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RISS 인기검색어
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- 저자 : Yingming Zhang (검색결과 5 건)
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Effects of Zn content on microstructure and magnetic properties of MnZn ferrite
Yingming Zhang,Yujie Yang,Dongyang Chen,Congliang Chen,Yuting Meng 한양대학교 청정에너지연구소 2023 Journal of Ceramic Processing Research Vol.24 No.2
The Mn1-xZnxFe2O4 (x = 0.46, 0.47, 0.48, 0.50, 0.51) ferrite materials were prepared by solid-state reaction. The effects ofvarying Zn concentration on the magnetic characteristics and microstructure of MnZn ferrites were investigated. All of theseferrites are one spinel phase, according to XRD analysis, and no additional heterogeneous phases are generated. Thediffraction peaks of the samples appear to be shifted to a higher angle compared to the standard cards. The sample's very bigand irregular grain development caused the sample's grain size to vary as the zinc level increased. The power loss of MnZnferrite can be decreased because to this phenomena. The PCV value decreases as the Zn level of the samples increases. The PCVof this ferrite is as high as 242.6 mW/cm3 at a frequency of 150 kHz with a Zn concentration of x = 0.46. Under the same testcircumstances, ferrite's PCV value is only 115.2mW/cm3 when the Zn concentration is x = 0.48. The complex permeability ofthe samples rises with an increase in Zn concentration. In the ferrite sample with the highest Zn content (x = 0.51), its μ' valuekeeps at a high level with the change of frequency. When the frequency is 10 kHz, the μ' value is as high as 260.9. Additionally,all of these ferrite samples demonstrated stability against interference at frequencies lower than 150 kHz.
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Optimized inverse distance weighted interpolation algorithm for γ radiation field reconstruction
Zhang Biao,Cao Jinjia,Lin Shuang,Li Xiaomeng,Zhang Yulong,Zheng Xiaochang,Chen Wei,Song Yingming 한국원자력학회 2024 Nuclear Engineering and Technology Vol.56 No.1
The inversion of radiation field distribution is of great significance in the decommissioning sites of nuclear facilities. However, the radiation fields often contain multiple mixtures of radionuclides, making the inversion extremely difficult and posing a huge challenge. Many radiation field reconstruction methods, such as Kriging algorithm and neural network, can not solve this problem perfectly. To address this issue, this paper proposes an optimized inverse distance weighted (IDW) interpolation algorithm for reconstructing the gamma radiation field. The algorithm corrects the difference between the experimental and simulated scenarios, and the data is preprocessed with normalization to improve accuracy. The experiment involves setting up gamma radiation fields of three Co-60 radioactive sources and verifying them by using the optimized IDW algorithm. The results show that the mean absolute percentage error (MAPE) of the reconstruction result obtained by using the optimized IDW algorithm is 16.0%, which is significantly better than the results obtained by using the Kriging method. Importantly, the optimized IDW algorithm is suitable for radiation scenarios with multiple radioactive sources, providing an effective method for obtaining radiation field distribution in nuclear facility decommissioning engineering.
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Development of Strain Measurement in Superconducting Magnet Through Fiber Bragg Grating
Hongjie Zhang,Fanping Deng,Qiuliang Wang,Luguang Yan,Yingming Dai,Keeman Kim IEEE 2008 IEEE transactions on applied superconductivity Vol.18 No.2
<P>Temperature and strain responses of fiber Bragg grating sensors were measured in cryogenic environment. With temperature from room temperature down to 77 K or 4.2 K, the temperature response was found to be relatively linear above 100 K, and the temperature sensitivity decreases with the decrease of temperature, and to approximately zero for temperature less than 50 K. Technologies were developed to eliminate the multi-peaks in strain experiment, so the strain response was measured at 77 K, and was found to be linear at constant temperatures.</P>
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Feng, Xueqing,Bao, Yaxin,Liu, Lijun,Huang, Lizhong,Zhang, Yingming Journal of International Conference on Electrical 2012 Journal of international Conference on Electrical Vol.1 No.2
This paper presents the performance investigation and design technology of a Line Start-up Permanent Magnet Synchronous Motor (LSPMSM) with super premium efficiency, including a design consideration and evaluation for motor start-up, key performance, and advanced finite element analysis FEA) for the design, improvement and verification, prototype build and test, design and test data comparison with a $Premium^{(R)}$ Efficient Induction Motor (PEIM). To assess the design technology, the LSPMSM prototype was built amended from a PEIM with the same frame, stator punching and rated output. Based on the prototype test, two novel design improvements and analyses have been done to eliminate noise and vibration. Additionally, the comparisons with the PEIM on the power factor, efficiency, frame size and active material consumption indicated that a significant performance improvement and active material cost reduction can be achieved by the LSPMSM.
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Shu Wang,Houpu Yang,Jiajia Guo,Miao Liu,Fuzhong Tong,Yingming Cao,Bo Zhou,Peng Liu,Lin Cheng,Fei Xie,Deqi Yang,Jiaqing Zhang 한국바이오칩학회 2011 BioChip Journal Vol.5 No.1
Neo-adjuvant chemotherapy for breast cancer substantially benefits patients who achieve pathological response. However, clinical or pathological response information can only be obtained a period of time after chemotherapy. The identification of novel bio-markers or the application of new technique that can be used to predict treatment response before che-motherapy would allow therapy to be tailored on an individual patient basis. The purpose of this study is to identify the chemo-sensitivity and chemo-resistance related proteins using antibody microarray profiling, and to develop a multi-protein predictive model for breast cancer. Total protein was extracted from core needle biopsy samples obtained from 15 patients before treatment with neo-adjuvant TA(combination of taxanes and anthracycline) chemotherapy. Protein profiling was analyzed by antibody microarray. 10 pati-ents were used as training set to develop the predictive model using the software PAM(prediction analysis of microarray). Another 5 patients were used as a validation set to test the model. In cross-validation, the mole-cular predictive model showed an accuracy of 90%, in independent validation, the model classified the cases with an accuracy of 80%. In conclusion, the proteomic predictive model has the potential to predict pathological response to neo-adjuvant TA chemotherapy.
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