scholarly journals Mission Planning of GEO Active Debris Removal Based on Revolver Mode

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yong Zhao ◽  
Yi Cao ◽  
Yang Chen ◽  
Zhijun Chen ◽  
Yuzhu Bai
Keyword(s):  
Fuel Consumption ◽  
Mathematical Optimization ◽  
Orbit Space ◽  
Optimization Method ◽  
Mission Planning ◽  
Planning Problem ◽  
Active Debris Removal ◽  
Debris Removal ◽  
Transfer Orbit ◽  
Accelerated Particle Swarm Optimization

The mission planning of active debris removal (ADR) of revolver mode on geosynchronous orbit (GEO) is studied in this paper. It is assumed that there are one service satellite, one space depot, and some pieces of space debris in the ADR mission. The service satellite firstly rendezvouses with the debris and then releases the thruster deorbit kits (TDKs), which are carried with the satellite, to push the debris to the graveyard orbit. Space depot will provide replenishment for the service satellite. The purpose of this mission planning is to optimize the ADR sequence of the service satellite, which represents the chronological order, in which the service satellite approaches different debris. In this paper, the mission cost will be stated firstly, and then a mathematical optimization model is proposed. ADR sequence and orbital transfer time are used as designed variables, whereas the fuel consumption in the whole mission is regarded as objective for optimizing, and a specific number of TDKs is also a new constraint. Then, two-level optimization is proposed to solve the mission planning problem, which is low-level for finding optimal transfer orbit using accelerated particle swarm optimization (APSO) algorithm and up-level for finding best mission sequence using immune genetic (IGA) algorithm. Numerical simulations are carried out to demonstrate the effectiveness of the model and the optimization method. Results show that TDK number influences the fuel consumption through impacting the replenishing frequency and TDK redundancy. To reduce fuel consumption, the TDK number should be optimized and designed with suitable replenishing frequency and minimum TDK redundancy.

An Enhanced TSP-Based Approach for Active Debris Removal Mission Planning

2021 ◽  
pp. 140-154
Author(s):  
João Batista Rodrigues Neto ◽  
Gabriel de Oliveira Ramos
Keyword(s):  
Mission Planning ◽  
Active Debris Removal ◽  
Debris Removal

The effects of parking orbit elements on designing of on-orbit servicing missions

2017 ◽  
Vol 233 (3) ◽  
pp. 793-810 ◽  
Author(s):  
Majid Bakhtiari ◽  
Kamran Daneshjou ◽  
Abbas Ali Mohammadi-Dehabadi
Keyword(s):  
Fuel Consumption ◽  
Visual Inspection ◽  
Planning Process ◽  
Mission Planning ◽  
New Approach ◽  
Optimisation Algorithm ◽  
Transfer Orbits ◽  
Parking Orbit ◽  
Debris Removal ◽  
Particle Swarm Optimisation Algorithm

Nowadays on-orbit servicing operations such as satellite refuelling, debris removal and visual inspection are considered as the most important issues in the space missions. Mission planning has a key role on the designation of such missions and it is strongly dependent on the required fuel. In this study, a new approach is proposed for the designing of the on-orbit operations with considering the parking orbit elements and location of the servicing satellites. The proposed method improves the previous mission planning process of the multiple servicing satellites in the terms of the reduction in the mission fuel consumption. Furthermore, a special rendezvous maneuver is considered for meeting the servicing satellites and the targets. Also, the transfer orbits are obtained through Lambert targeting. The optimisation of the problem is carried out by particle swarm optimisation algorithm and Taguchi technique is employed for the robust design of the control parameters of the optimisation algorithm. The results reveal that the proposed approach is an efficient way in the reduction of the fuel consumption in the on-orbit servicing missions rather than the conventional methods.

Dimensioning a recovery boiler furnace using mathematical optimization

TAPPI Journal ◽  
2015 ◽  
Vol 14 (2) ◽  
pp. 119-129 ◽  
Author(s):  
VILJAMI MAAKALA ◽  
PASI MIIKKULAINEN
Keyword(s):  
Radial Basis Function Network ◽  
High Capacity ◽  
Mathematical Optimization ◽  
Optimization Procedure ◽  
Optimization Method ◽  
Performance Criteria ◽  
Boiler Furnace ◽  
Starting Point ◽  
Recovery Boiler ◽  
Base Design

