Publications

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The development of scramjet engines is an important research area for advancing hypersonic and orbital flights. Progress toward optimal engine designs requires accurate flow simulations together with uncertainty quantification. However, performing uncertainty quantification for scramjet simulations is challenging due to the large number of uncertainparameters involvedandthe high computational costofflow simulations. These difficulties are addressedin this paper by developing practical uncertainty quantification algorithms and computational methods, and deploying themin the current studyto large-eddy simulations ofajet incrossflow inside a simplified HIFiRE Direct Connect Rig scramjet combustor. First, global sensitivity analysis is conducted to identify influential uncertain input parameters, which can help reduce the system's stochastic dimension. Second, because models of different fidelity are used in the overall uncertainty quantification assessment, a framework for quantifying and propagating the uncertainty due to model error is presented. These methods are demonstrated on a nonreacting jet-in-crossflow test problem in a simplified scramjet geometry, with parameter space up to 24 dimensions, using static and dynamic treatments of the turbulence subgrid model, and with two-dimensional and three-dimensional geometries.

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For film cooling of combustor linings and turbine blades, it is critical to be able to accurately model jets-in-crossflow. Current Reynolds-averaged Navier-Stokes (RANS) models often give unsatisfactory predictions in these flows, due in large part to model form error, which cannot be resolved through calibration or tuning of model coefficients. The Boussinesq hypothesis, upon which most two-equation RANS models rely, posits the existence of a non-negative scalar eddy viscosity, which gives a linear relation between the Reynolds stresses and the mean strain rate. This model is rigorously analyzed in the context of a jet-in-crossflow using the high-fidelity large eddy simulation data of Ruiz et al. (2015, "Flow Topologies and Turbulence Scales in a Jet-in-Cross-Flow," Phys. Fluids, 27(4), p. 045101), as well as RANS k-ε results for the same flow. It is shown that the RANS models fail to accurately represent the Reynolds stress anisotropy in the injection hole, along the wall, and on the lee side of the jet. Machine learning methods are developed to provide improved predictions of the Reynolds stress anisotropy in this flow.

The development of scramjet engines is an important research area for advancing hypersonic and orbital flights. Progress towards optimal engine designs requires both accurate flow simulations as well as uncertainty quantification (UQ). However, performing UQ for scramjet simulations is challenging due to the large number of uncertain parameters involved and the high computational cost of flow simulations. We address these difficulties by combining UQ algorithms and numerical methods to the large eddy simulation of the HIFiRE scramjet configuration. First, global sensitivity analysis is conducted to identify influential uncertain input parameters, helping reduce the stochastic dimension of the problem and discover sparse representations. Second, as models of different fidelity are available and inevitably used in the overall UQ assessment, a framework for quantifying and propagating the uncertainty due to model error is introduced. These methods are demonstrated on a non-reacting scramjet unit problem with parameter space up to 24 dimensions, using 2D and 3D geometries with static and dynamic treatments of the turbulence subgrid model.

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We report on the development of a model framework to simulate spray flames from direct injection of liquid fuel into an automotive cylinder engine. The approach to this challenging problem was twofold. On one hand, the interface-capturing multiphase computer code CLSVOF was used to resolve the rapidly evolving, topologically convoluted interfaces that separate the liquid fuel from the gas at injection: the main challenges to address were the treatment of the high-pressure flow inside the injector, which required the inclusion of compressibility effects; and the computational framework necessary to achieve a Direct Numerical Simulation (DNS) level of accuracy. On the other hand, the scales of turbulent fuel mixing and combustion in the cylinder engine were addressed by the high-performance computer code RAPTOR within the Large Eddy Simulation (LES) framework. To couple the two computational methods, a novel methodology was developed to de- scribe the dense spray dynamics in Raptor from the assigned spray size distribution and dispersion angle derived from CLSVOF. This new, independent Eulerian Multi-Fluid (EMF) spray module was developed based on the kinetic description of a system of droplets as a pressure-less gas; as we will show, it was demonstrated to efficiently render the near-nozzle coupling in mass, momentum, and energy with the carrier gas phase.

