Alain Rousseau
email: alain.rousseau@seftim.fr

Pierre Gruet
email: pierre.gruet@ineris.fr

Seftim Ineris

APPLICATION OF IEC 62305-2 RISK ANALYSIS STANDARD IN FRANCE

France standard board (UTE) has published IEC/EN 62305-2 in January 2005, more than one year before publication of the standard at IEC or EN level. Purpose was to gain experience when the voting stage occurred for this standard in 2006. UTE has also developped a specific software to apply this risk assessment methode. By now we have more than 2 years of application of both standard and software. The software called Jupiter is just a tool but it helps a lot in introducing data and making easy calculations. This software introduces features such as drawing of the building to calculate accurate collection areas, design of the lines and of circuitry inside the building, evaluation of fire risk existing inside the structure, accurate selection of the needed SPDs as well as an automatic provider of protection solution. This means that studies for simple building may be done by contractors when more complete studies still need to be done by experts but their task becomes a lot easier. This is perfectly in line with the Qualifoudre qualification scheme introduced by INERIS in France. We have now applied this risk method on a large amount of structures with various risks (explosive, radioactive, fire ...). Purpose of this paper is to share this experience and to discuss applicability of some parameters introduced in the standard IEC/EN 62305-2.

INTRODUCTION

IEC 62305-2 standard for risk assessment has been published in Europe as EN 62305-2, at the latest by October 2006 depending on the countries. When the standard can be implemented or not at IEC level it has to be implemented by law in Europe. France has decided to remove immediately all his previous risk evaluation methods as early as April 2006. This standard is part of the group of new standards that IEC TC81 (International Electrical Commission -technical committee N°81 in charge of lightning protection of structures) has released. 62305-1 deals with general information regarding lightning 62305-2 deals with risk assessment : do I need protection and if answer is yes which one ? 62305-3 deals with lightning protection systems (LPS) : how to set-up such a system and select its components ? 62305-4 deals with lightning electromagnetic pulse (LEMP) : how to set-up and design shields and bonding as well as selection of SPDs (surge protective device) used for equipotentiality ? France was using so far its own standards for risk (either risk against direct lightning NFC 17-100 or risk against induced surges C 15-443. From time to time we were also using IEC 61662 (ancestor of IEC 62305-2) for complex sites such as military or nuclear plants. Recognizing that method described in 62305-2 is more powerful and consistent than previous methods, French National Committee has decided to publish EN 62305-2 in a draft mature version in January 2005 under number 17-100-2. Purpose of this was to get experience on this method and been able to make comments and propose improvements especially at CENELEC level. Since publication of this document the method has been extensively applied by the authors on many site including chemical sites, explosive sites as well as other industrial sites.

IEC/EN 62305-METHOD

The new method is not so different in essence from the original one (IEC 61662) but many parameters have been refined. Opposed to other French methods, this one is purely based on probabilistic calculations and the parameters are coming from international scientific studies which have been largely documented and published (SIPDA, ICLP ...). This is very important as users of the method are sometimes suspicious of the validty of some parameters. economic value (structure and its content, service and loss of activity). For each of this loss a risk is defined. The total risk is then calculated has a sum of risk components defined below : Risk component for a structure due to flashes direct to the structure :

• RA: component related to injuries of living beings caused by touch and step voltages in the zones up to 3 m outside the structure;

• RB: component related to physical damage caused by dangerous sparking inside the structure triggering fire or explosion, which may also endanger the environment;

• RC: component related to failure of internal systems caused by LEMP; Risk component for a structure due to flashes near the structure :

• RM: component related to failure of internal systems caused by LEMP; Risk components for a structure due to flashes to a service connected to the structure :

• RU: component related to injuries of living beings caused by touch voltage inside the structure, due to lightning current injected in a line entering the structure.

• RV: component related to physical damage (fire or explosion triggered by dangerous sparking between external installation and metallic parts generally at the entrance point of the line into the structure) due to lightning current transmitted through or along incoming services;

• RW: component related to failure of internal systems caused by overvoltages induced on incoming lines and transmitted to the structure.;

Risk component for a structure due to flashes near a service connected to the structure • RZ: component related to failure of internal systems caused by overvoltages induced on incoming lines and transmitted to the structure;

For each of the risk associated to the 4 types of losses (called R1 to R4) and which need to be considered for the studied structure, the total risk will be calculated as a sum of the above described risk components. Each of the risk components itself will be calculated by using the generic formula given below R X = N X PXLX N X is the number of dangerous events for that risk P X is the probability of damage for that risk; L X is the consequent loss for that risk And X can take the values A, B, C, M, U, V, W or Z The risk component is defined as the number of lightning strikes on the building multiplied by the probability that this strike lead to a damage (hopefully not all strikes will create a damage) and multiplied by a loss factor taking care of the amount of losses (how many people are possibly injured, what are the possible protection measures) For risk R1 to R3 the total risk need to be lower than the acceptable risk RT given in the standard. For risk R4 there is no tolerable risk as the economic perception is different from a small company to a large group. Calculation is then made by comparing annual amount of losses without protection, annual amount of residual losses as soon as protection measures are implemented and annual cost of protection measures taking care of maintenance. The result is then an annual saving for the owner of the structure.

Let's imagine a telecom center (service to the public) which is located inside a building which is a national heritage. The owner of the building is willing to know if lightning protection will provide some savings to him. In addition, risk for loss of human life needs to be considered as there are some people inside (workers and customers). In such case risk R1, R2, R3 and R4 will be calculated. For each of the risk the appropriate protection measures may differ. For the simplest case of a building where only protection of human being is considered then only R1 will be calculated. R1 is also the risk which is calculated for sites where environemtal risk need to be addressed.

When risk cannot be sufficiently reduced, it is possible to defined specific zones inside the building to better protect the areas which are the more dangerous and avoid overprotecting the complete building.

TOOLS DEVELOPED TO APPLY THIS METHOD

As previously mentioned, this IEC standard became a French document in January 2005. As such it is used and will be used more and more and will replace existing documents dealing with the same topic. To allow the use of this standard for most of the lightning professionals it has been decided to provide tools to the user in order to facilitate his job. These tools are described below.

Forms

INERIS has developed in France a qualification for lightning protection professionals. This is called Qualifoudre. Under this qualification scheme, a professional can claim expertise for site survey, production of lightning protection equipment, set-up of protection measures and control of installations. His expertise in the selected field is attested by a letter which can be S for professional being able to work on simple structures (a house, small office) or C for complex structures (chemical plant for example) or even I for intermediate ones (not a simple nor a complex structure).

The qualification is approved by the Lightning Protection Association (APF), the Ministry of ecology, the Ministery of defense and the Federation of the insurance companies.

For companies which are claiming study capability "C" their ability to use UTE C 17-100-2 risk method needs to be proved. Under the Qualifoudre scheme many helping tools are provided to qualified companies, one of them being a form to facilitate on site data collection. As a matter of fact, the new method needs a better cooperation between the plant manager and the lightning engineer. This form (which is sent prior to the survey to the plant manager) is then useful to be sure that there is no misunderstanding on the amount of time the plant technicians need to involve for that action from one side and to be sure that, on the other side, at data collection time, no parameters is forgotten by the lightning engineer In addition, under the Qualifoudre banner, an internet forum offers possibility to the users of the method to exchange on problems encountered or even to ask for some help.

Jupiter software

The software is taking into account all the parameters described in the standard and offer to the user practical facilities such as the possibility to test immediately various possible protection means effect and selection of the most convenient one. Based on the data collected on site, the parameters describing the structure can be filled. There are interesting features in the software such as true calculation of the collection area taking care of real dimensions or evaluation based on fire brigade rules of the fire risk. Z^l" Ï !

