Dynamic evolution of interface roughness during friction and wear processes

Dynamic evolution of surface roughness and influence of initial roughness (Sa=0.282 to 6.73 µm) during friction and wear processes has been analyzed experimentally. The mirror polished and rough surfaces (28 samples in total) have been prepared by surface polishing on Ti-6Al-4V and AISI 1045 samples. Friction and wear have been tested in classical sphere/plane configuration using linear reciprocating tribometer with very small displacement from 130 to 200 microns. After an initial period of rapid degradation, dynamic evolution of surface roughness converges to certain level specific to a given tribosystem. However, roughness at such dynamic interface is still increasing and analysis of initial roughness influence revealed that to certain extent, a rheology effect of interface can be observed and dynamic evolution of roughness will depend on initial condition and history of interface roughness evolution. Multiscale analysis shows that morphology created in wear process is composed from nano, micro and macro scale roughness. Therefore, mechanical parts working under very severe contact conditions, like rotor/blade contact, screws, clutch etc. with poor initial surface finishing are susceptible to have much shorter lifetime than a quality finished parts

Identification of Local Lubrication Regimes on Textured Surfaces by 3D Roughness Curvature Radius

This paper proposes a new method of 3D roughness peaks curvature radius calculation and its application to tribological contact analysis as a characteristic signature of tribological contact. This method is introduced through the classical approach of calculation of radius of asperity in 2D. Actually, the proposed approach provides a generalization of Nowicki's method [ ], depending on horizontal lines intercepting the studied profile. Here, the basic idea consists in intercepting the rough surface by a horizontal plane and to calculate the cross section area without including “islands into islands”, i.e. the small peaks enclosed in bigger ones. Then, taking into account the maximal value of the height amplitude of the roughness included into this area, an appropriate algorithm is proposed, without requiring the classical hypothesis of derivability, which may be unstable when applied to engineering surfaces. This methodology is validated on simulated surfaces, and applied to engineering surfaces created experimentally, with a laboratory aluminium strip drawing process. The regions of the textured and lubricated specimens surface are analysed, and the results gives interesting prospects to qualitatively identify the local lubrication regimes: regions with high curvature radii correspond to severe contact (boundary/mixed lubrication regime) while regions with low curvature radii correspond to hydrodynamic lubrication regime

How to select the most relevant 3D roughness parameters of a surface

In order to conduct a comprehensive roughness analysis, around sixty 3D roughness parameters are created to describe most of the surface morphology with regard to specific functions, properties or applications. In this paper, a multiscale surface topography decomposition method is proposed with application to stainless steel (AISI 304), which is processed by rolling at different fabrication stages and by electrical discharge tool machining. Fifty-six 3Droughness parameters defined in ISO, EUR, and ASME standards are calculated for the measured surfaces. Then, expert software 'MesRug' is employed to perform statistical analysis on acquired data in order to find the most relevant parameters characterizing the effect of both processes (rolling and machining), and to determine the most appropriate scale of analysis. For the rolling process: The parameter Vmc (the Core Material Volume-defined as volume of material comprising the texture between heights corresponding to the material ratio values of p=10% and q=80%) computed at the scale of 3 mm is the most relevant parameter to characterize the cold rolling process. For the EDM Process, the best roughness parameter is SPD that represents the number of peaks per unit area after segmentation of a surface into motifs computed at the scale of 8 mm. SCANNING 9999:1-11, 2013. (c) Wiley Periodicals, Inc

Wetting of anisotropic sinusoidal surfaces - experimental and numerical study of directional spreading

Directional wettability, i.e. variation of wetting properties depending on the surface orientation, can be achieved by anisotropic surface texturing. A new high precision process can produce homogeneous sinusoidal surfaces (in particular parallel grooves) at the micro-scale, with a nano-scale residual roughness five orders of magnitude smaller than the texture features. Static wetting experiments have shown that this pattern, even with a very small aspect ratio, can induce a strong variation of contact angle depending on the direction of observation. A comparison with numerical simulations (using Surface Evolver software) shows good agreement and could be used to predict the fluid-solid interaction and droplet behaviour on textured surfaces. Two primary mechanisms of directional spreading of water droplets on textured stainless steel surface have been identified. The first one is the mechanical barrier created by the textured surface peaks, this limits spreading in perpendicular direction to the surface anisotropy. The second one is the capillary action inside the sinusoidal grooves accelerating spreading along the grooves. Spreading has been shown to depend strongly on the history of wetting and internal drop dynamics

The measurement problem on classical diffusion process: inverse method on stochastic processes

