arXiv subjects

Luis Bravo

Publications and source records attributed to Luis Bravo.

At least 19 recordsLinked to original sources

arXiv2026

Generalized Formulation to Predict Rossiter Modes for Subsonic to Hypersonic Flow

This paper describes the development of a generalized physics-based model to accurately estimate Rossiter modes for flow over rectangular cavities for regimes ranging from subsonic to hypersonic without the a priori knowlege of flow physics. The Heller-Bliss model is shown to diverge from direct numerical simulation (DNS) results, while the adapted model shows close alignment (within 10\%) with the DNS data at higher Mach numbers, and is physically reasoned on the basis of energy modes. Using an effective temperature to evaluate the speed of sound calculations and then using it to calculate the Strouhal number yields closer predictions to DNS data. The present work also establishes asymptotic limits for Strouhal numbers.

physics.flu-dyn↗

arXiv2025

Hybrid RANS-LES simulation of transverse fuel injection in a Mach-10 scramjet engine

Hypersonic flight poses unique propulsion challenges, requiring engines that maintain thrust, efficiency, and stability across a wide range of operating conditions. These engines must transition smoothly between flight regimes and altitudes. Scramjets (supersonic combustion ramjets) play a key role in addressing these challenges. Recent advancements in high-fidelity computational fluid dynamics (CFD) tools allow researchers to explore novel designs and improve the feasibility of hypersonic travel. In this work, we analyze a radical-farming type scramjet engine mounted at the University of Queensland's T4 Wind Tunnel at Mach 10. We use the Improved Delayed Detached Eddy Simulation (IDDES) model, which combines Reynolds-Averaged Navier-Stokes (RANS) and Large Eddy Simulation (LES) in different flow regions. A novel integrated modeling strategy is introduced, coupling the inlet, fuel injectors, combustor, and nozzle for full-scale engine analysis. Hydrogen combustion is modeled using a Finite Rate Chemistry (FRC) approach with a 12-species, 27-reaction mechanism to capture shock-induced chemical kinetics across equivalence ratios of $\phi = 0.5$ to $0.9$. The Takeno flame index analysis reveals multiple combustion regimes, with ignition occurring in the partially premixed regime. This is supported by Chemical Explosive Mode Analysis (CEMA), which identifies regions of high chemical sensitivity, correlating with observed hot pockets and providing insights into autoignition and flame stabilization mechanisms. The combination of IDDES and FRC improves the transport of hydrogen to hot pockets, producing combustion patterns that match experimental results. This work establishes a framework to address critical challenges in future air-breathing propulsion systems.

physics.flu-dyn↗

arXiv2025

Mutual Interactions Between a Thin Flexible Panel and Supersonic Flows

This paper discusses the mutual interactions between a thin flexible aluminum plate and supersonic flow using two-dimensional (2D) numerical simulations. Calculations are performed using an open source library, SU2, that solves partial differential equations governing fluid and structural dynamics. The configuration considered in this research effort is based on an experiment in which a thin flexible panel of 1.02 mm with a 50.8 mm overhang at the outer edge of a backward facing step is exposed to Mach 2 flow. The computational framework was first validated against measurements for both the initial transients of 10 ms and the fully started conditions at 0.4 s. Then, numerical studies were performed to analyze the fluid-structure interactions at 4 different Mach numbers between 0.5 and 3. The flow behavior revealed distinct phenomena, including shear layer separation for subsonic and transonic flows, and a fully enclosed recirculation region under the overhang in supersonic cases. The time-averaged flow field identified potential temperature hotspots during the initial transients, which intensified as time evolved. For Mach 0.50, the amplitude of the thin panel oscillations increased as the flow transitioned from transient to steady-state conditions. In the transonic case (M = 0.95), the oscillation amplitude became significantly larger, potentially leading to resonant behavior and structural failure (we did not model failure). However, in the supersonic cases, the oscillations stabilized and were sustained after the initial transients. The research quantitatively identifies the influence of the Mach number on the fluid-structure interaction phenomena, which affect pressure loads and the development of thermal hotspots, which are crucial elements in engineering design.

physics.flu-dyn↗

arXiv2025

Flow-field analysis and performance assessment of rotating detonation engines under different number of discrete inlet nozzles

