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Wang T.,Hohai University | Chen J.-S.,Hohai University | Wang T.,Huzhou Vocational and Technological College
Yantu Gongcheng Xuebao/Chinese Journal of Geotechnical Engineering | Year: 2014

The dam seepage flow contains many kinds of materials, forming the information flow, the information entropy of which can be used to determine the nature of the flow field; and the water chemistry and environmental isotope detection methods have been widely applied. Based on the knowledge of information entropy and set pair analysis, a new method consisting of water chemistry and environmental isotope detection, entropy weight-set pair analysis model, is introduced to ascertain the dam concentration leakage channels. Firstly, PH, conductance, Cl-, δD and δ18O are chosen as five detection indexes, and the connection degree of each index value to the classification standard is calculated. Then, the weight of each index is determined by using the information entropy weight method based on the principle of the maximum entropy. After that, the comprehensive connection degree of all samples from the drilling is calculated, and thus all the samples are classified so as to determine the resource of water. Finally, this new method is applied to detect the dam leakage channels of one south reservoir and the results are tested and improved by the method of horizontal velocity and temperature detection. It is concluded that the results of the entropy weight-set pair analysis model match those of the horizontal velocity and temperature detection very well. ©, 2014, Nanjing Hydraulic Research Institute. All right reserved.

Wang T.,Hohai University | Chen J.-S.,Hohai University | Wang T.,Huzhou Vocational and Technological College | Wang S.,Hohai University
Natural Hazards | Year: 2015

With the rapid development of industry and projects for ensuring the amounts of water that those industries require, the capacities and scales of hydraulic structures including reservoirs, dams, and weirs have increased sharply. Numerous dams experience some seepage, when water is held behind them; thus, dam leakage detection has been and continues to be a major concern. The basic task involves finding the path of the leakage, especially the concentrated leakage path. Using tracer techniques, we treat dam leaks as multiple attribute evaluation problems, which is one innovation presented in this paper. Entropy weight-set pair analysis, a new method of identifying leaks, is introduced. The water samples and the information flows including conductivity, pH, Cl−, D, and 18O are set as alternatives and indexes, respectively. Then, the connection degree is calculated according to set pair analysis, followed by the weight of each index using an information entropy weight method based on the principle of maximum entropy. Finally, the integrated degree of connection of all the samples is calculated, to provide a basis for classifying water samples and judging the adequacy of the water resources. To verify the validity and feasibility of this proposed model, the Ling’ao reservoir, which is situated in Guangdong province of China’s southeastern monsoon zone and notable for its particularly heavy seepage is taken as a case study. The results indicate that the model is suitable for objectively analyzing dam seepage problems, especially given that the results match those obtained for the horizontal velocity as measured with drillings and the temperature distribution across the dam body. © 2014, Springer Science+Business Media Dordrecht.

Yu Z.,Huzhou Vocational and Technological College | Sheng H.,Huzhou Vocational and Technological College | Zhen N.,Huzhou Vocational and Technological College
Shuju Caiji Yu Chuli/Journal of Data Acquisition and Processing | Year: 2011

An algorithm for estimating non-line of sight (NLOS) based on the ratio of the single-path arrival time to the received energy is presented to reduce effects on the non-line of sight error when a wireless sensor network has locating nodes. An NLOS formula based on the model of signal propagation path loss is constructed, and corrected in view of the antenna system's directivity. The measured data show that the node location error reduces significantly within 45 cm after the nodes are modified by NLOS. The method can meet the location requirements for all kinds of wireless sensor networks.

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