N 110°a nd a standard deviation of 7.7°; a mean incidence of 27° and a standard deviation of 6.9°.

The calculations of azimuth and incidence angle assume that the wave is propagated following a straight line in a homogeneous, isotropic medium.

The two groups of events classified by the wave rotation technique correspond to the events resulting from the blasting operations by units 57 and 55 (see Figure 1). Table 2 shows the comparison of the expected theoretical angles (azimuth and incidence angels) and the mean values of the angles calculated using the wave rotation technique. he events in group 1 are clearly associated with the operations of unit 57 (see Figure 1). The shots fired from that unit are located some 300 metres from the seismic station at the surface. As a result, the error in locating these events is of the order of 30 metres in the vertical plane and 40 metres in the horizontal plane. This error is determined by converting the standard deviations of the angles (incidence and azimuth) into the distances. Finally, the estimated resultant error is of about 50 metres. Figure 5 shows the azimuth and incidence angle for all the events associated with the shots fired by unit 57.

The shots 12 and 13 (see Figure 6) show fairly large differences between the calculated and measured azimuth values. This error was due to substantial saturation of these signals. We observed that the strongest events that gave substantial saturation of the signals generated significant bias in the calculation of wave rotation.

The events in group 2 are associated with the shots fired by unit 55. This unit is located about 890 metres from the seismic station. As a result, the error made in locating the shots is of the order of 100 metres in the vertical plane and 115 metres in the horizontal plane. The resultant error is of the order of 150 metres. Figure 7 shows the variations in the calculated angles of azimuth and incidence for the events associated with the shots fired by unit 55.

Influence of the length of the time window

which the length of the time window is determined, and the precision of the angles of azimuth and incidents calculated by signal rotation. For the shots fired by unit 57, about 300 metres from the monitoring station, the events show a principal frequency band between 200 and 400 Hz (see Figure 3b).

We carried out a sensitivity study to determine the influence of the length of the time window on the precision of the calculated azimuth and incidence of the seismic signal. We showed that there is a relation between the dominant frequency in the signal, from

Figure 8 shows the variations in the angles of azimuth and incidence as a function of the frequency from which the length of the time window is calculated. Equation 1gives the relationship between the length of the time window and the dominant frequency. The results show that the precision of the calculated angles depends on the length of the time window and on the associated dominant frequency. The precision of the results is considerably worsened for frequencies above 600 Hz and below 200 Hz -entirely outside the frequency range of the events -are used (Figure 8). For the shots fired at unit 55, a mining unit that is farther from the seismic monitoring station than unit 57, the signals recorded show a predominant frequency between 50 and 200 Hz. Figure 8 shows an example of the variations in angles of azimuth and incidence as a function of frequency for the events associated with unit 55. The results show, as in the previous example, that above 500 Hz, which is completely outside the frequency range of the events, the precision of the calculations of azimuth and incidence is considerably degraded.

Consideration of unfavourable cases

Within the 31 microseismic events used in the wave rotation technique, 3 cases did not work out. Indeed, good precision of the calculation was not associated with the dominant frequency of the signals. For these cases, we noted that the signal was extremely complex and had several dominant frequencies. In addition, the precision of the calculation varies from one dominant frequency to another or is linked to none of them dominant. Figure 10 gives an example of an unfavourable case where the precision of the azimuth calculations is not related to any dominant frequency in the signal. Figure 10 : Unfavourable case in which the azimuth is not associated with the dominant frequencies..

CONCLUSIONS

The microseismic events recorded during shotfiring operations in an underground mine were used to implement and validate the seismic wave rotation technique for estimating the location of the microseismic events recorded by a three-component station at the surface. The application of the seismic wave rotation technique to the 31 seismic events recorded produced the following results :

1. The covariance matrix method [START_REF] Cichowicz | An automatic S-phase picker[END_REF] used in this study gives good precision in estimating the incidence and azimuth angles of the seismic signal emerging at a threecomponent seismic station.

2. By applying the wave rotation technique it was possible to distinguish between two principal groups of microseismic events associated with the shots: one group of events represents the azimuth and incidence angle of unit 57 and one group represents the azimuth and incidence angle of unit 55. These results were compared with expected theoretical azimuth and incidence values at the site which have been used to validate the application of the wave rotation technique in the specific field context.

