建筑物沉降规律的综合时序分析   总被引：6，自引：0，他引：6  

崔晓东  兰孝奇  张兵良 《现代测绘》2004,27(1):36-38

建筑物的沉降监测数据序列具有趋势变化和随机变化的特点，本文针对两种变化项的特点分别建立相应的数学模型，再将其组合起来建立综合数学模型，从总体上把握沉降数据序列的变化规律。实例计算分析表明，此方法具有较高的拟合精度和预测能力，具有一定的应用参考价值。  相似文献   

Conditioning mean steady state flow on hydraulic head and conductivity through geostatistical inversion   总被引：5，自引：2，他引：3  

A. F.?Hernandez  S. P.?NeumanEmail author  A.?Guadagnini  J.?Carrera 《Stochastic Environmental Research and Risk Assessment (SERRA)》2003,17(5):329-338

Nonlocal moment equations allow one to render deterministically optimum predictions of flow in randomly heterogeneous media and to assess predictive uncertainty conditional on measured values of medium properties. We present a geostatistical inverse algorithm for steady-state flow that makes it possible to further condition such predictions and assessments on measured values of hydraulic head (and/or flux). Our algorithm is based on recursive finite-element approximations of exact first and second conditional moment equations. Hydraulic conductivity is parameterized via universal kriging based on unknown values at pilot points and (optionally) measured values at other discrete locations. Optimum unbiased inverse estimates of natural log hydraulic conductivity, head and flux are obtained by minimizing a residual criterion using the Levenberg-Marquardt algorithm. We illustrate the method for superimposed mean uniform and convergent flows in a bounded two-dimensional domain. Our examples illustrate how conductivity and head data act separately or jointly to reduce parameter estimation errors and model predictive uncertainty.This work is supported in part by NSF/ITR Grant EAR-0110289. The first author was additionally supported by scholarships from CONACYT and Instituto de Investigaciones Electricas of Mexico. Additional support was provided by the European Commission under Contract EVK1-CT-1999-00041 (W-SAHaRA-Stochastic Analysis of Well Head Protection and Risk Assessment).  相似文献   

Another look at the conceptual fundamentals of porous media upscaling     

G.?ChristakosEmail author 《Stochastic Environmental Research and Risk Assessment (SERRA)》2003,17(5):276-290

We suggest a critical look at the epistemic foundations of the porous media upscaling problem that focuses on conceptual processes at work and not merely on form manipulations. We explore the way in which critical aspects of scientific methodology make their appearance in the upscaling context, thus generating useful effective parameters in practice. The fons et origo of our approach is a conceptual blending of knowledge states that requires the revision of the traditional method of scientific argument underlying most upscaling techniques. By contrast to previous techniques, the scientific reasoning of the proposed upscaling approach is based on a stochastic model that involves teleologic solutions and stochastic logic integration principles. The syllogistic form of the approach has important advantages over the traditional reasoning scheme of porous media upscaling, such as: it allows the rigorous derivation of the joint probability distributions of hydraulic gradients and conductivities across space; it imposes no restriction on the functional form of the effective parameters or the shape of the probability laws governing the random media (non-Gaussian distributions, multiple-point statistics and non-linear models are automatically incorporated); it relies on sound methodological principles rather than being ad hoc; and it offers the rational means for integrating the multifarious core knowledge bases and uncertain site-specific information sources about the subsurface system. Previous upscaling results are derived as special cases of the proposed upscaling approach under limited conditions of porous media flow, a fact that further demonstrates the generalization power of the approach. Our hope is that looking at the upscaling problem in this novel way will direct further attention to the methodological exploration of the problem at the length and the detail that it deserves.I would like to thank Drs. A. Kolovos and D.T. Hristopulos for their valuable comments. The work was supported by grants from the Army Research Office (Grant no. DAAG55–98–1-0289) and the National Institute of Environmental Health Sciences (P42-ES05948 & P30-ES10126).  相似文献   

A BME solution of the inverse problem for saturated groundwater flow   总被引：3，自引：3，他引：0  

M. L.?SerreEmail author  G.?Christakos  H.?Li  C. T.?Miller 《Stochastic Environmental Research and Risk Assessment (SERRA)》2003,17(6):354-369

In most real-world hydrogeologic situations, natural heterogeneity and measurement errors introduce major sources of uncertainty in the solution of the inverse problem. The Bayesian Maximum Entropy (BME) method of modern geostatistics offers an efficient solution to the inverse problem by first assimilating various physical knowledge bases (hydrologic laws, water table elevation data, uncertain hydraulic resistivity measurements, etc.) and then producing robust estimates of the subsurface variables across space. We present specific methods for implementing the BME conceptual framework to solve an inverse problem involving Darcys law for subsurface flow. We illustrate one of these methods in the case of a synthetic one-dimensional case study concerned with the estimation of hydraulic resistivity conditioned on soft data and hydraulic head measurements. The BME framework processes the physical knowledge contained in Darcys law and generates accurate estimates of hydraulic resistivity across space. The optimal distribution of hard and soft data needed to minimize the associated estimation error at a specified sampling cost is determined. This work was supported by grants from the National Institute of Environmental Health Sciences (Grant no. 5 P42 ES05948 and P30ES10126), the National Aeronautics and Space Administration (Grant no. 60-00RFQ041), the Army Research Office (Grant no. DAAG55-98-1-0289), and the National Science Foundation under Agreement No. DMS-0112069.  相似文献   

