Zobrazeno 1 - 10
of 41
pro vyhledávání: '"Zare, Armin"'
Low-fidelity analytical models of turbine wakes have traditionally been used for wind farm planning, performance evaluation, and demonstrating the utility of advanced control algorithms in increasing the annual energy production. In practice, however
Externí odkaz:
http://arxiv.org/abs/2208.12196
Autor:
Abootorabi, Seyedalireza, Zare, Armin
Recent data-driven efforts have utilized spectral decomposition techniques to uncover the geometric self-similarity of dominant motions in the logarithmic layer, and thereby validate the attached eddy model. In this paper, we evaluate the predictive
Externí odkaz:
http://arxiv.org/abs/2208.11632
Autor:
Hewawaduge, Dhanushki, Zare, Armin
Publikováno v:
Phys. Rev. Fluids 7 (2022) 073901
We adopt an input-output approach to analyze the effect of persistent white-in-time structured stochastic base flow perturbations on the mean-square properties of the linearized Navier-Stokes equations. Such base flow variations enter the linearized
Externí odkaz:
http://arxiv.org/abs/2012.14918
Publikováno v:
J. Fluid Mech. 906 (2021) A7
Both experiments and direct numerical simulations have been used to demonstrate that riblets can reduce turbulent drag by as much as $10\%$, but their systematic design remains an open challenge. In this paper, we develop a model-based framework to q
Externí odkaz:
http://arxiv.org/abs/2002.01671
Model-free reinforcement learning attempts to find an optimal control action for an unknown dynamical system by directly searching over the parameter space of controllers. The convergence behavior and statistical properties of these approaches are of
Externí odkaz:
http://arxiv.org/abs/1912.11899
Publikováno v:
Annu. Rev. Control Robot. Auton. Syst., vol. 3, pp. 195-219, May 2020
Advanced measurement techniques and high performance computing have made large data sets available for a wide range of turbulent flows that arise in engineering applications. Drawing on this abundance of data, dynamical models can be constructed to r
Externí odkaz:
http://arxiv.org/abs/1908.09487
Publikováno v:
Phys. Rev. Fluids 4, 093901 (2019)
We utilize the externally forced linearized Navier-Stokes equations to study the receptivity of pre-transitional boundary layers to persistent sources of stochastic excitation. Stochastic forcing is used to model the effect of free-stream turbulence
Externí odkaz:
http://arxiv.org/abs/1807.07759
Autor:
Zare, Armin, Mohammadi, Hesameddin, Dhingra, Neil K., Georgiou, Tryphon T., Jovanović, Mihailo R.
Several problems in modeling and control of stochastically-driven dynamical systems can be cast as regularized semi-definite programs. We examine two such representative problems and show that they can be formulated in a similar manner. The first, in
Externí odkaz:
http://arxiv.org/abs/1807.01739
Publikováno v:
Phys. Rev. Fluids 4, 023901 (2019)
In this paper, we develop a model based on successive linearization to study interactions between different modes in boundary layer flows. Our method consists of two steps. First, we augment the Blasius boundary layer profile with a disturbance field
Externí odkaz:
http://arxiv.org/abs/1712.02024
Publikováno v:
J. Fluid Mech. (2017), vol. 812, pp. 636-680
In this paper, we address the problem of how to account for second-order statistics of turbulent flows using low-complexity stochastic dynamical models based on the linearized Navier-Stokes equations. The complexity is quantified by the number of deg
Externí odkaz:
http://arxiv.org/abs/1602.05105