Process integration multiscale approaches

A comprehensive understanding of the electronic, molecular, micro- and meso-scale issues associated with modeling catalytic processes requires a multiscale approach in order to integrate ... 

Non-stationary stochastic process. The noise-free measurements for this illustration are generated as integrated white noise. The variables are contaminated by independent identically distributed Gaussian errors with standard deviations 5, 20, 20, 15, 5. The multiscale Bayesian approach is... 

The integration of federated databases with predictive modeling and simulation tools represents an important opportunity for major advances in the effective use of massive amounts of data. The framework will need to include computational tools, evaluated experimental data, active databases, and knowledge-based software guides for generating chemical and physical property data on demand with quantitative measures of uncertainty. The approach has to provide vahdated, predictive simulation methods for complicated systems with seamless multiscale and multidisciplinary integration to predict properties and to model physical phenomena and processes. The results must be in a form that can be visualized and used by even a nonexpert. 

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