English

A Tensor-Based Formulation of Hetero-functional Graph Theory

Artificial Intelligence 2022-10-14 v2

Abstract

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.

Keywords

Cite

@article{arxiv.2101.07220,
  title  = {A Tensor-Based Formulation of Hetero-functional Graph Theory},
  author = {Amro M. Farid and Dakota Thompson and Wester Schoonenberg},
  journal= {arXiv preprint arXiv:2101.07220},
  year   = {2022}
}
R2 v1 2026-06-23T22:17:09.949Z