In high-performance electric sports vehicles,the application of woven composite materials with the purpose of lightweight has become an inevitable choice.It is considerably difference between traditional metal materia...In high-performance electric sports vehicles,the application of woven composite materials with the purpose of lightweight has become an inevitable choice.It is considerably difference between traditional metal materials and composites for the lightweight design strategy of electric vehicle structures,due to the multi-scale and anisotropic characteristics of fiber reinforced composites.Nevertheless,most of scholars are focus on the meso-scale mechanical responses of woven composites,and few studies are involved in their multi-scale mechanical behaviors and hierarchical design strategy of composite structures in electric vehicles.In this work,a multiscale analysis strategy was proposed to investigate mechanical behaviors of composite front firewall.Subsequently,a hierarchical optimization strategy with the objective of lightweight design of composite front firewall was carried out.Finally,a reasonable layout scheme of composite front firewall was quantitatively obtained.The maximum errors between the predicted and theoretical/experimental results in terms of equivalent engineering constants of fiber yarns and 2D twill woven composites(2DTWCs)were 8.8 GPa and 7%,respectively.It indicates that the multi-scale models can be used to evaluate the mechanical properties of 2DTWCs.Additionally,the total weight of optimized composite front firewall was reduced by 36%in comparison with the reference,and simultaneously the total stiffness was improved by 26%.Hence,it is an effective strategy to design lightweight composite structures of electric vehicles.We hope the proposed multi-scale and hierarchical design strategy could promote the further development of composite structures in high-performance electric sports vehicles.展开更多
In this study,a new algorithm was proposed for edge extraction of greenhouse strawberry leaf in natural light based on the 4-level daubechies 5(‘db5’)wavelet decomposition.This algorithm adopts different segmentatio...In this study,a new algorithm was proposed for edge extraction of greenhouse strawberry leaf in natural light based on the 4-level daubechies 5(‘db5’)wavelet decomposition.This algorithm adopts different segmentation methods for the reconstructed images at different scales to erase the external background and the internal leaf vein interference.There were two advantages of this method.One was that it can provide the abstraction from different spaces to express a same image.The other one was that some image features are hard to be acquired in some scale spaces,while the features are easy to be obtained in other scale spaces.In this image process methods,the Otsu threshold segmentation was to obtain the binary image areas,and the Canny segmentation is to obtain the accurate gradient edges,then the morphological methods and the logical calculus methods were to avoid the fragments inside the leaf area and the adhesions outside the leaf area.Since the strawberry leaf images were different respectively,and the greenhouse optical radiation and reflection may cause local non-uniform illumination of leaf image,the pseudo canny edges of leaf image ere divided into three categories in this research.The first category was the external pseudo canny edges area of the first layer reconstructed leaf image,the second category was the internal pseudo canny edges area in highlight of the third layer reconstructed leaf image,the third category was the internal pseudo canny edges area of significantly different grayscale of the third layer reconstructed leaf image.The different processing methods were constructed for the three kinds of different texture features based on the multi scale reconstructed images,then the complete and the accurate leaf edges without interference were obtained.Finally,the multi scale method was simplified and a remarkably effective segmentation algorithm was deduced for the greenhouse strawberry leaf in natural light.展开更多
基金supported in part by the major scientific and technological project of Shenzhen Municipal Science,Technology and Innovation Bureau(KJZD20230923114259049)National Key R&D Program of China(2023YFB2504605).
文摘In high-performance electric sports vehicles,the application of woven composite materials with the purpose of lightweight has become an inevitable choice.It is considerably difference between traditional metal materials and composites for the lightweight design strategy of electric vehicle structures,due to the multi-scale and anisotropic characteristics of fiber reinforced composites.Nevertheless,most of scholars are focus on the meso-scale mechanical responses of woven composites,and few studies are involved in their multi-scale mechanical behaviors and hierarchical design strategy of composite structures in electric vehicles.In this work,a multiscale analysis strategy was proposed to investigate mechanical behaviors of composite front firewall.Subsequently,a hierarchical optimization strategy with the objective of lightweight design of composite front firewall was carried out.Finally,a reasonable layout scheme of composite front firewall was quantitatively obtained.The maximum errors between the predicted and theoretical/experimental results in terms of equivalent engineering constants of fiber yarns and 2D twill woven composites(2DTWCs)were 8.8 GPa and 7%,respectively.It indicates that the multi-scale models can be used to evaluate the mechanical properties of 2DTWCs.Additionally,the total weight of optimized composite front firewall was reduced by 36%in comparison with the reference,and simultaneously the total stiffness was improved by 26%.Hence,it is an effective strategy to design lightweight composite structures of electric vehicles.We hope the proposed multi-scale and hierarchical design strategy could promote the further development of composite structures in high-performance electric sports vehicles.
基金This work was supported by the Beijing‘Urban agriculture project group’program and was undertaken by China Agricultural University.
文摘In this study,a new algorithm was proposed for edge extraction of greenhouse strawberry leaf in natural light based on the 4-level daubechies 5(‘db5’)wavelet decomposition.This algorithm adopts different segmentation methods for the reconstructed images at different scales to erase the external background and the internal leaf vein interference.There were two advantages of this method.One was that it can provide the abstraction from different spaces to express a same image.The other one was that some image features are hard to be acquired in some scale spaces,while the features are easy to be obtained in other scale spaces.In this image process methods,the Otsu threshold segmentation was to obtain the binary image areas,and the Canny segmentation is to obtain the accurate gradient edges,then the morphological methods and the logical calculus methods were to avoid the fragments inside the leaf area and the adhesions outside the leaf area.Since the strawberry leaf images were different respectively,and the greenhouse optical radiation and reflection may cause local non-uniform illumination of leaf image,the pseudo canny edges of leaf image ere divided into three categories in this research.The first category was the external pseudo canny edges area of the first layer reconstructed leaf image,the second category was the internal pseudo canny edges area in highlight of the third layer reconstructed leaf image,the third category was the internal pseudo canny edges area of significantly different grayscale of the third layer reconstructed leaf image.The different processing methods were constructed for the three kinds of different texture features based on the multi scale reconstructed images,then the complete and the accurate leaf edges without interference were obtained.Finally,the multi scale method was simplified and a remarkably effective segmentation algorithm was deduced for the greenhouse strawberry leaf in natural light.