Capacities of the largest new recovery boilers are steadily rising, and there is every reason to expect this trend to continue. However, the furnace designs for these large boilers have not been optimized and, in general, are based on semiheuristic rules and experience with smaller boilers. We present a multiobjective optimization code suitable for diverse optimization tasks and use it to dimension a high-capacity recovery boiler furnace. The objective was to find the furnace dimensions (width, depth, and height) that optimize eight performance criteria while satisfying additional inequality constraints. The optimization procedure was carried out in a fully automatic manner by means of the code, which is based on a genetic algorithm optimization method and a radial basis function network surrogate model. The code was coupled with a recovery boiler furnace computational fluid dynamics model that was used to obtain performance information on the individual furnace designs considered. The optimization code found numerous furnace geometries that deliver better performance than the base design, which was taken as a starting point. We propose one of these as a better design for the high-capacity recovery boiler. In particular, the proposed design reduces the number of liquor particles landing on the walls by 37%, the average carbon monoxide (CO) content at nose level by 81%, and the regions of high CO content at nose level by 78% from the values obtained with the base design. We show that optimizing the furnace design can significantly improve recovery boiler performance.

Electromagnetic-launch-based method for cost-efficient space debris removal

2020 ◽  
Vol 29 (1) ◽  
pp. 94-106
Author(s):  
Chongyuan Hou ◽  
Yuan Yang ◽  
Yikang Yang ◽  
Kaizhong Yang ◽  
Xiao Zhang ◽  
...  
Keyword(s):  
Space Debris ◽  
Orbit Space ◽  
Low Earth Orbit ◽  
Research Progress ◽  
Area Of Interest ◽  
Electromagnetic Launch ◽  
Debris Removal ◽  
Significant Research ◽  
Electromagnetic Launcher ◽  
Cost Efficient

AbstractThe increase in space debris orbiting Earth is a critical problem for future space missions. Space debris removal has thus become an area of interest, and significant research progress is being made in this field. However, the exorbitant cost of space debris removal missions is a major concern for commercial space companies. We therefore propose the debris removal using electromagnetic launcher (DREL) system, a ground-based electromagnetic launch system (railgun), for space debris removal missions. The DREL system has three components: a ground-based electromagnetic launcher (GEML), suborbital vehicle (SOV), and mass of micrometer-scale dust (MSD) particles. The average cost of removing a piece of low-earth orbit space debris using DREL was found to be approximately USD 160,000. The DREL method is thus shown to be economical; the total cost to remove more than 2,000 pieces of debris in a cluster was only approximately USD 400 million, compared to the millions of dollars required to remove just one or two pieces of debris using a conventional space debris removal mission. By using DREL, the cost of entering space is negligible, thereby enabling countries to remove their space debris in an affordable manner.

scholarly journals Modeling and Simulation of Mission Planning Problem for Remote Sensing Satellite Imaging

2018 ◽  
Vol 179 ◽  
pp. 03024 ◽  
Author(s):  
Yao Pan ◽  
Zhong Ming Chi ◽  
Qi Long Rao ◽  
Kai Peng Sun ◽  
Yi Nan Liu
Keyword(s):  
Remote Sensing ◽  
Time Window ◽  
Constraint Satisfaction Problem ◽  
Optimal Path ◽  
Time Constraint ◽  
Mission Planning ◽  
Planning Problem ◽  
Satellite Imaging ◽  
Problem Model ◽  
Remote Sensing Satellite

Mission planning problem for remote sensing satellite imaging is studied. Firstly, the time constraint satisfaction problem model is presented after analyzing the characteristic of time constraint. Then, An optimal path searching algorithm based on the discrete time window is proposed according to the non-uniqueness for satellite to mission in the visible time window. Simulation results verify the efficiency of the model and algorithm.

Satellite System Design Considering the Blocking Effect: Application to Active Debris Removal

2021 ◽  
pp. 1-9
Author(s):  
Yusuke Oki ◽  
Hiroyuki Okamoto ◽  
Takahiro Sasaki ◽  
Toru Yamamoto ◽  
Keiichi Wada
Keyword(s):  
System Design ◽  
Satellite System ◽  
Blocking Effect ◽  
Active Debris Removal ◽  
Debris Removal

Active Debris Removal for Mega-constellation Reliability

2020 ◽  
pp. 1043-1061
Author(s):  
Nikita Veliev ◽  
Anton Ivanov ◽  
Shamil Biktimirov
Keyword(s):  
Active Debris Removal ◽  
Debris Removal
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