High-temperature protection, structure optimization, and damage detection for missile-borne electronic devices
In this study, the high-temperature performance of hypersonic missile radomes was investigated through a combination of numerical simulations, experiments, and machine learning-based damage detection. Two- and three-dimensional steady-state and transient heat conduction models were developed in MATL...
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| Language: | English |
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Elsevier
2025-03-01
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| Series: | Results in Engineering |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123024021546 |
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| author | Bixiao Li Ruichan Lv |
| author_facet | Bixiao Li Ruichan Lv |
| author_sort | Bixiao Li |
| collection | DOAJ |
| description | In this study, the high-temperature performance of hypersonic missile radomes was investigated through a combination of numerical simulations, experiments, and machine learning-based damage detection. Two- and three-dimensional steady-state and transient heat conduction models were developed in MATLAB and COMSOL to examine the effects of different materials (ceramic, air and copper), filler configurations, and geometric shapes (cylindrical vs. conical) on radome insulation. Results indicated that introducing an air gap significantly reduced the peak temperature in the metallic layer (by up to 10–15 %), while shape optimization (e.g., cylindrical structures) further improved thermal uniformity. High-temperature damage simulations were performed using a Huffman Damage Coefficient, confirming that an air interlayer markedly decreased the damage area from 10 to 15 % to about 2–5 %. Laboratory tests employing infrared thermography validated the numerical predictions, showing consistency in temperature trends and structural integrity under ∼1000 °C heating. Furthermore, machine learning techniques (ResNet50) were applied to classify and detect microscopic damage, achieving a 95 % accuracy. These findings offer a robust theoretical and experimental basis for designing high-performance radomes and provide guidance for future integrated approaches to thermal protection in hypersonic missile systems. |
| format | Article |
| id | doaj-art-861447f5dd554241b3d0a11ec6c3b6b3 |
| institution | Kabale University |
| issn | 2590-1230 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Results in Engineering |
| spelling | doaj-art-861447f5dd554241b3d0a11ec6c3b6b32025-01-09T06:14:31ZengElsevierResults in Engineering2590-12302025-03-0125103911High-temperature protection, structure optimization, and damage detection for missile-borne electronic devicesBixiao Li0Ruichan Lv1State Key Laboratory of Electromechanical Integrated Manufacturing of High-performance Electronic Equipment, School of Mechano-Electronic Engineering, Xidian University, Xi'an, Shaanxi 710071, ChinaCorresponding author.; State Key Laboratory of Electromechanical Integrated Manufacturing of High-performance Electronic Equipment, School of Mechano-Electronic Engineering, Xidian University, Xi'an, Shaanxi 710071, ChinaIn this study, the high-temperature performance of hypersonic missile radomes was investigated through a combination of numerical simulations, experiments, and machine learning-based damage detection. Two- and three-dimensional steady-state and transient heat conduction models were developed in MATLAB and COMSOL to examine the effects of different materials (ceramic, air and copper), filler configurations, and geometric shapes (cylindrical vs. conical) on radome insulation. Results indicated that introducing an air gap significantly reduced the peak temperature in the metallic layer (by up to 10–15 %), while shape optimization (e.g., cylindrical structures) further improved thermal uniformity. High-temperature damage simulations were performed using a Huffman Damage Coefficient, confirming that an air interlayer markedly decreased the damage area from 10 to 15 % to about 2–5 %. Laboratory tests employing infrared thermography validated the numerical predictions, showing consistency in temperature trends and structural integrity under ∼1000 °C heating. Furthermore, machine learning techniques (ResNet50) were applied to classify and detect microscopic damage, achieving a 95 % accuracy. These findings offer a robust theoretical and experimental basis for designing high-performance radomes and provide guidance for future integrated approaches to thermal protection in hypersonic missile systems.http://www.sciencedirect.com/science/article/pii/S2590123024021546Thermal insulationRadome designCOMSOL simulationMachine learning |
| spellingShingle | Bixiao Li Ruichan Lv High-temperature protection, structure optimization, and damage detection for missile-borne electronic devices Results in Engineering Thermal insulation Radome design COMSOL simulation Machine learning |
| title | High-temperature protection, structure optimization, and damage detection for missile-borne electronic devices |
| title_full | High-temperature protection, structure optimization, and damage detection for missile-borne electronic devices |
| title_fullStr | High-temperature protection, structure optimization, and damage detection for missile-borne electronic devices |
| title_full_unstemmed | High-temperature protection, structure optimization, and damage detection for missile-borne electronic devices |
| title_short | High-temperature protection, structure optimization, and damage detection for missile-borne electronic devices |
| title_sort | high temperature protection structure optimization and damage detection for missile borne electronic devices |
| topic | Thermal insulation Radome design COMSOL simulation Machine learning |
| url | http://www.sciencedirect.com/science/article/pii/S2590123024021546 |
| work_keys_str_mv | AT bixiaoli hightemperatureprotectionstructureoptimizationanddamagedetectionformissileborneelectronicdevices AT ruichanlv hightemperatureprotectionstructureoptimizationanddamagedetectionformissileborneelectronicdevices |