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Rough surfaces in contact :artificial intelligence and boundary lubrication

by Rapetto, Marco

Abstract (Summary)
Interacting surfaces are found in mechanical systems and components. Since engineered surfaces are not perfectly smooth, only a fraction of the nominal surface area is actually in contact. This fraction is denoted as the real area of contact, Ar, and is formed by the sum of the contact spots between the two touching surfaces. If these contacting surfaces are sliding, then friction and wear occur in these actual contacts. Friction and wear may be controlled by lubrication: depending on the operating conditions different types of lubrication regime exist. When the surfaces are completely separated by the fluid film and load is carried by hydrodynamic action, contacts operate in hydrodynamic regime. When the load is carried by the lubricating fluid and asperity contact, the regime becomes mixed lubrication. In boundary lubrication, surfaces are in contact and the load is carried by surface asperities. In many cases this is the critical lubrication regime that governs the life of the components. Due to the complexity of thin film boundary lubrication, design of lubricated interfaces is still a trial-and-error process. The mechanism of formation and rupture of oxide layers and boundary layers is not completely known and a reliable model for rough surfaces in boundary lubrication is currently lacking. This study focuses on boundary lubrication regime: the effect of surface roughness on the real area of contact is investigated and a numerical model for the sliding interaction between two asperities in sliding contact is developed. Numerical simulations of normal, dry, friction free, linear elastic contact of rough surfaces are performed. A variational approach is followed and the FFT-technique is used to speed up the numerical solution process. Five different steel surfaces are measured using a Wyko optical profilometer and several 2-D profiles are taken. The real area of contact and the pressure distribution over the contact length are calculated for all the 2-D profiles. A new slope parameter is defined. An artificial neural network is applied to determine the relationship between the roughness parameters and the real area of contact. Boundary lubrication mechanism is usually controlled by the additives present in the oil that form low friction, protective layers on the wearing surfaces. Chemical reactions between the lubricant molecules and the asperity surface may take place. These reactions are activated by certain values of pressure and temperature. Fundamental research on the influence of surface roughness on contact conditions is hence required and is a key factor in understanding the wear mechanism in boundary lubrication condition since pressure distribution, shear stresses, frictional heating, mechanical wear highly depends on surface topography. Modelling boundary lubrication requires knowledge in many fields: contact mechanics, thermodynamics, surface chemistry etc, thus different sub-models interacting each other must be created. It is complicated and may be not feasible within a foreseeable time period to take into account all the different parameters and evaluate them. Artificial intelligence is a way to overcome the problem and determine the relationship between input parameters and desired outputs. An elasto-plastic analytical model is used to determine the variation of pressure distribution and shear stress during the collision process of two asperities in sliding contact. The outputs of the elasto-plastic model are inputs of the thermal model that calculates the temperature rise during the collision process. The desorption of the adsorbed layer is determined by using existing adsorption theories and finally the probability of wear is computed at each time step of the collision process. Different results obtained using different adsorption theories and different input parameters are compared.
Bibliographical Information:

Advisor:

School:Luleå tekniska universitet

School Location:Sweden

Source Type:Master's Thesis

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ISBN:

Date of Publication:01/01/2008

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