Solution Domain Analysis of Earth-Moon Quasi-Symmetric Free-Return Orbits

He, Bo-yong; Li, Haiyang; Zhou, Jianping

doi:10.2322/tjsass.60.195

Cited by 11 publications

(4 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The sequential quadratic programming (SQP) algorithm has a good advantage of computation efficiency [25], and it is employed to perform this optimization. However, the performance of the algorithm depends closely on the initial guesses for the design variables.…”

Section: Moon-to-earth Trajectory Optimization Methodmentioning

confidence: 99%

Multiphase Trajectory Optimization of a Lunar Return Mission to an LEO Space Station

Yang

Zhang

et al. 2021

International Journal of Aerospace Engineering

Self Cite

View full text Add to dashboard Cite

Lunar exploration architecture can be made more flexible and reliable with the support of a low-Earth orbit (LEO) space station. This study therefore evaluated a proposed hybrid optimization scheme to design the entire trajectory of a reusable spacecraft starting from trans-Earth injection (EI) at the perilune and ending at an LEO space station. As such a trajectory has multiple constraints and multiple dynamical models, it is divided into the trans-Earth phase, aerocapture phase, and postatmospheric phase. The optimization scheme is performed at two levels: sublevel and top level. At the sublevel, two novel pseudo rules are proposed to optimize the trans-Earth trajectory so that it satisfies the coplanar constraints of the space station. Then, in the aerocapture phase, the bank angle is optimized to satisfy the mission constraints, and in the atmospheric phase, the one-impulsive maneuver is performed and optimized to insert the spacecraft into the target space station orbit. The multiple phases are connected to each other by boundary conditions where the terminal state of the previous phase is transformed into the initial state of the following phase. At the top level, the vacuum perigee height is selected as the mission design variable based on problem characteristics analysis and a hybrid optimization scheme is conducted to minimize the total velocity increment. The simulation results demonstrate that the proposed hybrid optimization method is effective for the design of an entire trajectory with acceptable velocity cost which is less than that in the previous study. The coplanar constraints of the space station and other mission constraints in each phase are also satisfied. Furthermore, the proposed trajectory design method is shown to be applicable to a reusable spacecraft returning to an LEO space station parked in any arbitrary orbital plane.

show abstract

Section: Moon-to-earth Trajectory Optimization Methodmentioning

confidence: 99%

Multiphase Trajectory Optimization of a Lunar Return Mission to an LEO Space Station

Yang

Zhang

et al. 2021

International Journal of Aerospace Engineering

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, the basic assumptions of patched conic, i.e., (i) the Moon acting in a circular motion around the Earth, and (ii) neglecting the gravity of the central body successively, can cause considerable errors. Hence, a more accurate dynamical model containing ephemeris needs to be considered for the practical Earth-Moon mission [35,36]. It should also be noted that, in operations of practical engineering missions, midcourse impulses are always employed to eliminate the initial error in entering the Earth-Moon transfer orbit.…”

Section: Patched Conic Modelmentioning

confidence: 99%

Overview of Earth-Moon Transfer Trajectory Modeling and Design

Zhang¹,

Yu²,

Dai³

2023

Computer Modeling in Engineering &Amp; Sciences

View full text Add to dashboard Cite

The Moon is the only celestial body that human beings have visited. The design of the Earth-Moon transfer orbits is a critical issue in lunar exploration missions. In the 21st century, new lunar missions including the construction of the lunar space station, the permanent lunar base, and the Earth-Moon transportation network have been proposed, requiring low-cost, expansive launch windows and a fixed arrival epoch for any launch date within the launch window. The low-energy and low-thrust transfers are promising strategies to satisfy the demands. This review provides a detailed landscape of Earth-Moon transfer trajectory design processes, from the traditional patched conic to the state-of-the-art low-energy and low-thrust methods. Essential mechanisms of the various utilized dynamic models and the characteristics of the different design methods are discussed in hopes of helping readers grasp the basic overview of the current Earth-Moon transfer orbit design methods and a deep academic background is unnecessary for the context understanding.

show abstract

“…Peng et al [14] studied the parameter characteristics of the hybrid lunar transfer orbit and discussed the extension of the RD of the lunar surface. Li et al [16] proposed the multi-segment FRO that was composed of the two-segment FROs and it could extend the RD of the lunar surface compared with the one-segment FRO. He et al [17] studied the solution set of the Sun-perturbed optimal two-impulse trans-lunar orbit.…”

Section: Introductionmentioning

confidence: 99%

Fast Solution to the Free Return Orbit's Reachable Domain of the Manned Lunar Mission by Deep Neural Network

Yang,

Li,

Zhang

et al. 2024

J. of Syst. Eng. Electron.

Self Cite

View full text Add to dashboard Cite

It is important to calculate the reachable domain (RD) of the manned lunar mission to evaluate whether a lunar landing site could be reached by the spacecraft. In this paper, the RD of free return orbits is quickly evaluated and calculated via the classification and regression neural networks. An efficient databasegeneration method is developed for obtaining eight types of free return orbits and then the RD is defined by the orbit's inclination and right ascension of ascending node (RAAN) at the perilune. A classify neural network and a regression network are trained respectively. The former is built for classifying the type of the RD, and the latter is built for calculating the inclination and RAAN of the RD. The simulation results show that two neural networks are well trained. The classification model has an accuracy of more than 99% and the mean square error of the regression model is less than on the test set. Moreover, a serial strategy is proposed to combine the two surrogate models and a recognition tool is built to evaluate whether a lunar site could be reached. The proposed deep learning method shows the superiority in computation efficiency compared with the traditional double two-body model.

show abstract

Solution Domain Analysis of Earth-Moon Quasi-Symmetric Free-Return Orbits

Cited by 11 publications

References 13 publications

Multiphase Trajectory Optimization of a Lunar Return Mission to an LEO Space Station

Multiphase Trajectory Optimization of a Lunar Return Mission to an LEO Space Station

Overview of Earth-Moon Transfer Trajectory Modeling and Design

Fast Solution to the Free Return Orbit's Reachable Domain of the Manned Lunar Mission by Deep Neural Network

Contact Info

Product

Resources

About