The study permits to quantify the accuracy of the calculated azimuth and incidence angles related to the dominant frequency in the signal, from which the length of the time window used in the calculations is determined.

Figure 1 :Figure 2 :

 12 Figure 1 : Schematic delineation of the mining units and location of the microseismic monitoring station.

Figure 3 :

 3 Figure 3 : Typical microseismic signals: a) seismograms along the directions X, Y and Z; b) frequency spectra recorded during a shot fired 300 metres from the seismic station on the surface (unit 57).

Figure 4 :

 4 Figure 4 : Typical microseismic signals: a) seismograms along the directions X, Y and Z; b) frequency spectra recorded during a shot fired some 890 metres from the seismic station at the surface (unit 55).

Figure 5 :

 5 Figure 5 : Azimuth and incidence angle calculated from the eigenvector associated with the wave P.

Figure 6 :

 6 Figure 6 : Variations in incidence and azimuth of events associated with the shots fired by unit 57. The horizontal line shows the expected incidence and azimuth values.

Figure 7 :

 7 Figure 7 : Variations in the incidence and azimuth of the shots fired by unit 55. The horizontal line shows the expected incidence and azimuth values

Figure 8 :

 8 Figure 8 : Variations in azimuth and incidence as a function of frequency for the events at unit 55.

Figure 9 :

 9 Figure 9 : Variations in incidence and azimuth as a function of frequency for the events of unit 55

Table 1 :

 1 Classification of microseismic events recorded during the monitoring period

	Seismic events	Seismic events	Seismic events
	concomitant	concomitant with	recorded at times other
	with shotfiring	collapse	than those of roof
		phenomena	collapse and shotfiring
	31	66	168

ACKNOWLEDGEMENTS

The authors wish to express their thanks to the LORMINES and ARBED companies and the French Ministry for Industry for their financial contribution to this experiment. We should particularly like to thank the management and staff of ARBED's Terres Rouges mine for their support on the field.

BIBLIOGRAPHY


Yasser Elshayeb
email: yasser.elshayeb@ineris.fr

Samy Kouniali

Jean-Pierre Josien

Yves Gueniffey

Towards the determination of surface collapse type over abandoned mines in the Lorraine iron basin

Surface collapse is a major problem that follows many active or abandoned underground workings. Collapses result from roof deformation of underground workings, and/or controlled or uncontrolled rock caving. The uncontrolled rock caving could result in surface instability problem and loss of materials and/or human life. Over the past 90 years, and as result of underground-uncontrolled rock caving, 16 major accidents "surface collapse" has been reported in the French Lorraine iron basin. Some of these collapses were sudden and violent "happened over few minutes and up to few hours", led to loss of life in some cases, while others occurred progressively "within few days", with fewer effects on the surface environment. The sudden occurrence of these accidents is of big interest in order to be able to predict the risk induced by abandoned underground mines in this basin especially in areas where cities built and people live. The objective of this study is to try, with the aid of data analysis techniques, to define a criterion of rapidity of the accident where it is probable to occur according to the principal underground workings' geometry. This analysis was accomplished using Principal Component Analysis (PCA) and Discriminant Analysis (DA). With respect to the small number of accidents that had happened, we were able to define general criteria of the type of accident to be expected, using essentially the site's geotechnical and exploitation properties

INTRODUCTION

The French Lorraine's iron basin extends over 1500 square kilometers in the eastern part of France. Figure 1 shows a geographical situation map of the basin. The basin had been worked out since the 19 th and 20 th centuries. The method of exploitation consisted of rooms and pillars of various shapes followed by integral stooping.

In cases where the remained pillars were taken off, surface collapse occurred in a more or less controlled way, and in order to consider surface structures (houses, roads, infrastructure, etc.), the method of exploitation consisted of leaving in place "enough" amount of pillars (varying from 80% to 30%) in order to prevent uncontrolled collapse from occurring.

Unfortunately, the percentage of pillars left in place depended largely on the experience rather than depending on long-term stability analysis.

