Preprint 262 published
Preprint 262, ''Automated calibration of a poly(oxymethylene) dimethyl ether oxidation mechanism using knowledge-graph technology'', has been published!
Abstract
In this paper, we develop a knowledge-graph based framework for the automated calibration of combustion reaction mechanisms and demonstrate its effectiveness on a case study of poly(oxymethylene) dimethyl ether (PODEn, where n=3) oxidation. We develop an ontological representation for combustion experiments, OntoChemExp, that allows for the semantic enrichment of experiments within the J-Park Simulator (JPS, theworldavatar.com), an existing cross-domain knowledge-graph. OntoChemExp is fully capable of supporting experimental results in the Process Informatics Model (PrIMe) database. Following this, a set of software agents are developed to perform experimental results retrieval, sensitivity analysis, and calibration tasks. The sensitivity analysis agent is used for both generic sensitivity analyses and reaction selection for subsequent calibration. The calibration process is performed as a sampling task followed by an optimisation task. The agents are designed for use with generic models but are demonstrated with ignition delay time and laminar flame speed simulations. We find that calibration times are reduced while accuracy is increased compared to manual calibration, achieving fittings 92% more accurate. Further, we demonstrate how this workflow is implemented as an extension of the JPS.