Dynamic resilience

accounting the life-cycle conditions

Resilience models tend to remain static, lacking the agility to evolve as the systems–and our knowledge–do. Such limitation demands developing methods that are aware and able to capture the changes in the system’s conditions. To tackle the lack of model flexibility, I have implemented multi-scale modeling approaches supported by recursive Bayesian dynamic estimation methods with initial application to road networks (see Figure 1).

Figure 1. Smart resilience modeling to capture dynamic, uncertain, and evolving lifecycle conditions.

By introducing sequential information, estimates at different time scales and spatial locations have reflected a more reliable estimation (i.e., a reduced bias) of the statistics of interest, such as system failure probability and community functionality. In this line of work, measuring and updating resilience inferences has demonstrated a great benefit from leveraging the observed fluctuation in the system conditions as new data, knowledge, and models emerge. Results from this work are expected to allow timeliness and higher confidence in the computed resilience estimates for pre- and post-disaster events’ decision-making across the multiple temporal and spatial scales (see Figure 2).

Figure 2. Illustrative example of fusing observations across scales: component-level (left), structural-level (center), and even network scale (right).

  • Padgett JE, Rincon R, Panakkal P. (2024). “Future Cities Demand Smart and Equitable Infrastructure Resilience Modeling Perspectives.” Npj Natural Hazards, In Review, April 2024

  • Makhoul N, Roohi M, van de Lindt JW, Sousa H, Santos LO, Argyroudis S, Barbosa A, Derras B, Gardoni P, Lee JS, Mitoulis S, Moffett B, Navarro C, Padgett JE, Rincon R, Schmidt F, Shaban N, Stefanidou S, Tubaldi E, Xenidis Y, Zmigrodzki S. (2024) “Seismic resilience modelling of an interdependent built environment for integrating SHM and emerging technologies in decision-making” Structural Engineering International, 34:1,19-33, DOI:10.1080/10168664.2023.2295901.

  • Rincon R, Padgett JE. (2023). “Smart resilience: capturing dynamic, uncertain and evolving lifecycle conditions.” 8th International Symposium on Life-Cycle Civil Engineering (IALCCE 2023), Milan, Italy, July 2-6, 2023. In F. Biondini & D.M. Frangopol, Life-Cycle of Structures and Infrastructure Systems (1st ed., pp. 341–348). CRC Press. https://doi.org/10.1201/9781003323020-39.