7"

"""" "": ::::: As it can been seen there is a graphic display of the conclusions of the analysis : the building is not self protected. The user of the software should then introduced protection measures in order to bring the total risk below the red bottom line (tolerable risk) Fig. 3. Typical screen where the protection measures have been implemented

J co'al-JM-OOEOL.,. ooEQl.. 27E-10L. • • • • • • • • • • \ } -t---
With this software you also have access to many features. One of them is the green/red color code. Every risk component which is red is greater than tolerable risk. It is green in the other case. It is then very easy to determine the part or the zone of structure which needs a special care. This is reported on a specific screen where influence of each zone can be appreciated.

.

-. x •r • • < •r • • < ZÎ "•• .ff J . . . .- "• ,| • tilr 1 k I to • * !

Fig. 4. Influence of various zones on the total risk

The software propose some protection solution in an automatic way that the user can use or not. The economic evaluation and selection of appropriate SPD is also very easy due to a large data base of parameters and cost that the user can manage by himself based on his own experience.

APPLICATION OF JUPITER ON EXPLOSIVE SITES

.Sometimes the danger is very high and the potential damages are important. It is the case for installations with risk of explosion and with people in the lethal zone. If the duration of the risk of explosion is not well indicated, the calculated risk can be overestimated. In this case, it happens that the addition of protections with the best possible effectiveness does not reduce the risk under the tolerable value of 10 -5 . This too huge risk will in fact mask the other risk which even if less important are not minors. A good example is the risk of fire which is often present when there is explosive risk. It is then necessary to consider 2 situations: a normal situation during which the risk is for example the risk fire and a degraded situation where explosion can occur.

Let us suppose that the building to be protected is a warehouse storing solvent. Storage is very flammable and the interior of the building is classified ATEX (level 2) which means explosive atmosphere for short durations not exceeding a cumulative annual time of 100 hours. As the fire risk is present for 1 800 hours we need to consider this duration. But, by considering that storage is explosive and that the people are present in the zone during 1800 hours (even if the potential explosive risk is present for only 100 hours), the risk cannot be reduced with best available protections means. Calculation must then be carried out for 2 situations. In normal situation only the fire risk is considered and duration is 1 800 hours. It is possible to use protection means to reduce the risk to a tolerable value. In degraded situation, the explosion risk is considered but the duration of presence of the people in the zone at the risk is only 100 hours.

Figure 8 shows that the risk calculated for duration of 100 hours with explosive atmosphere is lower than the tolerable value. The probability that the lightning strikes the warehouse and be the trigger of an explosion is low due to the short duration of 100 hours.

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•;-• lît.îh iJ M : 12 10 -7 ÉJ 1

Fig. 8. Whithout protection measures but duration 100 h

When calculation is carried out for various situations, it is then necessary to install the protection means which reduce the risk in all the cases. In the above example, the protection means which reduces the risk as in figure 7 meets the need.

NEED FOR CLARIFICATION

No doubt that IEC/EN 62305-2) is a powerful tool. However, it is needed to clarify a few things to cover all the needs of the French lightning protection community (and perhaps of other countries too). More than 150 buildings have been studied in France using UTE C 17-100-2 method over a period of 2 year. Plants had different characteristics and covered a wide range of industrial site and buildings. Based on application of the method on a large number of cases it appeared that a few parameters needed to be better defined.

SPDs

There is no relationship between SPD characteristics and probability values that you can select in the standard. Of course, when you are an expert you know how to select the appropriate SPD and if one SPD is better than another. But who is really able to select the probability associated with an SPD which is behaving better than the requirements given by the calculation. An SPD protecting at 1 kV for a fixed value of current offers a better protection than an SPD protecting at 1,5 kV for the same value of current. How can we quantify this? If the needed protection level is 1,5 kV and the needed lightning discharge capacity is 10 kA 10/350 who could say which of the following SPDs is the best? SPD1 has a current capability of 40 kA 10/350 and protective level of 1,5 kV. SPD2 has a current capability of 15 kA 10/350 only but a protective level of 1 kV. It is already not easy to say what is the best choice but it is furthermore difficult to associate probabilities to both. Mainly the document is related to probabilities associated to currents withstand which is probably one of the good parameter to avoid flashover problems at the entrance of installation (but not the only one) but which is quite irrelevant when downstream protection is needed (coordinated SPDs). In addition, to mix SPD with lightning protection level of the LPS creates confusion. What to do when there is no LPS and direct lightning is not relevant? SPD are clarified in Europe by type related to testing capabilities.

To have a SPD Type 1 (the one used in case of LPS) defined for a lightning protection level 3 for example can only create confusion. Better coordination is needed between LPS and SPD standards and SPD probabilities should be better defined in the risk standard. Jupiter provides some tools to help selecting appropriate SPDs but the standard should be more detailed regarding this issue and avoid confusion in the head of the reader.

Concept of coordinated SPDs

You need to use SPDs in front of each sensitive equipment and SPDs should all be coordinated together. But if you use only entrance SPDs (SPDs for equipotentiality) and other SPDs in front of a particular zone (with a high fire risk for example) are you complying with criteria to consider you have a coordinated system? It seems that it is not the case based on present definition when in practice such a protection at needed place will be sufficient.

Shielding of cables

The key parameter is the shield resistance. Who is able to give this value in practice? Surely not the electrical technician responsible for the building. Should we make measurements? Try to locate the manufacturer reference number and try to get data from him? If you have many days in front of view it is perhaps possible but for most of the cases a simplification is needed. This non practicality will lead countries to develop alternative method for their contractors and this approach is going against the initial target.

Number of people injured inside a building in case of a lightning strike

In some cases this data can be obtained from discussions between the structure owner or manager and the lightning expert but in a lot of other cases this is quite difficult to achieve. If you use the generic values proposed by the standard you will get a protection scheme which is clearly over designed. In some cases you will not be able to reduce the risk below the tolerable risk and this means according to the French law that you may not be able to run your plant! The only remaining solution is then to install storm detectors and stop this critical activity during stormy periods.

External zones

They are only considered for the risk of touch and step voltage. But if you have an explosive area in the building or if you store dangerous products with possible impact on environment it is likely that people outside the building will be injured and not due to step and touch voltage. This needs to be considered. In addition, when a toxic cloud is released to the atmosphere in case of surges generated by a lightning strike, how should we consider the number of people potentially injured? 1 000, possibly more ... This should be better defined in the standard. In the same way, if a truck is bringing explosive material from the outside, its presence outside of the building should be also taking into account in the explosive risk. Protection of external zone should take into account other aspects than the pure risk of touch and step voltage.

Storm detectors

So far, the only solution in some cases to reduce the risk below tolerable risk is to use a storm detector. Simple way of doing so is to consider that there is nobody in the dangerous zone in such a case (once again this does not cover the risk of people being outside the building or of a released chemical cloud spreading around). But in fact, a storm detector has also an efficiency. It may not detect 100% of all storms. In some cases, the user will change the settings in order to avoid too many false alarms leading to a detection ratio of less than 100%. In such a case, such a ratio cannot be introduced in the method. Of course, there is no standard for such storm detectors so far in spite of some attempt in France and at Cenelec level, but we cannot ignored such a tool for the risk evaluation and a probability should be associated to it in the same way it is for SPDs or LPS.

