Gilles Armand

Mountaka Souley

A viscoplastic model including damage for deep argillaceous rocks: blind predictions of drift behaviour

Keywords: Long term behaviour, viscoplastic model, damage, deep claystone

In order to demonstrate the feasibility of a radioactive waste repository in clay-stone formation, the French national radioactive waste management agency (ANDRA) started in 2000 to build an underground research laboratory at Bure. One of the key issues is to understand long term behaviour of drifts. Souley et al. [4] proposes a new macroscopic viscoplastic model of Callovo-Oxfordian clay-stones based on both laboratory and field observations which aimed to improve the viscoplastic strain predictions around the drifts. An example of a blind prediction of the excavation of a drift parallel to ah (using this new model) is presented and compared to in situ measurement. Results show the influence the damage state on viscoplastic strain rates, advantages and disadvantages of this new approach.

1.

INTRODUCTION

In November 1999, Andra started the construction work of the Meuse Haute-Marne underground research laboratory (URL) (Figure 1) in the district of Bure, located in the North-east of France. From 2000 until 2005, the construction of the experimental site has allowed us to study the radioactive waste repository feasibility in deep geological formation. The main results are presented in the "dossier 2005" [1]. The target horizon for the laboratory is a 135 m thick layer of argillaceous rock that lies between about 420 and 555 meters below the surface at the URL site. Argillaceous rock contains a mixture of clay minerals (40 % to 45 %), silica and carbonate-rich sedimentary. The construction of the URL itself serves a research purpose through monitoring of the excavation effects (?). The main goal of the geomechanical in situ investigations is to understand the rock response to the excavation of underground engineered structures and to the development of the damaged zone. At short term (during excavation work), the major issues are to understand the rock mass deformations, the hydromechanical coupling, and the effect of excavation works on transport properties in the vicinity of the drifts. The long term behaviour remains also a key issue for repository design and reversibility. At the main level of the laboratory, geomechanical measurements and EDZ characterization have been performed (convergence, extensometer ..) in drifts either parallel or perpendicular to the horizontal major stress. Armand et al. [START_REF] Armand | Characterisation of the Excavated Damaged Zone (EDZ) in the Meuse Haute-Marne underground research laboratory[END_REF] describe the EDZ characterization and the induced fractures pattern observed during the excavation works. They exhibit that high deformation rates appear in the fractured area [START_REF] Armand | Characterisation of the Excavated Damaged Zone (EDZ) in the Meuse Haute-Marne underground research laboratory[END_REF]. Those in situ observations conducted Souley et al. [START_REF] Souley | A viscoplastic model including damage for deep argillaceous rocks[END_REF] to propose a new macroscopic viscoplastic model for Callovo-Oxfordian clay-stones based on field observations and the previous models (short-term or long-term behaviour) in order to improve the viscoplastic strain predictions around the drifts. Since the end of 2006, a new research program has started in the URL in which Andra continues to study different excavation and support techniques in order to understand the effect on the EDZ extent and to optimize the excavation method. The feedback of previous experiments shows that "Mine-by-test" experiments are the best way to increase the knowledge on drift behaviour. A "Mine-by-test" provides a large in situ characterization and is a good opportunity to develop and validate constitutive models and numerical tools able to predict the hydromechanical behaviour of Callovo-Oxfordian clay-stones, as it was performed during the MODEX-REP European project [START_REF] Su | Constitutive Models for the Meuse/Haute-Marne Argillites -MODEX-REP, European Commission -Nuclear science and technology, Contract[END_REF] around the main access shaft. The new excavations (GED drift, figure 1b) performed in 2008 provide the first opportunity to test the new macroscopic viscoplastic model [START_REF] Souley | A viscoplastic model including damage for deep argillaceous rocks[END_REF] thanks to blind prediction. This paper presents the experimental layout and the associated blind predictions. The authors used this new model to perform 3D calculations using the real construction steps. Those calculations show up the advantage of the new model. Comparisons with in situ data allow checking the efficiency of this numerical approach.

BRIEF DESCRIPTION OF THE RHEOLOGICAL MODEL

Numerous campaigns of laboratory tests (uniaxial/triaxial, mono/multi-stage creep and relaxation) have been undertaken for characterizing the mechanical and hydromechanical short and long-term behaviour of the argillites. As a result, several constitutive models were developed in the framework of MODEX-REP European project [START_REF] Su | Constitutive Models for the Meuse/Haute-Marne Argillites -MODEX-REP, European Commission -Nuclear science and technology, Contract[END_REF]. The new model [START_REF] Souley | A viscoplastic model including damage for deep argillaceous rocks[END_REF] can be seen as a unification of two rheological models for clay-stones: one for the short-term response is based on the extension of Hoek-Brown criterion to describe the damage in pre-peak phase (approached by the theory of plasticity), failure and residual phase; the other for the long-term behaviour according to the modified Lemaître's model with creep threshold.

The main characteristic of this model is the coupling of damage with creep behaviour of the argillites based on the obviousness of the damage impact on the viscoplastic strain rates. In situ measurement exhibits high deformation rate in the fracture zone observed around the drift [START_REF] Armand | Characterisation of the Excavated Damaged Zone (EDZ) in the Meuse Haute-Marne underground research laboratory[END_REF]. Those deformations are mainly due to the induced fractures (EDZ) and their aperture. The modelling is performed in the framework of continuum mechanics, and viscoplasticity in some way will take into account the mechanical behaviour of this fractured zone. More precisely, in agreement with in situ observations, it was supposed that the postfailure material, in regards to its new microstructure, must have some creep characteristics which differ from those of the intact material. In particular the viscoplastic strain rate and the activation energy must reflect the failure of the claystones. For a damaged material (between the intact and failure states), a function of interpolation was proposed for the strain-hardening parameter since sufficient creep tests are not available on the damaged samples of clay-stones. The influence of damage on creep activation energy has been approached by an exponential function.

Finally the coupling between the induced damage and the creep behaviour is only clarified in one way: (damage -¥ viscoplastic strain rates) since for the moment, we do not consider the influence of viscoplastic strains on the damage threshold or more generally on the long-term strength of clay-stones. On the other hand, viscoplastic strains modify the stress field which, in its turn, is corrected while it exceeds damage criterion possibly changing indirectly EDZ extent. The set of constitutive equations and their implementation in FLAC3D© code as well as verification and validation tests are widely presented in [START_REF] Souley | A viscoplastic model including damage for deep argillaceous rocks[END_REF].

EXPERIMENTAL LAYOUT

In situ stress state and GED drift

The in situ stress state at the Meuse/Haute-Marne site has been measured by comprehensive combined methods. The vertical stress profile is presently well-known on the site. The horizontal stress anisotropy a H /ah is closed to 1.3 close to the main level (-490 m) [START_REF] Wileveau | Complete in situ stress determination in an argillite sedimentary formation[END_REF], respectively equal to 12.7 and 12.4 MPa for modelling task. The drift network grows following both horizontal principal stresses. GED drift is far away from other drifts and excavated perpendicular to the horizontal major stress. It is excavated with a pneumatic hammer. Supports consist of 2.2 m radial bolts, 10 cm of synthetic fibers reinforced shotcrete and sliding steel arches (installed every meter).

The front is also reinforced with 11 synthetic anchors (12 m long) emplaced at the front every 6 m. Excavation started in May 2008 and will be finalized by the end of January 2009.

Figure 2:

Geometrical model for blind prediction of GED, meshing and boundary conditions

Experiment layout

The experiment layout consists of 6 convergence sections (with 5 convergence measurements per section, 4 extensometers 30 meter long, with 7 measurements anchors (at 1, 2, 3.5, 5, 8, 15 and 30 m from the wall) and 4 extensometers 1 meter long. A geological mapping of front (every 5 meters) and the structural analysis of all cored boreholes (even in borehole performed for other experiments) have been carried out during excavation work to characterize the fracture zone. Extensometer and convergence section have been installed during the excavation work. The other boreholes will be drilled after the excavation. Multi-packer systems with 3 or 6 chambers from the wall to 6 m deep, have although been emplaced to perform pore pressure measurement and permeability tests. Those data are not presented because the numerical analysis is a purely mechanical analysis.

