An AI-based climate impact assessment framework for infrastructure in northern Canada

The thawing of permafrost, due to climate change or alterations in the ground surface energy balance, poses significant threats to infrastructure and communities in northern Canada. A main step towards the design of resilient infrastructure is to assess the climate threat (exposure) and predict the response of the infrastructure (vulnerability). The stability of permafrost is correlated to the changes in the ground surface temperatures. However, the high-quality projections of surface temperature — an important entity in engineering simulations — are not often available.
In this project, an AI-based geomechanical framework will be developed to predict and assess the integrity of northern infrastructure affected by permafrost degradation. Moreover, life cycle analyses will be performed to compare the advantages and disadvantages of popular mitigation solutions against permafrost thaw.
The results will be processed into several forms, such as standard datasets, geospatial information layers, interactive maps, and an on-demand web service API, to be used by a wide range of stakeholders in various applications, including engineering design and maintenance, agriculture, hydrology, policymaking, and risk management.

Intern: 
Ali Fatolahzadeh Gheysari
Faculty Supervisor: 
Pooneh Maghoul;Ahmed Shalaby
Province: 
Manitoba
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