一维问题的等效远置动力人工边界条件

在土-结构动力相互作用分析中,黏性人工边界条件和黏弹性人工边界条件虽具有计算效率和精度较高的优点,但施加边界单元的工作量较大;远置边界虽然具有处理技术简单、精度高等优点,但又存在计算成本高的问题。为克服黏性人工边界和黏弹性人工边界施加边界黏弹性单元工作量大、远置边界计算成本高的缺点,基于波的传播理论和波在介质交界面上的反射、透射原理,通过设置完全透射层并大大降低波在透射层的传播速度的方法,提出了一种等效远置动力人工边界条件并对其进行数值验证分析。研究结果表明,所提出的等效远置动力人工边界条件仅需通过合理选取透射层的参数,即可实现反射波向无限地基传播的模拟,具有精度和效率较好、不需施加边界单元工作量等优点,可应用到土-结构动力相互作用分析当中。     

RELIABILITY BASED ANALYSIS ON RESERVOIR INDUCED EARTHQUAKES

Reservoir induced earthquakes (RIE) are caused by impoundment of reservoir,with the characteristics of small magnitude and shallow focal depth,but they can also lead to not only economic loss,but also many serious secondary disasters,such as dam destruction,landslide,producing greater damages far more than the damages directly produced by earthquakes.So study on RIE is quite significant in the field of dam construction,thus more attentions should be paid to RIE.There are many factors to induce reservoir earthquakes,such as geological condition,rock mass mechanical index,state of crustal stress,pore pressure distribution,all of which are extremely difficult to measure due to the presence of many randomness;even if applying most advanced methods to measure them,the values fluctuate in great range,without a certain value in time and space.The great variety of these parameters gives rise to troubles to analyze RIE by deterministic approaches.How to handle the randomness of these factors has become vital problem in the field of RIE research.In this study,based on probability theory,and taking the main influence factors as stochastic variables,a new method to analyze probability of RIE was proposed by applying reliability theory.Firstly,the factors inducing reservoir earthquakes were analyzed,of which pore pressure in fault caused by water impounding of reservoir plays a vital role in triggering earthquakes.Then,taking these factors,including attitude,friction coefficient,cohesion of fault plane,stress state of fault plane and pore pressure in fault,as stochastic variables,performance function of triggering earthquakes was established by applying Coulomb stress on the fault plane,and reliability theory was used to analyze probability of earthquake induced by main factors.A special case analysis showed that:(1) The probability of induced earthquakes dramatically increases as pore pressure in fault increases;under the condition of equal pore pressure at triggering earthquakes area,probability of induced earthquakes obviously rises with enlarging of variation of pore pressure;(2) those faults with strike approximately parallel to horizontal maximum principal stress direction or with steep dip angle about more than 60° are prone to inducing earthquake;(3) as horizontal minimum principal stress increases,which has greater effect on induced earthquakes than horizontal maximum principal stress,probability of induced earthquakes becomes lower and fault keeps in more stable condition;(4) probability of induced earthquakes gradually decreases with the increase of friction coefficient and cohesion of fault plane;However,the effect of friction coefficient on induced earthquakes is much greater than the cohesion of fault plane.     

衡水冀16井水位异常变化调查与分析

衡水冀16井水位2014年10月27日突升之后并维持在高值变化,在高值变化的同时出现多次阶升阶降变化形态。此井井深为1700.41米,突升幅度为0.0588m,以前从未出现过上述情况,该异常变化是否是前兆异常?为了确定异常性质,从供电系统、观测仪器、对比观测、环境干扰等方面进行调查和分析,最终排查出是泄流口排水池堵塞造成水位变化,不是地震前兆异常,对异常变化机理进行初步分析,为判断水位异常变化积累了经验。     

双轴应力下非贯通节理岩体压缩损伤本构模型

针对目前节理岩体损伤变量定义中大多仅考虑节理长度、倾角等几何性质,而未考虑节理抗剪强度等力学性质的不足,基于断裂力学中的由于单个节理存在引起的附加应变能增量与损伤力学中的损伤应变能释放量相关联的观点,推导出了在双轴应力下含单条非贯通闭合节理岩体的损伤变量计算公式,并根据断裂力学理论对双轴压缩荷载下的单个节理尖端应力强度因子计算方法进行了研究,得出了应力强度因子KⅠ、KⅡ的计算公式;同时考虑多节理间的相互作用,给出了单组单排及单组多排非贯通节理尖端应力强度因子计算公式,由此建立了相应的节理岩体双轴压缩损伤本构模型,并利用该模型进行了相应的算例分析。结果表明：对含单条非贯通闭合节理的岩体而言,当节理倾角小于其内摩擦角时,岩体强度与完整岩石相同,岩体损伤为0,而后随着节理倾角增加,岩体强度、损伤随节理倾角的变化分别呈开口向上及向下的抛物线,当节理倾角约为60°时,岩体损伤最大,强度最低。随着节理长度增加,岩体损伤增加,而随着节理内摩擦角的增加,岩体损伤则减小;对含单组单排非贯通闭合节理的岩体而言,当节理总长度一定时,随着单条节理长度的减小及节理条数的增加,岩体损伤则逐渐减小,但其减小幅度与节理条数并不呈线性关系。     

