A comparative study of concentrated plasticity models in dynamic analysis of building structures

Concentrated plasticity (CP) models are frequently used in static and dynamic building analysis and have been implemented in available commercial software. This investigation deals with three different CP‐models, a simplified macroelement model (SEM) for a complete building story, a frame element with elasto‐plastic interaction hinges (PH), and a frame element with fiber hinges (FB). The objectives of this work are to evaluate the quality of the earthquake responses predicted by these models and to identify important aspects of their implementation and limitations for their use in dynamic analysis. The three elements are tested in a single‐story asymmetric plan building and in a three‐story steel building. Results show that base shear and global response values are usually computed with better accuracy than interstory deformations and local responses. Besides, the main limitation of elasto‐plastic CP models is to control the displacement offsets that result from perfect elasto‐plastic behavior. On the other hand, calibration of the SEM‐model shows that global responses in steel structures may be computed within 20% error in the mean at a computational cost two orders of magnitude smaller than that of the other CP elements considered. However, the three element models considered lead to increasing levels of accuracy in the dynamic response and their use depends on the refinement of the analysis performed. Copyright © 2005 John Wiley & Sons, Ltd.     

Incorporating Spatial Dependence in Predictive Vegetation Models: Residual Interpolation Methods*

Predictive vegetation modeling can be used statistically to relate the distribution of vegetation across a landscape as a function of important environmental variables. Often these models are developed without considering the spatial pattern that is inherent in biogeographical data, resulting from either biotic processes or missing or misspecified environmental variables. Including spatial dependence explicitly in a predictive model can be an efficient way to improve model accuracy with the available data. In this study, model residuals were interpolated and added to model predictions, and the resulting prediction accuracies were assessed. Adding kriged residuals improved model accuracy more often than adding simulated residuals, although some alliances showed no improvement or worse accuracy when residuals were added. In general, the prediction accuracies that were not increased by adding kriged residuals were either rare in the sample or had high nonspatial model accuracy. Regression interpolation methods can be an important addition to current tools used in predictive vegetation models as they allow observations that are predicted well by environmental variables to be left alone, while adjusting over‐ and underpredicted observations based on local factors.     

Analysis of pressuremeter geometry effects in clay using critical state models

The conventional interpretation methods of pressuremeter testing effectively approximate pressuremeter membranes as infinitely long. As a result, the effects of the two‐dimensional geometry of pressuremeters are ignored, leading to an overestimation of soil shear strength by pressuremeter testing, as demonstrated in several previous studies. This paper presents results of a numerical study of two‐dimensional geometry effects on self‐boring pressuremeter tests in undrained clay. The results are obtained using critical state soil models with an effective stress formulation. This is in contrast to most (if not all) existing studies on pressuremeter geometry effects, which were based on perfectly plastic soil models (e.g. Yu (Cavity expansion theory and its application to the analysis of pressuremeters. DPhil Thesis, The University of Oxford, 1990), Yeung and Carter (Proc. 3rd Int. Symp. on Pressuremeters, 1990), and Houlsby and Carter (Géotechnique, 1993; 43 (4):567–576)). The present study suggests that the overestimation of soil strength due to the neglect of finite pressuremeter length is significantly affected by the soil model used in the calculations. It is found that for clays with a high overconsolidation ratio (OCR) the strength overestimation predicted using critical state soil models could be considerably smaller than that predicted using perfectly plastic soil models. The main conclusion of this numerical study is that care must be exercised before directly applying any numerically determined pressuremeter geometry correction factors in practice. Copyright © 2005 John Wiley & Sons, Ltd.     

Statistical and geostatistical features of streambed hydraulic conductivities in the Platte River, Nebraska

