Benjamin Guillot
email: benjamin.guillot42@hotmail.fr

S Jégou

Laurent Barrallier
email: laurent.barrallier@ensam.eu

Lecturer, Sébastien Jegou
email: sebastien.jegou@ensam.eu

Degradation of gaseous nitriding of steel by lubricant contamination -Effect of in-situ pre-treatments

Keywords:

The present work focuses on the industrial inhibition of gaseous nitrided parts and on the industrial in-situ pre-treatment that can be used to avoid these inhibitions. The first objective is to obtain a repeatable defective nitriding process on carbon iron-based alloys, while the second is to determine the ability of determined in-situ pre-treatments to counter the

previously mastered inhibition. Machining oil is used in order to obtain an industrially consistent inhibition. Its presence before chemical treatment strongly inhibits the adsorption of nitrogen atoms at the other surface, leading to heterogeneous nitriding properties of the treated samples. EDS analysis of oil residues indicates the presence of several elements, such as sulphur and carbon. As several studies already focused on the influence of sulphur on nitriding properties, experimentations on the influence of carbon are detailed. Contamination by carbon deposit leads to similar inhibition as in the case of a machining oil contamination.

Literature analyses lead to the determination of three in-situ pre-treatments, namely urea (CH 4 N 2 O), pre-oxidation and ammonium chloride (NH 4 Cl), to counter the detrimental effects such contaminations. Although all the processes enable to suppress the nitriding inhibition due to the presence of machining oil, ammonium chloride indicates the best capability to activate the adsorption of nitrogen of machining oil contaminated surfaces.

Introduction

Thermochemical surface treatments of steels, such as nitriding or carburizing, are of high importance in industry. Gaseous nitriding is known to generate residual stress and hardness gradients at the surface of the treated parts, up to 1 mm in depth for long treatments [START_REF] Hirsch | Treatment of iron and steel[END_REF]. It consists in heating between 450 and 590 °C a carbon iron-based alloy in a nitrogen-rich atmosphere, for a duration varying between 50 and a few hundredth hours. The ammonia molecule is submitted to a catalytic decomposition phenomenon, leading to the adsorption of atomic nitrogen N ads at the iron surface and the formation of gaseous hydrogen [START_REF] Ehrlich | The mechanism of chemisorption on metals[END_REF][START_REF] Grabke | Reaktionen von Ammoniak, Stickstoff und Wasserstoff and der Oberfläche von Eisen[END_REF][START_REF] Ertl | Mechanism and Kinetics of Ammonia Decomposition on Iron[END_REF].

The increase in nitrogen surface concentration leads to the diffusion of this element to the core of the treated parts [START_REF] Rozendaal | The development of nitrogen concentration profiles on nitriding iron[END_REF] and the formation of a nitrided layer that can be dissociated in two parts, depending on the nitriding parameters. At the surface of the sample, a compound layer composed of ε-Fe 2-3 N and/or γ'-Fe 4 N can develop [START_REF] Inokuti | Formation of Fe 3 N, Fe 4 N and Fe 16 N 2 on the Surface of Iron[END_REF], followed by a so-called diffusion layer composed of a tempered martensitic (ferritic with carbides) matrix with interstitially dissolved nitrogen, cementite at grain boundaries and finely dispersed alloying elements nitrides MN (M = Cr, Mo, V, …) [START_REF] Mortimer | Precipitation of nitrides in ferritic iron alloys containing chromium[END_REF].

Before nitriding, parts are submitted to different industrial processes, notably in order to give the parts their final shape. These steps can strongly alter the surface state of the parts, being potentially detrimental for the nitriding process. The surface state can be distinguished in two kinds, namely the mechanical state and the physical and chemical state. The first can be altered by rough machining and mechanical surface treatments and can lead to a modification of both precipitation [START_REF] Brahmi | Study of aluminium nitride precipitation in pure Fe-Al-N alloy by thermoelectric power measurements[END_REF][START_REF] Meka | Interrelationships of defects, nitride modification and excess nitrogen in nitrided Fe-4.75 at.% Al alloy[END_REF] and diffusion kinetics [START_REF] Guillot | Influence of strain hardening on gaseous nitriding of steels[END_REF]. However, it should be emphasised that non-negligible modifications are enabled by extremely high deformation rates, such as 80%, generally obtained by cold-rolling [START_REF] Biglari | Analysis of the nitrogen absorption isotherms of cold-rolled Fe-2 at.% Al specimens with different AlN precipitate dimensions[END_REF]. Also, it doesn't seem that this state enables to obtain an industrially non-conforming nitrided part.

Physical and chemical states of a surface also impact the catalytic properties of the substrate and can even reach the total inhibition of the catalytically based reactions [START_REF] Bartholomew | Mechanisms of catalyst deactivation[END_REF]. These substrate alterations can modify the nitriding phenomenon and potentially lead to industrial nonconforming parts after treatment. The deactivation of treated surfaces has different origins, such as poisoning or fooling and can be generated during machining, stocking or different treatments applied to the parts before the nitriding treatment. Poisoning is due to a particle, which is easily and strongly adsorbed at the surface of the catalyst, leading to the blocking of the active sites, or in some case, a modification of the electric adsorption properties of the surface. In the case of iron, Maxted et al. reported that poisons are elements of group 5A (N, P, As, Sb) and 6A (O, S, Se, Te) [START_REF] Maxted | The poisoning of metallic catalysis[END_REF]. In the case of nitriding of steels, sulphur, that can be present in machining oils or lubricants, is known to strongly impact the adsorption of nitrogen atoms at the surface of iron [START_REF] Arabczyk | Poisoning of iron catalyst by sulfur[END_REF][START_REF] Grabke | Kinetics of Gas-Solid Interactions[END_REF]. Fouling of the catalytic element, which consists in a physical blocking of the active sites, mostly by carbon-based particles, prevents the contact between the catalyst and other elements of the transformation [START_REF] Hawkins | The impact on catalyst performance due to poisoning and fouling mechanisms[END_REF]. The carbon particles are generally due to the catalytic dehydrogenation of high molecular weight hydrocarbons. No work on the influence of carbon presence at the surface of parts before nitriding has been found.

In order to counter all these sources of pollution and guarantee the reliability and quality of the nitriding process, several pre-treatments are industrially used. Some are reported to increase the nitriding kinetics, while others are used to counter the detrimental effect of a potentially degraded surface as introduced in the previous paragraph. Treatments can be group in three categories: physical and mechanical, liquid and finally, gaseous treatments.

Physical and mechanical treatments that affect in-depth the material before nitriding, concern mainly cathode sputtering and shot peening respectively. Baranowska et al. showed that cathode sputtering, before 3 h nitriding of pure iron, enables to strongly increase the compound layer thickness [START_REF] Baranowska | Activation of surface in gas nitriding process[END_REF]. It was shown on low alloyed steel that a mechanical pretreatment, inducing nanostructured surface induced by plastic deformation can involve an increase of diffusion kinetics in the case of a nitriding treatment of 15 h [START_REF] Hassani-Gangaraj | The effect of nitriding, severe shot peening and their combination on the fatigue behavior and microstructure of a low-alloy steel[END_REF]. However, it must be considered that these results are obtained for short durations of treatments. The impact of such pre-treatment on the nitriding properties could be negligible for industrial durations of hundredth of hours.

Liquid treatments consist mainly in washing, dipping and rinsing the parts with specific, chemically controlled products. Birky compared the efficiency of several pre-treatments applied before few hours of gaseous nitriding of two steel grades [START_REF] Birky | Optimizing surface activation for repeatable compound layer growth[END_REF]. Chemical multi-stage washing of samples enabled a faster and more homogeneous compound layer formation. If this preparation improves the reliability of the treatment, no results indicates higher nitriding properties than the reference. The misuse of these processes can lead to the presence of residues at the surface of parts, leading to a potential inhibition of the nitriding. Haase studied the impact of several surface cleaner builders on the nitrogen concentration after a defined nitriding process [START_REF] Haase | Residue-free surface cleaning prior to heat treatment, Surface Modification Technologies IX[END_REF]. The presence of residues generated by some of these products, such as sodium metasilicate Na 2 O 3 Si or borax Na 2 B 4 O 7 .10H 2 O, leads to a strong reduction of the adsorption of nitrogen. It was also shown that rinsing a part is essential in order to limit the presence of residues and to obtain conforming nitriding properties [START_REF] Haase | Industrial free cleaning using halogen free cleaning agents : surfactant solutions and hydrocarbon solvents[END_REF].

