E. Henley and H. Kumamoto, Probabilistic risk assessment, 1992.

S. Epstein and A. Rauzy, Can we trust PRA? Reliability Engineering & System Safety, pp.195-205, 2005.

M. Cepin, Analysis of truncation limit in probabilistic safety assessment, Reliability Engineering & System Safety, vol.87, issue.3, pp.395-403, 2005.
DOI : 10.1016/j.ress.2004.06.009

D. Lindley and N. Singpurwalla, Reliability (and Fault Tree) Analysis Using Expert Opinions, Journal of the American Statistical Association, vol.68, issue.3, pp.87-90, 1986.
DOI : 10.1080/01621459.1986.10478241

G. Apostolakis, The concept of probability in safety assessments of technological systems, Science, vol.250, issue.4986, pp.1359-1364, 1990.
DOI : 10.1126/science.2255906

T. Aven, Foundations of Risk Analysis: A Knowledge and Decision-Oriented Perspective, 2003.

J. Helton and W. Oberkampf, Alternative representations of epistemic uncertainty, Reliability Engineering & System Safety, vol.85, issue.1-3, pp.1-10, 2004.
DOI : 10.1016/j.ress.2004.03.001

P. Limbourg and E. De-rocquigny, Uncertainty analysis using evidence theory ? confronting level-1 and level-2 approaches with data availability and computational constraints, Reliability Engineering and System Safety, pp.550-564, 2010.

G. Apostolakis and S. Kaplan, Pitfalls in risk calculations, Reliability Engineering, vol.2, issue.2, pp.135-145, 1981.
DOI : 10.1016/0143-8174(81)90019-6

D. Huang, T. Chen, and M. Wang, A fuzzy set approach for event tree analysis. Fuzzy Sets and Systems, pp.153-165, 2001.

T. Aven, On the Need for Restricting the Probabilistic Analysis in Risk Assessments to Variability, Risk Analysis, vol.14, issue.3, pp.354-360, 2010.
DOI : 10.1111/j.1539-6924.2009.01314.x

T. Aven, Interpretations of alternative uncertainty representations in a reliability and risk analysis context. Reliability Engineering & System Safety, pp.353-360, 2011.

T. Aven and R. Steen, The concept of ignorance in a risk assessment and risk management context. Reliability Engineering and System Safety, pp.1117-1122, 2010.

T. Aven and E. Zio, Some considerations on the treatment of uncertainties in risk assessment for practical decision making, Reliability Engineering & System Safety, vol.96, issue.1, pp.64-74, 2010.
DOI : 10.1016/j.ress.2010.06.001

S. Ferson, L. Ginzburg, and R. Akcakaya, Whereof one cannot speak: when input distributions are unknown, Risk Analysis, 1996.

G. Klir and B. Yuan, Fuzzy Sets and Fuzzy Logic: Theory and Applications, 1995.

H. Tanaka, L. Fan, and F. Lai, Fault-Tree Analysis by Fuzzy Probability, IEEE Transactions on Reliability, vol.32, issue.5, pp.453-457, 1983.
DOI : 10.1109/TR.1983.5221727

G. Liang and M. Wang, Fuzzy fault tree analysis using failure possibility. Microelectronics Reliability, pp.583-597, 1993.
DOI : 10.1016/0026-2714(93)90326-t

H. Huang, X. Tong, and M. Zuo, Posbist fault tree analysis of coherent systems, Reliability Engineering & System Safety, vol.84, issue.2, pp.153-169, 2004.
DOI : 10.1016/j.ress.2003.11.002

D. Yuhua and Y. Datao, Estimation of failure probability of oil and gas transmission pipelines by fuzzy fault tree analysis, Journal of Loss Prevention in the Process Industries, vol.18, issue.2, pp.83-88, 2005.
DOI : 10.1016/j.jlp.2004.12.003

R. Ferdous, F. Khan, B. Veitch, and A. P. , Methodology for computer aided fuzzy fault tree analysis. Process safety and environmental protection, pp.217-226, 2009.

K. Misra and G. Weber, A new method for fuzzy fault tree analysis. Microelectronics Reliability, pp.195-216, 1989.

K. Soman and K. Misra, Fuzzy fault tree analysis using resolution identity and extension principle, International Journal of Fuzzy Mathematics, vol.1, pp.193-212, 1993.

