Sébastien Granger

Ahmed Loukili

Gilles Pijaudier-Cabot

Mouloud Behloul

SELF HEALING OF CRACKS IN CONCRETE: FROM A MODEL MATERIAL TO USUAL CONCRETES

This paper deals with the self healing of cracks phenomenon, in concrete, and especially with its role on mechanical properties. In a first phase, an experimental program, including mechanical tests, acoustic emission investigation and SEM observations, is carried out on an ultra high performance concrete, considered as a model material. This concrete is characterized by its low Water/Cement ratio, which implies that the quantity of potential reactive compounds in the microstructure upon cracking is very high. Prismatic notched specimens are damaged under three points bending and then totally immerged in water for different ageing times, so as to activate the self healing phenomenon, only possible in presence of water. After this ageing phase, the mechanical behaviour of the healed specimens is characterized by means of three points bending tests. A fast recovery of global stiffness and a slight improvement of structural strength are thus highlighted, depending on the time of ageing. Acoustic emission is also performed on this model material. In order to follow the micro-cracking processes and to show that the mechanical contribution of the self healing is related to the precipitation of crystals in the pre-existing crack, the specimens are instrumented with an acoustic emission system, during all the tests. 2D location maps of micro-cracks are thus obtained and clearly show the micro-cracking of the newly formed crystals for healed specimens. The analysis of the cumulative number of detected events, and of the energy extracted from each detected signals highlight the two damage regimes for healed specimens, the newly formed crystals damage followed by the continuation of the preexisting crack propagation. This research work on the model concrete is completed with microscopic investigations by SEM, which show that new C-S-H have precipitated in the cracks. The same mechanical tests are then applied to usual concretes, and the influence of mix design on the phenomenon is analysed. Four different concretes, with Water/Cement ratio from 0.3 to 0.5, and including silica fume or not, are analysed, and the mechanical behaviour of healed specimens from these concretes is characterized.

INTRODUCTION

For many concrete structures in the course of their lifetime or close to their end, the assessment of durability is a key parameter needed in order to know whether safety and security is still ensured or not. The presence of cracks, due to mechanical stresses or time dependent effects (creep, shrinkage…) is one of the major factors which can influence on durability and serviceability, in terms of resistance, permeability or transfer properties.

Self healing of cracks is a phenomenon acting positively on these durability problems. The phenomenon is only possible in presence of water (dissolved CO 2 in water is not always needed) and consists in chemical reactions of compounds present on the crack surfaces. These reactions produce new crystals, and the accretion of these from the opposite surfaces of the crack bridges it eventually, so that continuity can be re-established. The essential requirement, with water, is the presence of compounds capable of further reaction. Thus, cement and cementious materials, hydrated or unhydrated, are the other essential element of the phenomenon. There are two major hypotheses regarding the reactions of healing [START_REF] Neville | Autogenous healing -A concrete miracle?[END_REF]: the hydration of anhydrous clinker available in the microstructure of hardened concrete, and the precipitation of calcium carbonate CaCO 3 . The first hypothesis requires water only, when the second one requires the presence of carbon dioxide in addition. Silting up of cracks or deposition of debris can also contribute to healing, in a minor part.

The majority of research works carried out on this topic highlights the phenomenon by means of water permeability tests. A diminution of flow rate through cracked specimens is the main method to show the self healing of cracks. Edvardsen [START_REF] Edvardsen | Water permeability and autogenous healing of cracks in concrete[END_REF] performed such tests, conducted on small concrete specimens, with a single tension crack each. The typical results show a significantly decreasing rate at the early stages, and then leakage quickly drops to a reduce level. These results highlight the two regimes of the reaction, first immediate reaction on the surfaces of cracks, and then reaction by diffusion through the newly formed crystals. Edvardsen explains the phenomenon by the crystallisation of calcium carbonate exclusively. Hearn [START_REF] Hearn | Self-sealing property of concrete -Experimental evidence[END_REF][START_REF] Hearn | Self-sealing, autogenous healing and continued hydration: what is the difference?[END_REF] carried out also water permeability tests on mortar, with 25% anhydrous clinker, and water cured concrete, containing an insignificant amount of unhydrated clinker. The author investigates the chemical effects, like continuing hydration, dissolution and deposition of soluble species. Chemical analysis of water, inflow and outflow, points out a significant increase in Ca 2+ concentration in outflow, which indicates a phenomenon of dissolutionprecipitation, especially of calcium carbonate. Such experiments have also been performed by Reinhardt et al. [START_REF] Reinhardt | Permeability and self-healing of cracked concrete as a function of temperature and crack width[END_REF], who investigate the role of temperature and of crack width. In brief, these main investigations show that the phenomenon is of particular importance for problems of transfer and watertightness, because it diminishes leakage through cracks.

Concerning the mechanical impact, a few studies have been conducted. Jacobsen et al. [START_REF] Jacobsen | Self healing of high strength concrete after deterioration by freeze/thaw[END_REF] performed tests on concrete cubes damaged by freeze/thaw cycles, and then stored in water. Damage and self healing were measured by frequency resonance and compressive strength. Freeze/thaw cycles led to loss in both resonance frequency and compressive strength, and self healing gives a substantial recovery of the frequency, but only a small recovery of compressive strength, which was explained by the fact that cracks were only partly filled with new products. SEM observations conducted show that the most of the crystals seen in the cracks are new C-S-H. Pimienta et al. [START_REF] Pimienta | Retention of the mechanical performances of Ductal specimens kept in various aggressive environments[END_REF] also provide some insights about the mechanical properties of healed specimens. The authors also reported that the frequency resonance of specimens damaged and then aged in water, tends to recover its initial value. Nevertheless, 2nd International Symposium on Advances in Concrete through Science and Engineering 11-13 September 2006, Quebec City, Canada knowledge about the mechanical properties is scanty, and this contribution aims at providing some new insights concerning the mechanical behaviour of healed concrete. An experimental program is developed, first, on an ultra high performance concrete, considered as a model material. Prismatic notched specimens are damaged under three points bending and then totally immerged in water for different ageing times. After this ageing phase, the mechanical behaviour of the healed specimens is characterized by means of three points bending tests, and compared with the mechanical behaviour of non-healed cracked specimens. Acoustic emission analysis and SEM observations are also performed in order to show that new crystals have crystallized in the cracks and to qualify these crystals. Then, the same mechanical tests are conducted on four usual concretes, with different Water/Cement ratio, in order to analyse the influence of concrete composition on the phenomenon.

THE EXPERIMENTAL PROGRAM

Concrete specimens

The first part of the experimental program is carried out on an ultra high performance concrete (UHPC), with a low Water/Cement ratio close to 0.2. This implies that the amount of anhydrous clinker in the microstructure is very high, in the order of 50% [START_REF] Loukili | A study on delayed deformations of an ultra high strength cementitious material[END_REF]. This concrete is considered as a model material for this research work, because of this specificity. In fact, the quantity of potential reactive compounds upon cracking is very high. The composition of this concrete consists of sand, water, cement, silica fume and a superplasticizer. In order to have a localized crack during the mechanical tests, a notch of depth 20 mm and thickness 1.5 mm is performed in each specimen by placing a plate at the midpoint perpendicular to the long direction of the mould. After casting, the concrete specimens (with dimensions of 50x100x500 mm 3 ) are cured for 2 days at 20°C and 100% relative humidity. A thermal treatment is then applied, so as to accelerate hydration and activate the pouzzolanic reaction. The specimens are placed in a climate chamber with a controlled environment of 90°C and 100% relative humidity during 48 hours. With this treatment, concrete is stable, and exhibits very low creep and shrinkage [START_REF] Acker | Micromechanical analysis of creep and shrinkage mechanisms[END_REF][START_REF] Acker | Swelling, shrinkage and creep: a mechanical approach to cement hydration[END_REF].

