Ground motion prediction equation considering combined dataset of recorded and simulated ground motions

Himalayan region is one of the most active seismic regions in the world and many researchers have highlighted the possibility of great seismic event in the near future due to seismic gap. Seismic hazard analysis and microzonation of highly populated places in the region are mandatory in a regional scale. Region specific Ground Motion Predictive Equation (GMPE) is an important input in the seismic hazard analysis for macro- and micro-zonation studies. Few GMPEs developed in India are based on the recorded data and are applicable for a particular range of magnitudes and distances. This paper focuses on the development of a new GMPE for the Himalayan region considering both the recorded and simulated earthquakes of moment magnitude 5.3–8.7. The Finite Fault simulation model has been used for the ground motion simulation considering region specific seismotectonic parameters from the past earthquakes and source models. Simulated acceleration time histories and response spectra are compared with available records. In the absence of a large number of recorded data, simulations have been performed at unavailable locations by adopting Apparent Stations concept. Earthquakes recorded up to 2007 have been used for the development of new GMPE and earthquakes records after 2007 are used to validate new GMPE. Proposed GMPE matched very well with recorded data and also with other highly ranked GMPEs developed elsewhere and applicable for the region. Comparison of response spectra also have shown good agreement with recorded earthquake data. Quantitative analysis of residuals for the proposed GMPE and region specific GMPEs to predict Nepal–India 2011 earthquake of Mw of 5.7 records values shows that the proposed GMPE predicts Peak ground acceleration and spectral acceleration for entire distance and period range with lower percent residual when compared to exiting region specific GMPEs.     

基于全局弱式无单元法直流电阻率正演模拟

全局弱式无单元法是在有限单元法基础上发展起来的一种数值模拟方法,它采用局部支持域内的节点信息来构造形函数实现局部精确逼近,摆脱了单元,仅依赖于节点信息,具有预处理简单、模拟精度高、灵活性强的特点,适用于复杂地电条件下直流电阻率正演模拟.本文采用RPIM构造直流电阻率全局弱式无单元法形函数,利用RPIM形函数推导了直流电阻率全局弱式无单元法方程.然后,编制了直流电阻率全局弱式无单元法正演模拟Fortran程序,利用该程序对典型的地电模型进行了正演模拟,并将正演结果与基于线性插值的FEM正演结果及解析解进行对比,结果表明采用RPIM形函数的全局弱式无单元法用于直流电阻率正演模拟的正确性及有效性,且在同等条件下,全局弱式无单元法模拟精度高于矩形剖分的FEM,更有利于指导电法勘探的数据解译;利用该程序对复杂地电模型进行了正演模拟,结果表明全局弱式无单元法对复杂地电模型模拟效果良好,适应性强,灵活性高,可任意加密节点提高模拟精度.

     

Developing constitutive models from EPR‐based self‐learning finite element analysis

A constitutive model that captures the material behavior under a wide range of loading conditions is essential for simulating complex boundary value problems. In recent years, some attempts have been made to develop constitutive models for finite element analysis using self‐learning simulation (SelfSim). Self‐learning simulation is an inverse analysis technique that extracts material behavior from some boundary measurements (eg, load and displacement). In the heart of the self‐learning framework is a neural network which is used to train and develop a constitutive model that represents the material behavior. It is generally known that neural networks suffer from a number of drawbacks. This paper utilizes evolutionary polynomial regression (EPR) in the framework of SelfSim within an automation process which is coded in Matlab environment. EPR is a hybrid data mining technique that uses a combination of a genetic algorithm and the least square method to search for mathematical equations to represent the behavior of a system. Two strategies of material modeling have been considered in the SelfSim‐based finite element analysis. These include a total stress‐strain strategy applied to analysis of a truss structure using synthetic measurement data and an incremental stress‐strain strategy applied to simulation of triaxial tests using experimental data. The results show that effective and accurate constitutive models can be developed from the proposed EPR‐based self‐learning finite element method. The EPR‐based self‐learning FEM can provide accurate predictions to engineering problems. The main advantages of using EPR over neural network are highlighted.     

长江口附近海域台风浪的数值模拟--以鹿沙台风和森拉克台风为例

利用SWAN波浪模型计算长江口附近海域的台风浪,鉴于长江河口岸界和地形复杂,拟采用曲线网格.为证实曲线网格下的SWAN模型对于复杂地形的有效性,首先选用美国特拉华大学波浪水池实验资料对SWAN模型进行检验,结果表明利用曲线网格能不过多增加计算量而提高关键区域的计算精度.以0215号鹿沙台风和0216号森拉克台风为例,将SWAN模型应用到长江口附近海域,进行台风浪的数值模拟.通过浮标测站实测资料验证,表明有效波高计算值与实测值符合良好.通过综合分析模型计算的波浪场,说明SWAN模型能合理地反映长江口附近海域台风浪的分布.     

