The objective of this Master's thesis is to find, using genetic algorithm (GA), an optimal profile for lubricating gap of a thrust bearing of a turbocharger. Compared to the analytical profile, the optimal profile is expected to have minimized friction for an equivalent load capacity. Friction minimization is one way to increase the efficiency of the thrust bearing; it reduces the friction losses in the bearing. An initial problem was given: a thrust bearing with Load capacity 1000 N, inner and outer radii of 30mm and 60mm respectively, rotor speed of 45000 rpm and angle of running surface of $0.5^0$. Lubricant properties were also provided for the initial problem: oil density of $ 840 kg/m^3$, dynamic viscosity $(\eta)$ of 0.01 Pa.s With this data, the numerical solution of the Reynolds equation was computed using MATLAB. To obtain more information, the minimum lubricating gap thickness was also computed using MATLAB. With this information, the shape of the analytical profile, and its characteristics were found. The analytical profile was then used a guide to create a general profile. The general profile thus obtained is then optimized using GA. The characteristics of the generated profile is then computed and compared to that of the analytical profile.
Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:451223 |
Date | January 2021 |
Creators | Ochulo, Ikechi |
Contributors | Vacula, Jiří, Novotný, Pavel |
Publisher | Vysoké učení technické v Brně. Fakulta strojního inženýrství |
Source Sets | Czech ETDs |
Language | English |
Detected Language | English |
Type | info:eu-repo/semantics/masterThesis |
Rights | info:eu-repo/semantics/restrictedAccess |
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