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
以花生壳、柑橘皮的不同炭化材料和碳纤维作为水中污染物的吸附剂,对重金属Cu2+进行了吸附研究。吸附试验结果表明:当改变水中p H时对吸附效果影响比较大,p H 5.5时吸附剂对水中Cu2+的吸附量最大;吸附时间在90 min后达到了吸附平衡状态...以花生壳、柑橘皮的不同炭化材料和碳纤维作为水中污染物的吸附剂,对重金属Cu2+进行了吸附研究。吸附试验结果表明:当改变水中p H时对吸附效果影响比较大,p H 5.5时吸附剂对水中Cu2+的吸附量最大;吸附时间在90 min后达到了吸附平衡状态;花生壳、柑橘皮吸附效果最好的加工炭化温度为250℃。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.
文摘以花生壳、柑橘皮的不同炭化材料和碳纤维作为水中污染物的吸附剂,对重金属Cu2+进行了吸附研究。吸附试验结果表明:当改变水中p H时对吸附效果影响比较大,p H 5.5时吸附剂对水中Cu2+的吸附量最大;吸附时间在90 min后达到了吸附平衡状态;花生壳、柑橘皮吸附效果最好的加工炭化温度为250℃。