Linear interpolation and joint model fitting of experimental transiograms for Markov chain simulation of categorical spatial variables

In Markov chain random field (MCRF) simulation of categorical spatial variables with multiple classes, joint modeling of a large number of experimental auto and cross-transiograms is needed. This can be tedious when mathematical models are used to fit the complex features of experimental transiograms. Linear interpolation can be used to perform the joint modeling quickly regardless of the number and the complexity of experimental transiograms. In this paper, we demonstrated the mathematical validity of linear interpolation as a joint transiogram-modeling method, explored its applicability and limitations, and tested its effect on simulated results by case studies with comparison to the joint model-fitting method. Simulations of a five-class variable showed little difference in patterns for interpolated and fitted transiogram models when samples were sufficient and experimental transiograms were in regular shapes; however, they neither showed large difference between these two kinds of transiogram models when samples were relatively sparse, which might indicate that MCRFs were not much sensitive to the difference in the detail of the two kinds of transiogram models as long as their change trends were identical. If available, expert knowledge might play an important role in transiogram modeling when experimental transiograms could not reflect the real spatial variation of the categorical variable under study. An extra finding was that class enclosure feature (i.e., a class always appears within another class) was captured by the asymmetrical property of transiograms and further generated in simulated patterns, whereas this might not be achieved in conventional geostatistics. We conclude that (i) when samples are sufficient and experimental transiograms are reliable, linear interpolation is satisfactory and more efficient than model fitting; (ii) when samples are relatively sparse, choosing a suitable lag tolerance is necessary to obtain reliable experimental transiograms for linear interpolation; (iii) when samples are very sparse (or few) and experimental transiograms are erratic, coarse model fitting based on expert knowledge is recommended as a better choice whereas both linear interpolation and precise model fitting do not make sense anymore.     

Incorporating spectral data into logistic regression model to classify land cover: a case study in Mt. Qomolangma (Everest) National Nature Preserve

Only few models for land-cover classification incorporated spectral data into ordinary logistic regression (OL model) in the Mt. Qomolangma (Everest) National Nature Preserve (QNNP) in China. In this study, spectral variables were incorporated into OL model and autologistic regression (AL) model to classify six main land covers. Twelve environmental variables and seven spectral variables of 10,000 stratified random sites in the QNNP were quantified and analyzed; OL model, AL model, OL model with spectral data (OLM model), and AL model with spectral data (ALM model) were estimated. The OLM and ALM models produced better estimates of regression coefficients and significantly improved model performance and overall accuracy for the grassland, sparsely vegetated land, and bare land compared with OL and AL models.     

模糊可变集合方法在降雨相似性分析中的应用

基于特定流域场次降雨具有的相似性,应用考虑区间值模糊可变的模糊可变集合方法进行场次降雨相似性分析。通过计算各场次降雨隶属于各降雨级别的特征值及与目标场次降雨之间的相似距离,从而获得流域场次降雨相似性排序,有效解决了场次降雨相似分析中的模糊性和不确定性问题。找出与实时阶段场次降雨相似的历史场次降雨,预估水库实时阶段面临的洪水过程及量级,可为水库防洪调度提供信息参考。     

岩石内变量蠕变模型研究

通过一系列砂岩、页岩和辉绿岩室内蠕变试验,获得了不同应力和初始应变状态下岩石蠕变特性。通过误差分析讨论了计算蠕变速率时如何选择时间增量。讨论了复杂加、卸载条件下时间相关蠕变模型的局限性,提出采用不可恢复应变作为内变量来描述复杂条件下岩石蠕变性质,并据此提出了岩石的内变量蠕变模型。试验数据与模型拟合结果对比表明,内变量蠕变模型较好地反映了3种岩石的蠕变行为。此外,还初步讨论了模型在岩石率相关性质研究中的适用性,并利用相关试验数据进行了验证。     

利用蒙特卡罗方法的剩余静校正及其应用

针对剩余静校正问题,讨论了统计方法中的蒙特卡罗法用于反射波能量最大化剩余静校正的方法。分别论述了反射波叠加能量最大化法和蒙特卡罗方法,以及蒙特卡罗方法如何应用于剩余静校正的计算中,并用实例说明了该方法的效果。通过实际应用蒙特卡罗剩余静校正方法,解决了经野外静校正后残留的剩余静校正问题,并通过与其他剩余静校正方法的实际应用对比,说明了蒙特卡罗剩余静校正方法的优势。对于大剩余量的静校正问题,蒙特卡罗剩余静校正方法仍然可以很好的解决,并且不会产生串相位问题,说明蒙特卡罗剩余静校正方法是可靠的。     

基于BP神经网络的地磁变化场预测研究

以现有地磁台站的长期海量观测数据为基础,忽略地磁场成因及众多影响因素的复杂作用机理,对地磁变化场的时空关联性进行分析,挖掘数据中蕴含的规律信息,进一步构建基于BP神经网络的地磁变化场预测模型。通过实际地磁台站的观测数据对模型预测结果进行验证,结果表明,对于任意选取的100组验证数据,均方根误差为4.8 nT,求解精度能够满足一般科学研究对地磁变化场的精度需求。