Covering the Northern part of the Province, Ontario’s low-volume roads provide a link from remote resource areas to markets. Thus, preserving this transportation asset from the two main sources of pavement deterioration, namely traffic loading and the environment is extremely critical to the movement of goods and to the economy. In particular, Northern Ontario’s secondary highways are challenged by a combination of heavy, low frequency traffic loading and a high number of freeze-thaw cycles for which most of these highways have not been structurally designed. Therefore they experience environmental damage and premature traffic-induced deterioration. To cope with this issue, the Ontario Ministry of Transportation places Spring Load Restrictions (SLR) every year during spring-thaw. For economic reasons, the duration of SLRs is usually fixed in advance and is not applied proactively or according to conditions in a particular year. This rigidity in the schedule needs to be addressed, as it can translate into economic losses either when the payload is unnecessarily restricted or when pavement deterioration occurs. While the traditional approaches are usually qualitative and rely on visual observations, engineering judgment and historical records to make SLR decisions, the latest approaches resort to climatic and deflection data to better assess the bearing capacity of the roadway. The main intent of this research was to examine how the use of a predictor for frost formation and thawing could improve the scheduling of load restrictions by tracking the frost-strengthening and thaw-weakening of the pavement structure. Based on field data captured in Northern Ontario, and on a preliminary analysis that found good correlation between frost thickness in the roadway and Road Weather Information Systems (RWIS) variables, more advanced frost and thaw predictors were developed as part of this research and are presented herein. The report outlines how the model was developed, details the calculation algorithms, and proposes an empirical methodology for a systematic site-specific calibration. This research also involved several experimental and numerical tools, including the use of a Portable Falling Weight Deflectometer (PFWD) to estimate pavement strength during spring thaw, and the use of the Mechanistic-Empirical Pavement Design Guide (MEPDG) software to simulate the impact of SLR on the performance of typical Northern Ontario low volume roads.

Covering the Northern part of the Province, Ontario’s low-volume roads provide a link from remote resource areas to markets. Thus, preserving this transportation asset from the two main sources of pavement deterioration, namely traffic loading and the environment is extremely critical to the movement of goods and to the economy. In particular, Northern Ontario’s secondary highways are challenged by a combination of heavy, low frequency traffic loading and a high number of freeze-thaw cycles for which most of these highways have not been structurally designed. Therefore they experience environmental damage and premature traffic-induced deterioration. To cope with this issue, the Ontario Ministry of Transportation places Spring Load Restrictions (SLR) every year during spring-thaw. For economic reasons, the duration of SLRs is usually fixed in advance and is not applied proactively or according to conditions in a particular year. This rigidity in the schedule needs to be addressed, as it can translate into economic losses either when the payload is unnecessarily restricted or when pavement deterioration occurs. While the traditional approaches are usually qualitative and rely on visual observations, engineering judgment and historical records to make SLR decisions, the latest approaches resort to climatic and deflection data to better assess the bearing capacity of the roadway. The main intent of this research was to examine how the use of a predictor for frost formation and thawing could improve the scheduling of load restrictions by tracking the frost-strengthening and thaw-weakening of the pavement structure. Based on field data captured in Northern Ontario, and on a preliminary analysis that found good correlation between frost thickness in the roadway and Road Weather Information Systems (RWIS) variables, more advanced frost and thaw predictors were developed as part of this research and are presented herein. The report outlines how the model was developed, details the calculation algorithms, and proposes an empirical methodology for a systematic site-specific calibration. This research also involved several experimental and numerical tools, including the use of a Portable Falling Weight Deflectometer (PFWD) to estimate pavement strength during spring thaw, and the use of the Mechanistic-Empirical Pavement Design Guide (MEPDG) software to simulate the impact of SLR on the performance of typical Northern Ontario low volume roads.

Pavements in Canada that are built on top of frost susceptible soil experience loss of support in early spring as the frozen structure begins thawing. To minimize pavement damage, low- volume roads rely on Spring Load Restrictions (SLR), since building these roads to withstand spring thaw is usually not feasible. However, implementing SLR increases operational costs to commercial transporters and impacts local economies. The Ministry of Transportation Ontario (MTO) is routinely faced with requests from the truck industry to lift restrictions on certain roads, and questioning from municipalities that seek understanding on the needs for SLR in their roads. To help answer these questions, a comprehensive study was performed at 15 Seasonal Load Adjustment (SLA) stations across Ontario. The data collected included Falling Weight Deflectometer (FWD) testing, borehole investigation, climatic data, traffic volumes, and pavement rehabilitation data. A backcalculation using the FWD data estimated pavement structural capacity and remaining service life for each SLA for different dates throughout spring, followed by a life cycle analysis using the rehabilitation data. The SLAs were divided in three groups of similar pavement support conditions based on the service life analysis results. Results indicate that none of Group 1 SLAs need load restrictions, with the calculated remaining service life being greater than 25 years for all test dates. Within Group 2, pavement recovery throughout spring suggests that SLR could extend service life, although generally not necessary for the intended life cycle. Results indicate most SLAs in Group 2 achieving a full life cycle from the last rehabilitation activities for estimates based on early spring parameters, suggesting that these roads were likely designed with spring conditions accounted for. For Group 3, the lack of structural support and low service life values indicate the need for strict load restrictions to avoid excessive damage and maintain serviceability. Pavements with high-quality subgrades, granular structures and non-frost susceptible materials, thick asphalt layers and major rehabilitation activities were found to generally perform well for spring conditions. However, with several site-specific conditions, an overall recommendation for implementation of SLR cannot be generalized based on the pavement structure and subgrade soil type alone. The structural condition and thawing behaviour of individual sites must be thoroughly understood before a decision is made, as investigation might indicate that some roads can withstand full traffic year-round and would not need SLR, while others might need more rigorous restrictions. In addition to the service life analysis, approximately 600 lane km of deflection data was collected using a Multi-Speed Deflectometer in Southern Ontario. Recommendations were made for potential applications of the equipment as a network screening device, able to identify weak road sections in a time and cost-effective manner prior to a detailed investigation using FWD; and for regular monitoring of road conditions at a network level, including the monitoring of seasonal variations. / Thesis / Master of Applied Science (MASc)