Developing constitutive models from EPR‐based self‐learning finite element analysis

A constitutive model that captures the material behavior under a wide range of loading conditions is essential for simulating complex boundary value problems. In recent years, some attempts have been made to develop constitutive models for finite element analysis using self‐learning simulation (SelfSim). Self‐learning simulation is an inverse analysis technique that extracts material behavior from some boundary measurements (eg, load and displacement). In the heart of the self‐learning framework is a neural network which is used to train and develop a constitutive model that represents the material behavior. It is generally known that neural networks suffer from a number of drawbacks. This paper utilizes evolutionary polynomial regression (EPR) in the framework of SelfSim within an automation process which is coded in Matlab environment. EPR is a hybrid data mining technique that uses a combination of a genetic algorithm and the least square method to search for mathematical equations to represent the behavior of a system. Two strategies of material modeling have been considered in the SelfSim‐based finite element analysis. These include a total stress‐strain strategy applied to analysis of a truss structure using synthetic measurement data and an incremental stress‐strain strategy applied to simulation of triaxial tests using experimental data. The results show that effective and accurate constitutive models can be developed from the proposed EPR‐based self‐learning finite element method. The EPR‐based self‐learning FEM can provide accurate predictions to engineering problems. The main advantages of using EPR over neural network are highlighted.     

青藏高原隆升的非线性动态有限元仿真研究

根据青藏高原的地质特征建立分析模型，采用3维动态有限元方法，在计算仿真板块速度场的基础上，计算在青藏高原的隆升过程中该地区地壳岩石的等效应力和位移随时间的变化，计算仿真得到的速度场与1998年GPS观测的速度场吻合良好；与过去一贯的假设相反，计算结果反映出地壳应力场不是静态的，而是此起彼伏，不断变化的，应力值最大且变化最剧烈的地区在克什米尔地区、鄂尔多斯地区和鲜水河－小江断裂带，与地震多发区域吻合。     

用双三次样条函数和GPS资料反演现今中国大陆构造形变场

将中国大陆现今构造变动视为一种连续的地壳变形,利用双三次样条函数模拟了近期GPS测定的大陆内部及周边地区412个测站速率,反演大陆地区自洽的构造变动速度场和应变率场.模拟结果显示:印度板块与欧亚板块的碰撞、挤压是构成中国大陆内部岩石层水平形变的主要驱动力.印度板块在东喜马拉雅构造结深深插入青藏高原,造成地壳大规模的缩短和抬升.青藏高原东南部的喜马拉雅带、拉萨和羌塘地块以及青藏高原东南边的川滇地区,内部构造活动强烈,其内部的构造变形包含地壳碎片的冲断、褶皱和侧向逃逸.大陆地壳(或岩石圈)的增厚,尤其是喜马拉雅山脉南北向的快速缩短和青藏高原东西向的缓慢拉张,大约吸收了印欧板块会聚量的85%,西藏中东地区东西向的拉张速率达到了(16±2.0)mm/a,且顺时针方向扭转明显.印度板块相对欧亚板块运动的欧拉极为(29.7°N, 19.3°E, 0.392°/Ma);华南地块相对于欧亚大陆向东(102°±7.4°)南的运动速率是(11±1.54)mm/a,华南块体相对欧亚板块运动的欧拉极为(62.25°N, 126.56°E, 0.141°/Ma);塔里木地块相对较稳定,其西部运动速度高于东部运动速度,作顺时针方向旋转.总体上讲,中国大陆运动方向为北偏东呈辐射状,从西部近南北方向的运动转向东部地区东南方向的运动,绕东喜马拉雅构造结有一顺时针方向的旋转.横穿喜马拉雅构造带及青藏内部的南北向压缩速率为(19±2.0)mm/a,横穿西天山构造带的南北向压缩平均速率为(13±1.5)mm/a,横穿东天山构造带的南北向压缩平均速率为(6.0±1.4)mm/a.阿尔金断裂带的左旋走滑速率为(6±1.2)mm/a.     

Simulations of multimode bolometric interferometers

We describe a procedure for the numerical modelling of astronomical interferometers, with particular relevance to far-infrared and submillimetre wavelengths. The scheme is based on identifying a set of modes that carry power from the sky to the detector. The procedure is extremely general, and can be used to model scalar or vector fields, in any state of coherence and polarization, the only limitation being that the propagation of a coherent field through the system be described by an integral transform, a constraint that is in practise always met.
We present simulations of ideal, multimode two-dimensional interferometers, and show that the modal theory reproduces the correct behaviour of both Michelson and Fizeau interferometers. We calculate simulated visibility data for a multimode bolometric Michelson interferometer, with a synthesized source, and produce a dirty map, recovering the original source with the usual artefacts associated with interferometers.     

GPS/LEO掩星观测的变分同化技术

在简单介绍GPS/LEO掩星探测大气的发展历史和科学意义之后,详细阐述了反演的基本原理;分析了标准反演中存在的问题,并说明一维变分同化(1DVAR)在反演方法中的重要性;给出了一维变分同化中价值函数的求解,以及各种同化因子;简单介绍了对当前气象学中普遍使用的四维变分同化(4DVAR);重点讨论了各种同化方法,以及使用各种同化因子的优缺点。最后,通过CHAMP卫星的观测实例分析,验证了GPS数据在数值天气预报(NWP)中的作用,以及相对于标准反演法一维变分对气象要素的改进。     

小波分析理论在GPS技术中的应用

在GPS数据处理中 ,存在着误差影响、影响波的干扰、周跳和数据量大等问题。误差影响和影响波的干扰实质是在接收卫星信号时受到其它因素的影响 ;周跳是由于卫星信号的失锁而造成信号的不连续 ;数据量大是因为GPS观测需要采样间隔小又连续观测所致。由于小波理论具有时频分析、波形分解、特征提取和快速小波变换等特性 ,应用小波变换和波形分解可以解决误差影响和影响波的干扰的问题 ;应用特征提取可以解决周跳检测问题 ;应用快速小波变换可进行数据压缩     

Wavelet Analysis of Space Solar Telescope Images

The scientific satellite SST (Space Solar Telescope) is an important research project strongly supported by the Chinese Academy of Sciences. Every day, SST acquires 50 GB of data (after processing) but only 10GB can be transmitted to the ground because of limited time of satellite passage and limited channel volume. Therefore, the data must be compressed before transmission. Wavelets analysis is a new technique developed over the last 10 years, with great potential of application. We start with a brief introduction to the essential principles of wavelet analysis, and then describe the main idea of embedded zerotree wavelet coding, used for compressing the SST images. The results show that this coding is adequate for the job.     

Correcting systematic effects in a large set of photometric light curves

We suggest a new algorithm to remove systematic effects in a large set of light curves obtained by a photometric survey. The algorithm can remove systematic effects, such as those associated with atmospheric extinction, detector efficiency, or point spread function changes over the detector. The algorithm works without any prior knowledge of the effects, as long as they linearly appear in many stars of the sample. The approach, which was originally developed to remove atmospheric extinction effects, is based on a lower rank approximation of matrices, an approach which has already been suggested and used in chemometrics, for example. The proposed algorithm is especially useful in cases where the uncertainties of the measurements are unequal. For equal uncertainties, the algorithm reduces to the Principal Component Analysis (PCA) algorithm. We present a simulation to demonstrate the effectiveness of the proposed algorithm and we point out its potential, in the search for transit candidates in particular.