Simulation codes often utilize finite-dimensional approximation resulting in numerical error. Some examples include, numerical methods utilizing grids and finite-dimensional basis functions, particle methods using a finite number of particles. These same simulation codes also often contain sources of uncertainty, for example, uncertain parameters and fields associated with the imposition of initial and boundary data,uncertain physical model parameters such as chemical reaction rates, mixture model parameters, material property parameters, etc
The goal of this thesis is to make predictive simulations with Reynolds-Averaged Navier-Stokes (RANS...
Using Computational Fluid Dynamics (CFD) to predict a flow field is an approximation to the exact pr...
Numerical simulation has now become an integral part of engineering design process. Critical design ...
Given input sources of uncertainty, non-intrusive uncertainty propagation methods quantify the uncer...
The present paper addresses the question: ``What are the general classes of uncertainty and error so...
This study investigates and demonstrates a methodology for uncertainty propagation and robust design...
Computational Fluid Dynamics (CFD) is the standard numerical tool used by Fluid Dynamists to estimat...
A classic approach to Computational Fluid Dynamics (CFD) is to perform simulations with a fixed set ...
Engineering practice is nowadays inconceivable without the presence of computational tools. Within t...
International audienceThis article adresses the delicate issue of estimating physical uncertainties ...
The increasing relevance of simulation-based design has created a need to accurately estimate and bi...
In computational fluid dynamics simulations of industrial flows, models based on the Reynolds-averag...
This paper describes the use of formally designed experiments to aid in the error analysis of a comp...
“Mathematics is the language with which God has written the universe. ” Galileo “All models are wron...
When modeling physical systems, several sources of uncertainty are present. For example, variability...
The goal of this thesis is to make predictive simulations with Reynolds-Averaged Navier-Stokes (RANS...
Using Computational Fluid Dynamics (CFD) to predict a flow field is an approximation to the exact pr...
Numerical simulation has now become an integral part of engineering design process. Critical design ...
Given input sources of uncertainty, non-intrusive uncertainty propagation methods quantify the uncer...
The present paper addresses the question: ``What are the general classes of uncertainty and error so...
This study investigates and demonstrates a methodology for uncertainty propagation and robust design...
Computational Fluid Dynamics (CFD) is the standard numerical tool used by Fluid Dynamists to estimat...
A classic approach to Computational Fluid Dynamics (CFD) is to perform simulations with a fixed set ...
Engineering practice is nowadays inconceivable without the presence of computational tools. Within t...
International audienceThis article adresses the delicate issue of estimating physical uncertainties ...
The increasing relevance of simulation-based design has created a need to accurately estimate and bi...
In computational fluid dynamics simulations of industrial flows, models based on the Reynolds-averag...
This paper describes the use of formally designed experiments to aid in the error analysis of a comp...
“Mathematics is the language with which God has written the universe. ” Galileo “All models are wron...
When modeling physical systems, several sources of uncertainty are present. For example, variability...
The goal of this thesis is to make predictive simulations with Reynolds-Averaged Navier-Stokes (RANS...
Using Computational Fluid Dynamics (CFD) to predict a flow field is an approximation to the exact pr...
Numerical simulation has now become an integral part of engineering design process. Critical design ...