Nicolas Baghdadi

Nicolas Gratiot

Jean-Pierre Lefebvre

Carlos Oliveros

Anne Bourguignon

J.-P Lefebvre

Coastline and mudbank monitoring in French Guiana: contributions of radar and optical satellite imagery

The constant migration of mudbanks resulting from the sedimentary discharge of the Amazon River has an enormous impact on the French Guianese economy. Consequently, there is great local interest in finding tools that can be used in mapping and monitoring the mudbank migration with an acceptable level of reliability and a high frequency of measurement. This involves the ability to detect submarine mudbanks that interfere with access to port channels and impede navigation. Radar and optical satellite images of French Guiana acquired between 1997 and 2001 have been analysed to assess their utility in detecting mudbanks and monitoring coastline change. In the present study, the information derived from radar and optical satellite imagery was analysed with respect to tidal height. The influence of the radar incidence angle was considered, as well as the advantages of having multidate sequences when mapping coastal zones undergoing significant change. A comparative study between radar (European Remote Sensing Satellite (ERS) and RADARSAT) and optical (advanced spaceborne thermal emission and reflection radiometer (ASTER)) images was also conducted. The results show that low-angle radar is more suitable for detecting mudbanks, whereas high-angle radar is more appropriate for monitoring coastline change. Emerged mudbanks and mudbanks under a shallow layer of water (a few tens of centimetres at the most) are easily detectable in radar images. For high tidal levels, the optical images provide more information on the mudbanks than the radar images. Conversely, for low tidal levels, the information on the mudbanks is more detailed with radar imagery.

Résumé. Le déplacement continu des bancs de vase en provenance de l'Amazone a un impact très important sur l'économie guyanaise. La recherche d'outils permettant la cartographie des bancs et le suivi de leur migration dans des conditions acceptables de fiabilité et de rapidité présente donc un grand intérêt local. Ceci se traduit par la détection en mer des bancs de vase qui viennent perturber l'accès aux chenaux (ports) ce qui constitue un gêne pour la navigation. Des images satellitaires radar et optique, acquises sur la Guyane française entre 1997 et 2001, ont été analysées pour examiner leurs apports à la détection des bancs de vase, et au suivi de l'évolution du trait de côte. L'information issue de l'imagerie satellitaire radar et optique a été étudiée en fonction de la hauteur d'eau. Nous avons analysé l'influence de l'angle d'incidence radar et l'intérêt des séquences multi-dates pour cartographier les zones côtières soumises à des importantes modifications. Une étude comparative entre imagerie radar (ERS et RADARSAT) et optique (ASTER) a également été effectuée ainsi que la relation entre bathymétrie et information satellitaire. Les résultats montrent qu'une incidence radar faible est plus adaptée à la détection des bancs de vase tandis qu'une incidence radar forte est plus appropriée pour le suivi du trait de côte. Les bancs de vase émergés ou immergés sous une faible couche d'eau (quelques dizaines de centimètres au maximum) sont facilement détectables sur les images radar. Pour des hauteurs d'eau élevées, l'imagerie optique permet une meilleure caractérisation des bancs de vase comparativement à l'imagerie radar. Dans le cas d'une faible hauteur d'eau, les résultats montrent que les informations sur les bancs de vase sont plus détaillées avec l'imagerie radar.

Introduction

In view of its geographic location (Figure 1) to the northwest of the mouth of the Amazon River (Cape Orange), the coast of French Guiana is constantly affected by the migration of mudbanks under the influence of surface oceanic circulation [START_REF] Augustinus | The changing shoreline of Surinam (South America)[END_REF]. The Amazon drains an enormous quantity of fine-grained sediments, estimated at some 1.2 billion tonnes per year [START_REF] Eisma | Recent and sub-recent changes in the dispersal of Amazon mud[END_REF]. A large part of these sediments flows out into the Atlantic Ocean, although an estimated 15%-20% is transported along the French Guiana coast carried by the Guianese Current [START_REF] Wells | Physical processes and fine-grained sediment dynamics, coast of Surinam, South America[END_REF]. The migration of mudbanks generates cyclic depositional and erosional phases that considerably alter the morphology of the French Guiana and Surinam coasts [START_REF] Augustinus | The changing shoreline of Surinam (South America)[END_REF]. The mudbanks migrate from southeast to northwest, particularly during the rainy season, at an annual rate of about 1 km per year, judging from the rate of movement of their intertidal zone [START_REF] Froidefond | Migration of mud-banks and changing coastline in French Guiana[END_REF]. The region is subjected to a dominant wave regime generated by the trade winds from the northeast that persist throughout the majority of the year. Average wave heights along the Guiana coast range from 0.75 m in September to 1.6 m during the period of high winds (February to May). Wave height nevertheless varies locally towards the coastline depending on the nature of the seabed and progressively decreases with the interaction of water laden heavily with mud. Sediment mobilization is high when ocean forcing is strong (average wind speeds 6-8 m/s from February to May) and is reflected by an accumulation of fluid mud at the front of the mudbank, forming mud lakes. When ocean forcing decreases (June to January), the fluid mud consolidates and contributes to the progression of the mudbank. Tidal range along the Guiana coast indicates upper mesotidal conditions, with spring tide low-and high-water levels being 1.0 and 3.1 m, respectively, above chart datum (tide gauge station near Kourou; Service hydrographique et océanographique de la marine (SHOM)).

The mudbanks can extend alongshore for 20-35 km and offshore out to the 15 m isobath, i.e., about 20 km from the coast (Figure 2). They are linked to the coast by heterogeneous geomorphic units, including (i) the schorre (i.e., that part only submerged during the highest spring tides), (ii) the intertidal zone (above water at low level tide), and (iii) the subtidal zone (permanently submerged).

Four main coastal features can be described: (i) the coastline is defined as the boundary between the mature mangroves and the ocean fringe; (ii) the intertidal zone (or upper slikke), adjacent to the coast, is made up of an accumulation of plastic sediments that can be shaped into perennial features such as tidal dewatering channels and longshore bars (clinoforms) and is characterized by algal and plant colonies and remains static during mudbank migration; (iii) the outer fringe of the intertidal zone (lower slikke) is composed of poorly consolidated bare mud that is still transportable; and (iv) the subtidal zone, as yet poorly understood, can be identified primarily by its damping effects on incident swell waves.

The interbank zones typically have a sawtooth shoreline pattern. Because of the absence of a mud substrate, there is less damping of swell and the waves reach the coast. The breaking surf contributes to shoreline regression with the creation of microcliffs. The trees growing in the erosional zone are uprooted and form a characteristic band of debris along the coast.

Two geomorphic units, which lie directly over an old consolidated clay seabed, can be observed in the interbank zone, namely "mudcapes" and mudflats. These units do not extend into the subtidal zone. The mudcapes are created by sediments trapped near the estuaries during transport. Owing to the direction of littoral drift on the French Guianese continental shelf, the mudcapes generally form on the right banks of the river mouths. The mudflats form when sediments are trapped by specific coastline features, such as coves and capes.

The presence of mudbanks brings about rapid changes in the coastal zone. On the one hand, changes in seabed depth in areas of accretion frequently hinder navigation. On the other hand, areas of erosion are related to shoreline regression of a few hundred metres per year [START_REF] Allard | Cartographie de l'évolution du trait de côte en Guyane de 1950 à 1994[END_REF]. This retreat has a considerable effect on the coastal ecosystem, mainly because of the massive destruction of the mangroves [START_REF] Singhroy | Interpretation of SAR images for coastal zone mapping in Guyana[END_REF]. These rapid rates of change cause real problems in coastal management. Fisheries, ocean transport, and tourism must constantly adapt to these changes.

The French Guianese authorities, however, are most concerned about the impacts on port activities because of the great economic importance. Sedimentation in the access channels to the ports of Cayenne (the economic capital) and Kourou (the space centre) can seriously disrupt commercial shipping traffic. This makes daily dredging necessary, an ongoing and costly operation. Remaining informed on the sedimentation state of the navigation channels is a major concern, a need that is currently met through bathymetric monitoring by regular echo sounding. Dredging is a laborious task that would be easier to plan and carry out if a quick preliminary reconnaissance were feasible, even if only approximate (concentrating on the most important sites). The ability to monitor mudbank evolution and map mudbank location throughout the area can be crucial, especially during periods of high sedimentation and coastal erosion. Spaceborne remote sensing can provide data on the Earth's surface in a way that is repetitive, programmable, and relatively inexpensive. A monitoring system using satellite images can facilitate planning and provide managers with an effective decision-making tool.

In view of the humid tropical climate prevalent in this region, the use of optical images for coastal environment mapping poses a problem owing to the frequent cloud cover. Radar sensors can overcome most of the weather constraints, thus providing a great advantage when observations need to be recorded all year round. In addition, radar images are highly sensitive to surface roughness and may be able to detect the presence of an underwater mudbank, providing that the following hypotheses are confirmed:

(1) An increase in surface roughness tends to increase the amount of radar backscatter [START_REF] Baghdadi | Potential of ERS and RADARSAT data for surface roughness monitoring over bare agricultural fields[END_REF][START_REF] Rakotoarivony | Radar backscattering over agricultural bare soils[END_REF]. In shallow-water areas (mudbanks, for example), a change in wave motion occurs in a shoreward direction. The influence of the seabed increases directly with the shallowness of the water and the height of the waves and can cause the waves to break. Wave damping and breaking can be revealed by a change in the appearance of the sea surface, and in this way the associated mudbank can be detected in radar images.

(2) Wave damping, which commonly occurs on the nearshore mudbank, makes the water surface smoother. The high near-bed sediment load (fluid mud layer), commonly on the top of the bank, tends to attenuate water ripples by changing capillary motion and can be reflected by lower backscatter.

(3) Conversely, waves breaking over a consolidated mud bed will increase the water surface roughness. Similarly, depending on wave conditions, a sudden rise in the seabed can cause breakers that show up in the images in the form of a lineation at the discontinuity [START_REF] Vogelzang | On the signatures of river outflow fronts in radar imagery[END_REF].