The in-situ gaseous activating processes show a growing interest in the nitriding applications [START_REF] Friehling | Nucleation of iron nitrides during gaseous nitriding of iron; effect of a preoxidation treatment[END_REF]. These processes, enabling the surface preparation of the parts in the nitriding oven, strongly limit the potential sources of contamination between the activation and the final nitriding process, increasing its reliability. It consists in activating the surface by a direct contact between the surface and a gas at temperatures lower than the nitriding process. The gas can come from solid species at room temperature that generates an activating gas under thermal decomposition.

One of the most common in-situ pre-treatment is pre-oxidation. Friehling et al. shows that this process reduces the incubation time of nitride nucleation [START_REF] Friehling | On the effect of preoxidation on nitriding kinetics[END_REF]. Two hypotheses on the nature of this impact have been settled in another work. One suggests that the presence of an iron oxide layer influences the nitride nucleation while the other suggests that the presence of this layer inhibits the desorption or nitrogen during the catalytic decomposition of ammonia, leading to a higher amount of nitrogen at the surface. Pre-oxidation also modifies the iron nitride nucleation localization from grain boundaries to homogeneously on the whole surface.

This enhanced nucleation is explained by an accelerated dissociation of NH [START_REF] Irretier | Influence of contaminants on gas nitriding[END_REF]. The impact of the pre-treatment varies according to the contaminant nature, and in the case of machining oil, 30 min of pre-oxidation had an even higher detrimental effect on final surface hardness.

The second kind of in-situ pre-treatments is often referred as solid preparation. These are carried out by placing the solid-reactant in the nitriding oven, generating a gaseous product during its thermal decomposition. A patent filed by Christiansen et al. indicates the consistence of this kind of pre-treatments in the case of nitriding [START_REF] Christiansen | A method of activating an article of passive ferrous or non-ferrous metal prior to carburising, nitriding and/or nitrocarburising[END_REF]. The patent establishes a list of the employable products, including urea CH 4 N 2 O and indicates that this kind of pretreatments enables to nitride stainless steels but also low-alloyed steel with a surface contaminated with lubricant residues or severely deformed by a rough machining. It establishes a minimal temperature, in order to obtain the right decomposition product of, at least, 350 °C. The time is expected to be long enough to enable the treatment of the whole surface. In order to determinate the potential product responsible for the surface activation, it is necessary to study the thermal decomposition of this product. The work lead by Schaber et al. on this subject indicates complex decomposition and re-composition [START_REF] Schaber | Thermal decomposition (pyrolysis) of urea in an open reaction vessel[END_REF]. However, at 350 °C, for long enough treatments, every solid product totally decomposes into gaseous species. Amongst these, cyanic acid HNCO is formed, starting at 350 °C and reaching a maximum of concentration around 400 °C. It is expected that this substance is responsible for the surface activation.

A patent filed by the company Parker Netsushori Kogyo indicates the possibility to prepare surfaces before nitriding by using ammonium chloride NH 4 Cl [START_REF] Hoshino | Method for activating surface of metal member[END_REF]. The thermal decomposition of this product leads to the formation of gaseous hydrogen chloride HCl and ammonia NH 3 . The hydrogen chloride is expected to chemically attack the surface, leading to the decomposition of a potentially contaminated layer. While the first product enables the activation of surface, the presence of ammonia can lead to its adsorption and the potential formation of a white layer before the nitriding treatment, generating a protection against eventual detrimental oxidation of the surface.

The most common sources of industrial nitriding inhibitions are the poisoning adsorption of specific species, namely sulphur, or an inhibition by the physical presence of carbon at the surface of the parts. In order to counter these defects, surface activation processes are industrially used. While mechanical and liquid preparation are known and widely used, few results have been found concerning the surface activation potential of gaseous pre-treatments.

The present work focuses on the ability of three in-situ gaseous pre-treatments, namely preoxidation, urea and ammonium chloride, to activate the surface of industrially machined samples with several degrees of water-dissolved machining oil lubricants.

Experimental procedure

Material

Samples (17×13×5 mm 3 ) are manufactured from a 33CrMoV12-9 grade steel, austenitized at 920 °C for 90 min followed by a quenching and tempering at 640 °C under nitrogen atmosphere in order to have a tempered martensite material. The chemical composition, analysed by spark emission spectrometry (SPECTROMAXx MX5M BT from SPECTRO), is provided in Table I. Before any treatments, samples are degreased, rinsed in water and dried in alcohol. This state is referred in the rest of the study as the reference state.

Nitriding

Nitriding is carried out using a SETSYS Evolution thermogravimetric analyser from SETARAM Instrumentations. The atmosphere is composed of a mixture of ammonia, hydrogen and nitrogen (200 mL.min -1 ). The temperature is set up at 520 °C, for a nitriding potential of K N = 3.7 atm -1/2 during 300 min. The duration of treatment is chosen to be low as the impact of the physical and chemical state on the nitriding properties should be decreasing with the nitriding duration. Three vacuums down to 20 Pa followed by refilling with helium was performed before each treatment. Heating and cooling steps are conducted under an atmosphere of neutral gas, He and N 2 , at a rate of 10 °C.min -1 . Mass gain curves are corrected from fluid dynamics using a copper covered sample under the same treatment conditions.

Material characterization

After nitriding, samples are grinded and polished down to a 0.5 µm diamond solution and cleaned by ultrasound during 3 min before being etched with a 2%-nital solution (2 mL of nitric acid HNO 3 in 98 mL of ethanol C 2 H 6 O). Microstructure observations are carried out under an Olympus BX41M optical microscope equipped with a PixelLink camera and a JEOL JSM 7001F FEG scanning electron microscope (SEM) using a 15 kV acceleration voltage. Hardness profiles were obtained using a LEICA VMHT device with a load of 1.9 N applied during 15 s. The effective depth of nitrided layers is defined as the depth for which the hardness value is equal to the bulk hardness plus 100 HV0.2 [START_REF]Aciers -Détermination de l'épaisseur totale ou conventionnelle des couches minces durcies superficielles[END_REF]. The chemical composition is analysed by a SPECTROMAXx MX5M BT spark optical emission spectrometer from SPECTRO, Amtek. Depth profiling is obtained by successive mechanical grinding until elimination of previous sparks. Layer removal was controlled by dial indicator.

Profiles are obtained from four measurements at different locations of one side of samples.

Oil-based contamination

Contamination is carried out using a BLASOCUT BC 935 Kombi machining oil from Blaser Swisslube. Although the chemical composition is not fully known, the product is composed of phenoxypropanol C 9 H 12 O 2 , petroleum sulfonates, sodium salts and carboxylic acid ether.

Samples were soaked in a mixture of machining oil and water. The machining oil is dissolved in water at different ratio. Several ratios were studied in this part of the work, namely 1, 5 and 25 %. After 1 min of soaking, samples are taken out from oil bathing and droplets of oil at the surface are manually removed using an absorbing paper. Samples are then immediately placed in the thermogravimetric analyser for thermochemical treatments.

Carbon deposition

In order to study the influence of the presence of carbon on the treated surface, carbon deposition was performed on a sample under a vacuum bell using a heated carbon wire heated by joule effect. Considering the time of the experimentation, the carbon layer thickness on the facing side can be estimated between 300 and 500 nm. On the opposite face, it is expected that no or little carbon is deposited.

Pre-treatments

Pre-oxidation was carried out in the thermogravimetric analyser. The vacuum procedure proposed in the nitriding section is applied before the pre-oxidation treatment in order to avoid unwanted oxidation from residual air. Pre-oxidation is carried out at a fixed temperature of 350 °C during 1 h. The atmosphere is composed of pure oxygen at a rate of 30 mL.min -1 mixed with helium at a rate of 200 mL.min -1 . After oxidation, sample is cooled to room temperature under inert gas in order to visually control its aspect. The pre-treatment, if correctly carried out, generates a layer of iron oxides at the surface of the part, leading to a blue aspect of the overall surface. As a direct consequence, an optical observation of the surface before nitriding gives qualitative information on the quality and homogeneity of the pre-treatment.

Urea and ammonium chloride used were pure at 99.0 % and are solid at room temperature. A mass of 200 mg of products is introduced with the treated sample in an atmosphere controlled oven (HM70 from Pyrox). Pre-treatments are carried out at 400 °C during 100 min under inert gaseous nitrogen N 2 in order to prevent the sample from oxidation during heating. Heating and cooling of the sample are carried out at 10 °C.min -1 under inert gas N 2 . After cooling down to room temperature, samples are immediately introduced in the thermogravimetric analyser in order to be nitrided.

Results

The reference state

The mass gain, obtained by thermogravimetric analysis, of the sample is presented in Fig. 1.