This paper presents streambed hydraulic conductivities of the Platte River from south-central to eastern Nebraska. The hydraulic conductivities were determined from river channels using permeameter tests. The vertical hydraulic conductivities (K _v ) from seven test sites along this river in south-central Nebraska belong to one statistical population. Its mean value is 40.2 m/d. However, the vertical hydraulic conductivities along four transects of the Ashland test site in eastern Nebraska have lower mean values, are statistically different from the K _v values in south-central Nebraska, and belong to two different populations with mean values of 20.7 and 9.1 m/d, respectively. Finer sediments carried from the Loup River and Elkhorn River watersheds to the eastern reach of the Platte River lowers the vertical hydraulic conductivity of the streambed. Correlation coefficients between water depth and K _v values along a test transect indicates a positive correlation – a larger K _v usually occurs in the part of channel with deeper water. Experimental variograms derived from the vertical hydraulic conductivities for several transects across the channels of the Platte River show periodicity of spatial correlation, which likely result from periodic variation of water depth across the channels. The sandy to gravelly streambed contains very local silt and clay layers; spatially continuous low-permeability streambed was not observed in the river channels. The horizontal hydraulic conductivities were larger than the vertical hydraulic conductivities for the same test locations.     

黄土区人类活动影响下的 产汇流模拟研究

日益频繁的人类活动改变了流域下垫面条件,对流域产汇流产生很大的影响。本文以黄河中游典型支流岔巴沟为研究区域,提出利用基于DEM的分布式水文模拟技术,探讨流域人类活动过程中的产汇流模拟,避免了经验公式的概化和由此引起的局限。模拟的结果证实了该方法的可行性。采用网格滞蓄的方法可以在子网格上体现人类活动引起的下垫面的变化及其对产汇流的影响,反映各个时期的产汇流条件,对降雨做出合理响应。     

Critical rainfall statistics for predicting watershed flood responses: rethinking the design storm concept

Recent advances have been made to modernize estimates of probable precipitation scenarios; however, researchers and engineers often continue to assume that rainfall events can be described by a small set of event statistics, typically average intensity and event duration. Given the easy availability of precipitation data and advances in desk‐top computational tools, we suggest that it is time to rethink the ‘design storm’ concept. Design storms should include more holistic characteristics of flood‐inducing rain events, which, in addition to describing specific hydrologic responses, may also be watershed or regionally specific. We present a sensitivity analysis of nine precipitation event statistics from observed precipitation events within a 60‐year record for Tompkins County, NY, USA. We perform a two‐sample Kolmogorov–Smirnov (KS) test to objectively identify precipitation event statistics of importance for two related hydrologic responses: (1) peak outflow from the Six Mile Creek watershed and (2) peak depth within the reservoir behind the Six Mile Creek Dam. We identify the total precipitation depth, peak hourly intensity, average intensity, event duration, interevent duration, and several statistics defining the temporal distribution of precipitation events to be important rainfall statistics to consider for predicting the watershed flood responses. We found that the two hydrologic responses had different sets of statistically significant parameters. We demonstrate through a stochastic precipitation generation analysis the effects of starting from a constrained parameter set (intensity and duration) when predicting hydrologic responses as opposed to utilizing an expanded suite of rainfall statistics. In particular, we note that the reduced precipitation parameter set may underestimate the probability of high stream flows and therefore underestimate flood hazard. Copyright © 2016 John Wiley & Sons, Ltd.     

Spatiotemporal estimation of snow depth using point data from snow stakes,digital terrain models,and satellite data

Snow availability in Alpine catchments plays an important role in water resources management. In this paper, we propose a method for an optimal estimation of snow depth (areal extension and thickness) in Alpine systems from point data and satellite observations by using significant explanatory variables deduced from a digital terrain model. It is intended to be a parsimonious approach that may complement physical‐based methodologies. Different techniques (multiple regression, multicriteria analysis, and kriging) are integrated to address the following issues: We identify the explanatory variables that could be helpful on the basis of a critical review of the scientific literature. We study the relationship between ground observations and explanatory variables using a systematic procedure for a complete multiple regression analysis. Multiple regression models are calibrated combining all suggested model structures and explanatory variables. We also propose an evaluation of the models (using indices to analyze the goodness of fit) and select the best approaches (models and variables) on the basis of multicriteria analysis. Estimation of the snow depth is performed with the selected regression models. The residual estimation is improved by applying kriging in cases with spatial correlation. The final estimate is obtained by combining regression and kriging results, and constraining the snow domain in accordance with satellite data. The method is illustrated using the case study of the Sierra Nevada mountain range (Southern Spain). A cross‐validation experiment has confirmed the efficiency of the proposed procedure. Finally, although it is not the scope of this work, the snow depth is used to asses a first estimation of snow water equivalent resources.