Process informatics tools for predictive modeling: Hydrogen combustion

Abstract

Predictive modeling of chemical reaction systems is facilitated through development of an automated data‐centric infrastructure, Process Informatics Model (PrIMe). Modeling and analysis tools were built to bridge the PrIMe Data infrastructure with DataCollaboration, a framework designed to make inferences from experimental observations in the context of an underlying model. The developed tools were integrated with the PrIMe Workflow Application, allowing users to create and run drag‐and‐drop applications on the fly. Organizing the data, linking the data to scientific methods, and automating the analysis offer new venues of scientific inquiry, such as evaluating the consistency of heterogeneous data records, making uncertainty‐quantified predictions, quantifying the contribution of newly obtained or even hypothetical data to the question of interest, or testing similar “what–if” scenarios. The developed system is demonstrated for the chemical kinetics of hydrogen combustion. © 2011 Wiley Periodicals, Inc. Int J Chem Kinet 44: 101–116, 2012

Document Details

Document Type
Pub Defense Publication
Publication Date
Dec 04, 2011
Source ID
10.1002/kin.20627

Entities

People

  • Andrew Packard
  • Michael Frenklach
  • Xiaoqing You

Organizations

  • Air Force Office of Scientific Research
  • National Science Foundation
  • Office of Science

Tags

Readers

  • Combustion science or combustion engineering.
  • Computational Modeling and Simulation
  • Database Systems and Applications

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference