Resilience Engineering

Problem:

In socio-physical systems, such as urban environments where social behaviors and physical infrastructures are intertwined, interdependencies and uncertainties present significant challenges. The interconnectedness of these systems means that a disruption in one component can cascade, affecting others in unforeseen ways. For example, damage to a power grid can impair transportation networks, which in turn can hinder emergency response efforts, amplifying the overall impact of a disaster.

Uncertainty arises from the complex interactions within these systems and the unpredictable nature of external hazards. Factors such as human behavior, technological failures, and natural disasters contribute to this unpredictability, making it challenging to anticipate and mitigate potential failures. Traditional risk assessment methods may not fully capture these complexities, leading to an underestimation of potential risks.

Given these challenges, there is a critical need for resilience engineering—a field focused on designing systems that can adapt to and recover from disruptions. Resilience engineering emphasizes the importance of flexibility, redundancy, and the capacity to absorb shocks, ensuring that socio-physical systems can maintain functionality or recover swiftly after adverse events. By incorporating resilience principles, engineers and planners can develop infrastructures and communities that are better equipped to handle uncertainties and interdependencies, thereby enhancing overall societal resilience.

Experts:

Maria Nogal, Erica Arango

Publications:

Huang, Y., Qin, G., Yang, M., & Nogal, M. (2025). Dynamic quantitative assessment of service resilience for long-distance energy pipelines under corrosion. Reliability Engineering & System Safety, 256, 110792. DOI: https://doi.org/10.1016/j.ress.2024.110792
Arango, E., Nogal, M., Yang, M., Sousa, H.S., Stewart, M.G., and Matos, J.C. (2023). Dynamic thresholds for the resilience assessment of road traffic networks to wildfires. Reliability Engineering & System Safety, vol. 238, October 2023, 109407. DOI: https://doi.org/10.1016/j.ress.2023.109407.
Teixeira, R., Martinez-Pastor, B., Nogal, M., & O’Connor, A. (2022). Metamodel-based metaheuristics in optimal responsive adaptation and recovery of traffic networks. Sustainable and Resilient Infrastructure, 7(6), 756-774. DOI: https://doi.org/10.1080/23789689.2022.2029325.
Teixeira, R., Martinez-Pastor, B., Nogal, M., Micu, A., & O'Connor, A. (2022). The role of multi-fidelity modelling in adaptation and recovery of engineering systems. In Vol. 36 (2022): International Probabilistic Workshop 2022. Czech Technical University in Prague. [Download]
Martinez-Pastor, B., Nogal, M., O’Connor, A., & Teixeira, R. (2022). Identifying critical and vulnerable links: A new approach using the Fisher information matrix. International Journal of Critical Infrastructure Protection, 39, 100570. DOI: https://doi.org/10.1016/j.ijcip.2022.100570.
Martinez-Pastor, B., Nogal, M., O'Connor, A., & Teixeira, R. (2021). Transport network resilience: a mapping and sensitivity analysis strategy to improve the decision-making process during extreme weather events. International Journal of Critical Infrastructures, 17(4), 330-352. DOI: https://doi.org/10.1504/IJCIS.2021.120165.
Kammouh, O., Nogal, M., Cimellaro, G. P., & Wolfert, A. R. M. (2020). Resilience quantification of large-scale water distribution networks: A probabilistic approach. In 30th European Safety and Reliability Conference, ESREL 2020 and 15th Probabilistic Safety Assessment and Management Conference, PSAM15 2020 (pp. 1183-1190). Research Publishing, Singapore. [Download]
Nogal, M., Nápoles, O. M., & O’Connor, A. (2019). Structured expert judgement to understand the intrinsic vulnerability of traffic networks. Transportation Research Part A: Policy and Practice, 127, 136-152. DOI: https://doi.org/10.1016/j.tra.2019.07.006
Nogal, M., & Honfi, D. (2019). Assessment of road traffic resilience assuming stochastic user behaviour. Reliability Engineering & System Safety, 185, 72-83. DOI: https://doi.org/10.1016/j.ress.2018.12.013.
Nogal, M., & Honfi, D. (2019). Resilience Assessment of the Traffic Network Luxembourg-Metz. The Power of Information. In 29th European Safety and Reliability Conference, ESREL 2019, 22 September 2019 through 26 September 2019 (pp. 1389-1395). Research Publishing Services. [Download]
Nogal, M., Honfi, D., & O'Connor, A. (2019). Resilience of road transport systems considering the stochastic response of travellers. In 13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP13 Seoul, South Korea, May 26-30, 2019. [Download]
Nogal, M., & O’Connor, A. (2018). Resilience assessment of transportation networks. In Routledge handbook of sustainable and resilient infrastructure (pp. 199-215). Routledge. [Download]
Nogal, M., O’Connor, A., Martinez-Pastor, B., & Caulfield, B. (2017). Novel probabilistic resilience assessment framework of transportation networks against extreme weather events. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 3(3), 04017004. DOI: https://doi.org/10.1061/AJRUA6.0000908
Nogal, M., & O’Connor, A. (2017). Cyber-transportation resilience. Context and methodological framework. In Resilience and Risk: Methods and Application in Environment, Cyber and Social Domains (pp. 415-426). Dordrecht: Springer Netherlands. [Download]
Roege, P. E., Collier, Z. A., Chevardin, V., Chouinard, P., Florin, M. V., Lambert, J. H., ... & Todorovic, B. (2017). Bridging the gap from cyber security to resilience. In Resilience and Risk: Methods and Application in Environment, Cyber and Social Domains (pp. 383-414). Springer Netherlands. [Download]
Nogal, M., O'Connor, A., Caulfield, B., & Martinez-Pastor, B. (2016). Resilience of traffic networks: From perturbation to recovery via a dynamic restricted equilibrium model. Reliability Engineering & System Safety, 156, 84-96. DOI: https://doi.org/10.1016/j.ress.2016.07.020

Projects:

FOURIER

InnOvative ArtiFicial IntelligencE methodologIes for monitoRing and maintaining large-scale complex infrastrUctures and obtaining greener, more Resilient and smart societies (HORIZON-MSCA-2022).

Resilient Hydro Twin

Participatory Integrated Digital Twin for Adaptive Urban Resilience to Water Extremities (NWO Merian Fund Water Disaster Management 2024).