Knowledge Graph Approach to Combustion Chemistry and Interoperability

Abstract

In this paper, we demonstrate through examples how the concept of a Semantic Web based knowledge graph can be used to integrate combustion modeling into cross-disciplinary applications and in particular how inconsistency issues in chemical mechanisms can be addressed. We discuss the advantages of linked data that form the essence of a knowledge graph and how we implement this in a number of interconnected ontologies, specifically in the context of combustion chemistry. Central to this is OntoKin, an ontology we have developed for capturing both the content and the semantics of chemical kinetic reaction mechanisms. OntoKin is used to represent the example mechanisms from the literature in a knowledge graph, which itself is part of the existing, more general knowledge graph and ecosystem of autonomous software agents that are acting on it. We describe a web interface, which allows users to interact with the system, upload and compare the existing mechanisms, and query species and reactions across the knowledge graph. The utility of the knowledge-graph approach is demonstrated for two use-cases: querying across multiple mechanisms from the literature and modeling the atmospheric dispersion of pollutants emitted by ships. As part of the query use-case, our ontological tools are applied to identify variations in the rate of a hydrogen abstraction reaction from methane as represented by 10 different mechanisms.

Automated Calibration of a Poly(oxymethylene) Dimethyl Ether Oxidation Mechanism Using the Knowledge Graph Technology

“…Figure 3 depicts how combustion experiment measurements and chemical mechanisms may be connected. The task of linking species with reactions has already been achieved in previous work, 16 linking OntoKin with OntoSpecies. This allows the linking of OntoChemExp to both species and reactions via provision of unique species identifiers within OntoSpecies.…”

Universal Digital Twin - A Dynamic Knowledge Graph

“…It is able to use computational chemistry data to calculate thermodynamic quantities required by the reaction mechanisms, and link the resulting quantities to the computational chemistry calculations used to derive them (Farazi et al, 2020b). It is able to identify inconsistencies in the data (Farazi et al, 2020c) and interact with high performance computing (HPC) facilities in the real world to perform additional computational chemistry calculations to generate the data required to resolve the problems . It includes experimental data (for combustion experiments) and is able to automate the process of calibrating reaction mechanisms versus experiment data (Bai et al, 2021).…”

“…Figure 4 illustrates how this was achieved. See references (Eibeck et al, 2019;Farazi et al, 2020c) for more details of the implementation and results.…”

“…Virtual sensor agents report the resulting air quality estimates at different locations. Adapted from Farazi et al (2020c).…”

“…The scope of World Avatar project has since broadened considerably. It has demonstrated the use of ontologies to facilitate interoperability between models and data from different technical domains (Devanand et al, 2020;Farazi et al, 2020c), developed an agent discovery and composition service to allow agents to be combined to perform more complex tasks (Zhou et al, 2019), developed a blockchain-based smart contract system to enable an agent marketplace (Zhou et al, 2020a), and demonstrated a parallel world framework for scenario analysis (Eibeck et al, 2020). It also now includes a Cities Knowledge Graph project with researchers at ETH Zurich to improve the planning and design of cities, and a Pharma Innovation Programme Singapore (PIPS) project to allow the World Avatar to control laboratory robots performing chemistry experiments.…”