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Comparative risk assessment for fossil energy chains using Bayesian Model Averaging
Spada, M., & Burgherr, P. (2020). Comparative risk assessment for fossil energy chains using Bayesian Model Averaging. Energies, 13(2), 295 (21 pp.). https://doi.org/10.3390/en13020295
Probabilistic assessment of realizing the 1.5 °C climate target
Marcucci, A., Panos, E., Kypreos, S., & Fragkos, P. (2019). Probabilistic assessment of realizing the 1.5 °C climate target. Applied Energy, 239, 239-251. https://doi.org/10.1016/j.apenergy.2019.01.190
Overview and recommendations for regionalized life cycle impact assessment
Mutel, C., Liao, X., Patouillard, L., Bare, J., Fantke, P., Frischknecht, R., … Verones, F. (2019). Overview and recommendations for regionalized life cycle impact assessment. International Journal of Life Cycle Assessment, 24(5), 856-865. https://doi.org/10.1007/s11367-018-1539-4
Effects of distribution choice on the modeling of life cycle inventory uncertainty: an assessment on the ecoinvent v2.2 database
Muller, S., Mutel, C., Lesage, P., & Samson, R. (2018). Effects of distribution choice on the modeling of life cycle inventory uncertainty: an assessment on the ecoinvent v2.2 database. Journal of Industrial Ecology, 22(2), 300-313. https://doi.org/10.1111/jiec.12574
How inelastic scattering stimulates nonlinear reactor core parameter behaviour
Rochman, D., Vasiliev, A., Ferroukhi, H., Dokhane, H., & Koning, A. (2018). How inelastic scattering stimulates nonlinear reactor core parameter behaviour. Annals of Nuclear Energy, 112, 236-244. https://doi.org/10.1016/j.anucene.2017.10.018
Life cycle inventories of electricity supply through the lens of data quality: exploring challenges and opportunities
Astudillo, M. F., Treyer, K., Bauer, C., Pineau, P. O., & Amor, M. B. (2017). Life cycle inventories of electricity supply through the lens of data quality: exploring challenges and opportunities. International Journal of Life Cycle Assessment, 22(3), 374-386. https://doi.org/10.1007/s11367-016-1163-0
A robust optimisation approach accounting for the effect of fractionation on setup uncertainties
Lowe, M., Aitkenhead, A., Albertini, F., Lomax, A. J., & Mackay, R. I. (2017). A robust optimisation approach accounting for the effect of fractionation on setup uncertainties. Physics in Medicine and Biology, 62(20), 8178-8196. https://doi.org/10.1088/1361-6560/aa8c58
Incorporating the effect of fractionation in the evaluation of proton plan robustness to setup errors
Lowe, M., Albertini, F., Aitkenhead, A., Lomax, A. J., & MacKay, R. I. (2016). Incorporating the effect of fractionation in the evaluation of proton plan robustness to setup errors. Physics in Medicine and Biology, 61(1), 413-429. https://doi.org/10.1088/0031-9155/61/1/413
Nuclear data uncertainty for criticality-safety: Monte Carlo<em> vs</em>. linear perturbation
Rochman, D., Vasiliev, A., Ferroukhi, H., Zhu, T., van der Marck, S. C., & Koning, A. J. (2016). Nuclear data uncertainty for criticality-safety: Monte Carlo vs. linear perturbation. Annals of Nuclear Energy, 92, 150-160. https://doi.org/10.1016/j.anucene.2016.01.042
Uncertainties in key low carbon power generation technologies - Implication for UK decarbonisation targets
Kannan, R. (2009). Uncertainties in key low carbon power generation technologies - Implication for UK decarbonisation targets. Applied Energy, 86(10), 1873-1886. https://doi.org/10.1016/j.apenergy.2009.02.014
Life cycle inventories for the nuclear and natural gas energy systems, and examples of uncertainty analysis
Dones, R., Heck, T., Faist Emmenegger, M., & Jungbluth, N. (2005). Life cycle inventories for the nuclear and natural gas energy systems, and examples of uncertainty analysis. International Journal of Life Cycle Assessment, 10(1), 10-23. https://doi.org/10.1065/lca2004.12.181.2