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Fast uncertainty quantification of spent nuclear fuel with neural networks
Albà, A., Adelmann, A., Münster, L., Rochman, D., & Boiger, R. (2024). Fast uncertainty quantification of spent nuclear fuel with neural networks. Annals of Nuclear Energy, 196, 110204 (8 pp.). https://doi.org/10.1016/j.anucene.2023.110204
The iPWR MELCOR 2.2 parametric sensitivity analysis
Malicki, M., Darnowski, P., & Lind, T. (2023). The iPWR MELCOR 2.2 parametric sensitivity analysis. In 20th international topical meeting on nuclear reactor thermal hydraulics (NURETH-20) (pp. 4220-4233). American Nuclear Society.
Probabilistic risk assessment for the piping of a nuclear power plant: uncertainty and sensitivity analysis by using SINTAP procedure
Mao, G., Niffenegger, M., & Mao, X. (2022). Probabilistic risk assessment for the piping of a nuclear power plant: uncertainty and sensitivity analysis by using SINTAP procedure. International Journal of Pressure Vessels and Piping, 200, 104791 (10 pp.). https://doi.org/10.1016/j.ijpvp.2022.104791
Physics-based 0D-U-I-SoC cell performance model for aqueous organic redox flow batteries
Mourouga, G., Schaerer, R. P., Yang, X., Janoschka, T., Schmidt, T. J., & Schumacher, J. O. (2022). Physics-based 0D-U-I-SoC cell performance model for aqueous organic redox flow batteries. Electrochimica Acta, 415, 140185 (18 pp.). https://doi.org/10.1016/j.electacta.2022.140185
Impact of various source of covariance information on integral parameters uncertainty during depletion calculations with CASMO-5
Hursin, M., Rochman, D., Vasiliev, A., Ferroukhi, H., & Pautz, A. (2021). Impact of various source of covariance information on integral parameters uncertainty during depletion calculations with CASMO-5. In M. Margulis & P. Blaise (Eds.), EPJ web of conferences: Vol. 247. PHYSOR2020 - international conference on physics of reactors: transition to a scalable nuclear future (p. 09005 (10 pp.). https://doi.org/10.1051/epjconf/202124709005
A framework based on statistical analysis and stakeholders' preferences to inform weighting in composite indicators
Lindén, D., Cinelli, M., Spada, M., Becker, W., Gasser, P., & Burgherr, P. (2021). A framework based on statistical analysis and stakeholders' preferences to inform weighting in composite indicators. Environmental Modelling and Software, 145, 105208 (16 pp.). https://doi.org/10.1016/j.envsoft.2021.105208
Uncertainty and sensitivity analysis of the chemistry of cesium sorption in deep geological repositories
Ayoub, A., Pfingsten, W., Podofillini, L., & Sansavini, G. (2020). Uncertainty and sensitivity analysis of the chemistry of cesium sorption in deep geological repositories. Applied Geochemistry, 117, 104607 (12 pp.). https://doi.org/10.1016/j.apgeochem.2020.104607
On data assimilation with Monte-Carlo-calculated and statistically uncertain sensitivity coefficients
Siefman, D., Hursin, M., Aufiero, M., Bidaud, A., & Pautz, A. (2020). On data assimilation with Monte-Carlo-calculated and statistically uncertain sensitivity coefficients. Annals of Nuclear Energy, 135, 106951 (13 pp.). https://doi.org/10.1016/j.anucene.2019.106951
On nonintrusive uncertainty quantification and surrogate model construction in particle accelerator modeling
Adelmann, A. (2019). On nonintrusive uncertainty quantification and surrogate model construction in particle accelerator modeling. SIAM-ASA Journal on Uncertainty Quantification, 7(2), 383-416. https://doi.org/10.1137/16M1061928
Determination of sobol sensitivity indices for correlated inputs with SHARK-X
Hursin, M., Siefman, D., Perret, G., Rochman, D., Vasiliev, A., & Ferroukhi, H. (2018). Determination of sobol sensitivity indices for correlated inputs with SHARK-X. In Proceedings of the PHYSOR 2018 (p. (12 pp.). American Nuclear Society.
Convergence analysis and criterion for data assimilation with sensitivities from Monte Carlo neutron transport codes
Siefman, D., Hursin, M., Aufiero, M., Bidaud, A., & Pautz, A. (2018). Convergence analysis and criterion for data assimilation with sensitivities from Monte Carlo neutron transport codes. In Proceedings of the PHYSOR 2018 (p. (10 pp.). American Nuclear Society.
Ranking of uncertain parameters for dynamic event tree analysis: a case study based on a Station Black Out scenario
Rahman, S., Karanki, D. R., Epiney, A., Zerkak, O., & Dang, V. N. (2015). Ranking of uncertain parameters for dynamic event tree analysis: a case study based on a Station Black Out scenario. In 16th international topical meeting on nuclear reactor thermal hydraulics (NURETH-16) (pp. 5734-5747). American Nuclear Society.
Producing synthetic natural gas from microalgae via supercritical water gasification: a techno-economic sensitivity analysis
Brandenberger, M., Matzenberger, J., Vogel, F., & Ludwig, C. (2013). Producing synthetic natural gas from microalgae via supercritical water gasification: a techno-economic sensitivity analysis. Biomass and Bioenergy, 51, 26-34. https://doi.org/10.1016/j.biombioe.2012.12.038
Probabilistic fracture assessment of piping systems based on FITNET FFS procedure
Qian, G., & Niffenegger, M. (2011). Probabilistic fracture assessment of piping systems based on FITNET FFS procedure. Nuclear Engineering and Design, 241(3), 714-722. https://doi.org/10.1016/j.nucengdes.2011.01.019
Two techniques of sensitivity and uncertainty analysis of fuzzy expert systems
Baraldi, P., Librizzi, M., Zio, E., Podofillini, L., & Dang, V. N. (2009). Two techniques of sensitivity and uncertainty analysis of fuzzy expert systems. Expert Systems with Applications, 36(10), 12461-12471. https://doi.org/10.1016/j.eswa.2009.04.036
Charge, mass and heat transfer interactions in solid oxide fuel cells operated with different fuel gases - a sensitivity analysis
Nagel, F. P., Schildhauer, T. J., Biollaz, S. M. A., & Stucki, S. (2008). Charge, mass and heat transfer interactions in solid oxide fuel cells operated with different fuel gases - a sensitivity analysis. Journal of Power Sources, 184(1), 129-142. https://doi.org/10.1016/j.jpowsour.2008.05.044