Surrogate Modeling and Parametric Optimization Strategy for Minimizing Sonic Boom in a Morphing Aircraft

This paper presents a multidisciplinary optimization framework developed by the authors and applied to small-size supersonic aircraft. The multidisciplinary analysis suite is based on the combination of low (empirical) and high-fidelity computational fluid dynamics (CFD) and computational structure mechanics (CSM) tools for predicting the overall aircraft performance and the sonic boom overpressure at supersonic flight, which represents the most challenging environmental constraint for supersonic aircraft. The analysis suite is coupled with a multi-objective optimization strategy for quantifying the trade-off between the maximum take-off weight, mission range, and the sonic boom overpressure. The optimization framework is applied to a small-size supersonic business-jet cruising at Mach number M = 1.8 and featuring a double delta wing. The trade-offs between disciplines are well captured and an optimized configuration achieving the target mission range with a lower maximum take-off weight, and a moderate sonic boom signature is obtained through changes in wing dihedral and sweep. A more drastic reduction of the sonic boom signature is also obtained but at the cost of a significant reduction of the aircraft performance.

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Performance evaluation and parametric optimization strategy of a thermocapacitive heat engine to harvest low-grade heat

Energy Conversion and Management ◽

10.1016/j.enconman.2019.01.012 ◽

2019 ◽

Vol 184 ◽

pp. 40-47 ◽

Cited By ~ 4

Author(s):

Jian Lin ◽

Zhihui Zhang ◽

Xingyi Zhu ◽

Chao Meng ◽

Ning Li ◽

...

Keyword(s):

Performance Evaluation ◽

Parametric Optimization ◽

Heat Engine ◽

Low Grade ◽

Optimization Strategy ◽

Low Grade Heat

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Onboard Trajectory Generation of Hypersonic Morphing Aircraft

International Journal of Aerospace Engineering ◽

10.1155/2021/6683684 ◽

2021 ◽

Vol 2021 ◽

pp. 1-11

Author(s):

Chenxin Zhang ◽

Yankun Zhang ◽

Changzhu Wei

Keyword(s):

Trajectory Optimization ◽

Pseudospectral Method ◽

Mean Value ◽

Optimization Strategy ◽

Initial State ◽

Morphing Aircraft ◽

Initial Errors ◽

Aerodynamic Model ◽

Gauss Pseudospectral Method ◽

Trajectory Database

In this paper, a trajectory optimization strategy for the hypersonic morphing aircraft is proposed, and the AMPI method is used to generate the online trajectory with initial state errors. Firstly, the aerodynamic model and propulsion model of the hypersonic morphing aircraft were established considering the wingspan and the scramjet. Secondly, the optimization strategy was proposed via Gauss pseudospectral method considering the control variables including angle of attack (AOA) and wingspan. The optimized trajectory met the final constraints and path constraints with the objective to minimize the time of the ascent phase. Then, the AMPI method was used to generate online trajectory without solving OCP or NLP on the base of trajectory database calculated by the optimization strategy. The simulation results indicate high accuracy of AMPI method and the final errors corresponding to different initial errors were acceptable. The mean value of the CPU time of the method was about 0.1 second, which shows real-time capability.

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Conceptual Morphing Aircraft Sizing Using a Multi-Level Optimization Strategy

46th AIAA Aerospace Sciences Meeting and Exhibit ◽

10.2514/6.2008-166 ◽

2008 ◽

Author(s):

Michael Skillen ◽

William Crossley

Keyword(s):

Optimization Strategy ◽

Morphing Aircraft ◽

Multi Level ◽

Aircraft Sizing

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Improving the effectiveness of traditional education based on computer artificial intelligence and neural network system

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189249 ◽

2020 ◽

pp. 1-11

Author(s):

Wenjuan Ma ◽

Xuesi Zhao ◽

Yuxiu Guo

Keyword(s):

Neural Network ◽

Artificial Intelligence ◽

Education Reform ◽

Traditional Education ◽

Machine Learning Algorithms ◽

Local Optimum ◽

Optimization Strategy ◽

Fish School ◽

Tlbo Algorithm ◽

Neural Network System

The application of artificial intelligence and machine learning algorithms in education reform is an inevitable trend of teaching development. In order to improve the teaching intelligence, this paper builds an auxiliary teaching system based on computer artificial intelligence and neural network based on the traditional teaching model. Moreover, in this paper, the optimization strategy is adopted in the TLBO algorithm to reduce the running time of the algorithm, and the extracurricular learning mechanism is introduced to increase the adjustable parameters, which is conducive to the algorithm jumping out of the local optimum. In addition, in this paper, the crowding factor in the fish school algorithm is used to define the degree or restraint of teachers’ control over students. At the same time, students in the crowded range gather near the teacher, and some students who are difficult to restrain perform the following behavior to follow the top students. Finally, this study builds a model based on actual needs, and designs a control experiment to verify the system performance. The results show that the system constructed in this paper has good performance and can provide a theoretical reference for related research.

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