A multi-objective, multidisciplinary design optimization methodology for the conceptual design of a spacecraft bi-propellant propulsion system

Fazeley, H. R.; Taei, Hojat; Naseh, Hassan; Mirshams, Mehran

doi:10.1007/s00158-015-1304-2

Cited by 18 publications

(7 citation statements)

References 17 publications

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“…Richie et al [4] introduced an efficient, structured approach for the optimization of satellite attitude and orbit control as well as power subsystem. Fazeley et al [5] applied a multiobjective and multidisciplinary optimization method to the design of a bipropellant propulsion system of a spacecraft. In conclusion, the current researches mainly focus on three parts: (1) the optimization of the system parameters such as orbit, payload, mass, and power; (2) the selection of important schemes for the subsystems; and (3) the component level optimization of each subsystem.…”

Section: Introductionmentioning

confidence: 99%

Genetic Programming Method for Satellite System Topology and Parameter Optimization

Dong

et al. 2020

International Journal of Aerospace Engineering

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In this paper, a genetic programming method for satellite system design is proposed to simultaneously optimize the topology and parameters of a satellite system. Firstly, the representation of satellite system design is defined according to the tree structure. The genetic programming method is designed based on that representation. Secondly, according to the tree structure of different satellite schemes, different multiscale satellite models are established, in which various physical fields couple together. Then, an evaluation system is also proposed to test the performances of different satellite schemes. Finally, the application to the design of an earth observation satellite demonstrates the effectiveness of the proposed method.

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Section: Introductionmentioning

confidence: 99%

Genetic Programming Method for Satellite System Topology and Parameter Optimization

Dong

et al. 2020

International Journal of Aerospace Engineering

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“…It is defined by the nozzle design parameters' minimum and maximum limits. Achieving the highest possible efficiency, along with the lowest mass and power consumption, are the most common goals of the designers of space systems (Fazeley et al, 2016). In this study the performance, mass and pressure drop of the catalyst bed are considered as the design objective.…”

Section: Design Parameter and Design Criteriamentioning

confidence: 99%

A kriging based multi objective gray wolf optimization for hydrazine catalyst bed

Meibody¹,

Naseh²,

Ommi³

2019

10.5267/j.esm

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The main aim of this paper is to present a novel multi-objective gray wolf optimization (MOGWO) by utilizing the Kriging meta-model. To this end, surrogate models are used in Multi-Objective Gray Wolf Optimizer as the fitness function. The meta-model is obtained based on exact analysis and numerical simulations. Inheritable Latin Hypercube Design (ILHD) is used as the design of experiments for generation and testing the Kriging model. Then, sensitivity analysis is done to evaluate the effect of design parameter on system responses. The sensitivity analysis leads to appropriate selection of optimization design variables. Hence, the MOGWO algorithm is applied to the problem, the set of non-dominated optimal points are obtained as Pareto Front and one optimal point is selected based on the minimum distance approach. The most important purpose of the methodology is to improve the time consuming in multi-objective optimization problems. In conclusion, for the design of hydrazine catalyst bed was utilized from the proposed methodology. In case, design variables are catalyst bed pellet diameter, loading factor, thrust chamber pressure and Reaction efficiency and objective functions are increasing performance and reducing mass and pressure drop. The results of optimal catalyst bed parameters and also corresponding value of objective functions are shown the performance of methodology in the space propulsion system applications.

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“…Several multi-objective MDO approaches for launch vehicle design have been investigated in the literature [3][4][5]. Castellini et al [3] proposed a comparison of seven population-based algorithms (e.g.…”

Section: Introductionmentioning

confidence: 99%

Surrogate model-based multi-objective MDO approach for partially Reusable Launch Vehicle design

Brevault¹,

Balesdent²,

Hebbal³

et al. 2019

AIAA Scitech 2019 Forum

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Reusability of the first stage of launch vehicles may offer new perspectives to lower the cost of payload injection into orbit if sufficient reliability and low refurbishment costs can be achieved. One possible option that may be explored is to design the launch vehicle first stage for both reusable and expendable uses, in order to increase the flexibility and adaptability to different target missions. This paper proposes a multi-level MDO approach to design aerospace vehicles addressing multi-mission problems. The proposed approach is focused on the design of a family of launchers for different missions sharing commonalities using multi-objective Bayesian Optimization to account for the computational cost associated with the discipline simulations. The multi-mission problem addressed in this paper considers two missions: a reusable configuration for a SSO orbit with a medium payload range and recovery of the first stage using a glider strategy; and an expendable configuration for a medium payload injected into a Geostationary Transfer Orbit (GTO). A dedicated MDO formulation introducing couplings between the missions is proposed in order to efficiently solve the multi-objective MDO problem while limiting the number of calls to the exact MDA thanks to the use of Gaussian Processes and multi-objective Efficient Global Optimization.

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A multi-objective, multidisciplinary design optimization methodology for the conceptual design of a spacecraft bi-propellant propulsion system

Cited by 18 publications

References 17 publications

Genetic Programming Method for Satellite System Topology and Parameter Optimization

Genetic Programming Method for Satellite System Topology and Parameter Optimization

A kriging based multi objective gray wolf optimization for hydrazine catalyst bed

Surrogate model-based multi-objective MDO approach for partially Reusable Launch Vehicle design

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