Место издания:Orlando, Florida, USA, Orlando, Florida, США
Первая страница:84
Последняя страница:84
Аннотация:An automated data-centric infrastructure, Process Informatics
Model (PrIMe), was applied for validation and optimization
of a syngas combustion model. The Bound-toBound
Data Collaboration (B2B-DC) module of PrIMe
was employed to discover the limits of parameter modi-
fications based on the systematic uncertainty and consistency
analysis of the model-data system, with experimental
data including shock-tube ignition delay times and laminar
flame speeds. The initial H2/CO reaction model, assembled
from 73 reactions and 17 species, was subjected to
a B2B-DC analysis. For this purpose, a dataset was constructed
that included a total of 167 experimental targets
and 55 active model parameters. Consistency analysis of
the composed dataset revealed disagreement between models
and data. Further analysis suggested that removing
45 experimental targets, 8 of which were self-inconsistent,
would lead to a consistent dataset. This dataset was subjected
to a correlation analysis, which highlights possible
directions for parameter modification and model improvement.
Additionally, several methods of parameter optimization
were applied, some of them unique to the B2B-DC
framework. The optimized models demonstrated improved
agreement with experiment, as compared to the initiallyassembled
model, and their predictions for experiments not
included in the initial dataset (i.e. a blind prediction) were investigated.