Manufacturing Data Uncertainties Propagation Method in Burn-Up Problems

Monte Cario uncertainty propagation approaches in ADS burn-up calculations

In activation calculations, there are several approaches to quantify uncertainties: deterministic by means of sensitivity analysis, and stochastic by means of Monte Carlo. Here, two different Monte Carlo approaches for nuclear data uncertainty are presented: the first one is the Total Monte Carlo (TMC). The second one is by means of a Monte Carlo sampling of the covariance information included ...

Data Fitting Problems with Bounded Uncertainties in the Data

Automatic Propagation of Uncertainties

Motivated by problems in metrology, we consider a numerical evaluation program y = f(x) as a model for a measurement process. We use a probability density function to represent the uncertainties in the inputs x and examine some of the consequences of using Automatic Differentiation to propagate these uncertainties to the outputs y. We show how to use a combination of Taylor series propagation a...

Ensemble modeling for data fusion in manufacturing process scale-up

Ensemble modeling for data fusion in manufacturing process scale-up Ran Jin & Xinwei Deng a Grado Department of Industrial and Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA b Department of Statistics, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA E-mail: Accepted author version posted online: 23 Apr 2014.Publ...

Taxonomy and Uncertainties of Cloud Manufacturing

The manufacturing industry is currently undergoing rapid changes because of the rapid growth of advanced technologies in information systems and networks, which allow for collaboration around the world. This combination of the latest information technologies and advanced manufacturing networks has led to the growth of a new manufacturing model known as Cloud Manufacturing. Because Cloud Manufac...