The determination of frost penetration is one of the main requirements in considering environmental effects in pavement design in cold regions. At the present time, the frost depth of pavements in Sweden is estimated computationally using computer software which approximates the heat equation by finite difference. Due to the geographical positioning of Sweden, a wide range of air freezing index and frost penetration depths were observed with lower values in the south and higher values in the north. This paper introduces a simplified design chart which is obtained by empirically correlating the air freezing index estimated from temperature measurements by 44 local meteorological stations to the maximum frost penetration depth obtained by 49 RWIS Road Weather Information Station data. The results are classified depending on their location and the climatic zones defined by the Swedish pavement design codes. Nonlinear prediction intervals are implemented to provide a range of possible frost penetration depths since local site conditions are not taken into account. Further research is required to consider local on-site effects such as frost susceptibility of pavement materials, the thermal conductivity of layers, access to water and snow covering.

Longer Heavier Vehicles provide an improvement in energy efficiency and environmental performance compared to traditional Heavy-Duty Vehicles. In Sweden, the maximum permissible vehicle gross weight has been increased from ∼64 to ∼74 tonnes without increasing the axle load limits. The consequence of this is investigated in this study. Response from two instrumented thin flexible pavements subjected to loading from three types of heavy vehicles (∼64, ∼68 and ∼74 tonnes) has been measured and the recordings were compared with numerical calculations based on 2D multilayer elastic calculations. Pavement damage contribution by the three vehicles was thereafter investigated. As long as the number of axles is increased to compensate for the increased vehicle loading and dual wheels are used, ∼74 tonnes vehicle are not more aggressive to the two thin pavement structures compared to the lighter vehicles with fewer axles but higher average axle loads and tyre pressure.

The seasonal variations of the climatic factors such as temperature, moisture, and freeze-thaw cycles are known to influence the material properties and structural behavior of flexible pavement structures. Mechanistic models are required to predict the behavior of the structure throughout the entire year including the winter frost and spring thaw periods. In this study, the mechanical response of an instrumented flexible pavement structure located in the north of Sweden has been investigated at four different times during a year under loading by falling weight deflectometer and three different long heavy vehicles (~64, ~68 and ~74 ton). The mechanical response values recorded by the sensors embedded in the structure have been compared to the numerical model values obtained by 2D multilayer elastic calculations. It is shown that multilayer elastic theory provides a reasonable prediction of the mechanical behavior on the condition that the stiffness of the asphalt concrete is adjusted according to the temperature variations of the layer and the stiffness of the unbound granular layers is adjusted according to moisture content levels.

Long Heavy Vehicles (LHV) are considered more efficient and environmentally friendly transportation of goods compared to conventional trucks. Thus, the maximum allowable gross vehicle weight (GVW) in Sweden was increased on part of the road network from 64 to 74 tons in 2018 by increasing the vehicles' length and the number of axle groups per vehicle but not the axle load limits. This change in loading conditions is expected to lead to changes in the structural response and degradation rate of thin pavements on the low-volume road network. To improve our understanding of thin pavements behaviour exposed to multiple axle loadings two thin pavement structures located in the north of Sweden were instrumented with road response and climate sensors. Four measurement campaigns were carried out within one year by in-situ stress and strain measurements from the built-in sensors as LHV passes over at normal speed. The recorded response was compared with numerical calculations based on multilayer elastic theory (MLET). Values of stresses and strains showed a generally good agreement with high values of coefficient of determination R-2 during different seasons when the asphalt stiffness values were adjusted based on temperature and granular layer stiffness values based on moisture.

An accurate temperature prediction tool is an important part of any mechanistic-empirical (M-E) pavement design and performance prediction method. In this paper, a one-dimensional finite control volume (FCV) model is introduced that predicts the temperature within a pavement structure as a function of time and depth. The main input data required for the model are continuous time series of air temperature for conductive heat transfer, solar radiation for radiative heat transfer, and wind speed for convective heat transfer. The heat balance equation for each control volume of the FCV model is solved using an implicit scheme. To validate the numerical model, comparisons were made to measured temperature data from four test sections in Sweden located in regions with different climatic conditions. A good agreement was obtained between the calculated and measured temperature values within the asphalt layer, and temperature in the granular layers with the values of the coefficient of determination R2 ranging from 0.866 to 0.979. The model is therefore suitable to be implemented as a pavement temperature prediction tool in M-E design.