Modellseismische Untersuchungen an 2- und 3-dimensionalen Testmodellen,Teil 1

Summary Following the recommendation of the European Seismological Commission (Copenhagen 1966) to carry out comparative measurements on simple seismic models with a prescribed velocity-depth distribution (test models), an attempt was made to compare results obtained with different model techniques. In the present paper, model investigations with the first two proposed test models carried out by 2- and 3-dimensional model techniques are described. Seismogrammes, travel-time curves and amplitude-distance curves of the models investigated are given. A quantitative comparison of the results shows a satisfactory agreement.     

Improving a regional model using reduced complexity and parameter estimation

The availability of powerful desktop computers and graphical user interfaces for ground water flow models makes possible the construction of ever more complex models. A proposed copper-zinc sulfide mine in northern Wisconsin offers a unique case in which the same hydrologic system has been modeled using a variety of techniques covering a wide range of sophistication and complexity. Early in the permitting process, simple numerical models were used to evaluate the necessary amount of water to be pumped from the mine, reductions in streamflow, and the drawdowns in the regional aquifer. More complex models have subsequently been used in an attempt to refine the predictions. Even after so much modeling effort, questions regarding the accuracy and reliability of the predictions remain. We have performed a new analysis of the proposed mine using the two-dimensional analytic element code GFLOW coupled with the nonlinear parameter estimation code UCODE. The new model is parsimonious, containing fewer than 10 parameters, and covers a region several times larger in areal extent than any of the previous models. The model demonstrates the suitability of analytic element codes for use with parameter estimation codes. The simplified model results are similar to the more complex models; predicted mine inflows and UCODE-derived 95% confidence intervals are consistent with the previous predictions. More important, the large areal extent of the model allowed us to examine hydrological features not included in the previous models, resulting in new insights about the effects that far-field boundary conditions can have on near-field model calibration and parameterization. In this case, the addition of surface water runoff into a lake in the headwaters of a stream while holding recharge constant moved a regional ground watershed divide and resulted in some of the added water being captured by the adjoining basin. Finally, a simple analytical solution was used to clarify the GFLOW model's prediction that, for a model that is properly calibrated for heads, regional drawdowns are relatively unaffected by the choice of aquifer properties, but that mine inflows are strongly affected. Paradoxically, by reducing model complexity, we have increased the understanding gained from the modeling effort.     

A discrete model for response estimation of soil-structure systems with embedded foundations

The need for simplifi ed physical models representing frequency dependent soil impedances has been the motivation behind many researches throughout history. Generally, such models are generated to capture impedance functions in a wide range of excitation frequencies, which leads to relatively complex models. That is while there is just a limited range of frequencies that really in? uence the response of the structure. Here, a new methodology based on the response-matching concept is proposed, which can lead to the development of simpler discrete models. The idea is then used to upgrade an existing simple model of surface foundations to the case of embedded foundations. The applicability of the model in both frequency domain and time domain analyses of soil-structure systems with embedded foundations is discussed. Moreover, the accuracy of the results is compared with another existing discrete model for embedded foundations.     

A hybrid artificial neural network-numerical model for ground water problems

Numerical models constitute the most advanced physical-based methods for modeling complex ground water systems. Spatial and/or temporal variability of aquifer parameters, boundary conditions, and initial conditions (for transient simulations) can be assigned across the numerical model domain. While this constitutes a powerful modeling advantage, it also presents the formidable challenge of overcoming parameter uncertainty, which, to date, has not been satisfactorily resolved, inevitably producing model prediction errors. In previous research, artificial neural networks (ANNs), developed with more accessible field data, have achieved excellent predictive accuracy over discrete stress periods at site-specific field locations in complex ground water systems. In an effort to combine the relative advantages of numerical models and ANNs, a new modeling paradigm is presented. The ANN models generate accurate predictions for a limited number of field locations. Appending them to a numerical model produces an overdetermined system of equations, which can be solved using a variety of mathematical techniques, potentially yielding more accurate numerical predictions. Mathematical theory and a simple two-dimensional example are presented to overview relevant mathematical and modeling issues. Two of the three methods for solving the overdetermined system achieved an overall improvement in numerical model accuracy for various levels of synthetic ANN errors using relatively few constrained head values (i.e., cells), which, while demonstrating promise, requires further research. This hybrid approach is not limited to ANN technology; it can be used with other approaches for improving numerical model predictions, such as regression or support vector machines (SVMs).     

