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Quantifying the impact of travel time duration and valuation on modal shift in Swiss passenger transportation
Luh, S., Kannan, R., McKenna, R., Schmidt, T. J., & Kober, T. (2024). Quantifying the impact of travel time duration and valuation on modal shift in Swiss passenger transportation. Applied Energy, 356, 122412 (26 pp.). https://doi.org/10.1016/j.apenergy.2023.122412
Exploring the trilemma of cost-efficiency, landscape impact and regional equality in onshore wind expansion planning
Weinand, J. M., McKenna, R., Heinrichs, H., Roth, M., Stolten, D., & Fichtner, W. (2022). Exploring the trilemma of cost-efficiency, landscape impact and regional equality in onshore wind expansion planning. Advances in Applied Energy, 7, 100102 (17 pp.). https://doi.org/10.1016/j.adapen.2022.100102
Multi-objective shape optimization of radio frequency cavities using an evolutionary algorithm
Kranjčević, M., Adelmann, A., Arbenz, P., Citterio, A., & Stingelin, L. (2019). Multi-objective shape optimization of radio frequency cavities using an evolutionary algorithm. Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 920, 106-114. https://doi.org/10.1016/j.nima.2018.12.066
Multi-objective optimization of energy arbitrage in community energy storage systems using different battery technologies
Terlouw, T., AlSkaif, T., Bauer, C., & van Sark, W. (2019). Multi-objective optimization of energy arbitrage in community energy storage systems using different battery technologies. Applied Energy, 239, 356-372. https://doi.org/10.1016/j.apenergy.2019.01.227
A fast and scalable low dimensional solver for charged particle dynamics in large particle accelerators
Ineichen, Y., Adelmann, A., Bekas, C., Curioni, A., & Arbenz, P. (2013). A fast and scalable low dimensional solver for charged particle dynamics in large particle accelerators. Computer Science, 28(2-3), 185-192. https://doi.org/10.1007/s00450-012-0216-2
Importance measures and genetic algorithms for designing a risk-informed optimally balanced system
Zio, E., & Podofillini, L. (2007). Importance measures and genetic algorithms for designing a risk-informed optimally balanced system. Reliability Engineering and System Safety, 92(10), 1435-1447. https://doi.org/10.1016/j.ress.2006.09.011