Nonlinear Static Procedure for Multi-Story Asymmetric Frame Buildings Considering Bi-Directional Excitation

The present article focuses on a nonlinear static procedure (NSP) for a multi-story asymmetric frame building with regular elevation subjected to bi-directional ground motion. In this procedure, two simplified models—an equivalent single-story model and an equivalent single-degree-of-freedom (SDOF) model—are used to predict the peak response of multi-story asymmetric buildings. The peak response is predicted through pushover analysis of an equivalent single-story model considering the effect of bi-directional excitations and an estimation of the nonlinear response of equivalent SDOF models. The predicted results are compared with the nonlinear dynamic analysis results, and satisfactory predictions can be obtained by the proposed procedure.     

A combined procedure for recovering phytoliths and starch residues from soils,sedimentary deposits and similar materials

Presented is a combined procedure for recovering phytoliths and starch residues from soils, sedimentary deposits and similar materials. It is designed to be reliable, simple and time efficient, and is outlined in detail and summary as a practical, step-by-step method. It has been carried out successfully on many types of soils and other deposits, including clays, silts and sands; waterlogged, porous, peaty, volcanic and coralline soils; and sediment cores and coprolites from a range of environmental settings in both tropical and temperate climates. Mounting phytoliths and starch residues on slides for microscopy is included.     

Large-Scale Experimental Investigation on Mustafa Pasha Mosque

To evaluate the seismic stability of Mustafa Pasha Mosque in Skopje strengthened by an advanced mixed technology, shaking table tests were carried out on a model in scale 1:6. The investigation was performed within the activities of the Sixth Framework Program PROHITECH – “Earthquake Protection of Historical Buildings by Reversible Mixed Technologies”. To define the effectiveness of the proposed strengthening the testing procedure consisted of two main phases: testing of the original model and testing of the strengthened model. The observed seismic behavior and damage during each phase of the testing program were analyzed on the basis of the obtained experimental results.     

On-line Model Updating in Hybrid Simulation Tests

Hybrid simulation has emerged as a relatively accurate and efficient tool for the evaluation of structural response under earthquake loading. In conventional hybrid simulation the response of a few critical components is obtained by testing while the numerical module is assumed to follow an analytical idealization. Where there is a much larger number of analytical components compared to the experimental parts, the overall response may be dominated by the idealized parts hence the value of hybrid simulation is diminished. It is proposed to modify the material constitutive relationship of the numerical model during the test, based on the data obtained from the physically tested component. An approach based on genetic algorithms is utilized as an optimization tool to identify the constitutive relationship parameters used in updating the numerical model. The proposed model updating approach is verified through two analytical examples of steel and reinforced concrete frames. The results show the effectiveness of the updating process in minimizing the errors, compared to the assumed exact solution.     

Bayesian Updating of Seismic Demand Models and Fragility Estimates for Reinforced Concrete Bridges with Two-Column Bents

Probabilistic models have been developed in a previous study by the authors to estimate the seismic deformation demands on structural components of reinforced concrete (RC) bridges with two-column bents. However, such models should be updated to reflect the latest laboratory of field data. Using a Bayesian approach, this article updates a currently available probabilistic model for the deformation demands of columns in bridges with two-column RC bents. The updated model incorporates information from newly available experimental data from shake table tests conducted based on a record of the 1994 Northridge Earthquake for a structural system with three bents with two columns per bent. The updated model is more accurate than the previous one in predicting the deformation demand of bridges with two-column RC bents and reduces the statistical uncertainty due to the addition of new data. As an application, fragility estimates for an example bridge are computed using the updated model both at the component (column) and system (bridge) levels.     

