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用光学及电子显微镜(SEM.TEM)观察不同热处理的40Cr 钢的冲击及断裂韧性断口、及金相组织,阐明其间相互关系;断口结构可反映断裂特征,组织情况;细化晶粒提高强度、塑性和冲击韧性,但却减少脆断的特性距离 l 因而降低 K_(1c)模;减少碳(杂质)偏聚而使其呈较均匀地分布,从而减少可诱发塑坑的较粗大的碳(杂质)化合物的析出,即增加塑坑的间距 di 以及增加塑断组成物。从而都可增加断裂临界应变 ef,都可以提高 K_(1c)40Cr 复合热处理既靠先超高温淬、回火以减少碳(杂质)偏聚,改善其分布,以反增加位错马氏体从而提高 K_(1c),也靠后淬、回火细化晶粒而提高强度、塑性和冲击韧性,各自发挥长处达到强韧化。  相似文献   
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An a posteriori (off-line) approach to the simultaneous detection and identification of quasi-periodic fragments in a numerical sequence using their segments is analyzed. The solution of the problem is proposed for the case when the number of the desired fragments is known. The following assumptions are made. (i) Each desired fragment of the numerical sequence coincides with an element of the given alphabet of the reference sequences that have equal lengths (i.e., number of elements). (ii) Only a segment (part) of the desired fragment can be processed; unprocessable parts of the fragment are interpreted as lost data. (iii) The numbers of the elements in the sequence that correspond to the beginning of the desired fragment and the boundaries of the segment in the fragment represent deterministic (rather than random) quantities; the boundaries of the segments are different for different fragments; and the desired fragments are quasi-periodic in the sequence. (iv) Gaussian uncorrelated noise impedes the observation of the sequence that contains quasi-periodic segments of the reference sequences. It is demonstrated that the essence of the problem under study lies in the verification of a set of hypotheses on the mean value of a random Gaussian vector (the power of this set exponentially increases with an increase in the dimension of the vector—the sequence length). An effective a posteriori algorithm that provides for maximum-likelihood detection and identification is validated. The estimates of the time and space complexity are related to the parameters of the problem. The results of the numerical simulation are presented. This work was supported by the Russian Foundation for Basic Research, project no. 03-01-00036 and 06-01-00058. Aleksandr V. Kel’manov. Born April 25, 1952. Graduated from Izhevsk State Technical University in 1974. Received candidate’s degree in 1980 and doctoral degree in 1994. Leading researcher of the Sobolev Institute of Mathematics, Siberian Division, Russian Academy of Sciences. Scientific interests: mathematical methods for pattern recognition; discrete optimization; effective algorithms for the analysis and recognition of random sequences; algorithms for the solution of applied problems; and methods and algorithms for the processing, recognition, and synthesis of voice signals. Author of more than 120 papers. Sergei A. Khamidullin. Born March 28, 1952. Graduated from Novosibirsk State University in 1974. Received candidate’s degree in 1997. Senior researcher of the Sobolev Institute of Mathematics, Siberian Division, Russian Academy of Sciences. Scientific interests: mathematical methods for pattern recognition; discrete optimization; effective algorithms for the analysis and recognition of random sequences; algorithms for the solution of applied problems; and methods and algorithms for the processing, recognition, and synthesis of voice signals. Author of more than 80 papers.  相似文献   
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The microscopic structures of PLZT(7.9/70/30 and x/65/35, x = 7 or 8) ceramics were studied by means of transmission electron microscopy. The presence of micro-regions in PLZTs was first verfied.  相似文献   
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A dispersion equation for the capillary oscillations of a charged drop of incompressible liquid possessing a finite electric conductivity is derived with an allowance for the energy lost as a result of the electromagnetic wave emission. The magnitude of the electromagnetic radiation losses of the oscillating drop linearly increases with the electric conductivity and the surface mobility of charge carriers.  相似文献   
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A new method for compression of grayscale images containing a small number of graphical elements is proposed. The method is characterized by high compression ratios, small losses, and good readability of the processed images. It is based on morphological methods of image analysis and could be used to store images of documents produced by fax machines, scanners, etc. Igor I. Falomkin. Born 1979. Graduated from the Faculty of Physics, Moscow State University, in 2001. Scientific interests: image analysis and recognition, analysis and interpretation of experimental data.  相似文献   
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