基础隔震单层偏心结构扭转地震反应分析

采用微分型滞回恢复力模型模拟隔震支座的恢复力特性，对基础隔震单层偏心结构的扭转地震反应进行分析，研究隔震系统偏心距和上部结构偏心距对结构扭转反应的影响。结果表明，采用隔震技术可以显著降低隔震结构的扭转地震反应。     

不同轴压比RCS梁柱组合件恢复力模型研究

以6个1/2模型RCS梁柱节点拟静力试验为基础,研究不同轴压比下RCS组合件的滞回性能。试验结果表明:梁铰破坏时试件的滞回曲线饱满,耗能能力优于构造破坏;随着轴压比的增大,试件滞回环愈加丰满,初始刚度有所增加,承载力有所增大;随着加载位移的增加,刚度退化速率变慢,且梁铰破坏时随着轴压比增大,刚度退化速率变大。基于试验结果和现有恢复力模型理论,建立的三折线骨架曲线模型与实际试验骨架曲线具有较高的吻合度,能较好的反映轴压比对其滞回特性的影响,可为该RCS梁柱组合件的弹塑性分析及工程应用提供参考。     

桩-土-结构体系随机地震响应的实用计算方法及参数分析

考虑地震的随机性和土体的非线性,引入粘弹性边界,提出了一种在谐响应分析中直接输入加速度的加载方式,建立了基于虚拟激励法、等效线性化法和确定性动力有限元法相结合的非线性桩-土-结构体系随机地震响应的实用计算方法.采用该法对单桩支承的剪切型结构进行了较为全面的参数分析.结果表明基岩地震动输入水平,桩长度和土体模量都对结构反应有较大影响.该方法可方便的用于随机地震下桩-土-结构体系的参数分析中.     

联合多点地质统计学与序贯高斯模拟的随机反演方法

岩相和储层物性参数是油藏表征的重要参数,地震反演是储层表征和油气藏勘探开发的重要手段.随机地震反演通常基于地质统计学理论,能够对不同类型的信息源进行综合,建立具有较高分辨率的储层模型,因而得到广泛关注.其中,概率扰动方法是一种高效的迭代随机反演策略,它能综合考虑多种约束信息,且只需要较少的迭代次数即可获得反演结果.在概率扰动的优化反演策略中,本文有效的联合多点地质统计学与序贯高斯模拟,并结合统计岩石物理理论实现随机反演.首先,通过多点地质统计学随机模拟,获得一系列等可能的岩相模型,扰动更新初始岩相模型后利用相控序贯高斯模拟建立多个储层物性参数模型;然后通过统计岩石物理理论,计算相应的弹性参数;最后,正演得到合成地震记录并与实际地震数据对比,通过概率扰动方法进行迭代,直到获得满足给定误差要求的反演结果.利用多点地质统计学,能够更好地表征储层空间特征.相控序贯高斯模拟的应用,能够有效反映不同岩相中储层物性参数的分布.提出的方法可在较少的迭代次数内同时获得具有较高分辨率的岩相和物性参数反演结果,模型测试和实际数据应用验证了方法的可行性和有效性.     

生活垃圾卫生填埋地质环境(LFGE)效应的系统分析方法研究——以上海浦东新区为例

在系统分析总结国内外本领域的研究发展现状的基础上,以上海浦东新区城市生活垃圾卫生填埋处理为研究背景,首次提出ＬＦＧＥ效应系统分析方法的完整理论和应用体系,体系主要包括：ＬＦＧＥ效应的主控因素特征分析;在垃圾淋滤试验、有关土的工程性能试验和反映运移转化特征的土柱试验基础上的作用机制研究;具单元、组合、整体模拟及压实效应模拟功能的模拟计算研究;在不确定性条件存在下,随机模拟研究和以贝叶斯决策分析理论为基础的ＬＦＧＥ效应决策分析技术经济转换研究     

简单随机模式进一步分析(Ⅰ)——非线性外通函数项处理

本文利用等效线性化法和Fokker-planck方程,对一个简单的非线性随机模式非线性项在不同气候时期的参数化进行了讨论,得到了冰期、间冰期和现代气候的概率分布密度及输出响应特征。     

地震活动的随机标度和非线性标度律

把地震作为一个复杂系统，研究了地震活动的随机性质．当不考虑震级范围时，全球地震活动、人震的余震和区域震群均有以幂次律为特征的长尾现象．地震的强度由震级确定，具有一特定震级的地震可形成一个地震活动系列，很多这样的地震活动系列就形成具有各种震级的地震的集合．不同地震系列间的统计特征由随机标度来表征，随机标度表明了由地震震级分类的不同地震系列间统计时刻的标度关系．为了统一地方、区域和全球地震活动性的统计特性，引入了非线性标度率．     

STOCHASTIC THEORY OF THE DISTRIBUTION OF SEDIMENT PARTICLES SUSPENDED IN A TURBULENT FLOW

The random motion of sediment particles suspended in a turbulent flow is studied by means of stochastic process. Results of analysis of particle's frequency response to the random force exerted on the particle due to fluid turbulence suggest that only the lower part of the whole frequency range of the eddy motion will govern the motion of the particle. The mean values of particle velocity and displacement in the vertical direc- tion are calculated and it is found that particle velocity vp- can be decomposed into a mean motion and a velocity fluctuation vp- , where is equal to the fall velocity in tranquil fluid. An Ito^ random differential equation for particle dis- placement Yp is developed, from which a Fokker-Planck equation for the probability density function p(y,t) is derived on the basis of the theory of Markov process, where y denotes the vertical coordinate. The vertical distribution of the particle is thus interrelated to the random motion of the particle. The an effect that a particle will be subject to in the neighborhood or the bottom boundary is taken into consideration and a corresponding Fokker-Planck equation is developed. Analytical solution of the Fok- ker-Planck equation including the lift force effect shows that probability density p(y,t) for the particle displacement has a maximum value at y = H where the perpen- dicular component of the lift force balances the particle gravity. This theoretical result agrees with experimental observations as reported in literature.     

Parameter identification in tidal models with uncertain boundary conditions

In this paper a parameter estimation algorithm is developed to estimate uncertain parameters in two dimensional shallow water flow models. Since in practice the open boundary conditions of these models are usually not known accurately, the uncertainty of these boundary conditions has to be taken into account to prevent that boundary errors are interpreted by the estimation procedure as parameter fluctuations. Therefore the open boundary conditions are embedded into a stochastic environment and a constant gain extended Kalman filter is employed to identify the state of the system. Defining a error functional that measures the differences between the filtered state of the system and the measurements, a quasi Newton method is employed to determine the minimum of this functional. To reduce the computational burden, the gradient of the criterium that is required using the quasi Newton method is determined by solving the adjoint system.