Monitoring the seasonal variation of the properties of pavement materials is an essential practice to protect pavements from early deterioration. In spring season, the top layers of pavement start to thaw while the bottom layers are still frozen. As a result, the moisture remains contained in the top layers and can not be drained. Consequently, pavement layers experience high strains therefore Spring Load Restrictions (SLR) are applied to protect pavement from early deterioration. As thawing continues to advance throughout the spring season, the pavement starts to recover its strength until pavement reaches its full strength at the end of thawing process. Determination of the application and lifting times of SLR is a challenging issue. An early application, or late lifting, of SLR wastes the opportunity to carry more loads. A late application, or early lifting, of SLR causes damage to the pavement structure and accelerates pavement failure. In winter season, the winter load premium can not be allowed until frost penetration reaches a certain depth. The depth of frost penetration can be either measured in the field. Having a reliable model to predict the depth of frost penetration provides a time and cost effective alternative to field measurements. This paper introduces the analysis conducted to develop a simplified model to predict the frost penetration in Manitoba. This work represents part of an ongoing study which aims to provide better understanding to the seasonal variation of the properties of pavement materials. The climatic and seasonal monitoring data for the Oak Lake test section, which was collected as part of the Long-Term Pavement Performance (LTPP) Program, was utilized for this purpose. The proposed frost penetration model was compared to the Northern Ontario frost penetration model and a good agreement was found between them.
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