Bibliographic references

2.9. Bibliographic references#

[BR_METHOD_1]

H. Akaike. Information theory and an extension of the maximum likelihood principle. 2nd International Symposium on Information Theory, 1971. URL: http://link.springer.com/chapter/10.1007/978-1-4612-1694-0_15, doi:10.1007/978-1-4612-1694-0_15.

[BR_METHOD_2]

Robert J. Budnitz, George E. Apostolakis, and David M. Boore. Recommendations for probabilistic seismic hazard analysis: guidance on uncertainty and use of experts. In NUREG/CR-6372 / UCRL-ID-122160 Vol 1. 1997. URL: https://www.osti.gov/biblio/479072-krGkYU/webviewable/, doi:https://doi.org/10.2172/479072.

[BR_METHOD_3]

Patrick Carton, M. Giraudeau, and F. Davenel. New fides models for emerging technologies. 2017 Annual Reliability and Maintainability Symposium (RAMS), pages 1–6, 2017. URL: https://ieeexplore.ieee.org/document/7889686, doi:https://doi.org/10.1109/RAM.2017.7889686.

[BR_METHOD_4]

Safety Chair of Risk, Uncertainty Quantification of ETH Zurich under the supervision of Prof. B. Sudret, and Dr. S. Marelli. Uqlab - matlab®-based uncertainty quantification framework. Online, accessed 08.04.2020, 2020. URL: https://www.uqlab.com/.

[BR_METHOD_5]

SIGMA Clermont. Ferum - finite element reliability using matlab. Online, accessed 08.04.2020, 2020. URL: https://www.sigma-clermont.fr/en/ferum.

[BR_METHOD_6]

SIGMA Clermont. Openturns: an industrial software for uncertainty quantification in simulation. Online, accessed 08.04.2020, 2020. URL: https://www.sigma-clermont.fr/en/ferum.

[BR_METHOD_7]

Homayoon Dezfuli, Dana Kelly, Curtis L. Smith, Kurt G. Vedros, and William J. Galyean. Bayesian inference for NASA probabilistic risk and reliability analysis. In NASA/SP-2009-569. 2009. URL: https://ntrs.nasa.gov/citations/20090023159, doi:20090023159.

[BR_METHOD_8]

Ditlevsen O. and Madsen H.O. Structural Reliability Methods. Wiley, 2007. URL: http://od-website.dk/books/OD-HOM-StrucRelMeth-Ed2.3.7.pdf.

[BR_METHOD_9]

Daniel Fink. A compendium of conjugate priors. 1997.

[BR_METHOD_10]

European Cooperation for Space Standardization (ECSS). Ecss space project management - project planning and implementation. Standard ECSS-M-ST-10C Rev. 1, ECSS, 2009. URL: https://ecss.nl/standard/ecss-m-st-10c-rev-1-project-planning-and-implementation/.

[BR_METHOD_11]

European Cooperation for Space Standardization (ECSS). Ecss space engineering - product assurance management. Standard ECSS-Q-ST-10C, Rev 1, ECSS, 2016. URL: https://ecss.nl/standard/ecss-q-st-10c-rev-1-product-assurance-management-15-march-2016/.

[BR_METHOD_12]

European Cooperation for Space Standardization (ECSS). Ecss space engineering - system engineering general requirements. Standard ECSS-E-ST-10C, Rev 1, ECSS, 2017. URL: https://ecss.nl/standard/ecss-e-st-10c-rev-1-system-engineering-general-requirements-15-february-2017/.

[BR_METHOD_13]

Paul H. Garthwaite, Joseph B. Kadane, and Anthony O'Hagan. Statistical methods for eliciting probability distributions. Journal of the American Statistical Association, 100:680 – 701, 2005. URL: https://www.tandfonline.com/doi/abs/10.1198/016214505000000105, doi:https://doi.org/10.1198/016214505000000105.

[BR_METHOD_14]

Andrew Gelman, John Carlin, Hal Stern, Donald Rubin, David Dunson, and Aki Vehtari. Bayesian data analysis. CRC Press, 3rd edition, 2013. ISBN 9781439840955.

[BR_METHOD_15]

Missoum S. Harrison Sanchez A. and Martinez Teuscher J.P. Design space decomposition using support vector machines for reliability-based design optimization. 2012. URL: https://arc.aiaa.org/doi/abs/10.2514/6.2006-6927, doi:https://doi.org/10.2514/6.2006-6927.

[BR_METHOD_16]

R. B. Stone I. Y. Tumer. Analytical method for mapping function to failure during high-risk component development. Proceedings of the Design Engineering Technical Conferences, 2001. URL: https://asmedigitalcollection.asme.org/IDETC-CIE/proceedings-abstract/IDETC-CIE2001/80241/129/1090879, doi:10.1115/DETC2001/DFM-21173.

[BR_METHOD_17]

Quanterion Solutions Incorporated. Failure mode / mechanism distributions. Technical Report FMD-2016, QUANTERION, 2016. URL: https://www.quanterion.com/wp-content/uploads/2015/12/FMD-2016-1.pdf.

