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A recently proposed model coupling with the solid-fluid of the saturated sand was utilized to study the deformation band.
Based on the critical state plasticity model by Borja and Andrade, the hydraulic conductivity tensor was naturally treated
as a function of the spatial discretization matrix about the displacement and the stress field, allowing a more realistic
representation of the physical phenomenon. The fully Lagrangian form of the Darcy law was resolved by Piola algorithm, and
then the flow law was gained, leading to the implementation of a modified model of the saturated sand. Then the criterion
for the onset of localization was derived and utilized to detect instability. The constitutive model was implemented in a
finite element program coded by FORTRAN, which was used to predict the formation and development of shear bands in plane strain
compression of saturated sand. At last, the formation mechanism of the shear band was discussed. It is shown that the model
works well, and the simulation sample bifurcates at 1.18% axial strain, which is in a good qualitative agreement with the
experiment. The pore pressure greatly affects the onset and development of the deformation band, and it obviously increases
around the localization-prone regions with the direction toward the outer side of the normal of the shear band, while the
pore stress flows nearly horizontally and is distributed equally far away the shear band region.
Foundation item: Project(2006G007-C) supported by the Foundation of the Science and Technology Section of Ministry of Railway of China; Project(77206)
supported by the Excellent PhD Thesis Innovation Foundation of Central South University, China 相似文献
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In order to predict the danger of coal and gas outburst in mine coal layer correctly, on the basis of the VLBP and LMBP algorithm in Matlab neural network toolbox, one kind of modified BP neural network was put forth to speed up the network convergence speed in this paper. Firstly, according to the characteristics of coal and gas outburst, five key influencing factors such as excavation depth, pressure of gas, and geologic destroy degree were selected as the judging indexes of coal and gas outburst. Secondly, the prediction model for coal and gas outburst was built. Finally, it was verified by practical examples. Practical application demonstrates that, on the one hand, the modified BP prediction model based on the Matlab neural network toolbox can overcome the disadvantages of constringency and, on the other hand, it has fast convergence speed and good prediction accuracy. The analysis and computing results show that the computing speed by LMBP algorithm is faster than by VLBP algorithm but needs more memory. And the resuits show that the prediction results are identical with actual results and this model is a very efficient prediction method for mine coal and gas outburst, and has an important practical meaning for the mine production safety. So we conclude that it can be used to predict coal and gas outburst precisely in actual engineering. 相似文献
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利用极限氧指数(LOI)、酒精喷灯燃烧实验、锥形量热仪,热重(TG)分析等方法对比研究了滑石粉、碳酸钙、硼酸锌和炭黑对阻燃聚丙烯(PP)土工格栅试样阻燃性能的影响,并分析了这几种阻燃性能测试结果之间的相关性。结果表明,LOI与酒精喷灯燃烧实验结果及点燃时间(TTI)之间的相关性较好,4种填料的加入都会降低试样的LOI和TTI,其中碳酸钙和炭黑含量较高时,试样的LOI下降幅度较大,并使试样无法通过酒精喷灯燃烧实验;但锥形量热仪测试结果表明,4种填料对试样燃烧过程的影响有所差别,硼酸锌的加入可降低试样的热释放速率(HRR)、总释放热(THR)和生烟速率(SPR);炭黑的加入提高了试样的热稳定性并降低了试样的HRR,但对THR和SPR有不利影响;滑石粉和碳酸钙的加入降低了试样的SPR,但使试样的HRR及THR增大。结合各种测试方法,可以判定4种无机填料中硼酸锌为阻燃PP土工格栅试样最适宜的无机填料。 相似文献
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在大量调研的基础上,结合作者在试验中的经验教训,对目前混凝土结构抗火性能试验中存在的问题做了阐述,这些问题有的是关于试验标准和方法认识上存在一定争议的,有些是实验室和真实情况之间的差异的,有些是目前技术水平限制所产生的,有些是目前试验领域缺乏研究或还没有认识到需要研究的问题,讨论了一些有价值的建议和研究方向,对今后混凝土结构抗火性能试验有较大的借鉴意义。 相似文献