Developing Slope Asset Management Tools Considering Geotechnical and Remote Sensing Data for Transportation Infrastructure

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Transportation infrastructure is a critical strategic asset as defined by the Government of Canada. In the proposed program, we are focused on the management of railway and highway corridors exposed to potential hazards originating from rock slopes - termed Geotechnical Assets (GA). Geotechnical Asset Management (GAM) is increasingly being adopted by managers of transportation corridors, with development in the evaluation of asphalt, bridges and culverts. Design techniques and methods for testing the condition of these assets are established, for example the Pavement Condition Index demonstrates a rapid decline in quality if maintenance is not done at a critical time. Applying these concepts to GAs is the emerging research topic in this field. Geotechnical Assets, in particular slopes, are less well understood due to the inherent variability in the materials which are largely hidden from view within the slope, and the lack of specific and reliable understanding of the influence of repeated events that trigger failures, leading to progressive deterioration in the material strength and slope condition. GAM is required to understand present condition and risk, prioritize maintenance and improve the life cycle. The potential for cut slope failure is often estimated using qualitative rating systems: where higher failure probability slopes are identified, detailed work is done to assess the hazard in more detail and to devise mitigation strategies, which may include monitoring, warning, protection or support. The consequence of failing to detect impending failure or  implement effective solutions, is the impact of unexpected and damaging landslide events on the transportation corridor. This may lead to loss of infrastructure capacity while emergency repairs are made, damage that extends beyond the infrastructure, financial loss, injury and in extreme cases, fatalities. In this project, we will define rock slope "types", representative of expected change in behaviour and condition over time. The condition curves defined will guide evaluation and mitigation of the GA slopes, in order to reduce unexpected failures, optimise expenditures and guide risk based decision making. Using the remote monitoring techniques we have developed using LiDAR and photogrammetry will permit us to evaluate infrastructure slope behaviour in a variety of geological and slope management settings, considering our ongoing work on rock slopes in Canada and monitoring data collected from slopes worldwide. From this analysis, we will also define the factors that influence rock slope condition curves, including engineering mitigation works. Using game engine physics based simulation tools, calibrated on rock slopes, we will assess how well the condition curves represent future slope behaviour. This should lead to a change in policy that encourages agencies to take a forward looking approach to asset management.  The proposed program will train 1PDF, 3PhD, 5MASc and 4UG students.