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Your search keyword '"Liu, Xiaochen"' showing total 14 results
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14 results on '"Liu, Xiaochen"'

8. Compressive Creep Prediction of Corundum-Mullite Refractories Based on BP Neural Network

Author

Pan Chuancai, Xue Fei, Lin Guowei, Xie Jinli, Zeng Luju, Liu Yueqiang, Yi Shuai, Liu Xiaochen, Deng Lina, and Zhang Hang

Subjects
Materials science, Artificial neural network, engineering, Compressive creep, Corundum, Mullite, Composite material, engineering.material
Abstract

Compressive creep of corundum-mullite refractories is an important performance to measure whether they can be used stably for a long time at high temperature. Therefore, a compressive creep prediction method of corundum-mullite refractory based on BP neural network is proposed. The inputs of the BP neural network are the content of Al2O3, SiO2, Fe2O3 and the time of high temperature whereas creep rate is the output. The results show that the predicted results can correspond well with the experimental results. The developed BP neural network model can efficiently and accurately predict the creep rate of corundum-mullite refractories.

Published
2019

9. Microgrid Control Technology Based on Neural-Like P Systems with State Values

Author

Liu Yangyang, Liu Xiaochen, Liang Bin, Yang Guang, and Zehao He

Subjects
Control theory, Computer science, Control (management), State (computer science), Microgrid
Abstract

By utilizing the mobile energy storage characteristics and random dispersion of electric vehicles, it is coordinated with the wind power storage unit to optimize the economic and reliable operation of the system.In this paper, the integrated microgrid of wind, photovoltaic, energy storage and electric vehicle is studied. Under the premise of ensuring the safety and stability of the system, the control goal is to meet the needs of electric vehicles users as much as possible and to maximize the utilization ratio of new energy. The operation control strategies of power battery under disordered charging and orderly charging/discharging are considered respectively. Subsequently, the operation model of wind turbine generation and electric vehicles orderly charging/discharging is established by using the neural-like P system with "state value", and the operation modes of each unit are obtained according to the operation of microgrid. Finally, the effects of disordered charging and orderly charging/discharging of electric vehicles on the safe and stable operation of the microgrid system are compared by simulation experiments.

Published
2019

12. Highly sensitive biosensor based on a microcantilever and alternating current electrothermal technology.

Author

Wang, Lihao, Fu, Dengyuan, Liu, Xiaochen, Zhao, Junyuan, Zhao, Jicong, Yuan, Quan, Zhu, Yinfang, Yang, Jinling, and Yang, Fuhua

Subjects
ALTERNATING currents, VIBRIO parahaemolyticus, DETECTION limit, MAGNITUDE (Mathematics), CANTILEVERS
Abstract

This work presents a highly sensitive biosensor based on a microcantilever and alternating current (AC) electrothermal technology. The AC electrothermal unit was developed and integrated with the cantilever chip to improve the capture efficiency of the molecules under test. The AC electrothermal effect enhanced the aggregation of molecules around the microcantilever, increased their binding probability to the sensor and improved the detection performance of the biosensor. This microcantilever sensor was used to detect Vibrio parahaemolyticus and achieved a detection limit of ∼5 × 105 CFU ml−1, one order of magnitude lower than that of the sensor without AC electrothermal technology. Meanwhile, the detection time was reduced to 40 min, nearly half that of the conventional cantilever sensors. [ABSTRACT FROM AUTHOR]

Published
2021
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