A C-band accelerator structure was used to accelerate electrons at the Shanghai soft X-ray free-electron laser test facility (SXFEL-TF) in Shanghai Institute of Applied Physics (SINAP). The microwave system of this ac...A C-band accelerator structure was used to accelerate electrons at the Shanghai soft X-ray free-electron laser test facility (SXFEL-TF) in Shanghai Institute of Applied Physics (SINAP). The microwave system of this accelerator structure used a 110 MW pulse modulator and a klystron (PV-5050) to provide the power supply. A pulse transformer is a crucial device in a modulator klystron system and plays significant roles in voltage level transformation, matching impedances, and polarity inversion. This study presents the optimization of a high-voltage pulse transformer. The design considerations of reducing flattop ringing and flattop droop, and shortening leading edge are provided. The model simulation, mechanical design, and the relevant experimental results are also presented.展开更多
Delayed detached eddy simulation(DDES)is performed to investigate an open cavity at Ma0.85.Clean cavity and cavity with leading-edge saw tooth spoiler and flattop spoiler,are modeled.The results obtained from clean ca...Delayed detached eddy simulation(DDES)is performed to investigate an open cavity at Ma0.85.Clean cavity and cavity with leading-edge saw tooth spoiler and flattop spoiler,are modeled.The results obtained from clean cavity prediction are compared with experimental sound pressure level(SPL)data from QinetiQ,UK.DDES results agree well with the experimental data.Furthermore,comparisons are made with the predicted SPL between the three configurations to find out the effect of different passive control methods.Both the spoilers can suppress the over-all SPL up to 8dB.The main focuses of this investigation are to exam the DDES method on cavity aeroacoustic analysis and test the noise suppression effect by saw tooth spoiler and flattop spoiler.展开更多
Disruption prediction using a long short-term memory(LSTM)algorithm has been developed on EAST,due to its inherent advantages in time series data processing.In the present work,LSTM is used as the model and the AUC(ar...Disruption prediction using a long short-term memory(LSTM)algorithm has been developed on EAST,due to its inherent advantages in time series data processing.In the present work,LSTM is used as the model and the AUC(area under receiver operation characteristic curve)is used as the evaluation index.When the model is trained on data from the plasma current flattop phase and tested on data from the same period multiple times,the highest AUC is 0.8646 and the training time is about 6900 s per epoch.For comparison,the last 1000 ms of the flattop phases are intercepted as short time sequences.When the model is trained on data from short time sequences and tested on data from the same period,the highest AUC is increased to 0.9379 and the training time is restricted to 36 s per epoch.When the best model trained on the short time sequences is applied to the flattop phase for testing,the AUC is up to 0.9189.The experiment results show that it is possible for LSTM to train the model on data from short time sequences and migrate the model to the entire flattop phase,with a shorter training time and higher AUC value.展开更多
基金supported by the National Natural Science Foundation of China(No.11675250)
文摘A C-band accelerator structure was used to accelerate electrons at the Shanghai soft X-ray free-electron laser test facility (SXFEL-TF) in Shanghai Institute of Applied Physics (SINAP). The microwave system of this accelerator structure used a 110 MW pulse modulator and a klystron (PV-5050) to provide the power supply. A pulse transformer is a crucial device in a modulator klystron system and plays significant roles in voltage level transformation, matching impedances, and polarity inversion. This study presents the optimization of a high-voltage pulse transformer. The design considerations of reducing flattop ringing and flattop droop, and shortening leading edge are provided. The model simulation, mechanical design, and the relevant experimental results are also presented.
基金supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD)the Funding of Jiangsu Innovation Program for Graduate Education (KYLX_0296)the Fundamental Research Funds for the Central Universities
文摘Delayed detached eddy simulation(DDES)is performed to investigate an open cavity at Ma0.85.Clean cavity and cavity with leading-edge saw tooth spoiler and flattop spoiler,are modeled.The results obtained from clean cavity prediction are compared with experimental sound pressure level(SPL)data from QinetiQ,UK.DDES results agree well with the experimental data.Furthermore,comparisons are made with the predicted SPL between the three configurations to find out the effect of different passive control methods.Both the spoilers can suppress the over-all SPL up to 8dB.The main focuses of this investigation are to exam the DDES method on cavity aeroacoustic analysis and test the noise suppression effect by saw tooth spoiler and flattop spoiler.
基金supported by the National Magnetic Confinement Fusion Energy R&D Program of China(2018YFE0304100,2018YFE0302100)Anhui Provincial Natural Science Foundation(1808085MA25)。
文摘Disruption prediction using a long short-term memory(LSTM)algorithm has been developed on EAST,due to its inherent advantages in time series data processing.In the present work,LSTM is used as the model and the AUC(area under receiver operation characteristic curve)is used as the evaluation index.When the model is trained on data from the plasma current flattop phase and tested on data from the same period multiple times,the highest AUC is 0.8646 and the training time is about 6900 s per epoch.For comparison,the last 1000 ms of the flattop phases are intercepted as short time sequences.When the model is trained on data from short time sequences and tested on data from the same period,the highest AUC is increased to 0.9379 and the training time is restricted to 36 s per epoch.When the best model trained on the short time sequences is applied to the flattop phase for testing,the AUC is up to 0.9189.The experiment results show that it is possible for LSTM to train the model on data from short time sequences and migrate the model to the entire flattop phase,with a shorter training time and higher AUC value.