Seismic resistance of precast concrete shear walls

The earthquake resistance of stacked precast concrete simple shear walls found typically in Large Panel buildings of the cross-wall type is studied. Physical model testing on a small shaking table facility and analytical techniques are compared. Results of the testing of four models to failure portrayed the non-linear effects of rocking and shear slip that were assumed in several analytical studies but were never before measured experimentally. The physical model studies are supplemented with an independent mathematical analysis using a modified version of the dynamic, non-linear computer code Drain 2–D. Correlation of the analytical and experimental results show that the computer study can be used to predict the overall shear wall response. Results of the small scale model and the mathematical model studies indicate that the simple shear wall behaves in a non-linear manner, even for low magnitudes of base acceleration. Non-linear effects, usually concentrated in only one or two joints, reduced force levels and increased displacements. The four small scale models that were tested withstood high magnitudes of base acceleration without collapse.     

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.     

A Simple Relation to Constrain Groundwater Models Using Surface Deformation

A simple relation between pore pressure change and one-dimensional surface deformation is presented. The relation is for pore pressure change in a confined aquifer that causes surface deformation. It can be applied to groundwater models of any discretization and is computationally efficient. The estimated surface deformation from model results can be compared to observed surface deformation through geodetic techniques such as Differential Interferometric Synthetic Aperture Radar. Model parameters then are constrained using the observed surface deformation. The validity of this relation is shown through constraint of model parameters for surface uplift due to pore pressure increase caused by wastewater disposal injection.     

利用非均匀细胞自动机模拟震级与应力降关系

为解释实际观测资料震源破裂过程与自相似(分形)模型的不一致性, 本文基于观测结果, 构建了由81×81个细胞单元组成二维非均匀断层模型, 并通过设计的细胞自动机模拟程序进行了模拟试验。 研究结果表明: 断层结构非均匀性是影响孕震过程特征的重要因素, 而且地震强度分布并非简单的自相似。 随着断层非匀质性增加, 破裂过程出现由相对的脆性破坏向塑性破坏特征变化的趋势。 利用细胞自动机不仅能较好地解释震级-频度关系中的大、 小震级段低头现象, 而且也可解释大震级事件具有相对恒定的应力降, 得到了与实际观测研究相一致的结果。     

Towards dynamic catchment modelling: a Bayesian hierarchical mixtures of experts framework

Despite the abundance of existing hydrological models, there is no single model that has been identified as performing consistently over the range of possible catchment types and catchment conditions. An attractive alternative to selecting a single model is to combine the results from several different hydrological models, thereby providing a more appropriate representation of model uncertainty than is the case otherwise. Methods based on Bayesian statistical techniques provide an ideal means to compare and combine competing models, as they explicitly account for model uncertainty. Bayesian model averaging is one such alternative that combines individual models by weighting models proportional to their respective posterior probability of selection. However, the necessity of having fixed weights for each model over the entire length of the simulation period means that the relative usefulness of different models at different times is not considered. The hierarchical mixtures of experts (HME) framework is an appealing extension of the model averaging framework that allows the individual model weights to be estimated dynamically. Consequently, a model more capable at simulating low flow characteristics attains a higher weight (probability) when such conditions are likely, switching over to a lower weight when catchment storage increases. In this way, different models apply in different hydrological states, with the probability of selecting each model being allowed to depend on relevant antecedent condition characteristics. HME models provide additional flexibility compared with simple combinations of models, by allowing the way that model predictions are combined to depend on predictor variables. Thus, for hydrological models, the ‘switch’ from one model to another can depend on the existing catchment condition. This new modelling framework is applied using a simple conceptual model to 10 selected Australian catchments. The study regions are chosen to vary considerably in terms of size, yield and location. Results from this application are compared with the alternative where a single fixed model structure is applied. Comparison of the model simulations using the maximum log‐likelihood and the Nash‐Sutcliffe coefficient of efficiency show that more variance in streamflow was explained by the HME model, compared with the conceptual model alone for each of the catchments investigated. Copyright © 2006 John Wiley & Sons, Ltd.     