CONCLUSIONS

French national committee has decided in January 2005 to implement the draft international standard IEC 62305-2 into a French document. This is clearly supported by most of the actors and especially INERIS which has included this requirement in his qualification scheme named Qualifoudre. To support this development, tools have been developed and UTE, the French electrical standard body, has developed a powerful software named Jupiter. This will allow a greater number of people to use the method. At the same time, to allow this general use, a few parameters need to be clarified. They are accessible to the lightning expert, even if in some cases it may be quite difficult to get the data or relate these data to probability values. But for less skilled users, the task may be discouraging. The risk calculation being so powerful it should be a pity to not make the necessary clarifications which will make this document the only reference in lightning risk management.

Fig. 1 .

 1 Fig. 1. First page (example) of Qualifoudre data collection form

Fig. 1 .

 1 Fig. 1. Exemple of calculation of the collection areaWhen the data regarding the structure and its connected services are introduced the risk calculation can start. This lead to a diagram as in Figure2.

Fig. 2 .

 2 Fig. 2. Typical screen where the protection measures have not been implemented

Fig. 5 .

 5 Fig. 5. Protection measures have not been implemented

  Fig. 6. Best protection measures have been implemented

Table 1 :

 1 Typical values of tolerable risk RT

	Types of loss	RT (year-1)
	Loss of human life (R1)	1(T 5
	Loss of service to the public	1(T 3
	(R2) and Loss of cultural
	heritage (R3)

Table 2 :

 2 Data collection form

	Data collection form of a structure
	to be protected against lightning
	STRUCTURE (N°, name, function)	B1
	Dimensions (Length, width, maximum	20x20x10
	height, height of chimney)	m
	Relative situation of the structure	Isolated
	Number of floor	1
	Type of wall (concrete, metal, wood...)	Concrete
	Type of roof (concrete, metal, asbestos	Tiles
	cement, tile...)
	Type of soil inside structure (concrete,	Concrete
	linoleum, wood...)
	Distance between the metal frame	2m
	Resistivity of the ground (ohm.m)	300 Q..m
	Type of soil (clay, granite, silica, humus...)	Clay
	Are metal part equipotentially bonded ?	Yes
	Are reinforcements of the concrete	0,2
	connected into a mesh ? (mesh size ?)
	Numbers of electrodes for lightning earth.	2
	Surge counters (indication on the counter)	1(0)
	Installation of SPDs on the powerlines (type	Type	1
	of protection, state).	SPDs
	Fire protection (simple detection, automatic	Manual fire
	extinction, extinguisher, presence of	extingui-
	fireman or time before their intervention)	shers

sources of damage are defined : flashes to a structure, flashes near a structure, flashes to a service and flashes near a service. 3 types of damages are defined : injuries to living beings; physical damage (damage to the structure i.e. destruction by direct hit, fire, explosion ...) and failures of electrical equipments. 4 types of losses are defined : loss of human life, loss of service to the public, loss of cultural heritage and loss of


E Klein

ALomax A Lomax

3D Acoustic and Microseismic Location of Collapse Events in Complex, 3D Geological Structures

Scientific), A. Lizeur (INERIS), F

Introduction

Passive microseismics is a well developed technique that has been widely used since the 1970s and 1980s in active underground mines to monitor stress changes around the workings and in geothermal fields to image fracture networks activated during production and injection. In addition, application of this technique to petroleum characterization has been increasing in the past decade following its successful use on the Barnett Shale in the Fort Worth basin, Texas [START_REF] Jones | Petroleum reservoir characterization using downhole microseismic monitoring[END_REF]. Real-time microseismic monitoring and more recently acoustic monitoring of underground silent voids is also often included in early-warning systems dealing with geohazards (Contrucci et al, 2010a;[START_REF] Nadim | Monitoring of ground failures in subsurface complex cavities[END_REF].

Event location is of primary importance to accurately identify the zones of rupture and determine source characteristics such as magnitude or moment tensor. For a mine geometry, this location requires taking into account complex velocity models with direct-search event location methods. For the case of acoustic monitoring it can be assumed that the acoustic waves do not transmit through the host rock, so their propagation is governed by reflection and diffraction at the cavity boundaries. This leads to a complex travel-time field that can be modelled based on the same algorithms as those used currently in microseismics.

In this extended abstract we first present a fast marching method to determine the travel-time field, rays and ray take-off angles in complex 3D media, for application with direct-search event location methods. We then present a series of examples to illustrate the potential of the chosen methodology using a 2D model based on the geometry of an abandoned salt mine instrumented with dual microseismic -acoustic stations. Finally, we discuss further applications on 3D complex structures.

Event location in 3D complex media with a few numbers of sensors

Among the three basic classes of methods to calculate travel-times and rays (full-waveform methods, ray methods, and eikonal and shortest-path, graph-based methods), the eikonal fast-marching method (FMM) is one of the most efficient and stable when considering complicated 3D velocity structures. FMM solves the wavefront propagation problem through numerical solution of the eikonal equation for ray propagation, with repeated application of Huygen's principle while taking into account causality -that is to say that information only flows forward in time [START_REF] Sethian | Level set methods and fast marching methods[END_REF]. This condition makes the method unconditionally stable in the presence of shadow zones, diffractions and caustics, and also makes it applicable to 2D and 3D regular and irregular grids.

In addition to the generation of the travel-times from one point in a gridded velocity model to all others points in the model, FMM also permits the calculation of ray-paths and take-off angles through post-processing of the travel-time field using finite-differences to follow the local time gradient back from the receiver to the source. This is of great importance for improving microseismic locations when using only a small numbers of sensors. Take-off angles measured at a 3D receiver are useful to constraint direct search event location method, especially in limited-aperture situations like borehole monitoring.

Application to the case of an abandoned salt mine

An abandoned room and pillar salt mine located below an urbanized area has been instrumented in 2005 by INERIS [START_REF] Nadim | Monitoring of ground failures in subsurface complex cavities[END_REF]. The mine can approximately be circumscribed into a 300 meters * 350 meters area with regular and large galleries (-17 meters wide and 6 meters high), with an approximated total of 360 pillars (-15 meters large * 15meters wide) cut by around 20 km of cumulated intersecting galleries and an extraction ratio close to 75%.

Three dual acoustic-microseismic stations have been set up in different locations with the aim of detecting precursory signals of fracturing that may lead to a roof collapse process. Each station is composed of a highly sensitive microphone installed in a gallery and of a geophone clamped above in the solid part of the roof, both sensors being equipped with built-in amplifiers. The objective of the monitoring system is to alert if a significant event occurs between two inspection visits, triggering then an extra inspection.

To analyze acoustic wave propagation and assess the resolution of FMM along with the Oct-Tree direct-search location method [START_REF] Lomax | Fast, probabilistic earthquake location in 3D models using oct-tree importance sampling[END_REF] in the context of the abandoned salt mine, we consider various virtual geometries of sensors and collapse events.

First we consider an ideal situation with a dense and regular receiver distribution (acoustic sensors are placed at every second gallery intersection). In Figure 1 (left), the reverse travel-time field is computed for a receiver in the third gallery from the West and first gallery from the South; the acoustic travel-time field is constrained to not transmit into the host rock (pillars). It shows that the travel-time field is almost circular, due to the regular geometry of the mine and large proportion of void space however, the diffractions around the pillars are visible as cusps and perturbations in the travel-time field (Figure 1-Left). Then, given this ideal geometry and synthetic arrival-times with 0.01s noise corresponding to events throughout the site, we observe a good ability to relocate correctly the synthetic events: stations are available at a wide range of distances and directions enabling good constraint on the location (Figure 1-Right). At the boundaries of the site the pdf locations can be elongated or irregular, with some significant mislocations, due to the absence of stations outside of the modeled area and consequent poor station coverage.