This experimentation was carried out several times in order to study the variability of the experiment. The mean value of final mass gain is 1.49 ± 0.03 mg.cm -2 . The results also show important nitriding kinetics during the first hours of the treatment. After nitriding, the sample showed a homogeneous light grey matt surface. Observation of the microstructure reveals a compound layer, with a mean thickness value of 9 ± 0.9 µm, followed by a diffusion zone

A C C E P T E D M A N U S C R I P T Page 11
(Fig. 2A). Hardness measurements are given in Fig. 3. The hardness profile shows a surface hardness value of 940 HV0.2 at 40 µm and an effective depth of 135 µm. The nitrogen and carbon in-depth composition profiles are given in Fig. 4. After 5 h of nitriding at 520 °C, the nitrogen profile is characterized by a smooth transition from 1.2 wt. % at the compound/diffusion interface to the un-nitrided core material. A decarburization of the nitrided surface and an enrichment of carbon in front of the diffusion front are also observed.

The occurring of this phenomenon during gaseous nitriding of low-alloyed steels is known and was already characterised [START_REF] Fallot | Rôle du carbone lors de la nitruration d'aciers de construction et influence sur les propriétés mécaniques[END_REF].

Influence of cutting oil contamination

The mass gain profiles obtained during nitriding of two oil contaminated samples (1 and 5 %) are provided in Fig. 1. The 1 %-contaminated sample has a final mass gain of 0.72 mg.cm -2 , while the 5 %-contaminated sample has a very low final mass gain of 0.14 mg.cm -2 . The mass gain curves are also spread over time indicating a strong impact of oil residues on the kinetics of nitriding. The nitriding of a 1 %-contaminated sample has been carried out 4 times, leading to a final mass gain of 0.67 ± 0.10 mg.cm -2 . Contrary to the relatively low variability of the mass gain profiles obtained during the nitriding of reference samples, the nitriding of samples contaminated by 1 % of oil leads to a higher variability, that can be assigned to the heterogeneity of the film of water-dissolved oil at the surface of samples. In facts, the surface tension of the sample leads to the presence of oil in the shape of drops of various sizes. Fig. 5 provides a macrograph of the two large faces of the 1 % oiled sample after 5 h nitriding at 520 °C. The observation indicates two distinctive aspect of the surface. For most of the sample, the surface shows a matt light grey aspect while the rest of it has a metallic aspect.

Observation carried out where the aspect of the sample is matt light grey (P1 in Fig. 5)

indicates the presence of a thin white layer. Its thickness is more than 3 times lower than the reference sample(s) (2.7 and 9 µm respectively) after 5 h of nitriding at 520 °C.

Microstructural observations carried at point P2 of the 1 % oil-contaminated sample are provided in Fig. 2B. The aspect did not change at this point after nitriding (P2 in Fig. 5), and corresponds to either an un-nitrided zone or to a zone where a diffusion layer is present without a compound layer.

Microhardness measurements (Fig. 3) were carried out at the two different locations on the 1 %-oiled sample indicated by P1 and P2 in Fig. 5. Locations were chosen according to their macroscopic appearance from dark to bright grey matt that leads to the assumption of different kinetics of nitriding. Hardness profiles show that the nitrided surface is characterized by different effective depths (130 and 75 µm for P1 and P2 respectively). It confirms the heterogeneous nitriding of the treated surface due to the presence of a non-uniform film of oil.

The superficial hardness is however not modified in the present cases. This suggests a similar enrichment of nitrogen in the diffusion zone or the presence of a compound layer at a different stage of growth.

Finally, OES analyses (Fig. 6) have been carried out at the two points A and B, indicated in Fig. 5. Due to the heterogeneity of the sample, no variability is presented. These two zones are respectively characterized by a heterogeneous metallic and matt aspect and a homogeneous matt aspect that refers to nonconforming and conforming nitrided zones respectively. Chemical composition profiles are in agreements with previous observations. Zone B (homogeneous aspect) exhibits a nitrogen in-depth profiles similar to the reference after 5 h of nitriding at 520 °C whereas the progress of nitrogen enrichment in the zone with a heterogeneous aspect (point A) is less important, in terms of surface value and of affected depth.

Increasing the fraction of oil from 1 to 5 % in water tends to fully hinder the kinetics of nitriding. The final mass gain only reaches 0.14 mg.cm -2 after 5 h at 520 °C (Fig. 1). The global aspect of the sample after nitriding is unchanged, which indicates that almost no white layer was formed at the surface of the part. Light microscope observations after nitriding showed no compound layer formed and almost no modification of the initial microstructure on the whole sample. Microhardness measurements carried at several points of the sample confirmed the hinder of nitriding with a surface hardness (50 µm below the surface) that reaches only 400 HV0.2 after 5 h of nitriding against 930 HV0.2 for the reference state (Fig. 3).

Influence of a carbon deposition on nitriding

This section focuses on the analysis of machining oil residues generated at nitriding temperatures. Before experimentation, the sample was submitted to polishing down to a 0.5 µm diamond solution and cleaned by ultrasound during 3 min before dipping, in order to dissociate oil residues from machining chips. After dipping in a 1 % oil-water solution, the surplus of solution was manually removed with an absorbing paper. Following an isothermal treatment at 350 °C during 1 h, the surface of the sample was observed with SEM and backscattered electrons. The sample is characterized by small particles of 1 to 5 µm diameters, dispersed regularly at the surface (Fig. 7). According to EDS analysis as compared to the reference zone, the observed particles are mainly composed of carbon, but also oxygen, calcium and silicon (Fig. 8). Sulphur, oxygen and calcium are also present in the surrounding.

As several studies over the influence of sulphur on nitriding have been found in the literature, this work focuses on the influence of a pure carbon deposit. A sample was nitrided after being submitted to a carbon deposition process, as detailed in part 2.4. The nitriding kinetics during the two first hours is slower and the final mass gain (0.58 mg.cm -2 ) is nearly three times lower than the reference that reaches 1.49 mg.cm -2 (Fig. 9). The two sides of the sample have a very heterogeneous appearance after nitriding. The exposed face (facing the carbon wire during deposition prior to nitriding) indicates mostly a metallic aspect (Point C, Fig. 10). A few areas with a matt light grey aspect appear at the bottom of the part (Point A, Fig. 10). The microstructural observation of the exposed face indicates that a very thin compound layer is present in the zones where a matt grey aspect is present (Fig. 11A, corresponding to observation at point A in Fig. 10). The white layer reaches a thickness of 2.5 µm. In the zone where a metallic aspect can be observed, a diffusion layer is observed without a compound layer (Fig. 11B, corresponding to observation at point C in Fig. 12). The presence of carbon at the surface seems detrimental for the nitriding process. This observation is confirmed by microhardness measurements, carried out at several points of the exposed face (Fig. 10).

Measurements carried out at points where a thick compound layer is present (Point A, Fig. 10)

indicates hardness values at 50 µm of 890 HV 0.2, which is close to the reference. However, measurements carried out at points where a thin, or no compound layer could be observed indicates a strongly diminished hardness value at 50 µm (Point C, Fig. 10).

Pre-oxidation and machining oil

Figure 12 gives the mass gain during nitriding of a reference sample, submitted to preoxidation before nitriding. It indicates lower kinetics of nitriding after pre-oxidation. After five hours of treatment, the final mass gain of this sample reaches 1.34 mg.cm -2 which is 0.15 mg.cm -2 lower to the reference. The sample had a homogeneous matt light grey aspect on the whole surface. The microstructure observations and microhardness measurements exhibit very little difference with the reference sample. The nitrided surface is, as a consequence, very similar to the reference one and the results suggest that the delay in the kinetics of nitriding observed in Fig. 12 corresponds to the initial presence of an oxide layer due to preoxidation.

Pre-oxidation was carried out on samples immersed in machining oil water diluted at different degrees: 1 %, 5 %, 25 % and pure oil. The corresponding mass gain profiles during nitriding are provided in Fig. 13. Pre-oxidation considerably increase the kinetics of nitriding of oil-contaminated samples. Detrimental effects of 1 and 5 % oil solutions on nitriding are almost entirely suppressed after pre-oxidation. Microstructure observations of the 1 %-contaminated sample indicate a homogeneous white layer, slightly thinner than the reference.

Microhardness measurements of the 1 %-contaminated sample indicate a mean surface hardness of 900 HV 0.2. This value is very close to the reference sample. The effective depth is equal to 135 µm as for the reference. For the 5 %-contaminated sample pre-oxidised, the microstructure observations show a thick white layer (Fig. 14A), similar as for the 1 %contaminated treated with pre-oxidation. Hardness measurements show that the surface hardness reaches 875 HV0.2, which is almost the same as the reference and that the effective depth reaches 125 µm, which is lower than the reference (Fig. 15).

Pre-oxidation and carbon deposition

Pre-oxidation was tested on carbon deposition prior to nitriding. The mass gain curve clearly indicates that the surface with a carbon deposition was activated by pre-oxidation (Fig. 9).