CALCULATIONS AND RESULTS

Geometry, boundary conditions and excavation sequence

In relation to the symmetry of GED drift (70 m long and considered as isolated) and its orientation with respect to the initial stress state (parallel to a h ), only the half domain is modelled. The geometrical model (150 m high, 57 m wide and 100 m long) shown in figure 2 consists of 574770 elements with following characteristics: 5 cm radially around the measurement sections A, B, C, D, E and F (located at 19.5, 35.5, 51.5, 59, 61 and 63.5 respectively from the beginning of GED drift) and 40 cm axially on both sides of each measurement section. The real advance velocity during the drilling of GED is used herein: the mean advance velocity is of 1 m/day except the break time to install materials.

Results

The EDZ distribution around the GED drift is firstly examined. When the face is positioned at sections B and C for example, fractured zones (from peak to the residual behaviour) are not yet formed around the drift. From a face at 5 m after each section (that is to say two radii of gallery) to the end of excavation, the fractured zones extend from 0 to 29 cm depending on the position (floor, roof of drift side) and the section. Contrary, a damaged zone (pre-peak behaviour) is systematically formed as soon as the GED face reaches the position of a given section (80, 110 and 120 cm, respectively at side, roof and floor of GED). In relation to anisotropy of the in situ stress state, more damage is obtained in the vertical direction compared to the horizontal ones (along a H ) whereas the difference in EDZ geometry and extent between the floor and the roof is related to their geometries. The extent of damaged zone becomes 170, 260 and 270 cm respectively at side, roof and floor at the end of excavation.

The evolutions of viscoplastic strains in time are also examined along vertical and horizontal boreholes in section C (figure 3). If the maximum of deformation in the horizontal direction is reached at the GED sides, the model predicts a maximum of viscoplastic strain inside the rock matrix in the vertical directions. It is also noted that the amplitude of the viscoplastic deformations is well correlated to the intensity and the extension of EDZ (i.e. high viscoplastic strains occur in the more damaged zones) in accordance with the philosophy of the model and the in situ observations. In particular, at the end of 10 years, the predicted viscoplastic strain rates at 2 m from the GED wall of 2e 12 and 4e 12 s-1 respectively in the horizontal and vertical directions.

Comparison with in situ data

The analysis of measured and predicted convergences shows that in the vertical direction and independently of the measurements section: (a) the short-term the velocity of measured convergences are higher than those predicted, but at long-term, we can expect that the measured convergence velocities tend asymptotically towards the predictions; (b) the amplitude of measured convergences are higher than those predicted. In particular, calculation underestimates from 13 to 44% vertical convergence respectively in sections B and C at the end of 80 days.

For horizontal convergences we note that at 80 days after the passage of GED face to a given section, measured/predicted (in mm) convergences are of: 23/30; 18/39; 33/47 respectively for the sections B and C. This illustrates the over-estimation character of predictive calculations in horizontal direction. The comparison of horizontal and vertical convergences rate is given as an example for section A and B (figure 4). It is thus noted that contrary to convergences, the predicted convergences velocities are in agreement with those measured at court term. More precisely, of horizontal convergence velocities (average calculated on the "stages" and expressed in mm/j) in the form of measured/predicted are: 0.04/0.05; 0.05/0.05 and 0.09/0.08 respectively in the sections have, B and C.

CONCLUSIONS AND PERSPECTIVES

This paper presents firstly a 3D blind prediction of the behaviour of a GED drift oriented parallel to a h . The prediction is performed using new macroscopic viscoplastic model of Callovo-Oxfordian clay-stones which includes the impact of damaged and fractured zones in the near field behaviour. The comparison of the convergence predictions in 6 sections and the first measurements indicates that the model underestimates the values of vertical convergences and over-estimates horizontal convergences. On the other hand, the convergences rates are well produced particularly in the horizontal direction as of the 100 first days. The enriching of the model, particularly for the fractured zones (viscoplastic rates and modules), is in the course of reflexion and will integrate the measurements of convergences and extensometric currently in acquisition.

Figure 1 :

 1 Figure 1: Meuse Haute Marne URL : (a) Location and geology, (purple: extension forecasted in 2012)

Figure 3 :Figure 4 :

 34 Figure 3:Viscoplastic strains along vertical and horizontal boreholes (section C)


Marion Keirsbulck
email: marion.keirsbulck@afsset.fr

Nathalie Bonvallot

Corinne Mandin

Séverine Kirchner

Frédéric Dor

Christophe Rousselle

Setting of French indoor air quality guidelines for chronic exposure to benzene

Keywords: Benzene, Indoor air, Health effect, Guideline, General population

Indoor air quality guidelines (IAQGs) provide safe levels of indoor pollutant concentrations below which adverse health effects are not expected to occur in the general population, including susceptible groups. The development of French IAQGs has been on-going since 2005 in the framework of the National Environment and Health Action Plan (NEHAP, 2004(NEHAP, -2008)).

According to toxicological and epidemiological data, benzene inhalation leads to acute and chronic effects. For long-term exposure, haematological effects and leukaemia have been observed in the Pliofilm cohort. Benzene is classified as carcinogenic for humans and its genotoxic effects have been demonstrated. Considering non carcinogenic effects and available toxicological reference values for benzene, the IAQG of 10 g.m -3 is proposed to protect the general population for long-term exposure. To protect from carcinogenic effects, the proposed IAQGs are based on WHO's potency slope factor: 2 and 0.2 g.m -3 respectively associated with an excess lifetime risk of 10 -5 and 10 -6 .

INTRODUCTION

In France, indoor pollutant levels have been considerably investigated in different environments (homes, schools, offices…) over the last few years. While the health effects of outdoor air pollution have been widely studied, health effects of indoor exposures need to be assessed. There is also a lack of reference values to facilitate management of indoor air quality. In this context, it seems necessary to promote the development of specific healthbased indoor air quality guidelines (IAQGs).

Many countries already have guideline values, and the World Health Organization is currently developing IAQGs [START_REF] Who | Development of WHO guidelines on indoor air quality, World Health Organization, Regional Office for Europe[END_REF]. At the European Union level, the INDEX project (supported by the Directorate General for Health and Consumers DG-SANCO) elaborated IAQGs for 13 priority chemical pollutants in 2004 [START_REF] Koistinen | The INDEX project: executive summary of a European Union project on indoor air pollutants[END_REF]. In order to update if necessary, or to extend the approach to other compounds, the French Agency for Environmental and Occupational Health Safety (AFSSET) and the French Scientific and Technical Centre for Building (CSTB) have been leading a multi-partner working group in charge of the development of IAQGs based on health criteria.

As a first step, the methodological approach was developed and a list of substances of concern was established; this list included benzene as high priority compound (AFSSET, 2007a). Benzene comes from outdoor air (exhaust fumes from mobile sources) and from indoor sources such as combustion (heating, cooking, incense burning, smoking...), attached garages, building materials and furniture, storage of solvents, etc. Inhalation is the main route of exposure for the general population (EC-JRC, 2004). In French residences, benzene concentrations in bedrooms range from 0.4 to 22.8 g.m -3 (mean over 7 days), with a median of 2.1 g.m -3 (study in [2003][2004][2005], passive sampling, 541 residences) [START_REF] Kirchner | État de la qualité de l'air dans les logements français[END_REF].

METHODS

According to the WHO, IAQGs correspond to safe levels of pollutant concentrations below which adverse health effects are not expected to occur in the general population, including subgroups considered susceptible due to their health status or age [START_REF] Who | Air Quality Guidelines for Europe[END_REF]. For genotoxic carcinogenic compounds, guideline values are expressed as risk levels corresponding to a probability of cancer occurring.

