Paola Cinnella

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• Professor
• Professor at Sorbonne University

The robust optimization (RDO) of complex flow configurations by means of advanced CFD models often relies on surrogate models to approximate the response of the cost function and to reduce the computational cost. The construction of accurate surrogates is a difficult task, namely for highly dimensional design and event spaces. In this paper we desc...

Oral presentation slides

A stochastic machine-learning framework is developed to enhance Reynolds-Averaged Navier-Stokes (RANS) predictions of turbulent flows while quantifying model uncertainty. The approach combines Bayesian symbolic identification to derive interpretable, uncertainty-aware corrections for specific flow classes (expert models) with a Mixture-of-Experts m...

A cost-effective multi-objective shape optimization strategy is proposed for high-Reynolds number flows involving complex phenomena such as boundary layer transition, shock-wave interactions, and turbulent wakes. These processes are poorly captured by Reynolds-Averaged Navier--Stokes (RANS) models, necessitating higher-fidelity approaches like Larg...

Hypersonic flow conditions pose exceptional challenges for Reynolds-averaged Navier–Stokes (RANS) turbulence modeling. Critical phenomena include compressibility effects, shock/turbulent boundary layer interactions, turbulence–chemistry interaction in thermo-chemical non-equilibrium, and ablation-induced surface roughness and blowing effects. This...

This book collects 12 lectures from the recent VKI lecture series "Machine Learning for Fluid Dynamics," jointly organized by VKI and ULB in February 2024. The lecture series explored how modern machine-learning methods can be applied to study and solve challenges in fluid dynamics. In line with the VKI lecture series tradition, it brings together...

This study investigates dynamic mesh adaptation (DMA) for hybrid RANS/LES (HRLES) simulations of compressible turbulent flows. HRLES models, which blend Reynolds-Averaged Navier–Stokes (RANS) and Large Eddy Simulation (LES), are by their nature very sensitive to the computational mesh, because of the very different resolution requirements in the RA...

Hypersonic flow conditions pose exceptional challenges for Reynolds-Averaged Navier-Stokes (RANS) turbulence modeling. Critical phenomena include compressibility effects, shock/turbulent boundary layer interactions, turbulence-chemistry interaction in thermo-chemical non-equilibrium, and ablation-induced surface roughness and blowing effects. This...

High-fidelity numerical simulations based on wall-resolved large-eddy simulations (LES) are used to investigate the vortex shedding dynamics in a linear turbine cascade. The profile geometry is the well-documented LS59 highly-loaded rotor blade. The simulation campaign covered several outlet Mach numbers (subsonic and transonic) and several experim...

This paper presents a combined numerical and experimental study of the high-subsonic organic vapor flow in a linear turbine cascade. The profile geometry is the well-documented LS59 highly-loaded rotor blade and the working fluid is Novec649, a dense gas used in organic Rankine cycles. Large-eddy simulations are carried out with and without the rou...

This study investigates dynamic mesh adaptation (DMA) for hybrid RANS/LES (HRLES) simulations of compressible turbulent flows. HRLES models, which blend Reynolds-Averaged Navier-Stokes (RANS) and Large Eddy Simulation (LES), are by their nature very sensitive to the computational mesh, because of the very different resolution requirements in the RA...

Accurate turbulent closures for the Reynolds-Averaged Navier-Stokes (RANS) equations are essential for a wide range of applications in engineering. Despite a plethora of proposed RANS models, there is no consensus on a single « best » model, and model choice is based on expert judgment. The uncertainty about model choice corresponds to an « epistem...

An idealized transonic blade configuration is studied using Delayed Detached Eddy Simulations (DDES), with focus on the loss mechanisms associated with the base pressure and turbulent wake development. The working fluid is Novec649, which is commonly used in low temperature Organic Rankine Cycle (ORC) power plants. Due to the molecular complexity o...

The free-stream turbulence (FST) induced transition in perfect and non-ideal gas zero-pressure-gradient flat-plate boundary layers is investigated by means of large-eddy simulations. The study focuses on the influence of large incoming disturbances over the laminar-to-turbulent transition, by comparing two different integral length scales $L_f$ , w...

****ACCEPTED FOR PUBLICATION IN FLOW, TURBULENCE AND COMBUSTION***** A machine learning-based methodology for blending data-driven turbulent closures for the Reynolds-Averaged Navier-Stokes (RANS) equations is proposed to improve the generalizability across different flow scenarios. Data-driven models based on sparse Bayesian learning and symbolic...

