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• W3042315843 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." @default.
• W3042315843 created "2020-07-23" @default.
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• W3042315843 date "2020-07-16" @default.
• W3042315843 modified "2023-09-27" @default.
• W3042315843 title "Knowledge Graph Approach to Combustion Chemistry and Interoperability" @default.
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• W3042315843 doi "https://doi.org/10.1021/acsomega.0c02055" @default.
• W3042315843 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7391961" @default.
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