P. Suresh, A. Babar, V. Raj, and V. , Uncertainty in fault tree analysis: A fuzzy approach. Fuzzy Sets and Systems, pp.135-141, 1996.

C. Baudrit and D. Dubois, Practical representations of incomplete probabilistic knowledge, Computational Statistics & Data Analysis, vol.51, issue.1, pp.86-108, 2006.
DOI : 10.1016/j.csda.2006.02.009

C. Baudrit, D. Dubois, and D. Guyonnet, Joint Propagation and Exploitation of Probabilistic and Possibilistic Information in Risk Assessment, IEEE Transactions on Fuzzy Systems, vol.14, issue.5, pp.593-608, 2006.
DOI : 10.1109/TFUZZ.2006.876720

C. Baudrit, D. Dubois, and N. Perrot, Representing parametric probabilistic models tainted with imprecision. Fuzzy Sets and System, pp.1913-1928, 2008.

D. Dubois, Possibility theory and statistical reasoning, Computational Statistics & Data Analysis, vol.51, issue.1, pp.47-69, 2006.
DOI : 10.1016/j.csda.2006.04.015
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.324.6983

D. Dubois and H. Prade, Possibility Theory: An Approach to Computerized Processing of Uncertainty, 1988.

P. Baraldi and E. Zio, A Combined Monte Carlo and Possibilistic Approach to Uncertainty Propagation in Event Tree Analysis, Risk Analysis, vol.8, issue.4, pp.1309-1326, 2008.
DOI : 10.1111/j.1539-6924.2008.01085.x

R. Flage, P. Baraldi, F. Ameruso, E. Zio, T. Aven et al., Handling epistemic uncertainties in fault tree analysis by probabilistic and possibilistic approaches, Risk and Safety: Theory and Applications. Supplement Proceedings of the European Safety and Reliability Conference, pp.1761-1768, 2009.

R. Flage, P. Baraldi, E. Zio, and T. Aven, Possibility-probability transformation in comparing different approaches to the treatment of epistemic uncertainties in a fault tree analysis

P. Limbourg, R. Savic, J. Petersen, and H. Kochs, Fault tree analysis in an early design stage using the Dempster-Shafer theory of evidence, Risk, Reliability and Societal Safety -Proceedings of the European Safety and Reliability (ESREL) 2007 Conference, pp.713-722, 2007.

P. Limbourg, R. Savi6, J. Petersen, and H. Kochs, Modelling uncertainty in fault tree analyses using evidence theory, Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, vol.222, issue.3, pp.291-301, 2008.
DOI : 10.1243/1748006XJRR142

S. Ferson, V. Kreinovich, L. Ginzburg, K. Sentz, and D. Myers, Constructing probability boxes and Dempster-Shafer structures. Sandia National Laboratories, 2003.

S. Ferson, R. Nelsen, J. Hajagos, D. Berleant, J. Zhang et al., Dependence in probabilistic modeling, Dempster-Shafer theory, and probability bounds analysis, 2004.

J. Helton, J. Johnson, W. Oberkampf, and C. Storlie, A sampling-based computational strategy for the representation of epistemic uncertainty in model predictions with evidence theory, Computer Methods in Applied Mechanics and Engineering, vol.196, issue.37-40, pp.3980-3998, 2007.
DOI : 10.1016/j.cma.2006.10.049

J. Helton, J. Johnson, W. Oberkampf, and C. Sallaberry, Representation of Analysis Results Involving Aleatory and Epistemic Uncertainty. Sandia National Laboratories, 2008.

K. Sentz and S. Ferson, Combination of Evidence in Dempster-Shafer Theory. Sandia National Laboratories, 2002.

G. Shafer, A Mathematical Theory of Evidence, 1976.

S. Ferson and J. Hajagos, Arithmetic with uncertain numbers: rigorous and (often) best possible answers, Reliability Engineering & System Safety, vol.85, issue.1-3, pp.135-152, 2004.
DOI : 10.1016/j.ress.2004.03.008

S. Ferson and W. Tucker, Sensitivity in risk analyses with uncertain numbers, 2006.

S. Ferson, V. Kreinovich, J. Hajagos, W. Oberkampf, and L. Ginzburg, Experimental Uncertainty Estimation and Statistics for Data Having Interval Uncertainty, 2007.

