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What Entitles Us to Make Predictions?

Thursday, March 22, 2012
3:30PM – 5PM
POB 6.304

Robert Moser, Gabriel Terejanu & Todd Oliver

Niels Bohr once said "Prediction is very difficult, especially about
the future." His comment is relevant to computational science and the
use of computational models in decisions about physical systems. In
computational science and engineering, the predictions we need to make
are generally for quantities for which there are no data under the
conditions of the prediction, since otherwise no predictions would be
needed. Fundamentally, then, the predictions we are interested in are
extrapolations from available information. At the Center for
Predictive Engineering and Computational Sciences (PECOS), we are
developing a conceptual context in which to assess such
predictions. It involves four distinct processes: uncertainty
modeling, model calibration, validation and predictive assessment. As
we apply them, these processes rely on several ingredients, including:
model inadequacy modeling, Bayesian inference, Bayesian model
selection, sensitivity analysis and prior knowledge regarding the
reliability and domain of applicability of the physics models
involved. This approach will be discussed, and as examples, the ideas
will be applied to several physics modeling problems being pursued at
PECOS.

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