In general, within the station network the maximum likelihood hypocenter is very close to the theoretical hypocenter almost every time, with close coincidence near the centre of the network.

Practically, for costs and technical reasons, monitoring devices often comprise only a few numbers of receivers, sometimes positioned far away from the area of interest due to difficult access conditions. Thus the receiver distribution is often very poor.

When relocating a theoretical event while considering a poor receiver distribution with few stations near the source, the location pdf increases in volume . Besides, a discrepancy in the relocation is observed: the event is located in a gallery intersection adjacent to the intersection where the theoretical event was placed. When considering few stations irregularly dispersed across the site (Figure 2-Right), the /«//locations remain quite well constrained in areas surrounded by receivers, thanks to the aperture of the available stations. The pdfs increase in volume and become more complex for events occurring outside of the network (southeast corner for example) indicating low confidence in event location: in some configurations, it becomes difficult to locate the source at the scale of the mine quarter.

Further application: the monitoring of a large-scale cavern collapse

Between 2005 and 2009, a solution mine was instrumented in order to monitor a large-scale cavern collapse (see Figure 3 and Contrucci et al, 2010b for full detail). It allowed the recording of the unique microseismic database comprising more than 60 000 events, including 30 000 events during the last three days preceding the collapse.

Until now, a ID velocity model was used to process the data and locate the events. This velocity model was estimated using a series of calibration shots made on the surface at the beginning of the experiment in 2005. For computational convenience, the model was taken as fixed during the whole experiment.

The geology of the site however considerably evolved along with the cavern extension, leading to a for more complex velocity model. First, massive roof falls occurred due to the failure of the indurated anhydrites overlying the salt layer allowing vertical propagation of cavern dome the towards the surface. Second, the rupture of a massive and competent bed of dolomite overlying the cavern at -120 meters depth led 24 hours later to the general collapse of the overburden [START_REF] Contrucci | Multi-parameter monitoring of a solution mining cavern collapse: first insight of precursors[END_REF].

Figure 1 .

 1 Figure 1. Left) Travel-time field computed when considering a receiver placed in the third gallery starting from the West and first gallery from the South. Right) Location of events throughout the site obtained using the ideal array geometry. Stations are represented by black triangles, true and calculated locations are represented respectively by green and blue symbols; the location pdf is shown in red (red cloud of points).

Figure 2 .

 2 Figure 2. Left) Location of an event occurring in the upper right corner of the site obtained using a poor receiver distribution. Right) Several locations using a dispersed and irregular receiver distribution. Stations are represented by black triangles, true and calculated locations are represented respectively by green and blue symbols; the location pdf is shown in red (red cloud of points).

The fixed velocity model assumption undoubtedly leads to strong location errors, especially during the last days of the experiment. Also, it almost prohibits the use of S-arrivals in the location process, since the computed travel-time field does not take into the increasing volume of brine in the cavern which clearly affects S-wave propagation.

Thus the possibility of using an evolving, 3D model would help to reduce the location errors and improve the analysis


E Klein

Mining Induced Seismicity -Monitoring of a Large Scale Salt Cavern Collapse

Ineris), I. Contrucci (Ineris), NT. Cao (Ineris) & P. Bigarre (Ineris

Introduction

Nowadays, risk management and mitigation related to underground extraction raises more than ever complex issues related to a constant increase in people's vulnerability induced by societal humandetermined paths of development. The instability of these underground works, especially when they are extended, may indeed result in the appearance of settlement, residual subsidence, localized or generalized collapse, potentially with significant social and economic impacts.

Thus, to improve our understanding in large scale ground failure phenomenon induced by underground mining works, a field experiment was undertaken by the partners of GISOS (a consortium of public organizations that includes INERIS and focusing research resources on underground geostructures) in collaboration with the SOLVAY company: a solution mine located in the Lorraine salt basin (at Cerville-Buissoncourt southwards from Nancy, France) was instrumented in 2004 previously to its collapse which was triggered in February 2009, as part of the mining scheme. To monitor the cavern collapse a permanent multi-parameter monitoring system featuring high resolution microseismic along with surface leveling monitoring was set up.

In this extended abstract, we first describe the on-site instrumentation installed by INERIS and present the data collected during this experimentation. We will then see that this unique dataset enables to accurately identify the main stages in the evolution of the solution mine up and help to demonstrate the full capability of multi-parameter monitoring and on-line expertise to enhance the risk management strategy in this domain.

Site description and instrumentation layout

The geology of the site is characterized by a succession of sub-horizontal layers from the ground surface down to the salt deposit which lies between 180 and 260 m depth. The overburden consists in (1) alternating layers of clay-sandstone-marl up to a depth of -123 m; (2) a massive, stiff and slightly fractured competent bed of dolomite and anhydrites (known as Beaumont dolomite layer), -8.5 m thick; (3) -60 m of marls with more or less indurated anhydrites; (4) the salt layer underlying to a depth of -280 meters.

The salt mining method set-up by SOLVAY consists in producing brine by intensive dissolution using the "channel and drilling method" (Figure 1-a-b). This technique relies on the injection of fresh water (or recycle brine) through dedicated wells placed upstream of two parallel lines of solution mining wells that reach the bottom of the salt deposit. Brine is extracted downstream. This technique leads to the formation of a cavern in line with the water injection drilling holes. It develops during operation until the cavern roof collapses (Figure 1-b). This ultimately results in the formation of a sinkhole that reaches the surface. The permanent monitoring system installed by INERIS based on a SYTGEM multi-parameter system is detailed in Contrucci et al. (2010a). It comprised (Figure 1-c): • A high resolution microseismic network made up of nine sensors including four 3D sensors, all equipped with miniature wideband geophones (40-1000 Hz) distributed on site and cemented into boreholes at depths of between 2 and 125 meters. • A surface leveling monitoring system comprising a motorised laser tacheometer measuring the position of 17 targets, aligned both inside and outside the subsidence area and two RTK (Real Time Kinematic) differential GPS stations (one placed on a stable zone, the second positioned at the very centre of the expected collapsing area).

The automatic on-line microseismic data processing was performed by the SYTMIS software from INERIS. It was parameterized on a routine basis included P-wave picking using an STA/LTA algorithm and 3D location of events based on a non-linear inversion method [START_REF] Contrucci | Management of post-mining large-scale ground failures: blast swarms field experiment for calibration of permanent microseismic early-warning systems[END_REF]).

In practice it was difficult to achieve reliable automatic on-line S-wave picking and thus improved 3D location, because far-field assumptions were not always valid during the experiment. In addition, some seismograms did not show any S arrivals: in such cases it was therefore difficult to define a criterion for no S-waves picking. For these reasons we chose not to use these S phases for automatic location. The velocity model used that comprised 3 layers, according to the geology (see Contrucci et al. 2010a for full details) was defined through statistic inversion of calibration data (shots carried out on surface in 2005).