The methodological approach developed by the working group is based on three steps for any given substance. First, the human and/or animals health effects for inhalation exposure are described, taking into account associated durations of exposure (acute, sub-chronic or chronic). Susceptible subgroups of populations are identified [START_REF] Afsset | Indoor Air Quality Guideline Value Proposals -Framework document and methodological elements[END_REF]. The consistency of toxicokinetic and toxicodynamic data, and related effects, is analysed. Secondly, existing guideline values and toxicological reference values (TRVs) are collected and described: guideline values established within international bodies such as the WHO or by the European Commission are collected; guideline values established at a national scale (proposed by other bodies or countries) are summarized. In addition, available TRVs for inhalation from the US-Environmental Protection Agency-Integrated Risk Information System (US-EPA, IRIS), the Agency for Toxic Substances and Disease Registry (ATSDR), the Office of Environmental Health Hazard Assessment (OEHHA), Health Canada and the Dutch Agency for environmental health (RIVM) are also collected. Finally an in-depth critical analysis of available values (guidelines and TRVs) is carried out. Duration of exposure, critical health effects, studied populations, point of departure doses (NOAEL or LOAEL), safety factors, low-dose extrapolation are specified and discussed. IAQGs are proposed if there is one or more already existing guideline value established exclusively on health considerations and/or one or more TRV for inhalation. The choice among the reliable values is made on a case-by-case basis according to additional criteria (e.g. establishment date, animal or human data, etc.). If there is neither a guideline value, nor a reliable TRV for inhalation, the working group does not set any IAQG, indicating that additional assessment and research are required.

RESULTS AND DISCUSSION

The available toxicological and epidemiological data indicate that benzene inhalation leads to both acute and chronic effects, and allow for a good description and comprehension of benzene toxicokinetics and mode of action. The observed chronic effects are bone marrow depression expressed as leukopenia, anaemia, thrombocytopenia, leading to pancytopenia and aplastic anaemia. A causal relationship exists between exposure to benzene or solvents containing benzene at the workplace and the development of leukaemia in a rubberworker cohort (Pliofilm). The International Agency for Research on Cancer (IARC), the US-EPA and the European Commission have classified benzene as a known human carcinogen, respectively, group 1 in 1987, category A in 1998, and category 1 in 2004. The analysis of benzene's mode of action indicates that benzene and the reactive metabolites cause chromosomal aberrations in humans after chronic exposure. Data in animals support the genotoxic action of benzene. The AFSSET-CSTB working group has considered benzene as a carcinogenic compound via a genotoxic mechanism. Available guidelines and toxicological reference values for genotoxic-carcinogenic haematological effects are presented in Table 1. An analysis of the studies used for the construction of these values was performed. All values were determined on the basis of human epidemiological data. For non-carcinogenic effects, the ATSDR and the US EPA used a benchmark dose as a critical dose to derive the TRV. 240 exposed subjects versus 44 were respectively taken into account. Moreover, the study of [START_REF] Lan | Hematotoxicity in workers exposed to low levels of benzene[END_REF], which was chosen by ATSDR, was considered more appropriate because the characterisation of exposure at low concentrations is divided into three levels. The working group proposed the IAQG of 10 g.m -3 to protect the general population for long-term exposure (conventionally over 1 year of exposure). For carcinogenic-genotoxic effects, the unit risk values for which sufficient data were available were discussed. The WHO's value is based on different models (concentrationdependent model and multiplicative risk model), using the Pliofilm cohort [START_REF] Rinsky | Leukemia in benzene workers[END_REF][START_REF] Rinsky | Benzene and leukemia: an epidemiologic risk assessment[END_REF] and different exposure matrixes [START_REF] Crump | Quantitative estimates of risk of leukemia from occupational exposure to benzene[END_REF][START_REF] Paustenbach | Reevaluation of benzene exposure for the pliofilm (rubberworker) cohort (1936-1976)[END_REF][START_REF] Paustenbach | Benzene toxicity and risk assessment, 1972-1992: Implications for future regulation[END_REF]. The geometric mean of the range of excess lifetime risk of leukaemia estimates is 6 10 -6 (µg.m -3 ) -1 . Since the dose-response relationship remains unknown at low concentrations, the use of a concentration-dependent model and a multiplicative risk model is considered relevant. The WHO unit risk value of 6 10 -6 (µg.m -3 ) -1 , published in 2000, was considered as being the most relevant unit risk value by the group. The concentrations of benzene associated with an excess lifetime risk of 10 -5 and 10 -6 are respectively 2 and 0.2 g.m -3 . The group considers that then the choice of an acceptable risk level is the responsibility of policy makers.

CONCLUSIONS

The methodological approach is relevant to set IAQG recommendation for chronic exposure, whatever the health effect is. This approach also allows IAQGs for other exposure duration :

• for short-term exposure: 30 g.m -3 , mean over 14 days;

• for subchronic exposure: 20 g.m -3 mean over 1 year.

Table 1 .

 1 Available guideline and toxicological reference values for non-carcinogenic and genotoxic-carcinogenic haematological effects following chronic exposure (scientific review until September 2007):

	organization date	value	study	construction
	Chronic exposure -Non carcinogenic effects OEHHA 1999 REL = 60 µg.m -3 US EPA 2003 RfC = 30 µg.m -3	Tsai et al. 1983 UF =10 Rothman et al. UF =300
	ATSDR	2007 MRL = 9.7 µg.m -3	1996 Lan et al. 2004 UF =10
	Chronic exposure -Genotoxic-carcinogenic effects WHO 2000 ERU i = 6.10 -6 (µg.m -3 ) -1 US EPA 1998 ERU i = 2.2 -7.8.10 -6 (µ g.m -3 ) -1 RIVM 2001 Cr = 2.10 -2 mg.m -3 OEHHA 2005 ERU i = 2.9 .10 -5 (µg.m -3 ) -1 Health Canada 1991 CT 0.05 = 15 mg.m -3	Rinsky et al. 1981 -1987 Rinsky et al. 1981 -1987 no information no information linear and non-linear mathematical models linear mathematical model not clear no information al.1987 Rinsky et mathematical model

This method was tested and consolidated on several substances. Formaldehyde and carbon monoxide IAQGs for acute and chronic exposure were published in 2007. Elaboration of IAQGs for tetrachloroethylene, trichloroethylene and naphthalene is ongoing; they will be published in 2009. These elaborated guideline values may then been used by policy makers to set regulatory levels. This work is now also contributing to the development of WHO guidelines for indoor air quality initiated by WHO-Europe in 2006.

ACKNOWLEDGEMENT

To the French Agency for Environmental and Occupational Health Safety (AFSSET) and to the Scientific and Technical Centre for Building (CSTB) for their scientific support and coordination of the work.


Corinne Mandin

Jacques Ribéron

Serge Collet

Jean-Luc Besombes

Nicolas Pissot

Nadine Allemand

Eva Leoz-Garziandia

Impact of residential wood burning on indoor air quality

Keywords: Wood burning, PAHs, Particulate Matter, VOCs

This study aims at characterizing indoor air quality in single family dwellings burning wood regularly, studying the air change rate during wood burning and analyzing impact on outdoor air. Field investigations were performed, in February and November 2007, in six occupied houses located in rural areas (two equipped with an opened fireplace, two with respectively an old closed fireplace and a recent one, and two with respectively an old woodstove and a recent one). Continuous measurements of air temperature, relative humidity, carbon monoxide, nitrogen oxides, polycyclic aromatic hydrocarbons (PAHs) were performed in the room equipped with the wood burning appliance. Moreover in this room and in the main bedroom, PM 10 and PM 2.5 , PAHs (on PM 10 fraction), volatile organic compounds (VOCs), aldehydes, ketones, and tracers of wood combustion such as levoglucosan and methoxyphenols on PM 10 fraction, were also measured. Air exchange rates and building permeability were characterized through different means.

INTRODUCTION

Data on the impact of domestic wood burning appliances on air quality are rather poor. Use of such heating systems may increase as the use of renewable energy is encouraged. Besides, according to national inventories, wood burning represents a non-negligible source of organic pollutants in ambient air. Thus the project aims at characterizing indoor air quality (IAQ) in single family dwellings burning wood, studying the air change rate during wood burning and analyzing impact on outdoor air. Field investigations were performed, in February and November 2007, in six occupied houses located in rural areas. Only the results concerning IAQ are presented hereafter.

METHODS

Six occupied houses located in rural areas (60 to 80 km North from Paris) were instrumented. Two houses were equipped with an opened fireplace, two others with respectively an old closed fireplace and a recent one, and the two last ones with respectively an old woodstove and a recent one. In each home, the measurements were operated before (one day) and during wood burning (one day with nominal burning conditions and the following day with reduced ones). Standardized wood logs (identical humidity content in particular) were provided by the French National School of wood industries for all the six campaigns.

