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A New Approach for the Reliability-Based Robust Design Optimization of Mechanical Systems under the Uncertain Conditions

机译:不确定条件下机械系统的可靠性鲁棒设计优化的一种新方法

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A mechanical system inherently affected by the conditions, factors, and parameters of uncertainties. Without including the uncertainty effects in the design procedure, the designs may not be robust and reliable. Robust design optimization (RDO) method is a procedure to find the insensitive design with respect to the variations. On the other hand, reliability is measured by the probability of satisfying a specific design criterion. Therefore, a reliable design is a design that satisfies the specified criteria even with some uncertainties in variables and parameters. Reliability-based design optimization (RBDO) is an optimization procedure that incorporates reliability requirements to find the proper design. Since RDO and RBDO are usually the expensive computational approaches, the Reliability-Based Robust Design Optimization (RBRDO) may be difficult to apply. In this paper, a new model for the reliability based robust design optimization is introduced. First, two new factors that are called “chance - penalty function” and “reliability multiplier” are introduced. Based on these new factors, the optimality, the robustness, and the reliability functions as three objective functions are modeled. Then, a combined model for the RBRDO of the mechanical systems under the uncertain conditions is proposed. Finally, the application of the proposed method is demonstrated through the design of two case studies under uncertain conditions, and the computational results are compared to the obtained results from classical methods.
机译:受不确定性的条件,因素和参数固有的机械系统。如果在设计过程中没有包括不确定性效果,则设计可能不稳定可靠。鲁棒设计优化(RDO)方法是一个关于差异找到不敏感设计的过程。另一方面,通过满足特定设计标准的概率来测量可靠性。因此,可靠的设计是一种满足指定标准的设计,即使在变量和参数中存在一些不确定性。基于可靠性的设计优化(RBDO)是一种优化过程,包括可靠性要求来查找正确的设计。由于RDO和RBDO通常是昂贵的计算方法,因此可以难以应用基于可靠性的鲁棒设计优化(RBRDO)。本文介绍了一种基于可靠性的鲁棒设计优化的新模型。首先,介绍了称为“机会 - 惩罚函数”和“可靠乘数”的两个新因素。基于这些新因素,为三个客观函数的最优性,鲁棒性和可靠性函数进行了建模。然后,提出了在不确定条件下的机械系统RBRDO的组合模型。最后,通过在不确定条件下设计两个案例研究来证明所提出的方法的应用,并且将计算结果与古典方法的获得结果进行比较。

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