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A tensor-based formulation of hetero-functional graph theory
Recently, hetero-functional graph theory (HFGT) has developed as a means to mathematically model the structure of large-scale complex flexible engineering systems. It does so by fusing concepts from network science and model-based systems engineering (MBSE). For the former, it utilizes multiple grap...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9637230/ https://www.ncbi.nlm.nih.gov/pubmed/36335143 http://dx.doi.org/10.1038/s41598-022-19333-y |
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author | Farid, Amro M. Thompson, Dakota J. Schoonenberg, Wester |
author_facet | Farid, Amro M. Thompson, Dakota J. Schoonenberg, Wester |
author_sort | Farid, Amro M. |
collection | PubMed |
description | Recently, hetero-functional graph theory (HFGT) has developed as a means to mathematically model the structure of large-scale complex flexible engineering systems. It does so by fusing concepts from network science and model-based systems engineering (MBSE). For the former, it utilizes multiple graph-based data structures to support a matrix-based quantitative analysis. For the latter, HFGT inherits the heterogeneity of conceptual and ontological constructs found in model-based systems engineering including system form, system function, and system concept. These diverse conceptual constructs indicate multi-dimensional rather than two-dimensional relationships. This paper provides the first tensor-based treatment of hetero-functional graph theory. In particular, it addresses the “system concept” and the hetero-functional adjacency matrix from the perspective of tensors and introduces the hetero-functional incidence tensor as a new data structure. The tensor-based formulation described in this work makes a stronger tie between HFGT and its ontological foundations in MBSE. Finally, the tensor-based formulation facilitates several analytical results that provide an understanding of the relationships between HFGT and multi-layer networks. |
format | Online Article Text |
id | pubmed-9637230 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-96372302022-11-07 A tensor-based formulation of hetero-functional graph theory Farid, Amro M. Thompson, Dakota J. Schoonenberg, Wester Sci Rep Article Recently, hetero-functional graph theory (HFGT) has developed as a means to mathematically model the structure of large-scale complex flexible engineering systems. It does so by fusing concepts from network science and model-based systems engineering (MBSE). For the former, it utilizes multiple graph-based data structures to support a matrix-based quantitative analysis. For the latter, HFGT inherits the heterogeneity of conceptual and ontological constructs found in model-based systems engineering including system form, system function, and system concept. These diverse conceptual constructs indicate multi-dimensional rather than two-dimensional relationships. This paper provides the first tensor-based treatment of hetero-functional graph theory. In particular, it addresses the “system concept” and the hetero-functional adjacency matrix from the perspective of tensors and introduces the hetero-functional incidence tensor as a new data structure. The tensor-based formulation described in this work makes a stronger tie between HFGT and its ontological foundations in MBSE. Finally, the tensor-based formulation facilitates several analytical results that provide an understanding of the relationships between HFGT and multi-layer networks. Nature Publishing Group UK 2022-11-05 /pmc/articles/PMC9637230/ /pubmed/36335143 http://dx.doi.org/10.1038/s41598-022-19333-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Farid, Amro M. Thompson, Dakota J. Schoonenberg, Wester A tensor-based formulation of hetero-functional graph theory |
title | A tensor-based formulation of hetero-functional graph theory |
title_full | A tensor-based formulation of hetero-functional graph theory |
title_fullStr | A tensor-based formulation of hetero-functional graph theory |
title_full_unstemmed | A tensor-based formulation of hetero-functional graph theory |
title_short | A tensor-based formulation of hetero-functional graph theory |
title_sort | tensor-based formulation of hetero-functional graph theory |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9637230/ https://www.ncbi.nlm.nih.gov/pubmed/36335143 http://dx.doi.org/10.1038/s41598-022-19333-y |
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