In two rooms (e.g. the living-room, where the appliance was located, and the main bedroom), PM 10 and PM 2.5 were collected on quartz fiber filters for a differed gravimetric analysis. Levoglucosan and methoxyphenols were also sampled on quartz fiber filters in the PM 10 fraction. Both particulate (quartz fiber filters) and gas (ORBOTM 43 tubes) phases of PAHs (18 congeners) were sampled using a modified ChemPass sampler (R&P) with a PM 10 head. Canister and Sep-Pack cartridges were respectively used for VOCs and aldehyde/ketone sampling. The samplings were performed during 8 h in the middle of each room, at about 1.5 m from the floor.

Only in the living-room, continuous on-line measurements were performed for:

• NOx: chemiluminescent analyzer (Thermo Environment Instruments 42C);

• PAHs: photo-ionization analyzer (ECOCHEM PAS-2000);

• CO and O 2 : multigas sensor (OLDHAM MX2100);

• temperature: PT100 probe.

In two of the six dwellings, air leakage of the building envelope was measured using blower door technique. Moreover the air renewal rate was measured using tracer gas technique by the decay method. In the four other dwellings magnitude of air exchange was assessed through visual inspection of the envelope components and through spot measurements of CO 2 or exhausted airflow rate in case of a mechanical ventilation.

RESULTS

Indoor concentrations measured in the living-room are presented in Table 1. Table 2 focuses on both PM 10 and PM 2.5 indoor (living-room and bedroom) and outdoor concentrations. Air exchange measurements (2 houses) or estimations (4 houses) show that there is no difference according to burning conditions. Air exchange rate varies from 0.5 to 2.5 h -1 .

DISCUSSION

The NO 2 concentrations are influenced by the wood burning. But they remain in the range of NO 2 concentrations that were measured in 62 Parisian dwellings in 2000 [START_REF] Mosqueron | Personal exposure of Paris office workers to nitrogen dioxide and fine particles[END_REF].

PAHs concentrations (measured with the photo-ionization analyzer) are influenced by wood burning and can reach rather high values, up to 80 ng.m -3 , in comparison to other studies such as RIOPA one, Relationships of Indoor, Outdoor, and Personal Air [START_REF] Turpin | Relationships of Indoor, Outdoor, and Personal Air (RIOPA). Part II, Analyses of Concentrations of Particulate Matter Species[END_REF]; there is no specific data for French indoor environments. PAH particulate and gaseous phase measurements show that naphthalene has a major contribution in the total sum of PAHs.

In some dwellings, PM 2.5 and PM 10 concentrations are clearly impacted by wood burning. Whereas the indoor/outdoor ratio is below 1 when the appliance is off, it overrides 1 during wood burning, largely in some cases (see Table 2). During the French national "Housing campaign" [START_REF] Kirchner | État de la qualité de l'air dans les logements français[END_REF]), PM 2.5 and PM 10 were measured in the living-room in the presence of occupants (from 5 pm to 8 am on weekdays and 24h/24 during the week-end).

The indoor concentration geometric means were respectively 19.1 µg.m -3 (95 th percentile: 133 µg.m -3 ) and 31.3 µg m -3 (95 th percentile: 183 µg.m -3 ). PM 2.5 and PM 10 concentrations measured here during wood burning are above the mean values in French dwellings (except for open fireplace 1), but they remain in the range of possible indoor concentrations.

The indoor benzene concentrations are clearly influenced by wood burning, except in the case of old closed fireplace (without explanation). The indoor geometric mean measured during the French "housing campaign" was 2.1 µg.m -3 (95 th percentile: 7.2 µg.m -3 ) [START_REF] Kirchner | État de la qualité de l'air dans les logements français[END_REF]. Concentrations in the instrumented houses are in the same order of magnitude than this mean value, whereas they are in the range of the higher values as soon as the appliance is on.

Finally, formaldehyde indoor concentration is not influenced by wood burning, which has also been previously observed by [START_REF] Lévesque | Wood-burning appliances and indoor air quality[END_REF] and [START_REF] Gustafson | The impact of domestic wood burning on personal, indoor and outdoor levels of 1,3-butadiene, benzene, formaldehyde and acetaldehyde[END_REF].

No common influence can be drawn between nominal and reduced burning conditions. When available, concentrations in the bedroom (not presented here, except for particles in Table 2) were in the same order of magnitude as the concentrations in the living-room, showing influence of wood burning even in distant rooms. Finally due to the very low number of tested appliances (one or two in each category), it was decided not to provide any comparison between them.

CONCLUSION

This study is the first to investigate the potential impact of wood burning on IAQ in France. It is also the first one to measure PAHs and tracers of wood combustion such as levoglucosan and methoxyphenols indoors.

The magnitude of the impact on indoor air is various depending on the compounds that are considered; major influence is observed on benzene, particle, and PAH indoor levels, minor one for NO 2 . Formaldehyde indoor concentrations appear as not being influenced by wood burning, which is coherent with the fact that this compound has major other emission sources in residential environment.

Table 1 .

 1 Concentrations in the living-room by appliance and by burning condition.

	Appliance	Burning condition	NO 2 (µ g.m -3 ) (a)	PAHs (a,b) (ng.m -3 )	PM 10 (µg.m -3 )	PM 2.5 (µg.m -3 )	Benzene (µg.m -3 )	Formaldehyde (µg.m -3 )
	Old	Without	nd	nd	nd	nd	1.5	14.1
	woodstove	Nominal	23.9	29.8	nd	nd	5.4	17.8
		Reduced	12.8	13.1	nd	nd	2.0	15.4
	Recent	Without	17.0	7.8	34.2	1.1	0.5	18.6
	woodstove	Nominal	37.1	50.2	nd	23.1	10.9	36.4
		Reduced	53.2	79.7	67.0	11.8	8.5	32.4
	Open	Without	4.6	3.7	<LoQ	<LoQ	1.4	12.3
	fireplace 1	Nominal	11.7	27.5	1.2	3.4	4.1	9.0
		Reduced	8.0	4.8	2.3	1.1	3.3	9.0
	Open	Without	34.6	12.8	3.9	nd	2.1	6.0
	fireplace 2	Nominal	nd	nd	nd	nd	nd	nd
		Reduced	34.6	28.8	38.5	29.9	1.5	5.9
	Old closed	Without	0.8	nd	nd	nd	8.8	21.2
	fireplace	Nominal	16.6	7.3	51.1	nd	6.4	24.2
		Reduced	60.2	25.9	36.4	nd	7.5	18.9
	Recent	Without	122.6	6.1	23.0	nd	1.3	12.2
	closed	Nominal	246.7	13.4	70.7	33.8	7.4	26.9
	fireplace	Reduced	115.9	17.1	130.1	66.4	18.1	25.0

nd: not determined (sampling or analytical problem); LoQ: limit of quantification "without" means that the appliance was not operating (a): average of 8-hour on-line measurements; (b): PAHs measured with the photo-ionization analyzer

Table 2 .

 2 PM indoor and outdoor concentrations by appliance and by burning condition.

	Appliance	PM 10 (µg.m -3 ) condition Living-room Bedroom Outdoor Living-room Bedroom Outdoor Burning PM 2.5 (µ g.m -3 )
	Recent	Without	34.2	2.1	22.9	1.1	1.1	14.6
	woodstove	Nominal	nd	95.8	23.3	23.1	35.8	10.6
		Reduced	67.0	65.5	23.3	11.8	14.4	14.8
	Recent	Without	23.0	nd	18.7	nd	53.5	12.7
	closed	Nominal	70.7	nd	16.7	33.8	nd	9.9
	fireplace	Reduced	130.1	155.4	8.6	66.4	nd	5.5
	nd: not determined (sampling or analytical problem)

ACKNOWLEDGEMENTS

The authors thank the French Agency for environment and energy savings (ADEME) and the French Ministry of the environment (MEEDDAT) for their financial support.


Jean Poulleau

Cécile Raventos

Philippe Fayolle

Emmanuel Fiani

Philippe Fayolle²

Robustness of the QAL2 calibration (EN14181). Uncertainty on the results given by a calibrated AMS

The European Directives on waste incineration (2000/76/CE) and on large combustion plants (2001/80/CE) require to refer to international and national standards for emission monitoring and they specify requirements for the performance characteristics and the total uncertainty attached to the results provided by the automated monitoring systems (AMS) used for continuous monitoring.

