In this paper, we evaluate the robustness and recovery of connected critical infrastructures (CIs) under a system-of-systems (SoS) framework taking into account: (1) the dependencies among the components of an individual CI and the interdependencies among different CIs; (2) the variability in component performance, by a multistate model; and (3) the epistemic uncertainty in the probabilities of transitions between different components states and in the mean values of the holding-times distributions, by means of intervals. We adopt the goal tree success tree–dynamic master logic diagram (GTST–DMLD) for system modeling and perform the quantitative assessment by Monte Carlo simulation. We illustrate the approach by way of a simplified case study consisting of two interdependent infrastructures (electric power system and gas network) and a supervisory control and data acquisition (SCADA) system connected to the gas network.
Skip Nav Destination
Article navigation
September 2015
Research Papers
Analysis of the Robustness and Recovery of Critical Infrastructures by Goal Tree–Success Tree: Dynamic Master Logic Diagram, Within a Multistate System-of-Systems Framework, in the Presence of Epistemic Uncertainty
E. Ferrario,
E. Ferrario
Chair on Systems Science and the Energetic Challenge,
European Foundation for New Energy, Electricité de France, École Centrale Paris–Supelec
, Grande Voie des Vignes, 92295 Chatenay Malabry
, France
e-mail: elisa.ferrario@ecp.fr
Search for other works by this author on:
N. Pedroni,
N. Pedroni
Chair on Systems Science and the Energetic Challenge,
European Foundation for New Energy, Electricité de France, École Centrale Paris–Supelec
, Grande Voie des Vignes, 92295 Chatenay Malabry
, France
e-mails: nicola.pedroni@ecp.fr, nicola.pedroni@supelec.fr
Search for other works by this author on:
E. Zio
E. Zio
Chair on Systems Science and the Energetic Challenge,
European Foundation for New Energy, Electricité de France, École Centrale Paris–Supelec
, Grande Voie des Vignes, 92295 Chatenay Malabry
, France
; Politecnico di Milano
, 20133 Milano
, Italy
e-mails: enrico.zio@ecp.fr, enrico.zio@supelec.fr, enrico.zio@polimi.it
Search for other works by this author on:
E. Ferrario
Chair on Systems Science and the Energetic Challenge,
European Foundation for New Energy, Electricité de France, École Centrale Paris–Supelec
, Grande Voie des Vignes, 92295 Chatenay Malabry
, France
e-mail: elisa.ferrario@ecp.fr
N. Pedroni
Chair on Systems Science and the Energetic Challenge,
European Foundation for New Energy, Electricité de France, École Centrale Paris–Supelec
, Grande Voie des Vignes, 92295 Chatenay Malabry
, France
e-mails: nicola.pedroni@ecp.fr, nicola.pedroni@supelec.fr
E. Zio
Chair on Systems Science and the Energetic Challenge,
European Foundation for New Energy, Electricité de France, École Centrale Paris–Supelec
, Grande Voie des Vignes, 92295 Chatenay Malabry
, France
; Politecnico di Milano
, 20133 Milano
, Italy
e-mails: enrico.zio@ecp.fr, enrico.zio@supelec.fr, enrico.zio@polimi.itManuscript received July 29, 2014; final manuscript received January 14, 2015; published online July 1, 2015. Assoc. Editor: Alba Sofi.
ASME J. Risk Uncertainty Part B. Sep 2015, 1(3): 031001 (14 pages)
Published Online: July 1, 2015
Article history
Received:
July 29, 2014
Revision Received:
January 14, 2015
Accepted:
April 27, 2015
Online:
July 1, 2015
Citation
Ferrario, E., Pedroni, N., and Zio, E. (July 1, 2015). "Analysis of the Robustness and Recovery of Critical Infrastructures by Goal Tree–Success Tree: Dynamic Master Logic Diagram, Within a Multistate System-of-Systems Framework, in the Presence of Epistemic Uncertainty." ASME. ASME J. Risk Uncertainty Part B. September 2015; 1(3): 031001. https://doi.org/10.1115/1.4030439
Download citation file:
Get Email Alerts
Cited By
A FMEA Optimization Method Based on TODIM and Best Worst Method-Water Filling Theory in Pythagorean Fuzzy Language Environment for Reliability Assessment of Industrial Robot
ASME J. Risk Uncertainty Part B (June 2025)
A Data Driven Black Box Approach for the Inverse Quantification of Set-Theoretical Uncertainty
ASME J. Risk Uncertainty Part B (September 2025)
Uncertainty Quantification in the Prediction of Remaining Useful Life Considering Multiple Failure Modes
ASME J. Risk Uncertainty Part B (September 2025)
Daily Engine Performance Trending using Common Flight Regime Identification
ASME J. Risk Uncertainty Part B
Related Articles
Uncertainty of Integral System Safety in Engineering
ASME J. Risk Uncertainty Part B (June,2022)
Seismic Reliability Assessment of a Concrete Water Tank Based on the
Bayesian Updating of the Finite Element Model
ASME J. Risk Uncertainty Part B (June,2017)
Special Issue on Uncertainty Quantification in Multiscale System Design and Simulation
ASME J. Risk Uncertainty Part B (March,2018)
Risk Assessment of Decommissioning Options Using Bayesian Networks
J. Offshore Mech. Arct. Eng (November,2002)
Articles from Part A: Civil Engineering
Risk Assessment for Stream Modification Projects in Urban Settings
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering (June,2015)
Data-Driven Development of Three-Dimensional Subsurface Models from Sparse Measurements Using Bayesian Compressive Sampling: A Benchmarking Study
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering (June,2023)
Uncertainty Quantification of Power Spectrum and Spectral Moments Estimates Subject to Missing Data
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering (December,2017)
Framework for Post-Earthquake Risk Assessment and Decision Making for Infrastructure Systems
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering (March,2015)
Related Proceedings Papers
Related Chapters
Constrained Noninformative Priors with Uncertain Constraints: A Hierarchical Simulation Approach (PSAM-0437)
Proceedings of the Eighth International Conference on Probabilistic Safety Assessment & Management (PSAM)
QRAS Approach to Phased Mission Analysis (PSAM-0444)
Proceedings of the Eighth International Conference on Probabilistic Safety Assessment & Management (PSAM)
Advances in the Stochastic Modeling of Constitutive Laws at Small and Finite Strains
Advances in Computers and Information in Engineering Research, Volume 2