Plume aerodynamic effects of cushion engine in lunar landing

During the second period of China ＂Tanyue＂ Project, the explorer will softland on the moon. The cushion engines are used to decelerate the explorer and reduce the impact on the lunar ground. It is necessary to study its plume effects on the explorer component. The self-developed PWS （Plume WorkStation） software based on direct simulation Monte Carlo （DSMC） method is used to simulate the plume effects of two 150 N engines. Due to the complex structure of the explorer, PWS uses a decoupling method to treat the boundary mesh, which mainly interacts with simulation particles, and has no relation with the computational grids. After the analytical expressions of plane surfaces and curved surfaces of each boundary block are given, the particle position within or without the boundary blocks can be easily determined. Finally the 3D plume field of two 150 N engines is simulated. The pressure, temperature and velocity distributions of plume field are clearly presented by three characteristic slices. The aerodynamic effects on the explorer bottom, the landfall legs and antenna are separately shown. The compression influence on the plume flow of four landfall legs can be observed.

Uncertainty analysis and probabilistic design optimization of hybrid rocket motors for manned lunar landing

To obtain a conceptual design for a hybrid rocket motor(HRM)to be used as the Ascent Propulsion System in the Apollo lunar module,the deterministic design optimization(DDO)method is applied to the HRM design.Based on the results of an uncertainty analysis of HRMs,an uncertainty-based design optimization(UDO)method is also adopted to improve the design reliability.The HRM design process,which is a multidisciplinary system,is analyzed,and a mathematical model for the system design is established to compute the motor performance from the input parameters,including the input variables and model parameters.The input parameter uncertainties are quantified,and a sensitivity analysis of the model parameter uncertainties is conducted to identify the most important model parameter uncertainties for HRMs.The DDO and probabilistic UDO methods are applied to conceptual designs for an HRM to be used as a substitute for the liquid rocket motor(LRM)of the Ascent Propulsion System.The conceptual design results show that HRMs have several advantages as an alternative to the LRM of the Ascent Propulsion System,including nontoxic propellant combination,small motor volume,and comparable functions,such as restarting and throating.Comparisons of the DDO and UDO results indicate that the UDO method achieves more robust and reliable optimal designs than the DDO method.The probabilistic UDO method can be used to develop better conceptual designs for HRMs.

Characteristic analysis and design of near moon abort trajectory for manned lunar landing mission

The safety of astronauts would be severely threatened if the lunar-landing spacecraft were under an emergency during the near moon phase of flight, which was far from the Earth. For the problem of mission abort caused by the main engine (service propulsion system, SPS) failure during lunar orbit insertion, firstly, the family of trajectories resulted from SPS premature shutdown and corresponding abort trajectories were analyzed; then an algorithm that can be applied to the near moon abort trajectories was proposed using patched-conic technique. The characteristics of the abort trajectory, such as energy consumption and return time of flight, were analyzed and presented. Finally, simulation examples were given to demonstrate various cases of near moon SPS failure. The results of the simulation have validated the approach proposed.

Hybrid uncertainty-based design optimization and its application to hybrid rocket motors for manned lunar landing

Design reliability and robustness are getting increasingly important for the general design of aerospace systems with many inherently uncertain design parameters.This paper presents a hybrid uncertainty-based design optimization（UDO） method developed from probability theory and interval theory.Most of the uncertain design parameters which have sufficient information or experimental data are classified as random variables using probability theory,while the others are defined as interval variables with interval theory.Then a hybrid uncertainty analysis method based on Monte Carlo simulation and Taylor series interval analysis is developed to obtain the uncertainty propagation from the design parameters to system responses.Three design optimization strategies,including deterministic design optimization（DDO）,probabilistic UDO and hybrid UDO,are applied to the conceptual design of a hybrid rocket motor（HRM） used as the ascent propulsion system in Apollo lunar module.By comparison,the hybrid UDO is a feasible method and can be effectively applied to the general design of aerospace systems.

Neuro-Optimal Guidance Control for Lunar Soft Landing

Returning to moon has become a top topic recently. Many studies have shown that soft landing is a challenging problem in lunar exploration. The lunar soft landing in this paper begins from a 100 km circular lunar parking orbit. Once the landing area has been selected and it is time to deorbit for landing, a ΔV burn of 19.4 m/s is performed to establish a 100×15 km elliptical orbit. At perilune, the landing jets are ignited, and a propulsive landing is performed. A guidance and control scheme for lunar soft landing is proposed in the paper, which combines optimal theory with nonlinear neuro-control. Basically, an optimal nonlinear control law based on artificial neural network is presented, on the basis of the optimum trajectory from perilune to lunar surface in terms of Pontryagin's maximum principle according to the terminal boundary conditions and performance index. Therefore some optimal control laws can be carried out in the soft landing system due to the nonlinear mapping function of the neural network. The feasibility and validity of the control laws are verified in a simulation experiment.

Direct dynamic-simulation approach to trajectory optimization

This paper proposes a new direct method for an efficient trajectory optimization using the point that the dynamics of a deterministic system are uniquely determined by initial states and controls imposed over the time horizon of interest.To effectively implement this concept,the Hermite spline is adopted to interpolate the continuous controls and the system dynamics are integrated with corresponding control parameters in prior.As a result,the optimal control problem can be transcribed into a nonlinear programming problem which has no dynamic equality constraints and no intermediate states in its design variables.In addition,the paper proposes an efficient recursive Jacobian estimation technique and introduces a Jacobian transformation matrix to straightforwardly handle the general state constraints.Important properties of the present method are thoroughly investigated through its applications to the trajectory optimization for a soft lunar landing from a parking orbit,including the detailed analyses for the de-orbiting phase.The computed results are compared with those using the pseudo-spectral method to demonstrate an extreme outperformance of the proposed method in the aerospace applications over the traditional direct method.