## About

151

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Introduction

We delve into the intricate world of turbulent flows through high-fidelity numerical simulations. We also endeavor to craft models that mirror real-world conditions

Additional affiliations

July 2016 - December 2017

September 2012 - June 2016

Education

September 2008 - July 2012

## Publications

Publications (151)

The baseline two-equation Reynolds-averaged Navier–Stokes (RANS) models include fluid density but lack calibration for compressible flows, making them inadequate for high Mach numbers. Various compressibility corrections have been proposed to integrate the van Driest transformation or the semilocal transformation, i.e., a given compressible law of...

Turbulent flow physics regulates the aerodynamic properties of lifting surfaces, the thermodynamic efficiency of vapor power systems, and exchanges of natural and anthropogenic quantities between the atmosphere and ocean, to name just a few applications of contemporary importance. The space-time dynamics of turbulent flows are described via numeric...

The baseline Launder-Spalding k − ε model cannot be integrated to the wall. This paper seeks to incorporate the entire law of the wall into the model while preserving the original k − ε framework structure. Our approach involves modifying the unclosed dissipation terms in the k and ε equations specifically within the wall layer according to direct...

The mean flow in a turbulent boundary layer (TBL) deviates from the canonical law of the wall (LoW) when influenced by a pressure gradient. Consequently, LoW-based near-wall treatments are inadequate for such flows. Chen et al. ( J. Fluid Mech. , vol. 970, 2023, A3) derived a Navier–Stokes-based velocity transformation that accurately describes the...

The conventional k-ε model accurately predicts the slope of the logarithmic law but falls short in estimating its intercept as well as the buffer layer. This limitation can be addressed either through a two-layer formulation or by introducing additional terms. However, both strategies necessitate extra adjustable constants and ad-hoc functions. In...

We report direct numerical simulation (DNS) results of the rough-wall channel, focusing on roughness with high $k_{rms}/k_a$ statistics but small to negative $Sk$ statistics, and we study the implications of this new dataset on rough-wall modelling. Here, $k_{rms}$ is the root-mean-square, $k_a$ is the first order moment of roughness height, and $S...

A primary objective of integral methods, such as the momentum integral method, is to discern the physical processes contributing to skin friction. These methods encompass the momentum, kinetic energy and angular momentum integrals. This paper reformulates existing integrals based on the double-averaged Navier–Stokes equations, and extends their app...

Additive manufacturing (AM) offers many potential advantages to constructing gas turbine components such as allowing for more complex geometry in carefully optimized designs. AM processes, such as direct laser sintering, create roughness with distinct characteristics including periodicity from layers of fused material and varying roughness element...

This study explores the grid convergence properties of wall-modeled large-eddy simulation (WMLES) solutions as the LES grid approaches the direct numerical simulation (DNS) grid. This aspect of WMLES is fundamental but has not been previously investigated or documented. We investigate two types of grid refinements: one where the LES/wall-model matc...

We examine and benchmark the emerging idea of applying the large-eddy simulation (LES) formalism to unconventionally coarse grids where RANS would be considered more appropriate at first glance. We distinguish this idea from very-large-eddy-simulation (VLES) and detached-eddy-simulation (DES), which require switching between RANS and LES formalism....

Turbulent flow physics regulates the aerodynamic properties of lifting surfaces, the thermodynamic efficiency of vapor power systems, and exchanges of natural and anthropogenic quantities between the atmosphere and ocean, to name just a few applications. The dynamics of turbulent flows are described via numerical integration of the non-linear Navie...

Machine-learned augmentations to turbulence models can be advantageous for flows within the training dataset but can often cause harm outside. This lack of generalizability arises because the constants (as well as the functions) in a Reynolds-averaged Navier–Stokes (RANS) model are coupled, and un-constrained re-calibration of these constants (and...

We examine and benchmark the emerging idea of applying the large-eddy simulation (LES) formalism to unconventionally coarse grids where RANS would be considered more appropriate at first glance. We distinguish this idea from very-large-eddy-simulation (VLES) and detached-eddy-simulation (DES), which require switching between RANS and LES formalism....