High-fidelity numerical simulations based on wall-resolved large-eddy simulations (LES) are used to investigate the vortex shedding dynamics in a linear turbine cascade. The profile geometry is the well-documented LS59 highly-loaded rotor blade. The simulation campaign covered several outlet Mach numbers (subsonic and transonic) and several experim...

This paper presents a combined numerical and experimental study of the high-subsonic organic vapor flow in a linear turbine cascade. The profile geometry is the well-documented LS59 highly-loaded rotor blade and the working fluid is Novec649, a dense gas used in organic Rankine cycles. Large-eddy simulations are carried out with and without the rou...

This study aims at providing evidence of the importance of using high-fidelity methods for accurate loss estimation during initial ORC turbine design. The case of a supersonic stator vane in both linear and annular cascades is used to exemplify the divergences in loss between flows where crucial features including the boundary layers, the wake and...

This study explores the turbulent breakdown of high-enthalpy hypersonic boundary layers under adiabatic wall conditions using direct numerical simulations, with a focus on finite-rate chemistry effects. By subjecting a Mach 10 boundary layer to controlled perturbations via suction and blowing, the investigation shows the evolution from laminar to f...

In this manuscript, we combine non-intrusive reduced-order models (ROMs) with space-dependent aggregation techniques to build a mixed-ROM , able to accurately capture the flow dynamics in different physical settings. The flow prediction obtained using the mixed formulation is derived from a convex combination of the predictions of several previousl...

The integration of machine learning (ML) techniques for addressing intricate physics problems is increasingly recognized as a promising avenue for expediting simulations. However, assessing ML-derived physical models poses a significant challenge for their adoption within industrial contexts. This competition is designed to promote the development...

Technological advancements have substantially increased computational power and data availability, enabling the application of powerful machine-learning (ML) techniques across various fields. However, our ability to leverage ML methods for scientific discovery, i.e. to obtain fundamental and formalized knowledge about natural processes, is still in...

*****Accepted in Journal of Computational Physics. To appear***** A stochastic Machine-Learning approach is developed for data-driven Reynolds-Averaged Navier-Stokes (RANS) predictions of turbulent flows, with quantified model uncertainty. This is done by combining a Bayesian symbolic identification methodology for learning stochastic RANS model co...

The agamid lizards of the genus Draco are undoubtedly the most renown reptilian gliders, using their rib-supported patagial wings as lifting surfaces while airborne. Recent investigations into these reptiles highlighted the role of body posture during gliding, however, the aerodynamics of postural changes in Draco remain unclear. Here, we examine t...

This chapter provides an introduction to data-driven techniques for the development and calibration of closure models for the Reynolds-Averaged Navier-Stokes (RANS) equations. RANS models are the workhorse for engineering applications of computational fluid dynamics (CFD) and are expected to play an important role for decades to come. However, RANS...

This article introduces an innovative two-stage, two-temperature ejector cycle (NTDERC) capable of simultaneously generating cooling and electricity. It harnesses waste heat from exhaust gases and is purposefully designed to operate with a neutral carbon footprint. To minimize global warming potential, we opted for a mixture of isobutane/propane (5...

Detailed turbulence and trailing edge vortex shedding measurements employing hot-wire anemometry and numerical simulations using a high-resolution unsteady Reynolds-averaged Navier-Stokes method were conducted for the high subsonic flow of the organic vapor Novec 649 through the VKI turbine cascade at elevated pressure and temperature level. Turbul...

A joint numerical and experimental investigation of an idealized blade vane configuration, representative of an ORC turbine, is undertaken using Novec649 as the working fluid. First laminar-turbulent transition over the blade is studied by means of large-eddy simulation (LES). The geometry of the leading edge is modified to avoid an incipient separ...

A p-adaptation strategy is developed in the framework of successive correction k-exact finite volume schemes. A new error estimator based on the decay of the successive correction terms use to reconstruct the solution within one cell is introduced to drive the adaptation process. The criterion relies on low-order derivatives, is efficiently estimat...

Purpose The purpose of the paper is to analyse the performances of closures and compressibility corrections classically used in turbulence models when applied to highly-compressible turbulent boundary layers (TBLs) over flat plates. Design/methodology/approach A direct numerical simulation (DNS) database of TBLs, covering a wide range of thermodyn...

