二维有限元网格的自适应剖分及程序实现

有限单元法在计算岩土力学领域已得到广泛应用。在有限元的分析计算中，前处理工作即准备计算数据耗时费力。如何简化前处理工作、实现网络自动生成对于推广有限元分析至关重要。作者在综合考虑多种算法原理的基础上，对非规则几何图形、复连通域的二维模型提出了一套新的自适应剖分算法。该算法可以同时生成三角形单元和四边形单元，还能对单元形状进行规则性调整。给出了详细的实施步骤，并编写了相应的应用程序，应用程序同时提供了对单元节点进行优化排序的功能。实际应用表明，能够高效快速地给出良好的剖分网格。     

蒸发皿系数Kp计算方法研究

应用指标回归法和定性（风速和相对湿度）定量（吹程）资料，建立了蒸发皿系数Kp计算方程，并用黄河下游引黄灌区48个观测站实测资料进行了验证计算。计算结果表明，应用该方程，可大大改善Kp值的计算精度。     

改进的最小二乘法在水文分析计算中的应用

在水分析计算中，经常涉及到变量之间的线性或非线性拟合，而在拟合各种特性曲线时，通常应用以实测资料与拟合曲线间的误差平方和最小作为目标函数的方法——最小二乘法，但这种方法忽视了所有实测点应与拟合曲线间的相对误差尽量不超过某一百分比的原则，为了达到上述要求，提出了非线性的加权最小二乘法及线性相关方程的最小距离平方和法，探讨改进了传统的最小二乘法达到优化的效果。最小距离平方和法与常用的图解法相比，本法所得成果较为客观；与传统的单方向(x或y方向)最小二乘回归法相比，所求线性方程不会因坐标系的选取而改变。最后应用算例进行了初步讨论。     

任意面积储量计算方法研究

这里介绍了一种任意面积储量计算方法，该方法的核心技术是充分利用现有的石油勘探、开发数据库资料，由计算机来自动确定任意含油面积，进而通过容积法来计算石油储量。该方法解决了用求积仪来求取面积时的大量手工操作，在储量计算过程中自动化程度高，具有方便、灵活、实用的特点。     

浅水方程数值计算方法的研究

求解以水位为变量的连续方程,并根据Navier-Stokes方程压力修正算法的基本思想,建立了浅水方程的水位修正算法,放宽了对离散时间步长的限制.通过对离散方程系数矩阵的重新构造,建立了高分辨率有限元格式,该格式既具有较高的离散精度又避免了数值解的伪振荡.对动量方程的阻力项做负坡线性化处理,提高了露滩计算的稳定性.数值模拟结果与解析解吻合良好,表明所建立的数值计算方法是正确的和可靠的.     

新疆天山地区地貌分形与多重分形特征研究

利用投影覆盖法和投影覆盖概率对新疆天山地区不同构造地貌类型进行了分形与多重分形特征的研究。结果表明：在所研究的标度范围内，不同地貌区均表现出明显的多度域分形，分维值总体上呈现出高山区＞中低山区＞盆地区特点，多重分形谱Dq的形态和值域范围也表现出不同特征。研究认为，地貌表面的分维值与地貌形成的内外力地质作用方式和强度密切相关，并提出5-6km的尺度可作为地貌学研究中宏观与微观作用的分界点。     

分形学:现代地图学的非线性数学分析方法

分析了地图学的传统数学分析方法，讨论了对象复杂性与方法简单化的矛盾，阐述了分形几何学，为现代地图学研究的定量化、系统化提供了新的数学分析方法。     

DLT程序设计与应用

在近景摄影测量直接线性变换原理的基础上，加入附加条件建立附加有平行条件的直接线性变换函数模型，探讨了在解算过程中用数据探测法剔除粗差，用验后补偿的方法补偿系统误差的实现。鉴于非量测像机在近景摄影洲量中应用导致直接线性变换解法的重要性和实用性及数据量大、解算过程过于复杂的情况。用VC 编制了直接线性变换的解算程序，对其关键的方法和用法进行了说明。     

A Linear Programming Approach to Determine the Normative Composition of Sedimentary Rocks

The analysis of modal and normative composition of sedimentary rocks is widely used for studying their sources and tectonic settings. The normative calculation of the mineral composition of rocks in this study is formulated as a linear programming problem and is solved by means of the simplex method. This enables both simultaneous and successive subtraction of a set of basic minerals from a rock sample represented by its chemical composition {SiO₂...LOI}. Such an approach provides a more exact calculation of the contribution of basic minerals in the rock. This mathematical approach is used to study two representative sets of sandstones and fine-grained rocks from a Meso- to Neoproterozoic marginal basin of southeastern Siberia (Uchur–Maya region, Yakutia) and a Pennsylvanian-Lower Permian uplifted continental block in Colorado, USA. The calculated normative mineral compositions of the Siberian sandstones are consistent with the observed modal compositions. These sandstones vary from K- Feldspar rich arkoses at the base of the sequence (the Uchur Group, lower Riphean) to quartz arenites or lithic sandstones and wacke in transgressive successions of the middle-upper Riphean. Arkoses and quartz arenites are dominant in Meso- to Neoproterozoic Siberia. These samples represent craton interior uplifted basement and quartzose, recycled orogen provenance of a stable craton in Rodinia. There are higher but consistent discrepancies between the calculated and observed compositions for the Pennsylvanian to Lower-Permian arkoses and quartz arenites (Sangre de Cristo, Belden, and Maroon Formations). The differences between the predicted and observed mineralogy may be due to uncertainties in the modes in the matrix and cement of the sandstones. This normative program should supplement modal calculations and provide better genetic constructions, especially in case of matrix-rich sandstones.     

A comparison of three image-object methods for the multiscale analysis of landscape structure

Within the conceptual framework of Complex Systems, we discuss the importance and challenges in extracting and linking multiscale objects from high-resolution remote sensing imagery to improve the monitoring, modeling and management of complex landscapes. In particular, we emphasize that remote sensing data are a particular case of the modifiable areal unit problem (MAUP) and describe how image-objects provide a way to reduce this problem. We then hypothesize that multiscale analysis should be guided by the intrinsic scale of the dominant landscape objects composing a scene and describe three different multiscale image-processing techniques with the potential to achieve this. Each of these techniques, i.e., Fractal Net Evolution Approach (FNEA), Linear Scale-Space and Blob-Feature Detection (SS), and Multiscale Object-Specific Analysis (MOSA), facilitates the multiscale pattern analysis, exploration and hierarchical linking of image-objects based on methods that derive spatially explicit multiscale contextual information from a single resolution of remote sensing imagery. We then outline the weaknesses and strengths of each technique and provide strategies for their improvement.