The main objective of the present study is to test the potential of European Remote Sensing Satellite (ERS) and RADARSAT images to detect and map mudbanks. Images obtained between 1997 and 2001 have been studied in the light of variable acquisition parameters and tidal conditions. The radar images are compared to optical images obtained from the advanced spaceborne thermal emission and reflection radiometer (ASTER) sensor. The present study aimed to determine the capabilities of remote sensing tools, specifically in terms of mapping mudbanks and coastline monitoring. This article presents the data used, the interpretation of radar and optical images, and the results obtained.

Database description

Six RADARSAT images, two ERS images, and three ASTER images were studied. The radar images, obtained between February 1997 and May 2001, have incidence angles of 28°-47°for the RADARSAT images and about 23°for the ERS images. The ASTER images have 14 spectral bands, from the visible to the thermal infrared. Table 1 lists the specifications of the images used.

The radar images were radiometrically calibrated for the purpose of converting signal intensity to the backscattering coefficient σ o [START_REF] Laur | Derivation of backscattering coefficient sigma-0 in ERS-1 SAR PRI products[END_REF][START_REF] Shepherd | Extraction of beta nought and sigma nought from RADARSAT CDPF products[END_REF]. The radar and optical images were then geometrically corrected based on ground-control points taken from the Institut Géographique National, Paris (IGN) topographic base maps at1:25000scale (Universal Transverse Mercator (UTM), zone 22, International 1909). To improve the quality of the radar images without losing information, they were filtered usinga3×3median filter. The radar images were processed to enhance the detection of geomorphic features. Referencing accuracy was about 20 m.

Data concerning tidal level, tidal phase, wind speed and direction, and rainfall were available for the dates that the satellite images were acquired (Table 1).

Tidal height was recorded using two tide gauges located at Kourou (5°10′N, 52°37′W) and Cayenne (4°57′N, 52°20′W), managed by the Direction departementale de l'équipement (DDE). Data were derived from digital tidal curves, giving a tidal amplitude accuracy of the order of 1 cm. For certain dates, when data were lacking for one or both of the stations, the relationship between the stations was analysed using tidal predictions of SHOM. This analysis revealed an average difference between tidal heights measured at Kourou and Cayenne of approximately 0.11 m (Kourou = Cayenne -0.11 m). For those dates where no tidal curves were available (7-04-2001 and 8-03-2001), the values derived from the tidal curves at Kourou and Cayenne were compared against those predicted by SHOM for certain dates; the average difference proved to be minor (+0.04 m for Kourou and +0.05 m for Cayenne). The variance between the tidal predictions and the tidal curves is nevertheless lower for Kourou than for Cayenne. Thus, to calculate tidal height at Kourou, we used the SHOM predictions for Kourou corrected for the average variance observed between the tidal curve for Kourou and the predicted value (+0.04 m). To calculate tidal height at Cayenne, we simply added 0.11 m to the value estimated for Kourou.

The tidal heights for the images vary between 1.05 and 2.88 m for the Kourou station and between 1.16 and 2.99 m for the Cayenne station (tidal height is the instantaneous altitude of the sea surface above low-water datum).

The meteorologic data were provided by Météo France. The wind data averaged over3hv a r yslightly depending on the station (maximum 20°for wind direction and 2 m/s for wind speed). The adopted values correspond to the average for the four available stations (3 at Kourou and 1 at Cayenne). The rainfall data, measured with a 6 min interval, reveal no rain for the dates when the images were acquired.

No wave observations or measurements were available for the Guianese shoreline and coastal zone. The waves that reach the shore are generated by wind conditions over the Atlantic; they are essentially derived from the northeast, where trade winds persist throughout the majority of the year. The tidal heights in bold were derived from tidal curves.

Table 1. Specifications of the images used in the study.

Mudbank monitoring

The potential of radar imagery

Interpretation of radar images

The radar images were interpreted according to incidence angle and tidal height. The geomorphic features described previously were observable in the processed images from the ERS and RADARSAT scenes. The interaction between the radar wave and the mudbanks is affected mainly by surface roughness, and this is reflected in turn by the return signal. Two roughness states related to the geomorphic features were recognised: a smooth state corresponding to fluid mud layers, and a rough state corresponding to slikke compartments. Microcliffs and ridges provide typical high backscattering coefficients.

The image acquired on 15-02-1997 (Figure 3a) shows the location of the part of the mudbank that is either above water or under a shallow layer of water at low tide level (region labelled 1). Easily identifiable and corresponding to bare and smooth mud or flat calm water, this part of the bank yields a low radar response. It is easily recognised owing to the low tidal height (1.55 m) at the moment the image was taken. A slikke is detectable in the same image, mostly above water at the time of acquisition, and with a mangrove in its early stage of colonization (region 2). It is characterized by a high radar backscatter with a heterogeneous distribution. The mature mangrove is also characterized by a high backscatter response, but this time with a very homogeneous distribution. Inland from region 2, a few low-backscatter areas are noted, corresponding to flat calm water or to a network of mudflat streams. The appearance of a slikke in front of the mouth of the Kaw River was observed during a field survey in 1998 (Lefebvre et al. 2 ). The present radar image indicates that the slikke was already present in 1997.

In the RADARSAT image taken on 1-05-2001 (Figure 3b), a mudflat some 1500 m wide and extending 6 km into the mouth of the Mahury River is easily identified (region 3). Because of the low tidal height (1.46 m) at the moment the image was acquired, the mudflat is either emerged or under a shallow layer of water. Region 1 of the mudbank in the 15-02-1997 ERS-1 image caused the coast to prograde in places over a period of 4 years (Figure 3b, region 4). By comparing the 15-02-1997 image (Figure 3a, region 1) with the 1-05-2001 image (Figure 3b, region 3), we note a westward migration of the mudbanks and confirm a rate of migration of about 1 km per year [START_REF] Froidefond | Migration of mud-banks and changing coastline in French Guiana[END_REF].

Tidal height for the RADARSAT image taken on 7-04-2001 (Figure 4a) was about 2.80 m, and only the edge of the mudcape is distinguishable by the presence of a highbackscatter lineation (region 5). The bright radar response observed at the lineation in region 5 represents a mudflat formed by accumulating sediments. The ground truthing carried out in 2002 in this area indicates that this signal feature is related to the existence of a microcliff some 0.30 m high. In the image taken on 24-04-2001 (Figure 4b), this lineation is barely visible over a small portion of the bank (region 6). This could be due to (i) tidal height, which was 19 cm higher at the time; (ii) the difference in incidence angle (40°on 7-04-2001 and 47°on 24-04-2001); or (iii) a difference in wave action.

In the ERS image taken on 8-09-1999 (Figure 5a)w ec a n locate the slikke portion of the mudbank that extends 20 km from Kourou to Cayenne, with a maximum width of 4 km. Part of this slikke is above water, and part is under a shallow layer of water. The area generally shows low backscatter (smooth, wet mud or a shallow layer of calm water) interrupted locally by very high backscatter (ridges). The drainage networks are also visible in Figure 5a, which yield an intermediate radar response (region 7). In the image dated 14-06-2000 (Figure 5b) we note areas of ocean with a low radar response (region 8), possibly produced by atmospheric disturbance [START_REF] Trebossen | Contribution of radar SAR imagery for mapping coastal's areas: examples of sedimentational and erosional zones in French Guiana and Mauritania[END_REF]. The sedimentation at the mouth of the Mahury River is clearly depicted in the image taken on 8-09-1999 (Figure 6a, region 9), being major along the right bank and minor along the left bank.

Incidence angle and tidal height

Three factors seem to be important in controlling radar reflectance within our study area: (i) the effect of incidence angle θ,( ii) the relationship between radar signal and tidal height H (relative to low-water datum) at the moment the image was taken, and (iii) the wave conditions. Owing to the lack of data, the effect of wave forcing was not quantified in this study. Although the various field investigations carried out during the Programme National d'Environnement Côtier (PNEC) national programme for coastal environments (2000)(2001)(2002)(2003)(2004) helped during image interpretation, the opportunities for ground truthing coinciding with imagery were very limited. The following analysis thus remains subject to discussion and interpretation. A comparison between images, presented in the following points, enables a better understanding of the effects of the angle of radar incidence and tidal height.

(1) The images taken on 1-05-2001 and 7-04-2001 have similar incidence angles (40°and 41°, respectively), and a time gap that is small enough to assume that no major geomorphic evolution occurred between the two (Figures 3b and4a). Any differences between the images would thus be due to oceanic conditions (wave, tidal height (H), etc.). One area, which appears submerged on 7-04-2001, is above water on 1-05-2001 (Figure 3b, region 10). Tidal heights were 2.80 and 1.46 m, respectively, when the images were taken. Since the images were taken only 1 month apart, the emergence of this area in the 1-05-2001 image is attributed to this large difference in tidal height. The mudflat area extends 1 km offshore in places. The bright band labelled 5 in Figure 4a may represent waves breaking at the submerged seaward scarp margin of region 10 in Figure 3b. This margin may correspond to a "bar-like" mud feature, as reported by [START_REF] Allison | Seasonal sediment storage on mudflats adjacent to the Amazon River[END_REF] along the Cabo Orange at the border between French Guiana and Brazil. The authors reported a colonization of the bar-like feature in a few months, and a similar observation is also deduced from the optical image interpretation presented in the subsections to The potential of optical imagery. The variations observed between these two images are essentially due to the difference in tidal height (about 1.34 m). Such a large difference means that it is difficult to analyse the influence of the tidal phase, which was outgoing on 7-04-2001 and incoming on 1-05-2001. The wind conditions were similar for the two dates (cf. Table 1).