We report on the development of a model framework to simulate spray flames from direct injection of liquid fuel into an automotive cylinder engine. The approach to this challenging problem was twofold. On one hand, the interface-capturing multiphase computer code CLSVOF was used to resolve the rapidly evolving, topologically convoluted interfaces that separate the liquid fuel from the gas at injection: the main challenges to address were the treatment of the high-pressure flow inside the injector, which required the inclusion of compressibility effects; and the computational framework necessary to achieve a Direct Numerical Simulation (DNS) level of accuracy. On the other hand, the scales of turbulent fuel mixing and combustion in the cylinder engine were ad- dressed by the high-performance computer code RAPTOR within the Large Eddy Simulation (LES) framework. To couple the two computational methods, a novel methodology was developed to describe the dense spray dynamics in Raptor from the assigned spray size distribution and dispersion angle derived from CLSVOF. This new, independent Eulerian Multi-Fluid (EMF) spray module was developed based on the kinetic description of a system of droplets as a pressure-less gas; as we will show, it was demonstrated to efficiently render the near-nozzle coupling in mass, momentum, and energy with the carrier gas phase.

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For film cooling of combustor linings and turbine blades, it is critical to be able to accurately model jets-in-crossflow. Current Reynolds Averaged Navier Stokes (RANS) models often give unsatisfactory predictions in these flows, due in large part to model form error, which cannot be resolved through calibration or tuning of model coefficients. The Boussinesq hypothesis, upon which most two-equation RANS models rely, posits the existence of a non-negative scalar eddy viscosity, which gives a linear relation between the Reynolds stresses and the mean strain rate. This model is rigorously analyzed in the context of a jet-in-crossflow using the high fidelity Large Eddy Simulation data of Ruiz et al. (2015), as well as RANS k-e results for the same flow. It is shown that the RANS models fail to accurately represent the Reynolds stress anisotropy in the injection hole, along the wall, and on the lee side of the jet. Machine learning methods are developed to provide improved predictions of the Reynolds stress anisotropy in this flow.

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Previously, a theory has been presented that explains how discrete vapor–liquid interfaces become diminished at certain high-pressure conditions in a manner that leads to well known qualitative trends observed from imaging in a variety of experiments. Rather than surface tension forces, transport processes can dominate over relevant ranges of conditions. In this paper, this framework is now generalized to treat a wide range of fuel-oxidizer combinations in a manner consistent with theories of capillary flows and extended corresponding states theory. Different flow conditions and species-specific molecular properties are shown to produce distinct variations of interfacial structures and local free molecular paths. These variations are shown to occur over the operating ranges in a variety of propulsion and power systems. Despite these variations, the generalized analysis reveals that the envelope of flow conditions at which the transition from classical sprays to diffusion-dominated mixing occurs exhibits a characteristic shape for all liquid–gas combinations. As a result, for alkane-oxidizer mixtures, it explains that these conditions shift to higher pressure flow conditions with increasing carbon number and demonstrates that, instead of widely assumed classical spray atomization, diffusion-dominated mixing may occur under relevant high-pressure conditions in many modern devices.

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Until recently, modern theory has lacked a fundamentally based model to predict the operating pressures where classical sprays transition to dense-fluid mixing with diminished surface tension. In this paper, such a model is presented to quantify this transition for liquid-oxygen–hydrogen and n-decane–gaseous-oxygen injection processes. The analysis reveals that respective molecular interfaces break down not necessarily because of vanishing surface tension forces but instead because of the combination of broadened interfaces and a reduction in mean free molecular path. When this occurs, the interfacial structure itself enters the continuum regime, where transport processes rather than intermolecular forces dominate. Using this model, regime diagrams for the respective systems are constructed that show the range of operating pressures and temperatures where this transition occurs. The analysis also reveals the conditions where classical spray dynamics persists even at high supercritical pressures. As a result, it demonstrates that, depending on the composition and temperature of the injected fluids, the injection process can exhibit either classical spray atomization, dense-fluid diffusion-dominated mixing, or supercritical mixing phenomena at chamber pressures encountered in state-of-the-art liquid rocket engines.

