Transformada da incerteza puramente numérica para a avaliação de incertezas - Brito Junior, Ademir Alves de (2016)
In this work, a numerical version of Unscented Transform was developed. In the developed approach, any probability distributions can be mapped by means of linear or non-linear functions, thus allowing fast acquisition of the probability distributions of the outputs/ simulation model responses, or more specifically, the evaluation of the uncertainty model. For practical purposes of distribution mapping, the computational cost is considerably lower than that demanded by the Monte Carlo method, which is based on a massive random sampling, thus presenting high computational cost. The application in Biomechanics problems shows the efficiency of the proposed method.