Project description
Expanding quantised fracture mechanics models to predict climate change impact on snow/ice fragilisation
Fracture mechanics theories remain incomplete, limiting the capacity to accurately predict material/structural strength, which is critical in civil and mechanical engineering as well as in material science. The ERC-funded FRAMEGLOW project aims to tackle this challenge from a fundamental engineering science perspective. As such, it will formulate a more thorough fracture mechanics theory, which is quantised/finite. Following its formulation, the theory and related models will be refined drawing from other disciplines, such as tribology and thermodynamics, to model the impacts of climate change on snow/ice avalanche fragilisation. Ultimately FRAMEGLOW aims to advance the fundamental understanding of fracture mechanics, predict avalanches under global warming and potentially avert related tragedies.
Objective
Fracture mechanics theories are still incomplete, and this limits our current ability to predict the strength of materials, which is particularly important in civil and mechanical engineering. FRAMEGLOW aims to address this critical knowledge gap in understanding from a fundamental engineering science perspective, by (i) developing a complete fracture mechanics theory, and (ii) using it to solve a critical global problem, i.e. how climate change/global warming will lead -on different size and time scales- to global ice and snow fragilization, and thus (iii) providing important societal benefits (e.g. dynamic avalanche risk maps), potentially saving human lives. After the formulation of a (more) complete fracture theory, starting from the quantized/finite/discrete fracture mechanics theory proposed by the PI, other disciplines will be coupled for the specific application, namely tribology (to describe the transition imposed by climate change on friction, from dry to wet) and thermodynamics (global warming/temperature effects on material properties). Discrete numerical models, developed by the PI in recent years, are the ideal counterpart (as phase field models) of the complete quantized fracture mechanics theory and will accordingly be extended and used for mutual comparisons and analytically intractable problems. Physics-based machine learning tools and data-driven state of the art “snowpack” code calculations will also be adopted for data analysis and snowpack predictions under climate change. Laboratory or field experiments and observations will also be performed for inputs and comparisons with both analytical and numerical modelling. This will allow to surpass the limitations of current material strength predictions, crucial in our civil and mechanical engineering, and the related ability in predicting ice and especially snow avalanches, hopefully to save human lives
Fields of science (EuroSciVoc)
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CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
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Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
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Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
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Call for proposal
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(opens in new window) ERC-2024-ADG
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38122 Trento
Italy
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