非线性铀成矿作用--以上第三系砂岩型铀矿为例

本以滇西上第三系陆相砂岩铀矿为例研究非线性铀成矿作用。与铀矿化有关的参数可分为矿化参量和控制参量,矿化参量以及矿化在控制参量中的分布均遵从对数正态分布,控制参量(温度、压力和地球化学条件)的耦合作用对铀矿化的概率和平均品位的控制作用是非线性的,铀矿化在控制参量构成的相空间中的变化轨迹是一复杂的超曲面。非线性铀成矿作用具分形特征。     

非线性弹性地基上矩形薄板的主参数共振

分析非线性弹性地基上受参数激励小挠度矩形薄板的主参数共振问题,由冯卡门方程和伽辽金方法得到系统的非线性振动方程,它是杜分-马休型方程,应用非线性振动的多尺度法得到平均方程。数值计算结果表明：阻尼系数、地基系数、几何参数对主参数共振曲线影响明显。     

A New Strategy for Solving a Class of Constrained Nonlinear Optimization Problems Related to Weather and Climate Predictability

There are three common types of predictability problems in weather and climate, which each involve different constrained nonlinear optimization problems: the lower bound of maximum predictable time, the upper bound of maximum prediction error, and the lower bound of maximum allowable initial error and parameter error. Highly efficient algorithms have been developed to solve the second optimization problem. And this optimization problem can be used in realistic models for weather and climate to study the upper bound of the maximum prediction error. Although a filtering strategy has been adopted to solve the other two problems, direct solutions are very time-consuming even for a very simple model, which therefore limits the applicability of these two predictability problems in realistic models. In this paper, a new strategy is designed to solve these problems, involving the use of the existing highly efficient algorithms for the second predictability problem in particular. Furthermore, a series of comparisons between the older filtering strategy and the new method are performed. It is demonstrated that the new strategy not only outputs the same results as the old one, but is also more computationally efficient. This would suggest that it is possible to study the predictability problems associated with these two nonlinear optimization problems in realistic forecast models of weather or climate.     

一个半线性耦合抛物型方程组爆破解的速率估计

考虑一个方程和非线性边界条件耦合的半线性抛物型方程组,运用Scaling方法、Green函数、Schauder估计等方法,研究该方程组解的爆破速率,并给出非线性反应项和吸收项对爆破速率的影响。     

三种非线性回归逐时气温预报比较订正

选取ECMWF和T639的2013年1月至2014年12月的数值预报场构造预报因子,基于神经网络、支持向量机和构造函数的非线性方法,预报地面逐时气温。试验结果显示,在单个方法预报误差较大时,3种方法的偏差订正集成方法更利于减小误差,通过偏差订正,3种非线性方法预报效果良好,平均绝对误差减小了0.5 ℃。在近1年独立样本的预报检验中,集成方法、神经网络、支持向量机和构造函数预报的平均绝对误差分别为1.5 ℃、1.7 ℃、1．8 ℃和1．4 ℃,总体上构造函数预报更为准确。     

外包钢-混凝土组合梁与钢管混凝土柱连接节点的滞回性能研究

为研究外包钢-混凝土组合梁与钢管混凝土柱连接节点的抗震性能,基于外包钢-混凝土组合梁与钢管混凝土柱连接节点低周反复荷载作用下的试验结果和有限元的模拟,分析了两类试验节点的滞回特性,提出外包钢-混凝土组合梁与钢管混凝土柱连接节点的三折线恢复力模型及其特征参数的取值范围,并给出恢复力模型表达式。结果表明,试件具有良好的耗能能力,建立的恢复力模型骨架曲线与试验值接近;有限元与试验所得的滞回曲线及骨架曲线在弹性阶段吻合较好,随着荷载的反复,两者之间的差异逐渐增大。     

Effect of abutment modeling on the seismic response of bridge structures

Abutment behavior significantly influences the seismic response of certain bridge structures. Specifically in the case of short bridges with relatively stiff superstructures typical of highway overpasses, embankment mobilization and inelastic behavior of the soil material under high shear deformation levels dominate the response of the bridge and its column bents. This paper investigates the sensitivity of bridge seismic response with respect to three different abutment modeling approaches. The abutment modeling approaches are based on three increasing levels of complexity that attempt to capture the critical components and modes of abutment response without the need to generate continuum models of the embankment, approach, and abutment foundations. Six existing reinforced concrete bridge structures, typical of Ordinary Bridges in California, are selected for the analysis. Nonlinear models of the bridges are developed in OpenSees. Three abutment model types of increasing complexity are developed for each bridge, denoted as roller, simplified, and spring abutments. The roller model contains only single-point constraints. The spring model contains discrete representations of backfill, bearing pad, shear key, and back wall behavior. The simplified model is a compromise between the efficient roller model and the comprehensive spring model. Modal, pushover, and nonlinear dynamic time history analyses are conducted for the six bridges using the three abutment models for each bridge. Comparisons of the analysis results show major differences in mode shapes and periods, ultimate base shear strength, as well as peak displacements of the column top obtained due to dynamic excitation. The adequacy of the three abutment models used in the study to realistically represent all major resistance mechanisms and components of the abutments, including an accurate estimation of their mass, stiffness, and nonlinear hysteretic behavior, is evaluated. Recommendations for abutment modeling are made.     

动态非线性滤波模型非线性强度的曲率度量及其应用

基于微分几何的两种曲率——参数影响曲率和固有曲率,给出了定量描述非线性滤波问题的非线性强度的方法,分别采用扩展Kalman滤波方法和Unscented Kalman滤波方法进行了模拟实验。结果验证了这些曲率确实能够度量非线性滤波问题的非线性强度,且能够评估非线性滤波算法的状态估计性能。     

粒子群神经网络及其在非线性系统辨识中的应用

介绍了一种新的神经网络权值优化算法——粒子群优（Particle Swarm Optimization，PSO）算法，提出了用粒子群神经网络对非线性系统进行系统辨识的构思。仿真实验结果表明，粒子群算法具有比BP算法更强的非线性系统辨识能力和更好的泛化能力。     

非线性半参数模型最小二乘核估计的直接解法

基于非线性半参数模型最小二乘核估计,给出了其参数分量和非参数分量估计的构造式,导出了参数分量和非参数分量顾及二次项直接解法的计算公式。用实测数据进行计算,证明了对于非线性半参数模型最小二乘核估计,可采用顾及二次项的直接解法。