Mechanical test configuration

The principle of the mechanical tests carried out is a preliminary phase aimed at cracking the prismatic notched specimens, followed by the ageing in specific conditions, enabling self healing or not, and then the mechanical characterization of these aged specimens.

During the first phase of the mechanical program, specimens are loaded under three points bending (figure 1). The tests are notch opening controlled with a constant rate of 0.05 µm/s. The aim of this first step is to get a controlled cracking of the specimen. Pre-cracking is performed in the post peak regime: after having reached the peak (comprised between 3 and 4 kN), unloading is performed when the applied load reaches 2 kN, which represents approximately 60% of the peak load. Thus, a single residual crack width of 10 µm, which permits to get a fast self healing, is aimed. This unloading is also notch opening controlled with the same rate as loading. Pre-cracking phases are quite reproducible and residual crack widths for specimens after unloading range between 8 µm and 15 µm. After this first step, the specimens are stored in specific conditions for ageing. Five different periods of ageing have been selected: 1, 3, 6, 10 and 20 weeks. There are two kinds of ageing: for each period, cracked specimens have been stored in water, and others in air. Specimens aged in water have been totally immerged in tap water at 20°C, with nor movement neither renewal. Specimens aged in air have been stored at 20°C and 50% relative humidity. After each period of ageing, the last step of the experimental program consists in reloading the specimens under three points bending, in order to characterize their residual mechanical behaviour. Tests are also notch opening controlled and are conducted until total failure.

Acoustic emission acquisition

In order to follow and to characterize the cracking processes, all the specimens are instrumented with an Acoustic Emission (AE) system, during the pre-cracking and reloading phases. The aim is to locate the microcracks (called AE events) which appear during the tests. The instrumentation consists of a MISTRAS system, a general-purpose interface bus (for extraction of AE parameters, such as amplitude, energy, duration…) and a PC for data storage analysis. Four piezoelectric transducers (with a resonance frequency of 150 kHz) are placed in a rectangular array just above the notch of the specimens, in order to cover the expected zone of crack path, and to minimize errors in the AE event location algorithms. The dimensions of the rectangular array are 140x65 mm 2 (figure 2). The transducers are placed on one side of the specimen, and coupled to the material with a silicon glue. The detection value (in amplitude) is set to 35 dB, in order to overcome the background noise, and the detected signals are amplified with 40 dB gain amplifiers. The frequency range of acquisition is set from 20 kHz to 400 kHz.

A planar location algorithm is used for AE location. It is based on the triangulation of the differences between detection times by each transducer. Three transducers are enough, but the accuracy is improved with an additional one. For the UHPC used in this research work, the accuracy of location, checked with Hsu Nielsen simulations, is ±3 mm, which is correct in comparison with the diameter of the transducers (15 mm). We do not take into account the thickness of the beam, and all the events detected within the thickness of the specimen are projected onto the same place in the 2D maps.

MECHANICAL CHARACTERIZATION OF THE SELF HEALING OF CRACKS

Three kinds of mechanical results are presented on figure 3. These are curves for a specimen pre-cracked and then reloaded immediately, and for specimens cracked and aged during three weeks (before reloading) in water and in air. The objective of this figure is to show the effect of storage in water, and to compare with the storage in air and with the immediate reloading of the specimen. The curves display the applied load versus the crack mouth opening displacement (CMOD). Each curve presents two parts: the pre-cracking phase, consisting in loading and unloading when the applied load reaches 2 kN in the post peak regime, and the reloading phase, immediate or after ageing. The reproducibility of the pre-cracking phase of the tests can be seen on this figure. It also shows that the cracked specimen immediately reloaded and the specimen aged in air, have the same mechanical behaviour while reloading, which is the typical reloading after cracking. On the contrary, there is a difference with the mechanical behaviour for the specimen stored in water, especially on the reloading stiffness and the reloading peak load.

If we consider the influence of the ageing time, which is, of course, an important parameter, figure 4 presents the average reloading curves for specimens stored in air and in water (reloading curves for 3 specimens), and for 4 different periods of ageing: 1, 6, 10 and 20 weeks. For the sake of clarity, only the reloading parts of the total curves are presented. The CMOD at the beginning of the tests is shifted to 0, in order to have the same initial state, but in reality we should have the value of the residual CMOD at the end of the pre-cracking phase. We can notice that specimens stored in air exhibit very similar mechanical behaviour for the different periods of ageing. It means that air has no influence on the mechanical properties of cracked specimens, even for a long period of ageing. The reloading part corresponds to the re-opening of the existing crack until the reloading peak load, followed by the continuation of the crack propagation. On the contrary, there is a clear evolution of the mechanical behaviour of specimens stored in water with the time of ageing. The initial reloading stiffness is not the same as for specimens aged in air, and it increases. There is also a slight improvement of flexural strength and a change in stiffness in the pre-peak phase which evolves with time.

In order to get a confirmation that these observed mechanical behaviours are due to the self healing of the pre-existing crack and not to the evolution of concrete itself in water, the average result of tests conducted on specimens which have been stored in water for 10 weeks, and then cracked and immediately reloaded, is compared with the mechanical behaviour of specimens pre-cracked and aged 10 weeks in water. It shows that storage in water without crack does not improve the mechanical properties of the specimen. We have the same mechanical behaviour as those of a non-aged specimen cracked and immediately reloaded: there is no curing effect by storing in water, and it is a consequence of the thermal treatment. So, the evolution of the mechanical behaviour established for cracked specimens stored in water can indeed be explained by the self healing of cracks phenomenon, and not by the bulk improvement upon ageing.

Figure 5 shows the evolution of the ratio between the reloading stiffness with healing, and the reloading stiffness without healing, as a function of the ageing time. It is noticeable that there is a fast recovery by self healing, and this stiffness tends to those of healthy specimen, which is represented by the straight line on the graph. These results can be explained by the fact that products are formed in the crack, especially, if we consider the low W/C ratio, new C-S-H. These crystals make a bridge between the two faces of the crack and progressively fill it, making the specimen recover its initial stiffness.

Concerning the flexural resistance, figure 6 represents the evolution (with the ageing time) of the peak load upon reloading for healed specimens. It shows that self healing provides a slight improvement of strength, compared with the strength of non healed specimens. Nevertheless, the initial flexural strength is not reached, and a kind of explanation wil be provided according to SEM observations, later in the contribution.

