5 papers
Global Recovery from Local Data: Interior Nudging for 2D Navier-Stokes equations in a Physical Domain
Rui Fang, Ali Pakzad
In many real-world applications of data assimilation (DA), the strategic placement of observers is crucial for effective and efficient forecasting. Motivated by practical constrain…
Data Assimilation in Large Eddy Simulation: Addressing Model-Observation Mismatch from Navier-Stokes Data
Adam Larios, Ali Pakzad, Nicholas White
In atmospheric and turbulent flow modeling, Large Eddy Simulation (LES) is often used to reduce computational cost, while observational data typically originates from the underlyin…
Statistical Estimates for 2D stochastic Navier-Stokes Equations
Anuj Kumar, Ali Pakzad
The statistical features of homogeneous, isotropic, two-dimensional stochastic turbulence are discussed. We derive some rigorous bounds for the mean value of the bulk energy dissip…
Continuous data assimilation for two-phase flow: analysis and simulations
Yat Tin Chow, Wing Tat Leung, Ali Pakzad
We propose, analyze, and test a novel continuous data assimilation two-phase flow algorithm for reservoir simulation. We show that the solutions of the algorithm, constructed using…
On the zeroth law of turbulence for the stochastically forced Navier-Stokes equations
Yat Tin Chow, Ali Pakzad
We consider three-dimensional stochastically forced Navier-Stokes equations subjected to white-in-time (colored-in-space) forcing in the absence of boundaries. Upper and lower boun…