In direct and large eddy simulations, very small space steps are used close to the solid walls in order to resolve the boundary-layer structures. Due to the restrictive CFL stability criteria of explicit time-stepping schemes, the maximum allowable time step is also very small, leading to high computational costs, notably for converging flow statis...

This PhD thesis aims to enhance the current RANS turbulence models using Machine Learning (ML), and is organized in three main parts. First, we employ the Sparse Bayesian Learning (SBL) algorithm to derive sparse and stochastic closures of EARSM-type for the baseline k − ω SST model to address turbulent separated flows. The resulting models, denote...

In the recent years, increased attention has been given to Organic Rankine cycle (ORC) systems which find their use in small scale applications such as waste-heat recovery [1].

Organic Rankine cycle (ORC) is widely used for waste-heat recovery and eco-friendly power generation.

The freestream turbulence-induced transition of a dense-gas boundary layer past a thick leading edge representative of turbine blades is investigated with large-eddy simulations. Due to the high Reynolds number conditions, typical of Organic Rankine Cycle applications, transition occurs early on the blade. In such conditions, the freestream turbule...

Computational models of fluid flows based on the Reynolds-Averaged Navier–Stokes (RANS) equations supplemented with a turbulence model are the gold standard in engineering applications. A plethora of turbulence models and related variants exist, none of which are fully reliable outside the range of flow configurations for which they were calibrated...

A high-order shock-capturing central finite-difference scheme is evaluated for numerical simulations of hypersonic high-enthalpy flows out of thermochemical equilibrium. The scheme is an extension to thermochemical out-of-equilibrium flows of the technique presented in Sciacovelli et al. (2021) for high-speed flows in chemical nonequilibrium. It re...

High Reynolds transonic ideal and non-ideal gas flows around a smooth circular cylinder are investigated by means of Large Eddy Simulations over a range of Mach numbers encompassing the drag divergence. The global aerodynamic performance of the cylinder in both air and a dense vapor are compared, as well as the influence of the thermodynamic behavi...

****ACCEPTED FOR PUBLICATION IN THE INTERNATIONAL JOURNAL OF NUMERICAL METHODS FOR HEAT AND FLUID FLOW**** A priori tests of turbulence models for the compressible Reynolds-Averaged Navier–Stokes (RANS) are performed by using Direct Numerical Simulations (DNS) data of zero-pressure-gradient flat-plate turbulent boundary layers. The DNS database cov...

The freestream turbulence-induced transition of a dense-gas boundary layer past a thick leading edge representative of turbine blades is investigated with large-eddy simulations. Due to the high Reynolds number conditions, typical of Organic Rankine Cycle applications, transition occurs early on the blade. In such conditions, the freestream turbule...

REVIEW PAPER ACCEPTED IN COMPUTERS & FLUIDS. ******This article reviews recent advances in the understanding of turbulent flows of non-ideal gases through the use of high-fidelity direct and large eddy simulations. In particular, the focus is on so-called dense gases, i.e. flows of organic vapours, which are characterised by moderate to high molecu...

ACCEPTED FOR PUBLICATION IN FLOW, TURBULENCE AND COMBUSTION******High Reynolds transonic ideal and non-ideal gas flows around a smooth circular cylinder are investigated by means of Large Eddy Simulations over a range of Mach numbers encompassing the drag divergence. The global aerodynamic performance of the cylinder in both air and a dense vapor a...

A probabilistic framework is used to learn data-driven corrections of the baseline k−ω SST turbulence model for a selected flow classes, including channel flow, jet flow, and separated flows. Specifically, we use a Bayesian sparse symbolic regression algorithm, which delivers explicit analytical expressions for the correction terms. The data-driven...

This article reviews recent advances in the understanding of turbulent flows of non-ideal gases through the use of high-fidelity direct and large eddy simulations. In particular, the focus is on so-called dense gases, i.e. flows of organic vapours, which are characterised by moderate to high molecular complexity and weight, making them deviate from...

MUSICAA, a high-order finite differences solver relying on parallel multi-block strategy, alongside coordinate transformations and implicit time stepping, is used to analyze several industrial flows. Diverse case configurations are presented with the aim of comparing different scale-resolving approaches, validating the multiblock finite differences...

Boundary layers of Novec649, a low-global-warming potential fluid of interest for low-grade heat recovery, are investigated numerically by means of linear stability theory, direct numerical simulation (DNS) and large-eddy simulations (LES). This organic vapour is of interest in organic Rankine cycle (ORC) turbines and realistic thermodynamic condit...

