数字管网连通分析的淘汰算法与实现

本文从图论的观点出发,分析了数字化市政管网的构成和连通的特点,探索出数字化管网线路连通性分析的规律,提出了逐步淘汰算法进行连通性分析的方法。给出了基于mapbsic的实现这种算法的关键语句和注意问题。     

饱和流体多孔介质中AVA特征分析及储层参数反演研究

AVA(Amplitude Versus Angle)技术是基于常规介质模型(均匀各向同性介质模型)发展起来的,由于忽略了储层的孔隙结构和充填流体的影响,造成AVA特征中是部分对地震波能量的吸收和衰减作用反映不足.从振幅特征方程的实际应用出发,建立起各参数与常规岩性参数之间的关系.以Gassmann方程与Biot理论为基础,推导出振幅特征方程中弹性参数与常规岩性、储层参数(如:纵波速度、横波速度、密度、孔隙度、流体参数Kf)之间的转化关系式,详细研究饱和流体多孔介质模型中的AVA特征,比较该介质模型与常规介质模型在AVA特征上的差异,并将饱和流体多孔介质AVA技术应用于川西凹陷深层须家河组储层预测,通过多波AVA储层参数的反演研究,为直接利用地震资料进行储层识别并进一步识别其流体特征提供了一种有力手段.     

基于遗传算法的空基导航信号增强平台组网优化方法研究

根据空基导航信号增强平台的工作原理设计了组网优化评价指标;然后简单介绍了遗传算法的基本原理,对空基增强平台的空间位置进行了二进制编码;最后采用通用的遗传算法对空基导航信号增强平台空间分布进行优化搜索。仿真实验结果证明该算法能够对空基导航信号增强平台进行有效布置,覆盖范围内导航服务误差分布合理,并且能够根据实际要求对空基平台进行优化调整。     

The ionospheric eclipse factor method (IEFM) and its application to determining the ionospheric delay for GPS

A new method for modeling the ionospheric delay using global positioning system (GPS) data is proposed, called the ionospheric eclipse factor method (IEFM). It is based on establishing a concept referred to as the ionospheric eclipse factor (IEF) λ of the ionospheric pierce point (IPP) and the IEF’s influence factor (IFF) . The IEF can be used to make a relatively precise distinction between ionospheric daytime and nighttime, whereas the IFF is advantageous for describing the IEF’s variations with day, month, season and year, associated with seasonal variations of total electron content (TEC) of the ionosphere. By combining λ and with the local time t of IPP, the IEFM has the ability to precisely distinguish between ionospheric daytime and nighttime, as well as efficiently combine them during different seasons or months over a year at the IPP. The IEFM-based ionospheric delay estimates are validated by combining an absolute positioning mode with several ionospheric delay correction models or algorithms, using GPS data at an international Global Navigation Satellite System (GNSS) service (IGS) station (WTZR). Our results indicate that the IEFM may further improve ionospheric delay modeling using GPS data.     

变形分析的神经网络技术应用实例

大型工程施工过程中的变形监测、分析与预报极为重要。变形分析建模的方法很多,神经网络技术的应用是其中之一。文中结合某深基坑工程的监测资料和工作经验,运用神经网络BP算法进行预测分析。简述BP神经网络的基本概念,介绍基坑变形分析的BP神经网络的具体模型结构,将神经网络方法预报结果与实测数据对比效果较好。该成果对生产实践具有参考价值。     

模拟退火算法在控制网平差中的应用

线性最小二乘估计在对非线性函数进行线性近似的过程中会产生模型误差,而一些非线性参数估计方法可能因为函数复杂而难以求导,法方程系数矩阵秩亏或呈病态矩阵时难以求解,非线性迭代解法有时对初始值的选择存在依赖性,不恰当的初始值会导致迭代无法收敛。针对这些问题,引入了模拟退火算法,介绍了该算法的基本原理、计算步骤和收敛性,并以3个控制网平差应用为例,说明该算法具有无需求导求逆,简洁实用,易于编程等优势,并能实现全局优化,获得高精度的平差结果。     

波流共存场中多向随机波浪传播变形数学模型

基于波作用量守恒方程建立了波流共存场中多向随机波浪传播变形数学模型,模型中考虑了波浪绕射的影响和水流引起的波浪弥散多普勒效应,应用包含水流和地形影响的激破波模式计算波浪破碎的能量耗散,采用一阶上迎风有限差分格式离散控制方程。分别计算了有无近岸流情况下单向和多向随机波浪的波高分布,考虑水流影响的数值计算结果与物理模型实验数据吻合良好,比较分析表明,所建立的数学模型能够复演由于离岸流引起的波高增大,可用于波流共存场多向随机波浪传播变形的模拟和预报。     

基于非充分掺混模式的流域来水组成模型

针对如何减小数值求解对流输运方程耗散误差的问题,引进断面计算浓度的概念来计算河段平均浓度,提出了非充分掺混模式的有限控制体积法离散对流输运方程的新算法,据此构建了模拟流域内的水源组成以及不同水源在流域内的时空变化情况的流域来水组成模型。通过数值试验与具体实例验证,结果表明所提出的非充分掺混模式的新算法可有效地提高流域来水模型的计算精度。     

物权法对节约集约利用土地的法理解析——以青岛市崂山区分层出让建设用地使用权为例

土地资源具有稀缺性和不可再生性,土地供给日渐紧张,拓展土地利用空间、将土地利用由平面趋向立体化发展的趋势日渐成熟。青岛市崂山区将建设用地使用权分层出让,不但垂范了法规政策,对区域经济的发展也具有很大的现实意义。     

Numerical simulation of a stratigraphic model

A multi-lithology diffusive stratigraphic model is considered, which simulates at large scales in space and time the infill of sedimentary basins governed by the interaction between tectonics displacements, eustatic variations, sediment supply, and sediment transport laws. The model accounts for the mass conservation of each sediment lithology resulting in a mixed parabolic, hyperbolic system of partial differential equations (PDEs) for the lithology concentrations and the sediment thickness. It also takes into account a limit on the rock alteration velocity modeled as a unilaterality constraint. To obtain a robust, fast, and accurate simulation, fully and semi-implicit finite volume discre tization schemes are derived for which the existence of stable solutions is proved. Then, the set of nonlinear equations is solved using a Newton algorithm adapted to the unilaterality constraint, and preconditioning strategies are defined for the solution of the linear system at each Newton iteration. They are based on an algebraic approximate decoupling of the sediment thickness and the concentration variables as well as on a proper preconditioning of each variable. These algorithms are studied and compared in terms of robustness, scalability, and efficiency on two real basin test cases.