Abstract

With the increasing complexity of modern aircraft technology and tight coupling among subsystems, the design of aircraft requires collaborative work of experts in various fields to make the right decisions, and therefore achieve the expected performance with less cost and risk. In this paper, an agile decision support system (ADSS) for aircraft design was proposed by comprehensively integrating and applying modeling and simulation (M&S), artificial intelligence, data mining, and group decision-making technology. The ADSS provides a rich set of simulation, assessment, and optimization tools for decision makers, which can offer an important objective reference to effectively improve the decision accuracy. A simulation and test environment was implemented for rapid assessment of different designs based on the developed multidisciplinary and multiphysical coupling virtual prototyping models and three kinds of virtual test methods. In the process of group decision making, valuable application modes can be discovered through data mining to reduce decision-making difficulty and improve the efficiency. Furthermore, a sensitivity analysis–based multilevel optimization strategy was developed for high-dimensional optimization design problems to meet the fast response requirement of the ADSS. Different cases were given for the data mining application, virtual test, and optimization design, respectively, to validate the proposed agile decision-making process.

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Go to Journal of Aerospace Engineering
Journal of Aerospace Engineering
Volume 29Issue 2March 2016

History

Received: Oct 3, 2014
Accepted: Apr 9, 2015
Published online: Aug 13, 2015
Discussion open until: Jan 13, 2016
Published in print: Mar 1, 2016

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Ni Li, Ph.D. [email protected]
Associate Professor, School of Automation Science and Electrical Engineering, Research Field: System Modeling and Simulation, Virtual Prototyping, Beihang Univ., Haidian District, Beijing 100191, China. E-mail: [email protected]
Runxiang Tan [email protected]
Master Student, School of Automation Science and Electrical Engineering, Research Field: Group Decision-Making, Beihang Univ., Haidian District, Beijing 100191, China. E-mail: [email protected]
Zhanpeng Huang [email protected]
Ph.D. Student, School of Automation Science and Electrical Engineering, Research Field: Virtual Prototyping, Virtual Reality, Beihang Univ., Haidian District, Beijing 100191, China (corresponding author). E-mail: [email protected]
Ph.D. Student, School of Automation Science and Electrical Engineering, Research Field: Virtual Prototyping, Beihang Univ., Haidian District, Beijing 100191, China. E-mail: [email protected]
Guanghong Gong, Ph.D. [email protected]
Professsor, School of Automation Science and Electrical Engineering, Research Field: Complex System Modeling, Beihang Univ., Haidian District, Beijing 100191, China. E-mail: [email protected]

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