Journal of Cold Regions Engineering

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December 2007

Volume 21, Issue 4, pp. 107-141

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J. Cold Reg. Eng. 21, 107 (2007); http://dx.doi.org/10.1061/(ASCE)0887-381X(2007)21:4(107) (1 page)

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Seasonal Frost Effects on the Soil–Foundation–Structure Interaction System

Zhaohui Joey Yang, M.ASCE, Utpal Dutta, Deju Zhu, Elmer Marx, M.ASCE, and Niren Biswas

J. Cold Reg. Eng. 21, 108 (2007); http://dx.doi.org/10.1061/(ASCE)0887-381X(2007)21:4(108) (13 pages) | Cited 1 time

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This paper presents the results of more than one year’s monitoring efforts and analysis of the effects of environmental variables on the dynamic properties of a selected bridge in Anchorage, Alaska. A seismic monitoring system was installed on the bridge to study these effects. The dynamic properties of the bridge have been identified from the recorded time histories which include ambient noises, traffic-induced vibrations, and small-magnitude earthquakes. Hourly air temperature data from nearby meteorological station during the period of study were collected to estimate the frozen soil depth for modeling purpose. A finite-element model and multiple-input autoregressive model were applied to study the effects of environmental variables on the dynamic properties. The results show that the environmental variables can significantly affect the dynamic properties by modifying the stiffness of the bridge system and the seasonal frost is found to have the dominating effects over air temperature on the bridge dynamic properties in cold regions. The results show that the models explain well the variation of dynamic properties with environmental variables.

Cellular-Automata Model for Dense-Snow Avalanches

F. Barpi, M. Borri-Brunetto, and L. Delli Veneri

J. Cold Reg. Eng. 21, 121 (2007); http://dx.doi.org/10.1061/(ASCE)0887-381X(2007)21:4(121) (20 pages) | Cited 2 times

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This paper introduces a three-dimensional model for simulating dense-snow avalanches, based on the numerical method of cellular automata. This method allows one to study the complex behavior of the avalanche by dividing it into small elements, whose interaction is described by simple laws, obtaining a reduction of the computational power needed to perform a three-dimensional simulation. Similar models by several authors have been used to model rock avalanches, mud and lava flows, and debris avalanches. A peculiar aspect of avalanche dynamics, i.e., the mechanisms of erosion of the snowpack and deposition of material from the avalanche is taken into account in the model. The capability of the proposed approach has been illustrated by modeling three documented avalanches that occurred in Susa Valley (Western Italian Alps). Despite the qualitative observations used for calibration, the proposed method is able to reproduce the correct three-dimensional avalanche path, using a digital terrain model, and the order of magnitude of the avalanche deposit volume.
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J. Cold Reg. Eng. 21, 141 (2007); http://dx.doi.org/10.1061/(ASCE)0887-381X(2007)21:4(141) (1 page)

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