The buckling load of carbon fiber composite cylindrical shells(CF-CCSs)was predicted using a backpropagation neural network improved by the sparrow search algorithm(SSA-BPNN).Firstly,two CF-CCSs,each with an inner dia...The buckling load of carbon fiber composite cylindrical shells(CF-CCSs)was predicted using a backpropagation neural network improved by the sparrow search algorithm(SSA-BPNN).Firstly,two CF-CCSs,each with an inner diameter of 100 mm,were manufactured and tested.The buckling behavior of CF-CCSs was analyzed by finite element and experiment.Subsequently,the effects of ply angle and length–diameter ratio on buckling load of CF-CCSs were analyzed,and the dataset of the neural network was generated using the finite element method.On this basis,the SSA-BPNN model for predicting buckling load of CF-CCS was established.The results show that the maximum and average errors of the SSA-BPNN to the test data are 6.88%and 2.24%,respectively.The buckling load prediction for CF-CCSs based on SSA-BPNN has satisfactory generalizability and can be used to analyze buckling loads on cylindrical shells of carbon fiber composites.展开更多
High-performance carbon nanofibers are highly dependent on the performance of their precursors,especially polyacrylonitrile(PAN).In this work,the copolymer of PAN(coPAN)was synthesized for electrospinning.A self-assem...High-performance carbon nanofibers are highly dependent on the performance of their precursors,especially polyacrylonitrile(PAN).In this work,the copolymer of PAN(coPAN)was synthesized for electrospinning.A self-assembling set-up was used for the stretching of single coPAN nanofibers.FTIR and Raman spectroscopies were used to characterize the chemical structure of coPAN nanofibers.Scanning electron microscopy(SEM)and atomic force microscopy(AFM)were used to monitor the morphology of single coPAN nanofibers under different drawing times.Micro-tensile test was used to determine the mechanical properties of single coPAN nanofibers.The results indicated that the drawing led to an increase in degree of molecular orientation along the fiber axis from 0.656 to 0.808,tensile strength from 304 MPa to 595 MPa,and modulus from 3.1 GPa to 12.4 GPa.This research would provide fundamental information of high-performance electrospun coPAN nanofibers and offer opportunities for the preparation of high-performance carbon nanofibers.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.52271277)the Natural Science Foundation of Jiangsu Province(Grant.No.BK20211343)+1 种基金the State Key Laboratory of Ocean Engineering(Shanghai Jiao Tong University)(Grant.No.GKZD010081)Postgraduate Research&Practice Innovation Program of Jiangsu Province(Grant.No.SJCX22_1906).
文摘The buckling load of carbon fiber composite cylindrical shells(CF-CCSs)was predicted using a backpropagation neural network improved by the sparrow search algorithm(SSA-BPNN).Firstly,two CF-CCSs,each with an inner diameter of 100 mm,were manufactured and tested.The buckling behavior of CF-CCSs was analyzed by finite element and experiment.Subsequently,the effects of ply angle and length–diameter ratio on buckling load of CF-CCSs were analyzed,and the dataset of the neural network was generated using the finite element method.On this basis,the SSA-BPNN model for predicting buckling load of CF-CCS was established.The results show that the maximum and average errors of the SSA-BPNN to the test data are 6.88%and 2.24%,respectively.The buckling load prediction for CF-CCSs based on SSA-BPNN has satisfactory generalizability and can be used to analyze buckling loads on cylindrical shells of carbon fiber composites.
基金financially supported by the National Natural Science Foundation of China(Nos.21774053,21975111,and 51903123)Natural Science Foundation of Jiangsu Province(No.BK20190760)+1 种基金Major Special Projects of Jiangxi Provincial Department of Science and Technology(No.20114ABF05100)Technology Plan Landing Project of Jiangxi Provincial Department of Education(No.GCJ2011-24)。
文摘High-performance carbon nanofibers are highly dependent on the performance of their precursors,especially polyacrylonitrile(PAN).In this work,the copolymer of PAN(coPAN)was synthesized for electrospinning.A self-assembling set-up was used for the stretching of single coPAN nanofibers.FTIR and Raman spectroscopies were used to characterize the chemical structure of coPAN nanofibers.Scanning electron microscopy(SEM)and atomic force microscopy(AFM)were used to monitor the morphology of single coPAN nanofibers under different drawing times.Micro-tensile test was used to determine the mechanical properties of single coPAN nanofibers.The results indicated that the drawing led to an increase in degree of molecular orientation along the fiber axis from 0.656 to 0.808,tensile strength from 304 MPa to 595 MPa,and modulus from 3.1 GPa to 12.4 GPa.This research would provide fundamental information of high-performance electrospun coPAN nanofibers and offer opportunities for the preparation of high-performance carbon nanofibers.