While the carbon-contaminated samples had a final mass gain of 0.58 mg.cm -2 , the pre-treated sample reached a final mass gain of 1.49 mg.cm -2 , similar to the reference. Macroscopic observation of the samples after treatment shows a homogeneous matt grey layer.

Microstructure observations indicate a similar nitrided surface to the reference with a white layer thickness of 9 µm (Fig. 14B). Microhardness in-depth profiles are given in Fig. 16, for the exposed side of the sample. Surface hardness reaches 870 HV0.2 for this face. The nitriding depth is equal to 145 µm, which is higher than the reference (135 µm).

Urea

Surface preparation by urea and NH 4 Cl were investigated in the case of nitriding of steels contaminated with machining oil and compared to pre-oxidation. The impact of a preparation using urea on mass gain kinetics is given in Fig. 17. Urea preparation involves slightly lower kinetics of nitriding during the first hours as compared to the reference. However, the final mass gain reaches 1.45 mg.cm -2 , which is lower but close to the reference (1.49 mg.cm -2 ).

Urea pre-treatment on a 1 % oil-contaminated sample leads to a final mass gain per surface of 1.43 mg.cm -2 . Thermogravimetric analyses of samples contaminated by a 5 % oil solution and prepared with urea indicate a final mass gain of 1.36 mg.cm -2 while the sample without preparation barely reached 0.14 mg.cm -2 . The corresponding microhardness measurements are given in Fig. 18. The hardness at 50 µm reaches 860 and 870 HV0.2 for 1 and 5 % waterdissolved oil, and the effective depth reaches 135 and 120 µm respectively.

The preparation with urea also had a significant effect on contaminations by 25 % of oil. The final mass gain per surface reached 0.68 mg.cm -2 . This value is lower than the reference but higher than the final mass gain of the sample contaminated by 5 % of oil, nitrided without preparation process. However, it is lower than the one obtained by a pre-oxidation in similar conditions (1.25 mg.cm -2 ). The sample contaminated with 25 % of oil and prepared under urea showed a very thin white layer, with a few locations where it could not be observed, in agreement with the mass gain curve. The mechanical properties of the sample contaminated with 25 % of oil and prepared under urea are lower, in terms of surface hardness and nitriding depth, than the reference (Fig. 18).

NH 4 Cl

The thermogravimetric analyses carried out over the reference sample and samples contaminated with oil and prepared with ammonium chloride are provided in Fig. 19. No reduction of the nitriding kinetics could be observed after applying this pre-treatment to the reference sample. The final mass gain is 1.49 mg.cm -2 , which is equal to the reference. The hardness at 50 µm reaches 900 HV0.2 and the effective depth is 140 µm (Fig. 20).

The final mass gains of samples prepared with ammonium chloride after a 5 % and 25 % oilcontamination reach 1.49 and 1.39 mg.cm -2 , indicating a strong surface activation potential of the considered product (Fig. 19). Hardness-depth profiles of these samples are indicated in Fig. 20. Hardness at 50 µm of all the samples contaminated by different degrees of oil dilution and prepared with ammonium chloride are close to the reference. The samples contaminated by 5 and 25 % have a hardness at 50 µm of 920 and 880 HV0.2 respectively. The effective depths of the 5 and 25 % samples reach 140 µm, which is slightly higher than the reference, but equal to the reference sample prepared under oxygen.

Discussion

The impact of a machining oil film on the nitriding properties is non-negligible. While the considered product is industrially used at a 8 % rate, a 1 % oil film strongly inhibits the nitriding properties. This is confirmed by observing the final mass gain, that are divided by 2 after 5 h of nitriding at 520 °C and K N = 3.7 atm -1/2 (Tab. II) and the strong reduction of mechanical properties (Tab. III). Even if the industrial parts are highly cleaned before nitriding, and are thus theoretically free from oil residues, their complex shapes can lead to a detrimental surface preparation. In the case of nitriding of an oil-contaminated sample, the variability of the final mass gain measure is high and can be attributed to the heterogeneity of the oil film obtained by immersion. The variability of 1 % contaminated and nitrided samples remains low enough, compared to the diminishing of final mass gain, for not being detrimental in the present analysis. Increasing the oil-based contamination indicates that the higher the concentration of oil, the lower the nitriding kinetics is. This result is not in agreement with the work done by Irretier et al., where a contamination by residues of machining oil had no significant impact on the nitriding properties generated after a 4 h nitriding at 520 °C and K N = 10 atm -1/2 [START_REF] Irretier | Influence of contaminants on gas nitriding[END_REF]. However, the criterion of evaluation of the nitriding quality was chosen to be the surface hardness. It has been shown in the present work that the surface hardness is not sufficient in order to estimate the quality of nitriding. In Fig. 3, it can be observed that the values of surface hardness are the same for several areas of the sample but in-depth profiles vary leading to non-compliant nitriding depth.

The nature of the industrial oil used is also a source of difference with the literature due to the complex chemical composition of oils. Precautions must be taken during comparisons. The reduction of nitriding kinetics is due to machining oil residues at the surface of parts. After isothermal treatment at 350 °C of a sample immersed in water-dissolved oil, SEM characterizations of the surface mainly indicate the presence of oxide, silicon, calcium, sulphur and carbon compounds in these residues. The inhibition of catalysis properties by sulphur poisoning is a much studied phenomenon. Only a low amount of sulphur concentration can dramatically lower the catalytic properties [START_REF] Arabczyk | Poisoning of iron catalyst by sulfur[END_REF][START_REF] Grabke | Kinetics of Gas-Solid Interactions[END_REF]. In the present study, the effect of a carbon deposition on nitriding was shown to also have a strong and detrimental influence on the nitriding kinetics. The deactivation of catalytic properties of steels by the presence of an oil film can then be expected from the carbon residues on the treated surface.

During heating to nitriding temperature, most of the oil film is burnt. Hawkins makes the distinction between three kinds of carbon deposits [START_REF] Hawkins | The impact on catalyst performance due to poisoning and fouling mechanisms[END_REF]. The firsts are fine and loose carbons, generally generated by dehydrogenation of carbon-containing gas, and are easily removed by oxidation in air. The seconds are resinous polymeric like carbons due to the dehydrogenation of high molecular weight compounds, such as alkanes and naphthenes. These two first categories are expected to be burnt in air at temperatures from 300 °C. If not, heating will induce the formation of graphitic carbon (the third kind of carbon deposit) that regroups dehydrogenation of single aromatic rings hydrocarbons, such as benzene, leading to multiring, graphitic form polymers that cannot be removed by air oxidation. It is not expected to burn in air at temperatures below 580 °C. In the case of the experimentations lead in this work, the burning of oil by heating at nitriding temperatures generates residues of carbon of the third kind, leading to a local complete inhibition of catalytic properties. SEM-observations indicated that these residues are homogeneously spread out all over the surface, locally inhibiting the catalytic deactivation. At the locations where the surface is clean from residues, nitriding occurs as in the reference case. As a consequence, for contaminated samples, the effective surface is reduced, leading to an inhibited global amount of nitrogen adsorption during the process. If the contamination is high enough, the inhibition of nitrogen adsorption can lead to the prevention of the compound layer formation.

Three surface in-situ preparations were investigated. Urea and NH 4 Cl were compared to preoxidation prior to nitriding. Their efficiency was tested on samples immersed in waterdissolved oil. Some work has been done over the influence of pre-oxidation before gaseous nitriding. During the present work, it has been carried out over cleaned and contaminated samples. During the pre-treatment of cleaned samples, the early nitriding kinetics observations showed that an incubation time has been settled by the pre-oxidation. It should be considered that the layer formed during pre-oxidation is decomposed during the heating under neutral gas and during the nitriding process. This is expected to happen by the phenomenon of oxide layers reduction that occurs due to the presence of hydrogen. This reduction can generate an incubation time during the nitriding treatment, depending on the thickness of the layer. However, this result is in contradiction with the different results obtained in the literature, indicating that a pre-treatment by oxidation reduces the incubation time already present during the nitriding process [START_REF] Friehling | Nucleation of iron nitrides during gaseous nitriding of iron; effect of a preoxidation treatment[END_REF]. It should be considered that the pretreatment parameters can influence the layer formed. Irretier et al. prepared the samples with a very low partial oxygen pressure (5.7 10 -23 Pa) [START_REF] Irretier | Influence of contaminants on gas nitriding[END_REF], while the oxidation process was carried out, in this work, with a partial oxygen pressure of approximately 13 10 3 Pa. As a consequence, it can be assumed that the layer formed during the present work is thicker than the one obtained in the reference, leading to a non-negligible reduction duration, and so, a higher nitriding incubation time. As a reminder, no optimisation of the pre-treatment parameters is carried out during this work.