This study explores in depth rotating detonation engines (RDEs) fueled by premixed stoichiometric hydrogen/air mixtures through two-dimensional numerical simulations including a detailed chemical kinetic mechanism. To model the spatial reactant non-uniformities observed in practical RDE combustors, the referred simulations incorporate different numbers of discrete inlet nozzles. The primary focus here is to analyze the influence of reactant non-uniformities on detonation combustion dynamics in RDEs. By systematically varying the number of reactant injection nozzles (from 15 to 240), while maintaining a constant total injection area, the study delves into how this variation influences the behavior of rotating detonation waves (RDWs) and the associated overall flow field structure. The numerical results obtained here reveal significant effects of the number of inlets employed on both RDE stability (self-sustaining detonation wave) and performance. RDE configurations with a lower number of inlets exhibit a detonation front with chaotic behavior (pressure oscillations) due to an increased amount of unburned gas ahead of the detonation wave. This chaotic behavior can lead to the flame extinguishing or decreasing in intensity, ultimately diminishing the engine's overall performance. Conversely, RDE configurations with a higher number of inlets feature smoother detonation propagations without chaotic transients, leading to more stable and reliable performance metrics. This study uses high-fidelity numerical techniques such as adaptive mesh refinement (AMR) and the PeleC compressible reacting flow solver. This comprehensive approach enables a thorough evaluation of critical RDE characteristics including detonation velocity, fuel mass flow rate, impulse, thrust, and reverse pressure waves under varying reactant injection conditions.

physics.flu-dyn↗

arXiv2024

Hypersonic Boundary Layer Transition and Heat Loading

Hypersonic boundary layer transition using high-order methods for direct numerical simulations (DNS) is largely unexplored, although a few references exist in the literature. Experimental data in the hypersonic regime are scarce, while almost all existing hypersonic codes have low-order accuracy, which could lead to erroneous results in long-time integration and at high Reynolds numbers. Here, we focus on the transition from laminar to turbulent flow, where the Nusselt number may be five times or higher than the Nusselt number in the turbulent regime. The hypersonic flow regime must be modeled accurately using realistic chemistry to predict heat flux on the surface correctly. In this study, we simulate hypersonic boundary layer transition on a flat plate to compute the thermal and shear stresses on the wall. The domain is initialized with a laminar Blasius solution of compressible boundary layer equations. The transition to turbulence is induced using suction and blowing from a thin strip on the wall. Sponge regions are defined at the inflow and outflow boundaries to eliminate the solution contamination due to the reflections of the boundary conditions. In the spanwise direction, periodic boundary conditions are imposed. The numerical method applied here is a sixth-order compact finite difference in the interior of the domain coupled with a fourth-order Runge-Kutta time-stepping scheme for a structured Cartesian grid using staggered variables. The base finite difference code can perform simulations of non-equilibrium hypersonic flows. The numerical scheme is stabilized using the approximate deconvolution model (ADM) and artificial diffusion coefficients. We investigated the effect of non-equilibrium chemistry on the non-linear instability growth with hypersonic boundary layers. We also quantify thermal loads during the boundary layer laminar to turbulent transition for Mach number 10.

physics.flu-dyn↗

arXiv2024

High fidelity simulations of unstart phenomena in a scramjet inlet due to angle of attack

This work investigates the unsteady behavior of unstart phenomena within a scramjet inlet using advanced computational techniques. Scramjets and ramjets, with their reliance on inlet compression, offer promising airbreathing propulsion for hypersonic regimes. This research focuses on understanding and modeling the onset of unstart phenomena in supersonic inlets, a critical step towards developing mitigation strategies. These strategies have the potential to improve engine efficiency, range, and maneuverability of hypersonic vehicles. To achieve this, the state-of-the-art compressible flow solver, Eilmer, is used to simulate shockwave behavior within the inlet/isolator of a planar scramjet characterized experimentally at North Carolina State University (NCSU). Baseline comparisons are presented with the wind tunnel experiments via the shock structures present within the isolator section conducted at Mach 3.9 on a 3D scramjet inlet model. Simulations are then carried out at varying angles of attack (0 to 10 deg) and multiple pitch rates (10 deg/sec and 100 deg/sec) to demonstrate the shock train inertial response and to characterize unstart onset. In both cases the timing of inlet unstart is observed to correlate well with the rapid surge in exit pressure as well as shock detachment at the lower leading edge region. Lastly, exit pressures are significantly higher in the 10 deg/s case than in that of the 100 deg/s case at the same angle of attack. These observations suggest that unstart is not only dependent on angle of attack but also on AoA pitch rate. The findings provide valuable insights into the unsteady flow behavior during hypersonic inlet unstart, with potential applications for unstart detection at high angles of attack.