This study presents a detailed analysis of the flow topologies and turbulence scales in the jet-in-cross-flow experiment of [Su and Mungal JFM 2004]. The analysis is performed using the Large Eddy Simulation (LES) technique with a highly resolved grid and time-step and well controlled boundary conditions. This enables quantitative agreement with the first and second moments of turbulence statistics measured in the experiment. LES is used to perform the analysis since experimental measurements of time-resolved 3D fields are still in their infancy and because sampling periods are generally limited with direct numerical simulation. A major focal point is the comprehensive characterization of the turbulence scales and their evolution. Time-resolved probes are used with long sampling periods to obtain maps of the integral scales, Taylor microscales, and turbulent kinetic energy spectra. Scalar-fluctuation scales are also quantified. In the near-field, coherent structures are clearly identified, both in physical and spectral space. Along the jet centerline, turbulence scales grow according to a classical one-third power law. However, the derived maps of turbulence scales reveal strong inhomogeneities in the flow. From the modeling perspective, these insights are useful to design optimized grids and improve numerical predictions in similar configurations.

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Significant inadequacies of current models for multiphase flows present a major barrier to rapid development of advanced high-efficiency low-emissions combustion devices. Liquid spray atomization processes largely determine fuel-air mixture formation, which subsequently govern combustion and controls performance, emissions, and durability of a device. The current study presents a fundamentally-consistent framework to model the effects of breakup processes, liquid drop deformations, and internal flow dynamics on mass, momentum, and energy exchange functions. This framework builds on the Taylor Analogy Breakup (TAB) model which naturally quantifies local drop deformation dynamics. Real-fluid multicomponent thermodynamic property modeling and Gradient Theory simulations facilitate accurate calculations of molecular two-phase interface exchange functions, surface tensions forces, drop oscillations, and breakup processes. The analysis establishes that these drop dynamics, along with finite liquid viscosity effects, significantly alter gas-liquid exchange functions. The study quantifies these effects for the resulting drag coefficients of liquid drops and demonstrates significant deviations from the classic dynamic drag model, which is widely applied in modern simulations performed in academia and industry. This work also quantifies effects, which originate from gas-liquid coupling dynamics, on evaporation and heating rates. The analysis establishes that the consideration of these coupling dynamics modify mass and energy transfer rates even more significantly than the corresponding drag forces from momentum exchange. This physical complexity, however, is largely neglected in modern studies from academia and industry. A new set of equations is presented to improve the modeling of drop breakup processes to address the current shortcomings in the prediction of resulting drops proper- ties over the full range of relevant breakup conditions. The framework is based on a refined energy balance equation which explicitly enforces drop momentum conservation during the breakup process. The introduced modeling framework is entirely derived from conservation equations for mass, momentum, and energy and does not, as a consequence, introduce new modeling constants. The significance of the developed modeling advances to fuel injection processes is demonstrated using Large Eddy Simulation (LES) with a Lagrangian-Eulerian modeling approach.

Large-eddy-simulation (LES) is quickly becoming a method of choice for studying complex thermo-physics in a wide range of propulsion and power systems. It provides a means to study coupled turbulent combustion and flow processes in parameter spaces that are unattainable using direct-numerical-simulation (DNS), with a degree of fidelity that can be far more accurate than conventional engineering methods such as the Reynolds-averaged Navier-Stokes (RANS) approximation. However, development of predictive LES is complicated by the complex interdependence of different type of errors coming from numerical methods, algorithms, models and boundary con- ditions. On the other hand, control of accuracy has become a critical aspect in the development of predictive LES for design. The objective of this project is to create a framework of metrics aimed at quantifying the quality and accuracy of state-of-the-art LES in a manner that addresses the myriad of competing interdependencies. In a typical simulation cycle, only 20% of the computational time is actually usable. The rest is spent in case preparation, assessment, and validation, because of the lack of guidelines. This work increases confidence in the accuracy of a given solution while minimizing the time obtaining the solution. The approach facilitates control of the tradeoffs between cost, accuracy, and uncertainties as a function of fidelity and methods employed. The analysis is coupled with advanced Uncertainty Quantification techniques employed to estimate confidence in model predictions and calibrate model's parameters. This work has provided positive consequences on the accuracy of the results delivered by LES and will soon have a broad impact on research supported both by the DOE and elsewhere.

