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4. Numerical research on flow field starting of supersonic compressor in outlet-opening wind tunnel

Author

ZHANG Tianlong, WANG Xu, LIN Tianqi, XU Xiangshen, and MU Wenpeng

Subjects
outlet-opening wind tunnel, supersonic, flow filed starting, compressor, cascade flow field, Motor vehicles. Aeronautics. Astronautics, TL1-4050
Abstract

The process from test starting to supersonic flow state established in an outlet-opening wind tunnel，i. e. the starting problem of supersonic flow，has become a recognized challenge. In order to establish the feasible flow field starting method，and lay the foundation for the use of outlet-opening wind tunnel，three-dimensional numerical simulation research is carried out，which is based on a certain wind tunnel，and taken the panel blade of supersonic compressor as the research object. The failure reason of supersonic flow field starting on experimental condition is analyzed，and three flow field starting schemes are established. The results show that the starting failure reason is the formation of a strong normal shock wave at the leading edge of the cascade. Increasing the inlet total pressure alone cannot establish the supersonic flow. The supersonic cascade flow field can be started by increasing the overflow gap width on lower wall side，but the number of effective cascade passages is decreased and the boundary layer thickness is increased. Maintaining the width of overflow gap on the upper and lower walls at more than 1.0 pitch，the setting upper and lower supersonic walls in front of cascade and conducting suction can effectively start the supersonic flow field. The maximum fluctuation of outlet Mach number is 0.01，the maximum fluctuation of outlet flow angle is 0.09°. The periodicity can meet the experimental requirements.

Published
2024
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17. Passive microfluidic devices for cell separation

Author

Zhang, Tianlong, Di Carlo, Dino, Lim, Chwee Teck, Zhou, Tianyuan, Tian, Guizhong, Tang, Tao, Shen, Amy Q., Li, Weihua, Li, Ming, Yang, Yang, Goda, Keisuke, Yan, Ruopeng, Lei, Cheng, Hosokawa, Yoichiroh, and Yalikun, Yaxiaer

Published
2024
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22. Can experiment determine the stacking fault energy of metastable alloys?

Author

Suna, Xun, Lu, Song, Xie, Ruiwen, An, Xianghai, Li, Wei, Zhang, Tianlong, Liang, Chuanxin, Ding, Xiangdong, Wang, Yunzhi, Zhang, Hualei, and Vitos, Levente

Subjects
Condensed Matter - Materials Science, Physics - Applied Physics
Abstract

Stacking fault energy (SFE) plays an important role in deformation mechanisms and mechanical properties of face-centered cubic (fcc) metals and alloys. In metastable fcc alloys, the SFEs determined from density functional theory (DFT) calculations and experimental methods often have opposite signs. Here, we show that the negative SFE by DFT reflects the thermodynamic instability of the fcc phase relative to the hexagonal close-packed one; while the experimentally determined SFEs are restricted to be positive by the models behind the indirect measurements. We argue that the common models underlying the experimental measurements of SFE fail in metastable alloys. In various concentrated solid solutions, we demonstrate that the SFEs obtained by DFT calculations correlate well with the primary deformation mechanisms observed experimentally, showing a better resolution than the experimentally measured SFEs. Furthermore, we believe that the negative SFE is important for understanding the abnormal behaviors of partial dislocations in metastable alloys under deformation. The present work advances the fundamental understanding of SFE and its relation to plastic deformations, and sheds light on future alloy design by physical metallurgy.

Published
2020

32. Machine Learning Allows Calibration Models to Predict Trace Element Concentration in Soil with Generalized LIBS Spectra

Author

Sun, Chen, Tian, Ye, Gao, Liang, Niu, Yishuai, Zhang, Tianlong, Li, Hua, Zhang, Yuqing, Yue, Zengqi, Delepine-Gilon, Nicole, and Yu, Jin

Subjects
Physics - Chemical Physics, Computer Science - Machine Learning, Physics - Instrumentation and Detectors, Physics - Plasma Physics
Abstract

Calibration models have been developed for determination of trace elements, silver for instance, in soil using laser-induced breakdown spectroscopy (LIBS). The major concern is the matrix effect. Although it affects the accuracy of LIBS measurements in a general way, the effect appears accentuated for soil because of large variation of chemical and physical properties among different soils. The purpose is to reduce its influence in such way an accurate and soil-independent calibration model can be constructed. At the same time, the developed model should efficiently reduce experimental fluctuations affecting measurement precision. A univariate model first reveals obvious influence of matrix effect and important experimental fluctuation. A multivariate model has been then developed. A key point is the introduction of generalized spectrum where variables representing the soil type are explicitly included. Machine learning has been used to develop the model. After a necessary pretreatment where a feature selection process reduces the dimension of raw spectrum accordingly to the number of available spectra, the data have been fed in to a back-propagation neuronal networks (BPNN) to train and validate the model. The resulted soilindependent calibration model allows average relative error of calibration (REC) and average relative error of prediction (REP) within the range of 5-6%., Comment: 34 pages

Published
2019
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39. Neutralization mechanism of a human antibody with pan-coronavirus reactivity including SARS-CoV-2

Author

Sun, Xiaoyu, Yi, Chunyan, Zhu, Yuanfei, Ding, Longfei, Xia, Shuai, Chen, Xingchen, Liu, Mu, Gu, Chenjian, Lu, Xiao, Fu, Yadong, Chen, Shuangfeng, Zhang, Tianlong, Zhang, Yaguang, Yang, Zhuo, Ma, Liyan, Gu, Wangpeng, Hu, Gaowei, Du, Shujuan, Yan, Renhong, Fu, Weihui, Yuan, Songhua, Qiu, Chenli, Zhao, Chen, Zhang, Xiaoyan, He, Yonghui, Qu, Aidong, Zhou, Xu, Li, Xiuling, Wong, Gary, Deng, Qiang, Zhou, Qiang, Lu, Hongzhou, Ling, Zhiyang, Ding, Jianping, Lu, Lu, Xu, Jianqing, Xie, Youhua, and Sun, Bing

Published
2022
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