physics.flu-dyn↗

arXiv2024

Analysis of thermochemical non-equilibrium hypersonic flow over a waverider with uncertainty quantification

The objective of this work is to assess the impact of parameter uncertainty on hypersonic aerothermal surface heating predictions in Reynolds-Averaged Navier-Stokes (RANS) simulations using non-intrusive uncertainty quantification (UQ) techniques. RANS-based models are considered indispensable tools in computational fluid dynamics (CFD) analysis for the iterative and cost-effective exploration of innovative design concepts. However, these RANS models heavily rely on empirical constants that often require tuning due to the lack of physical knowledge and complexity of the problem, introducing significant uncertainties that hinder their predictive capabilities. Therefore, this research investigates the influence of the turbulent Prandtl number uncertainty, that governs the level of shear stress and heat flux present in the turbulent flow, on key output quantities of interest (QoIs). The US3D hypersonics solver is employed to simulate aeroheating over a hypersonic waverider configuration using the classical Menter Shear Stress Transport (SST) turbulence model. A polynomial chaos expansion (PEC) framework is presented that enables a global sensitivity analysis and forward propagation of uncertainty for a range of turbulent prandtl number, generating statistics including skewness and kurtosis of the QoIs. In addition, Sobol indices are calculated to quantify the relative contribution of the turbulent prandtl number to the overall uncertainty in the heat flux and surface pressure outputs. The results provide valuable insights into the underlying aeroheating behavior in RANS simulations under hypersonic non-equilibrium flow conditions over a waverider previously studied at the Arnold Engineering Development Center (AEDC) facility. These findings will inform future design processes and improve the reliability of RANS-based predictions in hypersonic applications.

physics.flu-dyn↗

arXiv2024

Deep operator learning-based surrogate models for aerothermodynamic analysis of AEDC hypersonic waverider

Neural networks are universal approximators that traditionally have been used to learn a map between function inputs and outputs. However, recent research has demonstrated that deep neural networks can be used to approximate operators, learning function-to-function mappings. Creating surrogate models to supplement computationally expensive hypersonic aerothermodynamic models in characterizing the response of flow fields at different angles of attack (AoA) is an ideal application of neural operators. We investigate the use of neural operators to infer flow fields (volume and surface quantities) around a geometry based on a 3D waverider model based on experimental data measured at the Arnold Engineering Development Center (AEDC) Hypervelocity Wind Tunnel Number 9. We use a DeepONet neural operator which consists of two neural networks, commonly called a branch and a trunk network. The final output is the inner product of the output of the branch network and the output of the trunk net. Because the flow field contains shocks across the entire volume, we conduct a two-step training approach of the DeepONet that facilitates accurate approximation of solutions even in the presence of discontinuities. We train various DeepONet models to understand and predict pressure $(p)$, density $(\rho)$, velocity $(u)$, heat flux $(Q_w)$, and total shear stress $(\tau_{w})$ for the AEDC waverider geometry at Ma=7.36 across AoA that range from $-10^{\circ}$ to $10^{\circ}$ for surface quantities and from $-14^{\circ}$ to $14^{\circ}$ for volume quantities.

physics.flu-dyn↗

arXiv2023

Fluid Dynamic Simulations of Mach and Regular Reflections in Oblique Shock-Wave Configurations using Adaptive Mesh Refinement