This study explores the grid convergence properties of wall-modeled large-eddy simulation (WMLES) solutions as the LES grid approaches the direct numerical simulation (DNS) grid. This aspect of WMLES is fundamental but has not been previously investigated or documented. We investigate two types of grid refinements: one where the LES/wall-model matc...

Direct numerical simulations are conducted for temporally evolving stratified wake flows at Reynolds numbers from $10\,000$ to $50\,000$ and Froude numbers from $2$ to 50. Unlike previous studies that obtained statistics from a single realization, we take ensemble averages among 80–100 realizations. Our analysis shows that data from one realization...

This paper explores the similarity of the streamwise velocity fluctuations in turbulent channels. In the analysis, we employ a one-dimensional scalar variant of the proper orthogonal decomposition (POD). This approach naturally motivates the introduction of two different levels of similarity which we will refer to as strong and weak similarity. Str...

The constants and functions in Reynolds-averaged Navier–Stokes (RANS) turbulence models are coupled. Consequently, modifications of a RANS model often negatively impact its basic calibrations, which is why machine-learned augmentations are often detrimental outside the training dataset. A solution to this is to identify the degrees of freedom that...

Insights gained from modal analysis are invoked for predictive large-eddy simulation (LES) wall modelling. Specifically, we augment the law of the wall (LoW) by an additional mode based on a one-dimensional proper orthogonal decomposition (POD) applied to a two-dimensional turbulent channel. The constructed wall model contains two modes, i.e. the L...

Generalisability and the consistency of the a posteriori results are the most critical points of view regarding data-driven turbulence models. This study presents a progressive improvement of turbulence models using simulation-driven Bayesian optimisation with Kriging surrogates where the optimisation of the models is achieved by a multi-objective...

Toward data-driven wall-modeled large-eddy simulations of different wall-bounded turbulent flows, a wall model is learned in this work using the wall-resolved large-eddy simulation (WRLES) data of the flow over periodic hills (PH) and the law of the wall (LoW). The feedforward neural network (FNN) is employed to construct the model. The obtained FN...

Ultrasonic flow meters with an intrusive two-stand configuration present a complex flow behaviour due to their unique geometry, which offers an interesting and challenging case to evaluate optimisation methods in wall-bounded flows. In this study, the design and analysis of computer models and shape optimisation by mesh morphing are utilised to pre...

In the current research, different architectures of physics-informed neural networks (PINNs) are implemented to investigate the mixed electroosmotic pressure driven (EOF/PD) flow in microchannels with non-uniform zeta-potential distribution on the walls. Through performing a detailed numerical simulation and PINN solutions based on Poisson-Boltzman...

The mean flow behaviour of a turbulent boundary layer over rough walls is expected to exhibit symmetries that govern the flow dynamics. In particular, when roughness elements are arranged in a spanwise symmetric manner, the mean flow above them should also exhibit spanwise symmetry. This symmetrical consideration has garnered substantial empirical...

The logarithmic law of the wall does not capture the mean flow when a boundary layer is subjected to a strong pressure gradient. In such a boundary layer, the mean flow is affected by the spatio-temporal history of the imposed pressure gradient; and accounting for history effects remains a challenge. This work aims to develop a universal mean flow...

Generalisability and the consistency of the a posteriori results are the most critical points of view regarding data-driven turbulence models. This study presents a progressive improvement of turbulence models using simulation-driven surrogate optimisation based on Kriging. We aim for the augmentation of secondary-flow reconstruction capability in...

We use experimental and simulation data to recalibrate the standard Spalart–Allmaras model. Free-shear flow, the buffer layer, the log layer, and flows with adverse pressure gradients are targeted. In this process, the recalibration does not affect untargeted flows. Our approach uses Bayesian optimization and feedforward neural networks. The recali...