(2) The images taken on 7-04-2001 and 24-04-2001 (Figures 4a and4b) represent a case of more comparative tidal heights (2.80 and 2.99 m at Cayenne, respectively). The lineation observed in the 7-04-2001 image, representing an area of high backscatter (Figure 4a, region 5), is only partially visible in the 24-04-2001 image (region 6). This could be because of the difference in incidence angle (41°on 7-04-2001 and 47°o n 24-04-2001) and (or) the small difference in tidal height associated with a higher elevation of region 6 compared with region 5 (0.19 m). Between 7-04-2001 and 1-05-2001, the wind regime moved progressively from the northeast (50°) to the east (80°). The early April swell is derived from the northeast, whereas the late April swell is derived from the east. Thus, the wave incidence along the shoreline changes considerably in the two images. In addition, the swell from the east is not as strong as that from the northeast. The wave breaking in the 7-04-2001 image (region 5) is no longer observed in the 24-04-2001 image because of a higher tidal height and a lower amplitude swell at this time. The tidal phase was outgoing for both images and thus cannot explain any differences.

(3) For the images taken on 7-04-2001 and 21-04-2001 (Figures 4a and6b), the difference in tidal height was 59 cm (2.80 and 2.21 m, respectively, at Cayenne). Wind conditions and tidal phase were similar during acquisition of the two images. The 14 days separating the two images is considered too short for any major geomorphic (4) In the image taken on 21-04-2001 (Figure 7b) ,af e w thin linear elements of the shoreward margins are recognised (regions 13 and 14) that are not entirely visible, nor as clear, as in the 1-05-2001 image (Figure 7a), despite tidal height being some 0.75 m higher than in the 1-05-2001 image (H = 1.46 m). The images were acquired during different tidal phases, outgoing on 21-04-2001 and incoming on 1-05-2001. It is not possible to analyse the influence that this variable has on the ability to detect linear features. Wind strength and direction were similar during acquisition of the two images (cf. Table 1). This comparison seems to confirm the advantage of images with a low incidence angle for detecting linear features (θ = 28°for 21-04-2001 and θ = 40°for 1-05-2001).

(5) The Kourou mudbank appears much wider in September 1999 than in February 1999 (Figures 8b and8a, respectively). For example, part of the Kourou bank is above water in the 8-09-1999 image and submerged in the 22-02-1999 image (Figure 8b, region 15). This is due to the low tidal height in September (0.84 m difference in tidal height between the two images), probably accentuated by extension of the mudflat itself during the 7 months separating the two images. The offshore extension of some 3 km observed between the two images is related to a mean slope of 1/4000 m, which is significantly lower than the mean value for stable mudflats of 1/1600 m [START_REF] Froidefond | Migration of mud-banks and changing coastline in French Guiana[END_REF]. Areas of bare mud are easily detectable in Figure 8b, which may again be due to the low incidence angle (47°for the image taken in February compared with 23°for the image taken in September).

(6) A larger area of the Kourou bank was emerged in June 2000 than in September 1999 (Figures 5b and5a, respectively), despite a tidal height of 1.35 m in June 2000 compared with 1.05 m in September 1999.

Considering the 9 months separating these two images, this difference is simply due to the natural evolution of the mudbank (sedimentation). However, the land-water boundary has not changed. The major sedimentation that occurred between September 1999 and June 2000 is not surprising, as it corresponds to the most active period of winds and wave forcing [START_REF] Nedeco | Surinam transportation study: report on hydraulic investigation[END_REF].

The potential of optical imagery

Interpretation of optical images

Cartography becomes more complex in humid tropical zones because of the poor representation by optical satellite imagery for climatic reasons. Not many optical images are available for French Guiana. Figure 9 is an ASTER false colour composite taken on 25-09-2001 using channels 4 (1.6-1.7 µm, shortwave infrared (SWIR)), 2 (0.63-0.69 µm, visible and nearinfrared (VNIR)), and 1 (0.52-0.60 µm, VNIR), corresponding to the red, green, and blue filters, respectively. In the ASTER image, the various areas shown are represented by different spectral signatures. Onshore, the mature mangrove cover appears as a deep red colour. In the coastal areas, the emerged part of the mudbanks can be distinguished by their grey colour, with the red spots corresponding to patches of growing mangrove. Offshore, the colours range from light green and blue along the shore, shading to darker blue farther offshore. The colours represent sediment-laden coastal waters of relatively shallow depth, and then a deepening of the water column with less sediment load.

The clouds appear in white and may have a black outline representing the shadow they cast.

As for the mudflat labelled region 10 (Figure 9), spectral variations are noted in the ASTER image; red represents the emerged part of the mudbank covered by mangrove, darker colours represent the emerged parts of the bank without vegetation, and blue-green represents the submerged part of the bank.

Comparison between optical and radar images

A comparison between the 31-10-2000 ASTER image (H = 1.84 m) and the 22-02-1999 radar image (H = 2.00 m) (Figures 10a and10b), which have very similar tidal heights (0.16 m difference), reveals good consistency concerning the location of the land-water boundary and the mudcapes, despite a gap of 18 months between the two. The mudcape has not changed significantly in this part of the coast.

A comparison between the ASTER image taken on 25-09-2001 (Figure 9) and the radar images highlights the topographic and textural situation of the right part of the Mahury River mouth. The following analysis is proposed, bearing in mind that a gap of 5 months exists between the acquisition of the radar images (April-May 2001) and acquisition of the ASTER image (September 2001). Considering the natural geomorphic evolution that may have taken place, the land-water boundary observed in the ASTER image is in good agreement with those of the 1-05-2001 and 21-04-2001 radar images (red and white lines). Furthermore, there is a satisfactory agreement between the limit of vegetation and the land-water boundary observed in the 7-04-2001 radar image (green line). Considering the tidal heights associated with the time of acquisition of these four images, region 10 is a mudcape that shows only a minor topographic variation, between H = 2.55 m and H = 2.80 m. Furthermore, the small patches of mangrove observed in region 10 are associated with a recent and sparse plant colonization. Consequently, the highbackscatter response of region 10 observed 5 months earlier in the 1-05-2001 and 21-04-2001 radar images (Figures 3b and6b) is not due to a young mangrove, but to bare mud undergoing the processes of consolidation. Hence, radar backscatter may be very high without any vegetation cover. The low-backscatter response of the soft fluid mud layer provides a drastic contrast and thus makes the radar system a useful tool for the interpretation of mudbank features.

Considering the natural morphodynamics that may have occurred, the land-water boundary observed in the ASTER image of 25-09-2001 is in good agreement with the radar image of 21-04-2001 (white line). By comparing the 25-09-2001 ASTER image (H = 2.55 m) with the 7-04-2001 radar image (H = 2.80 m) (green line, Figure 9), we note that when tidal levels are high and similar and the time gap is small, then the optical image is preferable because it yields a better mapping of the mudbanks. For the same case, the radar image provides less information. In the 7-04-2001 image, the only visible signs are high-backscatter lineations corresponding to microcliffs (region 5, Figure 4a).

The soft mudflat detected in the 1-05-2001 radar image (region 3) is not visible (submerged) in the ASTER image. The blue-green colour observed in this coastal area does not seem indicative of a mudflat because it extends well beyond the outer edges of the mudflats detected in the radar image. The colour of the water in the image may in fact be related to both the sediment load in the water and the depth to the seabed (representative of turbidity). Region 3 is certainly subjected to active erosion and vertical mixing processes. Owing to the very low settling velocity of cohesive sediments in this region (2 × 10 -5 -2×10 -4 m/s; [START_REF] Gratiot | Dynamic of mud banks in French Guiana: an experimental investigation of sediment settling processes[END_REF], the turbidity plumes associated with areas of erosion commonly extend over a long distance. This limits the potential of optical images in accurately locating the submerged parts of mudbanks. This drawback is also valid for radar images and, during this work, no significant signature was identified for water depths exceeding a few tens of centimetres.

In the case of low and similar tidal heights, comparing the ASTER image taken on 8-03-2001 (H = 1.24 m) with the ERS images taken on 14-06-2000 (H = 1.35 m) and 8-09-1999 (H = 1.05 m) (Figures 11a, 11b, and11c, respectively) reveals that the information concerning the mudbank is more detailed with radar imagery. This highlights the advantage of radar images with a low incidence angle compared to optical images. Between June 2000 and March 2001, the mudbank migrated westwards, with mudflat retreat to the southeast and accretion to the northwest. This trend was confirmed by field observations carried out in 2001. Surprisingly, this cannot be seen in the ASTER image. This led us to conclude that the ASTER image does not provide sufficient data concerning the extension of the mudbank that, according to the image but in contradiction with field observations, had mostly disappeared. This remains to be confirmed on the basis of the radar and optical images acquired on similar dates.

Coastline change

Coastline mapping provides information that is important for both coastal management and coastal development. In view of the difficulties associated with coastal access, the use of radar data can make the task of mapping easier and faster because, unlike optical data, radar data are available regardless of the cloud cover. Thus, by using multidate ERS and RADARSAT image sequences, we can monitor coastline change.

A composite image is shown in Figure 12a to illustrate coastline change over time. We selected images with similar tidal heights and reasonably large time gaps between them (15-02-1997 with H = 1.55 m, 14-06-2000 with H = 1.46 m, 1-05-2001 with H = 1.46 m). This figure shows that radar imagery is well suited for mapping and updating coastline change in many areas. Significant changes are observed locally (between 500 and 1000 m over 3 or 4 years). Similar results have been obtained using RADARSAT images on the Guiana coastline [START_REF] Singhroy | Interpretation of SAR images for coastal zone mapping in Guyana[END_REF][START_REF] Allard | Cartographie de l'évolution du trait de côte en Guyane de 1950 à 1994[END_REF]. Figure 12b illustrates the various directions of coastal movement by superposing the land-water boundary from the 1999 and 2001 images over the image taken on 15-02-1997. This is an efficient way of observing where marked erosion and deposition occur.

The land-water boundary is much clearer in the images with high incidence angles (15-02-1997, 7-04-2001, 24-04-2001, and 1-05-2001; θ > 40°) and less visible in the image taken on 21-04-2001 (θ = 28°) and the images taken on 14-06-2000 and 8-09-1999 (θ = 23°). Therefore, a higher θ value is preferable when mapping the coastline using radar images. The RADARSAT images yield a better definition of the coastline because of the high incidence angles that can be obtained.