The work carried out by Irretier et al. also showed that a pre-oxidation of 30 min in air improved the mechanical properties after nitriding in the case of 42CrMo4-grade steel, and inhibited these mechanical properties in the case of C15 and X155CrMoV12.1 grade steels [START_REF] Irretier | Influence of contaminants on gas nitriding[END_REF]. Neither of these results is in agreements with the present work. The considered preoxidation treatment only enabled to negligibly modify the mechanical properties of the treated sample.

On some specific alloys, the pre-oxidation treatment leads to a higher surface hardness for the reference state. This increase can be explained by supposing that the pre-oxidation treatment has an impact on the nitride precipitation, leading to thinner nitrides and as a consequence, higher hardness. It should also be considered that the activity of oxygen at the surface of the solid leads to the diffusion of carbon to the surface, indicating a loss of carbon in the first tenth micrometres of the substrate and a modification of nitriding properties.

Also, it should not be forgotten that the results presented by Irretier et al. shows that the pretreatment is very sensitive to the steel grade considered. The difference in chemical composition, notably in alloying elements, of the considered steels between the two studies could explain this divergence. The oxidation of high-chromium content alloys can lead to the formation of chromium oxide at the surface of parts, being detrimental for the nitriding process. Moreover, it should be considered that the mechanical surface preparation of the reference state is different between the two studies, potentially explaining the divergence of results.

Despite the influence of the thickness of the oxide layer on a reference sample, pre-oxidation has a strong capacity to counter the inhibition generated by machining oil residues. This impact can be observed over thermogravimetric analysis but also microstructure observations, hardness and residual stress measurements. While a pollution of 5 % diluted oil almost completely prevents the sample from nitriding, a 1 h pre-treatment by oxidation lead to a homogeneously nitrided sample, very close from the reference. This capacity to annihilate the degrading impact of oil residues has been confirmed up to a dilution of 25 % of oil in water.

This study stated that the carbonic particles of the machining oil residues might play an important role in the inhibition of nitriding by this kind of pollution. In order to verify this hypothesis, a pre-oxidation treatment (that has a strong impact on machining oil contamination) is applied to a carbon contamination. The results indicate that the use of this pre-treatment enables to remove the inhibiting carbon layer, leading to a nitrided layer similar to the reference. Pre-oxidation involves adsorption of oxygen at the surface of carbon residues leading to the cleaning of the surface by the formation of gaseous compounds, such as CO or CO 2 . The fact that the pre-oxidation treatment activates, in a similar way, a surface contaminated by oil and by carbon deposit leads, once again, to the conclusion that the presence of element carbon is a non-negligible reason for the inhibition of nitriding process by an oil-based contamination.

Finally, urea and ammonium chloride have been tested over reference and oil-based contaminations. Their impact on reference state before nitriding indicates no remarkable improvement on the nitriding properties, although the depth of residual stress profiles seems higher. In the case of the preparation of an oil-contaminated surface, both processes showed activating properties. Analyses of samples contaminated by 1 and 5 % oil, and prepared by oxidation, urea or ammonium chloride indicated microstructural and mechanical properties similar to the reference. In order to compare the different processes, the application of pretreatments over a 25 % oil-contaminated sample enables to determine that the ammonium chloride provides the higher surface activation capacity. This result can be confirmed by observing the final mass gain (Fig. 21), but also mechanical properties (Tab. III).

The activation properties of urea and ammonium chloride are certainly due to their capacity to generate a chemical etching of the contaminant. This hypothesis could be confirmed by using different methods of surface analysis.

Conclusions

The present work focuses on the inhibition of the gaseous nitriding process by an industrial contamination, namely machining oil. The results indicated a strong negative influence of this product over the nitriding properties, i.e. nitrogen adsorption, leading to a heterogeneous aspect of the parts and a global lowering of mechanical properties. In addition to the wellknown detrimental effect of sulphur and phosphate, the present work shows that the inhibition of the treated surface can be due to the presence of carbon particles leading to a strong alteration of the catalytic decomposition. The capacity of several in situ pre-treatments to counter this inhibiting effect has been studied. The pre-oxidation treatment has no impact on the nitriding of clean samples, neither in terms of nitriding kinetics nor mechanical properties.

It should be reminded that pre-treatment parameters are estimated from literature analysis and that no optimisation of these values is carried out. The pre-treatment proved to counter the inhibiting effect of machining oil-contaminations before nitriding, enabling to reach the reference nitriding properties, even for samples highly contaminated (25 % dilution rate).

Better results were obtained using ammonium chloride in terms of nitriding kinetics and nitrogen adsorption since no layer (such as iron oxide from pre-oxidation) has to be reduced.

The surface activation is expected to happen by decomposition of the contaminants, according to the atmosphere obtained during heating (NH 4 Cl decomposes into NH 3 and HCl). Although, urea product showed good surface activating properties in the case of low oil dilution rates, its Figure 5 -Overview of the two faces of the 1 %-contaminated sample nitrided during 5 h at 520 °C and a nitriding potential of 3.7 atm -1/2 . Microstructural observation (Fig. 2) and microhardness analyses (Fig. 3) are carried out at locations P1 and P2, while nitrogen content analysis (Fig. 6) are carried out at points A et B.

List of figure captions

Figure 6 -Nitrogen content profiles of the reference and at two locations (A and B, Fig. 5) of the 1 % oil-contaminated sample nitrided during 5 h at 520 °C and a nitriding potential of 3.7 atm -1/2 (OES analysis).

Figure 7 -SEM-BSE observations of 1 %-water diluted machining oil residues at the surface of polished samples after heating at the nitriding temperatures (520 °C) followed by direct slow cooling to room temperature under inert gas.

Figure 1 -

 1 Figure 1 -Mass gain profiles of the reference, 1 % and 5 % oil contaminated samples nitrided during 5 h at 520 °C and a nitriding potential of 3.7 atm -1/2 .

Figure 2 -

 2 Figure 2 -Optical microscope observations (2%-nital etching) of the reference (A) and at the point P2 (Fig. 5) of the 1 % oil contaminated (B) samples nitrided during 5 h at 520 °C and a nitriding potential of 3.7 atm -1/2 .

Figure 3 -

 3 Figure 3 -Microhardness profiles of the reference, of two different locations (P1 and P2, Fig. 5) of the 1 % oil-contaminated and of the 5 % oil-contaminated samples nitrided during 5 h at 520 °C and a nitriding potential of 3.7 atm -1/2 .

Figure 4 -

 4 Figure 4 -Nitrogen and Carbon content of the reference sample nitrided during 5 h at 520 °C and a nitriding potential of 3.7 atm -1/2 , measured by sparkle spectroscopy (OES analysis).

Figure 8 -

 8 Figure 8 -EDS mapping of machining oil residues heated at 520 °C: Carbon, Calcium, Sulphur, Oxygen and Silicon.

Figure 9 -

 9 Figure 9 -Mass gain profiles of the reference, carbon contaminated and carbon contaminated submitted to pre-oxidation samples nitrided during 5 h at 520 °C and a nitriding potential of 3.7 atm -1/2 .

Figure 10 -

 10 Figure 10 -Microhardness profiles and overview of the exposed face of the carbon contaminated sample nitrided during 5 h at 520 °C and a nitriding potential of 3.7 atm -1/2 .

Figure 11 -

 11 Figure 11 -Optical microscope observations (2%-nital etching) at two different locations A and B (indicated in Fig. 10) of the exposed face of the carbon contaminated sample nitrided during 5 h at 520 °C and a nitriding potential of 3.7 atm -1/2 .

Figure 12 -

 12 Figure 12 -Mass gain profiles of the reference and pre-oxidized samples nitrided during 5 h at 520 °C and a nitriding potential of 3.7 atm -1/2 .

Figure 13 -

 13 Figure[START_REF] Maxted | The poisoning of metallic catalysis[END_REF] -Mass gain profiles of the reference, oil contaminated and pre-oxidized after oil contamination samples nitrided during 5 h at 520 °C and a nitriding potential of 3.7 atm -1/2 .

Figure 14 -

 14 Figure14-Optical microscope observations (2%-nital etching) of the sample contaminated by 5 % oil and pre-oxidized (A) and of the sample pre-oxidized after a carbon contamination (B) followed by nitriding during 5 h at 520 °C and a nitriding potential of 3.7 atm -1/2 .

Figure 15 -

 15 Figure 15 -Microhardness profiles of the reference, 5 % oil-contaminated and 5 % oilcontaminated and pre-oxidized samples nitrided during 5 h at 520 °C and a nitriding potential of 3.7 atm -1/2 .