In the context of the interaction between a moving plane shock wave and an inclined wall (wedge), it is possible to distinguish four distinct shock reflection configurations. These shock wave reflections, which depend on the characteristics of the incident shock wave and the geometry of the surface that it interacts with, are (i) regular reflection (RR), (ii) simple Mach reflection (SMR), (iii) transition Mach reflection (TMR), and (iv) double Mach reflection (DMR). The impact of these shock reflections on flow properties can be significant so understanding them is important when predicting the behavior of shock waves in more complex flow configurations. Previous research works have explored the referred shock reflections through both numerical and experimental approaches, employing various gases and different flow and geometrical configurations. The present study involves the use of a high-fidelity computational fluid dynamics (CFD) tool, known as PeleC, which is a compressible solver based on AMReX specifically designed to handle complex flow configurations. Accordingly, by solving the time-dependent Euler equations for various 2D flow configurations, this work studies shock wave reflections accounting for four different Mach-based operating conditions and compares and analyzes the resulting density profiles on the wedge wall with experimental data. To strike a balance between model accuracy and computational efficiency, adaptive mesh refinement (AMR) is incorporated, and a mesh independence study is performed by varying the number of AMR levels. The results of this study demonstrate the capabilities of the CFD tool employed as it accurately predicts the sensitivity of wave characteristics to different operating conditions.

physics.flu-dyn↗

arXiv2023

Numerical Study of Distorted Tulip Flame Propagation in Confined Systems

Understanding the dynamics of premixed flames that propagates in confined systems is important in a wide range of applications. The study of premixed flames propagating in a closed channel covers a variety of complexities related to flame ignition, laminar flame development, and strong non-linear interaction between the flame and the surrounding walls. Accordingly, to study the dynamics of premixed flames propagating in closed channels, numerical simulations of the propagation of distorted tulip flames are carried out in this work. More specifically, a set of fully reactive compressible transport equations are solved here using the high-order PPM. A 21-step chemical kinetic mechanism is employed to model the chemical kinetics and the energy release in an air-hydrogen mixture. Computational mesh independence studies are carried out in this work by both refining grid elements and employing different levels of adaptive mesh refinements (AMR). The main results show that the classic tulip flame behavior evolves into a distorted one. Indeed, two consecutive collapses on the flame front are observed, which are related to wave pressure and the presence of reverse flow. It is particularly found that the pressure wave produced by the interaction of the flame skirt with the side walls reduces the flame velocity and contributes to the formation of tulip flames. This is consistent with the reduction in both flame area and pressure gradient at the flame tip. Furthermore, the collapse of flame cups is associated with the formation of the vortex near the channel side walls and the increase of pressure waves.

physics.flu-dyn↗

arXiv2023

Assessment of Large Eddy Simulation (LES) Sub-grid Scale Models Accounting for Compressible Homogeneous Isotropic Turbulence

Most sub-grid scale (SGS) models employed in LES (large eddy simulation) formulations were originally developed for incompressible, single phase, inert flows and assume transfer of energy based on the classical energy cascade mechanism. Although they have been extended to numerically study compressible and reactive flows involving deflagrations and detonations, their accuracy in such sensitive and challenging flows is an open question. Therefore, there is a need for both assessing these existing SGS models and identifying the opportunities for proposing new ones, which properly characterize reacting flows in complex engine configurations such as those characterizing rotating detonation engines (RDEs). Accordingly, accounting for the decay of free homogeneous isotropic turbulence (HIT), this work provides a comparison of four different SGS models when compressibility effects are present, (i) the classical Smagorinsky model, (ii) the dynamic Smagorinsky model, (iii) the wall-adapting local eddy-viscosity (WALE) model, and (iv) the Vreman model. More specifically, SGS models are firstly implemented in the open-source computational tool PeleC, which is a high-fidelity finite-volume solver for compressible flows, and then numerical simulations are carried out using them. In terms of results, turbulent spectra, and the decay of physical quantities such as kinetic energy, enstrophy, temperature, and dilatation are computed for each SGS LES model and compared with direct numerical simulations (DNS) results available in literature. The LES numerical results obtained here highlight that the studied SGS models are capable of capturing the overall trends of all physical quantities accounted for. However, they also emphasize the need of improved SGS models capable of adequately describing turbulence dynamics in compressible flows.

physics.flu-dyn↗

arXiv2023

Characterization of partial wetting by CMAS droplets using multiphase many-body dissipative particle dynamics and data-driven discovery based on PINNs