Conclusions and outlook

The negative economic impacts that mudbank migration can have on the French Guiana coast in terms of tourism, fisheries, and harbour dredging demonstrate the need to find new detection methods capable of tracking these movements in near-real time. The ability to detect variations in sea surface roughness from radar images is advantageous in that these data are not affected by cloud cover. A change in roughness tends to be associated with either an increase due to microcliffs or mud roughness on slikkes, or a decrease due to fluid mud layers and soft mudflats. In this context, satellite images could provide a tool of choice for acquiring up-to-date, repetitive data that are capable of providing decision-makers with useful tracking information. With appropriate programming, the satellite images could be made into databases that could be essential in coastal management.

The purpose of this study was to define a methodology for monitoring change in the coastal environment in an equatorial climatic zone, to help establish a process for rapid evaluation, and to propose a practical tool for locating the position of mudbanks. For better detection, the images should be acquired on dates when the tidal level is low. Low-angle radar is best suited to mapping the mudbanks (slikkes, mudflats, and fluid mud layers), whereas high-angle radar is better adapted to monitoring the coastline. The present work reveals that no clear signature can be related to mudbanks when water depth exceeds a few tens of centimetres. For high tidal levels, the optical images seem to provide more information on the mudbanks than the radar images. Conversely, for low tidal levels, the information on the mudbanks is more detailed with radar imagery. These two observations nevertheless merit confirmation through the analysis of radar and optical images acquired on similar dates. For a more accurate analysis of how radar and optical signal response vary with depth, shallowwater bathymetric readings will be needed in the future.

Conditions for radar-image acquisition must be chosen wisely to obtain the best analysis of the images. The theoretical advantages of radar images should be tested on a larger number of images, by planning depth soundings in mudbank areas on the same dates as radar acquisitions. Whenever possible in these cloudy areas, radar-image analysis should be complemented with optical data (Satellite pour l'observation de la terre (SPOT), LANDSAT, ASTER).

While using satellite imagery is indeed quick and relatively inexpensive compared to conventional field methods, it has also done away with certain limitations of the older sensors, the primary one being the difficulty of obtaining images in real time (it was impossible to program image acquisition on ERS, for example.) The new ENVISAT-ASAR radar sensor and sensors to be launched in the near future (RADARSAT-2, etc.) are multipolarizing, which will undoubtedly improve the characterization of our coastal environments.

Figure 1 .

 1 Figure 1. Location of the study site along the eastern part of the French Guiana coast (latitude 4°30′-5°30′N, longitude 51°50′-53°W).

Figure 2 .

 2 Figure 2. (a) Schematic representation of a mudbank. (b) Aerial photograph of the Kaw mudbank.

Figure 3 .

 3 Figure 3. The potential of radar imagery in detecting mudbanks (Mahury): (a) 15-02-1997 (H =1 . 5 5m ,θ = 41°, RADARSAT-HH); (b) 1-05-2001 (H =1.46m,θ = 40°, RADARSAT-HH). The numbers are regions referred to in the text. Land-water boundary from the 1-05-2001 image in red and from the 7-05-2001 image in green.

Figure 5 .

 5 Figure 5. The potential of radar imagery in detecting mudbanks (Kourou): (a) 8-09-1999 (H =1.05m,θ = 23°, ERS-VV); (b) 14-06-2000 (H =1 . 3 5m ,θ = 23°, ERS-VV). The numbers are regions referred to in the text.

Figure 4 .

 4 Figure 4. The potential of radar imagery in detecting mudbanks (Mahury): (a) 7-04-2001 (H =2 . 8 0m ,θ = 41°, RADARSAT-HH); (b) 24-04-2001 (H =2.99m,θ = 47°, RADARSAT-HH). The numbers are regions referred to in the text.

Figure 6 .

 6 Figure 6. The potential of radar imagery in detecting mudbanks (Mahury): (a) 8-09-1999 (H = 1.16 m, θ = 23°, ERS-VV); (b) 21-04-2001 (H = 2.21 m, θ = 28°, RADARSAT-HH). The numbers are regions referred to in the text. Landwater boundary from the 1-05-2001 image in red and from the 7-05-2001 image in green; mudflat boundary located at region 3 in the 1-05-2001 image in blue.

Figure 7 .

 7 Figure 7. The potential of radar imagery in detecting mudbanks (Mahury-Cayenne): (a) 1-05-2001 (H =1.46m,θ = 40°, RADARSAT-HH); (b) 21-04-2001 (H =2.21m,θ = 28°, RADARSAT-HH). The numbers are regions referred to in the text.

Figure 8 .

 8 Figure 8. The potential of radar imagery in detecting mudbanks (Kourou): (a) 22-02-1999 (H = 1.89 m, θ = 47°, RADARSAT-HH); (b) 8-09-1999 (H =1.05m,θ = 23°, ERS-VV). The number is a region referred to in the text.

Figure 9 .

 9 Figure 9. The potential of optical imagery in detecting mudbanks (Mahury): ASTER image taken on 25-09-2001 (H = 2.55 m). The numbers are regions referred to in the text. Land-water boundary from the 1-05-2001 image in red, from the 7-04-2001 image in green, and from the 21-04-2001 image in white; mudflat boundary located at region 3 in the 1-05-2001 image in blue.

Figure 10 .

 10 Figure 10. The potential of optical imagery in detecting mudbanks compared to that of a RADARSAT image (Approuague River to the east of Kaw): (a) ASTER image taken on 31-10-2000 (H = 1.84 m); (b) RADARSAT image taken on 22-02-1999 (H =2.00m,θ = 47°). Landwater boundary from the 31-10-2000 image in green.

Figure 11 .

 11 Figure 11. Comparison between optical and radar imagery for detecting mudbanks (Kourou): (a) ASTER image taken on 8-03-2001 (H = 1.24 m); (b) ERS image taken on 14-06-2000 (H = 1.35 m, θ = 23°); (c) ERS image taken on 8-09-1999 (H =1.05m, θ = 23°).

Figure 12 .

 12 Figure 12. The potential of radar imagery in monitoring coastline change (erosional and depositional cycles): (a) composite radar image from 15-02-1997 in red (H =1.55m,θ = 41°), 14-06-2000 in green (H =1.46m,θ = 23°), and 1-05-2001 in blue (H =1.46m,θ = 40°); (b) the various directions of coastal movement are shown by superposing the land-water boundaries from the images taken on 14-06-2000 (blue) and 1-05-2001 (red) over the image taken on 15-02-1997.

Corresponding author (e-mail: n.baghdadi@brgm.fr).

J.P. Lefebvre, F. Dolique, and N. Gratiot. Geomorphic evolution of coastal mudflat under oceanic influences: an example from the dynamic shoreline of French Guiana. Marine Geology. In preparation.

Acknowledgments

This article was written as part of a study funded by the Research Division of Bureau de Recherches Géologiques et Minières (BRGM) and the Programme National de l'Environnement Côtier (PNEC). Thanks to Georges Delpont and Christine King for their cooperation and advice. The images were provided free of charge by RADARSAT International (RSI) as part of the ADRO-2 project. The tidal gauge data were supplied by the DDE-Guyane Hydrographic Department.


M Huang

M Guibert

Jean Thevenet

C Fayolle

T Chaussée

L Guy

L Vanel

J.-L Loubet

P Sotta

J Thévenet

A new test method to simulate low-severity wear conditions experienced by rubber tire materials

Keywords: Tribometer, wear, abrasion, rubber, reinforced elastomers

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Considering the lifetime of tires, the wear resistance is of undisputed importance for tire tread materials [START_REF] Veith | A review of important factors affecting treadwear[END_REF][START_REF] Muhr | Rubber abrasion and wear[END_REF][START_REF] Grosch | Rubber friction and its relation to tire traction[END_REF][START_REF] Petitet | Matériaux caoutchoutiques -Morphologie, formulation, adhérence, glissance et usure[END_REF]. However, evaluating the wear property of rubbery materials in a realistic way is still a challenging task. On one side, in-field wear tests are costly and time consuming. On the other hand, in-field wear processes are complex. Different road and/or climate conditions, and even the driving habit, can have large impact on the testing results. Therefore, modelling and predicting wear resistance with laboratory tests remains a major issue. Though laboratory testers have been developed, the tire industry is still in need for better laboratory solutions to characterize the wear performance of rubber materials and fasten material selection.

The general concept of a wear test is to apply normal load together with slip between the material of interest and a abrading surface while interfacial friction induces wear of both sides. Accordingly, the wear rate of the material can be described by the weight or volume loss per unit sliding length or per unit frictional energy. For example, abradability can be defined as abraded volume per unit energy dissipation [START_REF] Grosch | Relation between abrasion and strength of rubber[END_REF]. A proper laboratory tribometer should be able to provide well controlled testing conditions as close to the real in-field situation as possible. For example, for a passenger car tire running at a constant 90 km/hour speed, the tread material faces a periodic pressure of about 0.3 MPa (0.7 MPa for a truck tire) at a frequency of about 10 Hz [START_REF] Mané | A new rotary tribometer to study the wear of reinforced rubber materials[END_REF]. Meanwhile, the tire slips against the road on its trailing edge when the contact is released, even without a relative speed between the road (e.g. even without acceleration, braking or steering). This is due to lateral compressive strain developing in the contact surface (Figure 1). Each contact contributes a slip length in a range of a fraction of a millimeter at a sliding velocity of a few centimeters per second [START_REF] Mané | A new rotary tribometer to study the wear of reinforced rubber materials[END_REF]. Also, relatively high shear rates -of order a hundred s -1 -are applied as a point of the material enters or exit the contact. Altogether, the wear is roughly of the order 2.5 × 10 -6 m of abraded height per slip meter for a truck tire tread in soft conditions. Thus, in order to model the real situation, a laboratory wear tester for rubber materials should be controlled intermittently (periodically switching between slide and non-slide mode, or load and unload mode). This is quite important and completely opposite results may be obtained if this point is ignored, as resilience, hysteresis, relaxation and fatigue behavior of rubber considerably impact the wear [START_REF] Veith | A review of important factors affecting treadwear[END_REF][START_REF] Muhr | Rubber abrasion and wear[END_REF]. Therefore, tests running only in a continuous way are not suitable to characterize tire tread materials. Typically, intermittent tests can be achieved in two ways: one by rolling wheel shaped samples; another one by blade abrasion (Figure 2). Although they both can enable a intermittent wear under a certain frequency by tuning the speed of the motion part(s) (e.g. the Pico and Blade abraders [START_REF] Liang | Rubber abrasion at steady state[END_REF][START_REF] Gent | Mechanisms of rubber abrasion[END_REF][START_REF] Gent | Abrasion of rubber by a blade abrader: effect of blade sharpness and test temperature for selected compounds[END_REF]) or the sliding angle (e.g. the LAT 100 and Akron abraders [START_REF] Grosch | The load dependence of laboratory abrasion and tyre wear[END_REF][START_REF] Heinz | A laboratory method to comprehensively evaluate abrasion, traction and rolling resistance of tire tread compounds[END_REF]), the actual sliding time/distance during a full period cannot be well controlled. Moreover, the normal force has to be fixed during the test by a dead load in most of the reported machines. Therefore, it is difficult to apply a dynamically controlled force profile.

