Time sorting filtering algorithm for deep space mission planning

2014 ◽  
Author(s):  
D.X. Chen ◽  
R. Xu ◽  
P.Y. Cui
Keyword(s):  
Space Mission ◽  
Mission Planning ◽  
Deep Space ◽  
Filtering Algorithm

scholarly journals An advance in transfer line chilldown heat transfer of cryogenic propellants in microgravity using microfilm coating for enabling deep space exploration

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
J. N. Chung ◽  
Jun Dong ◽  
Hao Wang ◽  
S. R. Darr ◽  
J. W. Hartwig
Keyword(s):  
Space Exploration ◽  
Fluid Management ◽  
Microgravity Condition ◽  
Space Mission ◽  
Low Earth Orbit ◽  
Earth Orbit ◽  
Deep Space ◽  
Deep Space Exploration ◽  
Quenching Efficiency ◽  
Proper Perspective

AbstractThe extension of human space exploration from a low earth orbit to a high earth orbit, then to Moon, Mars, and possibly asteroids is NASA’s biggest challenge for the new millennium. Integral to this mission is the effective, sufficient, and reliable supply of cryogenic propellant fluids. Therefore, highly energy-efficient thermal-fluid management breakthrough concepts to conserve and minimize the cryogen consumption have become the focus of research and development, especially for the deep space mission to mars. Here we introduce such a concept and demonstrate its feasibility in parabolic flights under a simulated space microgravity condition. We show that by coating the inner surface of a cryogenic propellant transfer pipe with low-thermal conductivity microfilms, the quenching efficiency can be increased up to 176% over that of the traditional bare-surface pipe for the thermal management process of chilling down the transfer pipe. To put this into proper perspective, the much higher efficiency translates into a 65% savings in propellant consumption.

scholarly journals A GA-SA Hybrid Planning Algorithm Combined with Improved Clustering for LEO Observation Satellite Missions

Algorithms ◽  
2019 ◽  
Vol 12 (11) ◽  
pp. 231
Author(s):  
Xiangyu Long ◽  
Shufan Wu ◽  
Xiaofeng Wu ◽  
Yixin Huang ◽  
Zhongcheng Mu
Keyword(s):  
Clustering Algorithm ◽  
Simulated Annealing Algorithm ◽  
Space Mission ◽  
Theory Model ◽  
Low Earth Orbit ◽  
Mission Planning ◽  
Experimental Simulation ◽  
Two Phase ◽  
Fitness Value ◽  
Planning Algorithm

This paper presents a space mission planning tool, which was developed for LEO (Low Earth Orbit) observation satellites. The tool is focused on a two-phase planning strategy with clustering preprocessing and mission planning, where an improved clustering algorithm is applied, and a hybrid algorithm that combines the genetic algorithm with the simulated annealing algorithm (GA–SA) is given and discussed. Experimental simulation studies demonstrate that the GA–SA algorithm with the improved clique partition algorithm based on the graph theory model exhibits higher fitness value and better optimization performance and reliability than the GA or SA algorithms alone.

Enabling Antenna Systems for Extreme Deep-Space Mission Applications

2007 ◽  
Vol 95 (10) ◽  
pp. 1976-1985 ◽  
Author(s):  
Ron Schulze ◽  
Robert E. Wallis ◽  
Robert K. Stilwell ◽  
Weilun Cheng
Keyword(s):  
Space Mission ◽  
Deep Space ◽  
Antenna Systems

Messenger: Flight Software Design for a Deep Space Mission

2007 ◽  
Author(s):  
David A. Artis ◽  
Brian K. Heggestad ◽  
Christopher J. Krupiarz ◽  
M. Annette Mirantes ◽  
J. Doug Reid
Keyword(s):  
Software Design ◽  
Space Mission ◽  
Deep Space
Sign in / Sign up

Export Citation Format

Share Document