2020
DOI: 10.1017/jmech.2019.41
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Multi-Objective Optimisation of an Aerostatic Pad: Design of Position, Number and Diameter of the Supply Holes

Abstract: In this paper, a rectangular aerostatic bearing with multiple supply holes is optimised with a multiobjective optimisation approach. The design variables taken into account are the supply holes position, their number and diameter, the supply pressure, while the objective functions are the load capacity, the air consumption and the stiffness and damping coefficients. A genetic algorithm is applied in order to find the Pareto set of solutions. The novelty with respect to other optimisations which can be found in… Show more

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Cited by 8 publications
(3 citation statements)
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“…The results of the variance regression model analysis are shown in Table 2 [19][20][21][22][23]. Table 3 shows that the lack of fit is not significant when the P of the model is less than 0.0001, indicating that the equation is significant.…”
Section: Response Surface Analysis Of the Triangular Groove Design Pa...mentioning
confidence: 99%
“…The results of the variance regression model analysis are shown in Table 2 [19][20][21][22][23]. Table 3 shows that the lack of fit is not significant when the P of the model is less than 0.0001, indicating that the equation is significant.…”
Section: Response Surface Analysis Of the Triangular Groove Design Pa...mentioning
confidence: 99%
“…In global optimization problems, other approaches include population-based methods, like Genetic Algorithms (see, [6][7][8][9]) and Swarm Intelligence-based methods (e.g., Particle Swarm Optimization methods, see [10][11][12]). These nature-inspired methods are somehow similar to multi-start methods since they are based on a set of starting guesses; however, this set is used as a swarm of interacting agents that move in the domain of the loss function, looking for a global minimizer.…”
Section: Introductionmentioning
confidence: 99%
“…Chen et al 9,10 studied the effect of backflow phenomenon and geometric parameters of rectangular grooves on the static performance of aerostatic bearing and made recommendations for bearing design. Colombo et al 11 took into account the effects of the position, number and diameter of orifice on the bearing load capacity, air consumption, stiffness and damping coefficients, solved the Pareto set of solution by genetic algorithm, and optimized the aerostatic porous bearing by using multi-objective optimization method. Chen 12 analyzed the influence of unbalanced magnetic force on the nonlinear dynamic behavior of the air bearing motorized spindle.…”
Section: Introductionmentioning
confidence: 99%