Current Status and Prospects of China's Road Freight Transportation Industry

Xu Liqun 인하대학교 정석물류통상연구원 2007 인하대학교 정석물류통상연구원 학술대회 Vol.2007 No.5

Fishbone Oscillations in the Experimental Advanced Superconductivity Tokamak

Liqing Xu,Liqun Hu,Yi Yuan,Yingying Li,Guo-Qiang Zhong,Hai-Qing Liu,Kaiyun Chen,Tong-Hui Shi,Yan-Min Duan 한국물리학회 2018 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.72 No.6

A fishbone oscillation was observed in the neutral beam injection plasma at Experimental Ad- vanced Superconductivity Tokamak (EAST). This m = 1/n = 1 (m, n: poloidal, toroidal mode numbers, respectively) typical internal kink mode travels in the ion-diamagnetism direction in the poloidal section with a rotation speed close to the ion diamagnetic drift frequency. A high thermal plasma beta and high amounts of energetic ions are necessary for the mode to develop. Fishbone oscillations can expel heavy impurities in the core, which favors sustaining a high-performance plasma. The born frequency of the fishbone oscillation is the ion diamagnetic drift frequency and the chirping down of the frequency during the initial growth phase is the result of a drop in ion- diamagnetic drift frequency. The excitation energy is thought to be due to the thermal plasma pressure gradient; however, the development of a fishbone oscillation is related to energetic ions. A fishbone oscillation was observed in the neutral beam injection plasma at Experimental Advanced Superconductivity Tokamak (EAST). This m = 1/n = 1 (m, n: poloidal, toroidal mode numbers, respectively) typical internal kink mode travels in the ion-diamagnetism direction in the poloidal section with a rotation speed close to the ion diamagnetic drift frequency. A high thermal plasma beta and high amounts of energetic ions are necessary for the mode to develop. Fishbone oscillations can expel heavy impurities in the core, which favors sustaining a high-performance plasma. The born frequency of the fishbone oscillation is the ion diamagnetic drift frequency and the chirping down of the frequency during the initial growth phase is the result of a drop in ion- diamagnetic drift frequency. The excitation energy is thought to be due to the thermal plasma pressure gradient; however, the development of a fishbone oscillation is related to energetic ions.

Artillery structural dynamic responses uncertain optimization based on robust Nash game method

Fengjie Xu,Guolai Yang,Liqun Wang 대한기계학회 2021 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.35 No.9

To coordinate the contradiction between artillery launching performance indexes under parameter uncertainty, this paper proposes an artillery structural dynamic responses optimization method based on robust Nash game theory. First, a multi-flexible body dynamic model for a 155 mm caliber artillery is established, which coupling the interior ballistic model, recoil force model, and balance mechanism model. Secondly, the live firing experiment is carried out to verify the accuracy of the established multi-flexible model. Then the muzzle vibration and maximum chamber pressure are selected as the players in the game. Because these two indexes can represent the most critical contradictory indexes of artillery, namely the firing accuracy and power. Afterward, to reduce the computational time, the BP neural network surrogate model is constructed to replace the original multi-flexible body dynamic model. Finally, the double-loop approach is adopted to search for the robust Nash equilibrium. The inner loop optimization is used to determine the worst-case scenario caused by the parameter uncertainty. The outer loop optimization is referred to as the robust Nash equilibrium solution process. The results show that the artillery structural dynamics responses have been significantly improved.

A new interval perturbation method for static structural response bounds using radial basis neural network differentiation

Yuwei Yao,Liqun Wang,Guolai Yang,Fengjie Xu,Lei Li 대한기계학회 2023 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.37 No.3

The interval perturbation method is an effective and successful tool in the uncertainty analysis; however, it suffers from the deficiency in the required differential information, which limits its application in complex engineering problems. To end this, this paper uses the radial basis neural network to formulate the derivative information, and its fine accuracy is demonstrated by a mathematical example. Moreover, a new interval analysis method combining interval perturbation and radial basis neural network differentiation, abbreviated as RBNNIPM is proposed. Furthermore, RBNNIPM is applied to calculate the boundaries of yield stress in a three-bar truss, and the detailed assessment proves that RBNNIPM has both high efficiency and high precision. Finally, an electromagnetic buffer model is established to certificate the practicability of RBNNIPM in practical engineering.

Explore the Secrecy in the Distribution of Red and Yellow Soil on the Earth

Zhongjie Ye,Liqun Xu 한국토양비료학회 2014 한국토양비료학회 학술발표회 초록집 Vol.2014 No.6

Transient Snakes in an Ohmic Plasma Associated with a Minor Disruption in the HT-7 Tokamak

Songtao Mao,Liqing Xu,Liqun Hu,Kaiyun Chen 한국물리학회 2014 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.64 No.9

A transient burst (2 ms, an order of the fast-particle slowdown timescale) of a spontaneous snakeis observed for the first time in a HT-7 heavy impurity ohmic plasma. The features of the low-Zimpurity snake are presented. The flatten electron profile due to the heavy impurity reveals theformation of a large magnetic island. The foot of the impurity accumulation is consistent with thelocation of the transient snake. The strong frequency-chirping behaviors and the spatial structuresof the snake are also presented.