During the 20 l century, we were able to localize and report 16 accidents of unpredicted collapses in the basin. Eight of them happened in a sudden and brutal way and led in sometimes to loss of life, while others happened in a progressive way and led only to the destruction of houses and infrastructures.

The increased concern of regional authority led us to try to define for the basin (where geological situations are almost the same) a criterion of discrimination between situations (underground workings) where brutal collapse are likely to happen and others where progressive ones are to be expected.

In order to be able to define this criterion over the basin, we have started with a back-analysis over the 16 cases already happened and tried to draw any geological, geotechnical, or geometrical aspects.

Then with the results obtained from this back analysis, we performed a statistical data analysis taking into consideration all available information.

With the aid of techniques like Principal Components Analysis (PCA) and Discriminant Analysis (DA), we were able to define such criterion, but were very sensible to the number of individuals used (16 accidents). Tincelin (1959) pointed out that in order to expect a brutal collapse, three geological conditions have to take place. These three conditions are; 1. the existence of a hard rock seam at the roof of the extracted iron bed; 2. the existence of a hard rock seam near the surface; 3. and the existence of an adjacent valley. According to our geological study of the accidents' areas, we were not able to prove that these enterions are discriminant due to the fact that in many situations where progressive collapse happened, these three conditions were also present. This fact allowed us to say that there might be some geological conditions that could favour the existence of brutal collapse, but we cannot just rely only on these three conditions for an overall discrimination in the basin.

One of the major problems that we have faced in working out on the back analysis is that in two adjacent situations, with the same geotechnical and geological conditions, brutal and progressive collapses occurred. This fact led us to conclude that not only geotechnical and geological conditions can discriminate between these two types of collapse, but they have to be coupled with geometrical conditions of extraction (ratio between extracted ore and ore left in place, size of pillars, depth, etc.).

STATISTICAL DATA ANALYSIS

Data collection and preparation

Table 1 shows the matrix of collected variables that we were able to make after the back analysis of the 16 accidents (we will call them individuals from here after).

These collected variables in the subsided zones included measured or observed variables:

• length of pillars (m) "Lng_P";

• width of pillars (m) "LrgP ";

• width of rooms (m) "Lrg j G";

• depth of the subsided zone (m) "H";

• thickness of exploited seams (m) "W_cum";

• whether the subsided zone is adjacent to other zones of exploitation "C_surch " coded as 1 for a virgin zone, 2 for a zone adjacent to a caved zone, and 3 for a zone surrounded by caved zones. The collected variables included also calculated variables that have physical significance:

• ratio between volume extracted and volume left in place (%) "Defruit", calculated as:

Taux=- Lng_PxLrg_P (Lng_P + Lrg_G)x(Lrg_P + Lrg_G) (1)
• surface of pillar (m 2 ) "Surface";

• Hydraulic diameter of pillars (m)"D_Hydr", calculated as:

D_Hydr=-Surface

(2)

(Lng_P + Lrg_P)x2
• maximum natural stress on pillars (MPa) "Sigjot", calculated as:

0.025 x H Sig_tot =
(1-Taux) buckling of pillars "El_P", calculated as:

El P = W -Cum Lrg_P (3) (4)
We have also assigned an ID for each individual and a variable called type of observed collapse "Type" has been added to the matrix of observed/calculated variables.

Principal Components Analysis (PCA)

Principal component analysis is an interdependence technique of data analysis in which all variables are simultaneously considered. The general purpose of this analysis is to find a way of condensing the information contained in a number of original variables into a smaller set of new composite dimensions (components) with a minimum loss of information. Hair et al. (1992).

The principal components analysis is based on the analysis of the correlation matrix. In a multivariate space of n dimensions, each variable in the model counts for one dimension. The eigenvalues of the correlation matrix might be though of as the amount of variability that is included in each eigenvector, i.e. the amount of variability included in each compo-* nent. Depending on the amount of variability that included in each component, we can decide to include only a limited number of components that include 80 or 90% of the variability of the model.

Our objective of using this type of factor analysis was to try to find from all collected variables, the ones that have significant representation of the population of 16 individuals. For this purpose, we have considered the variable "Type" as a. passive variable, i.e. it does not interfere in the definition of the factor model, but to be projected on the resultant factor graph in order to see its place. This technique allowed us to know which observed/calculated variables are correlated with the type of collapse and though could be used in the discriminant process.