Figure 16 -

 16 Figure 16 -Microhardness profiles of the reference and of the exposed face of the carbon contaminated samples nitrided during 5 h at 520 °C and a nitriding potential of 3.7 atm -1/2 .

Figure 17 -

 17 Figure 17 -Mass gain profiles of the reference and oil contaminated carbon prepared with urea samples nitrided during 5 h at 520 °C and a nitriding potential of 3.7 atm -1/2 .

Figure 18 -

 18 Figure 18 -Microhardness profiles of the reference and oil contaminated carbon prepared with urea samples nitrided during 5 h at 520 °C and a nitriding potential of 3.7 atm -1/2 .

Figure 19 -

 19 Figure 19 -Mass gain profiles of the reference and oil contaminated carbon prepared with ammonium chloride samples nitrided during 5 h at 520 °C and a nitriding potential of 3.7 atm - 1/2 .

Figure 20 -

 20 Figure 20 -Microhardness profiles of the reference and oil contaminated carbon prepared with ammonium chloride samples nitrided during 5 h at 520 °C and a nitriding potential of 3.7 atm -1/2 .

Figure 21 -FiguresFigure 1

 211 Figure 21 -Summary of the final mass gain of the reference, oil-contaminated and oilcontaminated prepared with oxygen/urea/ammonium chloride samples nitrided during 5 h at 520 °C and a nitriding potential of 3.7 atm -1/2 .

Table II :

 II Summary of the final mass gain [mg.cm-2 ] obtained by thermogravimetric analysis.

		-	Oxidation	Urea	NH 4 Cl
	Reference	1.49	1.34	1.46	1.49
	Oil 1 %	0.72	1.47	1.43	-
	Oil 5 %	0.14	1.40	1.36	1.48
	Oil 25 % Pure oil Carbon deposit	--0.58	1.25 0.39 1.49 M A N U S C R I P T 0.68 --	1.39 --
	A C C E P T E D
			Page 51

Table III :

 III Summary of the effective depth [µm] obtained by microhardness measurements.

		-	Pre-oxidation	Urea	NH 4 Cl
	Reference	135	-	-	-
	Oil 1 %	75 to 130	135	140	-
	Oil 5 %	0	135	120	140
	Oil 25 %	-		115	145
	Carbon deposit	0 to 90	145	-	-

Acknowledgments

This research was supported by BPIFrance (grant FUI AAP14-DefiNIT-F1302013U). The authors deeply thank Airbus Helicopters and Bodycote for sample machining and heat treatment. The authors also thank Ch. Dominici (CP2M, Aix-Marseille University) for carbon deposition.

ability to counter a machining oil-based contamination proved to be lower than the two previous processes for a rate of 25 %.

Highlights

 The impact of an oil-based contamination on nitriding properties is determined.

 Thermogravimetric, microstructural and mechanical analyses are used.

 Explanations on the oil-contamination are proposed.

 Surface activation capacities of in-situ treatment are analysed.

 In-situ treatments are based on oxygen, urea or ammonium chloride.


Alexis Paljic
email: alexis.paljic@inria.fr

Sabine Coquillart
email: sabine.coquillart@inria.fr

Jean-Marie Burkhardt
email: jean-marie.burkhardt@inria.fr

Paul Richard Istia

A Study of Distance of Manipulation on the Responsive Workbench TM

Virtual environments such as the Responsive Workbench TM1 allow the close manipulation of virtual objects. We define close manipulation as either direct manipulation or manipulation at a relatively small distance. This paper reports on two studies on close manipulation using the Responsive Workbench. The first study investigates the influence of manipulation distance on performance in a 3D location task. The results indicate that direct manipulation and 20 cm distance manipulation are more efficient than for 40 and 55 cm distances. The second study investigates the effect of two factors: the presence or absence of a visual clue, and the scale value, which is a variation of the scale (1 or 1.5) used to map the user's movements to the pointer. Task performance is significantly lower when using the visual clue, and when using the 1.5 scale.

Introduction

The design of efficient interfaces for 3D applications is a concern for application developers and researchers. Virtual environment systems like the CAVE TM2 , the Responsive Workbench TM (or Workbench), the FishTank, or Head-Mounted Displays (HMD's) are powerful technologies for interacting with 3D worlds. With such systems, the user is typically presented with stereoscopic views of the virtual world. By means of head tracking, the stereoscopic images can be presented to the user according to his viewpoint. In this case, the virtual and real spaces are superimposed and can be mixed together. By superimposing real and virtual spaces, systems utilizing head tracking allow close manipulation.

Close manipulation is often intended to provide the users with an intuitive way of interacting with 3D computer-¡ Corresponding author: Alexis Paljic, INRIA Rocquencourt, Domaine de Voluceau 78153 Le Chesnay Cedex France. 1 Responsive Workbench is a trademark of GMD. 2 CAVE is a trademark of University of Illinois.

generated worlds. In this paper, we define close manipulation as either direct manipulation, which is manipulation with the hand being as close as possible to the virtual objects, or manipulation at a relatively small distance (distances below one meter), with a gap separating the hand and the object being manipulated.

The workbench is one of the most attractive systems for close manipulation. Its table-like shape is well adapted to the close manipulation of virtual mock-ups or virtual models presented to the user. Unlike HMD, the workbench offers the advantage of not losing contact with the physical environment: the user's co-workers or his own body and hands. Furthermore, the workbench provides a large display and allows manipulation of models with a great freedom of movement.

As for most virtual environment systems, the design of user interfaces for the workbench is quite different from what we are used to with desktop configurations. Currently we have only a weak knowledge of user-interface principles with which to develop efficient interaction techniques suitable for the workbench. There is also clearly a need to provide both theoretically-grounded and empirically-validated rationales for the design of 3D interfaces. This paper presents two user studies addressing performance in different situations of close manipulation.

This study is also motivated by an observation frequently made during demonstrations on the workbench. Novice users often manipulate objects from a distance instead of bringing the hand as close as possible to the object. Holding the manipulated object at a distance is obviously a disadvantage at least for rotations because the center of rotation is at the hand and thus far from the object. However, does distance manipulation offer any compensating benefits? Is it more natural, more convenient, or more comfortable for the user? Should we advise, or even force the user to reduce as much as possible the distance of manipulation or not? More generally, close manipulation raises several questions: what is the influence of the distance of manipulation on task performance? Does the use of a virtual ray to fill the gap between the hand and the object in distance manipulation help the user? How does scaling user movements into the virtual world affect user performance? Some of these questions have been addressed previously, but never using a workbench. Extrapolating previous evaluation is hazardous because results differ depending on the configuration.

The objective of this study is to investigate the influence of the distance of manipulation on performance in a location task. An experiment using four values for distance was conducted so that the results could provide a view of performance variation for a large interval. A second experiment which studies the effect on user performance of two other conditions of manipulation is also presented. The first condition is the use of a virtual ray between the hand and the object being manipulated, the second consists of mapping user movements to the virtual objects with a 1.5 scale factor.

The next section describes the major previouslypublished studies related to close manipulation. In Section 3 we present the experiments and procedure used for the study. The results of the experiments are presented in Section 4, and a discussion is proposed in Section 5.

Related work

Two studies that compare direct manipulation and manipulation at a distance have been proposed by Mine [START_REF] Mine | Exploiting proprioception in virtual-environment interaction[END_REF] and Djajadiningrat et al. [2][3].

Mine [START_REF] Mine | Exploiting proprioception in virtual-environment interaction[END_REF] investigates the effect of proprioception on various interaction techniques using an HMD. In particular, the author carried out a study of direct manipulation to explore the differences between manipulating virtual objects colocated with one's hand and manipulating objects at a distance. The subjects performed a docking task using cubes. Three conditions were tested: manipulation of objects held in one's hand, objects held at a fixed offset and objects held at an offset varying according to the subject's arm extension. Statistical analysis shows that the manipulation of objects co-located with one's hand is significantly faster than the manipulation of objects at a fixed offset, as well as manipulation at a variable offset.

The study by Djajadiningrat et al. [START_REF] Djajadiningrat | Cubby : What You See is Where You Act. Interlacing the display and manipulation spaces[END_REF][3] compares direct manipulation and manipulation at a distance of 20 cm using two systems: a single screen fishtank-like setup and a smallsize, three-screen, head tracked, non-stereoscopic virtual reality system called Cubby. The study was performed using a puzzle reconstruction task. No significant difference in performance between the two conditions for manipulation was found. However, subjects reported a subjective preference for direct over distant manipulation within each set-up.

