Ruida Xie

Ruida Xie

PhD

Sitemap

A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

Pages

Posts

Future Blog Post

less than 1 minute read

Published:

This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.

Blog Post number 4

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 3

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 2

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 1

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

portfolio

Low-thrust transfer cost estimation based on Deep Learning

Published:

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.

Campaign-level off-Earth mining design and optimisation

Published:

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.

publications

Paper Title Number 3

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).

researchdata

2 Billion Impulsive Round-trip Trajectories

Published:

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.

Low-thrust trajectories: For Deep Learning Model Construction

Published:

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.

Low-thrust Roundtrip trajectories

Published:

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.

Time optimal trajectories for Global Trajectory Optimization Competition 11

Published:

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.

talks