THE PRECIPITATION OF NEW CRYSTALS

Acoustic emission analysis

The mechanical tests have shown the contribution of the self healing phenomenon on the mechanical properties of initially cracked specimens. The main aim of the acoustic tests performed during the mechanical tests is thus to highlight that this contribution is related to the precipitation of new crystals in the crack. The principle is to analyse micro-cracking during the reloading phase of the mechanical tests. So, location maps of micro-cracks are performed during the two steps of the mechanical tests, pre-cracking and reloading after ageing. The first kind of maps illustrates the initial micro-cracking processes and serves as a reference for the second one. The typical maps exhibit a very dense area of micro-cracks in the zone of crack path. In order to have an accurate location of the acoustic events in the macro-crack, we need to filter the detected signals. Otsuka [START_REF] Otsuka | Fracture process zone in concrete tension specimen[END_REF] have shown that 95% of the dissipated acoustic energy is located in the fracture process zone, and that the less energetic micro-cracks are not associated with the fracture process of concrete. After having selected the events with the most important energy, we have decided to eliminate those with an energy inferior to 2% of this maximal energy. The filtering energy is thus set to 1000 atto-Joule (aJ). The cumulative energy of these eliminated events is of course non negligible, but with this technique, we can keep only the micro-cracks of interest. Figure 7 presents a typical microcracking map of a specimen, just after the pre-cracking phase without filtering, and with filtering. The four points in the corners represent the transducers which form the rectangular array, and the other points are the micro-cracks detected. On the map with filtering, we can clearly see, at the end of the pre-cracking phase, where the macro-crack is located, and we are able to make the link with the results during the reloading phase. According to the same filtering criterion, new maps are obtained for aged specimens in order to locate the newly formed crystals micro-cracking. In a first analysis, they are performed during the reloading phase (in the pre-peak regime) until 18 µm crack mouth opening. Figure 8 presents the maps for a specimen aged in water and for a specimen aged in air, both during 10 weeks. It is noticeable that micro-cracks appear for the healed specimen in the region of the initial crack, while nearly no micro-cracks are detected for a non healed specimen. In one case, there is damage of crystals in the crack, and in the other case, there is only the re-opening of the existing crack, without any damage but with eventually some detected frictions. These results confirm that crystals have precipitated in the crack during storage in water, and they start being damaged in the pre-peak phase of reloading. The sudden decrease of the stiffness in the pre-peak regime is the consequence of this damage process. This result is confirmed by the analysis of the total number of detected acoustic events. The appearance of acoustic emission while fracturing is linked to the development of damage [START_REF] Landis | Micro-macro fracture relationships and acoustic emissions in concrete[END_REF]. Figure 9 presents the cumulative number of detected acoustic events as a function of the crack mouth opening displacement, for the reloading of two healed specimens and two non healed specimens (specimens aged during 10 weeks). Cumulative number of detected acoustic events

Crack mouth opening displacement (µm)

Figure 9: Evolution of the cumulative number of detected acoustic events for healed specimens and non healed specimens, during reloading phase So, we can see that in the case of healing, the development of damage appears sooner than for non healed specimens, which confirms the fact that new crystals are damaged in a first time during the reloading phase.

We can now consider, in a second analysis, a comparison during the reloading phase, not at the same CMOD, but at the same load level. Results at 90% of the peak load, in the post peak regime are analysed. Figure 10 represents the location maps in terms of energy. Points representing the micro-cracks are plotted according to their acoustic energy: the bigger the point, the more important the energy. If we sum these energies for events located below and above the pre-existing crack tip (which is for height of 50 mm from the bottom face of the specimen), we can notice that nearly 100% of the acoustic energy dissipated until 90% of the peak load is located in the preexisting crack, for the specimen which has been stored in water, although it is 50 % for a non healed specimen (acoustic events due to frictions or re-opening of micro-cracks). This result highlights the two regimes of damage for healed specimens: first we have damage of the newly formed crystals, and then continuation of the crack propagation. If we consider now the total energy dissipated, it is 50% less in the case of a healed specimen. This energy corresponds to the micro-cracking of the new crystals in the case of healing, and corresponds to the micro-cracking of healthy concrete in the case of non healing. We can thus consider that the mechanical properties of the new crystals should be less than those of healthy concrete.

SEM observations

In order to complete our mechanical and acoustic results, and to explain what really happens in the crack, SEM observations are performed. The essential aim is to determinate the nature of the new crystals that have precipitated in the crack. The observations are performed on the crack surfaces after the reloading phase, and are completed by some qualitative analysis by energy dispersive spectrometry (EDS) technique. Figure 11 presents the typical observations for a non healed crack surface, and for a healed one, with an enlargement of 10000. The typical crack surface without healing shows a very dense microstructure, made of C-S-H gel. On the contrary, the observations carried out on the healed surface are totally different. We can thus see a particular structure formed by alveolar crystals. EDS tests are carried out on several places in these crystals and give the typical result which can be seen on figure 12. This analysis reveals the typical composition of alveolar C-S-H. We can thus give some new explanations about the mechanical behaviour of healed specimens. Indeed, the fact that C-S-H have clearly precipitated in the crack explains the recovery of stiffness. Nevertheless, the special structure of these new C-S-H, in comparison with the very dense structure of hardened concrete, can not permit to recover the specimen strength. It is in fact difficult to build in the crack, the complex structure, which gives its strength to concrete, and especially all the links between C-S-H.

SELF HEALING FOR USUAL CONCRETES

After having investigated in details the phenomenon of self healing of cracks on an ultra high performance concrete, this research work is extended to usual concretes, and especially to the influence of composition on the phenomenon.

The same mechanical tests are conducted on four different concretes, including the precracking phase, the ageing, and finally the reloading phase in order to characterize the mechanical behaviour of healed specimens. Concrete are designed in order to get exactly the same granular skeleton (with a ratio gravel/sand equal to 1.45), and to keep the paste volume constant (cement, water, and additions). Only the water/cement ratio varies form 0.3 to 0.5, and one of this four concrete includes silica fume. The mix design proportions are presented in table 1. After casting, the prismatic specimens (dimensions 50x100x500 mm 3 ) have been cured in water for 120 days. Young modulus (followed by the measurement of resonance frequency) and compressive strength are stable at the end of this curing time. They are then stored in a climate chamber at 20°C and 50% relative humidity, but are not thermally treated. The specimens are then pre-cracked under 3 points bending. The four concretes are less brittle than the ultra high performance one. So it is difficult to aim a residual crack width of 10 µm with a significant damage. It was so decided to aim a residual crack width in the order of 20 µm. The specimens are then totally immerged in water at 20°C and their mechanical behaviour is characterized after 10 weeks of ageing. The mechanical behaviour of non aged specimens is also characterized in comparison: specimens are pre-cracked and then immediately reloaded. Figure 13 presents the typical results obtained for specimens of concrete 1, pre-cracked at 20 µm and aged for 10 weeks, compared with the mechanical behaviour of a non healed specimen. We could have represented the same result for the three other concretes. Qualitatively, we have exactly the same result: there is a very slight recovery of initial stiffness for healed specimens, and a very significant loss of flexural resistance, in comparison with non healed specimens. If we consider only the healed specimens, Figure 14 shows the average reloading curves (only the reloading part) for the four concretes, after 10 weeks of ageing. The curves display the ratio load applied on load at the unloading point of the pre-cracking phase, in order to be able to make comparisons. We can thus notice that the influence of composition of concrete on the phenomenon of self healing is quite limited for our tests. It appears that the highlighted deterioration of strength is less important for concrete with low W/C ratio, and for concrete which includes silica fume. But, this loss of strength is quite surprising. And we certainly need more information to be able to explain this result. Nevertheless, a first explanation based on the structure of the hardened cement paste could be advanced. Indeed, for the ultra high performance concrete, anhydrous cement grain present in the microstructure can be fractured in their whole volume, so that cement is directly in contact with water and can reacts. On the contrary, for usual concretes, the crack is preferentially located in the interface between cement paste and aggregates, and the intrusion of water can deteriorate this zone (increase of porosity) and thus degrade the strength. We can also wonder if the residual crack widths are not just too big to have the formed crystals bridging the gap between the two faces of the crack. As a conclusion, this investigation of the self healing on usual concretes indicates that the role of self healing on the mechanical properties of such concrete is limited. Further investigations, with, for instance, ageing conditions in air with high relative humidity and longer ageing times, could complete this part of the research work.

