Functional Connectivity Analysis (FCA): An efficient method to model infrastructure functionality

Abstract

Due to the severe aftermath of past disasters, governments globally have acknowledged the importance of critical infrastructure and enacted legislation to protect and improve the functionality of infrastructure vulnerable to natural and anthropogenic hazards (Dong & Frangopol 2016). Efforts to achieve such objectives involve making complex decisions and large investments, which require risk analysis of infrastructure.

An essential element in risk analysis is the time-varying functionality assessment for damaged infrastructure to capture the immediate impact of hazards on infrastructure and the ability of infrastructure to recover (Sharma et al. 2020). Network analysis methods, including topology-based and flow-based methods, are valuable tools for the functionality assessment of infrastructure. They help describe, study and interpret the behavior of infrastructure. Topology-based methods can capture connectivity patterns of network components and draw conclusions on the infrastructure performance (Guidotti et al. 2017). They have relatively low computational costs because they do not model the flow of resources from source facilities to consumers. However, for this reason, topology-based methods cannot provide comprehensive insights into the functional performance of infrastructure, thus, providing partial and possibly misleading responses. Flow-based methods provide accurate functionality assessment of infrastructure because they model the operational dynamics of the flow of resources (Sharma & Gardoni 2022). However, modeling the detailed operating mechanisms of infrastructure makes flow-based methods computationally intensive, especially for studying large complex infrastructure systems.

This paper introduces a novel hybrid approach for accurate functionality assessment of infrastructure with computational efficiency by introducing flow-related characteristics inﾭto topological connectivity metrics. This hybrid approach is helpful for the optimization and probabilistic analysis of infrastructure life cycles. This approach is then illustrated with a real-world example modeling the functionality of a water distribution system in Shelby County, Tennessee, in a post-earthquake scenario.

Keywords: infrastructure; functionality; performance; flow; connectivity metrics; computational efficiency

REFERENCE

Dong, Y., & Frangopol, D. M. (2016). Probabilistic time-dependent multihazard life-cycle assessment and resilience of bridges considering climate change. Journal of Performance of Constructed Facilities, 30(5), 04016034.

Guidotti, R., Gardoni, P., & Chen, Y. (2017). Network reliability analysis with link and nodal weights and auxiliary nodes. Structural Safety, 65, 12-26.

Sharma, N., Tabandeh, A., & Gardoni, P. (2020). Regional resilience analysis: A multiscale approach to optimize the resilience of interdependent infrastructure. Computer?Aided Civil and Infrastructure Engineering, 35(12), 1315-1330.

Sharma, N., & Gardoni, P. (2022). Mathematical modeling of interdependent infrastructure: An object-oriented approach for generalized network-system analysis. Reliability Engineering & System Safety, 217, 108042.