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Kinetic theory is often used as a framework to derive moment equations for sprays, with considerable success in the case of a dilute spray in a fully resolved (DNS) gas field. In the prospect of computing LES of atomization with a spray solver, a formalism that accounts for the non-linear interaction between high-loading regions and turbulence at the subfilter level is needed. So we first introduce a kinetic theory frame, where the phase space is extended to space-filtered spray quantities. This rigorous formalism is a comprehensive baseline but it requires closures. Second we quantify segregation, through a priori DNS, as a relevant space-filtered quantity to account for the spray’s subfilter behavior. Third we discuss an assumption on the subfilter spray structures which allows the closure of drag, heating, and collisions from the sole knowledge of segregation.

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Using hydrogen derived from coal in power generation is one of the potential strategies being considered for eliminating CO2 emissions from combustion. In a two-stage gas combustor, injection of hydrogen into a secondary combustor provides an effective means for achieving a wide range of power settings. However, when additional hydrogen is injected into the exit stream of the first stage turbine, the mixture may autoignite. This uncontrolled autoignition event is undesirable as it leads to strong acoustic waves and high levels of nitrogen oxides (NOx). Since hydrogen was not a main fuel in the past, studies of hydrogen combustion under gas turbine environments have not been extensively carried out. Autoignition of hydrogen depends on pressure in a nonlinear fashion and is sensitive to the unique transport properties of the small hydrogen molecules, making prediction of autoignition a very challenging task. For both steady and transient flames, Large Eddy Simulation (LES) is essential for obtaining a fundamental understanding of flame stability mechanisms. As such, this work performs a LES study aimed at modeling and understanding 1) key stability mechanism(s) related to flame propagation and/or autoignition, and 2) the effect of pressure on hydrogen combustion over the range of 1 to 20 bar.

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Liquid injection in systems such as liquid rockets where the working fluid exceeds the thermodynamic critical condition of the liquid phase is not well understood. Under some conditions when operating pressures exceed the liquid phase critical pressure, surface tension forces become diminished when the classical low-pressure gas-liquid interface is replaced by a diffusion-dominated mixing layer. Modern theory, however, still lacks a physically-based model to explain the conditions under which this transition occurs. In this paper, we derive a coupled model to obtain a theoretical analysis that quantifies these conditions for general multicomponent liquid injection processes. Our model applies a modified 32-term Benedict-Webb-Rubin equation of state along with corresponding combining and mixing rules that accounts for the relevant thermodynamic non-ideal multicomponent mixture states in the system. This framework is combined with Linear Gradient Theory, which facilitates the calculation of the vapor-liquid molecular structure. Dependent on oxygen and hydrogen injection temperatures, our model shows interfaces with substantially increased thicknesses in comparison to interfaces resulting from lower injection temperatures. Contrary to conventional wisdom, our analysis reveals that LOX-H2 molecular interfaces break down not necessarily because of vanishing surface tension forces, but because of the combination of broadened interfaces and a reduction in mean free molecular path at high pressures. Then, these interfaces enter the continuum length scale regime where, instead of inter-molecular forces, transport processes dominate. Based on this theory, a regime diagram for LOX-H2 mixtures is introduced that quantifies the conditions under which classical sprays transition to dense-fluid jets.