[BR_METHOD_18]

Bernardo J and Smith A. Bayesian Theory. John Wiley & Sons, 1994. URL: https://onlinelibrary.wiley.com/doi/book/10.1002/9780470316870.

[BR_METHOD_19]

Lunn D J, Thomas A, Best N, and Spiegelhalter D. The bugs project. Online, accessed 08.04.2020, 2000. URL: http://www.mrc-bsu.cam.ac.uk/software/bugs/.%20Accessed%2008.04.2020.

[BR_METHOD_20]

H. Jeffreys. An invariant form for the prior probability in estimation problems. The Royal Society, 1946. URL: https://royalsocietypublishing.org/doi/10.1098/rspa.1946.0056, doi:https://doi.org/10.1098/rspa.1946.0056.

[BR_METHOD_21]

Ridder A. Kleijnen, J.P.C. and Rubinstein R. Variance reduction techniques in monte carlo methods. SSRN Electronic Journal, 2010. URL: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1715474, doi:10.2139/ssrn.1715474.

[BR_METHOD_22]

Michael T. Kowal. Mechanical system reliability and cost integration using a sequential linear approximation method. Technical Report 19970017405, NASA, 1997. URL: https://ntrs.nasa.gov/citations/19970017405.

[BR_METHOD_23]

Sandia National Laboratories. Handbook of parameter estimation for probabilistic risk assessment. Technical Report NUREG/CR-6823 / SAND2003-3348P, U.S. Nuclear Regulatory Commission Office of Nuclear Regulatory Research Washington, 2003. URL: https://www.nrc.gov/docs/ML0329/ML032900131.pdf.

[BR_METHOD_24]

Plummer M. Jags - just another gibbs sampler. Online, accessed 08.04.2020, 2007. URL: http://mcmc-jags.sourceforge.net/.

[BR_METHOD_25]

Krenk S. Madsen H.O. and Lind N.C. Methods of Structural Safety. Courier Corporation, 2006. URL: https://books.google.fr/books/about/Methods_of_Structural_Safety.html?id=e8sZjD7so-AC&redir_esc=y.

[BR_METHOD_26]

E. R Melchers. Structural Reliability Analysis and Prediction. Wiley, 1999. URL: https://www.wiley.com/en-us/Structural+Reliability+Analysis+and+Prediction,+3rd+Edition-p-9781119265993.

[BR_METHOD_27]

David E. Morris, Jeremy E. Oakley, and John A. Crowe. A web-based tool for eliciting probability distributions from experts. Environ. Model. Softw., 52:1–4, 2014. URL: https://www.sciencedirect.com/science/article/pii/S1364815213002533?via%3Dihub, doi:https://doi.org/10.1016/j.envsoft.2013.10.010.

[BR_METHOD_28]

N.Y.) Rome Laboratory (Griffiss Air Force Base. Rome Laboratory Reliability Engineer's Toolkit: An Application Oriented Guide for the Practicing Reliability Engineer. The Division, 1993. URL: https://reliabilityanalytics.com/Rome_Laboratory_Reliability_Engineers_Toolkit.pdf.

[BR_METHOD_29]

N.Y.) Rome Laboratory (Griffiss Air Force Base. NIST/SEMATECH Engineering Statistics Handbook - e-Handbook of Statistical Methods. NIST, 2012. [Online; accessed 08.04.2020]. URL: http://www.itl.nist.gov/div898/handbook/, doi:https://doi.org/10.18434/M32189.

[BR_METHOD_30]

Gollwitzer S. Strurel system of programs for probabilistic reliability analysis. 2006. URL: http://dx.doi.org/10.1016/j.strusafe.2005.03.008, doi:http://dx.doi.org/10.1016/j.strusafe.2005.03.008.

[BR_METHOD_31]

Southwest Research Institute. Nessus software. Online, accessed 08.04.2020, 2020. URL: https://www.swri.org/nessus.

[BR_METHOD_32]

Thalès Alenia Space. Tec-qqd study - use of quantitative reliability requirements for space applications. Standard TASF-RAMS-0010, Thalès Alenia Space, 2016.

[BR_METHOD_33]

B. Sudret. Meta-models for structural reliability and uncertainty quantification. In Asian-Pacific Symposium on Structural Reliability and its Applications. 2012. URL: https://hal-enpc.archives-ouvertes.fr/hal-00683179/document, doi:https://doi.org/10.3850/978-981-07-2219-7_P321.

[BR_METHOD_34]

Stan Development Team. Stan: project homepage. Online, accessed 08.04.2020, 2017. URL: http://mc-stan.org/index.html.

[BR_METHOD_35]

Resit Unal, Charles B. Keating, Bruce A. Conway, and Trina M. Chytka. Development of an expert judgement elicitation and calibration methodology for risk analysis in conceptual vehicle design. In NASA NCC- 1-02044. 2004. URL: https://ntrs.nasa.gov/citations/20040016143, doi:20040016143.