Sinking Velocity Impact-Analysis for the Carrier-Based Aircraft Using the Response Surface Method-Based Improved Kriging Algorithm

The deck landing sinking velocity of carrier-based aircraft is affected by carrier attitude, sea condition, aircraft performance, etc. Its impact analysis is a complex nonlinear problem, and there even is some contradictory phenomenon that when the approach velocity increases, the sinking velocity d...

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Main Authors: Xiao-Feng Xue, Yuan-Zhuo Wang, Cheng Lu, Zhang Yun-Peng
Format: Article
Language:English
Published: Hindawi Limited 2020-01-01
Series:Advances in Materials Science and Engineering
Online Access:http://dx.doi.org/10.1155/2020/5649492
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spelling doaj-4c6b4743c60247ccb6b2c4f698b385e92020-11-25T02:06:17ZengHindawi LimitedAdvances in Materials Science and Engineering1687-84341687-84422020-01-01202010.1155/2020/56494925649492Sinking Velocity Impact-Analysis for the Carrier-Based Aircraft Using the Response Surface Method-Based Improved Kriging AlgorithmXiao-Feng Xue0Yuan-Zhuo Wang1Cheng Lu2Zhang Yun-Peng3School of Aeronautics, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Astronautics, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Aeronautics, Northwestern Polytechnical University, Xi’an 710072, ChinaSchool of Aeronautics, Northwestern Polytechnical University, Xi’an 710072, ChinaThe deck landing sinking velocity of carrier-based aircraft is affected by carrier attitude, sea condition, aircraft performance, etc. Its impact analysis is a complex nonlinear problem, and there even is some contradictory phenomenon that when the approach velocity increases, the sinking velocity decreases under certain circumstances. Aiming at exploring the impact of the various related deck landing parameters on sinking velocity for carrier-based aircraft in the actual environment, response surface method-based improved Kriging algorithm (IK-RSM) is proposed based on genetic algorithm and Kriging model. Based on the deck landing measured data of the F/A-18A aircraft in the actual operating environment, the impact degree of the 15 deck landing parameters on the sinking velocity is explored, respectively, by using the partial correlation analysis of multivariate statistical theory and the IK-RSM. It can be found that the 4 parameters are strongly correlated with the sinking velocity; that is, the aircraft glide angle and deck pitch angle are highly correlated with the sinking velocity; next, the approach velocity and the engaging velocity are moderately correlated with the sinking velocity. The 4 parameters above could be used to establish the impact analysis model of the sinking velocity. The genetic algorithm is applied to the correction coefficients optimization of the IK-RSM’s kernel functions, and the IK-RSM of the F/A-18A aircraft sinking velocity is formed. Compared with the Kriging model and the empirical formula, the sinking velocity prediction accuracy indexes of IK-RSM are the best; for example, the determination coefficient is 0.981, the mean relative error is 1.813%, and the maximum relative error is 6.771%. Furthermore, based on the sinking velocity IK-RSM and the sensitivity analysis method proposed, we have explained the reason for the contradictory phenomenon that when the approach velocity increases, the sinking velocity decreases at some samples. It could provide certain technical support for the flight attitude control related to the sinking velocity during the actual flight of carrier-based aircraft.http://dx.doi.org/10.1155/2020/5649492
collection DOAJ
language English
format Article
sources DOAJ
author Xiao-Feng Xue
Yuan-Zhuo Wang
Cheng Lu
Zhang Yun-Peng
spellingShingle Xiao-Feng Xue
Yuan-Zhuo Wang
Cheng Lu
Zhang Yun-Peng
Sinking Velocity Impact-Analysis for the Carrier-Based Aircraft Using the Response Surface Method-Based Improved Kriging Algorithm
Advances in Materials Science and Engineering
author_facet Xiao-Feng Xue
Yuan-Zhuo Wang
Cheng Lu
Zhang Yun-Peng
author_sort Xiao-Feng Xue
title Sinking Velocity Impact-Analysis for the Carrier-Based Aircraft Using the Response Surface Method-Based Improved Kriging Algorithm
title_short Sinking Velocity Impact-Analysis for the Carrier-Based Aircraft Using the Response Surface Method-Based Improved Kriging Algorithm
title_full Sinking Velocity Impact-Analysis for the Carrier-Based Aircraft Using the Response Surface Method-Based Improved Kriging Algorithm
title_fullStr Sinking Velocity Impact-Analysis for the Carrier-Based Aircraft Using the Response Surface Method-Based Improved Kriging Algorithm
title_full_unstemmed Sinking Velocity Impact-Analysis for the Carrier-Based Aircraft Using the Response Surface Method-Based Improved Kriging Algorithm
title_sort sinking velocity impact-analysis for the carrier-based aircraft using the response surface method-based improved kriging algorithm
publisher Hindawi Limited
series Advances in Materials Science and Engineering
issn 1687-8434
1687-8442
publishDate 2020-01-01
description The deck landing sinking velocity of carrier-based aircraft is affected by carrier attitude, sea condition, aircraft performance, etc. Its impact analysis is a complex nonlinear problem, and there even is some contradictory phenomenon that when the approach velocity increases, the sinking velocity decreases under certain circumstances. Aiming at exploring the impact of the various related deck landing parameters on sinking velocity for carrier-based aircraft in the actual environment, response surface method-based improved Kriging algorithm (IK-RSM) is proposed based on genetic algorithm and Kriging model. Based on the deck landing measured data of the F/A-18A aircraft in the actual operating environment, the impact degree of the 15 deck landing parameters on the sinking velocity is explored, respectively, by using the partial correlation analysis of multivariate statistical theory and the IK-RSM. It can be found that the 4 parameters are strongly correlated with the sinking velocity; that is, the aircraft glide angle and deck pitch angle are highly correlated with the sinking velocity; next, the approach velocity and the engaging velocity are moderately correlated with the sinking velocity. The 4 parameters above could be used to establish the impact analysis model of the sinking velocity. The genetic algorithm is applied to the correction coefficients optimization of the IK-RSM’s kernel functions, and the IK-RSM of the F/A-18A aircraft sinking velocity is formed. Compared with the Kriging model and the empirical formula, the sinking velocity prediction accuracy indexes of IK-RSM are the best; for example, the determination coefficient is 0.981, the mean relative error is 1.813%, and the maximum relative error is 6.771%. Furthermore, based on the sinking velocity IK-RSM and the sensitivity analysis method proposed, we have explained the reason for the contradictory phenomenon that when the approach velocity increases, the sinking velocity decreases at some samples. It could provide certain technical support for the flight attitude control related to the sinking velocity during the actual flight of carrier-based aircraft.
url http://dx.doi.org/10.1155/2020/5649492
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