Dynamic Chemical Model for H2/O2 Combustion Developed Through a Community Workflow

TL;DR

This paper presents a collaborative workflow for developing, evaluating, and optimizing elementary-reaction models for H2/O2 combustion, emphasizing community involvement and uncertainty quantification.

Contribution

It introduces a community-based, cyberinfrastructure-supported workflow for systematic model development, validation, and uncertainty analysis in combustion chemistry.

Findings

Optimized H2/O2 combustion model achieved.

Identified key reaction importance in high-pressure flames.

Highlighted inconsistencies in low-temperature shock-tube data.

Abstract

Elementary-reaction models for H2/O2 combustion were evaluated and optimized through a collaborative workflow, establishing accuracy and characterizing uncertainties. Quantitative findings were the optimized model, the importance of $\text{H}_2 + \text{O}_2(1\Delta) = \text{H} + \text{HO}_2$ in high-pressure flames, and the inconsistency of certain low-temperature shock-tube data. The workflow described here is proposed to be even more important because the approach and publicly available cyberinfrastructure allows future community development of evolving improvements. The workflow steps applied here were to develop an initial reaction set using Burke et al. [2012], Burke et al. [2013], Sellevag et al. [2009], and Konnov [2015]; test it for thermodynamic and kinetics consistency and plausibility against other sets in the literature; assign estimated uncertainties where not stated in the sources; select key data targets ("Quantities of Interest" or QOIs) from shock-tube and flame experimental data; perform conventional sensitivity analyses of QOIs with respect to Arrhenius pre-exponential factors; develop surrogate models for the model-predicted QOI values; evaluate model-vs.-data consistency using Bound-to-Bound Data Collaboration; and optimize model parameters within their estimated uncertainty bounds (feasible set). Necessary data and software for such analyses were developed and are publicly available through the PrIMe cyberinfrastructure. This community workflow proved to be a means to reveal inconsistencies, improvements, and uncertainty bounds. Even more significantly, it is a means of revealing which parameters and experimental findings are inconsistent with the larger body of work from the community and, thus, of designing new experiments and parameter calculations.