TY - GEN
T1 - Enriching On-orbit Servicing Mission Planning with Debris Recycling and In-space Additive Manufacturing
AU - Jie, Bai
AU - Tao, Chao
AU - Ping, Ma
AU - Ming, Yang
AU - Songyan, Wang
N1 - Publisher Copyright:
© 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2024
Y1 - 2024
N2 - On-orbit servicing (OOS) is a crucial research area with vast application prospects. There is currently a lack of studies focusing on a novel type of OOS scenario. In this scenario, In-Space Additive Manufacturing (ISAM) and Debris Recycling (DR) are incorporated into OOS. Traditional OOS obtains the necessary products for failed satellites through recycling space debris and ISAM, thereby improving sustainability and efficiency in the servicing process. We construct an optimization model. In this model, the total cost of velocity is chosen as the optimization objective. And mission sequences, orbital transfer time, service position, and service time are considered as design variables. Compared to traditional OOS, the novel optimization model is more prone to trapping optimizers in local optima. Therefore, we employ the Whale Optimization Algorithm (WOA) due to its ability to escape local optima. Simulation results demonstrate the effectiveness of the optimization model we have developed in representing the novel problem accurately. Moreover, the solution obtained through the utilization of the WOA closely approximates the optimal solution.
AB - On-orbit servicing (OOS) is a crucial research area with vast application prospects. There is currently a lack of studies focusing on a novel type of OOS scenario. In this scenario, In-Space Additive Manufacturing (ISAM) and Debris Recycling (DR) are incorporated into OOS. Traditional OOS obtains the necessary products for failed satellites through recycling space debris and ISAM, thereby improving sustainability and efficiency in the servicing process. We construct an optimization model. In this model, the total cost of velocity is chosen as the optimization objective. And mission sequences, orbital transfer time, service position, and service time are considered as design variables. Compared to traditional OOS, the novel optimization model is more prone to trapping optimizers in local optima. Therefore, we employ the Whale Optimization Algorithm (WOA) due to its ability to escape local optima. Simulation results demonstrate the effectiveness of the optimization model we have developed in representing the novel problem accurately. Moreover, the solution obtained through the utilization of the WOA closely approximates the optimal solution.
KW - Debris recycling (DR)
KW - In-space additive manufacturing (ISAM)
KW - Mission Planning
KW - On-orbit Service (OOS)
KW - Whale Optimization Algorithm (WOA)
UR - https://www.scopus.com/pages/publications/85176287218
U2 - 10.1007/978-981-99-7243-2_8
DO - 10.1007/978-981-99-7243-2_8
M3 - 会议稿件
AN - SCOPUS:85176287218
SN - 9789819972425
T3 - Communications in Computer and Information Science
SP - 86
EP - 100
BT - Methods and Applications for Modeling and Simulation of Complex Systems - 22nd Asia Simulation Conference, AsiaSim 2023, Proceedings
A2 - Hassan, Fazilah
A2 - Sunar, Noorhazirah
A2 - Mohd Basri, Mohd Ariffanan
A2 - Mahmud, Mohd Saiful Azimi
A2 - Ishak, Mohamad Hafis Izran
A2 - Mohamed Ali, Mohamed Sultan
PB - Springer Science and Business Media Deutschland GmbH
T2 - 22nd Asia Simulation Conference, AsiaSim 2023
Y2 - 25 October 2023 through 26 October 2023
ER -