55 citations · 179 across the 17 of their papers we have counts for
18 papers
AI Meets Turbulence Modeling: Complex Systems Perspective
Sharath S. Girimaji
Despite widespread enthusiasm, applying artificial intelligence and machine learning (AI/ML) to turbulence modeling has yielded only modest progress, primarily due to a lack of sit…
Coherence as Thermodynamic Organization: Toward a Non-Equilibrium Turbulence Theory
Sharath S. Girimaji
Since the foundational studies in the late nineteenth century, fluid turbulence has stood as a profound, unsolved challenge in classical physics. Much of this enduring difficulty s…
Turbulence closure modeling with machine learning approaches: A perspective
Sharath S. Girimaji
Turbulence closure modeling using machine learning is at an early crossroads. The extraordinary success of machine learning (ML) in a variety of challenging fields has given rise t…
Data-driven model for Lagrangian evolution of velocity gradients in incompressible turbulent flows
Rishita Das, Sharath S. Girimaji
Velocity gradient tensor, , in a turbulence flow field is modeled by separating the treatment of intermittent magnitude ($A = \sqrt{A_{ij}A_…
Prandtl number effects on the hydrodynamic stability of compressible boundary layers: flow-thermodynamic interactions
Bajrang Sharma, Sharath S. Girimaji
Hydrodynamic stability of compressible boundary layers is strongly influenced by Mach number (), Prandtl number () and thermal wall boundary condition. These effects manifes…
Modeling and Simulation of Transitional Rayleigh-Taylor Flow with Partially-Averaged Navier-Stokes Equations
Filipe S. Pereira, Fernando F. Grinstein, Daniel M. Israel +2
The partially-averaged Navier-Stokes (PANS) equations are used to predict the variable-density Rayleigh-Taylor (RT) flow at Atwood number 0.5 and maximum Reynolds number . Thi…
Partially-Averaged Navier-Stokes Simulations of Turbulence Within a High-Order Flux Reconstruction Framework
Tarik Dzanic, Sharath Girimaji, Freddie Witherden
High-order methods and hybrid turbulence models have independently shown promise as means of decreasing the computational cost of scale-resolving simulations. The objective of this…
Partially-Averaged Navier-Stokes Closure Modeling for Variable-Density Turbulent Flow
F. S. Pereira, F. F. Grinstein, D. M. Israel +2
This work extends the framework of the partially-averaged Navier-Stokes (PANS) equations to variable-density flow, \text{i.e.}, multi-material and/or compressible mixing problems w…
Turbulence closure modeling with data-driven techniques: Investigation of generalizable deep neural networks
Salar Taghizadeh, Freddie Witherden, Yassin Hassan +1
Generalizability of machine-learning (ML) based turbulence closures to accurately predict unseen practical flows remains an important challenge. At the Reynolds-averaged Navier-Sto…
Local vortex line topology and geometry in turbulence
Bajrang Sharma, Rishita Das, Sharath S. Girimaji
The local streamline topology classification method of Chong et al. (1990) is adapted and extended to describe the geometry of infinitesimal vortex lines. Direct numerical simulati…
Detailed derivation of scale-Space Energy Density Transport Equation for Compressible Inhomogeneous Turbulent Flows
S. Arun, A. Sameen, Balaji Srinivasan +1
Scale-space energy density function, , is defined as the derivative of the two-point velocity correlation. The function E describes the turbulent kinetic…
Turbulence closure modeling with data-driven techniques: physical compatibility and consistency considerations
Salar Taghizadeh, Freddie D. Witherden, Sharath S. Girimaji
A recent thrust in turbulence closure modeling research is to incorporate machine learning (ML) elements, such as neural networks, for the purpose of enhancing the predictive capab…
Characterization of velocity-gradient dynamics in incompressible turbulence using local streamline geometry
Rishita Das, Sharath S. Girimaji
This study develops a comprehensive description of local streamline geometry and uses the resulting shape features to characterize velocity gradient () dynamics. The local…
Revisiting turbulence small-scale behavior using velocity gradient triple decomposition
Rishita Das, Sharath S. Girimaji
Turbulence small-scale behavior has been commonly investigated in literature by decomposing the velocity-gradient tensor () into the symmetric strain-rate () and an…
Challenges in Modelling and Simulation of Turbulent Flows with Spatially-Developing Coherent Structures
F. S. Pereira, L. Eca, G. Vaz +1
The objective of this work is to investigate the challenges encountered in Scale-Resolving Simulations (SRS's) of turbulent wake flows driven by spatially-developing coherent struc…
Manufactured Turbulence with Langevin equations
Aashwin Mishra, Sharath Girimaji
By definition, Manufactured turbulence(MT) is purported to mimic physical turbulence rather than model it. The MT equations are constrained to be simple to solve and provide an ine…
'Proxy-equation' paradigm - A novel strategy for massively-parallel asynchronous computations
Ankita Mittal, Sharath Girimaji
Massively parallel simulations of transport equation systems call for a paradigm change in algorithm development to achieve efficient scalability. Traditional approaches require ti…
Advanced quasi-steady state approximation for chemical kinetics
Sharath Girimaji, Ashraf Ibrahim
Computational feasibility of turbulent reacting flows hinges on the reduction of large chemical kinetics systems to smaller more manageable reaction sets. Recently, several sophist…