Visit to University of California, Berkeley

Details of the work at University of California, Berkeley (UC Berkeley)

I have started my three-month visiting research program at UC Berkeley, USA, with the support of Brain Korea 21 Global Research Fellowship (Ministry of Education, South Korea). During my stay at UC Berkeley, I collaborate with the host, Prof. Ziqi Wang.

As a first step, we have developed a new advanced sampling-based method for reliability analysis of complex infrastructure networks (Lee et al., 2025). The permanent link via DOI number of the paper is HERE. The full reference information is as follows.

Lee, D., Wang, Z., & Song, J. (2025). Efficient seismic reliability and fragility analysis of lifeline networks using subset simulation. Reliability Engineering & System Safety, 260: 110947.

This paper proposes two informative limit-state functions (LSFs) to reformulate the traditional binary LSF for two-terminal reliability analysis of lifeline networks, thereby making the application of subset simulation (SS) possible. The first LSF quantifies the vulnerability of the most reliable path between the origin and destination nodes, whereas the other utilizes the shortest path. Both LSF reformulations represent the same failure domain as the original binary limit-sate function, while their function values at the safe domain differ. Moreover, a specialized SS is developed to generate network-level fragility curves by connecting intermediate failure events to the earthquake magnitude. As a result, the specialized SS can generate the network fragility curve in a single run. Furthermore, the sampling framework is successfully extended to assess k-terminal or k-out-of-N reliability. The accuracy and efficiency of the proposed framework are tested and demonstrated by numerical examples using the Hamiltonian Monte Carlo-based SS (HMC-SS). The results confirm the accuracy and efficiency of the proposed network LSFs, compared to other simulation-based methods directly applicable to binary LSFs. The first LSF generally has higher accuracy, while the second requires lower computation time.

Samples obtained from the (a) entire domain; (b) first subset; and (c) second subset using RP or SP

(a) Comparison of generated seismic fragility curves of San Jose highway bridge network; and (b) multi-state network fragility curves obtained by specialized HMC-SS.

References

RESS
Efficient seismic reliability and fragility analysis of lifeline networks using subset simulation

Dongkyu Lee, Ziqi Wang^*, and Junho Song^*

Reliability Engineering & System Safety, 2025

Abs DOI Bib HTML

Various simulation-based and analytical methods have been developed to evaluate the seismic fragilities of individual structures. However, the seismic safety and resilience of a community are substantially affected by network reliability, determined not only by component fragilities but also by network topology and commodity/information flows. However, seismic reliability analyses of networks often encounter significant challenges due to complex network topologies, interdependencies among ground motions, and low failure probabilities. This paper proposes to overcome these challenges by a variance-reduction method for network fragility analysis using subset simulation. The binary network limit-state function in the subset simulation is reformulated into more informative piecewise continuous functions. The proposed limit-state functions quantify the proximity of each sample to a potential network failure domain, thereby enabling the construction of specialized intermediate failure events, which can be utilized in subset simulation and other sequential Monte Carlo approaches. Moreover, by identifying an implicit relationship between intermediate failure events and seismic intensity, we propose a technique to obtain the entire network fragility curve with a single execution of specialized subset simulation. Numerical examples demonstrate that the proposed method can effectively evaluate system-level fragility for large-scale networks.
@article{lee2025efficient, author = {Lee, Dongkyu and Wang, Ziqi and Song, Junho}, title = {Efficient seismic reliability and fragility analysis of lifeline networks using subset simulation}, journal = {Reliability Engineering \& System Safety}, volume = {260}, pages = {110947}, keywords = {fragility, lifeline networks, network reliability, seismic reliability, subset simulation}, doi = {10.1016/j.ress.2025.110947}, year = {2025}, publisher = {Elsevier}, dimensions = {true}, }

Details of the work at University of California, Berkeley (UC Berkeley)

References

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