National Repository of Grey Literature 2 records found  Search took 0.01 seconds. 
Shape Optimization of the Machine Components due to Variability of Input Data
Sawadkosin, Paranee ; Jonák, Martin (referee) ; Novotný, Pavel (advisor)
The objective of this Master’s thesis is to find shape optimal design based on min- imizing friction force of thrust bearing by using genetic algorithm(GA) which is one of an optimization toolbox in Matlab. Reducing the friction force of thrust bearing is one way of making shaft to decreasing friction losses. With four parameters of thrust bearing geometry number of segments(m), angle of running surface(), segment inner radius(R0), and segment outer radius(R1) substitute in Reynolds’ equation. In order to know friction force, it is necessary to generate a connecting variable, oil film thickness(h0) from loading capacity(W ) and revolution per minute(rpm). Friction power loss, as well as weight func- tion conclude the final shape optimization of thrust bearing: m = 7, = 0.1, R0 = 15 mm, and R1 = 20 mm.
Shape Optimization of the Machine Components due to Variability of Input Data
Sawadkosin, Paranee ; Jonák, Martin (referee) ; Novotný, Pavel (advisor)
The objective of this Master’s thesis is to find shape optimal design based on min- imizing friction force of thrust bearing by using genetic algorithm(GA) which is one of an optimization toolbox in Matlab. Reducing the friction force of thrust bearing is one way of making shaft to decreasing friction losses. With four parameters of thrust bearing geometry number of segments(m), angle of running surface(), segment inner radius(R0), and segment outer radius(R1) substitute in Reynolds’ equation. In order to know friction force, it is necessary to generate a connecting variable, oil film thickness(h0) from loading capacity(W ) and revolution per minute(rpm). Friction power loss, as well as weight func- tion conclude the final shape optimization of thrust bearing: m = 7, = 0.1, R0 = 15 mm, and R1 = 20 mm.

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