31 citations · 57 across the 7 of their papers we have counts for
11 papers
Dynamically learning the parameters of a chaotic system using partial observations
Elizabeth Carlson, Joshua Hudson, Adam Larios +3
Motivated by recent progress in data assimilation, we develop an algorithm to dynamically learn the parameters of a chaotic system from partial observations. Under reasonable assum…
Sensitivity Analysis for the 2D Navier-Stokes Equations with Applications to Continuous Data Assimilation
Adam Larios, Elizabeth Carlson
We rigorously prove the well-posedness of the formal sensitivity equations with respect to the Reynolds number corresponding to the 2D incompressible Navier-Stokes equations. Moreo…
Continuous data assimilation applied to a velocity-vorticity formulation of the 2D Navier-Stokes equations
Matthew Gardner, Adam Larios, Leo G. Rebholz +2
We study a continuous data assimilation (CDA) algorithm for a velocity-vorticity formulation of the 2D Navier-Stokes equations in two cases: nudging applied to the velocity and vor…
Parameter Recovery and Sensitivity Analysis for the 2D Navier-Stokes Equations Via Continuous Data Assimilation
Elizabeth Carlson, Joshua Hudson, Adam Larios
We study a continuous data assimilation algorithm proposed by Azouani, Olson, and Titi (AOT) in the context of an unknown Reynolds number. We determine the large-time error between…
Continuous Data Assimilation with a Moving Cluster of Data Points for a Reaction Diffusion Equation: A Computational Study
Adam Larios, Collin Victor
Data assimilation is a technique for increasing the accuracy of simulations of solutions to partial differential equations by incorporating observable data into the solution as tim…
Approximate continuous data assimilation of the 2D Navier-Stokes equations via the Voigt-regularization with observable data
Adam Larios, Yuan Pei
We propose a data assimilation algorithm for the 2D Navier-Stokes equations, based on the Azouani, Olson, and Titi (AOT) algorithm, but applied to the 2D Navier-Stokes-Voigt equati…