Potassium‐argon ages on the Cainozoic volcanic rocks of New South Wales

During the Cainozoic there was widespread volcanism, mainly basaltic, in eastern New South Wales. Numerous new K‐Ar ages, together with previously published results, provide information on the age of virtually all the main volcanic provinces, and indicate that the volcanism started about 70 m.y. ago in the Late Cretaceous, and was continuous from about 60 m.y. ago (Palaeocene) until about 10 m.y. ago (middle Miocene). There has been no volcanic activity since 10 m.y. ago.

The ages of uplift of the Eastern Highlands are estimated from the relationship of the dated basaltic flows to the topography. A major uplift is deduced some time between the mid‐Cretaceous and late Oligocene, followed by a quiescent period. A further uplift started some time after the middle Miocene, and it continues to the present day. The highland was uplifted differentially both along and transverse to the axis.     

长春莲花山地区地下水化学特征及成因分析

在调查取样的基础上,充分利用前人成果资料,应用SPSS及地下水污染分析软件,对莲花山地区区域地质条件、水化学参数空间分布特征、地下水化学类型、地下水化学成因进行分析研究,认为：莲花山地区地下水的硬度较高且矿化度较大;HCO3-浓度的平均值最大,在地下水的离子中占据主导地位;TDS（溶解性总固体）浓度较高且不同区域间浓度相差较大;莲花山地区部分区域偏硅酸、锶达到矿泉水标准,是矿泉水开发潜力区;研究区Na+和K+同时来自岩盐和硅酸岩的溶解;研究区浅层地下水中的Ca2+和Mg2+主要来源于碳酸盐的溶解;莲花山地区浅层地下水发生了阳离子交换作用.     

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。     

河流相储层沉积学表征

以层次分析思想为指导,应用结构要素分析法,结合露头研究,解剖层内薄夹层并对砂体内部建筑结构进行详细研究,认为这样就可以预测性地描绘出胜利油区河流相单砂体的几何形态、连通性、以及储层非均质性,准确判断出砂体的成因类型,揭示了砂体内部建筑结构特征。进而适应高含水后期油田调整挖潜和三次采油的需要。     

控制差异沉降的桩筏基础桩径优化分析方法

桩径优化是桩筏基础以差异沉降最小化为目标的基础优化分析的重要组成部分。基于桩筏基础通用分析方法,结合遗传算法提出了包含非线性约束条件的以差异沉降控制为目标的桩筏基础桩径优化分析模型,并给出了优化分析的实施步骤。通过示例说明了桩径优化的实施情况,对比给出了优化前后基础沉降、桩基荷载分布与筏板分担比、筏板弯矩和剪力结果。最后通过参量分析研究了筏板厚度、桩基参量和土体参量对最优桩径确定的影响程度,桩长和土体特性对桩径优化结果影响显著,而桩体材料特性和筏板厚度对桩径优化结果影响不大。     

基于谐振子遗传算法的高效地下水优化管理模型

在传统遗传算法和模拟谐振子算法的基础上,结合两者的优点,提出了一种新型快速高效的谐振子遗传算法。通过一个理想的水资源管理模型的算例和一个华北平原典型区地下水资源优化的实际算例,从寻优结果和寻优效率两个方面对谐振子遗传算法、传统遗传算法和模拟谐振子算法进行了对比分析。在两个地下水管理模型中,与传统的遗传算法和模拟谐振子算法相比,新型的谐振子遗传算法搜索效率达到模拟谐振子算法搜索效率的2倍以上,得到的最优解比遗传算法所得到的最优解分别增加供水量1.1×10³ m³/d和0.47×10⁸ m³/a,说明谐振子遗传算法具有更强的全局搜索能力和更好的寻优效率。     

Groundwater level simulation using gene expression programming and M5 model tree combined with wavelet transform

ABSTRACT

In order to understand and adequately manage hydrological stress, it is necessary to simulate groundwater levels accurately. In this research, gene expression programming (GEP) and M5 model tree (M5) are used to simulate monthly groundwater levels. The models are combined with wavelet transform to produce two hybrid models: wavelet gene expression programming (WGEP) and wavelet M5 model tree (WM5). For the simulation, groundwater level, temperature and precipitation values from three observation wells and one meteorological station, located in Iran, are used. The results indicate that the hybrid models, WGEP and WM5, lead to a better performance than the simple models, GEP and M5. The performance of the two hybrid models is similar. It is also observed that selecting a suitable time lag for inputs plays an important role in the accuracy of the simple models. The selection of a suitable decomposition level strongly affects the accuracy of hybrid models.     

适应水文非一致条件的水库防洪优化调度

为完善变化环境下水库防洪调度方案,建立了集水文非一致性诊断、水文模型还现、设计洪水计算与水库调度规则优化于一体的水库适应性调控方法体系,并应用于沂沭泗水系仕阳水库.结果表明,仕阳水库入库洪水变异点发生在1975年;利用新安江模型对水文序列还现处理,得到满足一致性的设计洪水,其洪峰、最大24 h和最大72 h洪量均值,较原设计分别增大了 19.7%、14.5%和10.0%;建立了以防洪效益最大为目标函数的水库优化调度模型,采用动态规划进行求解.提出的适应性调度方案在20年、100年、1000年和5000年一遇设计洪水条件下,较水库现行设计方案最高洪水位分别降低了0.32、0.11、0.19和0.11 m.     

An improved optimal elemental method for updating finite element models

The optimal matrix method and optimal elemental method used to update finite element models may not provide accurate results. This situation occurs when the test modal model is incomplete, as is often the case in practice. An improved optimal elemental method is presented that defines a new objective function, and as a byproduct, circumvents the need for mass normalized modal shapes, which are also not readily available in practice. To solve the group of nonlinear equations created by the improved optimal method, the Lagrange multiplier method and Matlab function fmincon are employed. To deal with actual complex structures, the float-encoding genetic algorithm (FGA) is introduced to enhance the capability of the improved method. Two examples, a 7degree of freedom (DOF) mass-spring system and a 53-DOF planar frame, respectively, are updated using the improved method.The example results demonstrate the advantages of the improved method over existing optimal methods, and show that the genetic algorithm is an effective way to update the models used for actual complex structures.