Development of a method for maximum structural response prediction of a store externally carried by a jet fighter
Experimental structural response of equipment mounted in store carried externally by jet type aircraft is investigated, predicted and compared with responses suggested by military standards in this study. A representative store which is similar to Mark-83 warhead with guidance units in terms of mass...
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Veröffentlicht in: | Proceedings of the Institution of Mechanical Engineers. Part G, Journal of aerospace engineering Journal of aerospace engineering, 2022-03, Vol.236 (4), p.777-788 |
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creator | Kaplan, Engin Metin Acar, Erdem Bülent Özer, Mehmet |
description | Experimental structural response of equipment mounted in store carried externally by jet type aircraft is investigated, predicted and compared with responses suggested by military standards in this study. A representative store which is similar to Mark-83 warhead with guidance units in terms of mass and geometry is used in this study. The main scope of this study is to evaluate the structural response proposed by military standards with real test conditions and also suggest a new method with an artificial neural network to predict the maximum response. Seventy-five different flight conditions are used to train the network for low and high frequency components. Also, eight flight conditions apart from the training set of flight conditions are used to test the approach. Acceleration levels are collected in real flight conditions by the data storage system. In signal processing, vibration response is expressed as power spectral density functions in the frequency domain. Procedures to predict the maximum response from measurements are determined with statistical limits in the literature. Besides the well-known limits in literature, third-order polynomial normal and logarithmic transform is used, and the performance of the different limits is compared. It is found that the military standard vibration spectrum is conservative. Distribution-free and normal tolerance limits predicted low frequency acceleration spectral density magnitudes more accurately. Their prediction performances were better than those of the other tolerance limits and that of the military standard. Third-order polynomial transform predictions are found to be reasonable with respect to normal prediction limit and envelope approach. Finally, it can be concluded that the response prediction method proposed in this article works well for Mark-83 warheads with guidance unit carried externally by jet fighter. |
doi_str_mv | 10.1177/09544100211022244 |
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A representative store which is similar to Mark-83 warhead with guidance units in terms of mass and geometry is used in this study. The main scope of this study is to evaluate the structural response proposed by military standards with real test conditions and also suggest a new method with an artificial neural network to predict the maximum response. Seventy-five different flight conditions are used to train the network for low and high frequency components. Also, eight flight conditions apart from the training set of flight conditions are used to test the approach. Acceleration levels are collected in real flight conditions by the data storage system. In signal processing, vibration response is expressed as power spectral density functions in the frequency domain. Procedures to predict the maximum response from measurements are determined with statistical limits in the literature. Besides the well-known limits in literature, third-order polynomial normal and logarithmic transform is used, and the performance of the different limits is compared. It is found that the military standard vibration spectrum is conservative. Distribution-free and normal tolerance limits predicted low frequency acceleration spectral density magnitudes more accurately. Their prediction performances were better than those of the other tolerance limits and that of the military standard. Third-order polynomial transform predictions are found to be reasonable with respect to normal prediction limit and envelope approach. Finally, it can be concluded that the response prediction method proposed in this article works well for Mark-83 warheads with guidance unit carried externally by jet fighter.</description><identifier>ISSN: 0954-4100</identifier><identifier>EISSN: 2041-3025</identifier><identifier>DOI: 10.1177/09544100211022244</identifier><language>eng</language><publisher>London, England: SAGE Publications</publisher><subject>Acceleration ; Artificial neural networks ; Data storage ; Flight conditions ; Flight training ; Mathematical analysis ; Polynomials ; Power spectral density ; Predictions ; Signal processing ; Spectral density function ; Structural response ; Vibration response ; Warheads</subject><ispartof>Proceedings of the Institution of Mechanical Engineers. 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Part G, Journal of aerospace engineering</title><description>Experimental structural response of equipment mounted in store carried externally by jet type aircraft is investigated, predicted and compared with responses suggested by military standards in this study. A representative store which is similar to Mark-83 warhead with guidance units in terms of mass and geometry is used in this study. The main scope of this study is to evaluate the structural response proposed by military standards with real test conditions and also suggest a new method with an artificial neural network to predict the maximum response. Seventy-five different flight conditions are used to train the network for low and high frequency components. Also, eight flight conditions apart from the training set of flight conditions are used to test the approach. Acceleration levels are collected in real flight conditions by the data storage system. In signal processing, vibration response is expressed as power spectral density functions in the frequency domain. Procedures to predict the maximum response from measurements are determined with statistical limits in the literature. Besides the well-known limits in literature, third-order polynomial normal and logarithmic transform is used, and the performance of the different limits is compared. It is found that the military standard vibration spectrum is conservative. Distribution-free and normal tolerance limits predicted low frequency acceleration spectral density magnitudes more accurately. Their prediction performances were better than those of the other tolerance limits and that of the military standard. Third-order polynomial transform predictions are found to be reasonable with respect to normal prediction limit and envelope approach. Finally, it can be concluded that the response prediction method proposed in this article works well for Mark-83 warheads with guidance unit carried externally by jet fighter.