This paper takes the perspective of a user of direct-numerical-simulation (DNS) data and quantifies the uncertainties in DNS statistics for plane channel flows. We focus on high-order statistics, such as skewness, kurtosis, and viscous dissipation, and quantify the uncertainties due to wall-normal numerics and grids while minimizing the sampling er...

This paper explores the similarity of the streamwise velocity fluctuations in a channel. In the analysis, we employ a one-dimensional scalar variant of the proper orthogonal decomposition (POD). This approach naturally motivates the introduction of two different levels of similarity which we will refer to as strong and weak similarity. Strong simil...

Design for cooling effectiveness in turbine blades relies on accurate models for dynamic losses and heat transfer of internal cooling passages. Metal additive manufacturing (AM) has expanded the design space for these configurations, but can give rise to large-scale roughness features. The range of roughness length scales in these systems makes mor...

This work compares various existing rough-wall models on a large collection of rough surfaces with different characteristics and studies the potentials of these models in accommodating new datasets. We consider three empirical roughness correlations, two physics-based models, and one data-driven machine-learning model on 68 rough surfaces inside an...

This survey investigates wall modeling in large-eddy simulations (LES) using data-driven machine-learning (ML) techniques. To this end, we implement three ML wall models in an open-source code and compare their performances with the equilibrium wall model in LES of half-channel flow at eleven friction Reynolds numbers between 180 and 10 10. The thr...

This paper reports an experimental study of tip vortex flowfield and cavitation inception of a tip-loaded hydrofoil. Vortex strength, wandering, and turbulence statistics are characterized using stereo particle image velocimetry (SPIV) in a water tunnel facility, at a chord Reynolds number of 1.3×106. Cavitation physics are characterized using high...

Buoyant wakes encountered in the ocean environment are characterized by high Reynolds (Re) and Froude (Fr) numbers, leading to significant space-time resolution requirements for turbulence resolving CFD models, (i.e.,DNS, LES). Therefore, RANS based models are attractive for these configurations. The inherently complex dynamics of stratified system...

This paper focuses on the use of reinforcement learning (RL) as a machine-learning (ML) modeling tool for near-wall turbulence. RL has demonstrated its effectiveness in solving high-dimensional problems, especially in domains such as games. Despite its potential, RL is still not widely used for turbulence modeling and is primarily used for flow con...

The damage due to particulate matter ingestion by propulsion gas turbine engines can be significant, impacting the operability and performance of plant components. Here, we focus on the axial compressor whose blades become damaged when operated in dusty/sandy environments, resulting in significant performance degradation. In this work, CFD studies...

This paper focuses on the use of reinforcement learning (RL) as a machine-learning (ML) modeling tool for near-wall turbulence. RL has demonstrated its effectiveness in solving high-dimensional problems, especially in domains such as games. Despite its potential, RL is still not widely used for turbulence modeling and is primarily used for flow con...

The goal of this work is to investigate the feasibility of constructing data-driven dynamical system models of roughness-induced secondary flows in thermally stratified turbulent boundary layers. Considering the case of a surface roughness distribution which is homogeneous and heterogeneous in the streamwise and spanwise directions, respectively, w...

Model selection is a chronic issue in computational science. The conventional approach relies heavily on human experience. However, gaining experience takes years and is severely inefficient. To address this issue, we distill human experience into a recommender system. A trained recommender system tells whether a computational model does well or po...

Insights gained from the modal analysis are invoked for predictive large-eddy simulation (LES) wall modeling. Specifically, we augment the law of the wall (LoW) by an additional mode based on a one-dimensional proper orthogonal decomposition (POD) applied to a 2D turbulent channel. The constructed wall model contains two modes, i.e., the LoW mode a...

Domestic ultrasonic flow meters with an intrusive two-stand configuration present a complex flow behaviour due to their unique geometry, which offers an interesting case to evaluate optimisation methods in wall-bounded turbulent flows. In this study, the design and analysis of computer models by computational fluid dynamics is used to predict the t...

Domestic ultrasonic flow meters with an intrusive two-stand configuration present a complex flow behaviour due to their unique geometry, which offers an interesting case to evaluate optimisation methods in wall-bounded turbulent flows. In this presentation, design optimisation is used to perform robust design optimisation of the flow meter. The opt...