CONCLUSION

In the first part of this research work, the results of an experimental investigation on the mechanical behaviour of healed ultra high performance concrete specimens have been presented. After a controlled pre-cracking phase under three points bending, prismatic specimens are aged, in air or in water, during various durations ranging from 1 to 20 weeks. It appears that after storage in water exclusively, damaged beams tend to recover fast their initial global stiffness, and to improve slowly their flexural strength. These mechanical results are attributed to the phenomenon of self healing of crack. An acoustic emission analysis is then performed in order to confirm the precipitation of new crystals in the crack. Microcracking processes of healed specimens are thus investigated, and permit to locate the microcracking of these new crystals during the reloading phase of the mechanical tests. It also shows the two phases of the cracking processes of healed concrete, including damage of newly formed crystals and continuation of the crack propagation. All these investigations are corroborated with microscopic observations, which shows that new C-S-H, with an alveolar structure different from those of C-S-H of normal hydration, have precipitated in the crack. The mechanical tests are then applied to four usual concretes. The influence of composition of concrete on the phenomenon is analysed. The mechanical results obtained are totally different from those get on the ultra high performance concrete. Indeed, storage in water tends to deteriorate the mechanical strength of the specimens, which can be explained by the very different microstructure of these concretes, compared with the ultra high performance one. Further investigations are needed in order to get complete conclusions for usual concretes.

2ndFigure 1 :

 1 Figure 1: Mechanical test configuration

Figure 2 :

 2 Figure 2: Acoustic emission instrumentation -Rectangular array of 140x65 mm 2

  reloading cracking and 3 weeks ageing in water cracking and 3 weeks ageing in air Load (kN) Crack mouth opening displacement (µm)

Figure 3 :

 3 Figure 3: : Mechanical behaviour of a specimen cracked and immediately reloaded, of a specimen cracked and aged 3 weeks in water before reloading, and of a specimen cracked and aged 3 weeks in air before reloading -Pre-cracking and reloading phases

Figure 4 :

 4 Figure 4: Mechanical reloading behaviour of aged specimens for different ageing times -Comparison ageing in water and ageing in air -Average curves: (a) 1 week, (b) 6 weeks, (c) 10 weeks, and (d) 20 weeks

  on Advances in Concrete through Science and Engineering 11-13 September 2006, Quebec City, Canada

Figure 5 :

 5 Figure 5: Evolution of the ratio between the reloading stiffness with healing and the reloading stiffness without healing, as a function of time of ageing -Comparison with the average stiffness of healthy specimens

Figure 6 :

 6 Figure 6: Evolution of the reloading peak for healed specimens (storage in water) with the time of ageing -Comparison with the average reloading peak of non healed specimen

Figure 7 :

 7 Figure 7: Micro-cracking map of a specimen after the pre-cracking phase; a) Result without filtering, b) Result with filtering in energy: events with an energy higher than 1000 aJ

Figure 8 :

 8 Figure 8: Micro-cracking maps, during the reloading phase (until 18 µm -pre-peak regime) of specimens aged for 10 weeks; (a) ageing in water, (b) ageing in air

Figure 10 :

 10 Energy location maps at 90% of the peak load in the post peak regime; a) healed specimen, b) non healed specimen transducers on Advances in Concrete through Science and Engineering 11-13 September 2006, Quebec City, Canada

Figure 11 :

 11 Figure 11: SEM observations on the crack surfaces of the studied concrete; a) crack without healing, b) crack with healing -Enlargement of 10000

Figure 12 :

 12 Figure 12: Result of the energy dispersive spectrometry analysis on the alveolar crystals on the healed crack surfaces

Figure 13 :

 13 Figure 13: Mechanical behaviour of healed specimens (10 weeks) compared with mechanical behaviour of a non healed specimen, for concrete with W/C = 0.3

2ndFigure 14 :

 14 Figure 14: Average mechanical behaviour of specimens from different concrete compositions during the reloading phase

2nd

  International Symposium on Advances in Concrete through Science and Engineering 11-13 September 2006, Quebec City, Canada

Table 1 :

 1 Composition of the four concretes studied (for 1 m 3 )

		Concrete 1	Concrete 2	Concrete 3	Concrete 4
	W/C ratio	0.33	0.43	0.54	0.48
	Gravel (kg)	1051.3	1051.3	1051.3	1051.3
	Sand (kg)	722.7	722.7	722.7	722.7
	Water (L)	156	177	193	174
	Cement (kg)	476	410	360	366
	Silica fume (kg)	0	0	0	36
	Superplasiticizer (kg)	4	2	1	2


Gilles Pijaudier

Continuum Damage and Scaling of Fracture


Mireille Navarrete

Helene Brives

Maxime Catalogna

Lucie Gouttenoire

Claire Heinisch

Claire Lamine

Emilie Ollion

Sylvaine Simon

Hélène Brives

Farmers' involvement in collective experimental designs in a French region, Rhône-Alpes. How do they contribute to farmers' learning and facilitate the agroecological transition?

Keywords: Experiment, innovation, multi-actor learning, knowledge, agroecology, participatory research

la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Farmers' involvement in collective experimental designs

in a French region, Rhône-Alpes. How do they contribute to farmers' learning and facilitate the agroecological transition?

Introduction

The environmental impacts of agriculture call for a large change in farming systems and more generally in agricultural knowledge systems. In particular, the use of agroecological principles for designing and managing more sustainable agroecosystems, although highly promising, is a challenge as regard knowledge building [START_REF] Gliessman | Agroécology : the ecology of sustainable food systems[END_REF]. Agroecology promoters call for the development of new ways of learning based on interactions in-between farmers, and with advisors and scientists [START_REF] Francis | Innovative education in agroecology: Experiential learning for a sustainable agriculture[END_REF]. The reasons are twofold: first the ecological processes are uncertain, i.e. the speed and intensity of their effects on agroecological systems are not fully predictable. Second they are situated, i.e. very dependent on local situations. Therefore, the paradigm of generic knowledge built by scientists and its dissemination to farmers, which has prevailed for decades, has now to be replaced by a new paradigm, based on the development of farmers' learning and innovation processes on farms [START_REF] Prost | Innovative design for agriculture in the move towards sustainability: scientific challenges[END_REF]. On-farm learning may be a way for farmers to overcome problems related to uncertain and situated ecological processes by fitting cropping and husbandry practices to ecological situations, and by learning by doing. But this process is not so easy and could be supported by scientists and advisors.

Farmers mobilize a great diversity of sources of knowledge to imagine and manage crop and husbandry systems in an agroecological way. Besides traditional agricultural advisors' visits on farms, they find out information on agricultural newspapers or websites, during training courses or through peer-to-peer exchanges, experimentation, etc. [START_REF] Ingram | Technical and Social Dimensions of Farmer Learning: An Analysis of the Emergence of Reduced Tillage Systems in England[END_REF][START_REF] Kummer | Building Resilience through Farmers' Experiments in Organic Agriculture: Examples from Eastern Austria[END_REF]. We assume that farmers' involvement in experimental designs is a key activity for them to learn how to implement and manage new agroecological systems. Historically, in agronomy, experimentation has been considered as a way to build credible knowledge for scientists. Knowledge on crop or herd functioning was generated by testing theoretical hypotheses in factorial experiments. In that paradigm, the repeatability of experimental protocols and the data traceability are considered as key elements to produce scientific evidences, hence leading to a simplification of the experimental agrosystem under study, as it is usually done in experimental stations [START_REF] Murdoch | Sustainable knowledge[END_REF][START_REF] Ansell | Varieties of experimentalism[END_REF]. With the development of agroecology, repeatability is questioned: how to experiment a technique based on agroecological processes in several places: is it accurate to choose the same technical modality everywhere irrespectively of the local ecological situations? How to deal with the possibly contradictory information resulting from this choice? The usability of scientific experiments by farmers is also questioned: can the knowledge built with a situated experiment be re-used by farmers in other conditions?