The molten sand, a mixture of calcia, magnesia, alumina, and silicate, known as CMAS, is characterized by its high viscosity, density, and surface tension. The unique properties of CMAS make it a challenging material to deal with in high-temperature applications, requiring innovative solutions and materials to prevent its buildup and damage to critical equipment. Here, we use multiphase many-body dissipative particle dynamics (mDPD) simulations to study the wetting dynamics of highly viscous molten CMAS droplets. The simulations are performed in three dimensions, with varying initial droplet sizes and equilibrium contact angles. We propose a coarse parametric ordinary differential equation (ODE) that captures the spreading radius behavior of the CMAS droplets. The ODE parameters are then identified based on the Physics-Informed Neural Network (PINN) framework. Subsequently, the closed form dependency of parameter values found by PINN on the initial radii and contact angles are given using symbolic regression. Finally, we employ Bayesian PINNs (B-PINNs) to assess and quantify the uncertainty associated with the discovered parameters. In brief, this study provides insight into spreading dynamics of CMAS droplets by fusing simple parametric ODE modeling and state-of-the-art machine learning techniques.

physics.flu-dyn↗

arXiv2023

Dynamic spreading and infiltration of a molten sand droplet on a porous surface

Compared to smooth surfaces, droplet spreading on porous surfaces is more complex and has relevance in many engineering applications. In this work, we investigate the infiltration dynamics of molten sand droplets on structured porous surfaces using the multiphase many-body dissipative particle dynamics (mDPD) method. We carry out three-dimensional simulations with different equilibrium contact angles and surface porosities. The temporal evolution of the radius of the wetted area follows a power law, as in the case of a smooth surface. The infiltration rate on the other hand is dictated by the competition between spreading and capillary inhibition of the pores. Additionally, the temporal evolution of the droplet height and the contact angle on the porous surface is also presented.

physics.flu-dyn↗

arXiv2023

Deposition of sand particles on a solid substrate in a high-temperature subsonic flow

Ingestion of sand particles into gas turbine engines has been observed to cause damage to engine components and in some cases leads to catastrophic failure. One such mechanism responsible for engine failure occurs through the deposition of molten particles on the turbine blades in the hot-section of the engine. The deposited material reacts chemically and penetrates the thermal barrier coating (TBC) on the turbines blades eventually damaging them. In this work, we investigate the deposition of sand particles on a solid substrate using two-way coupled Euler-Lagrange simulations. In these simulations, hot gas at 1700 K is issued from a circular inlet at Mach 0.3. Simultaneously, spherical mono-dispersed sand particles, modeled after the Calcia-Magnesia-Alumino-Silicates(CMAS), are injected at a constant mass flow rate of 1 gram per minute. The deposition of these particles on a solid substrate, placed 20 cm away from the inlet along the axial direction, is investigated. Simulations are carried out for three different synthetic sand particles CMAS, AFRL 02 and AFRL 03. The effect of Stokes number on particle properties such as number of particle depositions, rebound velocity and coefficient of restitution are investigated.

physics.flu-dyn↗

arXiv2023

Deep neural operators can serve as accurate surrogates for shape optimization: A case study for airfoils

Deep neural operators, such as DeepONets, have changed the paradigm in high-dimensional nonlinear regression from function regression to (differential) operator regression, paving the way for significant changes in computational engineering applications. Here, we investigate the use of DeepONets to infer flow fields around unseen airfoils with the aim of shape optimization, an important design problem in aerodynamics that typically taxes computational resources heavily. We present results which display little to no degradation in prediction accuracy, while reducing the online optimization cost by orders of magnitude. We consider NACA airfoils as a test case for our proposed approach, as their shape can be easily defined by the four-digit parametrization. We successfully optimize the constrained NACA four-digit problem with respect to maximizing the lift-to-drag ratio and validate all results by comparing them to a high-order CFD solver. We find that DeepONets have low generalization error, making them ideal for generating solutions of unseen shapes. Specifically, pressure, density, and velocity fields are accurately inferred at a fraction of a second, hence enabling the use of general objective functions beyond the maximization of the lift-to-drag ratio considered in the current work.

physics.flu-dyn↗

arXiv2021

Theory and simulation of electrokinetic fluctuations in electrolyte solutions at the mesoscale