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This report documents the results of a project funded by DoD's Strategic Environmental Research and Development Program (SERDP) on the science behind development of predictive models for soot emission from gas turbine engines. Measurements of soot formation were performed in laminar flat premixed flames and turbulent non-premixed jet flames at 1 atm pressure and in turbulent liquid spray flames under representative conditions for takeoff in a gas turbine engine. The laminar flames and open jet flames used both ethylene and a prevaporized JP-8 surrogate fuel composed of n-dodecane and m-xylene. The pressurized turbulent jet flame measurements used the JP-8 surrogate fuel and compared its combustion and sooting characteristics to a world-average JP-8 fuel sample. The pressurized jet flame measurements demonstrated that the surrogate was representative of JP-8, with a somewhat higher tendency to soot formation. The premixed flame measurements revealed that flame temperature has a strong impact on the rate of soot nucleation and particle coagulation, but little sensitivity in the overall trends was found with different fuels. An extensive array of non-intrusive optical and laser-based measurements was performed in turbulent non-premixed jet flames established on specially designed piloted burners. Soot concentration data was collected throughout the flames, together with instantaneous images showing the relationship between soot and the OH radical and soot and PAH. A detailed chemical kinetic mechanism for ethylene combustion, including fuel-rich chemistry and benzene formation steps, was compiled, validated, and reduced. The reduced ethylene mechanism was incorporated into a high-fidelity LES code, together with a moment-based soot model and models for thermal radiation, to evaluate the ability of the chemistry and soot models to predict soot formation in the jet diffusion flame. The LES results highlight the importance of including an optically-thick radiation model to accurately predict gas temperatures and thus soot formation rates. When including such a radiation model, the LES model predicts mean soot concentrations within 30% in the ethylene jet flame.

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Prior HCCI optical engine experiments utilizing laser-induced fluorescence (LIF) measurements of stratified fuel-air mixtures have demonstrated the utility of probability density function (PDF) statistics for correlating mixture preparation with combustion. However, PDF statistics neglect all spatial details of in-cylinder fuel distribution. The current computational paper examines the effects of spatial fuel distribution on combustion using a novel combination of a 3-D CFD model with a 1-D linear-eddy model of turbulent mixing. In the simulations, the spatial coarseness of initial fuel distribution prior to the start of heat release is varied while keeping PDF statistics constant. Several cases are run, and as the initial mixture is made coarser, combustion phasing monotonically advances due to high local equivalence ratios that persist longer. The effect of turbulent mixing is more complex. For the case where the length scale of the initial distribution matches the integral length scale of turbulence, turbulent mixing leads to moderation of peak heat-release rate. The randomness of turbulence is captured in the simulation, and for the above case, cycle-to-cycle variation of the combustion is evident. In contrast, when the initial fuel distribution is significantly finer or coarser than the turbulence length scale, turbulent mixing does not affect combustion for two different reasons. For fine distributions, molecular diffusion alone homogenizes the fuel-air mixture prior to ignition, so turbulence adds nothing. For initial distributions that are coarse compared to the turbulence length scale, diffusion and turbulence are both ineffective at mixing, so again turbulence has a minimal effect on combustion.

This paper focuses on the application of the large eddy simulation (LES) technique to a swirling particle-laden flow in a model combustion chamber. A series of calculations have been performed and compared directly with detailed experimental measurements. The computational domain identically matches the laboratory configuration, which effectively isolates effects related to dilute particle dispersion and momentum coupling. Results highlight the predictive capabilities of LES when implemented with the appropriate numerics, grid resolution (as dictated by the class of models employed) and well-defined boundary conditions. The case study provides a clearer understanding of the effectiveness and feasibility of current state-of-the-art models and a quantitative understanding of relevant modeling issues by analyzing the characteristic parameters and scales of importance. The novel feature of the results presented is that they establish a baseline level of confidence in our ability to simulate complex flows at conditions representative of those typically observed in gas-turbine (and similar) combustors. © 2006 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

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