Crashworthy optimization of skeleton-filled FRP tubes based on back propagation neural network
Lightweight composite tubes have been widely used in vehicle safety systems as energy absorbers. To improve the crashworthiness of tubes, composite skeletons with a variety of cross-sectional profiles were ingeniously designed as internal reinforcements. Herein, a novel composite skeleton comprising...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-12-01
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| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844023102271 |
| _version_ | 1797383886266695680 |
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| author | Yu Xiong Haiyang Yang Xinyu Li Hongshuai Lei Guoxing Lu |
| author_facet | Yu Xiong Haiyang Yang Xinyu Li Hongshuai Lei Guoxing Lu |
| author_sort | Yu Xiong |
| collection | DOAJ |
| description | Lightweight composite tubes have been widely used in vehicle safety systems as energy absorbers. To improve the crashworthiness of tubes, composite skeletons with a variety of cross-sectional profiles were ingeniously designed as internal reinforcements. Herein, a novel composite skeleton comprising cross-ribs and an inner circle (OS-skeleton) was proposed and integrally fabricated through the special assembling molds. The novel OS-skeleton presented a steady progressive failure mode under dynamic impact loads, leading to remarkable material utilization and energy absorption characteristics. Subsequently, finite element analysis (FEA) models were developed. The predicted response curves and deformation modes were consistent with the experimental results. Finally, a multi-objective optimization utilizing the back propagation neural network (BPNN) was then conducted to further enhance the mean crushing force (MCF) and specific energy absorption (SEA) by adjusting several structural parameters. The results showed that MCF and SEA increased with the increasing thickness of the skeletons and the number of circumferential ribs. By comparison, the diameter of inner tube and the number of circumferential ribs showed a non-linear relationship with the energy absorption characteristics due to their combined effects. In sum, the proposed composite tubes filled with OS-skeletons could maximize certain aspects of crashworthiness performance through proper structural design, demonstrating great potential for lightweight energy absorbers. |
| first_indexed | 2024-03-08T21:27:27Z |
| format | Article |
| id | doaj.art-a1ed28739c354277815d0951f2a4d513 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-03-08T21:27:27Z |
| publishDate | 2023-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-a1ed28739c354277815d0951f2a4d5132023-12-21T07:35:28ZengElsevierHeliyon2405-84402023-12-01912e23019Crashworthy optimization of skeleton-filled FRP tubes based on back propagation neural networkYu Xiong0Haiyang Yang1Xinyu Li2Hongshuai Lei3Guoxing Lu4Institute of Advanced Structure Technology, Beijing Institute of Technology, Beijing, 100081, PR ChinaShanghai Electro-Mechanical Engineering Institute, Shanghai, 201109, PR China; Corresponding author.Institute of Advanced Structure Technology, Beijing Institute of Technology, Beijing, 100081, PR ChinaInstitute of Advanced Structure Technology, Beijing Institute of Technology, Beijing, 100081, PR China; Corresponding author.Faculty of Science, Engineering and Technology, Swinburne University of Technology, Hawthorn, Vic, 3122, AustraliaLightweight composite tubes have been widely used in vehicle safety systems as energy absorbers. To improve the crashworthiness of tubes, composite skeletons with a variety of cross-sectional profiles were ingeniously designed as internal reinforcements. Herein, a novel composite skeleton comprising cross-ribs and an inner circle (OS-skeleton) was proposed and integrally fabricated through the special assembling molds. The novel OS-skeleton presented a steady progressive failure mode under dynamic impact loads, leading to remarkable material utilization and energy absorption characteristics. Subsequently, finite element analysis (FEA) models were developed. The predicted response curves and deformation modes were consistent with the experimental results. Finally, a multi-objective optimization utilizing the back propagation neural network (BPNN) was then conducted to further enhance the mean crushing force (MCF) and specific energy absorption (SEA) by adjusting several structural parameters. The results showed that MCF and SEA increased with the increasing thickness of the skeletons and the number of circumferential ribs. By comparison, the diameter of inner tube and the number of circumferential ribs showed a non-linear relationship with the energy absorption characteristics due to their combined effects. In sum, the proposed composite tubes filled with OS-skeletons could maximize certain aspects of crashworthiness performance through proper structural design, demonstrating great potential for lightweight energy absorbers.http://www.sciencedirect.com/science/article/pii/S2405844023102271Thin-walled structuresFiber-reinforced plasticCrashworthinessMulti-objective optimization |
| spellingShingle | Yu Xiong Haiyang Yang Xinyu Li Hongshuai Lei Guoxing Lu Crashworthy optimization of skeleton-filled FRP tubes based on back propagation neural network Heliyon Thin-walled structures Fiber-reinforced plastic Crashworthiness Multi-objective optimization |
| title | Crashworthy optimization of skeleton-filled FRP tubes based on back propagation neural network |
| title_full | Crashworthy optimization of skeleton-filled FRP tubes based on back propagation neural network |
| title_fullStr | Crashworthy optimization of skeleton-filled FRP tubes based on back propagation neural network |
| title_full_unstemmed | Crashworthy optimization of skeleton-filled FRP tubes based on back propagation neural network |
| title_short | Crashworthy optimization of skeleton-filled FRP tubes based on back propagation neural network |
| title_sort | crashworthy optimization of skeleton filled frp tubes based on back propagation neural network |
| topic | Thin-walled structures Fiber-reinforced plastic Crashworthiness Multi-objective optimization |
| url | http://www.sciencedirect.com/science/article/pii/S2405844023102271 |
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