CEN TC 264 worked out in 2004 the EN 14181 standard which defines the various stages of quality assurance to be implemented to guarantee the reliability of the continuous emission monitoring. It applies to incineration and combustion plants but its use could be extended to other industrial plants after the publication of the future integrated European Directive which will replace the 7 already existing European directives.

The EN 14181 standard specifies three levels of quality assurance (indicated by initials QAL) and an annual test of monitoring: (annual monitoring test indicated by initials AST). They are as follows:

QAL1

A procedure to demonstrate that the AMS selected before their installation on site are adapted to the use for which they are intended, i.e. ready to measure with the required uncertainty.

QAL2

A procedure to check that the AMS are correctly installed and to calibrate them by comparison with the standard reference method (SRM). A test of variability is also carried out to check the compatibility of the AMS on site with the level of required uncertainty.

QAL3

A procedure using a control chart for the determination of the zero and span drift of the AMS, carried out with reference materials and allowing demonstrating that the AMS continue to provide reliable data with the level of required uncertainty.

AST

An annual test, corresponding to a mini QAL 2, to evaluate if the AMS functions satisfactorily.

These quality assurance levels follow a logical sequence to demonstrate the suitability of the AMS, its correct installation, commissioning, and calibration, followed by continuing and correct operation (see Figure 1). EN 14181 is one of the principal new tools, at the disposal of the actors implied in emission controls on stacks to ensure the reliability and the quality of the measurement results.

QAL1, while being based on EN 15267 which sets the certification rules of the AMS in Europe actually almost requires certification. EN 15267-3 describes the procedure to determine the performance characteristics of the AMS and to calculate the total measurement uncertainty for variation of standard conditions of the influence factors. The total measurement uncertainty determined under the field conditions at the limit value must be lower than 75% of the uncertainty objective fixed by the directive to be sure that the AMS will pass the tests QAL2 and QAL3 during its operation on site.

The QAL2 stage, by fixing the calibration procedure per comparison with the SRM, limits the simple method of calibration with materials of reference to restricted cases (quoted by GA X 43-132, worked out by the AFNOR commission to specify the details of implementation of EN 14181).

For the compounds being the subject of a continuous-monitoring, with the implementation of EN 14181, the controls carried out for regulatory purposes by the approved organizations do not have, as a main goal to check the conformity of the installation any more, but rather to check the state of correct operation of the AMS installed in the plant. Consequently, the data provided by the AMS will be considered of a sufficient quality to check the conformity of an installation at any period of the year and to calculate annual flows of pollutants rejected by the installation.

OBJECTIVES OF THE STUDY

The prime objective of this study financed by the French Ministry in charge of Environment and by ADEME ( ) was to check the quality and the robustness of the QAL2 according to test conditions met on site. For that, the various situations of the field were repeated:

• Case A : ideal conditions where the concentrations vary on all the range from 0 to daily ELV with 20 points

• Case B : concentration range varying on all the range from 0 to daily ELV with a limited number of points: 10 points

• Case C : concentration range restricted to 50% of the range from 0 to daily ELV with a limited number of points: 10 points

• Case D : concentration range reduced to a cloud of 5 points to which is added or not the zero point. For each case D1 (low concentrations) and D2 (high concentrations). the calibration functions obtained with or without the zero are compared and the Calibration function whose R 2 is largest is kept. In the thirds case studied D3, the 5 points are equally distributed on all the range of measurement.

From the digital processing of the results, it was given in which site configuration (possibility of varying the concentrations on site or not) or of uncertainty of the SRM, it can be most relevant to reduce the number of couples of points to even substitute for the suggested method of calibration QAL2, a simple adjustment by reference materials.

The second objective of the study aimed at using the test results in order to estimate the uncertainty attached to a result given by an AMS conformed with QAL1 requirements (thus linear and not very sensitive to interfering) when it is calibrated according to QAL2.

FACILITIES AND CONDITIONS OF TESTS

The QAL2 tests were related to 3 certified AMS from the Environnement S.A. company:

• A MIR-FT which can measure simultaneously by Fourier Transform Infra-red absorption (IRTF) the gases:

HCl, HF, NH 3 , SO 2 , NO, NO 2 , NOx, CO, TOC, H 2 O, N 2 O and the measurement of O 2 by an integrated Zirconia cell. Many other gases are also available on request.

• A MIR 9000 which measures continuously gas compounds by infra-red spectroscopy with gas filter correlation: HCl, HF, SO 2 , NO, NO 2 , NOx, CO, TOC, N 2 O

• A Graphite 52 M for the measurement of TOC with a flame ionization detector.

The tests related to two compounds for which the SRM is manual: HCl and SO 2 , three compounds for which the SRM is automatic: CO, NOx and TOC and finally, the peripheral compounds allowing the conversion of the data under the reference conditions (O 2 and H 2 O).

Five approved organizations took part in the tests: ANECO, BUREAU VERITAS, CETIAT, INERIS and LECES.

To facilitate the test program, it was implemented on the test bench of INERIS which can provide gas effluents resulting from combustions or waste incineration. It is equipped to accommodate five teams simultaneously.

Figure 2 -Test bench scheme

To generate gases, the bench (cf. figure n°2) is eq uipped by two boilers of approximately 50 kW each, the first fed with natural gas, the second with light fuel. The gases resulting from this combustion can be heated, humidified to simulate effluents leaving a scrubber and the concentrations of some pollutants increased by the controlled gas addition (CO, NO, SO 2 , HCl, etc) or vaporization of made up liquids (specific VOC).

The generated gases return in a steel loop, internally protected by a PTFE coating, where a flow of 300 kg/h. circulates. This loop is maintained in temperature by electric tracing. The internal diameter of the duct is 150 mm.

The concentrations of each compound varied from 0 to ELV 1/2h for waste incineration. All the compounds were measured in parallel.

RESULTS AND DISCUSSION

INFLUENCE OF THE NUMBER AND OF THE DISTRIBUTION OF THE POINTS ON THE STUDIED RANGE AND INFLUENCE OF THE SRM ON THE QUALITY OF THE CALIBRATION FUNCTIONS

• As recommended in the AFNOR guide GA X 43-132, the automatic AMS and SRM were adjusted before the calibration. This preliminary adjustment leads to Calibration functions with a slope close to 1 for the compounds which have an automatic SRM (O 2 , NOx, CO, TOC).

•

Calibration functions are of better quality when the SRM is automatic (R 2 coefficient much higher than 0,9 For the case D2, where the cloud of points is located in the highest part of the concentration range, the addition of the point (0,0) appreciably improves the quality of calibration function whose slope passes from 0,46 to 1,16 and R 2 from 0,81 to 0,99. For case D1, where the cloud of points is located in the lowest part of the concentration range, the addition of the point (0,0) does not improve the calibration function.

•

In a more general way, for the compounds whose SRM is manual, the characteristics of the calibration functions vary more noticeably according to the configuration because of the variability of SRM data. The quality of the calibration functions, very poor when it is difficult to vary the concentrations, can be highly improved by the addition of the point (0,0), including for the most favorable configurations (A, B and C). An example is given below with the measurement of the water vapor concentration: The addition of the point (0,0) highly improves the equations of calibration functions, including for configuration A. For D1 and D2, one passes from a slope of -0,297 to 0,995 and from 0,34 to 0,995 respectively. The determination coefficients pass from 0,169 to 0,999 and from 0,211 to 0,999 respectively.

H 2 O

VARIABILITY TEST AND SUSPECT VALUES

•

The tests of variability carried out with the whole set of data lead to some negative results for the compounds for which the SRM is manual.

In this case, the uncertainty of the implemented SRM, strongly influences the dispersion of the couples of points around the calibration function. When a manual SRM is implemented, suspect values are almost systematically detected by the test proposed by GA X 43-132. Although the test of variability is not very demanding, the result with this test can be negative by not removing any of the couples of points resulting from the tests. Thus, for HCl and SO 2 , we withdrew two pairs of values (tolerated by GA X 43-132). Without these withdrawals of suspect values, the results of the tests of variability on HCl and SO 2 are negative. In the case of an SRM with a high uncertainty, it is relevant to be able to remove one to two suspect couples not to weigh down over the AMS the threat of a rejection for lack of fidelity, which is actually due to the SRM and its implementation. After removal of one to two suspect data, the result of the test becomes positive. The test suggested in the guide GA X 43-132 is thus relevant. On the other hand, it would be more relevant, with the sight of the treated examples, not to exclude the couples from points remaining in the interval + 0,5 σ 0 around the calibration function (the guide indicates + 0,25 σ 0 ).