The accuracy of +/-5 mm for the GPS-RTK measurements was obtained thanks to the short interreceiver distance and the high stacking. The data collected by the tacheometer, although strongly sensitive to meteorological variations, showed a similar precision for the closest targets when applying a simple moving average to a few measurement cycles, a) b)

Area of collapse

Brief overview of the dataset

Very few microseismic events were recorded until February 2008, except during two small microseismic surges in May 2007. From March 2008, the microseismic trend was marked by several episodes of important activity (more than 10,000 events recorded in few days) and a change in the background noise that reached around 25 events per day [START_REF] Klein | Experimental monitoring of a solution-mining Cavern in Salt: identifying and analyzing earlywarning signals prior to collapse[END_REF]. Besides, the spatial and time migrations of the microseismogenic zone indicated clearly a rather vertical development of the cavern dome along with an apparent lateral dissymmetry. These observations were confirmed by gamma ray well-logging showing that massive marls roof falls of ~ 500,000 m3 occurred between February and May 2008 with a transverse asymmetric roof elevation [START_REF] Klein | Experimental monitoring of a solution-mining Cavern in Salt: identifying and analyzing earlywarning signals prior to collapse[END_REF]. From that point, decision was taken to definitely close the surface access to the zone, even though no significant subsidence was observed. At that time, the upper part of the geological overburden was indeed showing a rather stiff elastic response. However, it was admitted that the cavern had reached its critical dimensions based on numerical modeling considerations and expertise (Contrucci et al. 2010a). To accelerate the collapse triggering, SOLVAY decided to progressively lower the brine level. Intensive brine extraction began on the 10th February 2009 at 7:00 am (local time) and continued until the general collapse, three days later, on the 13th February 2009 at 5:45 am (local time). Figure 2 shows the microseismic activity recorded during that period versus: (a) brine level and (b) subsidence. This figure also illustrates the extraction regime which was conducted into two main phases: 1-a first pumping stage with a decrease in the brine level by 50 meters; 2-quasi-continuous pumping up to the collapse between 400 and 600 m3/h up to the collapse. During the first day of pumping, neither significant microseismicity nor surface subsidence could be observed. The impact of the diminution of the brine level became really effective at the end of the second day [START_REF] Contrucci | Multi-parameter monitoring of a solution mining cavern collapse: first insight of precursors[END_REF]) with a sudden acceleration of the microseismic energy release rate, showing more than 1 500 events in one hour (Figure 2). This microseismic swarm coincided with a dynamic rise of 9 meters of the brine level and marked a change of the subsidence regime (Figure 2), which velocity reached then -0.02 m /h. Beyond that stage, the sustained microseismic activity increased rapidly faster than during any other period. From that point, the pumping regime was not powerful enough to compensate the brine level rise, at the extraction wells, due to the pressure applied on the system by the overburden. The major peak of activity occurred early the third day, when the cumulative subsidence reached -0.40 meters. It coincided first with loud acoustic noises heard on site and, later on, with the breakdown of the microseismic probe installed in the Beaumont dolomite bed at 125 meters depth. These observations along with on-line 3D location results show that this major peak of activity is related to the global failure of the Beaumont dolomite rock bed (Figure 3-a). This major peak was then followed by an acceleration phase of the subsidence rate, which ultimately reached 1 meter per hour (Contrucci et al. 2010a). Less than 24 hours later, the ground surface collapsed leading to a crater of -150 meters in diameter (Figure 3-b). More than 30,000 events were recorded during the last 4 days preceding the collapse. The last GPS measurements, during the ground collapse and flooding of the zone, indicated a cumulative subsidence of 4 meters in the center of the area (Figure 2). Figure 3-b shows a photo of the crater few days after the cavern collapse.

Conclusion

Although in-depth data processing is still going on, the complete dataset seems to highlight a probable global dual mechanism. First: deep, slow and barely detectable rock mass fracturing starting from the salt roof up to the Beaumont dolomite bed. This lasts around one year and can almost only be monitored by a high resolution microseismic system. Second: a brutal and sudden failure of the overburden up to the surface, over less than one day, well detected by the ground surface displacement system. This second and sudden stage occurs rapidly after the brittle failure of the Beaumont dolomite bed. If the complex and delayed behavior of this bed between these two stages is not obvious, it can undoubtedly be monitored by high resolution microseismic system. This experiment highlights the potential of microseismic monitoring as a useful tool to assess overburden damage and salt cavern evolution. Thus, to ensure in time actions for risk management strategy in such geological context, an early warning system should clearly focus on microseismicity prior to the Beaumont dolomite failure. Besides, this unique four year experiment also demonstrates the full capability of multi-parameter monitoring and on-line expertise to enhance the risk management strategy in this domain.

Figure 1

 1 Figure 1: a) View of the site before the collapse, b) Illustration of the "channel and drilling method ". c) Location of the multi-parameter monitoring network and simplified E-W geological section showing the position of the 3D microseismic probes (black symbols) and ID (unfilled symbols) with depth.

Figure 2 :

 2 Figure 2: Between the 10th and 13th February 2009: Top) brine level measured at the extraction well (1 km away from the cavern). Down) Number of microseismic events recorded per hour superimposed to surface subsidence measured by the GPS-RTK device.

Figure 3

 3 Figure 3: a) 3D view of the microseismic events between the first and the second surge of activity, b) Photo of the crater observed on site few days after the cavern collapse.


Maxime Mikikian
email: maxime.mikikian@univ-orleans.fr

Marjorie Cavarroc

Lénaïc Couëdel

Laïfa Boufendi

Low frequency instabilities during dust particle growth in a radio-frequency plasma

Keywords: numbers: 52.27.Lw, 52.35.-g, 52.25.Vy, 52.25.Gj, 52.35.Ra

In this paper, instabilities appearing in a dusty plasma are experimentally investigated. These low frequency self-excited instabilities appear during dust particle growth and are characterized by a frequency spectrum evolving during this process. Beginning, time evolution and main characteristics of these instabilities are investigated thanks to electrical and optical measurements. Both signals show a clear evolution scheme with a well-defined succession of phases. From the beginning to the end of this scheme, regular oscillations and/or chaotic regimes are observed. Finally, instabilities stop when the dust particle size reaches few hundreds of nanometers and a stable three-dimensional dust cloud is obtained. A dust free region called void is then usually observed in the plasma center.

I. INTRODUCTION

In a plasma, dust particles can be grown using reactive gases like silane [1][2][3] or by ion bombardment on materials [4][5][6][7][8][9]. This formation is actively studied due to strong consequences that can arise from the presence of dust in plasma processing reactors [10,11] for microelectronics where cleanliness is a major requirement [12]. Furthermore, the interest is actually increasing due to the fact that nanometer dust particles can be useful for industrial applications like solar cells [13] or memories [14]. Laboratory dusty plasmas are also a very efficient way to produce and study astrophysical dusty media like planet atmospheres [15]. In capacitively coupled radiofrequency discharges, a dense cloud of submicron dust particles filling the whole space between the electrodes can be obtained. During their growth, dust particles acquire a negative charge by attaching more and more electrons [16][17][18]. Consequently, the growth can be studied through its influence on the plasma characteristics and in particular on the discharge current harmonics. Indeed, the current third harmonic is a robust tool to accuratly follow and identify growth steps [19]. Dust particle growth strongly affects plasma properties and can induce plasma instabilities. Self-excited instabilities have been observed in silane plasmas [20] (frequencies of few kHz for dust particles of few nanometers) and also in dusty plasmas produced by sputtering a carbon target [7,8] (frequencies around 100 Hz for dust particles around hundred nanometers). In this last experiment, the authors describe two different instability modes called the filamentary mode and the great void mode. The first one appears approximately one minute after the plasma ignition and is characterized by a broadband spectrum centered around 100 Hz. It corresponds to a beamlike striation of dust density and plasma glow. As dust particles are still growing, this stage is then followed by the great void mode which corresponds to the formation of a dust free region called void [7,9,[21][22][23] and its ro-tation in a horizontal plane in between the electrodes. The void region is due to the equilibrium between various forces acting on the negatively charged dust particles. These forces are principally due to ion drag, electric fields, thermal gradients, gas flow and gravity, and they define the cloud shape. The ion drag force is presently actively studied because it is suspected to be the main responsible of the void formation [8,[24][25][26][27][28][29][30][31][32][33], pushing the dust particles away from the discharge center. In this paper, observations and analyses of instabilities appearing during dust particle growth are performed. These instabilities look like the filamentary and great void modes in some stage of their evolution. Nevertheless, their time evolution is much more complicated and seven different regimes can be identified. Indeed, well defined frequencies are observed and the associated spectrum strongly evolves during the growth process. The instability complex shape underlines the coexistence of different phenomena that could interact and give regular or chaotic oscillations. The instability time evolution reveals drastic and sudden changes in shape and frequency that could not be easily correlated to dust particle size and density. A detailed analysis of the instability main characteristics is performed in order to underline and bring to the fore the complex phenomena that could arise in a plasma containing changing dust particles.