</description><subject>Acceleration</subject><subject>Artificial neural networks</subject><subject>Data storage</subject><subject>Flight conditions</subject><subject>Flight training</subject><subject>Mathematical analysis</subject><subject>Polynomials</subject><subject>Power spectral density</subject><subject>Predictions</subject><subject>Signal processing</subject><subject>Spectral density function</subject><subject>Structural response</subject><subject>Vibration response</subject><subject>Warheads</subject><issn>0954-4100</issn><issn>2041-3025</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp1kE9LxDAUxIMouK5-AG8Bz12TlzTdHmX9Cwte9FzS9HW3S9t0k1S2396WCh7Ed5nDzG94DCG3nK04T5J7lsZScsaAcwYAUp6RBTDJI8EgPieLyY-mwCW58v7AxouVWJDjI35hbbsG20BtSTVtMOxtQUvraKNPVdM31AfXm9A7XVOHvrOtR9o5LCoTKtvOmA_WIcVTQNfquh6o0c5VWNB8GN0DBlpWu_3oXpOLUtceb350ST6fnz42r9H2_eVt87CNjOAQIpAokOWYJkYAAsOcC6lYzGSaKmQ6F2miBMQKTGkSQKnWas0F46JMYyiMWJK7ubdz9tijD9nB9tNvPgMVwziVlGJM8TllnPXeYZl1rmq0GzLOsmnZ7M-yI7OaGa93-Nv6P_AN-IZ4EQ</recordid><startdate>202203</startdate><enddate>202203</enddate><creator>Kaplan, Engin Metin</creator><creator>Acar, Erdem</creator><creator>Bülent Özer, Mehmet</creator><general>SAGE Publications</general><general>SAGE PUBLICATIONS, INC</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0002-8576-4071</orcidid><orcidid>https://orcid.org/0000-0002-3661-5563</orcidid></search><sort><creationdate>202203</creationdate><title>Development of a method for maximum structural response prediction of a store externally carried by a jet fighter</title><author>Kaplan, Engin Metin ; Acar, Erdem ; Bülent Özer, Mehmet</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c312t-24e3e0be97c32e20eb13460504996e0ab397632562cfc72e4686813013f952dc3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Acceleration</topic><topic>Artificial neural networks</topic><topic>Data storage</topic><topic>Flight conditions</topic><topic>Flight training</topic><topic>Mathematical analysis</topic><topic>Polynomials</topic><topic>Power spectral density</topic><topic>Predictions</topic><topic>Signal processing</topic><topic>Spectral density function</topic><topic>Structural response</topic><topic>Vibration response</topic><topic>Warheads</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kaplan, Engin Metin</creatorcontrib><creatorcontrib>Acar, Erdem</creatorcontrib><creatorcontrib>Bülent Özer, Mehmet</creatorcontrib><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Proceedings of the Institution of Mechanical Engineers. Part G, Journal of aerospace engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kaplan, Engin Metin</au><au>Acar, Erdem</au><au>Bülent Özer, Mehmet</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Development of a method for maximum structural response prediction of a store externally carried by a jet fighter</atitle><jtitle>Proceedings of the Institution of Mechanical Engineers. Part G, Journal of aerospace engineering</jtitle><date>2022-03</date><risdate>2022</risdate><volume>236</volume><issue>4</issue><spage>777</spage><epage>788</epage><pages>777-788</pages><issn>0954-4100</issn><eissn>2041-3025</eissn><abstract>Experimental structural response of equipment mounted in store carried externally by jet type aircraft is investigated, predicted and compared with responses suggested by military standards in this study. A representative store which is similar to Mark-83 warhead with guidance units in terms of mass and geometry is used in this study. The main scope of this study is to evaluate the structural response proposed by military standards with real test conditions and also suggest a new method with an artificial neural network to predict the maximum response. Seventy-five different flight conditions are used to train the network for low and high frequency components. Also, eight flight conditions apart from the training set of flight conditions are used to test the approach. Acceleration levels are collected in real flight conditions by the data storage system. In signal processing, vibration response is expressed as power spectral density functions in the frequency domain. Procedures to predict the maximum response from measurements are determined with statistical limits in the literature. Besides the well-known limits in literature, third-order polynomial normal and logarithmic transform is used, and the performance of the different limits is compared. It is found that the military standard vibration spectrum is conservative. Distribution-free and normal tolerance limits predicted low frequency acceleration spectral density magnitudes more accurately. Their prediction performances were better than those of the other tolerance limits and that of the military standard. Third-order polynomial transform predictions are found to be reasonable with respect to normal prediction limit and envelope approach. 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subjects | Acceleration Artificial neural networks Data storage Flight conditions Flight training Mathematical analysis Polynomials Power spectral density Predictions Signal processing Spectral density function Structural response Vibration response Warheads |
title | Development of a method for maximum structural response prediction of a store externally carried by a jet fighter |
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