Application of LASSO to the Eigenvector Selection Problem in Eigenvector‐based Spatial Filtering

Eigenvector‐based spatial filtering is one of the often used approaches to model spatial autocorrelation among the observations or errors in a regression model. In this approach, a subset of eigenvectors extracted from a modified spatial weight matrix is added to the model as explanatory variables. The subset is typically specified via the selection procedure of the forward stepwise model, but it is disappointingly slow when the observations n take a large number. Hence, as a complement or alternative, the present article proposes the use of the least absolute shrinkage and selection operator (LASSO) to select the eigenvectors. The LASSO model selection procedure was applied to the well‐known Boston housing data set and simulation data set, and its performance was compared with the stepwise procedure. The obtained results suggest that the LASSO procedure is fairly fast compared with the stepwise procedure, and can select eigenvectors effectively even if the data set is relatively large (n = 10⁴), to which the forward stepwise procedure is not easy to apply.     

Pseudo-Dynamic Testing and Analytical Modeling of AAC Infilled RC Frames

Two concrete frames were tested by the PsD procedure. One frame was bare and the other was infilled with AAC blocks in the middle bay. The objective was to determine the effect of AAC infills on the seismic performance of reinforced concrete frames and developing an AAC strut model. Based on the test results, it was found that AAC infill panels did not modify the deformation response of the RC test frame significantly; however, shear in diagonal strut must be considered in boundary column design. A shear design procedure is proposed for the boundary columns in infilled frames. The drift limits of AAC infill panels measured during the tests were 0.005, 0.008, and 0.014 during diagonal cracking, corner crushing, and severe damage states, respectively.     

Numerical Assessment of Frictional Heating in Sliding Bearings for Seismic Isolation

This article proposes a numerical investigation of the frictional heating developed in sliding bearings under high velocities and the influence of the relevant temperature rise on the mechanical characteristics of the device. A three-dimensional finite element model of the bearing is created and frictional heat generation is modelled through a thermal source inserted at the sliding surface of the bearing, with intensity dependent on the coefficient of friction, the contact pressure and the velocity. The friction value is adjusted step-by-step on surface temperature and velocity and used to update the thermal flux and the resisting force developed by the bearing. The numerical predictions of temperature histories and force–displacement loops are compared with the results of laboratory tests to validate the numerical approach. The procedure can help in preliminary studies for the selection of bearing materials accounting for their thermal stability and for the estimation of change of design properties of sliding isolation bearings due to frictional heating.     

Natural Frequency of Single Pier Bridges Considering Soil-Structure Interaction

Because of the crucial role of free vibration frequency of a structure (e.g., a bridge) in design procedure, more realistic estimation of the frequency ends up in safer and more optimized design. As obtaining the free vibration frequencies of a bridge, considering soil-pile group-structure interaction, provide more realistic values, development of an analytical model to obtain such free vibration frequencies is studied in this research work. Most researchers have studied models with a single pile foundation. The purpose of this study is to assess soil-structure interaction (SSI) effects on dynamic performance of pile group supported bridges. A new analytical model is proposed to predict seismic analysis of these bridges. Applying the dynamic equations of motion for the system, SSI effects have been estimated. Based on the suggested analytical model, a new approximate equation is proposed for calculating natural frequency of pile group supported bridges. Equation accuracy has been investigated by comparing the results with those achieved by previous studies. Most periods calculated by the approximate equation are similar to those given for other case studies, indicating that the model could be applicable to other projects. Since the proposed model is very similar to real soil-pile-pier systems, this approximate equation can be used in preliminary seismic design of bridges.     

图们江地区开发决策支持系统的初步研究

本文讨论了图们江地区开发决策支持系统的组建原则,设计构建了较为实用的数据库系统、模型库系统和专家知识库系统,研制和开发了模型库人机对话三级管理系统。经初步运行验证,该系统是实用的,在某些方面也是可靠的。     

Quantitative basin modeling: present state and future developments towards predictability