This work aims to improve the turbulence modeling in RANS simulations for particle-laden flows. Using DNS data as reference, the errors of the model assumptions for the Reynolds stress tensor and turbulence transport equations are extracted and serve as target data for a machine learning process called SpaRTA (Sparse Regression of Turbulent Stress...

In this study we focus on a supersonic turbine configuration , typically adopted in Organic Rankine Cycles (ORCs) to deal with very high pressure ratios. RANS computations of an annular cascade as well as wall resolved Large Eddy Simulations of a linear cascade are performed, both in air and a dense vapor. Validation of the numerical methods is per...

Without a consensus on which model performs best, the choice of the suitable RANS model to simulate industrial flows still relies on expert judgment. To reduce the uncertainties associated with model selection , previous work has focused on combining a set of pre-specified RANS models. While these methods are promising, the combination weights are...

Plenary lecture at ETMM14

The propagation technique of high-fidelity data into Reynolds-averaged Navier Stokes (RANS) equations can play an important role in the development of data-driven RANS models. It is shown that the frozen treatment of the Reynolds force vectors (RFV) instead of Reynolds stress tensors (RST) results in lower propagation error; therefore, it can bring...

A joint numerical and experimental investigation of an idealized blade vane configuration, representative of an ORC turbine, is undertaken using Novec649 as the working fluid. First laminar-turbulent transition over the blade is studied by means of large-eddy simulation (LES). The geometry of the leading edge is modified to avoid an incipient separ...

For developing a reliable data-driven Reynold stress tensor (RST) model, successful reconstruction of the mean velocity field based on high-fidelity information (i.e., direct numerical simulations or large-eddy simulations) is crucial and challenging, considering the ill-conditioning problem of Reynolds-averaged Navier–Stokes (RANS) equations. It i...

The present contribution reports the outcome of an experimental and numerical investigation of the behavior of a constant-temperature hot-wire anemometer in the high subsonic flow up to a Mach number of 0.7 of the organic vapor NovecTM 649 at pressure and temperature levels of typical organic Rankine cycle (ORC) turbine applications. The experiment...

An experimental and numerical investigation was carried out to study the quasi-homogeneous and isotropic decaying grid-generated turbulence in a subsonic organic vapour flow. The turbulent motion was measured by means of hot-wire probes which were located downstream of the grid and were operated in the constant-temperature mode. The working fluid w...

The flow of an organic vapor at high subsonic Mach numbers past a circular cylinder was investigated using Background-oriented Schlieren (BOS) and computational fluid dynamics. The experiment was carried out in a closed-loop organic vapor wind tunnel (CLOWT) using Novec 649 as working-fluid which provides a compressibility factor of \(Z=0.91\) at t...

For obtaining turbulent fluctuations in compressible organic vapor flows, computational fluid dynamics (CFD) analysis tools were used to support the data reduction process of hot-wire anemometry signals. It was found that CFD can help during the calibration process of actual hot-wire probes operated in the constant-temperature mode. Such an approac...

The dynamics of a shock wave impinging on a transitional high-enthalpy boundary layer out of thermochemical equilibrium is investigated by means of a direct numerical simulation. The freestream Mach number is equal to 9, and the oblique shock impinges with a cooled flat-plate boundary layer with an angle of 10◦, generating a reversal flow region. I...

The ORC technology is subject to manifold sources of uncertainty that can have a severe impact on the thermodynamic and economic efficiency of plant components, particularly when the system is operated at off-design conditions. In this contribution we focus on the development of ORC turbines with stable performance under uncertainty: a novel multi-...

The aerodynamic performance of a cylinder Pitot probe for velocity measurements in compressible non-ideal gas flows, such as those encountered in Organic Rankine Cycle (ORC) turbines, is investigated by means of Computational Fluid Dynamics. Numerical simulations are performed at subsonic and transonic conditions, and freestream Reynolds numbers ar...

Keynote Lecture at Symposium of VKI PhD research. Rhodes St Genèse, BE, 9 th March 2023

*****ACCEPTED FOR PUBLICATION IN THE JOURNAL OF COMPUTATIONAL PHYSICS. Available online https://doi.org/10.1016/j.jcp.2023.112628***** In this article, we propose a data-driven methodology for combining the solutions of a set of competing turbulence models. The individual model predictions are linearly combined for providing an ensemble solution a...