Numerous studies have been performed to elucidate the mechanisms of abrasive wear of rubber-like materials [START_REF] Schallamach | Abrasion of rubber by a needle[END_REF][START_REF] Schallamach | Abrasion pattern on rubber[END_REF][START_REF] Schallamach | On the abrasion of rubber[END_REF][START_REF] Reznikovskii | Feature of the mechanism of abrasion of highly elastic materials[END_REF][START_REF] Grosch | The load dependence of laboratory abrasion and tyre wear[END_REF][START_REF] Bhowmick | Ridge formation during the abrasion of elastomers[END_REF][START_REF] Pulford | Failure of rubber by abrasion[END_REF][START_REF] Uchiyama | Wear of rubber through roll formation[END_REF][START_REF] Barquins | Friction and wear of rubber-like materials[END_REF][START_REF] Fukahori | Mechanism of rubber abrasion. 1. Abrasion pattern-formation in natural-rubber vulcanizate[END_REF][START_REF] Fukahori | Mechanism of rubber abrasion. Part2. General rule in abrasion pattern formation in rubber-like materials[END_REF][START_REF] Fukahori | Mechanism of rubber abrasion. Part3: how is friction linked to fracture in rubber abrasion?[END_REF][START_REF] Ramakrishnan | The effect of abrading surfaces on the wear of rubber tread compounds[END_REF][START_REF] Kim | Abrasion of selected rubber compounds with a DIN abrader[END_REF][START_REF] Iwai | Study on the formation of periodic ridges on the rubber surface by friction and wear monitoring[END_REF][START_REF] Liang | Rubber abrasion at steady state[END_REF][START_REF] Liang | The steady state abrasion of rubber: Why are the weakest rubber compounds so good in abrasion?[END_REF]. Blade abrasion has often been used. While it has proved to be very useful to elucidate wear pattern formation mechanisms [START_REF] Fukahori | Mechanism of rubber abrasion. 1. Abrasion pattern-formation in natural-rubber vulcanizate[END_REF][START_REF] Fukahori | Mechanism of rubber abrasion. Part2. General rule in abrasion pattern formation in rubber-like materials[END_REF][START_REF] Fukahori | Mechanism of rubber abrasion. Part3: how is friction linked to fracture in rubber abrasion?[END_REF], it is not directly representative of usage conditions. A sliding indenter rubbing on the rubber surface has also been used [START_REF] Mané | A new rotary tribometer to study the wear of reinforced rubber materials[END_REF]. Contact sliding is a necessary condition to observe wear, i.e. abrasion weight loss. Indeed, it has been shown that wear is univoquely associated to slip and does not occur in indentation experiments in the absence of slip [START_REF] Petitet | Matériaux caoutchoutiques -Morphologie, formulation, adhérence, glissance et usure[END_REF][START_REF] Petitet | Contribution à la compréhension des mécanismes élémentaires d'usure douce des élastomères chargés réticulés[END_REF][START_REF] Genin-Blanchard | Étude des mécanismes d'usure élémentaire des élastomères chargés réticulés[END_REF].

Generally speaking, there are two types of wear: the first one, known as intrinsic wear, generates very small rubber particles of a few micrometers. This dimension was found to be independent of the applied normal force [START_REF] Gent | Mechanisms of rubber abrasion[END_REF].

It essentially depends on the intrinsic characteristic size of the asperities of the abrading surface [START_REF] Fukahori | Mechanism of rubber abrasion. 1. Abrasion pattern-formation in natural-rubber vulcanizate[END_REF][START_REF] Heinrich | Hysteresis friction of sliding rubbers on rough and fractal surfaces[END_REF][START_REF] Persson | Qualitative theory of rubber friction and wear[END_REF]. As wear goes on, periodical patterns perpendicular to the sliding direction may be generated. This type of wear is called pattern abrasion and normally causes an increase of the wear. Pattern abrasion is related to tear mechanism and the wear rate can be predicted by the tearing energy [START_REF] Thomas | Factors influencing the strength of rubbers[END_REF][START_REF] Southern | Studies of rubber abrasion[END_REF]. Besides those two mechanisms, smearing of rubber was also observed in many cases, especially for NR and SBR compounds. Smearning generates a soft and sticky rubber layer on the contact surfaces, which is believed to be caused by thermal degradation and oxidation of the rubber material and strongly impacts the measured wear rate [START_REF] Muhr | Rubber abrasion and wear[END_REF]. However, the mechanism behind is not fully clear yet. The objective of this paper is to present new results of abrasion tests performed with a new experimental device (tribometer), which has been developed in order to model the wear of a tire tread in low severity conditions, under controlled environmental parameters. This device can be used to generate and characterize wear patterns in controlled, representative conditions, such as sample geometry, sliding speed, normal force, friction coefficient (by tuning the roughness of the disk) and temperature, with high repeatability.

Preliminary results obtained on some representative materials are shown. The main result that is emphazised here is the strong impact of the accumulation of wear debris in the contact zone. This is evidenced and quantified by measuring the effect of the cleaning frequency on the overall wear rate in a given sample under a given set of parameters.

Third body effects, either due to debris generated in-situ or due to exogenic abrasive particles, are widely documented in general wear studies of solid polymers [START_REF] Briscoe | Wear of polymers[END_REF]. On the other hand, rubber wear studies have mainly been focussed on two-body abrasion and on viscoelastic and fracture mechanisms associated to local roughness of the abrading surface [START_REF] Heinrich | Hysteresis friction of sliding rubbers on rough and fractal surfaces[END_REF][START_REF] Persson | Qualitative theory of rubber friction and wear[END_REF], including the most recent experimental and modeling studies [START_REF] Nguyen | An advanced abrasion model for tire wear[END_REF]. There are only a limited number of published studies which explicitly address the effects of a third body, and these are mainly dealing with exogenic abrading agents such as particles immersed in an abrasive liquid [START_REF] Zhang | Wet abrasion of polymers[END_REF][START_REF] Coveney | Behaviour of model abrasive particles between a sliding elastomer surface and a steel counterface[END_REF].

The paper is organized as follows. The studied material formulations are described in section 2.1, their mechanical properties are described in section 2.2. The tribometer is described in section 2.3 and test procedures and analyzes in section 2.4. Results are presented in section 3.

Materials and methods

Materials

The studied materials are Natural Rubber (NR CV60) matrices reinforced either with carbon black fillers (N121 from Cabot, sample C1) or highly dispersible precipitated silica (Zeosil ® 1165MP by Solvay, sample S2), as reported in Table 1. Samples were provided by Solvay Silica (Collongesau-Mont-d'Or, France). N121 has a specific surface of about 100 m 2 /g while Z1165 has about 160 m 2 /g. The silica was treated with triethoxysilylpropyltetrasulfur (TESPT), which covalently links the silica surface to the NR matrix. Samples were processed in a 1.5 liter intermeshing internal mixer (Brabender 380 cm 3 ) and sulfur vulcanized at a temperature of 145

Mechanical characterization

Wear resistance is closely related to the mechanical strength (e.g. tensile and tear), hardness and resilience of the materials. Mechanical properties of the materials have been characterized.The storage (G) and loss (G ′′ ) shear moduli were characterized at 40 • C in oscillatory shear at a frequency 10 Hz with a Metravib Dynamic Mechanical Analyzer. The variation of G ′ and G ′′ as a function of the strain amplitude γ are shown in Figure 3. G ′ curves can be fitted with a heuristic function of the form [START_REF] Kraus | Mechanical losses in Carbon Black Filled Elastomers[END_REF]:

G ′ = G ∞ + ∆G (1 + γ/γ c ) κ (1)
Fits of the G ′ vs. strain amplitude curves are reported in Fig. 3. The obtained fitting coefficients for the three samples are summarized in Table 2. As commonly observed in such samples, the moduli at small amplitude and the Payne effect amplitudes ∆G are much larger in the carbon blackreinforced sample than in the silica reinforced one [START_REF] Bomal | Developments in silica usage for decreased tyre rolling resistance[END_REF], while both samples have comparable values of the modulus G ′ at 50% amplitude.

Traction curves measured at T = 20 • C and at T = 60 • C are shown in Figure 4 for both samples. These curves have been obtained as the average over five different tests. The less pronounced non-linearity at small strain measured in Payne effect curves at T = 40 3 with the heuristic function in Eq. 1. Units for ∆G and G ∞ are in MPa, γ c values are in %.

Figure 3) is hardly measurable in these curves. Only at 20 • C does the curve for silica fillers show a more pronounced non linearity at small strain, as shown in the inset. Silica fillers result in a slightly lower modulus at high elongation, together with a slightly higher elongation at break.

