Web-based interactive 3D visualisation of asteroids
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This project developed 3D visualisation of different groups of asteroids
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This project developed 3D visualisation of different groups of asteroids
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This project is to develop rapid search technique for impulsive/low-thrust roundtrip NEA robotic missions
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This project is using machine learning techiniques to etimate low-thrust transfer cost without performing the actual optimisation. This technique greatly reduces the computation time and the accuracy outperforms and analytical solution, these two features enable more complex mission designs.
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This project is to solve the problem of large-scale off-Earth mining. Off-Earth mining is an economic activity and requires detailed prefeasibility study. The work covers target selection, trajectory generation, mission opportunity search, economic analyses and campaign scheduling and optimization.
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This project is for the GTOC11 held in Nov 2021.
Published in Journal 1, 2009
This paper is about the number 1. The number 2 is left for future work.
Recommended citation: Your Name, You. (2009). "Paper Title Number 1." Journal 1. 1(1). http://academicpages.github.io/files/paper1.pdf
Published in Journal 1, 2010
This paper is about the number 2. The number 3 is left for future work11.
Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2). http://academicpages.github.io/files/paper2.pdf
Published in Journal 1, 2015
This paper is about the number 3. The number 4 is left for future work.
Recommended citation: Your Name, You. (2015). "Paper Title Number 3." Journal 1. 1(3).
Published in , 2021
Recommended citation: Xie, R., Bennett, N.J. and Dempster, A.G., 2021. Target evaluation for near earth asteroid long-term mining missions. Acta Astronautica, 181, pp.249-270.
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This database stores nearly two billion impulsive round-trip trajectories to near Earth asteroids. This database enables numerical approach for mission analysis. The visualization of this database can be found on http://www.traplan.xyz/data.html. You may find an insecure icon on your chrome browser, this because the website is under development and I haven’t purchase a https certificate. Please simply ignore that. Please allow some minutes for the database to load.
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This database stores randomly generated low-thrust(LT) trajectories between NEAs. This database can be used for training interesting machine learning models. For example, using both feasible LT samples and infeasible samples to build a DNN classification model to distinguish LT transfer feasibilities. This database is valuable – obtaining such database requires hundreds of thousands of cores hours of high-performance computing system.
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This database stores low-thrust roundtrip missions to NEAs. The generation of this database used our advanced deep learning low-thrust transfer cost approximation technique, which replace the conventional optimization process. The estimation of low thrust transfer cost is as fast as solving a Lambert problem. The search process is based on grid search.
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This database was created for GTOC 11. The database stores randomly generated time optimal low thrust trajectories. The trajectories are from the asteroids provided in GTOC 11 to a random ‘Dyson Ring’ station. This database was used to train Deep Neural Network models as surrogate of conventional time optimal optimization process. It take ephemerides and output optimal low thrust transfer time directly without performing actual optimization process.
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This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
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This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.