Electrolyte solutions play an important role in energy storage devices, whose performance highly relies on the electrokinetic processes at sub-micron scales.\ Although fluctuations and stochastic features become more critical at small scales, the long-range Coulomb interactions pose a particular challenge for both theoretical analysis and simulation of fluid systems with fluctuating hydrodynamic and electrostatic interactions. Here, we present a theoretical framework based on the Landau-Lifshitz theory to derive closed-form expressions of fluctuation correlations in electrolyte solutions, indicating significantly different decorrelation processes of ionic concentration fluctuations from hydrodynamic fluctuations, which provides insights for understanding transport phenomena of coupled fluctuating hydrodynamics and electrokinetics. Furthermore, we simulate fluctuating electrokinetic systems using both molecular dynamics (MD) with explicit ions and mesoscopic charged dissipative particle dynamics (cDPD) with semi-implicit ions, from which we identify that the spatial probability density functions of local charge density follow Gamma distribution at sub-nanometer scale (i.e., 0.3 nm) and converge to Gaussian distribution above nanometer scales (i.e., 1.55 nm), indicating the existence of a lower limit of length scale for mesoscale models using Gaussian fluctuations. The temporal correlation functions of both hydrodynamic and electrokinetic fluctuations are computed from all-atom MD and mesoscale cDPD simulations, showing a good agreement with the theoretical predictions based on the linearized fluctuating hydrodynamics theory.

cond-mat.soft↗

arXiv2018

Computational Modeling and Analysis of Diesel-fuel Injection and Autoignition at Transcritical Conditions

The need for improved engine efficiencies has motivated the development of high-pressure combustion systems, in which operating conditions achieve and exceed critical conditions. Associated with these conditions are strong variations in thermo-transport properties as the fluid undergoes phase transition, and two-stage ignition with low-temperature combustion. Accurately simulating these physical phenomena at real-fluid environments remains a challenge. By addressing this issue, a high-fidelity LES-modeling framework is developed to conduct simulations of transcritical fuel spray mixing and auto-ignition at high-pressure conditions. The simulation is based on a recently developed diffused interface method that solves the compressible multi-species conservation equations along with a Peng-Robinson state equation and real-fluid transport properties. LES analysis is performed for non-reacting and reacting spray conditions targeting the ECN Spray A configuration at chamber conditions with a pressure of 60 bar and temperatures between 900 K and 1200 K to investigate effects of the real-fluid environment and low-temperature chemistry. Comparisons with measurements in terms of global spray parameters (i.e., liquid and vapor penetration lengths) are shown to be in good agreement. Analysis of the mixture fraction distributions in the dispersed spray region demonstrates the accuracy in modelling the turbulent mixing behavior. Good agreement of the ignition delay time and the lift-off length is obtained from simulation results at different ambient temperature conditions and the formation of intermediate species is captured by the simulations, indicating that the presented numerical framework adequately reproduces the corresponding low- and high-temperature ignition processes under high-pressure conditions, which are relevant to realistic diesel-fuel injection systems.

physics.flu-dyn↗

arXiv2018

Transcritical Mixing and Auto-Ignition of n-dodecane Liquid Fuel using a Diffused Interface Method

High-fidelity simulations of transcritical spray mixing and auto ignition in a combustion chamber are performed at high pressure and temperature conditions using a recently developed finite rate LES solver. The simulation framework is based on a diffused-interface (DI) method that solves the compressible multi-species conservation equations along with the Peng Robinson state equation and real-fluid transport properties. A finite volume approach with entropy stable scheme is employed to accurate simulate the non-linear real fluid flow. LES analysis is performed for non-reacting and reacting spray conditions targeting the ECN Spray A configuration at chamber conditions with a pressure of 60 bar and temperatures between 800 K and 1200 K to investigate effects of the real-fluid environment and low-temperature chemistry. Comparisons with measurements in terms of global spray parameters and mixture fraction distributions demonstrates the accuracy in modeling the turbulent mixing behavior. Good overall agreement of the auto-ignition process is obtained from simulation results at different ambient temperature conditions and the formation of intermediate species is captured by the simulations, indicating that the presented numerical framework adequately reproduces the corresponding low-and-high-temperature ignition processes under high-pressure conditions that are relevant to realistic diesel fuel injection systems.

physics.flu-dyn↗