******** ACCEPTED FOR PUBLICATION IN PHYSICAL REVIEW FLUIDS********************The dynamics of a shock wave impinging on a transitional high-enthalpy boundary layer out of thermochemical equilibrium is investigated for the first time by means of a direct numerical simulation. The freestream Mach number is equal to 9 and the oblique shock impinges w...

Surrogate models are necessary to optimize meaningful quantities in physical dynamics as their recursive numerical resolutions are often prohibitively expensive. It is mainly the case for fluid dynamics and the resolution of Navier-Stokes equations. However, despite the fast-growing field of data-driven models for physical systems, reference datase...

Customized SBL-EARSM models for specific flow cases are derived + combined using the 'Mixture of Experts' concept.

In the last decade or less, applications of data science, and more specifically of so-called machine learning (ML), in physical sciences have been growing exponentially. ML-assisted Computational Fluid Dynamics (CFD) models with magnified predictive capabilities and computational efficiency can play a game changing role in Aerospace and Energy indu...

A hypersonic turbulent boundary layer over a flat plate is numerically investigated. The large Mach number and temperature values in the freestream (M e = 12.48 and T e = 594.3 K, respectively) lead to a high-enthalpy regime and to the occurrence of thermochemical non-equilibrium effects. Vibrational relaxation phenomena are shown to be predominant...

An open-box machine learning algorithm (sparse symbolic regression) is used to generate improved turbulence models for sediment transport from DNS data. For that purpose, the SpaRTA (Sparse Regression of Turbulent Anisotropy) of Schmelzer et al. is extended to flows with sediment transport and a new dissipation analogy for constructing correction t...

Particle-laden ows occur in many ways in natural and technological situations. Jain et al. [1] presented four DNS studies of sediment transport with di erent particle shapes. The one conducted with spherical particles was used in the present work to apply a machine learning (ML) algorithm to improve the turbulence modelling in RANS simulations. Ch...

The high Reynolds number flow around a circular cylinder of an organic vapour at transonic inlet conditions is investigated by means of a Large Eddy Simulation (LES). This case is challenging on both the physical and computational point of view, due to the highly complex flow features requiring fine grids and long time integration. The high-fidelit...

Organic Rankine Cycle (ORC) power systems o er a great potential for waste heat recovery and environmental-friendly power generation but relatively little is known regarding the impact of real-gas e ects on loss mechanisms in ORC turbine expanders. A new experimental facility has been built at Uni- versity of Muenster which consists in a continuous...

The present contribution reports the outcome of an experimental and numerical investigation of the behavior of a constant-temperature hot-wire anemometer in the high subsonic flow up to a Mach number of 0.7 of the organic vapor Novec 649 at pressure and temperature levels of typical organic Rankine cycle (ORC) turbine applications. The experiments...

A novel Sparse Bayesian Learning (SBL) framework is introduced for generating stochastic Explicit Algebraic Reynolds Stress (EARSM) closures for the Reynolds-Averaged Navier–Stokes (RANS) equations from high-fidelity data. Building on the recently proposed SpaRTA (Sparse Regression of Turbulent Stress Anisotropy) algorithm of Schmelzer et al. (2020...

Surrogate models are necessary to optimize meaningful quantities in physical dy-1 namics as their recursive numerical resolutions are often prohibitively expensive. It 2 is mainly the case for fluid dynamics and the resolution of Navier-Stokes equations. 3 However, despite the fast-growing field of data-driven models for physical systems, 4 referen...

In direct and large eddy simulations, very small space steps are used close to the solid walls in order to resolve the boundary-layer structures. Due to the restrictive CFL stability criteria of explicit time-stepping schemes, the maximum allowable time step is also very small, leading to high computational costs, notably for converging flow statis...

A high-order shock-capturing finite-difference scheme for scale-resolving numerical simulations of hypersonic high-enthalpy flows, involving thermal non-equilibrium effects, is presented. The suitability of the numerical strategy for such challenging configurations is assessed in terms of accuracy and robustness, with special focus on shock-capturi...

****ACCEPTED FOR PUBLICATION IN INTERNATIONAL JOURNAL OF HEAT AND FLUID FLOW**** A novel Sparse Bayesian Learning (SBL) framework is introduced for generating stochastic Explicit Algebraic Reynolds Stress (EARSM) closures for the Reynolds-Averaged Navier-Stokes (RANS) equations from high-fidelity data. Building on the recently proposed SpaRTA (Spar...

