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- 저자 : Qiuyang Wei (검색결과 2 건)
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Effects of Freeze-Thaw-Drying-Wetting Cycles on Undrained Creep Behavior of an Expansive Clay
Wei-lie Zou,Qiuyang Pei,Zhong Han,Xie-qun Wang 대한토목학회 2024 KSCE Journal of Civil Engineering Vol.28 No.7
The creep behavior of an expansive clay under undrained conditions is investigated considering the effects of freeze-thaw-drying-wetting (FTDW) cycles. Compacted specimens were subjected to 1, 4, and 10 FTDW treatments. Macroscopic changes were recorded and mercury intrusion porosimetry tests were conducted to reveal the expansive clay’s structure evolution during the FTDW treatments. The undrained shear strength was first determined by the consolidated undrained shear tests for as-compacted specimens. Subsequently, saturated undrained creep tests under low confining pressure were performed at various deviator stress levels (D) to study the axial strain development with time for specimens subjected to different FTDW cycles (NFTDW). Experimental results show that 1) the macropores increase with the newly emerged peak at a diameter between 10 μm to 20 μm and micropores decrease after FTDW cycles; 2) the axial instantaneous strain (ai), creep strain (ac), and total strain (at) increase with FTDW cycles. The ai-D-NFTDW and at-D-NFTDW relationships of the specimens are distributed on a unique surface under a certain confining pressure level; 3) the axial strain rate decreases dramatically within the first 2,000 min and then remains nearly constant. Studies in this paper are valuable for advancing the understanding of the influences of environmental factors on the creep behavior of expansive clays.
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Mobile Robot Obstacle Avoidance Algorithms Based on Information Fusion of Vision and Sonar
Hongwei Gao,Qiuyang Wei,Yang Yu,Jinguo Liu 보안공학연구지원센터 2016 International Journal of Future Generation Communi Vol.9 No.8
In view of the problem of AS-R autonomous wheeled mobile robot obstacle avoidance, a rapid convergence of sonar and binocular stereovision sensor distance information in order to detect and avoid obstacle algorithm is proposed in this paper. The algorithm first uses binocular camera (CCD) to get three-dimensional image of the real environment, through the stereo matching and V-disparity method which is used to calculate disparity map, then obstacles is extracted by Hough lines detection algorithm, finally we will get information about obstacles and sonar return information with T-S fuzzy neural network fusion, then it will output walking controlled decisions. Experimental results proved that the algorithm is effective and practical.
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