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Calibration of a Freeze-Thaw Prediction Model for Spring Load Restriction Timing in Northern New England

机译:校准新英格兰北部春载限制正时冻结预测模型

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A major problem with low-volume roads located in seasonal frost areas is their susceptibility to damage from trafficking during spring thaw. Therefore, seasonal load restriction (SLR) policies that limit the axle loads of heavy trucks during the spring thaw period have been implemented in many countries in an effort to minimize costly roadway damage. Several agencies have been addressing the question of when to place and remove SLRs and have expressed the need for a prediction model to aid them in the process of posting roads. Models are available which predict the depth of frost and thaw penetration based upon air freezing and thawing indices, requiring only air temperature data for input. Various forms of these models have been used by transportation agencies in the United States and Canada. When using any prediction model, a key element is model validation and calibration for local conditions. The purpose of the research described herein was to calibrate a freeze-thaw index model for use in SLR timing in northern New England. Atmospheric weather data and measured subsurface temperature data obtained from nine field test sites in New Hampshire over a period of three years were used in this analysis. Frost and thaw coefficients for the model were calibrated on a site-specific basis. Results suggest that frost-thaw patterns were reasonably estimated at most of the nine test sites using this model, although the model tended to be too conservative in estimating end-of-thaw dates, with estimated end-of-thaw dates falling after measured dates in many instances.
机译:位于季节性霜冻区域的低批量道路的一个主要问题是他们对春季解冻过程中贩运损坏的敏感性。因此,在许多国家的春季解冻期间限制了重型卡车轴荷载的季节性负荷限制(SLR)政策,以尽量减少昂贵的道路损坏。若干机构一直在解决何时放置和删除SLR的问题,并表示需要预测模型,以帮助他们在发布道路的过程中。可提供型号,其基于空气冻结和解冻指数预测霜冻和解冻渗透的深度,需要仅需要输入空气温度数据。这些模型的各种形式已被美国和加拿大的运输机构使用。使用任何预测模型时,密钥元素是用于本地条件的模型验证和校准。本文所述的研究目的是校准新英格兰北部的SLR计时的冻融指数模型。在该分析中使用了从新汉普尔郡的九个田间测试场所获得的大气天气数据和测量的地下温度数据。模型的霜冻和解冻系数在特定于特的基础上校准。结果表明,使用该模型在九个测试站点中的大多数霜冻模式是合理估计的,尽管模型在估计解冻结束日期时往往过于保守,但估计估计在测量日期后落下的尾声日期在许多情况下。

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