邓肯-张非线性模型研究及其在ANSYS中的实现

对工程领域使用广泛的邓肯-张非线性本构模型进行了研究,总结了国内外的研究现状及理论成果,针对其无法判定因结压力降低时的加载情况,提出了相应的变形模量的计算方法,同时考虑中主应力、土体抗拉强度的影响对模型进行了修正。利用APDL编写程序实现了ANSYS的材料本构模型的二次开发,运用重启动方法实现单元应力修正后数据重写入数据库,通过试验模拟对比分析验证了模型的适用性。     

基于改进的BP神经网络集成的作物精准施肥模型

作物最优施肥量与土壤养分含量、产量之间存在复杂的非线性关系。为更加准确地模拟这种关系,提出一种改进的的BP神经网络集成方法。该方法采用K-均值聚类优选神经网络个体,采用拉格朗日乘子方法计算待集成的神经网络个体的权值。然后,基于农田肥料效应试验数据,以土壤养分含量和施肥量作为神经网络的输入,以产量作为神经网络的输出,建立了作物精准施肥模型。该模型通过求解一个非线性规划问题,能同时获得最大产量和最优施肥量。试验结果表明,在施肥模型的拟合精度方面,改进的神经网络集成方法（其均方根误差为64.54）明显优于单个神经网络方法（其均方根误差为169.74）。而且,作为一种定量模型,基于改进的神经网络集成的施肥模型优于传统施肥模型,能有效地指导精准施肥。     

基于非线性降维时序遥感影像的作物分类

当前基于时序遥感数据的作物分类方法大都需要较多专家知识及人工干预,难以自动化,也难以移植到其他地区。将光谱降维技术用于时序遥感影像分析可以很好地解决这一问题。其中,非线性降维方法已经成功应用于高光谱数据,并且获得了比线性降维方法更好的结果。但是,直接将非线性降维方法用于时序遥感影像无法充分利用其时相维度的信息。该文改进了一种非线性降维算法——Laplacian Eigenmaps(LE)用于时序遥感影像的作物分类,该方法更加关注相同时相下不同作物生长季的物候特征差异,而不再仅依赖于整个生长季的物候曲线轮廓。改进的LE算法被应用于美国伊利诺伊州覆盖作物全生长季的Landsat 8时间序列影像。降维后保留的波段结合随机森林分类器基于美国农业部Cropland Data Layer(CDL)提供的训练数据完成了一系列的分类试验,并与传统插值未降维的方法进行对比。试验结果表明,改进的LE降维方法完成了更高的整体及各个类别的分类精度,其中整体分类精度达到85.37%,该方法作为一种自动化的方法,不需要人工干预,可直接移植到其他研究区,并且只需要较少的训练样本就可以完成一个较高的分类精度,为日后不同尺度的作物识别和提取研究提供了有效的方法。     

Philip入渗模型参数的非线性预报模型

利用黄土高原区大田耕作土壤的水分入渗试验过程资料,拟合了Philip入渗模型参数,建立了以土壤体积含水率、干密度、粉、黏粒含量和有机质含量等土壤理化参数为输入变量,Philip入渗模型参数为输出变量的土壤传递函数,通过对函数的分析、检验,建立了土壤入渗参数S和A的多元非线性预测模型;在此基础上,运用灰色关联分析理论,将各输入变量进行了灰色排序。研究表明:用土壤体积含水率、干密度、粉粒含量、黏粒含量和有机质含量作为预报模型的输入参数可实现对入渗参数的预测,预测参数实测值与预测值之间的相对误差可控制在8%以下,所建立的非线性预测模型高度相关。     

