In this paper, a finite element method （FEM）-based multi-phase problem based on a newly proposed thermal elastoplastic constitutive model for saturated/unsaturated geomaterial is discussed. A program of FEM named as...In this paper, a finite element method （FEM）-based multi-phase problem based on a newly proposed thermal elastoplastic constitutive model for saturated/unsaturated geomaterial is discussed. A program of FEM named as SOFT, adopting unified field equations for thermo-hydro-mechanical-air （THMA） behavior of geomaterial and using finite element-finite difference （FE-FD） scheme for so/l-water-air three-phase coupling problem, is used in the numerical simulation. As an application of the newly proposed numerical method, two engineering problems, one for slope failure in unsaturated model ground and another for in situ heating test related to deep geological repository of high-level radioactive waste （HLRW）, are simulated. The model tests on slope failure in unsaturated Shirasu ground, carried out by Kitamura et al. （2007）, is simulated in the framework of soil-water-air three-phase coupling under the condition of constant temperature. While the in situ heating test reported by Munoz （2006） is simulated in the same framework under the conditions of variable temperature hut constant air pressure.展开更多
如何准确对岩体分级是深埋地下工程的一个难题。针对单一岩体评价模型存在误判的问题,提出了Random Over Sampler (ROS)改进机器学习算法集成权重岩体质量评价方法。采用ROS算法对类别非均衡样本进行采样处理,经SVM、KNN、NB、DT、RBF...如何准确对岩体分级是深埋地下工程的一个难题。针对单一岩体评价模型存在误判的问题,提出了Random Over Sampler (ROS)改进机器学习算法集成权重岩体质量评价方法。采用ROS算法对类别非均衡样本进行采样处理,经SVM、KNN、NB、DT、RBF、RF、LDA、LightGBM、XGBoost和GradientBoosting计算得到初步分级结果。将每一个分类器作为一个指标,确定每一个分类器的权重,建立ROS与机器学习算法的集成权重岩体质量评价模型,得到综合判别结果,大大降低了单一模型误判率。基于ROS改进机器学习算法集成权重提高了岩体质量评价模型的准确率,为岩体质量评价提供一种新的方法。展开更多
针对Hilbert-Huang变换方法中由于信号经验模态分解(empirical mode decomposition,简称EMD)过程中所存在的端点效应问题,分析了现有数据延拓方式的利弊,并在基于斜率(slope based method,简称SBM)方法以及改进方法(improved slope base...针对Hilbert-Huang变换方法中由于信号经验模态分解(empirical mode decomposition,简称EMD)过程中所存在的端点效应问题,分析了现有数据延拓方式的利弊,并在基于斜率(slope based method,简称SBM)方法以及改进方法(improved slope based method,简称ISBM)的基础上提出了一种全新的基于斜率再优化(reoptimization slope based method,简称RO-SBM)方法用于信号序列的极值点延拓,然后对延拓后的数据进行EMD分解,得到相应的本征模函数(intrinsic mode function,简称IMF)分量。数值仿真结果表明,采用基于RO-SBM方法进行数据延拓,相比镜像延拓以及ISBM方法,可以更有效地抑制EMD中的端点效应问题,提升HHT方法的信号分析性能。通过基于RO-SBM方法进行数据延拓的HHT方法准确分离出了某转子系统的局部碰摩径向振动信号中所包含的故障特征分量,并将此方法成功应用于旋转机械故障诊断领域。展开更多
文摘In this paper, a finite element method （FEM）-based multi-phase problem based on a newly proposed thermal elastoplastic constitutive model for saturated/unsaturated geomaterial is discussed. A program of FEM named as SOFT, adopting unified field equations for thermo-hydro-mechanical-air （THMA） behavior of geomaterial and using finite element-finite difference （FE-FD） scheme for so/l-water-air three-phase coupling problem, is used in the numerical simulation. As an application of the newly proposed numerical method, two engineering problems, one for slope failure in unsaturated model ground and another for in situ heating test related to deep geological repository of high-level radioactive waste （HLRW）, are simulated. The model tests on slope failure in unsaturated Shirasu ground, carried out by Kitamura et al. （2007）, is simulated in the framework of soil-water-air three-phase coupling under the condition of constant temperature. While the in situ heating test reported by Munoz （2006） is simulated in the same framework under the conditions of variable temperature hut constant air pressure.
文摘如何准确对岩体分级是深埋地下工程的一个难题。针对单一岩体评价模型存在误判的问题,提出了Random Over Sampler (ROS)改进机器学习算法集成权重岩体质量评价方法。采用ROS算法对类别非均衡样本进行采样处理,经SVM、KNN、NB、DT、RBF、RF、LDA、LightGBM、XGBoost和GradientBoosting计算得到初步分级结果。将每一个分类器作为一个指标,确定每一个分类器的权重,建立ROS与机器学习算法的集成权重岩体质量评价模型,得到综合判别结果,大大降低了单一模型误判率。基于ROS改进机器学习算法集成权重提高了岩体质量评价模型的准确率,为岩体质量评价提供一种新的方法。
文摘针对Hilbert-Huang变换方法中由于信号经验模态分解(empirical mode decomposition,简称EMD)过程中所存在的端点效应问题,分析了现有数据延拓方式的利弊,并在基于斜率(slope based method,简称SBM)方法以及改进方法(improved slope based method,简称ISBM)的基础上提出了一种全新的基于斜率再优化(reoptimization slope based method,简称RO-SBM)方法用于信号序列的极值点延拓,然后对延拓后的数据进行EMD分解,得到相应的本征模函数(intrinsic mode function,简称IMF)分量。数值仿真结果表明,采用基于RO-SBM方法进行数据延拓,相比镜像延拓以及ISBM方法,可以更有效地抑制EMD中的端点效应问题,提升HHT方法的信号分析性能。通过基于RO-SBM方法进行数据延拓的HHT方法准确分离出了某转子系统的局部碰摩径向振动信号中所包含的故障特征分量,并将此方法成功应用于旋转机械故障诊断领域。
