Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/148878
Title: Knowledge graph approach to combustion chemistry and interoperability
Authors: Farazi, Feroz
Salamanca, Maurin
Mosbach, Sebastian
Akroyd, Jethro
Eibeck, Andreas
Aditya, Leonardus Kevin
Chadzynski, Arkadiusz
Pan, Kang
Zhou, Xiaochi
Zhang, Shaocong
Lim, Mei Qi
Kraft, Markus
Keywords: Engineering::Chemical engineering
Issue Date: 2020
Source: Farazi, F., Salamanca, M., Mosbach, S., Akroyd, J., Eibeck, A., Aditya, L. K., Chadzynski, A., Pan, K., Zhou, X., Zhang, S., Lim, M. Q. & Kraft, M. (2020). Knowledge graph approach to combustion chemistry and interoperability. ACS Omega, 5(29), 18342-18348. https://dx.doi.org/10.1021/acsomega.0c02055
Journal: ACS Omega
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.
URI: https://hdl.handle.net/10356/148878
ISSN: 2470-1343
DOI: 10.1021/acsomega.0c02055
Rights: © 2020 American Chemical Society. This is an open access article published under a Creative Commons Attribution (CC-BY) License, which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCBE Journal Articles

Files in This Item:
File Description SizeFormat 
acsomega.0c02055.pdf6.27 MBAdobe PDFView/Open

SCOPUSTM   
Citations 20

17
Updated on Dec 3, 2022

Web of ScienceTM
Citations 20

13
Updated on Dec 8, 2022

Page view(s)

169
Updated on Dec 9, 2022

Download(s) 50

32
Updated on Dec 9, 2022

Google ScholarTM

Check

Altmetric


Plumx

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.