Meanwhile, farmers experimenting activity is now recognized as a way to enhance agroecological transition [START_REF] Kummer | Building Resilience through Farmers' Experiments in Organic Agriculture: Examples from Eastern Austria[END_REF][START_REF] Leitgeb | Farmers' experiments in Cuba[END_REF]. As these experiments realized in real conditions vary a lot, several typologies have been proposed, partially overlapping. [START_REF] Ansell | Varieties of experimentalism[END_REF] distinguish three experimental logics: "controlled experimentation", which is close to scientific approach, for analyzing a causeeffect relationship and test hypotheses; "Darwinian experimentation" which consists in gathering the largest possible number of individual experiments on a theme to identify success stories, and "generative experimentation" which consists in elaborating, testing innovative solutions to existing problems, and regularly adapting the system under study until it becomes efficient, as realized in agronomy with system experiments [START_REF] Deytieux | Expérimentation de systèmes de culture innovants : avancées méthodologiques et mise en réseau opérationnelle[END_REF]. For their part, [START_REF] Caniglia | Experiments and evidence in sustainability science: a typology[END_REF] identified 6 types of experiments in sustainability science, depending on two variables. The first one is the degree of control by scientists. It comprises three modalities: full control of the experiments by scientists, simultaneous control by scientists and actors, and no scientist control. The second variable characterizes the subject of experimentation. Either the experiments seek to understand sustainability problems and provide analytical knowledge on how practices could act on them. Or they focus on sustainability solutions in order to build actionable knowledge. It must be noted that the different types of experiments are not exclusive and rely on an ideal-typical categorization, whereas in practice, it can be considered that there is a continuum between all types. Anyway these typologies can be used to open the box of agroecological experimentations involving farmers.

Another key element in the literature for an agroecological transition is the development of local farmers' networks [START_REF] Gliessman | Editorial: Community-based participatory action research with agroecology[END_REF]. Their number has been growing recently and they are now even encouraged by agricultural policies (e.g. EIP at the European level, GIEE1 in France) to favor the agroecological transition. Collective dynamics are of great support for changing practices [START_REF] Elzen | Stimulating transitions towards sustainable farming systems[END_REF]. Such networks enable farmers to share experiences and knowledge [START_REF] Altieri | The agroecological revolution in Latin America: rescuing nature, ensuring food sovereignty and empowering peasants[END_REF][START_REF] Garbach | Grower networks support adoption of innovations in pollination management: The roles of social learning, technical learning, and personal experience[END_REF] and build technical innovations fitted to local conditions, such as reduced tillage systems in England [START_REF] Ingram | Technical and Social Dimensions of Farmer Learning: An Analysis of the Emergence of Reduced Tillage Systems in England[END_REF]. The frame of agroecology brings an increasing recognition of local knowledge and the place of farmers in knowledge generation is largely reconsidered [START_REF] Kloppenburg | Social theory and the de/reconstruction of agricultural science: local knowledge for an alternative agriculture[END_REF]. Farmers' networks are a way to develop situated knowledge usable by farmers, but also to collect and compare information on a wider range of situations, helping farmers to be more reflexive. [START_REF] Klerkx | Advances in knowledge brokering in the agricultural sector: towards innovation system facilitation[END_REF] highlighted that knowledge generation in the networks has to be supported, by what will be called here a "supporting actor". This supporting activity can present a range of styles. It can be purely facilitation when the supporting actor is not involved in the experimentation but ensures "that partners connect, and that information flows and learning occurs" [START_REF] Klerkx | Establishment and embedding of innovation brokers at different innovation system levels: Insights from the Dutch agricultural sector[END_REF]. In other cases, especially when the supporting actor is a researcher or an extensionist, he/she can be involved in the experimental design or even sometimes can be the leader [START_REF] Duru | Designing agroecological transitions; A review[END_REF].

Combining an experimenting dimension and a collective dimension could be a promising way for promoting agroecological knowledge and supporting the agroecological transition. Based on this assumption, the article focuses on farmers' involvement in collective on-farm experimentations of agroecological practices, whether the experiments are led by the farmers themselves or by external persons. The aim is (i) to describe and analyze a diversity of farmers' experimenting processes in relation to the network functioning (how and why did farmers initiate or contribute to experiments on agroecological practices or systems? How were the other members involved?), (ii) to understand how such multi-actor experimentations contributed to promote farmers' learning processes and finally to the agroecological transition.

As the object under study was the experimental designs, we only considered local networks, i.e. those where farmers were geographically close enough to visit each other's on-farm experiments. We adopted a large definition of farmers' network, considering not only the farmers' peer-to-peer exchanges, but also with agricultural advisors, vets or scientists who supported farmers in their experimenting processes or in some cases co-designed experiments, hereafter referred to as "supporting actors". As the term "farmers' experiments" is diversely interpreted, we considered that there is an experimenting activity if three activities are combined [START_REF] Catalogna | An agronomical framework for analyzing farmers' experiments[END_REF]: (1) planning a design to solve an identified problem and test potential solutions; (2) monitoring the system under experiment to observe the potential effects; and (3) drawing conclusions on the practices under experimentation. If the three steps are mandatory, the degree to which each step is performed is open. For example, the monitoring phase may be limited to visual observations on plants or animals without writing any information, or the conclusive phase may consist in initiating a reflexive process on how the practices should be adapted the following year, even if no clear conclusion has been drawn from the trial.

Research approach

Seven farmers' networks engaged in agroecological transitions: The research is part of a French participatory research project, called COTRAE 2 , studying how local farmers' networks are organized and how they build and exchange knowledge dealing with agroecology. The seven networks studied are located in the Auvergne-Rhone-Alpes region; they were all managing experiments during the study, on crop production (cereals, fruits) and/or livestock farming (dairy and beef cattle).

Interdisciplinary surveys of each farmers' network:

The research project was based on a close interaction between scientists from biotechnical sciences (agronomy, animal science) and social sciences (sociology, geography) and with farmers and supporting actors (vets, advisors, scientists, etc.). It was based on an empirical survey and participant observation.

Regarding the empirical survey, common guidelines were used to characterize the seven networks and the experiments realized. 48 farmers were interviewed (see the distribution per network on Table 1), the interviews taking place directly on the farms and lasting between one and two hours. As it was impossible to meet every farmer of a network, interviewees were selected to cover as far as possible the network diversity, i.e. farmers having a central vs minor place in the network organization (president, leader or simple member), more or less experimented in agroecology, and implementing experiments regularly or not for the collective. The supporting actors most involved in the seven networks were also surveyed, to understand their role in the network functioning and in particular in the experimentation process. As far as possible, the surveys were completed by participant observation of key interaction moments such as annual meetings, collective farm visits, etc. All these devices enabled to collect factual information on (i) farmers' networks (aims and activities of the network, information and objects exchanged, nature and frequency of the meetings, supporting actors, number and type of farmers, long-term network dynamics, etc.), and on (ii) the experimental designs (technical objects under study, number and location of the experiments, actors' involvement, etc.). Qualitative information issued from verbatims was collected to understand how the experiments contributed to farmers' knowledge building, more generally to the agroecological transition of the farms.

