Tensor Model for Representing Critical Infrastructure

Critical infrastructure ensures the stability of society, economic growth, and national security. This paper presents a tensor-based model for assessing infrastructure resilience, considering technical, economic, environmental, social, and managerial aspects.The proposed model represents infrastructure subsystems – generation, transportation, and resource consumption–across different operational phases: pre-disaster, crisis, and recovery. Tensor analysis enables a comprehensive evaluation of interactions between system components, multiple threat impacts, and resilience criteria such as functionality, recovery time, threat resistance, adaptability, and economic efficiency.By defining threat vectors for various disruptions, including cyberattacks, natural disasters, and technological failures, the model identifies vulnerabilities and provides insights for strengthening infrastructure resilience. The findings support strategic management, risk mitigation, and policy development in national security and engineering planning.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-10-21
DOI
https://doi.org/10.5281/zenodo.17731649
Primary Topic
Infrastructure Resilience and Vulnerability Analysis
Type
article
Field-Weighted Citation Impact
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article

Tensor Model for Representing Critical Infrastructure

Zenodo (CERN European Organization for Nuclear Research)
Infrastructure Resilience and Vulnerability Analysis
article

Tensor Model for Representing Critical Infrastructure

article en

Abstract

Critical infrastructure ensures the stability of society, economic growth, and national security. This paper presents a tensor-based model for assessing infrastructure resilience, considering technical, economic, environmental, social, and managerial aspects.The proposed model represents infrastructure subsystems – generation, transportation, and resource consumption–across different operational phases: pre-disaster, crisis, and recovery. Tensor analysis enables a comprehensive evaluation of interactions between system components, multiple threat impacts, and resilience criteria such as functionality, recovery time, threat resistance, adaptability, and economic efficiency.By defining threat vectors for various disruptions, including cyberattacks, natural disasters, and technological failures, the model identifies vulnerabilities and provides insights for strengthening infrastructure resilience. The findings support strategic management, risk mitigation, and policy development in national security and engineering planning.

Zenodo (CERN European Organization for Nuclear Research)
National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” (UA), Pukhov Institute for Modelling in Energy Engineering (UA), Donetsk National Technical University (UA)
Industry, innovation and infrastructure
Openalex Percentile: Top 47%
Infrastructure Resilience and Vulnerability Analysis
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