Experimental setup: Tribometer

As mentioned in introduction, wear is due to slipping in the contact. The general concept of the new rotary tribometer is thus to produce intermittent slipping at the rubber surface, at controlled contact frequency, pressure and accumulated sliding length comparable to real tires. The device must work in open cycle mode, i.e. abrasion wastes must be eliminated between each passage. The new experimental device that we have developed is a rotary tribometer working in controlled environment, with an in situ optical observation system. Intermittent contacts with fully independent control of contact pressure, contact time, contact frequency and sliding velocity are applied. The displacement rates at both onset and release of contact can be controlled independently thanks to fast closed loop control of the normal force. The frequency of elimination of wear debris from the contact zone is also a key parameter, as will be discussed later.

The general architecture of the rotary tribometer is schematized in Figure 6. An horizontal abrading disk (label i in Figure 6) rotates around the vertical axis (A) at the angular velocity ω (in rad/s). It provides the sliding motion at a sliding velocity v s = Rω where R is the track radius, i.e. the distance between the sample and the axis (A). In all tests shown here, R was kept fixed to 10.25 cm. The sliding direction is along x in Figure 6. The abrading disk (MICROPLAN FRANCE, label i in Fig. 6) is made of granite (granit bleu de Guéret), which maintains its surface roughness constant over test duration. The topography of the granite surface (granite 1200) was characterized with a Bruker 3400E optical interferometer using a ×5 objective on the optical column and ×5 at the camera. In this way, lateral resolution of order 2 µm and vertical resolution better than 0.1 nm are obtained. A 25 × 1 mm 2 image was obtained through numerical reconstruction from 30 1.3 × 1 mm 2 images. No difference was measured within and outside the wear track after more than 100 tests were performed. Figure 5 shows the averaged 1D power spectrum density of the surface. In the relevant q range, the 1D PSD shows an exponent of order -1.68, which is in full agreement with reported values for polished granite [START_REF] Wang | A study of the laboratory polishing behavior of granite as road surfacing aggregate[END_REF]. The surface is characterized by roughness indicators ⟨R a ⟩ = 0.35 ± 0.06 µm and ⟨R t ⟩ = 3.19 ± 0.78 µm for the fresh surface, while ⟨R a ⟩ = 0.38 ± 0.08 µm and ⟨R t ⟩ = 3.64 ± 1.03 µm for the cleaned worn surface, as measured by high resolution profilometry. These figures show that the surface roughness is indeed preserved during wear tests, which is not the case when e.g. polished stainless steel is used.

A fast piezoelectric dynamic actuator acting along vertical direction z (label b) is used to control the duration and frequency of contacts and the normal force between the sample and the disk. It can provide either constant or intermittent loading. In this way, the contact and/or release times and the sliding velocity are controlled independently. The whole device is fully controlled by a dedicated home-made LabVIEW software. The piezoelectric actuator (P-602.8SL from PI, label b in Fig. 6) has a displacement range ±0.5 mm. It is driven by a fast force-controlled loop to ensure a stable normal force with a tolerance smaller than around five percent of the set value. The piezo-actuator is fixed on a 2D y -z movable frame (label a). Therefore, the wear track can potentially be changed to provide access to fresh surface of the disk during the test.

A 3D load cell (KISTLER) (Figure 6 label e) measures the tangential (friction) force (along x axis) and the normal force (along z axis).

The aluminum sample holder (label c) is shaped as a cylinder of radius 100 mm with horizontal axis carefully set parallel to the abrading disk surface and perpendicular to the sliding direction (i.e. along y), as schematized in Figure 6). As mentioned in Section 2.1, samples are 2 mm thick disks of 10 or 18 mm diameter glued on the sample holder. A thermocouple thermal sensor (label f) is placed within the sample holder right to the rear of the sample and gives feedback to the heating unit. An optical camera (CMOS camera from R&D VISION) (label g) coupled to a LED light source (R&D VISION) (label h) records the whole wear process. In particular, the deformation of the sample during a contact can potentially be recorded in real time. Such data are not shown here.

General procedure of wear tests

The general test procedure is as follows:

Step 1. The sample is glued on the sample holder, weighted and loaded in the tribometer. Sample orientation is carefully adjusted using optical camera; Step 2. Wait for temperature equilibration; Step 3. Wear test period of a given number of contacts; Step 4. Sample together with sample holder is unloaded and weighed. Step 5. The wear track is cleaned. The sample surface is cleaned and the sample together with the sample holder is weighed again. Step 6. Sample is loaded back in the tribometer and test is iterated from step 2.

For all results shown here, the sliding speed was fixed to 5 cm/s during step 3. The actuator generates square pulses to provide cyclically intermittent slip with different normal forces varying from 10 N to 30 N. The contact time is 1 s followed by a non-contact (relaxation) duration of 0.1 s. Therefore, the full motion cycle (denoted as a 'wear-loop' in what follows) lasts 1.1 s. After a wear test period, the disk surface will be contaminated by the wear debris which affects the wear rate. Therefore, after a given number of wear-loops (e.g. every 500 wear-loops), the sample together with the sample holder is unmounted and the debris left on the track are removed physically by an eraser (STAEDTLER Mars plastic) and then chemically with acetone (Step 5). Debris are eliminated from the surface in exactly the same way as graphite particles are rubbed out from paper. Debris are stuck onto the very soft, sticky rubber material of the eraser and then eliminated together with the large eraser particles. The surface is then washed with acetone and blown with dry gas. At the same time, the sample surface is cleaned up with acetone and its weight loss is measured before and after cleaning. Such a testing period (from Step 2 to Step 6) is called a 'wear-stage'.

Wear is quantified by the weight loss of the sample during the wear test. Since elastomer materials are quite sensitive to the environment (hygrometry, temperature, ...), an identical unworn reference sample was always placed within the tribometer enclosure and its weight measured in parallel to that of the worn sample at each wear stage. This procedure allows to get rid of any change related to the environment (mostly potential moisture sorption).

At each wear-stage (number n), the weight of the wear debris left on the sample surface (∆m surf ace (n)) or on the abrading disk (∆m track (n)) during the current stage and the overall weight loss (∆m total (n)) are worked out as:

∆m surf ace (n) = m b (n) -m a (n) (2) ∆m track (n) = m a (n -1) -m b (n) (3)
∆m total (n) = ∆m track (n) + ∆m surf ace (n) = m a (n -1) -m a (n) (4)
where m a (n) and m b (n) are the weights measured respectively after and before cleaning the sample for the current stage n. m a (n -1) is measured in the previous wear stage (right before starting stage n). All measurements were calibrated by measuring the weight change of the reference sample, which generally did not change by more than 0.02 mg, which is of the order of the resolution of the balance, while the weight loss per wear stage ,i.e. per cycle of 500 wear-loops, is about 1 mg. The total accumulated weight loss after N wear stages ∆M total (N ) is then the sum of all ∆m total (n) increments (n = 1, ...N ). The cleaning method impacts the ratio between m a and m b , and then the wear rate. This will be discussed in section 3.1. With this procedure, the frequency of cleaning (number of contacts between two successive cleaning schemes) can be changed, keeping all other parameters constant. Also, the amounts of wear debris deposited on the disk surface or stuck to the sample surface can be estimated separately.

Figure 7 shows the force profile during one wear-loop. One highlight of the device we developed is the fast closed loop control of the normal force. The set point for the normal force is a square pulse. This allows us to maintain a constant normal force during the whole tests, even with changes of temperature, wear of the sample, etc.. The applied normal force is obtained through fast closed loop control, which insures that the normal force is regulated much faster than the onset of the full sliding of the sample, as illustrated in Figure 7.

The wear-loop initiates when the actuator compresses the sample against the disk surface, in about 25 ms. Concomitantly, the sample is sheared, resulting in increase of the tangential force until it reaches the maximum value F t = µF z , where µ is the apparent friction coefficient and F z is the applied normal force. Meanwhile, the plateau at maximum value F t corresponds to the fully-sliding state. The critical time to reach such state depends on the normal force, friction coefficient and mostly on the sliding speed. Generally speaking, the critical time increases with a higher tangential force and a lower speed. In our tests, a constant sliding speed V s = 5 cm/s was chosen and an average value 0.068 s was always used. Thus, during the ith wear-loop, the frictional energy E 1 was calculated as:

E 1 (i) = V s ∫ t 2 t 1 F t (t)dt (5)
where index i refers to the wear-loop number, t 1 = 0.068 s and t 2 = 1 s corresponds to the end of the contact duration. The total accumulated frictional energy E a after nth wear loop is obtained by:

E a (n) = n ∑ j=1 E 1 (j) (6)
Wear results are reported in terms of weight loss as a function of total accumulated friction energy: ∆M total (n) = f (E a (n)). Note that both quantities (total weight loss and friction energy) scale with the overall contact area. As the real contact area is not measured quantitatively and the contact pressure is not uniform within the contact surface, we shall not express the results in terms of normal pressure. Instead, for each set of presented results, the normal force and sample diameter will be specified. The correspondence to average normal pressure value may be established as follows.

Results and discussion

Tribological tests have been performed on the materials described in section 2.1. Both samples are representative of (though not identical to) real materials used in tire treads. We shall first describe results of wear tests in terms of sample weight loss measured as a function of total friction energy.

Linear wear and effect of track cleaning

One key issue in wear tests of rubber materials is how to deal with the debris. It was found that the measured wear rate is strongly affected by the cleaning scheme used during the test.

The results of a series of tests performed with sample C1 are shown in Figure 8. All tests were done at room temperature with a normal force 30 ± 1 N (see Fig. 7) and sample diameter 18 mm. The contact time was 1s, the time interval between two successive contacts was 0.1 s and the sliding velocity V s = 5 cm/s. All tests have a first step with the same conditions, using an interval of 500 contacts between two successive cleaning operations (ranging from 0 to roughly 6.5 kJ friction energy), as indicated in Fig. 8. Results obtained during this first step illustrate the perfect repeatability of the measurements. A perfect linear relationship between the total friction energy and total weight loss is observed. Accordingly, a wear rate can be defined as the slope of the line k a = d∆m total /dE a (n) (in units mg/kJ). After this first step, the cleaning frequency was either maintained to 500 contacts (green curve in Fig. 8) or changed to 250 (red curve) or 1000 ( blue curve) contacts. From the onset of this change, the relationship between weight loss and friction energy is still perfectly linear, but the slope (wear rate k a ) changes depending on the cleaning interval. The higher the cleaning frequency, the higher the wear rate. The dependance of the wear rate (the slope of the lines in the second stage of the tests in Fig. 8) on the cleaning frequency is illustrated in Figure 9. Fig. 9 also reports the average value of the wear debris left on the track during each wear stage ∆m track (n) for each chosen value of the cleaning interval. Thus, it appears that a cleaner surface (that is, a surface that is cleaned more often) gives a higher wear rate k a .

