Abstract

Aircraft emission targets worldwide and their climatic effects have put pressure in government agencies, aircraft manufacturers and airlines to reduce water vapour, carbon dioxide ([...]

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Computational modeling has become a powerful tool in biomedical engineering thanks to its potential to simulate coupled systems. However, real parameters are usually not accurately known, and variability is inherent in living organisms. To cope with this, probabilistic tools, statistical [...]

Abstract

Sampling approaches for uncertainty quantification for real-world engineering problems are associated with large computational time and cost. This cost comes from the expensive deterministic simulation. Usage of surrogate models is a common way to overcome this issue in engineering [...]

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A variety of wildfire models are currently used for prescribed fire management, fire behaviour studies and decision support during wildfire emergencies, among other applications. All these applications are based on predictive analysis, and therefore require careful estimation of aleatoric [...]

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The availability of machine learning techniques opens up possibilities in different fields of civil engineering. Their application in conjunction with numerical simulations overcomes the limitations in traditional approaches and pave the road for some new horizons. This communication [...]

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In this paper, we introduce a bi-fidelity stochastic collocation (SC) method for the linear transport equation with diffusive scaling and high-dimensional random inputs characterized by random variables. For the high-fidelity linear transport model, the asymptotic-preserving Discontinuous [...]

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In this study, we would like to evaluate and improve the performance of Wall-Modeled LargeEddy Simulation (WMLES) on the modeling of a pipe flow for which Direct Numerical Simulation (DNS) data is available [1] and considered as a reference for further comparisons. Models used in [...]

Abstract

High-fidelity scale-resolving simulations of turbulent flows can be prohibitively expensive, especially at high Reynolds numbers. Therefore, multifidelity models (MFM) can be highly relevant for constructing predictive models for flow quantities of interest (QoIs), uncertainty [...]

Abstract

All engineering problems consider uncertainties. These range from small production uncertainties to large-scale uncertainties coming from outside, such as variable wind speed or sunlight. Currently, modern methods for uncertainty propagation have large difficulties with estimation [...]