Long-lived Impurity-ion Snakes in the EAST ELM-free H-mode Sawtoothing Plasma

Tianpeng Ma,Liqing Xu,Liqun Hu 한국물리학회 2015 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.66 No.11

Two types of long-lived impurity-ion snakes (LLSs) including the ideal-like kink mode which damps before the large sawtooth crash, termed sawtooth-free LLSs (SF-LLSs) and complex LLSs (C-LLSs), which coexist with compound sawtooth and final damping after sawtooth crash were observed in EAST ELM-free H-mode sawtoothing plasma. These LLSs have an m = 1 structure, accompanied by several harmonic modes (m = 2, m = 3 . . .). There is a slight frequency-chirping behavior of the LLS. Similar with the typical sawtooth crash phase, a large crescent-shaped helical island-like structure in the core region of the C-LLSs was visible after the major crash of the coexisting compound sawtooth. The strong coupling of the C-LLSs and the 2/1 tearing mode (TM) can trigger a neo-classical tearing mode (NTM) due to a forced magnetic reconnection.

Preparation and Drug Release Behavior of Tussah Silk Fibroin Composite Membrane

Zhuang Hu,Kaixia An,Jia Wang,Xiaoxu Xu,Zhangpei Chen,Jianshe Hu,Liqun Yang 한국섬유공학회 2020 Fibers and polymers Vol.21 No.2

Silk fibroin (SF) aqueous solution was obtained by the degumming and dissolution of tussah silk, and then the obtained solution was chemically cross-linked with sodium alginate (SA) to form composite membrane, which could be used as a carrier for sustained drug release. The mechanical properties and dissolution rate of such composite membrane togetherwith the drug release behavior under different conditions were investigated. A series of structure-tunable composite membranes were prepared through altering the ingredients proportion, the pH value during fabrication, the concentration of Ca2+, and cross-linking time. The drug release behavior of the corresponding drug-loaded composite membrane was elaborate studied using artemisinin as the model drug. It was found that the drug release rate exhibited a decreasing trend with increasing the SF content, the Ca2+ concentration and the cross-linking time of the corresponding composite membrane. Moreover, the drug release behavior exhibited pH sensitivity, and the drug release rate could be promoted under weak alkaline conditions.

A new model approach to predict the unloading rock slope displacement behavior based on monitoring data

Jiang, Ting,Shen, Zhenzhong,Yang, Meng,Xu, Liqun,Gan, Lei,Cui, Xinbo Techno-Press 2018 Structural Engineering and Mechanics, An Int'l Jou Vol.67 No.2

To improve the prediction accuracy of the strong-unloading rock slope performance and obtain the range of variation in the slope displacement, a new displacement time-series prediction model is proposed, called the fuzzy information granulation (FIG)-genetic algorithm (GA)-back propagation neural network (BPNN) model. Initially, a displacement time series is selected as the training samples of the prediction model on the basis of an analysis of the causes of the change in the slope behavior. Then, FIG is executed to partition the series and obtain the characteristic parameters of every partition. Furthermore, the later characteristic parameters are predicted by inputting the earlier characteristic parameters into the GA-BPNN model, where a GA is used to optimize the initial weights and thresholds of the BPNN; in the process, the numbers of input layer nodes, hidden layer nodes, and output layer nodes are determined by a trial method. Finally, the prediction model is evaluated by comparing the measured and predicted values. The model is applied to predict the displacement time series of a strong-unloading rock slope in a hydropower station. The engineering case shows that the FIG-GA-BPNN model can obtain more accurate predicted results and has high engineering application value.

A new model approach to predict the unloading rock slope displacement behavior based on monitoring data

Ting Jiang,Zhenzhong Shen,Meng Yang,Liqun Xu,Lei Gan,Xinbo Cui 국제구조공학회 2018 Structural Engineering and Mechanics, An Int'l Jou Vol.67 No.2

To improve the prediction accuracy of the strong-unloading rock slope performance and obtain the range of variation in the slope displacement, a new displacement time-series prediction model is proposed, called the fuzzy information granulation (FIG)-genetic algorithm (GA)-back propagation neural network (BPNN) model. Initially, a displacement time series is selected as the training samples of the prediction model on the basis of an analysis of the causes of the change in the slope behavior. Then, FIG is executed to partition the series and obtain the characteristic parameters of every partition. Furthermore, the later characteristic parameters are predicted by inputting the earlier characteristic parameters into the GA-BPNN model, where a GA is used to optimize the initial weights and thresholds of the BPNN; in the process, the numbers of input layer nodes, hidden layer nodes, and output layer nodes are determined by a trial method. Finally, the prediction model is evaluated by comparing the measured and predicted values. The model is applied to predict the displacement time series of a strong-unloading rock slope in a hydropower station. The engineering case shows that the FIG-GA-BPNN model can obtain more accurate predicted results and has high engineering application value.