II. EXPERIMENTAL BASIS

A. Experimental set-up

The work presented here is performed in the PKE-Nefedov chamber designed for microgravity experiments [34]. The experimental set-up consists in a parallel plate rf discharge where an argon plasma (0.2 -2 mbar) is created in push-pull excitation mode (0 -4 W). The electrodes are separated by 3 cm and their diameter is 4 cm. The dust cloud is illuminated by a thin laser sheet perpendicular to the electrodes and the scattered light is recorded at 90 o with two standard CCD cameras at 25 images per second. In the first stages of growth, dust particles are very small and the scattered light is maxi-mum in the laser direction. Consequently, a third camera is watching the cloud with an angle lying approximately between 20 o and 30 o with respect to the incident laser direction. Instabilities are characterized by two different diagnostics. First, the time evolution of the amplitude of the discharge current fundamental harmonic is recorded. This electrical measurement is representative of global changes in plasma properties especially concerning the electron density. The second diagnostic is based on spatially resolved optical measurements. Five optical fibers are horizontally aligned (5 mm in between each fiber) and record the total plasma light with a spatial resolution of about 3 mm. This diagnostic gives local measurements that are of interest to detect any plasma motion or localized changes in order to better understand the integrated electrical measurements.

B. Dust particle growth

Dust particles are grown by sputtering a polymer layer deposited on the electrodes and coming from previously injected dust particles (3.4 µm, melamine formaldehyde). Typical working pressure is around 1.6 mbar and rf power is about 2.8 W. With these parameters dust particles start to be detected by the cameras approximately 1 min after the plasma ignition. A more complete description of the experimental set-up and some results concerning dust particle growth are given in [9]. The growth process leads to various shapes of the dust cloud (few layers, domelike shape, 3D dense cloud) due to the fact that we do not control precisely size and density of grown dust particles. Indeed, the growth process seems to be highly sensitive to gas purity. This effect is amplified by the fact that experiments are performed at static pressure (no gas flow). At least one hour of pumping between each experiment is needed to eliminate species formed during the previous run and/or coming from the outgassing of the walls and/or from the sputtered matter. This behavior is well observed on successive runs by using emission spectroscopy. Impurities like N 2 and OH are observed and their effect on dust particle formation is under investigations. Until now it is not clear if their presence prevents the sputtering or if the sputtering occurs but the growth cannot takes place. This effect of the gas purity has been previously reported in similar experiments [8]. Possible precursors like carbon molecules C 2 , CN and CH appear and the C 2 molecule seems to be a good indicator of dust formation [START_REF] Mikikian | Proc. 30 th EPS Conf. on Contr. Fusion and Plasma Phys[END_REF].

A very high dust density is obtained when base pressure before an experiment is sufficiently low (few 10 -6 mbar). A base pressure of few 10 -5 mbar drastically reduces the amount of grown dust particles. This base pressure dependence is even more drastic on the instability appearance. Indeed, in our experimental conditions, they are observed only if the base pressure is lower than 4×10 -6 mbar. Consequently, unstable conditions depend on gas purity and/or on dust particle density.

III. DUST PARTICLE GROWTH INSTABILITIES

Dust particle growth instabilities (DPGI) typically appear few tens of seconds after plasma ignition. Their appearance is well observed on both electrical and optical measurements [START_REF] Mikikian | Proc. of the 31 st EPS Conf. on Plasma Phys[END_REF][START_REF] Mikikian | New Vistas in Dusty Plasmas[END_REF]. Due to their low frequency and strong amplitude, DPGI beginning is also well detected by the naked eye looking at the plasma glow.

When dust particles are growing in a plasma, the amplitude of discharge current fundamental harmonic is decreasing due to the electron attachment on dust particle surface. This decrease is well observed in Fig. 1 from around 20 s (plasma ignition) to 800 s. Appearance of DPGI is also clearly evidenced by an increase of the fluctuation amplitude becoming a real oscillation. DPGI can last several minutes (more than 12 minutes in Fig. 1) and different regimes are evidenced. Their beginning instant is slightly changing from one experiment to another due to differences in dust particle density which is strongly dependent on gas purity. Nevertheless, statistics performed on several experiments allow to deduce some general behavior. For exemple, the pressure dependence is shown in Fig. 2. An decreasing exponential variation of DPGI appearance time as a function of pressure is observed: the higher the pressure, the shorter the appearance time. This variation underlines the relation between the instability appearance and dust particle density. Indeed, DPGI are observed only when a huge dust particle density is obtained. From our previous experiments [START_REF] Mikikian | Proc. 30 th EPS Conf. on Contr. Fusion and Plasma Phys[END_REF], we define the treshold pressure permitting dust particle growth around 1.2 mbar. At higher pressures, a shorter delay before formation of a dense cloud is measured. This delay is well evidenced in Fig. 2. At 1.4 mbar, nearly 2 minutes are necessary to initiate DPGI while only 40 s are required at 1.8 mbar. Two possibilities can explain this delay at low pressures: either a longer time is required to attain the critical dust density necessary to initiate DPGI or the dust density is lower and DPGI beginning needs bigger dust particles (ie longer time). These ex- planations are consistent with another observation: the lower the rf power, the longer the appearance time.

IV. PHASE IDENTIFICATION: ELECTRICAL AND OPTICAL MEASUREMENTS

As can be seen in Fig. 1, different regimes characterize DPGI. These different phases are easily brought to light by performing the same electrical measurements but in ac mode in order to improve oscilloscope vertical resolution. The resulting curve is presented in Fig. 3.

DPGI beginning is detected around 40 s and clear phases, numbered from 1 to 7, are observed. These different phases are better evidenced by performing Fourier analysis of electrical signals. A typical spectrogram is given in Fig. 4. In order to emphasize small ordered domains, spectrogram intensity has been normalized in- side each 100 s range (from 0 to 100 s intensity has been normalized to its maximum value inside this time domain and so on). Same Fourier analysis performed on spatially resolved optical measurements shows roughly the same spectrogram features and phases. From Figs. 3 and4 we can identify seven different regimes (a precise analysis of these different phases will be presented in following sections):

• Three ordered phases P1, P2, P3 (from ≃ 40 s to ≃ 80 s). • Chaotic phase P4 (from ≃ 80 s to ≃ 405 s).

• High frequency phase P5 (from ≃ 405 s to ≃ 435 s).

• Chaotic phase becoming more and more regular P6

(from ≃ 435 s to ≃ 600 s). • Regular oscillation phase P7 (from ≃ 600 s to ≃ 680 s)

All these phases are observed on both electrical and optical measurements confirming their real correlation to an unstable state of the plasma-dust particle system. The global scheme of these instabilities is different from the one describe in [7,8] where a filamentary mode (that could be related to our chaotic regime) is followed by a regular phase (great void mode). In our experiment, instabilities begin with regular oscillations (P1, P2, P3) followed by a long chaotic regime (P4). This chaotic phase (P4) suddenly ends with a high frequency phase (P5) and starts again (P6) becoming more and more ordered. Finally, the system reaches a regular phase (P7) that can be sustained for a long time (in the exemple given here the plasma has been switched off at 680 s).

