Optimal design for low sonic boom based on CoKriging surrogate model

Accurately predicting and effectively reducing sonic boom levels is one of the key issues in the development of the new generation of green supersonic civil aircraft. In order to improve the efficiency of low sonic boom optimal design for supersonic civil aircraft, a multi-fidelity optimal design pr...

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Main Authors: ZHANG Hanqi, XU Yue, ZHONG Min, LI Yan
Format: Article
Language:zho
Published: Editorial Department of Advances in Aeronautical Science and Engineering 2025-06-01
Series:Hangkong gongcheng jinzhan
Subjects:
Online Access:http://hkgcjz.cnjournals.com/hkgcjz/article/abstract/2023278
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author ZHANG Hanqi
XU Yue
ZHONG Min
LI Yan
author_facet ZHANG Hanqi
XU Yue
ZHONG Min
LI Yan
author_sort ZHANG Hanqi
collection DOAJ
description Accurately predicting and effectively reducing sonic boom levels is one of the key issues in the development of the new generation of green supersonic civil aircraft. In order to improve the efficiency of low sonic boom optimal design for supersonic civil aircraft, a multi-fidelity optimal design program for low sonic boom is developed based on the CoKriging surrogate model combined with fast sonic boom prediction method and high fidelity sonic boom prediction method. The sonic boom prediction results of the TU-144 model are basically consistent with the experimental results, verifying the reliability of the two prediction methods. A parameter sensitivity analysis and optimal design are conducted on the wing shape of a certain supersonic civil aircraft model. The results show that Stevens′ loudness level of the ground sonic boom is more sensitive to three parameters:the half span length of the outer wing, leading edge sweep angle of the outer wing, the half span length of the inner wing. After optimization, the maximum ground sonic boom overpressure is reduced by about 4 Pa, and the Stevens′ loudness level is reduced by 4.26 dB. Compared with the Kriging model that only uses high fidelity sample data, the CoKriging model integrates high and low fidelity sample data, saving about 43% of time cost while ensuring a certain prediction accuracy.
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institution OA Journals
issn 1674-8190
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publishDate 2025-06-01
publisher Editorial Department of Advances in Aeronautical Science and Engineering
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spelling doaj-art-f4c9bf8334c54b68a2b71e06aee8f5ee2025-08-20T02:39:03ZzhoEditorial Department of Advances in Aeronautical Science and EngineeringHangkong gongcheng jinzhan1674-81902025-06-011636069,8110.16615/j.cnki.1674-8190.2025.03.06hkgcjz-16-3-60Optimal design for low sonic boom based on CoKriging surrogate modelZHANG Hanqi0XU Yue1ZHONG Min2LI Yan3Chinese Aeronautical Establishment, Beijing 100012, ChinaChinese Aeronautical Establishment, Beijing 100012, ChinaChinese Aeronautical Establishment, Beijing 100012, ChinaChinese Aeronautical Establishment, Beijing 100012, ChinaAccurately predicting and effectively reducing sonic boom levels is one of the key issues in the development of the new generation of green supersonic civil aircraft. In order to improve the efficiency of low sonic boom optimal design for supersonic civil aircraft, a multi-fidelity optimal design program for low sonic boom is developed based on the CoKriging surrogate model combined with fast sonic boom prediction method and high fidelity sonic boom prediction method. The sonic boom prediction results of the TU-144 model are basically consistent with the experimental results, verifying the reliability of the two prediction methods. A parameter sensitivity analysis and optimal design are conducted on the wing shape of a certain supersonic civil aircraft model. The results show that Stevens′ loudness level of the ground sonic boom is more sensitive to three parameters:the half span length of the outer wing, leading edge sweep angle of the outer wing, the half span length of the inner wing. After optimization, the maximum ground sonic boom overpressure is reduced by about 4 Pa, and the Stevens′ loudness level is reduced by 4.26 dB. Compared with the Kriging model that only uses high fidelity sample data, the CoKriging model integrates high and low fidelity sample data, saving about 43% of time cost while ensuring a certain prediction accuracy.http://hkgcjz.cnjournals.com/hkgcjz/article/abstract/2023278sonic boomsurrogate modelsupersonic civil aircraftmulti-fidelityoptimal design
spellingShingle ZHANG Hanqi
XU Yue
ZHONG Min
LI Yan
Optimal design for low sonic boom based on CoKriging surrogate model
Hangkong gongcheng jinzhan
sonic boom
surrogate model
supersonic civil aircraft
multi-fidelity
optimal design
title Optimal design for low sonic boom based on CoKriging surrogate model
title_full Optimal design for low sonic boom based on CoKriging surrogate model
title_fullStr Optimal design for low sonic boom based on CoKriging surrogate model
title_full_unstemmed Optimal design for low sonic boom based on CoKriging surrogate model
title_short Optimal design for low sonic boom based on CoKriging surrogate model
title_sort optimal design for low sonic boom based on cokriging surrogate model
topic sonic boom
surrogate model
supersonic civil aircraft
multi-fidelity
optimal design
url http://hkgcjz.cnjournals.com/hkgcjz/article/abstract/2023278
work_keys_str_mv AT zhanghanqi optimaldesignforlowsonicboombasedoncokrigingsurrogatemodel
AT xuyue optimaldesignforlowsonicboombasedoncokrigingsurrogatemodel
AT zhongmin optimaldesignforlowsonicboombasedoncokrigingsurrogatemodel
AT liyan optimaldesignforlowsonicboombasedoncokrigingsurrogatemodel