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Efficient Robust Design Optimization of a Stacker-Reclaimer Structure Under Uncertainty

机译:不确定条件下的堆取料机结构的高效鲁棒设计优化

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A stacker-reclaimer structure (SRS) is a massive structure used for bulk material exploration. Performance of SRS is sensitive to the effect of uncertainty which may lead to catastrophic failure consequences. Thus, in this paper a comparatively new robust design optimization (RDO) approach for design of SRS is explored. The involved parameter of SRS e.g., material loading, incrustation, normal digging, etc., may not have well-defined probability density functions and can be expressed as uncertain but bounded (UBB) type parameters. Hence, RDO is explored for probabilistic as well as UBB cases. Solution of such RDO problem in full simulation approach would require extensive computational time. Hence, response surface method (RSM) based metamodeling approach has been adopted here to alleviate computational burden. Also, as conventional least squares method (LSM) based RSM may be a source of error, this study adopts a comparatively new moving LSM (MLSM) based adaptive RSM in RDO. The RDO results depict that UBB type uncertainty is more critical than the probabilistic case. The proposed MLSM based RDO approach yields reasonably accurate design solutions in a computationally efficient way. The proposed MLSM based RDO approach yields design solutions which ensures safe performance of SRS even in the presence of uncertainty.
机译:堆取料机结构(SRS)是用于散装物料勘探的大型结构。 SRS的性能对不确定性的影响很敏感,不确定性可能导致灾难性的故障后果。因此,本文探索了一种相对较新的鲁棒设计优化(RDO)方法来设计SRS。 SRS涉及的参数,例如材料负载,结壳,法线挖掘等,可能没有明确定义的概率密度函数,可以表示为不确定但有界(UBB)类型的参数。因此,针对概率和UBB案例研究了RDO。在完全仿真方法中解决这种RDO问题将需要大量的计算时间。因此,此处采用了基于响应面法(RSM)的元建模方法来减轻计算负担。而且,由于基于常规最小二乘法(RSM)的RSM可能是误差的来源,因此本研究在RDO中采用了一种相对较新的基于移动LSM(MLSM)的自适应RSM。 RDO结果表明,UBB类型不确定性比概率情况更为关键。所提出的基于MLSM的RDO方法以计算有效的方式提供了相当准确的设计解决方案。所提出的基于MLSM的RDO方法产生了设计解决方案,即使在存在不确定性的情况下,也可以确保SRS的安全性能。

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