Data analysis. The empirical data were first analyzed at the network level [START_REF] Benmansour | Les processus de transition agro écologique dans les collectifs agricoles : étude de son appropriation et de sa mise en oeuvre à partir de deux études de cas[END_REF][START_REF] Peureux | Organization of farmer groups impacts farmer experimentation and learning for agroecological practices[END_REF][START_REF] Ruiz | Etude d'un collectif agricole, la COPAV. Fonctionnement et expérimentations en médecines alternatives[END_REF][START_REF] Venot | Rôles d'expérimentations en arboriculture fruitière pour la transition vers l'agroécologie des exploitations[END_REF]. Comparing the actors' discourses with one another enabled to note possible discrepancies that were used to better question the network functioning. In a second step, a cross-case analysis of the seven networks was realized for a more generic interpretation of the data. An analytical framework was built on the literature on farmers' experiments and farmers' networks. We first analyzed how the networks were organized, what sort of objects or information were exchanged, and what was the role of supporting actors, from facilitators to leaders. Second we described the experiments: aims (understand a problem, find a solution…), nature of the experimental designs (referring to controlled, Darwinian, generative experiments) and organization (at the individual or collective scale). Finally, we identified the various ways the experiments realized within the networks helped farmers to learn new agroecological practices by building analytical vs actionable knowledge, local vs generic knowledge. Besides knowledge production, we identified various other ways the experiments engaged farmers in an agroecological transition.

Results

We now present major trends resulting from the cross-case analysis according the three dimensions (networks functioning, experiments, and their role in farmers learning and agroecological transition).

Characteristics and functioning of the farmers' networks under study

The size of the farmers' networks studied varied from 14 to 90 farmers. They differed in their organization and functioning, in their aim and in the role of experimentation (Table 1). SOL, GRB and CDA networks were organized around experiments. In the three cases, the networks did not pre-exist the experiment. In SOL and GRB, engineers were the ones who involved farmers in the experiment process whereas in CDA, experiment was initiated by the farmers themselves. In contrast, the farmers in CBR, CUP, COV and INS had a long history of practice exchanges, of sharing ideas and knowledge through farm and field visits, of training sessions and also of informal interactions. Experiment was only one activity among others.

The role of supporting actors varied from being a facilitator of collective actions to a referent devoted to the experiments. The most pro-active experiment referents initiated the experiments, elaborated the experimental design and the data recording protocols, analyzed data and were also responsible for the dissemination of the results among the farmers, inside or outside the network. In GRB, although the experiments were led on-farm, the engineers from the experimental organization were in charge of collecting and hierarchizing the farmers' needs and the potential solutions to be tested; then they identified the farms and plots most appropriate to carry out each experiment; and lastly they planned and monitored the trials. The SOL network was organized in the form of a participatory research; conducting the experiment was a collaborative work between pilot farmers and researchers through continuous interactions, even if each actor had a specific goal. Scientists facilitated the emerging of farmers' objectives and the collective design of innovative farming systems. Experiment outcomes were observed by the farmers but most data were monitored and collected by the researchers then shared, discussed and assessed altogether. In the COV network, one vet planned and facilitated the meetings devoted to experiments. He suggested some essential oil-based products and protocols to be tested and the data to record. He gathered information recorded by the farmers on their own farms and organized the final discussions on oil-based products' performances. Both CDA and CUP networks benefited from the support of two people: one was dedicated to facilitation whereas the other one coped with the technical aspects (monitoring experiments, collecting data, formalizing and sharing the outcomes). In only one network (CBR), the supporting actor had a very limited role in experimentation. The main reason it that she organized the network activities as a whole, in particular the training sessions where conservation agriculture experts were invited. But her activity as regards experimentation was limited to collecting the list of on-going experiments planned by each farmer, without significant contribution to their organization or monitoring. Accordingly, the farmers were willing to find external resources to help them to build and manage the experiments, and all claimed that "[they] lack [ed] hands, brains, time, and money".

Organization of experiments within the networks

Objects under experimentation

The experiments concerned either an individual technique (GRB: new fruit tree cultivars under organic farming), a new crop management (CUP: mixtures of grass species and the optimal crop management fitted to the local soil and climate conditions; CDA: optimal mix of old grain cultivars for each farmer), a new cropping system (SOL and CBR: new conservation tillage and crop rotation strategies), or new animal care protocols (COV) (Table 1).

Experimental designs

Among the farmers' networks surveyed, the experimental designs varied from very formal to very informal designs. In the informal experimental designs (e.g. CBR), the aim was to find a solution to a problem identified by the farmers; the system under experiment was quite realistic, similar to the way the farmers usually manage their crops/animals except for the practices under experiment. Some elements of the experimental choices were anticipated, but others were decided or adapted during the course of the experiment, depending on the system functioning or real climate/soil conditions, and this on-going adaptation enabled farmers to learn how to manage the new system. They observed the system dynamic, collected rather qualitative information, and did not systematically record them. The conclusions sometimes remained implicit: each farmer could draw conclusions on his/her own experiment, but did not necessarily make it explicit at the collective level. In the most formal experimental designs (e.g. GRB), several practices were compared one to another or to a control, on several micro-plots as replicates. The hypothesis tested was that the new practices would be more efficient than the control or current farmers' practices. Although carried out on real farms, such experiments followed the scientific pattern. The farmers were involved to manage crops during the experiments and implement the cropping practices, but most of the experimenting activities were taken up by the supporting actor (e.g. GRB and SOL).

A combination of several types of experimental designs

Several types of experiments were combined at the same time in some networks: formal and informal, individual and collective, at the initiative of all farmers, of leader farmers and of supporting actors. For example, in the COV network, two main kinds of experiments on alternative medicines were combined. On one side, numerous informal experiments where realized by the farmers to assess the efficiency of a given treatment (product, dosage, method of administration…) in their own situations. They decided to do the test on their own initiative, or following vets' or peers' advice. On the other side, a more formal experimentation was organized by the vet to validate generic curative protocols, which had to be suitable for every farmer in the network: the vet organized four 2-hour meetings with 6-8 farmers already using alternative medicines on their farms. They collectively defined which essential oil-based products they would test for each disease, and what would be the appropriate protocol. They also defined how they would observe and keep track of the results obtained when applying the protocols, using an observation grid. In the INS network, three types of experiments were combined: (i) some were carried out by a very experimented leader farmer in both his own greenhouses and that of other farmers; he tried to acclimate poorly-known biocontrol agents, not yet proposed by the technical animator. (ii) Other experiments were realized by less experimented farmers who tested some practices suggested by the technical animator or the leader farmer. (iii) Some experiments were organized on several farms by the experimental station to assess an agroecological practice into different contexts and farm conditions in order to build generic technical references.

Experimentation in farmers' networks as a way to favor agroecological transition

Experiments within the studied networks enabled the actors to elaborate new knowledge, as in scientific experimentation, but they also played other roles at the individual or collective levels which intertwined to contribute to the collective learning process.

Generating and sharing knowledge on the performances of the experimented practices

Depending on the network and on the type of experiments carried out within a network, the knowledge generated varied from information specific to one farmer, providing him information on how to implement a new agroecological practice on his farm, to more generic information such as technical references usable by technical advisors in varied conditions. All farmers surveyed indicated they gained personal knowledge through on-farm experiments.

For example, the second type of experiments in INS network (see Section 2) helped untrained farmers to discover the interest of biological pest control under their conditions and experiment practices already assessed in other farms. They progressively gained in entomology to better identify pests and natural enemies and learned about their life cycles. By contrast, more generic knowledge was built when a similar experimental protocol was deployed on several farms, or when complementary trials were carried out on different farms with similar monitoring: it concerned the generic sanitary protocols to cure diseases with alternative medicines for COV, the interest of mixed grass on various soil conditions for CUP, new pest control strategies for INS (thanks to the third type of experiments, see Section 2), performances of fruit cultivars under various climate conditions for GRB, and the efficiency of conservation techniques to improve soil health in SOL.