A critique review of the state of quantitative basin modeling is presented. Over the last 15 years, a number of models are proposed to advance our understanding of basin evolution. However, as of present, most basin models are two dimensional (2‐D) and subject to significant simplifications such as depth‐ or effective stress‐dependent porosity, no stress calculations, isotropic fracture permeability, etc. In this paper, promising areas for future development are identified. The use of extensive data sets to calibrate basin models requires a comprehensive reaction, transport, mechanical (RTM) model in order to generate the synthetic response. An automated approach to integrate comprehensive basin modeling and seismic, well‐log and other type of data is suggested. The approach takes advantage of comprehensive RTM basin modeling to complete an algorithm based on information theory that places basin modeling on a rigorous foundation. Incompleteness in a model can self‐consistently be compensated for by an increase in the amount of observed data used. The method can be used to calibrate the transport, mechanical, or other laws underlying the model. As the procedure is fully automated, the predictions can be continuously updated as new observed data become available. Finally, the procedure makes it possible to augment the model itself as new processes are added in a way that is dictated by the available data. In summary, the automated data/model integration places basin simulation in a novel context of informatics that allows for data to be used to minimize and assess risk in the prediction of reservoir location and characteristics.     

Types of Geochemical Soil Catenas

By analogy with soil catenas, which are groups of related soils differing from one another as a result of variation in relief and drainage, the author suggests the existence of geochemical soil catenas, in which the lateral migration of chemical elements links the related soils of uplands, slopes, and depressions into a geochemical entity. On the basis of the conditions of migration, soils are divided into geochemically autonomous, eluvial soils on uplands and geochemically subordinate soils on slopes (transaccumulative situations) and in depressions (superaqueous situations). In humid regions, geochemical soil catenas are distinguished mainly on the basis of the mobility of iron and aluminum compounds; in arid regions, mostly in terms of the mobility of the sulfates and chlorides of sodium and calcium. Geochemical soil catenas in the periglacial situations of the Antarctic and the Tien Shan and in the humid subarctic situation of northern Scandinavia were investigated in the field. The field data and the available literature are used to construct a typology of the world's principal geochemical soil catenas and their determinant factors.     

Calibration of an Advanced Constitutive Model for Babolsar Sand Accompanied by Liquefaction Analysis

In our research, we apply numerical modeling for prediction of liquefaction of sands during and after dynamic loading. In numerical modeling, to properly simulate the generation, redistribution, and dissipation of excess pore water pressure during and after dynamic loading, it is important to use a suitable constitutive model for soil. In this article, Dafalias and Manzari’s model [2004] (a critical state bounding surface plasticity model) was used to model the behavior of saturated sand due to relatively simple of formulations and a unique set of input parameters for a wide range of initial stress and void ratio. The attention in this article is on Babolsar sand. After calibration model parameters for Babolsar sand, the analysis of liquefaction using the modeling of a centrifuge test and predictions of model was carried out. The results indicate a reasonable performance of the model for prediction of behavior of types of sands. Also, Babolsar sand has more prone to dilatancy than Nevada and Toyoura sands.     

Prehistoric farming in the mfolozi and hluhluwe valleys of Southeast Africa: an archaeo-botanical survey

The Mfolozi and Hluhluwe Valleys of southeastern Africa are representative of a sub-tropical biome and have archaeological evidence for farming settlement spanning more than 1500 years. By collecting information on soils and plant communities within the same sample frame as archaeological data, the relative importance of environmental and anthropomorphic influences can be assessed. It is argued that, although climate and soils have determined the overall distribution of plant communities, human land use has had a considerable effect on the composition of both woodland and grassland. The nature of this interaction between man and environment provides inferential data on prehistoric economies and also aids the formulation of conservation policies in protected areas.     

Neural Network Modeling of Constrained Spatial Interaction Flows: Design, Estimation, and Performance Issues

In this paper a novel modular product unit neural network architecture is presented to model singly constrained spatial interaction flows. The efficacy of the model approach is demonstrated for the origin constrained case of spatial interaction using Austrian interregional telecommunication traffic data. The model requires a global search procedure for parameter estimation, such as the Alopex procedure. A benchmark comparison against the standard origin constrained gravity model and the two–stage neural network approach, suggested by Openshaw (1998), illustrates the superiority of the proposed model in terms of the generalization performance measured by ARV and SRMSE.     

