基于全相位多次互相关的Geiger声发射源定位方法

直接互相关在岩石声发射源定位中,会出现多次峰值与波形密集的问题,在求解过程中会出现无解的情况且定位精度不足,为了解决这些问题,提出一种基于全相位快速傅里叶变换（FFT）分析及多次互相关的岩石声发射源定位的算法。通过对50 mm×100 mm×50 mm的花岗岩进行断铅试验,利用小波变换对互相关分析的频谱进行预处理,同时发挥全相位FFT的相位不变性的优点,找出波形峰值,得到时间差,最后利用最小二乘法得到定位初始点,再通过Geiger迭代,得到最终定位坐标。在选取8个测点的基础上,经声发射监测试验结果表明：该方法比单独直接互相关更容易找到波峰,且波形清晰,初始点的选择有效解决了Geiger迭代法对初始值要求严格的问题,通过全相位分析及多次互相关计算,然后Geiger程序迭代,得到的定位结果比直接互相关精度更高,平均绝对误差比美国生产PCI–2型声发射仪器Geiger定位的结果低 2.40 mm,比基于多次互相关和Geiger算法的声发射源定位结果低3.31 mm,比全相位相位差法声发射测试时间延迟定位结果低1.74 mm 。     

Modeling atmospheric chemistry and transport with dynamic adaptive resolution

We discuss an adaptive resolution system for modeling regional air pollution based on the chemical transport model STEM. The grid adaptivity is implemented using the generic adaptive mesh refinement tool Paramesh, which enables the grid management operations while harnessing the power of parallel computers. The computational algorithm is based on a decomposition of the domain, with the solution in different subdomains being computed with different spatial resolutions. Various refinement criteria that adaptively control the fine grid placement are analyzed to maximize the solution accuracy while maintaining an acceptable computational cost. Numerical experiments in a large-scale parallel setting (~0.5 billion variables) confirm that adaptive resolution, based on a well-chosen refinement criterion, leads to the decrease in spatial error with an acceptable increase in computational time. Fully dynamic grid adaptivity for air quality models is relatively new. We extend previous work on chemical and transport modeling by using dynamically adaptive grid resolution. Advantages and shortcomings of the present approach are also discussed.     

水环境逆边界逆动态混合控制精确算法

根据逆边界逆动态控制理论,将河流水污染动态控制问题提为逆边界逆动态混合控制问题。针对多个或单个污染源排放浓度和排放总量计算,提出了一维对流-扩散方程逆控制的精确算法。该方法与现行最优控制方法相比,其优点是充分考虑了河流沿程的稀释混合容量,并能充分考虑水质动态标准和社会经济变化等因素,可获得动态控制精确解的近似解。     

0-1测试方法的径流时间序列混沌特性应用

径流时间序列混沌特性识别的常用方法是基于相空间重构的关联维数法、最大Lyapunov指数法和Kolmogorov熵法。引入一种新的时间序列混沌特性识别方法:0-1混沌测试方法。该方法直接应用于时间序列不需要相空间重构,并且通过量化指标K_c是否接近于0或1来识别时间序列的混沌特性。以Logistic映射生成的序列、金沙江流域和美国Umpqua河多年日径流序列为研究对象,首先利用0-1混沌测试方法进行了混沌特性识别和判定;然后基于相空间重构,运用相空间重构、伪最近邻点法、关联维数方法、最大Lyapunov指数法和Kolmogorov熵5种非线性研究方法分析了这两列径流时间序列混沌特性。研究结果表明0-1混沌测试方法简单有效。以上方法交互验证了该两列径流时间序列存在低维混沌特性。     

板状体磁异常数据反演的PSO算法

粒子群优化(PSO)算法是根据鸟群觅食过程中的迁徙和群集模型而提出的用于解决优化问题的算法,是一类随机全局优化技术,它通过粒子间的相互作用搜索复杂空间中的最优区域,其优势在于效率高,且又简单易实现。本文讨论了PSO算法用于板状体磁异常数据反演的方法,并与遗传算法(GA)进行了比较。理论和实测磁异常数据反演的结果表明,PSO算法具有更高的找寻最优解效率,是一种很有潜力的位场反演工具。     

A back analysis scheme for refined soil stratification based on integrating borehole and CPT data

Utilizing both borehole and Cone Penetration Testing (CPT) data in soil stratification helps to get more convincing soil stratification results. However, the soil classification results revealed by borehole (Unified Soil Classification System, USCS) and CPT tests (soil behavior type, SBT) are commonly not consistent. This study proposes a feasible solution to integrate the borehole and CPT data with the tree-based method. The tree-based method is naturally suitable for soil stratification tasks as it aims to divide the subsurface space into several clusters based on the similarities of the soil types. A novel boundary dictionary method is proposed to enhance the model performance on complex soil layer conditions. A probabilistic mapping matrix between the USCS-SBT system is built based on a collected municipal database with collocated borehole and CPT data. The optimal soil stratification results can be selected based on considering multiple borehole information and pruning the structure of trees. The structure of the trees can be optimized in a back analysis perspective with the Sequential Model-Based Global Optimization (SMBO) algorithm which aims to maximize the possibility of observing the borehole information based on the USCS-SBT probabilistic mapping matrix. The uncertainties of the optimal soil stratification results can be estimated based on a weighted Gini index method. The performance of the proposed method is validated based on a real case in New Zealand with a cross-validation method. The results indicate that the proposed method is robust and effective.     