一种湍流计算的非线性PANS模型

大多数雷诺平均湍流模型(RANS)基于线性和各项同性假设求解雷诺应力(Reynolds stress),因此对高压力梯度区、大曲率回流以及复杂的分离流动的预测误差较大.在近壁区较少网格的条件下,部分时均(PANS)方法被认为比大涡模拟(LES)获得结果更好.通过RNG k-ε湍流模型构造部分时均化模型,引入雷诺应力的非线性求解方法,提出了一种新的非线性PANS模型,并应用该非线性PANS模型分别对绕NACA0015水翼翼型流场和90°长方形截面弯管内流场进行了流动的数值模拟.结果表明:非线性PANS模型的数值结果与试验数据吻合较好,其在高压力梯度区的预测准确性高,并能准确预测流动分离诱发的三维非线性流动,证明了该方法捕捉高压力梯度、大曲率流动的有效性.该计算方法可以用来预测透平机械内部复杂的涡结构.     

A nonlinear,low data requirement model for producing spatially explicit fishery forecasts

Spatial variability can confound accurate estimates of catch per unit effort (CPUE), especially in highly migratory species. The incorporation of spatial structure into fishery stock assessment models should ultimately improve forecasts of stock biomass. Here, we describe a nonlinear time series model for producing spatially explicit forecasts of CPUE that does not require ancillary environmental or demographic data, or specification of a model functional form. We demonstrate this method using spatially resolved (1° × 1° cells) CPUE time series of North Pacific albacore in the California Current System. The spatial model is highly significant (P < 0.00001) and outperforms two spatial null models. We then create a spatial forecast map for years beyond the range of data. Such approaches can guide spatial management of resources and provide a complement to more data‐intensive, highly parameterized population dynamics and ecosystem models currently in use.     

二元立木材积模型的联立方程组估计方法

文章以兴安落叶松为例,使用联立方程组模型方法建立二元立木材积模型,该方法有效解决了二元立木材积模型的建模和预估前提不一致问题.在联立二元立木材积模型的估计中,分别采用了通常非线性估计方法和两步估计方法进行研究.研究结果证明:两种方法都能对模型进行估计,但两步估计可进一步减小系统偏差,达到通用性模型误差限要求,两步估计方法优于通常非线性估计.     

求解线性约束优化问题的一种全局优化算法

对求解无约束全局最优化问题的推进函数法进行了改进,用来求解带线性约束的全局优化问题.算例表明本文提出改进的算法是有效的.     

A New Beam Column Element of Space Framed Structures for Nonlinear Analysis of Geometric Material

An incremental virtual work equation of three dimensional(3D) beam column element is proposed based on the UL method. The geometric nonlinear tangent stiffness matrix for 3D beam column element is deduced with the consideration of warping, shear deformation and effects of moment spatial rotation. Material nonlinearity is addressed by introducing plastic hinges at the element ends. And the Orbison sectional strength is modified in order to consider the effects of torsion moment and warping. The elastic plastic tangent stiffness matrix is acquired as the element ends are in plastic phase based on the flow theory. With a case studied, it is shown that the model can be used to predict accurately the ultimate bearing capacity and instability mode of 3Dspace frames by only one or two elements, and address the effects of warping and shear deformations effectively.     

Aging Behavior Analysis of Asphalt based on Nonlinear Differential Dynamic Model

In order to study aging behavior and anti aging performance of asphalt, aging tests were carried out with rolling thin film oven test(RTFOT) and oven aging test at 60℃, and aged asphalt was extracted from pavements of different service life. Viscosity of asphalt samples was fitted with nonlinear differential dynamic model. With parameter study, property changes, aging rate of asphalt and the difference of aging mechanism were analysed under different aging conditions. It was shown that the nonlinear differential dynamic model can simulate asphalt aging process in the laboratory or on site effectively. At the same time, model parameters(L and r) can quantify aging state and aging rate. Asphalt had its limited aging state corresponding with different aging temperature. Ultimate aging degree of RTFOT and field aging were about 4~5 times of that of oven aging test at 60 ℃. And aging effect of RTFOT for 6h was about equivalent with that of field aging for 6 years. Thus time delay RTFOT can simulate long term aging of pavement asphalt.