Complementary aspects of linear flood routing modelling and flood frequency analysis

Similarity and differences between linear flood routing modelling (LFRM) and flood frequency analysis (FFA) techniques are presented. The moment matching used in LFRM to approximate the impulse response function (IRF) was applied in FFA to derive the asymptotic bias caused by the false distribution assumption. Proceeding in this way, other estimation methods were used as approximation methods in FFA to derive the asymptotic bias. Using simulation experiments, the above investigation was extended to evaluate the sampling bias. As a feedback, the maximum likelihood method (MLM) can be used for approximating linear channel response (LCR) by the IRFs of conceptual models. Impulse responses of the convective diffusion and kinematic diffusion models were applied and developed as FFA models. Based on kinematic diffusion LFRM, the equivalence of estimation problems of discrete‐continuous distribution and single‐censored sample are shown both for the method of moments (MOM) and the MLM. Hence, the applicability of MOM is extended for the case of censored samples. Owing to the complexity and non‐linearity of hydrological systems and resulting processes, the use of simple models is often questionable. The rationale of simple models is discussed. The problems of model choice and overparameterization are common in mathematical modelling and FF modelling. Some results for the use of simple models in the stationary FFA are presented. The problems of model discrimination are then discussed. Finally, a conjunction of linear stochastic processes and LFRM is presented. The influence of river courses on stochastic properties of the runoff process is shown by combining Gaussian input with the LCR of the simplified Saint Venant model. It is shown that, from the classification of the ways of their development, both LFRM and FFA can benefit. Copyright © 2006 John Wiley & Sons, Ltd.     

An immersed structure approach for fluid-vegetation interaction

We present an immersed structure approach for modeling the interaction between surface flows and vegetation. Fluid flow and rigid and flexible vegetative obstacles are coupled through a local drag relation that conserves momentum. In the presented method, separate meshes are used for the fluid domain and vegetative obstacles. Taking techniques from immersed boundary finite element methods, the effects of the fluid on the vegetative structures and vice versa are calculated using integral transforms. Using a simple elastic structure model we incorporate bending and moving vegetative obstacles. We model flexible vegetation as thin, elastic, inextensible cantilever beams. Using the immersed structure approach, a fully coupled fluid-vegetation interaction model is developed assuming dynamic fluid flow and quasi-static bending. This relatively computationally inexpensive model allows for thousands of vegetative obstacles to be included in a simulation without requiring an extremely refined fluid mesh. The method is validated with comparisons to mean velocity profiles and bent vegetation heights from experiments that are reproduced computationally. We test the method on several channel flow setups. We calculate the bulk drag coefficient in these flow scenarios and analyze their trends with changing model parameters including stem population density and flow Reynolds number. Bulk drag models are the primary method of incorporating small-scale drag from individual plants into a value that can be used in larger-scale models. Upscaled bulk drag quantities from this method may be utilized in larger-scale simulations of flow through vegetation regions.     

Instance‐based learning compared to other data‐driven methods in hydrological forecasting

Data‐driven techniques based on machine learning algorithms are becoming popular in hydrological modelling, in particular for forecasting. Artificial neural networks (ANNs) are often the first choice. The so‐called instance‐based learning (IBL) has received relatively little attention, and the present paper explores the applicability of these methods in the field of hydrological forecasting. Their performance is compared with that of ANNs, M5 model trees and conceptual hydrological models. Four short‐term flow forecasting problems were solved for two catchments. Results showed that the IBL methods often produce better results than ANNs and M5 model trees, especially if used with the Gaussian kernel function. The study showed that IBL is an effective data‐driven method that can be successfully used in hydrological forecasting. Copyright © 2007 John Wiley & Sons, Ltd.     