地铁深基坑支护的遗传神经网络位移反分析

针对目前已有的各种位移反分析方法存在的缺陷,利用神经网络具有的非线性映射能力和遗传算法具有的全局随机搜索能力,提出了一种基于遗传神经网络进行深基坑支护的位移反分析方法。该方法改变了BP算法依赖梯度信息的指导来调整网络权值的方法,而是利用遗传算法全局性搜索的特点,寻找最合适的网络连接权和网络结构等来达到优化的目的。结合地铁深基坑支护位移计算,应用该方法对某一地铁深基坑土体的力学参数进行了反演。结果表明：将位移观测值作为网络输入数据,土体力学参数作为输出数据,在较大的解空间内,该位移反分析方法收敛速度快、解的稳定性好、反演结果精度高,是一种理想的位移反分析方法。最后,采用该软件结合一个工程实例实现了应用遗传神经网络进行的基坑支护位移反分析。     

基于改进遗传算法的岩体结构面产状聚类分析

根据产状对结构面进行分组是研究岩体结构的重要环节。传统分组方法通常需要依靠地质经验,缺乏客观性,而现有的聚类方法也存在一些缺陷。基于变长度字符串遗传算法,提出了一种改进的K均值算法,实现了岩体结构面产状的自动聚类。该方法的核心思想是使用遗传算法为K均值算法选择恰当的聚类中心,克服了K均值(K-means)算法受初始聚类中心影响,易收敛于局部最优解的缺陷。由于使用了变长度字符串,该方法能够在聚类过程中自动确定最佳结构面组数,同时提供最优的分组结果。针对产状数据,提出了一种新的变异方法,该方法利用C++语言实现,并被应用于浙江省某地下水封洞库结构面产状数据的分析,得到较为合理的分组结果,证明了该方法的有效性。     

水库排沙调度优化模型

在分析水库排沙调度机理的基础上建立了水库排沙调度优化模型,以遗传算法作为寻优算法,并用BP神经网络拟合一维水沙数学模型计算成果的方法简化了泥沙淤积计算,使得所建模型得以有效求解。以三峡水库为例进行优化,结果表明,利用所建立的模型和求解方法可以有效优化三峡水库的排沙调度,在保证淤积不增多的基础上大大增加了发电效益。     

一种基于数值应力场的强度各向异性边坡稳定性分析方法

提出了一种基于数值应力场下的边坡临界滑动面和临界坡高的分析方法。该分析方法首先利用有限元得到边坡内部较为精确的应力场,再通过在边坡内部模拟类似于链式反应过程中粒子产生和运动规律,在此基础上完成临界滑动面的搜索。主要结论如下：（1）提出了一种基于数值应力场的边坡临界滑动面的搜索方法,该方法可在不对边坡滑动面形状和位置进行干预的情况下完成潜在破坏路径的搜索。（2）通过对算法中区域与边界、激发源、产物扩散路径、路径权值4方面要素进行合理控制,可使算法在具有较高精度的同时又能保证较好的分析效率。（3）算法能较为方便地考虑真实应力条件下地层强度各向异性对边坡稳定性的影响,并能对临界坡高进行很好的分析。（4）通过具体算例对本文算法的计算结果进行验证,将所得结果与PSO和Monte Carlo两种方法得到结果进行对比,对本文方法的可靠性进行了验证,取得了较好的效果。     

基于GIS的GA-BP模型开发及其在边坡稳定性预测中的应用

结合遗传算法的全局寻优性和BP算法的局部精确搜索求解特点,构建GA-BP模型,通过使用C++语言编写的GA-BP模型算法程序和avenue语言编写的动态连接脚本程序实现该模型与ArcView GIS的集成,并利用GIS平台的海量存储、空间分析及可视化功能,针对区域性边坡稳定性预测的特点,建立了边坡稳定性预测评价系统,该系统可以对研究区内收集到的所有边坡信息进行统一的存储和管理,并能对各边坡的稳定性实现实时的、可视化的预测评价。     

频率域反射波全波形速度反演

全波形反演不仅利用相位和振幅信息,还利用波形的细节变化,具有刻画模型精确细节的能力.在对稀疏矩阵直接LU分解求解的基础上,采用梯度预处理方法对声波介质速度模型进行了反射波全波形反演.采用误差反向传播算法计算目标函数梯度以及伪Hessian矩阵的对角线元素来做梯度预处理.数值模型的实验结果表明,利用有效的频率段便能反演出分辨率较高的速度结构,用低频反演出的结果作为高频反演的初始模型,减少了解的非唯一性.二维高斯光滑初始模型提供了有利的低频信息,得到较好的反演结果.伪Hessian矩阵的预处理吸收了高斯牛顿法的二次收敛优势,在不增加计算量的前提下,加快收敛速度.      

