摘要
研究了小型采样器在月表低气压低重力环境下对浅层月壤的铲挖阻力预测及参数优选问题。通过分析采样器铲斗—月壤间的相互作用,结合三轴试验仿真得出的月壤抗剪特性和弹塑性本构关系,分别对采样器的铲斗底面推移阻力和侧壁切削阻力进行了推导,实现了对月壤铲挖阻力的预测。在此基础上,以月壤铲挖阻力和收集速率为评价依据,针对0.2m深度以内的浅层月壤采样任务,利用自适应遗传算法确定了不同尺寸铲斗的最优铲挖参数。仿真结果表明,不同铲宽的月壤采样器均对应存在一个最优的铲挖深度和铲挖角,并且随着铲宽的增加,最优铲挖深度逐渐变大,最优铲挖角逐渐变小。
Research on the minitype sampler' s excavation resistance model of lunar regolith and the optimization of excavation parameters under low-gravity and low atmospheric pressure environment is conducted in this paper. The prediction model of lunar regolith excavation resistance is established, the soil cutting force and the soil penetration force are derived combined with the shear characteristics of lunar soil and its' elastic-plastic constitutive from the triaxial test simulation. On the basis of this model, for the purpose of lower resistance and higher collect ratio, optimal blade angle and blade depth in different bucket widths suitable for the lunar regolith sampling mission are determined by using the self- adapting genetic algorithm. The simulation results indicate that optimal blade angle and blade depth corresponding to different blade widths exist. With increase of the blade width, the optimal blade depth becomes larger, and the blade angle becomes smaller.
出处
《宇航学报》
EI
CAS
CSCD
北大核心
2014年第1期39-46,共8页
Journal of Astronautics
基金
教育部博士点基金(20112302120007)
国家自然科学基金(51105100)
关键词
浅层月壤
铲挖阻力
小型采样器
自适应遗传算法
多目标优化
Lunar regolith
Excavation resistance
Minitype sampler
Self-adapting genetic algorithm
Multi-objective optimization