PEST and AEM Modeling for Data Acquisition Planning

A well-planned field data collection program should be designed to (1) collect a sufficient set of data of the right types at the right locations, and (2) collect a parsimonious set of data to avoid unnecessary costs. Combining PEST and a simple analytic element method (AEM) groundwater flow model for the site of interest provides a relatively simple, low-cost method of developing such a program. AEM models are well suited to this approach because they are quick to develop yet hydraulically accurate, reducing impacts on project budgets at early data collection planning stages; and quick to run, solving rapidly for the many iterations that PEST requires to generate good parameter estimates. This article shows two examples of this method: one for a steady state watershed model, and one for a transient pumping test project to demonstrate that PEST coupled with a simple AEM model that sketches out the key features of a site conceptual model can be an efficient tool in planning key parts of a hydrogeologic site investigation.     

On lithospheric flexure seaward of the Bonin and Mariana trenches

More than 25 bathymetry profiles have been used to examine the flexure of the Pacific lithosphere seaward of the Izu-Bonin and Mariana trenches. Selected bathymetry profiles have been corrected for the effects of sediment loading and compared to simple elastic and elastic-plastic models for lithospheric flexure seaward of these trenches. Profiles of the northern Mariana trench, where the seaward wall is relatively gentle, can be explained by a simple elastic model without an applied horizontal load. Profiles of the Izu-Bonin and southern Mariana trenches, where the seaward wall is relatively steep, can be explained by an elastic-plastic model with an applied load of 4.0–6.0 kbar, depending on the uniform yield stress assumed. If it is assumed the yield stress varies with depth the horizontal load required is significantly reduced (?2.5kbar). The magnitude of the horizontal load cannot be determined with certainty, however, since it is not known how the yield stress may vary with depth. The elastic-plastic models examined all required significant differences (～1.0kbar) in the horizontal load along the Izu-Bonin and Mariana trenches. These differences, which reach a maximum between the northern Izu-Bonin and northern Mariana trenches, appear to correlate with changes in the pattern of seismicity and tectonics landward of these trenches.     

用一种墙体单元模型分析剪力墙结构

本文概括介绍了目前国内外分析剪力结构所采用的计算模型,并用虚拟原理推导了多垂直杆元模型的单元刚度矩阵,讨论了这一模型中相对转动中心高度的取值,接着提供了确定这一模型中的垂直杆元的轴向刚度和水平弹簧的抗剪刚度的计算方法,在计算抗剪刚度时,考虑了受弯和受剪之间的相互作用,使这一模型与实际结构更加符合,最后,提供了一个算例,并与试验结果比较,表明了该模型不仅力学概念清晰,计算简单,而且具有较好的计算精度     

Pre‐ and post‐test mathematical modelling of a plan‐asymmetric reinforced concrete frame building

Pre‐ and post‐test analyses of the structural response of a three‐storey asymmetric reinforced concrete frame building were performed, aimed at supporting test preparation and performance as well as studying mathematical modelling. The building was designed for gravity loads only. Full‐scale pseudo‐dynamic tests were performed in the ELSA laboratory in Ispra. In the paper the results of initial parametric studies, of the blind pre‐test predictions, and of the post‐test analysis are summarized. In all studies a simple mathematical model, with one‐component member models with concentrated plasticity was employed. The pre‐test analyses were performed using the CANNY program. After the test results became available, the mathematical model was improved using an approach based on a displacement‐controlled analysis. Basically, the same mathematical model was used as in pre‐test analyses, except that the values of some of the parameters were changed. The OpenSees program was employed. Fair agreement between the test and numerical results was obtained. The results prove that relatively simple mathematical models are able to adequately simulate the detailed seismic response of reinforced concrete frame structures to a known ground motion, provided that the input parameters are properly determined. Copyright © 2006 John Wiley & Sons, Ltd.     