•

For the compounds with automatic SRM, the tests of variability are always positive.

COMPARISON OF THE RESULTS OF QAL2 OF DIFFERENT PARTICIPANTS

11,5

Table n°5 : Average calibrated values for the various configurations We see that the influence of the configuration of the points on the slope of the calibration function or on the calibrated value remains often limited, if the operator adds the point (0,0) or forces the calibration function to pass by 0, since the measuring points are limited to a group of points of low size. The possibility of adding the point (0,0) is mentioned in GA X 43-132, whatever the configuration met during the tests, in the express condition of checking that the AMS gives a signal 0 with a reference material representing zero state.

ESTIMATE OF THE MEASUREMENT UNCERTAINTY THROUGH THE CONFIDENCE INTERVAL ON THE CALIBRATED VALUES

The summary table n°6 hereafter gives an estimate o f the confidence interval on the values calibrated for the various configurations:

The confidence interval is evaluated by considering in first estimate, 2 times the standard deviation of the calibrated values at the daily ELV obtained by the participants Confidence intervals allocated to the calibrated values, which can be considered as expanded uncertainties, are appreciably more important for the compounds where the SRM is manual. However, we have an exception with Graphite 52 M, where the measurand is a concentration index of VOCs and for which we know that measurement is very dependent on the configuration of the FID used and where the concept of accuracy of the SRM is quite relative (the response factors can be different from one model of analyzer to another).

We note that the calibrated value resulting from calibration QAL2 varies slightly for cases A, B, C or D2 for the compounds where the SRM is automatic.

The calibrated value resulting from calibration QAL2 varies more as soon as one varies the number of data, for the compounds where the SRM is manual.

• The impact of the configuration of the number and distribution of points on the effective range is less important when the uncertainty of the SRM is low.

We note that it is not inevitably necessary to have a high number of points to obtain a calibrated value close to the expected concentration and an acceptable uncertainty. We notice that in the case of a 5 points cloud, close to the top-of-the-range, since it is associated the point (0,0), the quality of the results in terms of accuracy and uncertainty was similar to the one we have in case A, where the 20 points are equally distributed on all the range. On the other hand, the cloud of points located at the bottom-of-the-range often led to calibrated values far away from the expected concentration and whose associated uncertainty can be very important.

Figure 1 -

 1 Figure 1the sequence of quality assurance levels in EN 14181

Figure 3 -

 3 Figure 3 -Influence of the number of points on the quality of the calibration function

  Figures n°4 : Calibrations functions obtained with MIR FT (H 2 O)

Table n°1 :

 n°1 Table of the selected emission limit val ues for the measurement campaign

	Compound	Range	ELV day	ELV ½ h
	SO 2	400 mg/m 0 3	50 mg/m 0 3	200 mg/m 0 3
	HCl	120	10	60
	NOx	1000	200	400
	CO	1000	50	150
	TOC	40	10	20

Table n°2 :

 n°2 ). Calibration functions obtained with MIR FT and Graphite52M (case A)The coefficient of determination of the equation of the calibration function is not affected by the number of points (20, 10 or 5 points) since those are equally distributed on the range of measurements. A contrario, when the range covered by the points gets narrow, the coefficient of determination is degraded. An example is given below with the TOC results:

						O 2	CO	TOC	NOx	HCl	SO 2
	Calibration function ax+b	a b	0,9834 0,1748	1,021 5,248	1,051 1,61	0,982 -0,163	0,875 0,839	1,186 -6,26
	coefficient R	2			0,944	0,9999	0,9975	0,9998	0,983	0,873
	TOC				case A	case B	case C	case D1	case D2	case D3
	Calibration function						With / without pt 0	With / without pt 0
			a		1,051	1,024	1,063	1,34 / 0,946	1,16 / 0,46	1,04
			b			1,61	1,79	1,606	0,785 / 1,988	0,099 / 9,424	1,44
	coefft R	2			0,997	0,998	0,986	0,905 / 0,895	0,995 / 0,810	0,998
	variability test	0,40<1,50 0,34<1,47 0,28<1,47	0,58<0,93	0,43<1,43	0,43<1,43

Table n°3 :

 n°3 Calibration functions and results of variability tests with Graphite 52M

Table n°4 :

 n°4 Calibration functions and results of variability tests obtained with MIR FT (H 2 O)

			case A	case B	case C	case D1	case D2
	Calibration function ax+b	without/with p t 0 without/with p t 0 without/with p t 0 without/with p t 0 without/with p t 0
			a 0,7425 / 0,993	0,892 / 1,000	0,584 / 0,994	-0,297 / 0,995	0,34 / 0,995
			b 3,2704 / 0,042	1,394 / 0,007	5,39 / 0,015	17,26 / 0,008	8,371 / 0,016
	coefft R	2	0,6783 / 0,996	0,8378 / 0,999	0,423 / 0,998	0,169 / 0,999	0,211 / 0,998
	Variability test	0,172 < 1,527	0,141 < 1,502	0,173 < 1,5	0,176 < 1,425	0,229 < 1,424

  Table n°5 hereafter provides the averages of the ca librated values of the participants at the level of the daily ELV (ELV d ), the various configurations:

		Compound measured	O 2	CO	NO	TOC	SO 2	HCl
	ELV d	in mg/m 0 3 at 11% of O 2	-	50	200	10	50	10
	Calibrated value (case A)	10,4	53,9	202,7	10,2	52,1	9,90
	QAL2 with 20 points distributed on all the range
	Calibrated value (case B)		54,2	203,4	10,2	48,4	9,79
	QAL2 with 10 points distributed on all the range
	Calibrated value (case C)		49,9	212,2	10,1	51,9	10,68
	QAL2 with 10 points distributed on 50% of the range
	Calibrated value (case D1 with pt 0,0)		51,8	178,0	9,6	48,9	8,43
	Case D1 without pt (0,0)		40,9	200,0		50,9	2,81
	QAL2 with a cloud of 5 points distributed on the lowest part of the range
	Calibrated value (case D2 with pt 0,0)		53,7	202,5	10,3	52,7	9,17
	Case D2 without pt (0,0)		58,3	209,5		20,7
	QAL2 with a cloud of 5 points distributed on the highest part of the range

Table n°6 :

 n°6 Confidence intervals on the calibrated values for the various configurations

		Compound measured	O 2	CO	NO	COT	SO 2	HCl
	ELV d	in mg/m 0 3 at 11% of O 2	-	50	200	10	50	10
	Confidence interval % on calibrated value	5,6	3,1	6,7	21,2	13,9	16,3
	QAL2 with 20 points distributed on all the range (case A)
	Confidence interval % on calibrated value		3,0	6,0	24,9	14,4	18.4
	QAL2 with 10 points distributed on all the range (case B)
	Confidence interval % on calibrated value		2,7	8,4	19,6	27,6	27,9
	QAL2 with 10 points distributed on 50% of the range (case C)
	Confidence interval % on calibrated value
	QAL2 with a cloud of 5 points distributed on the lowest part of the range (case D1+ pt 0,0)		19,9	6,1	42,6	14,9	19,3
	case D1			25,0	15,2		25,1	628
	Confidence interval % on calibrated value
	QAL2 with a cloud of 5 points distributed on the highest part of the range (case D2+pt 0,0)		3,6	6,4	19,7	16,6	16,1
	case D2			6,0	11,2		238	32,2

• We note that:

COMPARISON OF UNCERTAINTIES AT THE LEVEL OF THE DAYLY ELV EVALUATED BY A UNCERTAINTY BUDGET OF THE AMS (QAL1) OR OBTAINED DURING CONTROL QAL2

The second objective of the study aimed at using the test results in order to calculate on the one hand the uncertainty attached to a result given by a certified AMS (conform with QAL1, thus linear and with a low crosssensitivity), and on the other hand the uncertainty when it is calibrated according to QAL2.