Figures 2 and3 show the plots of correlation circles, i.e. projection of the observed variables, over planes defined by "First and Second" components of the factor analysis and "First and Third" components of the factor analysis.

In the principal component analysis, we can also make a projection of the individuals over the different planes defined by different components. The coordinates of each individual present their values with respect to different principal components. Figures 4 and5 show the projection of individuals over the factorial planes defines by components 1 & 2, and 1 & 3 respectively.

From these projections over the first, second and third components, we were able to remark that:

• We have called this component, the resistance of the subsided zone.

The third component (19% of the variability) is highly correlated with (Sig_to, H, and LrgG). This component could be thought of as the mechanical stress on the pillars. We can see clearly that the variable Defruit is highly correlated with the passive variable Type, and both lie on the quadrant of the circle, which means that they are equally correlated with the first and third components.

Projection of variable on the plane defined by components 1& 2

Projection of individuals over the plane 1x2 • i

1 / t ,' t ! [ \ '. \ ,,• • • ' DEF IROTAL \ \ \ "• ""• -... .
W_CUM i • | i SIG_TOT | \ ! **.. [ '• • -. . • • • .. . PROGRE'^Ç : a -, . .• • " • \ \ \ \ SURHACE. • D_HYDR; C_SURCH ; • LRG_P _/ • ! / LRG_G ..--'"'
""""

.a

Component 1 : 32,05% The above mentioned remarks led us to believe that the variables included in these two components (1 st and 3 rd components), are the ones to be used for the discrimination between the two types of individuals (brutal and progressive), and that the variable Defruit will be highly favourable for this discrimination.

Discriminant Analysis

The Discriminant Analysis (DA) is the appropriate statistical technique when the dependant variable is categorical and the independent variables are metric Hair et al. (1992).

This technique is widely used in many situations where the objective is to identify the group to which an object belongs.

In our case, the discriminant analysis is to be used in order to define a discriminant function that discriminates the most our population of individuals (collapse) into the two observed groups (brutal and progressive).

As mentioned earlier in the principal components analysis, we were able to define a group of variables (those highly correlated with the first and third com-ponents) to be included in the discriminant analysis and that the variable Defruit is most likely, the best one to start with.

Discriminant analysis could be performed in a simultaneous approach, i.e., all independent variables are considered concurrently, or it could be done in stepwise approach, i.e. variables are entered one by one into the discriminant function depending on their discriminating power.

The simultaneous approach is appropriate when, for theoretical reasons, the analyst wants to include all the independent variables in the analysis and is not interested in seeing intermediate results based only on the most discriminating variables.

The stepwise approach begins by choosing the single best discriminating variable. The initial variable is then paired with each of the other independent variables one at a time, and a second variable is chosen. The second variable is the one that is best able to improve the discriminating power of the function in combination with the first variable. The third and any subsequent variables are selected in a similar manner. As additional variables are included, some previously selected variables may be removed if the information they contain about group differences is available in some combination of the other included variables. The stepwise approach is useful when the analyst wants to consider a relatively large number of independent variables for inclusion in the function. By consequentially selecting the next best discriminating variable at each step, variables that are not useful in discriminating between groups are eliminated and a reduced set of variables is identified, and the reduced set typically is almost as good as, and sometimes better than, the complete set of variables.

Although our main intention, in the current case study was to be able to discriminate between the two groups of collapse with minimum number of variables, we have performed the discriminant analysis in both simultaneous and stepwise approaches in order to compare with the different results if any.

In order to be able to judge on the quality of discrimination, we have adopted the cross validation test, which consists of eliminating one individual from the analysis, finding out the discriminant function without this individual and then reclassifying it according to the resultant function. If it is classified correctly, then the test is successful, if not, the test is not successful. This procedure is done over all the individuals and results of this test are represented as a percentage of success.

