1.5k citations · 3.4k across the 43 of their papers we have counts for
14 papers · 1 filter
Data-driven Balanced Truncation for Predictive Model Order Reduction of Aeroacoustic Response
Elnaz Rezaian, Karthik Duraisamy
Rapid prediction of the aeroacoustic response is a key component in the design of aircraft and turbomachinery. While it is possible to achieve accurate predictions using direct sol…
The Minimal Attached Eddy in Wall Turbulence: Statistical Foundations, Inverse Identification and Influence Kernels
Karthik Duraisamy
Townsend's attached eddy hypothesis models the logarithmic region of high Reynolds number wall turbulence as a random superposition of wall-attached, self-similar eddies whose size…
A unified understanding of scale-resolving simulations and near-wall modeling of turbulent flows using optimal finite element projections
Aniruddhe Pradhan, Karthik Duraisamy
The main objective of this work is to develop a unified framework that can be used as a lens to quantitatively assess and augment a wide range of coarse-grained models of turbulenc…
Entropy-Stable Schemes in the Low-Mach-Number Regime: Flux-Preconditioning, Entropy Breakdowns, and Entropy Transfers
Ayoub Gouasmi, Karthik Duraisamy, Scott M. Murman
Entropy-Stable (ES) schemes, specifically those built from [Tadmor \textit{Math. Comput.} 49 (1987) 91], have been gaining interest over the past decade, especially in the context…
Generalizable Physics-constrained Modeling using Learning and Inference assisted by Feature Space Engineering
Vishal Srivastava, Karthik Duraisamy
This work presents a formalism to improve the predictive accuracy of physical models by learning generalizable augmentations from sparse data. Building on recent advances in data-d…
Sub-grid scale characterization and asymptotic behavior of multi-dimensional upwind schemes for the vorticity transport equations
Daniel Foti, Karthik Duraisamy
We study the sub-grid scale characteristics of a vorticity-transport-based approach for large-eddy simulations. In particular, we consider a multi-dimensional upwind scheme for the…
Perspectives on Machine Learning-augmented Reynolds-averaged and Large Eddy Simulation Models of Turbulence
Karthik Duraisamy
This work presents a review and perspectives on recent developments in the use of machine learning (ML) to augment Reynolds-averaged Navier--Stokes (RANS) and Large Eddy Simulation…
Prediction of Aerodynamic Flow Fields Using Convolutional Neural Networks
Yaser Afshar, Saakaar Bhatnagar, Shaowu Pan +2
An approximation model based on convolutional neural networks (CNNs) is proposed for flow field predictions. The CNN is used to predict the velocity and pressure field in unseen fl…
Modal Analysis of Fluid Flows: Applications and Outlook
Kunihiko Taira, Maziar S. Hemati, Steven L. Brunton +5
We present applications of modal analysis techniques to study, model, and control canonical aerodynamic flows. To illustrate how modal analysis techniques can provide physical insi…
Quad-rotor Flight Simulation in Realistic Atmospheric Conditions
Behdad Davoudi, Ehsan Taheri, Karthik Duraisamy +2
In trajectory planning and control design for unmanned air vehicles, highly simplified models are typically used to represent the vehicle dynamics and the operating environment. Th…
Reduced Order Modeling Framework for Combustor Instabilities Using Truncated Domain Training
Jiayang Xu, Cheng Huang, Karthik Duraisamy
A multi-fidelity framework is established and demonstrated for prediction of combustion instabilities in rocket engines. The major idea is to adapt appropriate fidelity modeling ap…
Turbulence Modeling in the Age of Data
Karthik Duraisamy, Gianluca Iaccarino, Heng Xiao
Data from experiments and direct simulations of turbulence have historically been used to calibrate simple engineering models such as those based on the Reynolds-averaged Navier--S…
Non-Markovian Closure Models for Large Eddy Simulations using the Mori-Zwanzig Formalism
Eric J. Parish, Karthik Duraisamy
This work uses the Mori-Zwanzig (M-Z) formalism, a concept originating from non-equilibrium statistical mechanics, as a basis for the development of coarse-grained models of turbul…
A Dynamic Subgrid Scale Model for Large Eddy Simulations Based on the Mori-Zwanzig Formalism
Eric J. Parish, Karthik Duraisamy
The development of reduced models for complex multiscale problems remains one of the principal challenges in computational physics. The optimal prediction framework of Chorin et al…