Our objective is to check coherence between the results of uncertainty resulting from exercises QAL1 and QAL2. For that it is advisable to calculate the uncertainty which one expects at the level of the limit value, starting from the budget of uncertainties determined on the basis of the evaluation of performance characteristics (QAL1) and to compare it with the uncertainty estimation that we have on the calibrated value of the AMS at the ELV.

Uncertainty at the ELV is given by taking into account the actual variation range of the influence factors and not the default variation range used during the AMS certification, to know if the AMS is in conformity with the European directives objectives. for the QAL 1 adapted to the measuring site and the QAL 2. We note that, when the uncertainty of the SRM is rather low (case of the majority of the automatic methods) then

, and when the uncertainty is higher (case of the manual methods and FID) then

This report leads to favour SRMs with low uncertainties, which is often the case for the automatic SRM.

Bibliographie

EN 14181 Quality Assurance of AMS NF GA X 43-132 Stack emissions -Quality assurance of the automatic measurement systems -Application of the standards EN 14181, EN 13284-2 et EN 14184


Amjad Abou Assali

Dominique Lenne

Bruno Debray

Case Retrieval in Ontology-Based CBR Systems

Keywords: Case-based reasoning, Ontology, Heterogeneous case base, Similarity measures, Similarity régions

This paper présents our knowledge-intensive Case-Based Reasoning platform for diagnosis, COBRA. It intégrâtes domain knowledge along with cases in an ontological structure. COBRA allows users to describe cases using any concept or instance of a domain ontology, which leads to a heterogeneous case base. Cases heterogeneity complicates their retrieval since correspondences must be identified between query and case attributes. We présent in this paper our System architecture and the case retrieval phase. Then, we introduce the notions of similarity régions and attributes' rôles used to overcome cases heterogeneity problems.

Introduction

In industrial sites concerned by the SEVESO directive, risks exist due to the présence of hazardous substances and processes. To reduce such risks, safety barriers are set up depending on the type of process and on the hazardous situation to control as well as on the local environmental conditions. However, barriers may not work properly, and thus hazards may arise. In such a case, industrial experts intervene to diagnose the barriers failure basing mostly on past failure expériences occurred in similar situations. The hypothesis of experts hère is that "if a barrier did not work correctly in a past similar situation, it is strongly probable that it does not work, in the current situation, for similar reasons". To simulate the experts' activity, we use a Case-Based Reasoning (CBR) approach [START_REF] Riesbeck | Inside Case-Based Reasoning[END_REF]. CBR is a problem-solving approach used to solve a new problem (target case) by remembering a previous similar situation (source case) and by reusing information and knowledge of that situation [START_REF] Aamodt | Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches[END_REF]. In the diagnosis activity, when no obvious cause of failure is found, experts may realize that more information is needed to find the right cause of failure. This led us to apply a conversational CBR approach where cases are enriched as experts advance in the diagnosis.

The System was first applied to the diagnosis of the failure of gas sensors installed in industrial plants. Such sensors are intended to detect certain gases so that if there is a leak somewhere in the site, a safety action can be undertaken. In this context, a case represents a diagnosis of the failure of a gas sensor in a given industrial environment.

In this paper, we introduce our platform COBRA (Conversational Ontologybased CBR for Risk Analysis), an ontology-based CBR platform. It allows to capitalize and reuse past failure expériences based on ontological models describing the domain and case structures. One of the interesting features of COBRA is that it allows a dynamic représentation of cases; i.e., users can define their cases' attributes at run time, which leads to a heterogeneous case base. However, this heterogeneity complicates the case retrieval phase. We describe in this paper the case retrieval phase as well as the similarity measures used. In addition, we présent our approach to overcome the cases heterogeneity problems.

Related Work

The intégration of gênerai domain knowledge into knowledge-intensive CBR Systems was an important aspect in several projects. In the CREER architecture [START_REF] Aamodt | Explanation-Driven Case-Based Reasoning[END_REF], we find a strong coupling between case-based and generalization-based knowledge. Thus, cases are submerged within a gênerai domain model represented as a densely linked semantic network. Fuchs & Mille proposed a CBR modeling at the knowledge level [START_REF] Fuchs | Une modélisation au niveau connaissance du raisonnement à partir de cas[END_REF]. They distinguished four knowledge models: 1) the conceptual model containing the concepts used to describe the domain ontology regardless of the reasoning process; 2) the case model that séparâtes the case into three parts: problem, solution, and reasoning trace; 3) the models describing the reasoning tasks; 4) and the reasoning support models. Diaz-Agudo & Gonzàlez-Calero [START_REF] Diaz-Agudo | An architecture for knowledge intensive CBR Systems[END_REF] proposed a domain-independent architecture that helps in the intégration of ontologies into CBR applications. Their approach is to build integrated Systems that combine case spécifie knowledge with models of gênerai domain knowledge. So, they presented CBROnto [START_REF] Diaz-Agudo | CBROnto: a task/method ontology for CBR[END_REF], a task/method ontology that provides the vocabulary for describing the éléments involved in the CBR processes, and that allows to integrate différent domain ontologies. CBROnto was reused later by JCOLIBRI, a powerful object-oriented framework for building CBR Systems [START_REF] Recio-Garcia | Ontology based CBR with jCOLIBRI[END_REF]. It splits the case base management into two concerns: persistence and in-memory organization, which allows différent storage médiums of cases (text/XML files, ontology, etc.) accessed via spécifie connectors. However, JCOLIBRI does not allow the treatment of dynamic and heterogeneous case bases. In this work, we decided to keep the interesting aspects of JCOLIBRI, and to add our own layer that allows to work with heterogeneous case bases. and RETAIN. In the "diagnose" phase, the System tries to identify failure causes from the retrieved similar cases. If no cause is found, or even if the diagnosis proposed by the System was not validated by the user, the System asks the user to "enrich" his case description, and thus new similar cases can be retrieved. This cycle is repeated until a relevant diagnosis is proposed by the System, or no solution is found.

-Knowledge containers layer: it contains three main containers: vocabulary, case base, and similarity measures. In knowledge-intensive CBR Systems, ontologies play an important rôle in representing thèse containers. They can be used as the vocabulary to describe cases and/or queries, as a knowledge structure where the cases are located, and as the knowledge source to achieve semantic reasoning methods for similarity assessment [START_REF] Recio-Garcia | Ontology based CBR with jCOLIBRI[END_REF]. The vocabulary and the case base rely on two knowledge models, the domain and case models respectively.

Domain Model

This model represents the knowledge about safety barriers, our current domain of application, in an ontological structure. Following the classification proposed by Oberle [START_REF] Oberle | Ontologies. In: Semantic Management of Middleware[END_REF], we hâve developed two types of ontologies : a core ontology that contains generic concepts about industrial safety such as EQUIPMENT, DANGEROUS PHENOMENON, SAFETY BARRIER, EFFECT, etc. A domain ontology describing the domain of safety barriers, in particular gas sensors. Its concepts are specializations of other concepts of the core ontology, and contains concepts such as: GAS SENSOR, SAFETY FUNCTION, ENVIRONMENTAL CONDITION, etc. Ontologies are represented in OWL Lite and hâve been developed by several experts of the INERIS, the French national expertise institute on industrial safety, with the help of an ontology expert [START_REF] Abou Assali | Ontology development for industrial risk analysis[END_REF].

Case Model

A case in our System represents a diagnosis expérience, and thus consists of three main parts: a description part describing the context of the expérience, a failure mode part describing the type of failure, and a cause part describing the différent possible causes of this failure. A case in gênerai is described by a pair (problem, solution). Accordingly, the description and failure mode parts of our model correspond to the problem part, and the cause part corresponds to the solution part. Inspired by the approach of JCOLIBRI, in order to enhance the communication between the case base and the domain model, the case model is represented within an ontology that intégrâtes the domain model. This ontology contains the main following concepts (Figure 1): 1) CBR-CASE that subsumes the various case types that may exist in the System; 2) CBR-DESCRIPTION that subsumes the case main parts, failure mode and cause; and 3) CBR-INDEX allowing to integrate the domain model concepts used to describe cases. Cases are thus represented by instances of the ontology and can hâve two types of attributes: Simple attributes corresponding to data-type properties of Fig. 1. Case model the ontology, and Complex attributes corresponding to instances of the ontology that hâve, in turn, their own simple properties. In the case authoring phase, we realized that cases do not share always the same attributes. Thanks to the developed platform, experts were allowed to use any concept from the domain model to describe their cases [START_REF] Abou Assali | COBRA: Une plateforme de RàPC basée sur des ontologies[END_REF]. This led to a heterogeneous case base, which complicated the case retrieval phase.

