Robust and reliable metamodels for mechanized tunnel simulations

The main objective of this paper is to construct a robust and reliable metamodel for the mechanized tunnel simulation in computationally expensive applications. To accomplish this, four metamodeling approaches have been implemented and their performance has been systematically evaluated through a comparative study utilizing pure mathematical test functions. These metamodels are quadratic polynomial regression, moving least squares, proper orthogonal decomposition with radial basis functions, and an extended version of the latest approach. This extended version has been proposed by the authors and named proper orthogonal decomposition with extended radial basis functions. After that, a system identification study for mechanized tunneling has been conducted through the back analysis of synthetic measurements. In this study, the best performing metamodel, that is the one suggested by the authors, has been employed to surrogate a complex and computationally expensive 3D finite element simulation of the mechanized tunnel. The obtained results demonstrate that the proposed metamodel can reliably replace the finite element simulation model and drastically reduce the expensive computation time of the back analysis subroutine.     

基于热重分析的菱镁矿分解动力学解析

本文利用热重(TG)分析方法,探讨了菱镁矿的热分解过程。根据热微商(DTG)曲线峰顶温度,结合Kissinger及Ozawa-Doyle方法拟合计算得到菱镁矿热分解的活化能和指前因子(lgA)分别为211.55 kJ/mol和11.07s-1。依次采用单曲线拟合、多元非线性拟合及Malek方法判定得出菱镁矿热分解过程属于三维相界反应模型(R3),其动力学方程为:dα/d T=(1011.07/β)·e-211.55×103/(8.314×T)·3(1-α)2/3。     

基于比例整体最小二乘的GPS高程拟合

针对GPS高程拟合过程中GPS基线观测量和水准高程观测量含有误差且残差中误差不相同的情况,在整体最小二乘(TLS)基础上引入比例因子λ来确定残差中误差的大小,即比例整体最小二乘(STLS)。实例计算表明,STLS比TLS和LS能够得到更好的估计参数,高程异常值拟合精度也相应提高。     

Towards a comprehensive approach to parameter estimation in land surface parameterization schemes

In climate models, the land–atmosphere interactions are described numerically by land surface parameterization (LSP) schemes. The continuing improvement in realism in these schemes comes at the expense of the need to specify a large number of parameters that are either directly measured or estimated. Also, an emerging problem is whether the relationships used in LSPs are universal and globally applicable. One plausible approach to evaluate this is to first minimize uncertainty in model parameters by calibration. In this paper, we conduct a comprehensive analysis of some model diagnostics using a slightly modified version of the Simple Biosphere 3 model for a variety of biomes located mainly in the Amazon. First, the degree of influence of each individual parameter in simulating surface fluxes is identified. Next, we estimate parameters using a multi‐operator genetic algorithm applied in a multi‐objective context and evaluate simulations of energy and carbon fluxes against observations. Compared with the default parameter sets, these parameter estimates improve the partitioning of energy fluxes in forest and cropland sites and provide better simulations of daytime increases in assimilation of net carbon during the dry season at forest sites. Finally, a detailed assessment of the parameter estimation problem was performed by accounting for the decomposition of the mean squared error to the total model uncertainty. Analysis of the total prediction uncertainty reveals that the parameter adjustments significantly improve reproduction of the mean and variability of the flux time series at all sites and generally remove seasonality of the errors but do not improve dynamical properties. Our results demonstrate that error decomposition provides a meaningful and intuitive way to understand differences in model performance. To make further advancements in the knowledge of these models, we encourage the LSP community to adopt similar approaches in the future. Copyright © 2012 John Wiley & Sons, Ltd.     

河西地区重力动态变化的二维离散小波多尺度分解

采用二维离散小波的多尺度分解技术，对1994～1995年和2002～2003年的河西地区重力动态变化进行分解，提取该地区不同层次的重力动态变化异常，结果反映了不同深度在一定尺度意义上的介质密度的动态变化分布。     

RESOLUTION OF MULTICOMPONENT FLUORESCENT MIXTURES BY ANALYSIS OF THE EXCITATION-EMISSION-FREQUENCY ARRAY

Fluorescence lifetime provides a third independent dimension of information for the resolution of totalluminescence spectra of multicomponent mixtures.The incorporation of this parameter into theexcitation-emission matrix(EEM)by the phase modulation technique results in a three-dimensionalexcitation-emission-frequency array (EEFA).Multicomponent analysis based on the three-dimensionalEEFA brings a qualitative change for the resolved spectra,i.e.individual spectra can be uniquely resolved,which is impossible with any two-dimensional analysis.In this paper we present a method for analyzingthe EEFA.We show mathematically that with the three-dimensional analysis of the EEFA individualspectra and lifetimes can be obtained.Our algorithm is developed in mathematical detail and isdemonstrated by its application to a two-component mixture.     

Generating non-stationary random fields of auto-correlated,normally distributed CPT profile by matrix decomposition method

This paper emphasises the true realisation of Cone Penetration Test (CPT) profiles considering non-stationary nature of the data. Formulation of stationary random field theory has been modified and adapted to non-stationary state in order to take into account the mean and variance variability for soil properties. Multi-variance correlation matrix along with the Cholesky decomposition technique was employed to produce realisations of non-homogenous and non-stationary random fields of CPT profiles. A piecewise and segmental data realisation according to the lithology and site class specifications acquired directly from CPT data is adopted in this study so as to render an accurate data simulation. For validation of proposed method 8 CPT test profiles collected from Urmia Lake site have been introduced and simulated by the stationary and non-stationary algorithms. The mean correlation coefficient between the actual CPT data profiles and related realisations along with some other important statistical parameters and their coefficients of variation strongly demonstrate that non-stationary random field generation technique gives quite better accuracy, by comparison to the conventional stationary random field generation scheme.     

基于小波分析的灰色-神经网络组合模型在大坝变形预测中的应用

监测序列经小波分解后可以得到各层分量。对低频分量采用灰色GM(1,1)模型进行建模预测,对高频分量采用BP神经网络进行建模预测,最后将各分量进行小波重构,得到监测序列的预测值。将预测值分别与没有进行小波分解直接用GM(1,1)模型预测的值和经小波分解的低、高频系数都采用GM(1,1)模型预测的值进行对比,发现经小波分解的灰色-神经网络组合模型预测精度更高。     

大气变量物理分解原理及其在区域暴雨分析中的应用

观测的全球大气变量可以物理分解为4个部分:纬圈平均的对称气候、非对称气候、纬圈平均的瞬变对称扰动和非对称扰动。文章用欧洲中期天气预报中心(ECMWF)ERA Interim全球再分析资料(0.75°×0.75°)介绍大气瞬变扰动量中的扰动风提取方法及其在区域暴雨分析中的应用。结果表明:用欧洲高分辨率再分析资料物理分解得到的扰动气流能够较好地反映暴雨的落区和风与雨之间的关系,如暴雨带位于低层大气扰动气流的辐合线上和稳定的暴雨带两侧扰动气流多呈对峙的辐合状态。     

应用MJO制作长江流域月降水预测的试验研究

用MJO指数RMM1、RMM2、振幅 1—25日平均代替月平均,用上月月平均RMM1和RMM2、振幅构造为右场,下月长江流域降水场为左场,SVD分析两场的关联,借助最优化技术,在降水场预测距平与实况距平同号总站数最大意义下确定系数,建立估计公式,由右场时间系数估计左场时间系数,最后反演降水场。尽管多数的月第一模态相关并不显著,但实际预测效果较好。