The cross-analysis suggests that promoting learning processes needs to be supported either by a scientist (SOL, CUP) or by peers (COV). For example, in SOL, to improve soil health, three small groups of farmers were organized within the network, each one having similar soils, climates, production systems and problems to solve. Within each small group, a new cropping system based on new soil management and crop rotation was co-designed between the farmers and the scientists. It was then experimented by a pilot farmer with the technical expertise of the other group members. The scientists in agronomy were responsible for recording and analyzing data. Then the three experiments were compared altogether to better understand how the new cropping practices affected soil health depending on local ecological conditions. The involvement of scientists in the trials was highly appreciated by the farmers, as it allowed them to benefit from scientific indicators of soil health (nematode numbers for example) and deepened their knowledge on soil functioning. In CUP network, the animal scientist helped building a common understanding of the problem by suggesting to consider other grass species in mixture beside alfalfa. Trials were designed during participatory meetings where the farmers, the animal scientist and a forage management advisor all decided on the location of the experiments, the mixtures to be tested, the technical practices to implement and the measurements to carry out. Once the experimental design was formalized by the researcher and the advisor, it was shared and approved by the network.

However, in other networks studied, the support did not come from scientists but peers, as indicated by a cattle farmer from COV: "I had a problem with somatic cell count. I tried homeopathy and I had some results […]. I'm in a good relationship with A [another farmer in the network]. He likes testing things. He tries and then I try the same thing, and then we check. It's like that. It's between us." In CBR network, there was a complementarity between few very innovative farmers having progressively assumed informal leader positions and the rest of the network. One of the leader farmers, who had always spent much time reading agricultural newspapers and discussing on web forums, was the first to start to experiment with cover crops. He gained information on how to implement them and how interesting it was in his own farming conditions. Then after inviting network members to come and observe the results on his farm, he convinced the rest of the network to join him in specific training sessions led by Chambers of agriculture and experts and to start working with cover crops. The other farmers experimented them on their own farms, which resulted in a larger assessment of the efficiency of the practices tested, in several soils and climate conditions, farm organizations, etc. The results, in turn, benefited the former farmer. In this case, although the objectives and protocols were planned and implemented at the individual level, the exchange of information at a collective level enabled to feed an essential need in the scope of agroecology, the search for the best-fitted practice in each location and situation.

Gaining information on related topics. Several farmers said that hosting an experiment was a way to benefit the expertise of the supporting actor on wider topics than the practice experimented, and in particular for the observation of natural regulations, a key element in agroecology. For example, some GRB fruit growers said that, during field monitoring and data collection with the supporting engineer, they learned a lot about natural enemies to control pests. Farmers of the INS network also learned to observe and recognize different pests and biological control agents with the help of the leader farmer and the entomologists accompanying the network. In the SOL network, farmers learned with scientists to use simple indicators to estimate the soil biological functioning.

Reassuring farmers' changes and improving their decision-making process. Because the experiment is realized on a limited surface area and/or because the farmer is accompanied by a supporting actor or peers, it enables him to implement a new cropping system without taking too much risk and to gain confidence. Experimentation by GRB engineers of new organic practices to control pests enabled farmers either (i) to adopt the new cropping strategy that had been experimented on their farm (when it was more efficient than the current practice), (ii) to confirm their initial cropping strategies (when the tested practice did not perform better than the current practice) and (iii) sometimes even to reconsider their system (e.g. a farmer understood that the only solution was to replant his orchard and to replace the cultivar by a low-susceptibility one because no satisfying control option could be found after several years of experimentation).

Fostering the network functioning. In CDA and COV networks, experimentation was a support for training sessions, field visits and even informal exchanges between farmers. The experiments reinforced the collective "innovation culture" within the COV network, the numerous meetings were also an appreciated opportunity for the participating farmers to exchange knowledge and experiences about alternative medicines. In CUP, which had strong historical habits of collective work in-between farmers, experimenting grass mixture on several farms and meetings organized to follow up the experiments were considered as key elements to foster the network functioning.

Discussion

Complexity around farmers' experiments

First of all, studying the experiments realized by the farmers is complex because even if conceptual categories can be drawn (see next section on intra-and inter-network variability), one experiment often falls into more than one category. For example, a farmer may be an experiment leader, a simple user or a facilitator for the others depending the experiment period or location. Moreover, there is a blurred frontier between experimenting or not. Some farmers belonging to the networks surveyed in the COTRAE project considered they were not experimenting. The reasons are twofold. First the term "experiments" has a heavy scientific dimension, which might scare some practitioners. Second, they considered they learned new knowledge by managing an agroecological system now and here instead of by planning an experiment (Renier et al., 2018). This rather shifts to adaptive management on real situations [START_REF] Foxon | Governing long-term social-ecological change : what can the adaptive management and transition management approaches learn from each other ?[END_REF]. Anyway, both experiential and experimental dimensions contribute to the farmers' learning process, as indicated by [START_REF] Lyon | How farmers research and learn: the case of arable farmers of East Anglia, UK[END_REF].

Moreover, the comparison of the seven case studies leads to the conclusion that the interaction between the individuals and networks in experimentation is much more complex than it could be initially thought from literature. Depending on the intensity of the collective dimension for building, managing and interpreting the experiments, as analyzed in the Results section, the resulting knowledge will be specific to one farming context or more generic. In particular, it depends on two dimensions: (i) Do the experiments try to answer a problem raised by one specific farmer or by the network as a whole? (ii) Do the networks aim at building actionable knowledge usable in specific local situations, to provide regional technical references, or even to build generic knowledge as in the scientific world? The different situations may interfere.

Intra-and inter-network variability of experiments

The experiments studied vary from very formal designs and protocols to much more informal ones. In the first case, the experiments are, at least partly, related to the scientific approach (controlled experimentation according to [START_REF] Ansell | Varieties of experimentalism[END_REF]. The supporting actors play a very active role, which refers to full or partial control by scientists according to [START_REF] Caniglia | Experiments and evidence in sustainability science: a typology[END_REF]. The resulting knowledge is expected to be usable outside the network (e.g. regional technical references, standard animal care protocols, soil health indicators).

Even if providing generic knowledge is the main goal, the fact that the experiments are realized on farms enables farmers to gain situated information on their own cropping or farming system. On the other hand, less formalized and only partly anticipated experimental designs, built by individual farmers, were identified. Such experiments are related to what [START_REF] Ansell | Varieties of experimentalism[END_REF] call generative experimentation in which the experiment aims at imagining and adapting a technical proposition in real time until it enables to solve the problem identified previously. The process often leads to situated knowledge easy to reuse for farmers. Difficulties to interpret the results may arise because of possible biases such as confounding factors, when some uncontrolled factors are responsible for the effects observed instead of the practices experimented. The cross-case analysis invites not to overfocus on discrepancies between farmers' experiments but rather argues for an in-depth analysis of the inner consistency of each experiment, between aims, practical organization and expected outcomes. Moreover a challenge is to imagine intermediate situations between the previous types, i.e. experiments specific enough to gain interest for individual farmers, but also shared enough among farmers to increase their capacity of analysis, by helping each farmer to make a diagnosis, understand his/her own crop or herd situation, or avoid confounding factors. One point must be highlighted, cutting across all experimental types: the experiment outcomes largely outreach the knowledge on the performances of the experimented practices: by experimenting, farmers learn how to manage a complex system or observe animals or plants differently, they gain confidence to move to a trajectory of technical change, which was also shown by [START_REF] Chantre | Trajectories of French field crop farmers moving toward sustainable farming practices: change, learning, and links with the advisory services[END_REF]. The experiment is also a support for exchanging between peers [START_REF] Garbach | Grower networks support adoption of innovations in pollination management: The roles of social learning, technical learning, and personal experience[END_REF].

