Knowledge Graph Approach to Combustion Chemistry and Interoperability
| Autor: | Jethro Akroyd, Leonardus Kevin Aditya, Mei Qi Lim, Kang Pan, Xiaochi Zhou, Feroz Farazi, Arkadiusz Chadzynski, Maurin Salamanca, Markus Kraft, Sebastian Mosbach, Andreas Eibeck, Shaocong Zhang |
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| Přispěvatelé: | Farazi, Feroz [0000-0002-6786-7309], Mosbach, Sebastian [0000-0001-7018-9433], Akroyd, Jethro [0000-0002-2143-8656], Zhou, Xiaochi [0000-0002-4008-9965], Kraft, Markus [0000-0002-4293-8924], Apollo - University of Cambridge Repository, School of Chemical and Biomedical Engineering, Cambridge Centre for Advanced Research and Education in Singapore (CARES) |
| Rok vydání: | 2020 |
| Předmět: |
Theoretical computer science
Computer science General Chemical Engineering Interoperability Chemical engineering [Engineering] Redox Reactions General Chemistry Linked data Ontology (information science) Kinetic Modeling Article 4017 Mechanical Engineering Chemistry Upload Software agent Graph (abstract data type) 4002 Automotive Engineering User interface QD1-999 Semantic Web 40 Engineering |
| Zdroj: | ACS Omega, Vol 5, Iss 29, Pp 18342-18348 (2020) ACS Omega |
| Popis: | 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. National Research Foundation (NRF) Published version This work was partly funded by the National Research Foundation (NRF), Prime Minister’s Office, Singapore, under its Campus for Research Excellence and Technological Enterprise (CREATE) program, and by the European Union Horizon 2020 Research and Innovation Program under grant agreement 646121. Markus Kraft gratefully acknowledges the support of the Alexander von Humboldt foundation. The authors are grateful to EPSRC (grant number: EP/R029369/ 1) and ARCHER for financial and computational support as a part of their funding to the UK Consortium on Turbulent Reacting Flows (www.ukctrf.com) (https://doi.org/10.17863/ CAM.54397). |
| Databáze: | OpenAIRE |
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