Note that for the carbon-black filled sample C1, a perfectly linear relationship is found up to 20 kJ total accumulated frictional energy when the cleaning frequency is maintained at 500 contacts.

Further results obtained with sample C1 are shown in Figure 10. In order to investigate a larger range of average normal pressure, the sample diameter was set to 10 mm with a normal force 20 N, other conditions being the same as before. After the same wear-stage of 500 contacts for all tests, the number of wear-loops during each wear stage was changed to 35 wear-loops (green triangle), 96 wear-loops (blue circles) or maintained at 500 wear-loops (red diamonds). Again, results obtained during the first step illustrate the perfect reproducibility of the measurements. Note that the absolute values of the rate k a in Figures 8 and10 are not fully comparable due to the difference in sample size and or normal pressure.

The tests shown in Figure 10 were repeated while changing the applied normal force (or equivalently average normal pressure). The inset in Figure 10 shows a summary of the wear rate of C1 sample tested under different normal force values with various cleaning frequencies.

A discussed above, for a given value of the normal force, the wear rate decreases as the period of the cleaning operation increases. Then, for a given cleaning frequency, the wear rate k a decreases as the normal force increases. This result may appear counter-intuitive at first sight. Remember, however, that the wear rate, expressed here as the slope of the total weight loss vs friction energy, takes into account explicitly the increased friction energy due to higher normal, hence tangential, force. Note also that the relative difference in wear rates observed when the normal force is changed from 10 to 20 N becomes smaller when the cleaning frequency is higher, i.e. on a surface which is cleaner on average.

All these results may be rationalized by assuming that wear debris sticking on the sample or disk surface have a protective effect against rubber wear. Applying a higher pressure, i.e. more severe conditions, generates more frictional energy per wear-loop, which in turns generates a larger amount of debris. Due to this reason, although the total weight loss per wear-loop increases, the apparent wear rate k a decreases in tests at higher pressure, because the so-called protective effect is then higher. This difference becomes less pronounced as the overall average amount of debris is smaller, as illustrated in Fig. 10 (inset). For example, when cleaning every 35 wearloops (which corresponds to exactly 3 revolutions of the rotating disk), the difference between 10 N and 20 N tests is within 10%.

Based on this idea, an "intrinsic" wear rate k i may be defined by extrapolation to an ideally clean surface, or equivalently to a cleaning frequency of one wear-loop. It should not depend on the pressure (at least within the current testing range)and should be higher than the rates measured here.

Friction coefficient

The impact of wear debris on the contact conditions, which affects the wear rate, is also demonstrated by the evolution of the apparent friction coefficient along a test. As reported earlier, the friction coefficient of rubber materials changes with applied normal force, due to the change in actual contact area. It also varies under different values of the sliding speed and temperature because of the viscoelastic nature of the material [START_REF] Grosch | Relation between friction and viscoelastic properties of rubber[END_REF][START_REF] Moore | The friction and lubrication of elastomers[END_REF][START_REF] Barquins | Rubber friction variation with rate and temperature: some new observations[END_REF][START_REF] Gal | Modelling of sliding friction for carbon black and silica filled elastomers on road tracks[END_REF]. Here we show that it is also affected by cleaning. Figure 11 shows the apparent friction coefficient of the C1 sample tested under two different normal force values at room temperature. The apparent friction coefficient is defined as µ a = Ft / Fz , where Ft and Fz are the average tangential and normal forces, respectively, when full sliding occurs during a wear-loop (see Figure 7). Black arrows indicate the points at which the disk and the sample surfaces were fully cleaned, which also separate different wear-stages. In this case, each stage contains 96 wear-loops (about 8 revolutions of the disk), except for stage 1 which lasted 500 wear-loops for initiating the sample surface to a stable state. Each time after cleaning, µ a shows a small, sudden increase, but then µ a decreases very rapidly quite far below its original value during the first 12 wear-loops after cleaning (corresponding to the first revolution of the disk). It then increases back until it reaches a steady value. A tentative, qualitative explanation may be the following one. During the first revolution, the sample always makes contact with a clean disk. Only a fraction of the generated debris is transfered to the track and they accumulate wear-loop after wearloop. As noticed above, the presence of more debris tends to attenuate the severity of the contact, as is reflected by the lower wear rate under higher normal force (see inset in Figure 10). Thus, debris accumulation may lead to a decrease of µ a . After this first revolution, the sample starts to make contact with a disk surface covered by wear debris. However, debris are still being tranfered from the sample surface to the disk until some equilibrium state (transfer rate) is reached. As the adhesion force at rubber-rubber interface is presumably stronger than at the rubber-disk interface, the measured F t , and thus µ a , values become larger. This process can last very long before reaching the equilibrium state. For example, as discussed above, although the wear rate k a measured for F z = 10 N is larger than for F z = 20 N, the total amount of debris generated during each wear-loop for F z = 20 N is larger (see Figure 10). This may possibly explain that the equilibrium state occurs faster for F z = 20 N than for F z = 10 N.

Non-linear wear observed in silica samples

In the previous section, the linear wear behaviour of carbon black filled samples under different testing conditions has been shown. This also applies to the silica filled sample S2. There are some differences in the behavior of both samples, however. First, the rate k a of the S2 sample is significantly larger than in the C1 sample. For instance, the rate k a of S2 is 1.60 and 1.12 when tested under a normal force of 10 N and 20 N, respectively, at room temperature and for a wear-stage of 500 wear-loops, which is about 40% to 50% larger than in C1 sample. More interestingly, the silica-filled sample S2 ''Smearing'' ''Fracture'' shows an increased wear rate after a few wear-stages. As shown in Figure 12, beyond a critical energy level of about 3.5 kJ, the wear rate starts to deviate upwards with respect to the initial linear regime. More importantly, beyond this value, the debris start to contain a small part which is insoluble in toluene. The top left and right pictures show the debris collected below and above approximately 3.5 kJ respectively, after 30 min sonication in toluene. Small unsoluble rubber particles can only be observed for the debris collected above approximately 3.5 kJ.

This suggests that two distinct mechanisms are at play in successive stages of wear, or contribute to a different extent in successive stages. These mechanisms are discussed in the next sections.

Sticky debris

A shown above, two distinct types of wear debris could be collected along wear tests. The first one constitutes a layer sticked on the sample surface. A representative example is shown in Figure 13, which shows the presence of a sticky layer of worn rubber on the sample surface before cleaning (a). This sticky layer accumulates in regions located behind wear ridges, which are protected by the presence of the protruding ridges and therefore are not in direct contact with the sliding abrading surface. This layer is removed at each wear stage by washing the surface, as illustrated in Figure 13(b).

The second type of wear debris is made of relatively large (from a few µm up to a few tens of µm or even larger) material fragments torn away from the sample. They may be mixed with sticky debris as shown in Figure 13. The corresponding wear mechanism becomes predominant when the ridge pattern has developed, after a transitory period at the beginning of the tests, during which ridge patterns are not yet developed. The duration of this period (in terms of the corresponding number of contacts) depends on the particular sample under study and on test control parameters.

A major difference was assessed by controlling the solubility of both types of wear debris in toluene (Top left picture in Figure 12). Sticky debris collected in the first stage of wear (case (a) in Figure 13) are soluble in toluene. This indicates that the associated mechanism corresponds to some degree of chemical degradation of the material, namely de-crosslinking and/or chain scission. After ageing for several days or more at ambient conditions, those debris become apparently unsoluble, but they can still be dissolved after sonication for about one minute. This may indicate that some bound rubber with relatively weak polymer-filler interactions was formed during ageing.

Conversely, wear debris collected in the later wear stages, for example the 4th stage, are not all soluble in toluene (Top right picture in Figure 12). This indicates that some of the collected debris correspond to bulk fragments of the material with a preserved local elastomer structure. For instance, the "tongue" part shown in Figure 13 may finally turn into such kind of insoluble debris.

The transition from the first ("chemical", or so-called "smearing") mechanism to the second one ("mechanical tearing") may correspond to a change in wear rate (as measured by the slope of the weight loss vs friction energy curves), as illustrated in Figure 12, which shows that the two successive stages of wear indeed correspond to different wear rates. In the first regime (which last up to about 3.5-4 kJ total accumulated friction energy for the particular sample studied here), debris consist of sticky layer. Chemical degradation is the predominent mechanism in this transitory regime. In the second regime (from about 3.5 -4 kJ), debris are mostly micrometric fragments. Mechanical tearing from the ridge pattern is the dominant mechanism. The crossover point between the two regimes under given test conditions depends on the particular sample under study.

For the C1 sample, sticky debris were mainly observed and larger debris particles did only appear in marginal amount, in the applied pressure range. This may due to the higher wear resistance provided by carbon black fillers.

Thermogravimetric Analysis (TGA) characterization of the unworn samples and wear debris was performed (Figure 14). TGA tests for sticky debris show a signficant weight loss (of order 18%) in the temperature range between 200 • C and about 340 • C, while larger size debris have a signal identical to that of the unworn material. This confirms that some chemical degradation has occurred specifically in sticky debris.

