http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Real-time fatigue crack prediction using self-sensing buckypaper and gated recurrent unit
Hyeonho Hwang,송진우,김흥수,Aditi Chattopadhyay 대한기계학회 2023 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.37 No.3
Aircraft is regarded as a collection of modern technologies from throughout all industries. However, it is inevitable to develop defects during its service life. In general, the aircraft has a periodic maintenance period, and is inspected according to a well-established process, for example non-destructive testing. However, the maintenance requires massive time and cost. If an unexpected defect occurs due to external environments before the maintenance cycle returns, it is impossible to prevent subsequent damage. This study proposes a novel realtime fatigue crack prediction method using self-sensing carbon nanotube buckypaper and deep learning algorithm. Carbon nanotube buckypaper was fabricated by the wet method. The physics-informed gated recurrent unit was used to predict real time crack growth. The physicsinformed deep learning model accurately predicted the fatigue crack length. The results showed that the proposed method is promising in detecting the real-time fatigue crack growth of aircraft structure.
Hyeonho CHO(조현호),Joonho LEE(이준호),Hyundo HWANG(황현도),Woonbong HWANG(황운봉),Jin-Gyun KIM(김진균),Sunghan KIM(김승한) 대한기계학회 2021 대한기계학회 춘추학술대회 Vol.2021 No.11
By using the spin assisted layer-by-layer technique, the graphene oxide/silk fibroin based bionanocomposites were manufactured. The water vapor annealing process was employed in order to enhance the interfacial properties between the graphene oxide and silk fibroin. Moreover, the mechanical properties of the graphene oxide-based nanocomposites were found to be influenced by the water vapor annealing process. The mechanical properties of the graphene oxide-based nanocomposites can be improved by water vapor annealing process. In order to understand the details of the mechanical behaviors of the graphene oxide-based nanocomposites, the finite element analysis models of the graphene oxide-based nanocomposites were established.