A. First three ordered phases DPGI begin with a succession of three ordered phases separated by clear transitions (Fig. 5). P1 and P2 phases are short and are not detected in all experiments while P3 phase lasts longer and is regularly observed. The three phases are well separated and evolve as a function of time. To explain the observed transitions between phases, it is necessary to also analyse the corresponding time series. As an example, Fig. 6 represents an electrical measurement obtained with a very short P2 phase in order to illustrate on the same figure P1-P2 and P2-P3 transitions. In Fig. 6, P1 phase is characterized by wide separated peaks with a mean frequency of about 40 Hz.

The transition from P1 to P2 corresponds to the growth of two small peaks between these higher amplitude patterns. The Fourier analysis traduces this change by a frequency decrease from about 40 Hz in P1 to about 30 Hz in P2. The small peaks continue to grow (P2 phase) and the higher amplitude ones decrease. Finally, all peaks reach the same amplitude characterizing P3 phase. The frequency of P3 phase is then approximately three times P2 frequency (around 94 Hz). P3 phase is robust (nearly always observed in our experiments) and lasts a sufficiently long time to evolve with dust particle growth (Fig. 5). Its frequency time evolution is always the same, it decreases, reaches a minimum value and then slightly increases until DPGI enter in the chaotic regime. Furthermore, the frequency range of P3 phase seems to be linearly dependent on the phase duration: the higher the frequency, the shorter the time duration. The time evolution of these three ordered phases is better observed on the frequency harmonics appearing due to the nearly sawtooth shape of electrical signals (Fig. 6).

Optical measurements recording the plasma light (integrated on all wavelengths) at different positions, show also three ordered phases (Fig. 7). Nevertheless, these P1, P2 and P3 phases have different characteristics than the ones observed on electrical measurements. Concerning the oscillation shape, the transition between P1 and P2 phases is here revealed by an increase of oscillation amplitude (Fig. 7). P3 phase is strongly marked by a clear amplitude modulation which is better evidenced near the plasma edge than in the plasma center. Concerning the oscillation frequency, some small discrepancies with electrical measurements are also observed, especially on P3 phase (Figs. 5 and8). Indeed, P1 and P2 phases are similar but when DPGI enter in P3 phase, the typical frequency is not tripled, like in electrical measurements, but remains around the same value than during P2 phase. Furthermore, optical measurements of this P3 phase are slightly different depending on the observed plasma region. The signal recorded by the optical fiber watching the plasma center (Figs. 8(a) and 8(c)) is not exactly the same than the one recorded near the plasma edge (Figs. 8(b) and 8(d)). Indeed, the central fiber gives a main frequency around 26 Hz and a small amplitude component around 31 Hz (Fig. 8(c)). The near plasma edge fiber gives same frequencies but also additional ones: one in between 26 and 31 Hz and another one around 3 Hz (Fig. 8(d)) that corresponds to the strong modulation observed in Fig. 7. These observations underline that some spatial considerations must be made to interpret this P3 phase. The first local indication concerns the frequency three times lower than for electrical measurements. This point seems to signify that a phenomenon oscillating at around 94 Hz affects the plasma, and consequently the electrical measurement, but is detected only one time out of three by the optical fibers. One possible explanation is that a plasma modification either appears successively in different places, or moves and comes back in front of an optical fiber with a frequency of about 30 Hz. This plasma modification appears successively in distinct locations of the plasma because it is not detected at 94 Hz by any optical fiber looking at the plasma center or edge. Investigations concerning this hypothesis are currently underway using a high speed camera. The second local indication giving credit to this hypothesis, is the difference between observations given by each optical fiber. Indeed, even if their Fourier spectrum is nearly similar and shows only small discrepancies, the recorded time series bring more information. Optical measurements performed by the near plasma edge fiber is in phase opposition with ones in the center. This behavior, coupled with the fact that a stronger modulation is observed near the plasma edge, could confirm a possible motion, or appearance in different places, of a modified plasma region.

B. Chaotic regime

After three different ordered phases, DPGI enter in a chaotic regime P4 (Fig. 5 after 80 s) with a strong increase in DPGI amplitude (Fig. 3). Then, the amplitude slowly decreases during the whole phase. P4 is also characterized by structured oscillations appearing in a transient manner. These structured regions are identified by some bright spots on electrical and optical spectrograms. On time series they appear as bursts of order. In Fig. 9(a), electrical signals reveal a clear transition between the P3 phase and the chaotic regime. This regime change is indicated by an arrow and a burst of order is encircled. A zoom of this burst of order is shown in Fig. 9(b). During the chaotic regime, structured oscillations in electrical signals always appear following a three peak structure (see for exemple between 94 s and 94.04 s in Fig. 9(b)) that could be related to the three peaks observed in P2 or P3 phases. Indeed, it could be a reemergence of these phases during the chaotic regime. To compare our observations with the filamentary mode [7,8], a Fourier spectrum of the whole chaotic regime (from 80 to 405 s) has been performed in Fig. 10. For electrical signals (Fig. 10(a)), a noisy main frequency around 28 Hz is observed and is equal to the frequency at the end of the P2 phase, confirming the possible reemergence of this phase. This frequency corresponds to the occurence frequency of the three peak structure regularly appearing during the chaotic regime (Fig. 9(b)). Due to these structures, multiple frequencies (54 Hz, 83 Hz and 107 Hz corresponding to the frequency between two successive peaks of one single three peak structure) are also detected in Fig. 10(a). For optical measurements (Fig. 10(b)), differences with electrical ones are the same than in the P3 phase: one optical oscillation corresponds to a three peak structure and consequently only the 28 Hz frequency appears (Fig. 10(b)). These spectra are very similar to the one obtained for the filamentary mode [8] even if in our experiments the presence of more ordered domains is observed. Thus, we can surmise that the chaotic regime we observe could be similar to this filamentary mode.

C. High frequency phase

In some experiments, the chaotic regime is suddenly interrupted by a strong frequency change (at 405 s in Figs. 3 and4). Indeed, this phase P5 is not always observed but when it is present its general characteristics are nearly always the same. This new phase appears after a continuous decrease of P4 phase amplitude and is defined by a radical change in DPGI amplitude and frequency. Indeed, DPGI turn into a low amplitude and high frequency (around 500 Hz) oscillation as shown in Fig. 11. This change happens suddenly when no fast modifications in dust particle size and density are expected. Furthermore, the phase frequency increases with time. In Fig. 4, this increase is nearly linear but non linear behaviors have also been observed in certain cases. As previously mentionned, this phase is not always observed which means relatively precise conditions must be fulfilled for its existence. This effect is well confirmed in the experiment described in Fig. 12 where this phase is interrupted before starting again. Small modifications in plasma or dust particle properties can easily turn the system from the high frequency phase to the chaotic one. Furthermore, this P5 phase can also be transformed in regular oscillations as shown in Fig. 12 at t= 294 s.

From these experimental results it can be assumed that this high frequency phase is a particular case of DPGI, obtained in a tight set of parameters and that can be easily turned in ordered or chaotic regimes.

