UNCERTAINTY IN THE DEVELOPMENT AND USE OF EQUATION OF STATE MODELS

Abstract

See, stats, and : https : / / www . researchgate . net / publication / 266524527 Uncertainty Equation Article DOI : 10 . 1615 / Int . J . UncertaintyQuantification . 2012003960 CITATIONS 0 READS 21 5 , including : V . Gregory Sandia 22 SEE Nathan Sandia 17 SEE Kristin University 32 SEE All . The . All - text and , letting . ABSTRACT In this paper we present the results from a series of focus groups on the visualization of uncertainty in Equation - Of - State (EOS) mod - els . The initial goal was to identify the most effective ways to present EOS uncertainty to analysts , code developers , and mate - rial modelers . Four prototype visualizations were developed to pre - sented EOS surfaces in a three - dimensional , thermodynamic space . Focus group participants , primarily from Sandia National Labora - tories , evaluated particular features of the various techniques for different use cases and discussed their individual workflow pro - cesses , experiences with other visualization tools , and the impact of uncertainty to their work . Related to our prototypes , we found the 3D presentations to be helpful for seeing a large amount of in - formation at once and for a big - picture view ; however , participants also desired relatively simple , two - dimensional graphics for better quantitative understanding , and because these plots are part of the existing visual language for material models . In addition to feed - back on the prototypes , several themes and issues emerged that are as compelling as the original goal and will eventually serve as a starting point for further development of visualization and analysis tools . In particular , a distributed workflow centered around material models was identified . Material model stakeholders contribute and extract information at different points in this workflow depending on their role , but encounter various institutional and technical bar - riers which restrict the flow of information . An effective software tool for this community must be cognizant of this workflow and al - leviate the bottlenecks and barriers within it . Uncertainty in EOS models is defined and interpreted differently at the various stages of the workflow . In this context , uncertainty propagation is difficult to reduce to the mathematical problem of estimating the uncertainty of an output from uncertain inputs .