Seismic Vulnerability Assessment of the Urban Building Environment in Nablus,Palestine

ABSTRACT

This article describes a specifically developed framework to produce a seismic physical vulnerability model of residential buildings in Nablus (Palestine) within the European project SASPARM2.0. Based on the structural taxonomy of the territory, two different forms were defined to collect geometrical and structural data of buildings by different stakeholders (citizens and practitioners). This data was then employed to produce fragility curves using the mechanics-based procedure SP-BELA. To estimate seismic risk, the developed fragility model was combined with a hazard curve for the corresponding location. The described procedure is implemented in a WebGIS platform that allows to georeference and assess the surveyed buildings and define retrofitting strategies. Finally, the article carries out a comparison between the fragility curves of buildings in Nablus and the ones calculated for similar building typologies within a UNDP Jordan project aiming at the integrated risk assessment in Wadi Musa and surroundings.     

Establishment of a Time-Varying Modified Kanai-Tajimi Non Stationary Stochastic Model of Seismic Records Based on the S-transform

This article investigates the time-varying characteristics of seismic records. Time-varying amplitude and energy spectrums are defined to reflect the time-frequency dependence, and a general formulation of the S-transform is introduced. The S-transform is tested with various window functions to analyse the Kobe seismic records. The results indicate that using a complex window function with properly adjusted parameters gives favorable outcomes. Analyses of three soil sites show that sites with hard soil feature seismic records with shorter stationary durations, higher frequency centers, and broader frequency bands than other soil sites. The average time-varying spectrums of the seismic records are simulated using a uniform non stationary stochastic model and a time-varying modified non stationary Kanai-Tajimi stochastic model. Empirical formulas are established for the time-varying spectrums of the earthquake records from these sites by nonlinearly fitting stochastic models to the record data. The values of the time-varying spectrum factors for different earthquake intensities and sites agreeing with the Chinese Seismic Code are obtained. Based on these analyses and observations, we propose using the solutions to the stochastic models to simulate non stationary ground motions.     

Rugged Plateaus and Extensive Floodplains — Modelling Landform Evolution in a Northern Australian Catchment

Medium to large natural catchments are often more spatially heterogeneous than small catchments or single landforms. Attempting to model landform evolution of large areas is consequently more complex. This paper demonstrates that modelling landform evolution in medium to large catchments can be improved by calibrating the model to smaller, more geomorphologically homogenous sub‐catchments. The paper investigates landform evolution in the Ngarradj catchment in the Northern Territory of Australia (a medium scale catchment of approximately 67 km²). The catchment is complex and contains two distinct landform regions; an upland plateau region with highly dissected sandstone and shallow, sandy soils, and a lowlands region with gentle, wooded slopes and floodplains with deep, sandy soils. The SIBERIA landform evolution model is calibrated and applied to the Ngarradj catchment. The complexity of the Ngarradj catchment is incorporated into the modelling by dividing the catchment into three sub‐catchments (Swift Creek (SC), Upper Main (UM) and East Tributary (ET)) which are relatively homogeneous and for which hydrology and sediment transport data are available. A discharge‐area relationship and long‐term, sediment loss rates for the catchment are derived based on an annual series flood frequency analysis of a 20 year runoff record predicted in a previous study. Sediment transport modelling incorporates both suspended and bedload sediment loss. The denudation rates derived using these data are 37, 63 and 77 mm kyr^?1 for the SC, UM and ET sub‐catchments, respectively. Model predictions indicate that the UM sub‐catchment will have the greatest mean erosion. This is balanced by the large amount of deposition that will occur in the upper Ngarradj valley of the UM sub‐catchment. Further deposition occurs on the floodplain of Ngarradj, with the area between the SC and ET/UM (up‐stream) sub‐catchments experiencing a small net accretion of sediment (15 mm kyr^?1).     

COINTEGRATION BETWEEN U.S. WHEAT MARKETS

ABSTRACT. Average monthly price data from twelve hinterland markets and the Houston port price for wheat are studied in a cointegration framework using the Engle-Granger "two-step" procedure and Johansen's maximum likelihood procedure. Out-of-sample forecasts from an error correction model are compared to those from a vector autoregression fit to levels and a univariate autoregression fit to first differences. This comparison suggests that modeling these (cointegrated) data as a levels vector autoregression, rather than as an error-correction process, results in significantly higher error bias, but lower error variance, at long horizons.