S. Ferson, P. Van-den-brink, T. Estes, K. Gallagher, O. Connor et al., Bounding uncertainty analyses Application of uncertainty analysis to ecological risks of pesticides, 2010.

R. Moore, Methods and Applications of Interval Analysis, 1979.
DOI : 10.1137/1.9781611970906

E. Zio, Computational Methods for Reliability and Risk Analysis, 2009.
DOI : 10.1142/7190

D. Watts, A simple model of global cascades on random networks, Proceedings of the National Academy of Sciences, vol.99, issue.9, p.5766, 2002.
DOI : 10.1073/pnas.082090499

R. Guimerà, A. Arenas, A. Dìaz-guilera, and F. Giralt, Dynamical properties of model communication networks, Physical Review E, vol.66, issue.2, p.26704, 2002.
DOI : 10.1103/PhysRevE.66.026704

G. Sansavini, M. Hajj, I. Puri, and E. Zio, A deterministic representation of cascade spreading in complex networks, EPL (Europhysics Letters), vol.87, issue.4, 2009.
DOI : 10.1209/0295-5075/87/48004

E. Zio and G. Sansavini, Modeling Interdependent Network Systems for Identifying Cascade-Safe Operating Margins, IEEE Transactions on Reliability, vol.60, issue.1, pp.94-101, 2011.
DOI : 10.1109/TR.2010.2104211
URL : https://hal.archives-ouvertes.fr/hal-00609638

E. Zio and G. Sansavini, Component Criticality in Failure Cascade Processes of Network Systems, Risk Analysis, vol.70, issue.6, pp.1196-1210, 2011.
DOI : 10.1111/j.1539-6924.2011.01584.x
URL : https://hal.archives-ouvertes.fr/hal-00658543

M. Fréchet, Généralisations du théorème des probabilités totales, Fundamenta Mathematica, vol.25, pp.379-387, 1935.

M. Frank, R. Nelsen, and B. Schweizer, Best-possible bounds for the distribution of a sum-a problem of Kolmogorov. Probability Theory and Related Fields, pp.199-211, 1987.

R. Sadiq, E. Saint-martin, and Y. Kleiner, Predicting risk of water quality failures in distribution networks under uncertainties using fault-tree analysis, Urban Water Journal, vol.53, issue.4, pp.287-304, 2008.
DOI : 10.1109/91.493904

D. Berleant and C. Goodman-strauss, Bounding the results of arithmetic operations on random variables of unknown dependency using intervals, Reliable Computing, vol.4, issue.2, pp.147-165, 1998.
DOI : 10.1023/A:1009933109326

D. Berleant and J. Zhang, Representation and problem solving with Distribution Envelope Determination (DEnv) Reliability Engineering and System Safety, pp.153-168, 2004.

D. Berleant and J. Zhang, Using Pearson Correlation to Improve Envelopes around the Distributions of Functions, Reliable Computing, vol.10, issue.2, pp.139-161, 2004.
DOI : 10.1023/B:REOM.0000015850.27690.3b

D. Berleant, L. Xie, and J. Zhang, Statool: a tool for distribution envelope determination (DEnv), an interval-based algorithm for arithmetic on random variables, Reliable Computing, vol.9, issue.2, pp.91-108, 2003.
DOI : 10.1023/A:1023082100128

D. Berleant, G. Anderson, and C. Goodman-strauss, Arithmetic on Bounded Families of Distributions: A DEnv Algorithm Tutorial Knowledge Processing with Interval and Soft Computing, pp.183-210, 2008.

J. Vaurio, Treatment of general dependencies in system fault-tree and risk analysis, IEEE Transactions on Reliability, vol.51, issue.3, pp.278-287, 2002.
DOI : 10.1109/TR.2002.801848

J. Vaurio, Consistent mapping of common cause failure rates and alpha factors. Reliability Engineering and System Safety, pp.628-645, 2007.

