Bayesian Optimization of crewed lunar free return abort trajectory. (December 2022)
- Record Type:
- Journal Article
- Title:
- Bayesian Optimization of crewed lunar free return abort trajectory. (December 2022)
- Main Title:
- Bayesian Optimization of crewed lunar free return abort trajectory
- Authors:
- Dong, Tianshan
Luo, Qinqin
Han, Chao - Abstract:
- Abstract: Maneuvering to a free return trajectory is a vital abort means for crewed lunar missions. A novel method of solving the fuel optimization of free return abort trajectory for Earth-Moon transfer by two-stage transformation on optimization model and Bayesian optimization is documented. Two new design variables—perilune altitude and transfer time from earth to perilune, instead of the original injection velocity vector, are introduced to transform the general model into a two-dimensional model. Each feasible abort trajectory is determined by a numerical method including initial estimate and exact solution. Then the characteristics of the relationship between the new variables and the fuel objective of impulse maneuver are applied to further transform the model into a one-dimensional model. Based on the Bayesian optimization method, fuel optimization is successfully and efficiently implemented for the free return abort trajectory at multiple abort moments during the Earth-Moon transfer. Furthermore, the influence of the initial Earth-Moon phase on the result of fuel optimization is presented. Numerical simulations are conducted to demonstrate the efficacy of the proposed method. Highlights: Fuel optimization of free return abort trajector. y for Earth-Moon transfer is studied. We propose a two-stage transformation method to overcome the difficulty of optimization model. Bayesian Optimization method is applied to solve the optimization efficiently based on problem'sAbstract: Maneuvering to a free return trajectory is a vital abort means for crewed lunar missions. A novel method of solving the fuel optimization of free return abort trajectory for Earth-Moon transfer by two-stage transformation on optimization model and Bayesian optimization is documented. Two new design variables—perilune altitude and transfer time from earth to perilune, instead of the original injection velocity vector, are introduced to transform the general model into a two-dimensional model. Each feasible abort trajectory is determined by a numerical method including initial estimate and exact solution. Then the characteristics of the relationship between the new variables and the fuel objective of impulse maneuver are applied to further transform the model into a one-dimensional model. Based on the Bayesian optimization method, fuel optimization is successfully and efficiently implemented for the free return abort trajectory at multiple abort moments during the Earth-Moon transfer. Furthermore, the influence of the initial Earth-Moon phase on the result of fuel optimization is presented. Numerical simulations are conducted to demonstrate the efficacy of the proposed method. Highlights: Fuel optimization of free return abort trajector. y for Earth-Moon transfer is studied. We propose a two-stage transformation method to overcome the difficulty of optimization model. Bayesian Optimization method is applied to solve the optimization efficiently based on problem's characteristics. The time window of abort trajectory and influence of the initial Earth-Moon phase is discussed. … (more)
- Is Part Of:
- Acta astronautica. Volume 201(2022)
- Journal:
- Acta astronautica
- Issue:
- Volume 201(2022)
- Issue Display:
- Volume 201, Issue 2022 (2022)
- Year:
- 2022
- Volume:
- 201
- Issue:
- 2022
- Issue Sort Value:
- 2022-0201-2022-0000
- Page Start:
- 288
- Page End:
- 301
- Publication Date:
- 2022-12
- Subjects:
- Free return abort trajectory -- Abort return on earth-moon transfer -- Trajectory optimization -- Optimization model transformation -- Bayesian optimization
Astronautics -- Periodicals
Outer space -- Exploration -- Periodicals
Astronautics
Periodicals
629.405 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00945765 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.actaastro.2022.08.052 ↗
- Languages:
- English
- ISSNs:
- 0094-5765
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0596.750000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 24106.xml