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Hybrid Autoencoder/Galerkin Approach for Nonlinear Reduced Order Modelling
This paper presents a novel nonlinear Reduced Order Model (ROM) that combines Proper Orthogonal Decomposition (POD) with deep learning …
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Sensitivity analysis for incompressible Navier--Stokes equations with uncertain viscosity using polynomial chaos method
We present a stability estimate for the sensitivity of the incompressible Navier–Stokes equations under uncertainty in model parameters …
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Stability of a continuous/discrete sensitivity model for the Navier–Stokes equations
This work presents a comprehensive framework for the sensitivity analysis of the Navier–Stokes equations, with an emphasis on the …
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Sensitivity analysis for a thermohydrodynamic model: uncertainty analysis and parameter estimation
This paper proposes an efficient computational strategy to deal with uncertainty propagation problems for the Navier–Stokes equations …
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Sensitivity equation method for the Navier–Stokes equations applied to uncertainty propagation
This works deals with sensitivity analysis for the Navier–Stokes equations. The aim is to provide an estimate of the variance of the …
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A modified sensitivity equation method for Euler equations in presence of shocks
Sensitivity analysis (SA) is the study of how the output of a mathematical model is affected by changes in the inputs. SA is widely …
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Sensitivity analysis and numerical diffusion effects for hyperbolic PDE systems with discontinuous solutions. The case of barotropic Euler equations in Lagrangian coordinates
Sensitivity analysis (SA) is the study of how the output of a mathematical model is affected by changes in the inputs. SA is widely …
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Optimization of running strategies according to the physiological parameters for a two-runner model
In order to describe the velocity and the anaerobic energy of two runners competing against each other for middle-distance races, we …
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