Case Retrieval

In this phase, similarity measures are employed to retrieve similar cases for a user query. Generally, with object-oriented case structures, similarity measures follow the "local-global principle" [START_REF] Bergmann | Similarity measures for object-oriented case représentations[END_REF][START_REF] Richter | Similarity. In: Case-Based Reasoning on Images and Signais[END_REF]. This principle is followed in our work since cases are represented by instances of the ontology. The similarity computation of two ontology concepts can be divided into two components [START_REF] Bergmann | Similarity measures for object-oriented case représentations[END_REF][START_REF] Recio-Garcia | Ontology based CBR with jCOLIBRI[END_REF]: a conceptbased similarity that dépends on the location of concepts in the ontology, and a slot-based similarity that dépends on the fillers of the common attributes between the compared objects.

Weighted Similarity Measures

Sometimes, query attributes may not hâve the same importance (weight) in the similarity computation. In this work, weights can be assigned to simple attributes (IGNORE or EXACT), and/or to complex attributes (in the interval [0, 1]).

Let Q = {qi : 1 < i < n,n G N*} be the user query, where </j is a simple or a complex attribute, and let il = {Cj : 1 < j < k, k G N*} be the case base, where Cj = {CJI : 1 < / < mj,nij G N*}. The concept-based similarity measure, sim cp t, is defined as follows: For each complex attribute, q & Q and c G C,

2*prof(LCS(g,c))

svm cpt {q, c)=w q * -- -- (1

) prof(q) + prof(c)

where w q is the weight assigned to q, prof is the depth of a concept (or an instance) in the ontology hierarchy, and LCS is the Least Common Subsumer concept of two instances. In a spécial case, when q and c represent the same instance in the ontology, we hâve: prof(LCS(q, c)) = prof(q).

The slot-based similarity measure, sim s i t is defîned as follows:

sim slt {q, c) = sfc | (2)

I O5 I

where CS is the set of common simple attributes of q and c, \CS\ is the set cardinality, q.s (or es) represents the simple attribute s of q (or c), and sim(q.s, es) is the similarity measure between the two simple attributes. For the moment, we consider only the first two weights (IGNORE, EXACT), and thus sim(q.s,c.s) can be defined as:

. , . f 1 if (w q , s = exact) A (v q , s = v c , s ) sim(q.s,c.s) = < .1, • ' [0 otherwise where w q , s is the weight of the simple attribute q.s, and v q , s is its value. Now, it is time to define the global similarity measure of the two complex attributes, q and c, which is given by the following formula [START_REF] Zhang | Weighted Ontology-Based Search Exploiting Semantic Similarity[END_REF]:

sim{q, c) = (1 -a) * sim cpt (q, c) + a * sim s i t (q, c) ( 3
)
where a is an expérience parameter (at présent, a = 0.4).

To compute the similarity between a case and a given query, each complex attribute of the query is compared to its corresponding attribute in the case. In homogeneous case bases, ail cases share the same predefmed structure, and thus, corresponding complex attributes are already identified. On the other side, heterogeneous case bases contain cases with différent structures. Therefore, before Computing the similarity, we need to détermine the corresponding complex attributes.

For each complex attribute q' G Q, let c' G Cj be the corresponding complex attribute in the case Cj G Q. To détermine c', we considered first that it is the attribute with which q' has the maximum similarity in the case Cj :

sim(q',c')= max (sim(q', Cji)) (4)
However, we realized that this définition of corresponding attribute is not sufncient, and that more conditions must be satisfied. The problem is that c' may hâve a maximum similarity with q 1 while, in reality, q 1 may hâve no corresponding attribute in Cj. The first improvement that we propose is to compare the obtained similarity sim(q', c') with the maximum similarity obtained for q' within the whole case base. This leads to the following condition:

1 vT > I 3 ( 5 )
where (3 is a spécifie threshold calculated after expérimentations (/? = 0.6). This condition led to better results, but it was not however sufncient in spécial cases. Thus, we propose to consider the following interesting notions:

Similarity Régions

We consider that the similarity measures are not always applicable to each pair of concepts (or instances) of the ontology. For example, a gas instance must not be comparée! at ail with an equipment instance. To prevent such comparisons, we propose to define the notion of similarity régions. A similarity région is a subbranch of the ontology hierarchy where concepts and instances are comparable with each other (Figure 2). The définition of such régions is manual and dépends on the target application. To compute the similarity between a query attribute and a case attribute, it must be verified first if thèse two attributes belong to the same similarity région.

Rôles of Attributes

For a given query attribute, several corresponding attributes may be found sometimes. Let's take, for example, the following excerpt of a case description: "At an industrial site, an infrared sensor was used to detect the méthane. Other gases were présent at the site such as the hydrogen. The sensor did not work as expected, and there was an explosion consequently". Now, let's suppose a query looking for cases where a gas sensor was used to detect the hydrogen. Following the approach presented till now, we find that the hydrogen of the case is the attribute corresponding to the hydrogen of the query. However, it is not the aimed resuit since we look for the hydrogen when it is the gas to be detected, which means that its actual corresponding attribute must be the méthane.

To solve this ambiguity, we propose to describe the rôle of case attributes that may give rise to ambiguous situations. For example, the hydrogen of the case is a gas présent at site, and the méthane is the gas to be detected. Thus, attributes that hâve same rôles are identified first. Then, for the other attributes, we follow the proposed approach (Formulas (4), [START_REF] Diaz-Agudo | An architecture for knowledge intensive CBR Systems[END_REF] along with similarity régions). This work led to the development of COBRA, a domain-independent CBR platform, as a JAVA application (Figure 3). It is based on JCOLIBRI, but it extends it with a layer that allows the treatment of dynamic and heterogeneous case bases. Thanks to the platform architecture, developing a new CBR System is made by supplying its domain ontology and reconfiguring some XML files. COBRA is used currently for two parallel objectives: to capitalize knowledge about gas sensor failures, and to provide support to experts and safety engineers to diagnose failure causes of gas sensors in industrial conditions. Experts can use any concept or instance of the domain model to describe their cases, which leads to a heterogeneous case base. Cases heterogeneity implicated that corresponding complex attributes, between a query and other cases, are complicated to identify. In this paper, we introduced the notions of similarity régions and attributes' rôles to overcome this problem.

Fig. 3. COBRA platform

To evaluate the proposed approach, cases hâve been added to the case base. They correspond to real situations observed in industry or to tests realized in the INERIS during campaigns for qualification of sensors. Thèse cases allowed us to do a preliminary validation of the case retrieval phase, which gave very satisfying results. The validation has been done to show the quality of results when adopting each of the improvements proposed; i.e., Formula 5, similarity régions, and attributes' rôles. We hâve also developed the "diagnose" phase of the CBR processes (out of the paper's scope). Then, more complex cases hâve to be added to the case base to allow validating our System. This validation will be done by experts at two levels:

-the first level concerns the CBR architecture: to what end the case structure and the reasoning processes are close to the real experts' activity? What other concepts should be added to the ontology? etc.

-the second level concerns the quality of diagnosis returned by the System for some given queries.

Fig. 2 .

 2 Fig. 2. Example of similarity régions

COBRA ArchitectureSeveral CBR architectures hâve been presented in the literature[START_REF] Aamodt | Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches[END_REF][START_REF] Lamontagne | Raisonnement à base de cas textuels: Etat de l'art et perspectives[END_REF]. Inspired by thèse architectures, COBRA architecture is composed of two main layers[START_REF] Abou Assali | COBRA: Une plateforme de RàPC basée sur des ontologies[END_REF]:-Processes layer: it contains the off-line process, case authoring, along with the reasoning processes: ELABORATE, RETRIEVE, DIAGNOSE, ENRICH, REVISE,

Acknowledgments. The présent work lias received the financial support of the Prench Ministry of Ecology and sustainable development. The authors also thank Mr. Sébastien Bouchet (INERIS) for his active participation to the development of the gas sensor ontology and the case base.