Networks as a resource for experimentation:

As showed previously, it is quite important to maintain a balance between individual and collective dynamics. The collective dynamic provides new ideas and a greater reflexivity on what is realized at the individual level. Complementary, the experiments at the individual level are a way to acquire situated knowledge directly usable by the individuals. Such process is long since it requires a reflexive analysis on what to change, how to change (before experimenting) and then how much change is achieved, and about the performances and limits of the tested system. That is where the network dynamic, by offering a variety of situations to observe and knowledge exchanges, saves time compared to individual experimenting dynamics.

In all the studied networks where collective experiment occurred, farmers were involved in the three steps defined by [START_REF] Hocdé | L'expérimentation en milieu paysan[END_REF] in the experimentation process: theme definition, protocol definition and results assessment. That refers to what the authors called collegial experimentation. But our cases showed a greater diversity of ways to involve farmers. In the first step, definition of the experimentation theme, farmers problems can be collected and farmers can be asked to agree on suggested goals or practices to test, or the experimentation theme can come from farmers' ideas. Regarding the second step, definition of the experimental protocol, the farmers surveyed often played a significant part in designing and planning the experimental protocol. But, only in a few cases, they were involved throughout the experimentation process and in particular when decisions had to be taken in the course of action (in SOL network, conducting the experiment was even a collaborative work between pilot farmers and researchers through continuous interactions). It must be noted that even when a strong collective experimenting process occurred, the last step (results assessment) always relied on the supporting actors. Monitoring the experiments, collecting data, formalizing the outcomes, disseminating results are very time-consuming activities in the long run which farmers usually cannot afford.

All our cases show that collective experimentation process requires facilitation activities. The supporting actors committed to knowledge production are not only researchers but also agricultural advisors from different types of organizations or engineers from an experimentation organization. These supporting actors play a key role for coordinating the networks and keeping collective dynamics. However, the term "Farmers" is not a homogenous category: some play a central role and help the others in the experimentation process because they have more time than the others to implement the trials, they are more familiar with the experimental approach, they accept to take more risks on their farms or because they are passionate to transfer knowledge to peers. Thanks to their experimentation leading activity, they can gradually embark others on experimentation. When taking farmers' involvement into account, one must question who the farmers committed and involved in experiment definition are and who they speak for.

Conclusion: Towards the combination of various experiments to favor the agroecological transition?

The article presents and analyses the diversity of experiments within seven farmers' networks experimenting agroecological practices. The diversity is described according several dimensions: role of scientists, technical advisors and farmers; nature of the experimental designs and protocols; nature of knowledge generated. It was shown that by experimenting, farmers not only assessed the performances of the experimented practices, they also learned how to manage a complex system and observe animals or plants differently, they gained confidence to move to a trajectory of technical change, and in some cases, the experiments stabilized the network for a period by supporting the exchanges between peers.

Based on the previous results, we assume that the combination between various types of experiments can be an efficient way for helping farmers to adopt and adapt agroecological systems. Such a combination was indeed observed on a few studied networks: some combined experiments designed by the farmers with others, on the same farms, leaded by an experimental station. Others partly planned experiments on several farm plots to be able to compare results. But the combination of complementary types of experiments has never been fully conceptualized in agricultural sciences. It raises several theoretical questions: how can the diversity of experiments be organized? by comparisons between farms the same year to explore the effects of several environmental situations and/or by comparisons along several years to capture long-term ecological dynamics? Which complementarity between on-farm and on-station experiments? How farmers can contribute to design and manage onstation experiments? It seems important to push forward researches that hybridize knowledge and ways of learning of both scientists and practitioners [START_REF] Francis | Innovative education in agroecology: Experiential learning for a sustainable agriculture[END_REF] to favor technical change and reach the large agroecological transition expected by both the society and public policies.

Table 1 .

 1 The seven networks' characteristics (the number of farmers interviewed is indicated in italic characters)

	Network Farmer number and	Organization of the network and	Aim of the collective	Technical objects
		production systems	supporting actor		experimented
	SOL	15 arable-crop	3 subgroups corresponding to	Experimenting to improve soil	Conservation tillage
		farmers	different production systems. On	health and learn knowledge on	practices, crop
		(N=3)	cropping system designed with the each, one pilot farmer experimented a	soil functioning	rotations
			rest of the subgroup. The experiments
			were monitored by two scientists in
			agronomy
	GRB	15 organic fruit	An experimental organization led by	Hosting agronomical	Fruit cultivars,
		growers (apple,	organic farmers who develops on-	experiments for the	biocontrol products,
		apricot, cherry,	station and on-farm experiments to	experimental organization	cropping practices for
		peach)	help growers improve their practices.		pest control
		(N=13)	2 engineers in charge of experiments.
	CDA	18 mixed crop	2 persons supporting the network	Testing old grain cultivars and	Crop associations
		livestock farmers	activities: one facilitates the collective	being autonomous in seeds	(legumes cereals), old
		(N=2)	monitors the experiments action and one organizes and	selling the grains production, processing and	grain cultivars
	CBR	30 farms (near 100	A network with a long history (close to	Historical aims: comparing	Conservation tillage
		farmers); mixed-crop-	50 years), in search for very	work margins and practices to	practices, animal
		livestock farmers (the	innovative practices thanks to training	improve the systems. More	feeding
		majority have dairy	sessions, farm visits, study trips and	recent aims: maximizing cover
		cattle, some beef	experiments. It is accompanied by an	crops and minimizing tillage;
		cattle)	advisor from the Chamber of	improving animal feed self-
		(N=9)	Agriculture	sufficiency with on-farm experiments
	CUP	14 livestock farmers	A network accompanied by 1 technical	Reducing the use of inputs and	Alfalfa cropping, then
		formerly using maize	advisor in charge of the network	improving the level of feed	mixtures of grass
		silage and now	animation and 1 animal science	autonomy on farm, sharing	species best fitted to
		changing for grass	researcher helping to organize the	agricultural machines (hay	local soil and climate
		hay	experiments	harvest) and mutual helping for	conditions
		(N=7)		labor-demanding tasks
	COV	About 90 livestock	Farmers organized in a non-profit	A mutual responsibility for	Treatments based on
		farmers	association linked to a veterinary clinic	animal health between the	essential oils and
		(N=11)	(4 vets) by an agreement. One vet in charge of developing the use of	farmers and the vets	alternative medicines, care protocols to be
			alternative medicines in the network		used by farmers
	INS	About 20 farmers.	An informal network accompanied by	Increasing knowledge on	Biological pest control,
		Fruit and vegetable	a technical advisor from the Chamber	functional biodiversity ;	mostly towards
		growers	of Agriculture and a logistic animator	developing local pest control	functional biodiversity
		(N=3)	development association. Close from a local organic agriculture	practices
			relationships with entomologists from
			technical and research institutes

th European IFSA Symposium, 1-5 July 2018, Chania (Greece)

French acronym for "Groupement d'intérêt économique et environnemental", farmers' networks financially supported by the French government since

to favor agroecological transition on farms

Acknowledgments

The project was supported by the program Pour et Sur le Développement Régional (PSDR4 Rhône-Alpes) and funded by INRA, Auvergne-Rhône-Alpes Region, Irstea and European Union through FEADER and EIP AGRI. The authors thank S. Benmansour, A Peureux, C. Ruiz and C. Venot for the first analysis at the farmer's networks level, and all the professionals involved in the project for the good execution of the research.