... For the sake of simplicity consider the plane problem of a rigid cylindrical body indenting a... more ... For the sake of simplicity consider the plane problem of a rigid cylindrical body indenting a beam ... The equations can be solved using the least square error method [461. ... 41] used finite difference methods to study the problem of axisymmetric contact between a rigid sphere and ...
Volume 7: 9th International Conference on Design Education; 24th International Conference on Design Theory and Methodology, 2012
ABSTRACT The design of engineering systems is often based on analysis models with substantial err... more ABSTRACT The design of engineering systems is often based on analysis models with substantial errors in predicting failures, that is epistemic uncertainty. The epistemic uncertainty is reduced by post design tests, and the safety of unsafe designs restored by redesign. When this process of design, test and redesign is to be based on probabilistic analysis, there is some controversy on whether uncertainty associated with variability (aleatory uncertainty) should be treated differently than the epistemic uncertainty. In this paper we compare several approaches to design and redesign and treatments of the epistemic uncertainties. These include safety factors, probabilistic approach disregarding redesign and regarding redesign, treating epistemic uncertainty and aleatory uncertainty the same, and more conservative treatment of the epistemic uncertainty. We demonstrate that the proposed approach can allow tradeoff of system performance against development cost (probability of redesign), while a standard reliability based design optimization, which does not take into account future redesign, provides only a single point on the tradeoff curve. We also show that the tradeoff can be achieved even with the traditional safety factor approach, without any probabilistic optimization. Furthermore, we investigate different treatments of epistemic error for probability of failure calculation. We find that it is possible to design to the 95th percentile of the probability of failure with modest mass penalty compared to treating epistemic and aleatory uncertainty alike.
... For the sake of simplicity consider the plane problem of a rigid cylindrical body indenting a... more ... For the sake of simplicity consider the plane problem of a rigid cylindrical body indenting a beam ... The equations can be solved using the least square error method [461. ... 41] used finite difference methods to study the problem of axisymmetric contact between a rigid sphere and ...
Volume 7: 9th International Conference on Design Education; 24th International Conference on Design Theory and Methodology, 2012
ABSTRACT The design of engineering systems is often based on analysis models with substantial err... more ABSTRACT The design of engineering systems is often based on analysis models with substantial errors in predicting failures, that is epistemic uncertainty. The epistemic uncertainty is reduced by post design tests, and the safety of unsafe designs restored by redesign. When this process of design, test and redesign is to be based on probabilistic analysis, there is some controversy on whether uncertainty associated with variability (aleatory uncertainty) should be treated differently than the epistemic uncertainty. In this paper we compare several approaches to design and redesign and treatments of the epistemic uncertainties. These include safety factors, probabilistic approach disregarding redesign and regarding redesign, treating epistemic uncertainty and aleatory uncertainty the same, and more conservative treatment of the epistemic uncertainty. We demonstrate that the proposed approach can allow tradeoff of system performance against development cost (probability of redesign), while a standard reliability based design optimization, which does not take into account future redesign, provides only a single point on the tradeoff curve. We also show that the tradeoff can be achieved even with the traditional safety factor approach, without any probabilistic optimization. Furthermore, we investigate different treatments of epistemic error for probability of failure calculation. We find that it is possible to design to the 95th percentile of the probability of failure with modest mass penalty compared to treating epistemic and aleatory uncertainty alike.
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Papers by Bhavani Sankar