تقرير
Upscaling Uncertainty with Dynamic Discrepancy for a Multi-scale Carbon Capture System
| العنوان: | Upscaling Uncertainty with Dynamic Discrepancy for a Multi-scale Carbon Capture System |
|---|---|
| المؤلفون: | Bhat, K. Sham, Mebane, David S., Storlie, Curtis B., Mahapatra, Priyadarshi |
| سنة النشر: | 2014 |
| المجموعة: | Statistics |
| مصطلحات موضوعية: | Statistics - Methodology |
| الوصف: | Uncertainties from model parameters and model discrepancy from small-scale models impact the accuracy and reliability of predictions of large-scale systems. Inadequate representation of these uncertainties may result in inaccurate and overconfident predictions during scale-up to larger models. Hence multiscale modeling efforts must quantify the effect of the propagation of uncertainties during upscaling. Using a Bayesian approach, we calibrate a small-scale solid sorbent model to Thermogravimetric (TGA) data on a functional profile using chemistry-based priors. Crucial to this effort is the representation of model discrepancy, which uses a Bayesian Smoothing Splines (BSS-ANOVA) framework. We use an intrusive uncertainty quantification (UQ) approach by including the discrepancy function within the chemical rate expressions; resulting in a set of stochastic differential equations. Such an approach allows for easily propagating uncertainty by propagating the joint model parameter and discrepancy posterior into the larger-scale system of rate expressions. The broad UQ framework presented here may have far-reaching impact into virtually all areas of science where multiscale modeling is used. Comment: 27 pages, 13 figures, submitted to the Journal of the American Statistical Association Revision on 12/16/14: corrected 6 figures to enhance readability |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/1411.2578 |
| رقم الأكسشن: | edsarx.1411.2578 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |