Publications
Journal Papers
Abolfazl Simorgh, Manuel Soler. Pathways to Sustainable Aviation: Aligning Flight Plans with Climate Goals, Communications Earth & Environment. 03 June 2024, PREPRINT (Version 1) available at Research Square https://doi.org/10.21203/rs.3.rs-4355046/v1
Simorgh, A., Soler, M., Dietmüller, S., Matthes, S., Yamashita, H., Castino, F., Yin, F: Robust 4D Climate-Optimal Aircraft Trajectory Planning under Weather-Induced Uncertainties: Free-Routing Airspace. Transportation Research Part D – Transport and Environment. Volume 131, June 2024, 104196. https://doi.org/10.1016/j.trd.2024.104196
Simorgh, A., Soler, M. Cerezo, Castino, F., Yin, F. Concept of Robust Climate-Friendly Flight Planning under Multiple Climate Impact Estimates. Transportation Research Part D – Transport and Environment. Volume 131, June 2024, 104215. https://doi.org/10.1016/j.trd.2024.104215
Federica Castino, Feijia Yin, Volker Grewe, Hiroshi Yamashita, Sigrun Matthes, Simone Dietmüller, Sabine Baumann, Manuel Soler, Abolfazl Simorgh, Maximilian Mendiguchia Meuser, Florian Linke, and Benjamin Lührs. Decision-making strategies implemented in SolFinder 1.0 to identify eco-efficient aircraft trajectories: application study in AirTraf 3.0 Geoscientific Model Development (GMD). Special issue: The Modular Earth Submodel System (MESSy) (ACP/GMD inter-journal SI). https://gmd.copernicus.org/preprints/gmd-2023-88/
Abolfazl Simorgh, Manuel Soler, Daniel González-Arribas, Sigrun Matthes, Volker Grewe, Simone Dietmüller, Sabine Baumann, Hiroshi Yamashita, Feijia Yin, Federica Castino, Florian Linke, Benjamin Lührs, Maximilian Meuser. A Comprehensive Survey on Recent Climate Optimal Aircraft Trajectory Planning. Aerospace, 2022, 9(3), 146; https://doi.org/10.3390/aerospace9030146, 2022.
Dietmüller, S. Matthes, S., Dahlmann, K., Yamashita, H., Soler, M., Simorgh, A., Linke, F., Lührs, B., Mendiguchia Meuser, M. , Weder, C., Yin, F., Castino, F., Grewe, V. (2022): A python library for computing individual and merged non-CO2 algorithmic climate change functions: CLIMaCCF V1.0, Geoscientific Model Development (GMD). Under Review. In pre-print. https://gmd.copernicus.org/preprints/gmd-2022-203/, 2022.
Yin, F., Grewe, V., Matthes, S., Yamashita, H., Dahlmann, K., Klingaman, E., Shine, K. P., Lührs, B., Linke, F.: Predicting the climate impact of aviation for en-route emissions: The algorithmic climate change function sub model ACCF 1.0 of EMAC 2.53. Geoscientific Model Development (GMD). https://doi.org/10.5194/gmd-2022-220, 2022.
Simorgh, A., Soler, M., González-Arribas, D., Linke, F., Lührs, B., Meuser, M. M., Dietmüller, S., Matthes, S., Yamashita, H., Yin, F., Castino, F., Grewe, V., and Baumann, S.: Robust 4D Climate Optimal Flight Planning in Structured Airspace using Parallelized Simulation on GPUs: ROOST V1.0, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2022-1010, 2022.
Conference papers
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SESAR innovation Days 2024: F4EClim Concept Poster. Matthes, S., Dietmüller, S., Simorgh, A., Soler, M., Yamashita, H., Castino, F., Yin, F: Zarah Lea Zengerling, Maximilian M. Meuser.
Open-Source Libraries
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CLIMaCCF. A Python library designed to compute the climate impact of aviation emissions using algorithmic Climate Change Functions (aCCFs). CLIMaCCF is released under GNU Lesser General Public License v3.0 (LGPLv3). Citing the Software Documentation Paper (Dietmüller et al. 2023) together with CLIMaCCF software DOI (doi: 10.5281/zenodo.6977273) and version number will serve to document the scientific impact of the software.
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ROC (Robust Optimal Control for Flight Planning). A robust trajectory optimization tool built to enable climate-friendly flight planning, even under uncertain weather conditions. Released under GNU Lesser General Public License v3.0 (LGPLv3). Abolfazl Simorgh, Daniel González, and Manuel Soler (2025). Aircraft-Operations-Lab/roc: v1.1.0 (v1.1.0). Zenodo. https://doi.org/10.5281/zenodo.15391956
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ROOST (Robust Optimization Of Structured Trajectories). The Python Library roost is a software package developed by UC3M. It is a tool for robust flight planning within the currently structured airspace. The main features of roost are: 1) integrates horizontal and vertical decision-making, 2) fast performance thanks to GPU-based parallelization, 3) considers climb, cruise, and descent phases 4) incorporate uncertainty in meteorological variables, as well as initial flight time and initial flight mass. ROOST is released under GNU Lesser General Public License v3.0 (LGPLv3). González Arribas, D., Andrés Enderiz, E., & Simorgh, A. (2022). Zenodo. https://doi.org/10.5281/zenodo.7495472