Convective stability analysis of the long-term storage of carbon dioxide in deep saline aquifers

Deep saline aquifers are one of the most suitable geologic formations for carbon sequestration. The linear and global stability analysis of the time-dependent density-driven convection in deep saline aquifers is presented for long-term storage of carbon dioxide (CO₂). The convective mixing that can greatly accelerate the CO₂ dissolution into saline aquifers arises because the density of brine increases upon the dissolution of CO₂ and such a density difference may induce instability. The effects of anisotropic permeability on the stability criteria, such as the critical time for the appearance of convective phenomena and the critical wavelength of the most unstable perturbation, are investigated with linear and global stability analysis. The linear stability analysis provides a sufficient condition for instability while the global stability analysis yields a sufficient condition for stability. The results obtained from these two approaches are not exactly the same but show a consistent trend, both indicating that the anisotropic system becomes more unstable when either the vertical or horizontal permeability increases.     

一种中分辨率遥感影像道路的快速搜索算法

基于动态规划的思想,提出了一种用于中等分辨率遥感影像的道路搜索算法,利用线段代价最小规则进行道路线段跟踪,实验结果表明算法相对简单、快速有效、抗噪性能好。     

An Aggregate Constraint Method for Inequality-constrained Least Squares Problems

The inequality-constrained least squares (ICLS) problem can be solved by the simplex algorithm of quadratic programming. The ICLS problem may also be reformulated as a Bayesian problem and solved by using the Bayesian principle. This paper proposes using the aggregate constraint method of non-linear programming to solve the ICLS problem by converting many inequality constraints into one equality constraint, which is a basic augmented Lagrangean algorithm for deriving the solution to equality-constrained non-linear programming problems. Since the new approach finds the active constraints, we can derive the approximate algorithm-dependent statistical properties of the solution. As a result, some conclusions about the superiority of the estimator can be approximately made. Two simulated examples are given to show how to compute the approximate statistical properties and to show that the reasonable inequality constraints can improve the results of geodetic network with an ill-conditioned normal matrix.     

Genetic Programming Approach for Predicting Surface Subsidence Induced by Mining

INTRODUCTIONThe study of surface subsidence resulting fromunderground mining holds significance in view ofbeneficial effects on national economy and people’sliving conditions.As is known,a large quantity ofminerals need to be exploited for modernization con-struction.Mining leads to surface subsidence,someunderground engineering and production facilities aredestroyed accordingly,which blocks the developmentof production and retards people’s living standard.To solve this contradiction,su…     

锥束CT图像重建算法的快速实现

本文基于锥束CT滤波反投影重建的FDK算法,通过两种算法改进并结合基于共享内存的OpenMP并行技术和代码优化,实现了锥束CT图像的快速重建.基于锥束CT实际投影数据的重建结果表明,图像重建速度得到了较大的提高,断层图像重建质量与FDK原型算法相当.     

Matlab与高级编程语言在科学计算中的联合运用

在数字地震观测、地震预报及地震工程研究中,Matlab作为一套功能强大的科学计算及数学分析软件,得到广泛的应用.本文介绍如何将Matlab高效的数值计算和分析能力与高级编程语言结合的方法.     

Best prediction in linear models with mixed integer/real unknowns: theory and application

In this contribution, we extend the existing theory of minimum mean squared error prediction (best prediction). This extention is motivated by the desire to be able to deal with models in which the parameter vectors have real-valued and/or integer-valued entries. New classes of predictors are introduced, based on the principle of equivariance. Equivariant prediction is developed for the real-parameter case, the integer-parameter case, and for the mixed integer/real case. The best predictors within these classes are identified, and they are shown to have a better performance than best linear (unbiased) prediction. This holds true for the mean squared error performance, as well as for the error variance performance. We show that, in the context of linear model prediction, best predictors and best estimators come in pairs. We take advantage of this property by also identifying the corresponding best estimators. All of the best equivariant estimators are shown to have a better precision than the best linear unbiased estimator. Although no restrictions are placed on the probability distributions of the random vectors, the Gaussian case is derived separately. The best predictors are also compared with least-squares predictors, in particular with the integer-based least-squares predictor introduced in Teunissen (J Geodesy, in press, 2006).     

遗传规划在岩石力学中的应用

本文探讨了遗传规划这一新的优化方法在岩石力学参数确定中的应用。由于影响岩石力学性能的各因素之间关系不明确,而遗传规划特别适用于各影响因素之间因果关系不明确的复杂非线性问题。它为预测岩石力学性能提供了一条新的技术途径。通过例子,说明该方法的实用性。     

考虑权值非负约束的泛克立格算法

泛克立格法是地质统计学的一种重要估值方法,当区域化变量在空间变异几何域内非平稳时常用泛克立格法来估值。然而,用泛克立格方程组计算估计权值时由于未对权的符号作任何限制,从而使得计算出的权值经常出现负权现象,而负权的存在有许多弊端,所以在许多应用中有必要对权值作非负要求。本文基于线性规划方法提出了一种考虑权值非负约束的泛克立格算法,该算法既考虑到了权值的非负约束条件,又利用了线性规划方法求解简便快捷的优点。     

Relationships between rainy days,mean daily intensity and seasonal rainfall in normal,flood and drought years over india

There are limitations in using the seasonal rainfall total in studies of Monsoon rainfall climatology. A correlation analysis of the individual station seasonal rainfall with all India seasonal mean rainfall has been made. After taking the significance test (strictly up to 5% level) the stations which are significantly correlated have been considered in this study in normal, flood and drought years respectively. Analysis of seasonal rainfall data of 50 stations spread over a period of 41 years suggests that a linear relationship fits better than the logarithmic relationship when seasonal rain-fall versus number of rainy days is studied. The linear relationship is also found to be better in the case of seasonal rainfall versus mean daily intensity.