D. Karanki and V. Dang, Quantification of uncertainty in fault tree analysis with correlated basic events, pp.1619-1628

H. Li, Hierarchical Risk Assessment of Water Supply Systems, 2007.

R. Ferdous, F. Khan, R. Sadiq, P. Amyotte, and B. Veitch, Fault and Event Tree Analyses for Process Systems Risk Analysis: Uncertainty Handling Formulations, Risk Analysis, vol.18, issue.1, pp.86-107, 2011.
DOI : 10.1111/j.1539-6924.2010.01475.x

Q. Zhang, A general method dealing with correlations in uncertainty propagation in fault trees, Reliability Engineering & System Safety, vol.26, issue.3, pp.231-247, 1989.
DOI : 10.1016/0951-8320(89)90013-6

Q. Zhang, A method dealing with correlations in uncertainty propagation by using traditional correlation coefficients, Reliability Engineering & System Safety, vol.41, issue.2, pp.107-114, 1993.
DOI : 10.1016/0951-8320(93)90023-R

A. Rushdi and K. Kafrawy, Uncertainty propagation in fault-tree analyses using an exact method of moments, Microelectronics Reliability, vol.28, issue.6, pp.945-965, 1988.
DOI : 10.1016/0026-2714(88)90295-8

K. Kafrawy and A. Rushdi, Uncertainty analysis of fault trees with statistically correlated failure data, Microelectronics Reliability, vol.30, issue.1, pp.157-175, 1990.
DOI : 10.1016/0026-2714(90)90021-E

D. Karanki, P. Jadhav, A. Chandrakar, A. Srividya, and A. Verma, Uncertainty analysis in PSA with correlated input parameters, International Journal of Systems Assurance Engineering and Management, vol.112, issue.1, pp.66-71, 2010.
DOI : 10.1007/s13198-010-0012-y

B. Huang and X. Du, A robust design method using variable transformation and Gauss???Hermite integration, International Journal for Numerical Methods in Engineering, vol.1, issue.12, pp.1841-1858, 2006.
DOI : 10.1002/nme.1577

M. Kalos and P. Whitlock, Monte Carlo methods. Volume I: Basics, 1986.

M. Marseguerra and E. Zio, Basics of the Monte Carlo Method with Application to System Reliability, 2002.

D. Karanki, H. Kushwaha, A. Verma, and S. Ajit, Uncertainty Analysis Based on Probability Bounds (P-Box) Approach in Probabilistic Safety Assessment, Risk Analysis, vol.2, issue.10, pp.662-675, 2009.
DOI : 10.1111/j.1539-6924.2009.01221.x

H. Regan, S. Ferson, and D. Berleant, Equivalence of methods for uncertainty propagation of real-valued random variables, International Journal of Approximate Reasoning, vol.36, issue.1, pp.1-30, 2004.
DOI : 10.1016/j.ijar.2003.07.013

F. Tonon, Using random set theory to propagate epistemic uncertainty through a mechanical system, Reliability Engineering & System Safety, vol.85, issue.1-3, pp.169-181, 2004.
DOI : 10.1016/j.ress.2004.03.010

I. Couso and S. Moral, Independence concepts in evidence theory, International Journal of Approximate Reasoning, vol.51, issue.7, pp.748-758, 2010.
DOI : 10.1016/j.ijar.2010.02.004

I. Couso, S. Moral, and P. Walley, Examples of independence for imprecise probabilities, Proceedings of the First International Symposium on Imprecise Probability and Their Applications, pp.121-130

I. Couso, S. Moral, and P. Walley, A survey of concepts of independence for imprecise probabilities, Risk Decision and Policy, vol.5, issue.2, pp.165-181, 2000.
DOI : 10.1017/S1357530900000156

D. Dubois, H. Prade, and S. Sandri, On Possibility/Probability Transformations, Pp, pp.103-112
DOI : 10.1007/978-94-011-2014-2_10

P. Smets, Constructing the Pignistic Probability Function in a Context of Uncertainty, Uncertainty in Artificial Intelligence, vol.5, pp.29-39, 1990.
DOI : 10.1016/B978-0-444-88738-2.50010-5

D. Dubois, L. Foulloy, G. Mauris, and H. Prade, Probability-Possibility Transformations, Triangular Fuzzy Sets, and Probabilistic Inequalities, Reliable Computing, vol.10, issue.4, pp.273-297, 2004.
DOI : 10.1023/B:REOM.0000032115.22510.b5
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.104.6216

D. Dubois, H. Prade, and P. Smets, A definition of subjective possibility, International Journal of Approximate Reasoning, vol.48, issue.2, pp.352-364, 2008.
DOI : 10.1016/j.ijar.2007.01.005