Alternative metrics for design decisions based on separating aleatory and epistemic probabilistic uncertainties

There is still much philosophical debate about whether a frequentist or subjective view of probability should be adopted. Some uncertainties (typically aleatory uncertainties) are naturally modelled using a frequentist approach, while others (epistemic uncertainties) are clearly subjective in nature. In light of this it has been argued, for example by the German philosopher Rudolf Carnap, that both potential descriptions of uncertainty should be maintained and treated separately. However, in current engineering practice it is common to make no distinction between these two types of uncertainty. Generally, uncertainty is represented by a single figure or distribution, for example a probability of failure, which incorporates both aleatory and epistemic uncertainties. This paper explores the idea of treating aleatory and epistemic uncertainties separately and proposes alternative metrics -based on the epistemic probability of an aleatory probability -which can potentially provide greater insight for the designer in engineering problems. The metrics are illustrated using two example engineering dynamics problems; the prediction of wind induced accelerations in a tall building and optimizing the design of sound-proofing in a car. It is shown that as well as providing further insight on the underlying contributing causes of uncertainty, treating aleatory and epistemic uncertainties as separate quantities, as opposed to in the traditional combined manner, can potentially lead to different design outcomes.

Automated summary

This paper discusses the importance of separating aleatory and epistemic uncertainties, proposes alternative metrics based on the epistemic probability of aleatory probabilities, and illustrates them through two engineering problems.