D. Second chaotic regime

After the high frequency phase, a second chaotic regime is usually observed. Two different types of this P6 phase are observed. The most usual is presented in Fig. 4 between 435 and 600 s. It corresponds to a phase similar to P4 but with more and more ordered regions. Figure 4 clearly shows that DPGI tend to stabilize to regular oscillations (≃ 600 s). This transition appears as a small and continuous increase in DPGI frequency. Nevertheless, some experiments show a slightly different behavior as in Fig. 13. Instead of slowly increasing, the frequency decreases and enters (still decreasing) in a regular oscillation phase. This behavior corresponds to void rotation in a horizontal plane which is clearly evidenced thanks to CCD camera images. The corresponding spectrogram is nearly similar to the one obtained in [8] related to the great void mode.

E. Final regular oscillation phase

The final step of DPGI often corresponds to a regular oscillation phase characterized by a spectrogram with a typical frequency around 18 Hz (Fig. 4) and its harmonics. The corresponding electrical signal is shown in Fig. 14. The signal shape is in particular marked by a sharp peak appearing at each period. This shape is similar to what is obtained during the "heartbeat" instability [23,[START_REF] Mikikian | New Vistas in Dusty Plasmas[END_REF] which corresponds to regular contractions and expansions of the void size. At this stage of DPGI, this regular oscillation phase can last for minutes and is robust, meaning that once it is set up it does not turn in another regime. Optical measurements performed in the plasma center show an evolution similar to the electrical one except near the sharp peak region as observed in [START_REF] Mikikian | Proc. of the 31 st EPS Conf. on Plasma Phys[END_REF]. Furthermore, near edge optical fiber signal is in phase opposition with the central one (as in [START_REF] Mikikian | Proc. of the 31 st EPS Conf. on Plasma Phys[END_REF]) emphasizing the similarity with the heartbeat instability.

V. DISCUSSION AND CONCLUSIONS

In this paper, self-excited instabilities induced by the formation of submicron dust particles are investigated. These instabilities appear when a sufficiently high dust particle density is reached. Instability frequency and shape change during the growth process and direct correlation with dust particle size and density cannot be easily deduced. Indeed, effects of both parameters on discharge behavior are difficult to separate: a high density of small particles can have roughly the same effect than a lower density of bigger particles, assuming that the total collection surface is identical and consequently the same amount of electrons can be captured. The only way to conclude on this point is to measure dust particle size and density but most commonly used in-situ diagnostics cannot be implemented on our experimental setup. Furthermore, an easy systematic collection of dust particles coming from one and only one experiment is not possible in our reactor. DPGI reproducibility can be obtained only with very low base pressures not reached in case of regular reactor opening. By comparing Fig. 1 with electrical characteristics obtained in silane based discharges [39] we can speculate that DPGI occur during the "coalescence phase" and last during the so-called "surface deposition phase". These phases [40] are characterized by a significant amount of negatively charged dust particles strongly impacting on plasma stability. This comparison with dust particle growth process in silane based chemistry must be taken carefully because the analogy has not been strictly proved yet. From visual observations we know that when DPGI occur, dust particles are not detected yet by our video system and are certainly smaller than 100 nm. When instabilities stop dust particle size could be of few hundreds of nanometers. The instability development follows a well-defined succession of phases that can be ordered or chaotic. At least seven different regimes have been evidenced and their occurence is strongly dependent on plasma and dust particle properties. Complex transitions between different ordered phases or between ordered and chaotic ones have been evidenced and underline the nonlinear behavior of these instabilities. Two observed phases seem to correspond to the ones reported in previous papers [7,8]. These phases, called the filamentary mode and the great void mode, can be a part of a more general behavior described in this paper. The new phases described here underline the complexity of phenomena behind observations and their high sensitivity to plasma and dust particle properties. Indeed, the complete scheme with seven phases can be observed in very specific experimental conditions usually encountered in this work. Striations (in our case, enhanced ionization regions appearing as bright spots or filaments) seem to be responsible for the different observed phases. The various regimes could be related to the way striations appear. Indeed, we can surmise that the ordered regimes could be striations appearing periodically and nearly at the same places. Following this hypothesis, the often observed three peak structure can correspond to three different striations. By analogy, chaotic regimes can be due to randomly appearing (in time and in space) striations. Optical measurements performed in different plasma positions bring to the fore that these instabilities need to be analyzed with spatial considerations. Differences with works reported in [7,8] can be the consequence of different plasma and/or dust particle properties, geometrical considerations or gas flow. Furthermore, our observations show that void formation is not a consequence of these instabilities as proposed in [24]. The void can be formed with or without instabilities preceding its appearance. In some conditions, the void is formed before instability beginning. In this case, the instability evolution scheme does not describe all the phases presented here. Similarities between the final regular oscillation phase and the heartbeat instability concerning the void region have been observed. It could indicate that dust particle growth instabilities and the heartbeat instability could be different aspect of the same physical phenomena.

FIG. 2 :

 2 FIG. 2: (Color online). Instability appearance time as a function of argon pressure.

7 FIG. 3 :

 73 FIG. 3: (Color online). Time evolution of the amplitude of the discharge current fundamental harmonic during dust particle growth (ac component). Instabilities appear around 40 s after plasma ignition. Successive phases are numbered from 1 to 7.

FIG. 4 :

 4 FIG. 4: (Color online). Spectrogram of electrical measurements corresponding to Fig. 3 and describing frequency evolution of DPGI as a function of time.

FrequencyFIG. 5 :

 5 FIG. 5: (Color online). First three ordered phases of DPGI and transition to a chaotic regime.

FIG. 6 :FIG. 7 :

 67 FIG. 6: (Color online). Transitions between the first three ordered phases observed on electrical measurements.

FIG. 8 :

 8 FIG. 8: (Color online). Spectrogram of optical measurements recorded (a) in the plasma center, (b) near the plasma edge. (c) zoom of (a), (d) zoom of (b).

FIG. 9 :

 9 FIG. 9: (Color online). Electrical measurements: (a) transition between P3 and P4 phases and encircled burst of order, (b) zoom of the encircled part of Fig. 9(a).

FIG. 10 :

 10 FIG. 10: (Color online). Fourier spectrum of the first chaotic regime on (a) electrical measurements, (b) central optical fiber measurements.

FIG. 11

 11 FIG. 11: (Color online). (a) Appearance of the high frequency phase in between two chaotic regimes, (b) zoom of (a).

FIG. 12 :

 12 FIG.12:(Color online). Spectrogram of a particular case of the high frequency phase. This phase is interrupted by a chaotic regime and is transformed in regular oscillations just before turning again in a chaotic regime.

FIG. 13

 13 FIG.13:(Color online). Spectrogram of a particular case of the second chaotic regime corresponding to void rotation in a horizontal plane.

FIG. 14 :

 14 FIG.14:(Color online). Electrical measurements corresponding to the final regular oscillation phase.

Time (s) Amplitude (a.u.)

	0.8	Beginning of instabilities
	0.75
	0.7
	0.65
	0.6
	0.55
	0.5
	0	100	200	300	400	500	600	700	800
	FIG. 1: (Color online). Time evolution of the amplitude of the
	discharge current fundamental harmonic during dust particle
	growth. Instabilities appear around 40 s after plasma ignition.

Acknowledgments

The PKE-Nefedov chamber has been made available by the Max-Planck-Institute for Extraterrestrial Physics, Germany, under the funding of DLR/BMBF under grants No.50WM9852. The authors would like to thank S. Dozias for electronic support, J. Mathias for optical support and Y. Tessier for experimental support. This work was supported by CNES under contract 793/2000/CNES/8344.

Author manuscript, published in "Physics of Plasmas 13 (2006) 092103" DOI : 10.1063/1.2337793