We conduct direct numerical simulations and study the evolution of a pair of counter-rotating vortices in a stratified and turbulent environment beyond the first vortex linking (which is due to the Crow instability). The initial position of the two vortices is perpendicular to the direction of thermal stratification. We vary the Froude number, the...

The mean velocity follows a logarithmic scaling in the surface layer when normalized by the friction velocity, i.e. a velocity scale derived from the wall-shear stress. The same logarithmic scaling exists for the mean temperature when one normalizes the temperature with the friction temperature, i.e. a scale derived from the wall heat flux. This te...

This survey investigates wall modeling in large eddy simulations (LES) using data-driven machine learning (ML) techniques. To this end, we implement three ML wall models in an open-source code and compare their performances with the equilibrium wall model in LES of half-channel flow at eleven friction Reynolds numbers between $180$ and $10^{10}$. T...

A stratified wake has multiple flow regimes, and exhibits different behaviors in these regimes due to the competing physical effects of momentum and buoyancy. This work aims at automated classification of the weakly and the strongly stratified turbulence regimes based on information available in a full Reynolds stress model. First, we generate a di...

Design for cooling effectiveness in internal flow systems relies on accurate models for dynamic losses and heat transfer. In these systems (e.g., gas turbine blades, intercoolers, heat exchangers), thousands of individual passages of varying configuration and roughness morphology can be present. In recent years, additive manufacturing (AM) has furt...

Estimates of grid-point and time-step requirements exist for many canonical flows but not for stratified wakes. The purpose of this work is to fill in this gap. We apply the basic meshing principles and estimate the grid-point and time-step requirements for RANS and LES of stratified wake flows at high Reynolds numbers, as arise in many geophysical...

Buoyant wakes are widely encountered in ocean environment and undersea vehicle flows. These are typically characterized by high Reynolds (Re) and Froude (Fr) numbers, so turbulence resolving CFD models of such flows, i.e., Direct Numerical Simulation (DNS) and Large Eddy Simulation (LES), require significant computational resources. Therefore, Reyn...

The goal of this work is to investigate the feasibility of constructing data-driven dynamical system models of roughness-induced secondary flows in thermally stratified turbulent boundary layers. Considering the case of a surface roughness distribution which is homogeneous and heterogeneous in the streamwise and spanwise directions, respectively, w...

Conventional empirical turbulence modeling is progressive: one begins by modeling simple flows and progressively works towards more complex ones. The outcome is a series of nested models, with the next, more complex model accounting for some additional physics relative to the previous, less complex model. The above, however, is not the philosophy o...

The mixing-layer analogy is due to Raupach, Finnigan & Brunet ( Boundary-Layer Meteorol. , vol. 25, 1996, pp. 351–382). In the analogy, the flow in the roughness sublayer of a homogeneous deep vegetation canopy boundary layer is analogous to a plane mixing layer rather than a surface layer. Evidence for the analogy includes the inflected velocity p...

Computational fluid dynamics using the Reynolds-averaged Navier-Stokes (RANS) remains the most cost-effective approach to study wake flows and power losses in wind farms. The underlying assumptions associated with turbulence closures are one of the biggest sources of errors and uncertainties in the model predictions. This work aims to quantify mode...

Metal additive manufacturing has enabled geometrically complex internal cooling channels for turbine and heat exchanger applications, but the process gives rise to large-scale roughness whose size is comparable to the channel height (which is 500 $\mathrm {\mu }$ m). These super-rough channels pose previously unseen challenges for experimental meas...

Swells are common in sea areas, but how swells affect the operation of an offshore wind farm is poorly understood. To fill in this knowledge gap, large-eddy simulations of turbine arrays above swells are performed. Specifically, downwind, upwind, and lateral swells with three different wave ages are considered. The results show that downwind and up...