塔河油气田AT1区块凝析气藏三维地质建模研究

以随机函数理论为基础,采用相控-多参数协同的随机建模方法,建立塔河油气田AT1区块凝析气藏三维地质模型,实现气藏精细三维表征。首先,以钻井和岩芯资料为基础构建储层构造模型;然后,以小层界面为控制条件建立储层结构模型;接着,在沉积相、地质条件的约束下,采用序贯指示模拟法来建立砂体骨架模型;随后,在砂体骨架模型内进行优势相计算,形成最终有效砂体骨架模型;最后,以有效砂体骨架模型为约束,采用序贯高斯模拟法建立储层物性参数模型。结果表明：将物性参数变量与微相分布结合的序贯高斯模拟法建立孔隙度等物性参数的分布模型,以及采用地质分析类比、地质统计分析等方法优选最佳模型是有效的地质建模方法;所建地质模型精确细致地表征了塔河油气田AT1区块凝析气藏构造格架及储层、流体三维分布,反映了辫状水道复合连片,东北向展布,储层物性受相控较明显,非均质性较强。     

宁波市地下水位动态与地面沉降预测分析

为了准确预测分析宁波市地下水位动态与地面沉降的发展趋势,建立了宁波市第四纪松散沉积层孔隙地下水流三维数值模拟模型和地面沉降与地下水位多元线性回归模型,预测了2009年底到2020年底的逐月地下水位动态和逐年地面沉降量的变化特征.结果表明,从2013年起,除山区沟谷孔隙潜水地下水位降落漏斗逐渐扩大外,其余孔隙水的地下水流场基本趋于稳定,地下水位年际变化很小,年地面沉降量也逐渐变小,由2012年的5.62 mm/a逐渐下降到2020年的5.54 mm/a,由地下水位下降引起的地面沉降基本得到控制.     

GALILEO系统仿真与分析

本文着重阐述了GALILEO仿真系统星座和误差模型的构建过程,利用该系统进行DOP值分析并通过定位解算验证了GALILEO系统的性能指标。通过与GPS系统性能指标进行比较,得出GALILEO系统的星座设计具有较好的DOP值分布特性,定位精度优于GPS定位精度。在进行差分定位时,其误差贡献比较大的是接收机噪声和卫星钟差,因此提高差分定位的关键是降低接收机的噪声水平和提高卫星钟差预报精度。     

北京一次冬季回流暴雪天气过程的数值分析

回流天气是华北地区冬、春、秋季节产生降雨（雪）的主要天气类型,预报员常常因对回流天气系统结构特征认识不足和诊断失误而导致预报的失败,是降雨（雪）预报的难点和重点。利用北京地区高分辨率快速循环同化中尺度数值预报系统（BJ-RUC）对2010年1月2—3日一次典型的回流暴雪天气过程进行模拟,分析数值模式的模拟能力,研究各层主要影响系统结构特征及形成暴雪的关键性条件,探讨典型回流暴雪天气过程的形成机理。主要结论为：数值模式对此次暴雪过程的近地面回流冷空气、中低层低值系统及变化特征、主要降雪时段和降雪量模拟效果较好,对降雪落区的模拟存在一定偏差。低层回流偏东风遇到地形后引起垂直运动主要在低层800 hPa以下,所产生的降雪量不大,而其与上游850～700 hPa低涡系统发展东移其前部的上升运动汇合所形成的大范围、深厚、强烈的上升运动是产生明显降雪的关键性条件。上游低涡系统前部西南暖湿气流相对应的大湿度区移近是产生较强降雪的重要条件。持续的低层回流冷空气湿度较大,对于低层大气起到水汽输送的作用。回流冷空气使低层大气维持长时间的水汽输送并与其上层东移的大湿度区相结合,增加湿层厚度,有利于降雪持续而形成较强降雪。降雪开始时间和降雪强度的变化与对流层中下转偏南风的时间和偏南风风速增大有关。     

引黄水在北大港水库蓄存期水质咸化的研究

依据引黄水在北大港水库蓄存期水质咸化的事实以及传质理论,定性地分析了引黄水水质咸化的主要原因,包括盐碱土传质作用、蒸发浓缩作用以及风的扰动加速传质作用等.在北大港水库旁修建了一个模拟试验水池,进行了现场模拟试验研究.依据水量平衡和氯离子总量平衡的原理,分别定量地计算了传质作用和蒸发浓缩作用对水质咸化影响的比重.结果表明,在模拟水池蓄水后的30 d内,传质作用对水质咸化影响的比重有随时间增加而增长的趋势;30 d后,传质作用对水质咸化影响的比重稳定在80%,蒸发浓缩作用对水质咸化影响的比重稳定在20%,说明导致水质咸化的最主要因素是盐碱土传质作用.