Results of the discriminant analysis with Simultaneous approach

Figure 6 present a graph of projection of individuals and the centre of gravity of each group, over the discriminant function defined by all the variables (simultaneous approach). This graph is to be re-garded as a one-dimensional graph as the discriminant function has only one dimension (brutal and progressive). The Y axis is plot only for presentation purpose only and does not have any significance.

Although, as we can see in Figure 6, that the two categories of individuals are discriminated on the graph, the simultaneous approach function failed to satisfy the cross validation test.

Results of the discriminant analysis with stepwise approach

After several trials with different sets of variables chosen according to experts knowledge of the sites and its characteristics with combination of the results of the principal components analysis, we were able to define a discriminant function using the stepwise approach and including only 7 variables {Defruit, Sig_Tot, H, W_cum, DJiydr, Lrg_G, C_Surch).

Figure 7 shows the projection of individuals and the centre of gravity of each group, over this discriminant function. This graph, as for the one defined by the simultaneous function has to be regarded as a one-dimensional graph, and that the Y axis does not have any significance and was only introduced for purpose of clarity of illustrations.

In Table 3 the results of the cross validation test are presented. We can see from Table 3 that this function defined with only 7 variables in a stepwise manner pass with 100% this test and could be considered as a better discrimination function than the one done in a simultaneous manner. This analysis could lead to the definition of zone risk map where we can provide areas of likely to subside in a brutal way and others likely to subside in a progressive way.

This method of analysis is highly recommended in similar cases where geological or geotechnical factors are not enough.

We have also to mention that due to the limited number of individuals (we have succeeded to find valid data for only 16 accidents over 100 years), we were not able to perform further tests on the produced function, and has to be used only in the context and within the limits of the geological and geotechnical parameters of the Lorraine iron basin.

REFERNCES

CONCLUSIONS

The problem of surface collapse is one of the major problems that concern all abandoned mining basins that have been exploited over the last century (XXth century).

In our case, the problem concerned an area of 1500 square kilometres and the impact of surface collapse on the population is a major concern to the regional authorities.

In collaboration with mining, geotechnical, and geological experts we started this study as a pilot study that could show the importance of data analysis in determining the type of expected collapse in absence of other geological criteria.

We were able to define, with the help of site's experts; a discriminant function that could be used in the discrimination of new studied zones, or zones of high importance to the society.

Figure 1 .

 1 Figure 1. Geographical situation of the Lorrain iron basin

  The first factorial plane (1 & 2) include 54% of the variability of the model, while the second plane (1 & 3) include 51% of the model variability. Components 1, 2 and 3 altogether include 73% of the model variability.• From the projection of individuals over the factorial plane 1 & 3, we can see clearly, a visual discrimination between brutal and progressive collapse, which was not the case in the factorial plane 1 & 2. This fact led us to concentrate on the factorial plane 1 & 3 in order to extract the variables that could enhance the discrimination between the individuals. • The first Component (32% of the variability) is highly correlated with the variables (W_cum, E1JP, DJfydr, Surface, and LrgP).

Figure 2 .

 2 Figure 2. Factor plot of variables over the factorial plane defined by the first two components of the factor analysis

Figure 3 .Figure S .

 3S Figure 3. Factor plot of variables over the factorial defined by components 1 & 3.plane

Figure 7 .

 7 Figure 7. Individuals projected over the discriminant function resultant of the stepwise approach.

Table 1 .

