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Experimental study on temperature stress calculation and temperature control optimization of concrete based on early age parameters
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作者 HU Yintao ZHOU Qiujing +3 位作者 YANG Ning QIAO Yu JIA Fan Xin Jianda 《中国水利水电科学研究院学报(中英文)》 北大核心 2023年第6期586-597,共12页
Temperature control curve is the key to achieving temperature control and crack prevention of high concrete dam during construction,and its rationality depends on the accurate measurement of temperature stress.With th... Temperature control curve is the key to achieving temperature control and crack prevention of high concrete dam during construction,and its rationality depends on the accurate measurement of temperature stress.With the simulation testing machine for the temperature stress,in the present study,we carried out the deformation process tests of concrete under three temperature curves:convex,straight and concave.Besides,we not only measured the early-age elastic modulus,creep parameters and stress process,but also proposed the preferred type.The results show that at early age,higher temperature always leads to greater elastic modulus and smaller creep.However,the traditional indoor experiments have underestimated the elastic modulus and creep development at early age,which makes the calculated value of temperature stress too small,thus increasing the cracking risk.In this study,the stress values of the three curves calculated based on the strain and early-age parameters are in good agreement with the temperature stress measured by the temperature stress testing machine,which verifies the method accuracy.When the temperature changes along the concave curve,the law of stress development is in consistent with that of strength.Under this condition,the stress fluctuation is small and the crack prevention safety of the concave type is higher,so the concave type is better.The test results provide a reliable basis and support for temperature control curve design and optimization of concrete dams. 展开更多
关键词 concrete dam temperature control curve early-age parameters temperature stress testing machine elastic modulus
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The Fuzzy Cluster Analysis in Identification of Key Temperatures in Machine Tool
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作者 ZHAO Da-quan 1, ZHENG Li 1, XIANG Wei-hong 1, LI Kang 1, LIU Da-cheng 1, ZHANG Bo-peng 2 (1. Department of Industrial Engineering, Tsinghua University, 2. Department of Precision Instruments and Mechanology, Tsinghua University, B eijing 100084, China) 《厦门大学学报(自然科学版)》 CAS CSCD 北大核心 2002年第S1期88-89,共2页
The thermal-induced error is a very important sour ce of machining errors of machine tools. To compensate the thermal-induced machin ing errors, a relationship model between the thermal field and deformations was need... The thermal-induced error is a very important sour ce of machining errors of machine tools. To compensate the thermal-induced machin ing errors, a relationship model between the thermal field and deformations was needed. The relationship can be deduced by virtual of FEM (Finite Element Method ), ANN (Artificial Neural Network) or MRA (Multiple Regression Analysis). MR A is on the basis of a total understanding of the temperature distribution of th e machine tool. Although the more the temperatures measured are, the more accura te the MRA is, too more temperatures will hinder the analysis calculation. So it is necessary to identify the key temperatures of the machine tool. The selectio n of key temperatures decides the efficiency and precision of MRA. Because of th e complexities and multi-input and multi-output structure of the relationships , the exact quantitative portions as well as the unclear portions must be taken into consideration together to improve the identification of key temperatures. I n this paper, a fuzzy cluster analysis was used to select the key temperatures. The substance of identifying the key temperatures is to group all temperatures b y their relativity, and then to select a temperature from each group as the repr esentation. A fuzzy cluster analysis can uncover the relationships between t he thermal field and deformations more truly and thoroughly. A fuzzy cluster ana lysis is the cluster analysis based on fuzzy sets. Given U={u i|i=0,...,N}, in which u i is the temperature measured, a fuzzy matrix R can be obta ined. The transfer close package t(R) can be deduced from R. A fuzzy clu ster of U then conducts on the basis of t(R). Based on the fuzzy cluster analysis discussed above, this paper identified the k ey temperatures of a horizontal machining center. The number of the temperatures measured was reduced to 4 from 32, and then the multiple regression relationshi p models between the 4 temperatures and the thermal deformations of the spindle were drawn. The remnant errors between the regression models and measured deform ations reached a satisfying low level. At the same time, the decreasing of tempe rature variable number improved the efficiency of measure and analysis greatly. 展开更多
关键词 The Fuzzy Cluster Analysis in Identification of Key temperatures in Machine Tool
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