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874 results on '"Yu Zhiwu"'

1. Research on the performance evolution of concrete under the coupling effects of sulfate attack and carbonation

Author

Chen Ying, Liu Peng, Yu Zhiwu, Li Siyang, Hu Cheng, and Lu Dapeng

Subjects
Coupling effect, Sulfate attack, Carbonation, Erosion product, Deterioration mechanism, Performance, Mining engineering. Metallurgy, TN1-997
Abstract

In this study, three coupled modes of coupling effect of sulfate attack and carbonation of concrete were carried out to investigate the change of mass, mechanical properties and apparent morphology. The phase composition, microstructure and morphological characteristics of erosion products were also studied by using environment scanning electron microscope (ESEM-EDS), Fourier infrared spectrometer (FTIR), and X-ray diffraction (XRD). The results indicated that the coupled mode played an obvious effect on the performance and microstructures of specimen due to effects of coupled mode on the deterioration mechanism and erosion products. The surface feature of specimen became worse with carbonation time, and plenty of surface efflorescence and desquamation of products were observed under the coupled mode of carbonation followed by sulfate attack. The relative compressive strength and dynamic elastic modulus of concrete specimen first increased and then decreased with carbonation time, and there existed relationship of a cubic function of single variable between them. The relative mass of concrete specimen increased with the increase of the erosion age of sulfate attack. The difference of the carbonation time per period test played a significant effect on the relative compressive strength and dynamic elastic modulus of concrete specimen, which was due to the dominant effect of carbonation.

Published
2023
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2. Effects of Side Load Chains of a Combine Harvester on Unbalanced Dynamic Vibrations of Its Threshing Drum

Author

Yu Zhiwu, Li Yaoming, Wang Xinzhong, Tang Zhong, and Jiahui Lu

Subjects
Engineering (General). Civil engineering (General), TA1-2040
Abstract

In order to study the influence of the side drive on the balance state of the threshing drum, this paper used the side eccentric load chain drive as the power on the threshing drum dynamic balance test bench. By analyzing the influence of different radial phases, different axial distances, and spiral combinations of the threshing drum on the counterweight, this paper studies the law of the effect of side partial load chain drive on the dynamic balance of the threshing drum and finds that the side chain drive has obvious influence on the unbalance phase of the threshing drum and the change of the axial distance of unbalance has little effect on the equilibrium state of the threshing drum. And from this, a vibration balance method based on the equivalent unbalance of the chain drive is proposed, which can predict and calculate the unbalance of the threshing drum. The unbalance of the threshing drum predicted by this method is smaller than the actual measured unbalance. The maximum error is 32.64% and the minimum error is 4.6%. In the two tests, the predicted unbalance is 1.24 mm/s in amplitude and 270 degrees in phase and amplitude 1.4 mm/s and phase 120 degrees, respectively. The measured unbalance is amplitude 1.587 mm/s and phases 286 degrees. The error between prediction and actual measurement is less than 32.64%, and the unbalance amplitudes that can be reduced by one-time dynamic balance are 0.856 mm/s and 0.674 mm/s, respectively. The research results in this paper provide an effective method for the balance state of the multidrum side chain transmission.

Published
2021
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3. Multi-View Graph Representation Learning Beyond Homophily

Author

Lin, Bei, Li, You, Gui, Ning, Xu, Zhuopeng, and Yu, Zhiwu

Subjects
Computer Science - Machine Learning, Computer Science - Social and Information Networks
Abstract

Unsupervised graph representation learning(GRL) aims to distill diverse graph information into task-agnostic embeddings without label supervision. Due to a lack of support from labels, recent representation learning methods usually adopt self-supervised learning, and embeddings are learned by solving a handcrafted auxiliary task(so-called pretext task). However, partially due to the irregular non-Euclidean data in graphs, the pretext tasks are generally designed under homophily assumptions and cornered in the low-frequency signals, which results in significant loss of other signals, especially high-frequency signals widespread in graphs with heterophily. Motivated by this limitation, we propose a multi-view perspective and the usage of diverse pretext tasks to capture different signals in graphs into embeddings. A novel framework, denoted as Multi-view Graph Encoder(MVGE), is proposed, and a set of key designs are identified. More specifically, a set of new pretext tasks are designed to encode different types of signals, and a straightforward operation is propxwosed to maintain both the commodity and personalization in both the attribute and the structural levels. Extensive experiments on synthetic and real-world network datasets show that the node representations learned with MVGE achieve significant performance improvements in three different downstream tasks, especially on graphs with heterophily. Source code is available at \url{https://github.com/G-AILab/MVGE}., Comment: 20 pages, 10 figures, accepted by ACM Transaction on Knowledge Discovery in Data

Published
2023

4. Open-Circuit Fault Detection Method for Full-Bridge Modular Multilevel Converter Sub-Modules

Author

Yu, Zhiwu, Yang, Weiye, Zhang, Pinjia, Zhu, Wenjie, Liu, Bi, Hu, Cungang, Cao, Wenping, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Tan, Kay Chen, Series Editor, Hu, Cungang, editor, and Cao, Wenping, editor

Published
2024
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