Stochastic estimation of facies using ground penetrating radar data   总被引：3，自引：2，他引：1  

S.?MoyseyEmail author  J.?Caers  R.?Knight  R. M.?Allen-King 《Stochastic Environmental Research and Risk Assessment (SERRA)》2003,17(5):306-318

Explicitly defining large-scale heterogeneity is a necessary step of groundwater model calibration if accurate estimates of flow and transport are to be made. In this work, neural networks are used to estimate radar facies probabilities from ground penetrating radar (GPR) images, yielding stochastic facies-based models that honour the large-scale architecture of the subsurface. For synthetic GPR images, a neural network was able to correctly identify radar facies with an accuracy of approximately 90%. Manual interpretation of a set of 450 MHz GPR field data from the Borden aquifer resulted in the identification of four radar facies. Of these, a neural network was able to identify two facies with an accuracy of near 80% and one with an accuracy of 44%. The neural network was not able to identify the fourth facies, likely due to the choice of defining facies characteristics. Sequential indicator simulation was used to generate facies realizations conditioned to the radar facies probabilities. Numerical simulations indicate that significant improvements in the prediction of solute transport are possible when GPR is used to constrain the facies model compared to using well data alone, especially when data are sparse.This work was supported by funding to R. Knight under Grant No. DE-FG07–00ER15118-A000, Environmental Management Science Program, Office of Science and Technology, Office of Environment Management, United States Department of Energy (DOE). However, any opinions, findings, conclusions, or recommendations expressed herein are those of the authors and do not necessarily reflect the views of DOE. Further support was provided by a Stanford Graduate Fellowship to S. Moysey. The authors would also like to thank James Irving for his assistance with processing of the radar data.  相似文献   

Simulation of near source ground motion and its characteristics     

S. Suzuki  K. Asano 《Soil Dynamics and Earthquake Engineering》2000,20(1-4)

It is fact that the severe ground motions of shear waves have a strong effect on the dynamic behavior of buildings and civil structures. We simulate near source strong motions of a pure shear wave and synthesize small motions, using the parameters based on the recorded accelerograms at the site that is regarded as a base rock in the Osaka basin, Japan. By making use of a stochastic technique, we can easily introduce higher frequency contents in the motions and apply the technique to the synthesis of small waves regarding as a green function. We also introduce to the analysis the useful relationships among the time duration T_d, the seismic moment M₀, the corner frequency f_c and the high cutoff frequency f_max which were regressed by a simple representation scheme. Considering two active faults that may affect severe damage on buildings and civil structures, we try to predict strong ground motions in Osaka basin and show the characteristics of them.  相似文献   

利用ERBE资料分析中国地区云辐射强迫的时空变化   总被引：7，自引：3，他引：4  

马晓燕  季国良 《高原气象》2000,19(2):150-158

利用１９８５￣１９８８年４年的ＥＲＢＥ资料,分析和揭示了我国大陆地区云辐射强迫变化的一些基本事实。结果发现：云强迫存在很大的区域差异和较强的季节变化,其中川黔地区是全国最大的云强迫负值区,其次是长江中下游地区和华北地区青藏高原为正、负值的过渡区,高原北侧的西北干旱区冬季为较弱的云强迫正值区。此外,云强迫还具有一定的年际变化。  相似文献   

北半球环流季节演变机制   总被引：4，自引：2，他引：2  

蔡尔诚 《气象与环境科学》2000,(3):8-9

提出了北半球大气环流季节变化的一种反馈机制：外界（太阳、海洋、陆地等）的热力强迫加热大气,形成波状低云;而波状低云又使高中纬大气冷却,进而影响高纬冷气团冬夏变化。根据波状低云影响高纬冷气团变化这一负反馈过程,对1958－1993年进行夏季旱涝预报试验,结果每年中国东部的主雨带基本可正确预测出来。  相似文献   

地球轨道旋回沉积节律研究进展——兼论轨道旋回的沉积学特征、年代学意义和研究方法   总被引：11，自引：0，他引：11  

柳永清 《地球科学进展》1998,13(3):217-224

地球轨道旋回是古代沉积记录中常见的由地球轨道参数变动控制的沉积节律，它不仅自身表现显著的节律性，而且通过反馈体系强烈影响着沉积作用。同时，轨道旋回节律在不同的沉积背景下以不同的沉积特征显现和规则性叠加。地球轨道旋回赋有的规则频率变化特征又使其具有年代学意义和应用价值，它是天文地质学、地层学及沉积学研究的重点内容。根据国内外资料综述了这些方面的研究进展，并探讨了地球轨道旋回的研究方法。  相似文献   

Seismic ground motion relationship in southern China based on stochastic finite-fault model   总被引：1，自引：0，他引：1  

郑斯华  黄玉龙 《地震工程与工程振动(英文版)》2004,3(1):11-21

The characteristics of seismic ground motions in southern China are difficult to determine statistically due to a lack of strong ground motion data. In this study, a stochastic finite-fault ground motion model was adopted to simulate the seismic ground motions at bedrock for southern China, based on parameters derived from small and medium earthquakes that have occurred in the region. From these, the response spectra was estimated. A set of ground motion attenuation relations hipswas then developed based on simulated peak ground motions and response spectral parameters through regression, which would be applicable for use in engineering practice. Through comparisons, it was demonstrated that the proposed ground motion relationships are generally consistent with those obtained from other reported ground motion attenuation models for southern China.  相似文献