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PROBABILISTIC DESIGNS OF AIR-BEARING SURFACE ON MANUFACTURING TOLERANCES

机译:制造公差上的空气表面的概率设计

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摘要

The focus in this paper is to automatically design the air-bearing surface (ABS) considering the randomness of its geometry as an uncertainty of design variables. Designs determined by the conventional optimization could only provide a low level of confidence in practical products due to the existence of uncertainties in either engineering simulations or manufacturing processes. This calls for a reliability-based approach to the design optimization, which increases product or process quality by addressing randomness or stochastic properties of design problems. In this study, a probabilistic design problem is formulated considering the reliability analysis which is employed to estimate how the fabrication tolerances of individual slider parameters affect the final flying attitude tolerances. The proposed approach first solves the deterministic optimization problem. Beginning with this solution, the reliability-based design optimization (RBDO) is continued with the probabilistic constraints affected by the random variables. Probabilistic constraints overriding the constraints of the deterministic optimization attempt to drive the design to a reliability solution with minimum increase in the objective. The simulation results of the probabilistic design are directly compared with the values of the initial design and the results of the deterministic optimum design, respectively. In order to show the effectiveness of the proposed approach, the reliability analyses by the Monte Carlo simulation are carried out. And the results demonstrate how efficient the proposed approach is, considering the enormous computation time of the reliability analysis.
机译:本文的重点是考虑其几何形状的随机性作为设计变量的不确定性来自动设计气浮表面(ABS)。由于工程仿真或制造过程中存在不确定性,通过常规优化确定的设计只能对实际产品提供低水平的信心。这要求基于可靠性的设计优化方法,通过解决设计问题的随机性或随机性来提高产品或过程的质量。在这项研究中,考虑了可靠性分析,提出了一个概率设计问题,该可靠性分析用于估计各个滑块参数的制造公差如何影响最终的飞行姿态公差。所提出的方法首先解决了确定性优化问题。从该解决方案开始,基于可靠性的设计优化(RBDO)继续受到随机变量影响的概率约束。超越确定性优化约束的概率约束试图以最小的目标增长将设计驱动到可靠性解决方案。将概率设计的仿真结果分别与初始设计的值和确定性最佳设计的结果直接进行比较。为了证明所提方法的有效性,进行了蒙特卡洛模拟的可靠性分析。结果表明,考虑到可靠性分析的大量计算时间,该方法的有效性。

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