Uncertainty quantification for systems of conservation laws
Uncertainty quantification through stochastic spectral methods has been recently applied to
several kinds of non-linear stochastic PDEs. In this paper, we introduce a formalism based …
several kinds of non-linear stochastic PDEs. In this paper, we introduce a formalism based …
Topology optimization of continuum structures under uncertainty–a polynomial chaos approach
A computational method for topology optimization in the presence of uncertainty is
proposed. The method combines the spectral stochastic approach for the representation and …
proposed. The method combines the spectral stochastic approach for the representation and …
Uncertainty quantification in stochastic systems using polynomial chaos expansion
In recent years, extensive research has been reported about a method which is called the
generalized polynomial chaos expansion. In contrast to the sampling methods, eg, Monte …
generalized polynomial chaos expansion. In contrast to the sampling methods, eg, Monte …
[HTML][HTML] A stochastic Galerkin lattice Boltzmann method for incompressible fluid flows with uncertainties
Efficient modeling and simulation of uncertainties in computational fluid dynamics (CFD)
remains a crucial challenge. In this paper, we present the first stochastic Galerkin (SG) lattice …
remains a crucial challenge. In this paper, we present the first stochastic Galerkin (SG) lattice …
A combined scheme of parallel-reaction kinetic model and multi-layer artificial neural network model on pyrolysis of Reed Canary
A comprehensive understanding of pyrolysis kinetics is crucial for the design of biomass
pyrolysis. In this study, a combined scheme was proposed for biomass pyrolysis. A kinetic …
pyrolysis. In this study, a combined scheme was proposed for biomass pyrolysis. A kinetic …
A non‐intrusive model reduction approach for polynomial chaos expansion using proper orthogonal decomposition
In this paper, a non‐intrusive stochastic model reduction scheme is developed for
polynomial chaos representation using proper orthogonal decomposition. The main idea is …
polynomial chaos representation using proper orthogonal decomposition. The main idea is …
Robust uncertainty propagation in systems of conservation laws with the entropy closure method
In this paper, we consider hyperbolic systems of conservation laws subject to uncertainties
in the initial conditions and model parameters. In order to solve the underlying uncertain …
in the initial conditions and model parameters. In order to solve the underlying uncertain …
[HTML][HTML] 3D CFD simulation of the interaction between front wheels&brake ducts and optimised five-element F1 race car front wings under regulations
FJ Granados-Ortiz, P Morales-Higueras… - Alexandria engineering …, 2023 - Elsevier
This investigation analyses the 3D performance of two optimal front wing designs according
to the Federation Internationale de l'Automobile 2021 regulations. These regulations imply a …
to the Federation Internationale de l'Automobile 2021 regulations. These regulations imply a …
Multi-scale approach for reliability-based design optimization with metamodel upscaling
For multi-scale materials, the interplay of material and design uncertainties and reliability-
based design optimization is complex and very dependent on the chosen modeling scale …
based design optimization is complex and very dependent on the chosen modeling scale …
A hyperbolicity-preserving stochastic Galerkin approximation for uncertain hyperbolic systems of equations
L Schlachter, F Schneider - Journal of Computational Physics, 2018 - Elsevier
Uncertainty Quantification through stochastic spectral methods is rising in popularity. We
derive a modification of the classical stochastic Galerkin method, that ensures the …
derive a modification of the classical stochastic Galerkin method, that ensures the …