A third study conducted by Poupyrev et al. [START_REF] Poupyrev | Egocentric object manipulation in virtual environments : Empirical evaluation of interaction techniques[END_REF] indirectly addresses the problem of close manipulation. An evaluation of different egocentric object manipulation techniques was carried out, among them the classical virtual hand and the go-go technique [START_REF] Poupyrev | The go-go interaction technique: Non-linear mapping for direct manipulation in VR[END_REF]. This study can be related to comparing direct and distant manipulation: the classical virtual hand method is direct manipulation since the object can be exactly co-located with the hand, and the go-go technique involves distance manipulation because the coupling between the input device and the cursor is non-linear. The study was done using a positioning task with an HMD system, so the user was totally immersed, without real-world visual feedback. For both techniques, the manipulated objects were located within arm's reach. When the task required moving the object closer or further away, statistical analysis did not reveal a significant difference in task performance due to technique. Conversely, when the initial and final positions of the object were at the same distance from the user, the direct manipulation technique was significantly 22% faster than the other techniques.

Method

The objective of this study is to investigate the effect of manipulation distance on user performance in an environment that allows close manipulation. In Mine's study, distance of manipulation is randomly set between 10 and 60 cm, making it difficult to analyze the effect of variations of the distance of manipulation. We chose to conduct our study on fixed distance values. Four values were chosen in order to observe the effect of distance of manipulation within a large range of distances related to close manipulation. Another reason why we chose fixed values of distance is that it allows the user to stabilize his behaviour for a given distance, which is much harder when the distance is randomly changed for each trial, as in Mine's study.

Twenty-four participants were asked to perform a set of location tasks, in which they were presented with four manipulation distances. The users performed the task with a virtual pointer controlled by a tracker held in the hand (see Figure 1).

Distance of manipulation was set by changing the offset between the hand and the virtual pointer or cursor (see Figure 2). For direct manipulation, the cursor was displayed as close as possible to the hand of the user. This closest position is the tip of the tracked stylus. Figures 3 and4 show two examples of close manipulation (direct and at a 55 cm distance).

As a continuation of the first study, and in order to help interpretation of its results, we carried out a second study to see how two common manipulation techniques could improve the user's performance in a 55 cm distance manipulation. The first manipulation technique consists of adding a virtual ray to bridge the gap between the user's hand and the cursor. The second maps the user's movements to the cursor with different scale values (1 and 1.5). The subjects, proce- dure, and equipment were the same for the two experiments, but the studied factors differ.

Equipment

The virtual environment system used for the experiment was a two-screen Responsive Workbench TM using a 1280 1024 resolution for each screen, a 96Hz vertical refresh rate, and shutter glasses (Crystal Eyes TM ) for stereo vision. A 6 degrees of freedom tracker was used for head tracking, and a Fastrak Stylus tracker with one button for hand tracking and selection. The application was developed with the SGI Performer API, and runs on an SGI Onyx2.

Procedure

The location task consists of clicking on a start sphere and then clicking on a target sphere that appears at another location. Nine target sphere locations were chosen, each at an equal distance from the start sphere (see Figure 5). Let us assume that the x-axis is pointing towards the user and the z-axis is pointing upwards. The start sphere always appears 40 cm above the center of the horizontal screen at (0,0,0) coordinates. Two spheres were on the yaxis: p1(0,20,0) and p2(0,-20,0), two on the top-bottom zaxis: p3(0,0,20) and p4(0,0,-20). Five spheres were off-axis and located at p5(10,10,14.14), p6(10,10,-14.14), p7(10,-10,14.14), p8(10,-10,-14.14), and p9(-10,-10,14.14). No visual indications regarding the target positions were displayed, and in particular, the axes on Figure 5 were not displayed. During the test, the start sphere and the cursor were always displayed, and the current target sphere was displayed only during the task.

The subjects were instructed to perform the task as fast as possible. To perform the task, the user stood in front of the workbench and held the tracked stylus in his/her dominant hand to control the virtual pointer. The pointer was a cross-shaped cursor, used for clicking on the start and target spheres. The distance of manipulation was determined by the offset between the hand and the cursor (see Figure 2).

A click on a sphere triggers the next sphere to appear if the center of the cursor is inside the volume of the sphere (2.5 cm radius sphere) and the stylus button is pressed.

Only the translations of the tracked stylus are mapped onto the cursor, not rotations. The reason for this choice was to ensure that all users completed the task using the same displacement strategy, whatever the distance to the cursor was. Thus, to control the cursor the user had to translate his hand, not turn his wrist.

Each of the subjects was presented with one of the 24 permutations of 4 manipulation conditions studied in the experiment. For each condition, the subject accomplished a session composed of 3 trial tasks and 18 experimental tasks. For the experimental tasks, targets appeared exactly two times on each of the nine pre-defined locations in a random order, yielding 18 targets. At the end of each experiment, the user was asked to sort the conditions in terms of easiness.

Studied factors

For the first experiment, the design was composed of two factors: target position (the 9 pre-defined targets) and offset which is the distance between the tip of the stylus tracker The direction of this offset is in all cases parallel to the xaxis (see Figure 5), so the cursor location in space is the position of the hand, plus a translation (0, 20, 40 or 55 cm) on the x-axis. In this experiment the movement mapping between the hand of the user and the cursor was 1 to 1, meaning that the user's hand translations were exactly copied to the cursor without any multiplying constant.

In the second experiment, we compared four situations of manipulation yielded by the combination of two factors. The first is visual clue, which is a virtual ray linking the hand of the user to the cursor (two values: displayed, not displayed). When the ray is displayed, it is always directed on the x-axis, because no rotations are applied. The second factor is scale, for which two values are tested: 1 and 1.5. For a 1 scale, the offset between the hand and the cursor is 55 cm. Using a 1.5 scale results in a variable offset between the hand and the cursor (attached to the ray) during manipulation. For a 1.5 scale, the origin of the scale is chosen in order to have a 55 cm distance between the hand and the cursor when the user positions the cursor on the start sphere. The last factor studied in this second experiment is the target position, with the same 9 pre-defined targets as in the first experiment. The only difference in target position is for the 1.5 scale manipulation: targets were 1.5 times further from the start sphere than in the other situations. This is to ensure that the user's physical hand displacement remains the same as with the 1 scale.

Participants

Seven female and seventeen male subjects participated in the experiment. They all had normal or corrected vision. Eighteen were right-handed, five left-handed. One of the left-handed persons preferred to hold the tracked Stylus in his right hand.

Results

Task completion time is the dependent variable gathered for each task: it is the time elapsed between the click on the start sphere and the click on the target sphere. Subject ratings for easiness were also gathered to examine the subjective perception of the various manipulation conditions.

First experiment

This study is a 4 (offset value) 9 (target position) design. Task completion times for the two repetitions of each target position are averaged together to yield a single value. Figure 6 shows mean completion times. Analysis of variance (ANOVA) for mean task completion time revealed a significant effect of the offset value (F(3,828)=131.191 p 0.0001). Post-hoc analysis for offset value using the Scheffé test shows that subjects perform the task faster for 0 cm and 20 cm offsets than for 40 cm and 55cm offsets. There are no significant differences between 0 and 20 cm, nor for 40 and 55 cm Target position (F(8,828)=16.55 p 0.0001) has a significant effect on task performance. Post-hoc analysis using the Scheffé test for target positions shows that the off-axis targets p8 and p9 required significantly more time than the others. Target p5 takes significantly more time than p2. On-axis targets were always completed faster than off-axis targets, except for p4, which required more time than p6 or p7 to reach, but these results are not significant. p2 is the easiest target overall. Significant interaction effects were found for offset values target position (F(24,828)=5.574 p 0.0001). Figure 7 shows mean completion time for each target.

Second experiment

This study is a 2 (visual clue) 2 (scale) 9 (target position) design. Anova for mean task completion time indicates that there is a significant effect of the visual clue (F(1,828)=20.249 p 0.0001). Globally, the users take more time to complete the task when the visual clue (virtual ray) is displayed than without this added information.

There is also a significant effect of the scale factor (F(1,828)=253.330 p 0.0001). Subjects performed the task significantly slower when the scale was 1.5. Figure 8 shows mean completion time for each condition. A significant effect was found for target position (F(8,828)=11,16 p 0.0001). Figure 9 shows mean completion time for each position. As in the first experiment, post-hoc analysis using the Scheffé test shows that the off-axis targets p8 and p9 required significantly more time than the others. Significant effects were found for both two-way interaction scale

Subjects comments

Subjects were asked to sort, in terms of easiness, the 4 manipulation conditions for each experiment. Table 1 summarizes rankings for the first experiment. Each column, corresponding to one condition, contains the number of persons who rated that condition respectively 1 (easiest), 2, 3 and 4 (hardest). For the first experiment, 0 and 20 cm dis-0 cm 20 cm 40 cm 55 cm 1 10 5 tance manipulations are significantly better rated (first and second) than 40 and 55cm ( ¢¡ ¤£ ¦¥ ¨ § =14.33, p 0.005). Conversely, the users show no significant preference between the manipulation conditions ( ¢¡ non significant) in the sec- ond experiment.

p1 p2 p3 p4 p5 p6 p7 p8 p9 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9
Target location Mean Completion time (s)

Discussion

For the first experiment, a simple model of user behaviour could have been that performance in completion time decreases linearly with manipulation distance. The results show that this is not the case and that user behaviour is more complex.