Wear Patterns

The competition between smearing and fracture wear mechanisms can be further confirmed by the observation of wear patterns. Generally speaking, a larger frictional force, obtained either by increasing F z or µ, helps initiating fracture on the rubber surface and subsequently generating ridge patterns. On the other hand, such increased frictional force also corresponds to a more severe test, which means that more energy will be released. This enhances the smearing effect, which works like 'melting' the patterns into sticky rubber. They together determine when and which kind of wear pattern can be formed. Figure 15 shows the surface of C1 and S2 samples after 2000 wear-loops (separated by 4 wear-stages in total in both cases) under different conditions. In (a), the surface looks smooth because the normal force was too small to fracture the sample surface (or, equivalently, because in this regime the smearing rate is larger than the 'crack growth rate'). When the normal force increases to 20 N (b), ridge patterns are clearly observed. However, at 60 • C, the increased smearing rate brings the surface to a smoother state again (Figure 15(c)). As silica filled samples show a lower wear resistance, ridge patterns are observed even for F z = 10 N (a') and become more pronounced as F z increases to 20 N (b'). These more severe patterns are associated to the nonlinear wear behaviour and insoluble debris, as was shown in Figure 12. However, almost all large ridge patterns disappear at 60 • C (c'). Although different testing conditions give different patterns and rates k a , all cases shown in Figure 15 give very good linear fitting (R 2 ≈ 0.999 or better) except for the cases shown in (a') and (b'). Only under the corresponding test conditions does the fracture mechanism contribute significantly to the measured weight loss.

Figure 16 shows how the patterns change along the wear tests of the C1 sample under different conditions. The pictures come from similar locations on the sample surface, indicated as (a-c) fields in Figure 15. Under moderate condition (10 N, RT, 1-1 to 1-4), the ridge pattern gradually disappears because of smearing. As the normal force is increased, those small ridges merge and grow to larger patterns (2-1 to 2-4). As temperature increases, those larger patterns are gradually destroyed and evolve into non-connected 'dots' arranged in lines parallel to the sliding direction (3-1 to 3-4).

Due to the cylindrical sample geometry, there is a decreasing local pressure gradient from the center to the edge of the sample. A change of the wear pattern is observed accordingly. Figures 16 (a) to (c) respectively show the top, middle and bottom parts of the field d in Figure 15(b) (after 2000 wear-loops). Figure 17(a) has the lowest pressure as it is close to the worn area edge. Tiny ridges perpendicular to the sliding direction are observed. The distance between these ridges is of order 10 µm. They stand for the the initiation of the wear. In Figure 17 (b) (middle area, medium local pressure), solitary patterns are formed resulting from the growing of the initial ridges. They are larger in size but not fully connected. In Figure 17 (c) (higher local pressure), those patterns further grow up and connect to form an even larger size pattern. Such a connected pattern will keep growing in size and will finally be torn off from the sample surface. This is quite similar to the mechanism observed in blade abrasion test [START_REF] Liang | Rubber abrasion at steady state[END_REF]. This process may be associated to the fracture wear mechanism.

Conclusion

We have developed a new rotary tribometer which allows performing accelerated laboratory wear tests. Contact parameters which are representative of real low severity wear conditions can be applied. The high quality of wear test results in terms of sensitivity and repeatability has been assessed.

The specific point emphasized in this paper is the strong impact of the presence of wear debris accumulated in the contact zone during the test. This impact was assessed by studying the dependence of the measured wear rate on the frequency at which wear debris are washed away from the contact. As a general conclusion, it may be said that the presence of debris has a protective effect of the sample surface against abrasive wear. This effect has been quantified. This emphasizes the importance of controlling the conditions in which wear debris are eliminated from the contact. To mimic real usage conditions and provide truly representative 'open cycle' conditions, wear debris should be washed away from the contact as often as possible. However, one may wonder whether wear rate in service may depend on the amount of tire debris accumulated on a road surface. This amount may probably vary to large extent depending on atmospheric conditions, traffic, the type of road and so on.

Carefully analyzing wear wastes also has allowed discriminating two distinct types of wear debris. At the beginning of the tests, wear debris essentially consist in a sticky layer of soluble (thus de-crosslinked elastomer material). As tests are continued further on, a new regime occurs with a well established ridge pattern, in which the predominant wear mechanism is due to tearing away of material fragments of micrometric sizes. These fragments are made of unsoluble -thus with a locally preserved crosslinked structureelastomer material.

The proposed testing procedure allows generating selectively and discriminating quantitatively the various wear mechanisms. It emphasizes a predominant control parameter, which is the amount of wear debris present within the contact zone.

Figure 1 :

 1 Figure1: Schematics of the contact zone of a tire tread groove. Slip occurs at the trailing edge of the contact zone, where the tangential over normal stress ratio becomes larger than the friction coefficient µ.

Figure 2 :

 2 Figure 2: Laboratory wear testers classified according to their contact modes. A comprehensive introduction is made by ISO 23794. Note that the pictures shown in this table only indicate general concepts rather than a layout of any real machine.

Figure 4 :

 4 Figure 4: Tensile engineering stress as a function of elongation strain measured at T = 20 • C and 60 • C for both samples C1 (filled with carbon black N121) and S2 (filled with silica). The inset is a zoom of the curves at 20 • C to show the non-linearity at small strain.

Figure 5 :

 5 Figure 5: The average 1D PSD of the granite surface.

Figure 6 :

 6 Figure 6: Schematics of the general architecture of the rotary tribometer. a: 2D movable frame (x and z axis); b: piezo-electric actuator; c: sample holder; d: sample; e: 3D load cell; f: thermocouple; g: optical camera; h: LED lightning; i: rotating abrading disk; j: temperature and atmosphere controlled chamber; k: heating unit. Note that the abrading disk diameter and sample size are not drawn to scale.

Figure 7 :

 7 Figure 7: Profiles of the displacement, normal (F z ) and tangential (F t ) forces during one wear-loop. Contact duration is 1 s. Vertical dashed line at about 80 ms indicates the onset of sample sliding. C1 sample.

Figure 8 :

 8 Figure8: The effect of changing the cleaning frequency on wear rate in sample C1 (filled with carbon black N121) tested at room temperature under a fixed normal force of 30 N, sample diameter 18 mm. After 4 identical wear cycles of 500 wear loops (cleaning both disk and sample surface every 500 contacts), the cleaning rate was maintained (green) or changed to 250 (red) or 1000 (blue) loops. Best linear fits for each case are shown.

Figure 9 :

 9 Figure 9: Wear rate (scale on left) and cumulated amount of wear debris left on the disk surface (scale on right) as a function of the number of contacts between two cleaning operations. Sample C1.

Figure 10 :

 10 Figure10: The effect of changing the cleaning frequency on the wear rate tested at room temperature under a fixed normal force of 20N. In the case of cleaning every 35 wearloops: the weight loss is only measured after each 3 wear-stages, as the weight loss in each stage of 35 wear-loops is too small. Lines are best linear fits. Inset: Wear rates measured at two different values of the normal force (10 N and 20 N) and three different cleaning frequencies[START_REF] Zhang | Wet abrasion of polymers[END_REF] 96 and 500 wear-loops as indicated). Sample C1.

Figure 11 :

 11 Figure 11: The evolution of the friction coefficient of sample C1 (filled with N121 carbon black) tested at room temperature under a normal force of 10 N (green) and 20 N (red). The disk and the sample surface was cleaned every 96 wear-loops.

Figure 12 :

 12 Figure 12: The wear behaviour of sample S2 (filled with Z1165 silica). The top figures show the solubility of the debris in toluene, collected either in the initial linear regime (left) or in the non-linear regime (right).

Figure 13 :

 13 Figure 13: A representative snapshot of wear pattern in the S2 sample (from zone 5 in Figure 15 (b')), shown before (a) and after (b) cleaning the sample surface, showing the presence of a sticky layer of worn rubber accumulated on the sample surface before cleaning (a). This layer is removed by washing the surface (b). The black arrow indicates the sliding direction.

Figure 14 :

 14 Figure 14: TGA spectrum of sticky debris and of the unworn C1 sample.

Figure 15 :

 15 Figure 15: The cleaned surface of C1 (N121) and S2c (Z1165) samples after 4 wear stages of 500 wear-loops each, tested in the following conditions (a) (a'): 10 N, room temperature; (b) (b'): 20 N, room temperature; (c) (c'): 20 N, 60 • C. The evolution of the marked fields 1, 2 & 3 along the test is shown in Figure16as: 1-1 to 1-4 (field 1), 2-1 to 2-4 (field 2) and 3-1 to 3-4 (field 3) respectively. Area 4 is directly zoomed in and shown in Figure17. Area 5 is zoomed in in Figure13. Normal (unprimed) labels refer to the C1 sample, primed labels to the S2 sample. For each test, the measured wear rate is indicated in the bottom left corner of the corresponding pattern. The sliding direction is vertical upwards.

Figure 16 :

 16 Figure 16: The evolution of the wear pattern of C1 sample tested under 10N, room temperature (1-1 to 1-4, area 1 in Figure 15); 20N, room temperature ( 2-1 to 2-4, area 2) and 20N, 60 • (3-1 to 3-4, area 3). Second indices 1, 2, 3 and 4 refers to the end of wear-stages 1, 2, 3 and 4, namely, after 500, 1000, 1500, 2000 wear-loops, respectively. The scale bar in 1-1 (resp. 2-1, 3-1) applies to 1-2 -1-4 (resp. 2-2 -2-4, 3-2 -3-4). The sliding direction is vertical upwards.

Figure 17 :

 17 Figure 17: Images of C1 sample after 2000 wear-loops under a normal force of 20 N at room temperature. (a), (b) and (c) are zoomed-in from the top, middle and bottom of area 4 in Figure 15(b) respectively. The sliding direction is vertical upwards.

Table 1 :

 1 Formulations of studied compounds. Units are in grams.

	• C and

Table 2 :

 2 Values of the parameters obtained by fitting the G ′ curves in Figure

	• C for the silica-filled sample (see

Acknowledgements

Part of this study was performed within the FP7 European Collaborative Project LORRY (Grant Agreement number: 314463), whose funding is acknowledged. This study was also partly funded by Solvay, which is gratefully acknowledged. We thank Yinping Tao from QMUL for her help in performing TGA tests.

Conflicts of interest

The authors declare no conflict of interest.