应用CP网络进行岩性识别

为通过测井解决岩性识别问题，引入了具有分类准确、算法简练等优点的CP（Counter-Propagation)网络。在详细介绍CP网络的网络模型和算法的基础上，结合某油田的实际测井资料，进行了CP网络识别研究。应用结果表明：CP网络训练周期短、识别准确率高、不存在收敛问题。通过试验研究得出结论：CP网络完全可以用于解决岩性识别等问题，具有广阔的应用前景。     

Reservoir description using dynamic parameterisation selection with a combined stochastic and gradient search

There is a correspondence between flow in a reservoir and large scale permeability trends. This correspondence can be derived by constraining reservoir models using observed production data. One of the challenges in deriving the permeability distribution of a field using production data involves determination of the scale of resolution of the permeability. The Adaptive Multiscale Estimation (AME) seeks to overcome the problems related to choosing the resolution of the permeability field by a dynamic parameterisation selection. The standard AME uses a gradient algorithm in solving several optimisation problems with increasing permeability resolution. This paper presents a hybrid algorithm which combines a gradient search and a stochastic algorithm to improve the robustness of the dynamic parameterisation selection. At low dimension, we use the stochastic algorithm to generate several optimised models. We use information from all these produced models to find new optimal refinements, and start out new optimisations with several unequally suggested parameterisations. At higher dimensions we change to a gradient-type optimiser, where the initial solution is chosen from the ensemble of models suggested by the stochastic algorithm. The selection is based on a predefined criterion. We demonstrate the robustness of the hybrid algorithm on sample synthetic cases, which most of them were considered insolvable using the standard AME algorithm.     

Parameters optimization on DHSVM model based on a genetic algorithm

Due to the multiplicity of factors including weather, the underlying surface and human activities, the complexity of parameter optimization for a distributed hydrological model of a watershed land surface goes far beyond the capability of traditional optimization methods. The genetic algorithm is a new attempt to find a solution to this problem. A genetic algorithm design on the Distributed-Hydrology-Soil-Vegetation model (DHSVM) parameter optimization is illustrated in this paper by defining the encoding method, designing the fitness value function, devising the genetic operators, selecting the arithmetic parameters and identifying the arithmetic termination conditions. Finally, a case study of the optimization method is implemented on the Lushi Watershed of the Yellow River Basin and achieves satisfactory results of parameter estimation. The result shows that the genetic algorithm is feasible in optimizing parameters of the DHSVM model.     

Streeter-Phelps模型参数估计的遗传算法

提出Streeter-Phelps模型参数估计的新方法--遗传算法(Genetic Algorithm),它不同于常规参数估计方法,其优点在于,从多个初始点开始寻优,并采用交迭和变异运算避免过早地收敛到局部最优解,可获得全局最优解,且不受初始值影响.该方法不必求导计算,编程简单快捷.给出了实例计算及与其他方法相比较的结果.     

Analytical study of freezing behavior of a cavity in thermo-poro-elastic medium

The goal of this paper is to present an analytical solution to have a first insight of the impact of ice formation on the surrounding porous rock on underground cavities like reservoir, pipes, tunnels or wellbores. Among the other analytical solutions found in the literature on this topic, the originality of this work resides in the rigorous theoretical framework of poromechanics, which considers the coupling between liquid water and ice crystal under thermodynamic equilibrium. Liquid water transport, thermal conduction, and elastic properties of the phases are also considered. Two analytical solutions are presented, based on a linearization of the system of governing equations. The first one deals with a spherical cavity within an infinite porous medium leading to an exact analytical solution. It allows validating the Stehfest’s algorithm on the numerical inversion of Laplace Transform, used in the second analytical solution, which considers a cylindrical excavation. The validity of this solution is assessed by comparing its results to that issued from a numerical resolution of the nonlinear system of equations. The analytical solution is then ultimately used to identify the influence of key parameters like the thermal/hydraulic conductivities, the amount of ice formed and the thermal dilatation coefficients on the mechanical response of a cylindrical cavity submitted to an internal frost.     

基于精确Riemann求解器的明满流过渡过程模拟

Preissmann窄缝法模拟明满流过渡过程方法简单,但存在明显的非物理振荡,抑制非物理振荡是该方法应用的关键。基于Godunov格式和精确Riemann求解器对明满流过渡过程进行模拟,针对Riemann问题代数恒等式在明满流交界处不光滑问题,提出了三阶收敛方法与二分法结合的迭代求解方法,保证迭代收敛至真实解;针对由于变量空间重构方法不能准确表达变量在空间中真实物理状态而导致的非物理振荡,提出了基于精确Riemann解的变量空间重构方法,准确表达激波间断在单元内的空间分布状态,从机理上抑制了非物理振荡。实例研究表明,数值计算结果与解析解或实测值吻合良好,研究成果为明满流过渡过程的高精度数值模拟提供了新的方法。