Non-linear inversion of resistivity profiling data for some regular geometrical bodies1

The inversion of resistivity profiling data involves estimation of the spatial distribution of resistivities and thicknesses of rock layers from the apparent resistivity data values measured in the field as a function of electrode separation. The drawbacks of using traditional curve-matching techniques to solve this inverse problem have been overcome by iterative linear techniques but these require good starting models even if the shape of the causative body is asssumed known. In spite of the recent developments in inversion techniques, no robust method exists for the inversion of resistivity profiling data for the simple model of dikes and spheres which are the classical models of geophysical prospecting. We apply three different non-linear inversion schemes to invert synthetic resistivity profiling data for the classical models embedded in a uniform matrix of contrasting resistivity. The three non-linear algorithms used are called the Metropolis simulated annealing (SA), very fast simulated annealing (VFSA) and a genetic algorithm (GA). We compare the performance of the three algorithms using synthetic data for an outcropping vertical dike model. Although all three methods were successful in obtaining optimal solutions for arbitrary starting models, VFSA proved to be computationally the most efficient.     

Advanced three-dimensional seismic imaging of deep supercritical geothermal rocks in Southern Tuscany

The seismic K-Horizon is the key to gaining understanding on the deep supercritical geothermal rocks in Southern Tuscany. The K-Horizon is hosted in metamorphic rocks, which cause strong seismic wavefield scattering resulting in a poor signal-to-noise ratio. Our study aims to reveal high-resolution seismic images of the K-Horizon below a geothermal field in Southern Tuscany, using an advanced three-dimensional seismic depth imaging approach. The key seismic pre-processing steps in the time domain include muting a large amount of persistent noise based on the statistical analysis of the seismic amplitudes, and tomostatics technique to correct for static effects. We carried out seismic depth imaging using Kirchhoff Pre-Stack Depth Migration and Fresnel Volume Migration techniques. Each migration technique was tested with constant and heterogeneous three-dimensional velocity models. Due to the difficulties in determining emergent angles for this low signal-to-noise ratio data set, the migration results with the heterogeneous three-dimensional velocity model show less coherent reflections compared to the migration results using the constant velocity model. Both velocity models however lead to relatively the same structure and depth of the K-Horizon, indicating the similarity of the average velocities along the wave propagation paths in both velocity models. With both velocity models Fresnel Volume Migration yields the K-Horizon with better reflection coherency and higher signal-to-noise ratio than standard Kirchhoff Pre-Stack Depth Migration. Nevertheless, both migration techniques have been able to reveal the K-Horizon with relatively high resolution and provide a reliable basis for geothermal rock characterization as well as steering of the first geothermal well penetrating the K-Horizon.     

A Hidden Markov Model Based Tool for Geophysical Data Exploration

--Unsupervised learning techniques provide a way of investigating scientific data based on automated generation of statistical models. Because these techniques are not dependent on a priori information, they provide an unbiased method for separating data into distinct types. Thus they can be used as an objective method by which to identify data as belonging to previously known classes or to find previously unknown or rare classes and subclasses of data. Hidden Markov model based unsupervised learning methods are particularly applicable to geophysical systems because time relationships between classes, or states of the system, are included in the model. We have applied a modified version of hidden Markov models which employ a deterministic annealing technique to scientific analysis of seismicity and GPS data from the southern California region. Preliminary results indicate that the technique can isolate distinct classes of earthquakes from seismicity data.     

Chloride in precipitation and streamwater for the upland catchment of river severn,mid-wales; some consequences for hydrochemical models

Variations in the concentration of Cl in rainfall and stream runoff are presented for two catchments in the Hafren forest of mid-Wales, Great Britain. Despite the large fluctuations in rainfall concentrations, Cl in the streamwater remains relatively constant. Using the two-reservoir Birkenes model, an attempt was made to simulate observed Cl in streamwater. The original model was unable to reproduce the observations and several modifications are suggested to provide better simulations. The resulting model is not the only one capable of reproducing the observations; other hydrochemical models will most probably also achieve this although emphasis will in each case be placed on different aspects. In this paper, it is suggested that the stochastic properties of water movement and chemical processes can account for the streamwater chemistry responses observed. On the catchment scale these processes will lead to an apparently deterministic behaviour that may well be described by simple relationships.