基于模态重分析技术,提出一种适合全局有限元模型(global finite element model, GFEM)的突风动响应高效计算方法。针对模型局部结构质量或刚度的细微变化,进行增量建模,充分利用现有构型结果,避免了传统分析中重复计算的步骤。对于质...基于模态重分析技术,提出一种适合全局有限元模型(global finite element model, GFEM)的突风动响应高效计算方法。针对模型局部结构质量或刚度的细微变化,进行增量建模,充分利用现有构型结果,避免了传统分析中重复计算的步骤。对于质量阵的变化,以已有构型模态向量为初始向量,通过迭代分析进行特征值求解,针对刚度阵的微小变化,特别引入Sherman-Morrison-Woodbury公式,实现刚度逆矩阵的增量分析,从而克服了大规模GFEM模型的特征值求解效率低的问题,最终建立了一套适合于工程应用的GFEM突风高效动响应分析方法。采用GTA模型进行了突风分析算法的验证,在此基础上,基于某模型机翼,对模态重分析算法在突风动响应分析中的应用进行了研究。结果表明,通过LU分解可避免保存稠密形式的刚度逆矩阵,通过合理的松弛因子和收敛阈值,可有效提升计算效率。展开更多
The dynamic ground subsidence due to underground mining is a complicated time-dependent and rate- dependent process. Based. on the theory of rock rheology and probability integral method, this study developed the supe...The dynamic ground subsidence due to underground mining is a complicated time-dependent and rate- dependent process. Based. on the theory of rock rheology and probability integral method, this study developed the superposltlOn model for the prediction and analysis of the ground dynamic subsidence in mining area of thick !oose layer. The model consists of two parts （the prediction of overlying bedrock and the prediction of thick loose layer）. The overlying bedrock is regarded as visco-elastic beam, of which the dynamic subsidence is predicted by the Kelvin visco-elastic rheological model. The thick loose layer is regarded as random medium, and the ground dynamic subsidence, is predicted by the probability integral model. At last, the two prediction models are vertically stacked in the same coordinate system, and the bedrock dynamic subsidence is regarded as a variable mining thickness input into the prediction model of ground dynamic subsidence. The prediction results obtained were compared w^th actual movement and deformation data from Zhao I and Zhao II mine, central China. The agreement of the prediction results with the. field measurements.show that the superposition model （SM） is more satisfactory and the formulae obtained are more effective than the classical single probability Integral model（SPIM）, and thus can be effectively used for predicting the ground dynamic subsidence in mining area of thick loose layer.展开更多
文摘基于模态重分析技术,提出一种适合全局有限元模型(global finite element model, GFEM)的突风动响应高效计算方法。针对模型局部结构质量或刚度的细微变化,进行增量建模,充分利用现有构型结果,避免了传统分析中重复计算的步骤。对于质量阵的变化,以已有构型模态向量为初始向量,通过迭代分析进行特征值求解,针对刚度阵的微小变化,特别引入Sherman-Morrison-Woodbury公式,实现刚度逆矩阵的增量分析,从而克服了大规模GFEM模型的特征值求解效率低的问题,最终建立了一套适合于工程应用的GFEM突风高效动响应分析方法。采用GTA模型进行了突风分析算法的验证,在此基础上,基于某模型机翼,对模态重分析算法在突风动响应分析中的应用进行了研究。结果表明,通过LU分解可避免保存稠密形式的刚度逆矩阵,通过合理的松弛因子和收敛阈值,可有效提升计算效率。
基金provided by the National Natural Science Foundation of China Youth Found of China (No.41102169)the doctoral foundation of Henan Polytechnic University of China (No. B2014-056)
文摘The dynamic ground subsidence due to underground mining is a complicated time-dependent and rate- dependent process. Based. on the theory of rock rheology and probability integral method, this study developed the superposltlOn model for the prediction and analysis of the ground dynamic subsidence in mining area of thick !oose layer. The model consists of two parts （the prediction of overlying bedrock and the prediction of thick loose layer）. The overlying bedrock is regarded as visco-elastic beam, of which the dynamic subsidence is predicted by the Kelvin visco-elastic rheological model. The thick loose layer is regarded as random medium, and the ground dynamic subsidence, is predicted by the probability integral model. At last, the two prediction models are vertically stacked in the same coordinate system, and the bedrock dynamic subsidence is regarded as a variable mining thickness input into the prediction model of ground dynamic subsidence. The prediction results obtained were compared w^th actual movement and deformation data from Zhao I and Zhao II mine, central China. The agreement of the prediction results with the. field measurements.show that the superposition model （SM） is more satisfactory and the formulae obtained are more effective than the classical single probability Integral model（SPIM）, and thus can be effectively used for predicting the ground dynamic subsidence in mining area of thick loose layer.
