Fibre-reinforced polymer(FRP)/rigid polyurethane foam(RPUF)interface is susceptible to moisture intrusion in addition to natural ageing during operation.This study investigated the influence of moisture intrusion on t...Fibre-reinforced polymer(FRP)/rigid polyurethane foam(RPUF)interface is susceptible to moisture intrusion in addition to natural ageing during operation.This study investigated the influence of moisture intrusion on the FRP/RPUF interface under natural ageing using experiments and molecular dynamics(MD)simulations.Water absorption,shear strength,and leakage current tests were used to clarify the changes in the interface performance.The degradation mechanism of moisture intrusion at the interface under natural ageing was revealed by MD simulation and micro-characterisation.The results show that the natural ageing of interfacial materials will slightly reduce the quality of the interface but will reduce the water resistance of the material and promote the process of water intrusion into the interface.In addition,water mainly invades the interface through RPUF.After water penetration,the interfacial bonding strength and insulation performance significantly decreased.Plasticisation and hydrolysis of interfacial materials are the main reasons for decreased interfacial adhesion.Hydrolysis can cause irreversible damage to the interface,increasing interface defects and water absorption.The vicious cycle of material hydrolysis is the ultimate cause of interfacial debonding.The polar molecules produced by this process and the water absorbed by the interface caused the degradation of the interface insulation performance.展开更多
In recent years,Deep Learning(DL),such as the algorithms of Convolutional Neural Networks(CNN),Recurrent Neural Networks(RNN)and Generative Adversarial Networks(GAN),has been widely studied and applied in various fiel...In recent years,Deep Learning(DL),such as the algorithms of Convolutional Neural Networks(CNN),Recurrent Neural Networks(RNN)and Generative Adversarial Networks(GAN),has been widely studied and applied in various fields including agriculture.Researchers in the fields of agriculture often use software frameworks without sufficiently examining the ideas and mechanisms of a technique.This article provides a concise summary of major DL algorithms,including concepts,limitations,implementation,training processes,and example codes,to help researchers in agriculture to gain a holistic picture of major DL techniques quickly.Research on DL applications in agriculture is summarized and analyzed,and future opportunities are discussed in this paper,which is expected to help researchers in agriculture to better understand DL algorithms and learn major DL techniques quickly,and further to facilitate data analysis,enhance related research in agriculture,and thus promote DL applications effectively.展开更多
基金National Natural Science Foundation of China,Grant/Award Number:52007065Fundamental Research Funds for the Central Universities,Grant/Award Number:2022MS071。
文摘Fibre-reinforced polymer(FRP)/rigid polyurethane foam(RPUF)interface is susceptible to moisture intrusion in addition to natural ageing during operation.This study investigated the influence of moisture intrusion on the FRP/RPUF interface under natural ageing using experiments and molecular dynamics(MD)simulations.Water absorption,shear strength,and leakage current tests were used to clarify the changes in the interface performance.The degradation mechanism of moisture intrusion at the interface under natural ageing was revealed by MD simulation and micro-characterisation.The results show that the natural ageing of interfacial materials will slightly reduce the quality of the interface but will reduce the water resistance of the material and promote the process of water intrusion into the interface.In addition,water mainly invades the interface through RPUF.After water penetration,the interfacial bonding strength and insulation performance significantly decreased.Plasticisation and hydrolysis of interfacial materials are the main reasons for decreased interfacial adhesion.Hydrolysis can cause irreversible damage to the interface,increasing interface defects and water absorption.The vicious cycle of material hydrolysis is the ultimate cause of interfacial debonding.The polar molecules produced by this process and the water absorbed by the interface caused the degradation of the interface insulation performance.
基金This project is partially supported by National Natural Science Foundation of China(No.31771680)Fundamental Research Funds for the Central Universities of China(No:JUSRP51730A)+4 种基金the Modern Agriculture Funds of Jiangsu Province(No.BE2015310)the Modern Agriculture Funds of Jiangsu Province(Vegetable)(No.SXGC[2017]210)the New Agricultural Engineering of Jiangsu Province(No.SXGC[2016]106)the 111 Project(B1208)the Research Funds for New Faculty of Jiangnan University.
文摘In recent years,Deep Learning(DL),such as the algorithms of Convolutional Neural Networks(CNN),Recurrent Neural Networks(RNN)and Generative Adversarial Networks(GAN),has been widely studied and applied in various fields including agriculture.Researchers in the fields of agriculture often use software frameworks without sufficiently examining the ideas and mechanisms of a technique.This article provides a concise summary of major DL algorithms,including concepts,limitations,implementation,training processes,and example codes,to help researchers in agriculture to gain a holistic picture of major DL techniques quickly.Research on DL applications in agriculture is summarized and analyzed,and future opportunities are discussed in this paper,which is expected to help researchers in agriculture to better understand DL algorithms and learn major DL techniques quickly,and further to facilitate data analysis,enhance related research in agriculture,and thus promote DL applications effectively.