In a high number of diffusive systems, measures are processed to calculate material parameters such as diffusion coefficients, or to verify the accuracy of mathematical models. However, the precision of the parameter determination or of the model relevance depends on the location of the measure itself. The aim of this paper is first to analyse, for a mono-dimensional system, the precision of the measure in relation with its location by an inverse problem algorithm and secondly to examine the physical meaning of the results. Statistical mechanic considerations show that, passing over a time–distance criterion, measurement becomes uncertain whatever the initial conditions. The criterion proves that this chaotic mode is related to the production of anti-entropy at a mesoscopique scale that is in violation to quantum theory about measurement

Perimeter analysis of the Von Koch island, application to the evolution of grain boundaries during heating

This paper introduces an analyse of the fractal dimension by Richardson’s method. Two different ways to calculate the fractal dimension are presented with their related calculation errors and applied the Von Koch curves. A Monte-Carlo simulation of the evolution of the grains’ boundaries when heating shows that the interfaces lose their fractal characteristics as reported in experimental work. This result is interpreted by dissipation of the energy during the evolution of the grain boundary

Statistical artefacts in the determination of the fractal dimension by the slit island method

This paper comments upon some statistical aspects of the slit island method which is widely used to calculate the fractal dimension of fractured surfaces or of materials’ features like grain geometry. If a noise is introduced when measuring areas and perimeters of the islands (experimental errors), it is shown that errors are made in the calculation of the fractal dimension and more than a false analytical relation between a physical process parameter and the fractal dimension can be found. Moreover, positive or negative correlation with the same physical process parameter can be obtained whether the regression is performed by plotting the variation of the noisy area versus the noisy perimeter of the considered islands or vice versa. Monte-Carlo simulations confirm the analytical relations obtained under statistical considerations

A numerical method to calculate the Abbott parameters: A wear application

A numerical technique was proposed to plot the Abbott curve and to compute its associated parameters defined by the DIN 4776 and ISO 13565 norms. These parameters were then extended and applied to non-sigmoid Abbott curves. By studying the discretisation errors, we show that a minimum of 200 intercepts, with parabolic interpolations between discretised data profiles, have to be taken into consideration to calculate the parameters as accurately as possible. Experimental profiles were eroded by means of a numerical wear model, and it was shown that the Abbott parameters correlate well with the wear model parameters. Our numerical estimations of Abbott parameters were performed for electro-eroded, tool machined, polished, worn and sandblasted surfaces. Manual measures were compared with our algorithmic method and it was shown that the difference is lower than 1% for Mr1 and Mr2 Abbott parameters, but the numerical technique leads to a lower dispersion

Multiscale measures of equilibrium on finite dynamic systems

This article presents a new method for the study of the evolution of dynamic systems based on the notion of quantity of information. The system is divided into elementary cells and the quantity of information is studied with respect to the cell size. We have introduced an analogy between quantity of information and entropy, and defined the intrinsic entropy as the entropy of the whole system independent of the size of the cells. It is shown that the intrinsic entropy follows a Gaussian probability density function (PDF) and thereafter, the time needed by the system to reach equilibrium is a random variable. For a finite system, statistical analyses show that this entropy converges to a state of equilibrium and an algorithmic method is proposed to quantify the time needed to reach equilibrium for a given confidence interval level. A Monte-Carlo simulation of diffusion of A* atoms in A is then provided to illustrate the proposed simulation. It follows that the time to reach equilibrium for a constant error probability, te, depends on the number, n, of elementary cells as: te∝n2.22±0.06. For an infinite system size (n infinite), the intrinsic entropy obtained by statistical modelling is a pertinent characteristic number of the system at the equilibrium

Physical Interpretations of the Numerical Instabilities in Diffusion Equations Via Statistical Thermodynamics

The aim of this paper is to analyze the physical meaning of the numerical instabilities of the parabolic partial differential equations when solved by finite differences. Even though the explicit scheme used to solve the equations is physically well posed, mathematical instabilities can occur as a consequence of the iteration errors if the discretisation space and the discretisation time satisfy the stability criterion. To analyze the physical meaning of these instabilities, the system is divided in sub-systems on which a Brownian motion takes place. The Brownian motion has on average some mathematical properties that can be analytically solved using a simple diffusion equation. Thanks to this mesoscopic discretisation, we could prove that for each half sub-cell the equality stability criterion corresponds to an inversion of the particle flux and a decrease in the cell entropy in keeping with time as criterion increases. As a consequence, all stability criteria defined in literature can be used to define a physical continuous 'time-length' frontier on which mesoscopic and microscopic models join