 1 Matrix of observed/calculated values

	ID	|Name and year		Defruit	H	W Cum
	Aud O2 l Audun-ïeT iche 1902	(%) 0,7	(m) 122	(ffi> 13,5
	Ësch'Ï9 ]ËscïierangeÏ9l9		0,65	170	6
	StMar 32 1Sainte-Marie 1932		0,65	153	5
	Mou 40 iMoutiers 1940		0,7	121	11
	Jar 49	Jamyl949			0,56	200	5
	Ron 54 Pvoncourt Ï954		0,7	147	7,5
	Ron 59	Roncourtl959		0,75	140	5
	Aub'72 "AubouéT972		0,45	150	6
	Roch>3 Rochonviïïers Ï973		0,62	190	4,5
	Roch 74 Rochonvillers 1974		0,61	190	4,5
	Crûs 77 'Crusne7 Ï977		0,5	180	3,8
	Vill 82	Ville-au-Montois 1982	0,55	166	4,5
	Aub 96 1 Auboué 1996 Coinville	0,53	170	5
	Aub 96 2 Auboué 1996 rue de		0,45	150	6
		Metz
	Mou 97 iMoutiers 1997		0,55	120	3
	Ron 99 iRoncourt 1999		0,53	140	2,5
	ID	Sig Tot	Lrg G	LngP		Lrg G 1 Surface
	Aud O2	(MPa) 10,17	(m) 4	( m ) . . 55	(m) M) 5 220
	Esch 19	17,61	6	70			6	420
	StMar_32 Mou 40	15,85 10,08	o|o	12 10			8 7 '	120 100
	Jar 49 Ron 54 __ 9	11,36 ___ 16,80	9 '/ 12	11 80 12			5 7 12	99 140 ' 144
	Aub72	12,00	11	70			7	720
	Roch73	15,00	6	13			5	78
	Roch 74	14,60	7,5	10			5	75
	Crus 77	10,80	11	25			6	275
	Vill 82	9,22	8,5	45			5	382
	Aub 96 1	10,85	6	7			3 "	.42 " "
	Aub 96 2	10,88	U	70			Î"	~"r 8406
	Mou 97	8,00	12	12			144
	Ron 99	8,94	6~i 85			6	510
	ID	D Hydr	E1_P	C_	Surch	Type
		(m).
	Aud O2	1,86	63,38	1			1 Brutal
	Esch 19	2,76	61,00	3			Brutal
	StMar 32	2,73	0,50	3			Brutal
	Mou 40 Jar 49	2,5 2,48	1,10 0,56	1 1			Brutal 1 Progressive
	Ron 54	2,59	91,07	2			Brutal
	Ron 59	3	30,42	2			Brutal
	Aub 72	4,75	50,55	•i			Progressive
	Roch 73	2,05	175	2			Brutal
	Roch 74	2,14	0,60	2			Brutal
	Crus 77	3,82	20,35	2			Progressive
	Vill 82	3,57	O,5JL	1			Progressive
	Aub 96 1	1,62	20,83	2			Progressive
	Aub 96 2	5,12	120.50	3			I Progressive
	Mou 97	3	0,25	2			1 Progressive
	Ron 99	2,8	80,42	2			1 Progressive

Individuals projected over the discriminant func- tion resultant of the simultaneous approach. Table 2. Results of the cross validation test for the simulta- neous approach's discriminant function.

  Table 2 represents the results of this test.

		Projection of	individuals over the axis defined by the discriminant function
				(Simultaneously alt variables are included)
	:	Ron 99 ;				Rod,74 '		'
	; • •	°t^z Crus 77 :Q Jar	9	Vifl2 o •	o	: ; :	0	• R< *fJ 3	'• ROT59 ^TL : Eacfi1s
						•			0	;
		1
	'	: CGP							CGB
	:	: •							• :'
				-2		0		2
					Discriminant function			o Progressif G Brutai
	Figure 6. Original data	Observed class Brutal	predicted class (Brutal Progressive 1 fTotal |8 0 8
				Progressive 10		8		8
		% brutal	1100,0 0,0	100,0
			(Progressive |0,0		100,0	[100,0
	Test de cross	Brutal	[6		2		8
	validation		[Progressive |2		6		8
		% pBrutal	|75,0	25,0	100,0
			Progressive 125,0	75,0	100,0

  Projection of individuals over the discriminant functionStepwise approach(Defruit, Sigjot, H. W_cum, DJiydr, Lrg_g, c_surch)

	-2	0	2
		Discriminant function	o •	Progressif Brutal

Table 3 . Results of the cross validation test for the stepwise approach's discriminant function.

 3

		[Observed	Predicted class	Total
		[class	Brutal Progressive |
	Original data	Brutal	8	0	8
		(Progressive	0	8	8
	%	Brutal	. 1 00,0 0,0	100,0
		Progressive 0,0	100,0	100,0
	Test de cross	Brutal	8	0	8
	validation	Progressive 0	8	8
	%	Brutal	100,0 0,0	100,0
		Progressive	0,0	100,0	100,0

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