The results for task completion time for the first experiment suggest the existence of two sets of manipulation distances between which user performance significantly differs. Distances from 0 to 20 cm can be interpreted as a direct manipulation area, since subject performance appears to be equivalent. This result replicates Djajadiningrat's result of no significant difference between 0 and 20 cm distance manipulations. For distances from 40 to 55 cm the task completion time is significantly higher than for 0 and 20 cm offsets. Furthermore, these higher distances seem to correspond to an area where the subjects adopt a different behaviour, or at least seem to be engaged in a more demanding task. It is possible that these results replicate those of Mine showing that distant manipulation results in higher completion times. Indeed, Mine et al. use a random distance from 10 to 60 cm for each trial, which could be considered as a manipulation distance of 35 cm on average, thus being much closer to our 40 cm condition, than the 0 to 20 cm area. However, the fact that the distance is not fixed in Mine's experiment is a important shift in settings between the two experiments.

We propose to interpet these results in terms of consistency among visual and propioceptive information, and their respective informativeness relative to the task. For the first set of distances, we can consider that the frame of reference for the user is his hand, meaning that the task is com-pleted by bringing the hand close to the desired location. In such manipulation, visual and proprioceptive information are strongly related and the user can easily use them jointly. For the second set of distances, we can consider that the frame of reference is the cursor, meaning that the task is done by bringing the cursor, not the hand, to the desired location. In this case, joint use of visual and proprioceptive information requires an additional treatment, because the two types of information are not as closely related as when the hand is the reference. The control of hand movement may be more complex because the user has to take into account the difference between the frame of reference (the cursor) and the frame associated with his hand. This additional treatment could explain the decrease in performance for the 40 to 55 cm set of distances.

Another explanation for the decrease in performance for the 40 cm to 55 cm interval could be a change in depth perception. Work by Yoshida et al. [START_REF] Yoshida | An improvement method for depth perception in stereoscopic display[END_REF] addressed the effect of the distance between the eyes and the screen on the perceived depth of a virtual object in a stereoscopic display. Using four values of distance between 60 and 100 cm, they found that the greater the distance, the more users underestimate the distance to the object. The error is always inferior to 10 mm. In our experiment, the users slightly moved back (maximum 40 cm) for the 40 and 55 cm offsets in order to have their arm in a comfortable position. Since head tracking was used, the user is likely to present the same depth perception errors indicated by Yoshida et al. However, these errors are small compared to the size of the spheres used for the task (5 cm diameter), suggesting that the biases due to depth perception are not likely to affect the user performance in any way.

For the second experiment, our hypothesis was that adding a ray (visual clue) that bridges the gap between hand and cursor would help the user. But on the contrary, results show that user performance is significantly lower when the ray is displayed 3 . This experiment was done with a 55 cm distance of manipulation where, according to the first hypothesis, the user would choose the cursor as the frame of reference. One hypothesis that can explain the results for visual clue is that visually linking the cursor and the hand forces the user to use his hand as the frame of reference, whereas in a normal distance manipulation (without visual clue) he would have chosen the cursor as the frame of reference. This might result in a cognitively confusing situation. However, further investigation is needed to address this cognitive issue.

The results for target position in the first experiment show that p8 and p9 take significantly longer to be clicked. We can raise different hypotheses. Target p9 is the furthest target from the user's eyes, so it is visually smaller and can be harder to see than the other targets. Target p8 is located in the lower-left manipulation area, and can be hidden by the arm of left-handed users when they click on the start sphere: this can lead to a greater time to find the target. The mean completion time for most of the off-axis targets (all except p6 and p7, which are faster to reach than p4) is higher than for on-axis targets, but these results are not statistically significant and further work is required to address this problem. Comparison between on-axis target completion times shows a result that is consistent with the results of a study of 3D point location done by Boritz and Booth [START_REF] Boritz | A study of interactive 3d point location in a computer simulated virtual environment[END_REF]: up and down (p1 and p2) targets take more time to reach than left and right targets (respectively p3 and p4). In our setting, these differences are not statisically significant. Boritz and Booth found one significant difference between left and down targets (p2 and p4).

Significant interaction effects between offset target position show that the difference for p8 and p9 compared to other targets is higher for 40 and 55 cm offsets. One explanation could be that the treatment for manipulation at 40 and 55 cm is more important as the offset grows, particularly for these two off-axis targets.

The results for the scale factor in the second experiment show that users manipulating with a 1 to 1 translation mapping (scale=1) perform better than with a variable offset (scale=1.5). This result is consistent with previous work done by Mine et al.[6]. The effect of the scale can be interpreted in light of the hypothesis on consistency between proprioceptive and visual information: as a higher offset induces more information treatment to control the movement, scale may also be a limit because it adds a supplementary difference between visual and proprioceptive information.

Subject comments on manipulation distance are consistent with the performance variation that we measured. Most users rate the closer manipulation to be easier. As distance of manipulation grows, subjects rate it to be harder. It is surprising to see that users prefer direct manipulation, whereas the reaction of users that are new to immersive displays is to manipulate at a distance from the virtual objects. In this experiment, for direct manipulation the users had to get close to the objects, otherwise they couldn't complete the task. This obligation may make them realize that direct manipulation is more comfortable. This tends to support the decision to give the users instructions to manipulate at the closest possible distance. These results are consistent with user comments retrieved by Mine and Djajadiningrat, where users prefer direct manipulation. In Poupyrev and al.'s experiment, all but three users do not prefer the direct manipulation technique, which could be due to the fact that the classical virtual hand technique is perceived as less innovative than the other techniques, particularly the go-go technique.

Conclusion and Future Work

An experiment was conducted to study the influence of distance of manipulation on a location task. Results show that manipulation at a closer distance (direct manipulation to 20 cm) is significantly more efficient than for 40 cm to 50 cm in our setting. The second experiment studied the influence of adding a visual clue or a scale on performance in the same location task. It was found that adding a visual clue (virtual ray) to fill the gap between the hand and the cursor lowers user performance, and also that using a 1.5 scale factor to map user movement to the cursor significantly lowers task performance.

To be able to use these results as rationales for 3D user interface design, it is important to replicate them on similar systems in order to check their stability.

In future work, we want to focus on the effect of training on performance in 3D location tasks within the context of direct and distance manipulation. The objective is to see how the performance between direct and distant manipulation can change with training, and particularly if distant manipulation can become as efficient as direct manipulation. Secondly, we plan to study the variation in performance in the transition interval (between 20 cm and 40 cm distance of manipulation) to see if, for example, there is a gap value of the offset for which performance significantly changes, or if performance decreases continuously.

Figure 1 .

 1 Figure 1. User performing the task.

Figure 2 .

 2 Figure 2. Side view of direct and distance manipulation on the workbench.

Figure 3 .

 3 Figure 3. Direct manipulation: the cursor used to interact with the objects (cross) is as close as possible to the user's hand.

Figure 4 .

 4 Figure 4. Distance manipulation: the cursor is 55 cm distant from the user's hand.

Figure 5 .

 5 Figure 5. Target locations: s is the start sphere, p1 to p9 are the target spheres, the x-axis is pointing towards the user, the z-axis is pointing upwards.

Figure 6 .

 6 Figure 6. Mean task completion time for each of the offset conditions with standard deviation bars (first experiment).

Figure 7 .

 7 Figure 7. Mean task completion time for each target position with standard deviation bars (first experiment).

Figure 8 .

 8 Figure 8. Mean completion time (seconds) for the second experiment conditions: Ray means that the virtual ray between the hand and the cursor is visible, S is the scale value.

Figure 9 .

 9 Figure 9. Mean completion time (seconds) for each target position in the second experiment

Table 1 . Subject rating for conditions in the first experiment, 1 is easiest, 4 is hardest.

 1

				2	7
	2	6	12	4	2
	3	3	4	12	5
	4	5	3	6	10

We discarded the hypothesis that a bias could be due to a change in image refresh rate by checking that it is the same for both conditions.

Acknowledgements

This study was partially funded by the Regional Council of Ile-de-France and the French Ministry of Research within the RNTL Perf-rv project. The Responsive Workbench used in the study has been partially funded by the Regional Council of Ile-de-France. The authors want to thank M. Stephen Kreisler and all the subjects who participated in the experiment.