Presentation of the Sparse Bayesian Learning and spatial model aggregation (x-MA) algorithms for turbulence model data-driven augmentation and uncertainty quantification, and application to the collaborative testing challenge at 2022 Symposium on Turbulence Modeling: Roadblocks, and the Potential for Machine Learning, in honour of 60th birthday of...

Keynote Lecture

A hypersonic, spatially-evolving turbulent boundary layer at Mach 12.48 with a cooled wall is analyzed by means of direct numerical simulations. At the selected conditions, massive kinetic-to-internal energy conversion triggers thermal and chemical nonequilibrium phenomena. Air is assumed to behave as a five species reacting mixture, and a two-temp...

A CFD-driven deterministic symbolic identification algorithm for learning explicit algebraic Reynolds-stress models (EARSM) from high-fidelity data is developed building on the frozen-training SpaRTA algorithm of [1]. Corrections for the Reynolds stress tensor and the production of transported turbulent quantities of a baseline linear eddy viscosit...

******ACCEPTED FOR PUBLICATION IN THE JOURNAL OF COMPUTATIONAL PHYSICS************** A CFD-driven deterministic symbolic identification algorithm for learning explicit algebraic Reynolds-stress models (EARSM) from high-fidelity data is developed building on the CFD-free SpaRTA algorithm of [1]. Corrections for the Reynolds stress tensor and the pro...

The ORC technology is subject to manifold sources of uncertainty that can have a severe impact on the thermodynamic and economic efficiency of plant components, particularly when the system is operated at off-design conditions. In this contribution we focus on the development of ORC turbines with stable performance under uncertainty: a novel multi-...

###ACCEPTED#### Robust predictions of turbulent turbomachinery flows, namely, flows through the NACA65 V103 compressor cascade at various operating conditions, are obtained by accounting for uncertainties associated with the turbulence models. First, an efficient strategy is introduced for calibrating turbulence model coefficients from high fidelit...

High-speed turbulent flows are encountered in most space-related applications (including exploration, tourism and defense fields) and represent a subject of growing interest in the last decades. A major challenge in performing high-fidelity simulations of such flows resides in the stringent requirements for the numerical schemes to be used. These m...

Presentation at Symposium on "Model-Consistent Data-driven Turbulence Modeling", Organized by U. Michigan, June 22-24, 2021 (ZOOM).

Presentation for Stanford University Fluid Mechanics Seminar Series. ENGR298. Spring Session 2020-2021.

The influence of high-enthalpy effects on hypersonic turbulent boundary layers is investigated by means of direct numerical simulations (DNS). A quasi-adiabatic flat-plate air flow at free-stream Mach number equal to 10 is simulated up to fully-developed turbulent conditions using a five-species, chemically-reacting model. A companion DNS based on...

The influence of high-enthalpy effects in hypersonic, spatially developing boundary layers is investigated by means of direct numerical simulations. The flow of a reacting mixture of nitrogen and oxygen over a flat plate at Mach 10, previously investigated in the literature using linear stability theory (LST), is simulated using a computational dom...

A CFD-driven approach for building data-augmented explicit algebraic Reynolds-stress models (EARSM) with improved performance with respect to a baseline linear eddy viscosity model for a given class of flows is presented. The proposed methodology is used to learn a model improving the predictions of the k-ω SST model for 2D turbulent separated flow...

This paper presents the application of high-order vorticity confinement (VC) to the simulation of two cases: the decay of compressible homogeneous isotropic turbulence (HIT) in an implicit LES approach and a flat plate with zero pressure gradient in a hybrid RANS/LES simulation. For the HIT case, VC has been found to reduce the numerical dissipatio...

********PUBLISHED IN COMPUTERS AND FLUIDS, AUGUST 2021*****************************High-speed turbulent flows are encountered in most space-related applications (including exploration, tourism and defense fields) and represent a subject of growing interest in the last decades. A major challenge in performing high-fidelity simulations of such flows...

******PUBLISHED IN PHYSICAL REVIEWS FLUIDS********* The influence of high-enthalpy effects on hypersonic turbulent boundary layers is investigated by means of direct numerical simulations (DNS). A quasi-adiabatic flat-plate air flow at free-stream Mach number equal to 10 is simulated up to fully-developed turbulent conditions using a five-species,...