Computational fluid dynamics using the Reynolds-averaged Navier–Stokes (RANS) remains the most cost-effective approach to study wake flows and power losses in wind farms. The underlying assumptions associated with turbulence closures are one of the biggest sources of errors and uncertainties in the model predictions. This work aims to quantify mode...

When manufacturing a turbine engine, the combustor annulus and the turbine annulus are created as separate parts and assembled. This leads to an inter-platform gap between the two components, which must be supplied with leakage air to prevent ingestion of the extremely hot combustion gases into the interior of the engine. The combustor and the turb...

We exploit Monin–Obukhov similarity theory and Townsend’s attached-eddy hypothesis and arrive at a logarithmic-linear law for the streamwise velocity variance in the surface layer of stably stratified boundary layers. To test the logarithmic-linear law, we conduct large-eddy simulations (LES) of stably stratified turbulent boundary layers at variou...

A practical application of universal wall scalings is near-wall turbulence modeling. In this paper, we exploit the semilocal scaling [Patel, Boersma, and Pecnik, Phys. Rev. Fluids, 2, 084604 (2017)] and derive an eddy conductivity closure for wall-modeled large-eddy simulation of high-speed flows. We show that while the semilocal scaling does not c...

Enhanced fluctuations, steep gradients, and intensified heat transfer are characteristics of wall-bounded turbulence at transcritical conditions. Although such conditions are prevalent in numerous technical applications, the structure of the thermal boundary layer under realistic density gradients and heating conditions remains poorly understood. S...

Flow over arrays of cubes is an extensively studied model problem for rough wall turbulent boundary layers. While considerable research has been performed in computationally investigating these topologies using DNS and LES, the ability of sublayer-resolved RANS to predict the bulk flow phenomena of these systems is relatively unexplored, especially...

Buoyant shear layers encountered in many engineering and environmental applications have been studied by researchers for decades. Often, these flows have high Reynolds and Richardson numbers, which leads to significant/intractable space-time resolution requirements for DNS or LES. On the other hand, many of the important physical mechanisms, such a...

The wall-modeled large-eddy simulation (WMLES) computational framework generally includes a wall-model solver outside the large-eddy simulation (LES) infrastructure, with the two solvers communicating only at the matching location and the wall. Having a wall-model solver outside the LES jeopardizes the performance of WMLES: first, the wall-model so...

8 This paper investigates the layered structure of a turbulent plane wall jet at a distance from the nozzle exit. Based on the force balances in the mean momentum equation, the turbulent plane wall jet is divided into 10 three regions: a boundary layer-like region (BLR) adjacent to the wall, a half free jet-like region (HJR) away from the wall, and...

In analogy with the classical concept of mass-flux-based streamlines, we define Angular Momentum Transport (AMT) lines as an aerodynamic functional diagnostic tool. The AMT lines are the ones whose tangents are given by the average angular momentum flux. The mathematical and physical properties of these AMT lines are exploited to study the generati...

Buoyant shear layers are encountered in many engineering and environmental applications, and have been studied by researchers in the context of experiments and modeling for decades. Often, these flows have high Reynolds and Richardson numbers, and this leads to significant/intractable space-time resolution requirements for DNS or LES modeling. On t...

Flow over arrays of cubes is an extensively studied model problem for rough wall turbulent boundary layers. While considerable research has been performed in computationally investigating these topologies using DNS and LES, the ability of sublayer-resolved RANS to predict the bulk flow phenomena of these systems is relatively unexplored, especially...

Reynolds-averaged Navier-Stokes (RANS) is one of the most cost-efficient approaches to simulate wind-farm-atmosphere interactions. However, the applicability of RANS-based methods is always limited by the accuracy of turbulence closure models, which introduce various uncertainties into the models. In this study, we estimate model-form uncertainties...

Calibrating a Reynolds-averaged Navier–Stokes (RANS) model against data leads to an improvement. Determining a priori if such an improvement generalizes to flows outside the calibration data is an outstanding challenge. This work attempts to address this challenge via global epistemic Uncertainty Quantification (UQ). Unlike the available epistemic...