Summary
As a physical fact, randomness is an inherent and ineliminable aspect in all physical measurements and engineering production. Hence, all material parameters are subject to stochastic fluctuations. However, highly accurate predictions are key to achieving the goals of resource-efficiency and sustainability in engineering and construction. In this context, randomness in material parameters constitutes a severe problem: if we can experimentally quantify the magnitude of fluctuations of material parameters, how can we numerically include this information to predict fluctuations in the reactions of construction parts or processes?
All existing strategies for the inclusion of stochasticity in engineering design share the drawback of large numerical costs, leading to inefficiencies, e.g., an increase in simulation time by orders of magnitude. This prevents their industrial application and, consequently, stochastic fluctuations are not factored into design. This is compensated for by adding buffers, e.g., overestimated safety factors, oversized wall thickness, or higher maintenance frequencies, all leading to increased economic and environmental costs.
Thus, a step change in engineering design is required to allow the inclusion of stochasticity into material modelling and engineering simulation, while minimising the numerical extra cost. Gen-TSM aims to meet this challenge by developing a novel strategy for efficient stochastic modelling of highly complex problems and creating a computational framework for the automated formulation of stochastic versions of existing material models. My vision is to unlock the currently untapped potential of material modelling and enable computing stochastic behaviour to become the new standard in engineering design. This would revolutionise current state of the art, allowing access to the full information field by including stochasticity into simulations at low computational costs.
All existing strategies for the inclusion of stochasticity in engineering design share the drawback of large numerical costs, leading to inefficiencies, e.g., an increase in simulation time by orders of magnitude. This prevents their industrial application and, consequently, stochastic fluctuations are not factored into design. This is compensated for by adding buffers, e.g., overestimated safety factors, oversized wall thickness, or higher maintenance frequencies, all leading to increased economic and environmental costs.
Thus, a step change in engineering design is required to allow the inclusion of stochasticity into material modelling and engineering simulation, while minimising the numerical extra cost. Gen-TSM aims to meet this challenge by developing a novel strategy for efficient stochastic modelling of highly complex problems and creating a computational framework for the automated formulation of stochastic versions of existing material models. My vision is to unlock the currently untapped potential of material modelling and enable computing stochastic behaviour to become the new standard in engineering design. This would revolutionise current state of the art, allowing access to the full information field by including stochasticity into simulations at low computational costs.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101124463 |
| Start date: | 01-06-2024 |
| End date: | 31-05-2029 |
| Total budget - Public funding: | 1 996 920,00 Euro - 1 996 920,00 Euro |
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Original description
As a physical fact, randomness is an inherent and ineliminable aspect in all physical measurements and engineering production. Hence, all material parameters are subject to stochastic fluctuations. However, highly accurate predictions are key to achieving the goals of resource-efficiency and sustainability in engineering and construction. In this context, randomness in material parameters constitutes a severe problem: if we can experimentally quantify the magnitude of fluctuations of material parameters, how can we numerically include this information to predict fluctuations in the reactions of construction parts or processes?All existing strategies for the inclusion of stochasticity in engineering design share the drawback of large numerical costs, leading to inefficiencies, e.g., an increase in simulation time by orders of magnitude. This prevents their industrial application and, consequently, stochastic fluctuations are not factored into design. This is compensated for by adding buffers, e.g., overestimated safety factors, oversized wall thickness, or higher maintenance frequencies, all leading to increased economic and environmental costs.
Thus, a step change in engineering design is required to allow the inclusion of stochasticity into material modelling and engineering simulation, while minimising the numerical extra cost. Gen-TSM aims to meet this challenge by developing a novel strategy for efficient stochastic modelling of highly complex problems and creating a computational framework for the automated formulation of stochastic versions of existing material models. My vision is to unlock the currently untapped potential of material modelling and enable computing stochastic behaviour to become the new standard in engineering design. This would revolutionise current state of the art, allowing access to the full information field by including stochasticity into simulations at low computational costs.
Status
SIGNEDCall topic
ERC-2023-COGUpdate Date
12-03-2024
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