Numerical Investigation and Optimization of a Flushwall Injector for Scramjet Applications at Hypervelocity Flow Conditions

An investigation utilizing Reynolds-averaged simulations (RAS) was performed in order to demonstrate the use of design and analysis of computer experiments (DACE) methods in Sandias DAKOTA software package for surrogate modeling and optimization. These methods were applied to a flow- path fueled with an interdigitated flushwall injector suitable for scramjet applications at hyper- velocity conditions and ascending along a constant dynamic pressure flight trajectory. The flight Mach number, duct height, spanwise width, and injection angle were the design variables selected to maximize two objective functions: the thrust potential and combustion efficiency. Because the RAS of this case are computationally expensive, surrogate models are used for optimization. To build a surrogate model a RAS database is created. The sequence of the design variables comprising the database were generated using a Latin hypercube sampling (LHS) method. A methodology was also developed to automatically build geometries and generate structured grids for each design point. The ensuing RAS analysis generated the simulation database from which the two objective functions were computed using a one-dimensionalization (1D) of the three-dimensional simulation data. The data were fitted using four surrogate models: an artificial neural network (ANN), a cubic polynomial, a quadratic polynomial, and a Kriging model. Variance-based decomposition showed that both objective functions were primarily driven by changes in the duct height. Multiobjective design optimization was performed for all four surrogate models via a genetic algorithm method. Optimal solutions were obtained at the upper and lower bounds of the flight Mach number range. The Kriging model predicted an optimal solution set that exhibited high values for both objective functions. Additionally, three challenge points were selected to assess the designs on the Pareto fronts. Further sampling among the designs of the Pareto fronts may be required to lower the surrogate model errors and perform more accurate surrogate-model-based optimization

Numerical Investigation and Optimization of a Flushwall Injector for Scramjet Applications at Hypervelocity Flow Conditions

An investigation utilizing Reynolds-averaged simulations (RAS) was performed in order to find optimal designs for an interdigitated flushwall injector suitable for scramjet applications at hypervelocity conditions. The flight Mach number, duct height, spanwise width, and injection angle were the design variables selected to maximize two objective functions: the thrust potential and combustion efficiency. A Latin hypercube sampling design-of-experiments method was used to select design points for RAS. A methodology was developed that automated building geometries and generating grids for each design. The ensuing RAS analysis generated the performance database from which the two objective functions of interest were computed using a one-dimensional performance utility. The data were fitted using four surrogate models: an artificial neural network (ANN) model, a cubic polynomial, a quadratic polynomial, and a Kriging model. Variance-based decomposition showed that both objective functions were primarily driven by changes in the duct height. Multiobjective design optimization was performed for all four surrogate models via a genetic algorithm method. Optimal solutions were obtained at the upper and lower bounds of the flight Mach number range. The Kriging model obtained an optimal solution set that predicted high values for both objective functions. Additionally, three challenge points were selected to assess the designs on the Pareto fronts. Further sampling among the designs of the Pareto fronts are required in order to lower the errors and perform more accurate surrogate-based optimization. sed optimization

Multi-layer Architecture For Storing Visual Data Based on WCF and Microsoft SQL Server Database

In this paper we present a novel architecture for storing visual data. Effective storing, browsing and searching collections of images is one of the most important challenges of computer science. The design of architecture for storing such data requires a set of tools and frameworks such as SQL database management systems and service-oriented frameworks. The proposed solution is based on a multi-layer architecture, which allows to replace any component without recompilation of other components. The approach contains five components, i.e. Model, Base Engine, Concrete Engine, CBIR service and Presentation. They were based on two well-known design patterns: Dependency Injection and Inverse of Control. For experimental purposes we implemented the SURF local interest point detector as a feature extractor and $K$-means clustering as indexer. The presented architecture is intended for content-based retrieval systems simulation purposes as well as for real-world CBIR tasks.Comment: Accepted for the 14th International Conference on Artificial Intelligence and Soft Computing, ICAISC, June 14-18, 2015, Zakopane, Polan

Comparison of Mixing Characteristics for Several Fuel Injectors at Mach 8, 12, and 15 Hypervelocity Flow Conditions

CFD analysis is presented of the mixing characteristics and performance of three fuel injectors at flight Mach numbers of 8, 12, and 15. The Reynolds-averaged simulations (RAS) were carried out using the VULCAN-CFD solver. The high Mach number flow conditions match those of the experiments conducted as a part of the Enhanced Injection and Mixing Project (EIMP) at the NASA Langley Research Center. The EIMP aims to investigate scramjet fuel injection and mixing physics, improve the understanding of underlying physical processes, and develop enhancement strategies relevant to flight Mach numbers greater than 8. The injectors include a fuel placement device, a strut, and a fluidic vortical mixer, a ramp. These fuel injectors accomplish the necessary task of distributing and mixing fuel into the supersonic cross-flow, albeit via different strategies. For comparison, a flush-wall injector is also included. This type of injector generally represents the simplest method of introducing fuel into a scramjet combustor. The three injectors represent the baseline configurations of the EIMP experiments. The mixing parameters of interest, such as mixing efficiency and total pressure recovery, are computed from the RAS and compared for the three flight conditions and injector configurations. In addition to mixing efficiency and total pressure recovery, the combustion efficiency and thrust potential are also computed for the reacting simulations. Plotting the total pressure recovery and thrust potential as a function of mixing efficiency provides added insight into critical aspects of combustor performance as the flight condition and injector type are varied

Analysis of the Two-Level NO PLIF Model for Low-Temperature High-Speed Flow Applications

The current work compares experimentally obtained nitric oxide (NO) laser-induced fluorescence (LIF) spectra with the equivalent spectra obtained analytically. The experimental spectra are computed from captured images of fluorescence in a gas cell and from a laser sheet passing through the fuel-air mixing flowfield produced by a high-speed fuel injector. The fuel injector is a slender strut that is currently being studied as a part of the Enhanced Injection and Mixing Project (EIMP) at the NASA Langley Research Center. This injector is placed downstream of a Mach 6 facility nozzle, which simulates the high Mach number airflow at the entrance of a scramjet combustor, and injects helium, which is used as an inert substitute for hydrogen fuel. Experimental planar (P) LIF is obtained by using a UV laser to excite fluorescence from the NO molecules that are present in either a gas cell or the facility air used for the EIMP experiments. The experimental data are obtained for several segments of the NO fluorescence spectrum. The selected segments encompass LIF lines with rotational quantum numbers appropriate for low-to-moderate temperature flows similar to those corresponding to the nominal experimental flow conditions. The experimental LIF spectra are then evaluated from the data and compared with those obtained from the theoretical models. The theoretical spectra are obtained from LIFBASE and LINUS software, and from a simplified version of the two-level fluorescence model. The equivalent analytic PLIF images are also obtained by applying only the simplified model to the results of the Reynolds-averaged simulations (RAS) of the mixing flowfield. Good agreement between the experimental and theoretical results provides increased confidence in both the simplified LIF modeling and CFD simulations for further investigations of high-speed injector performance using this approach

Black hole - neutron star mergers: the first mass gap and kilonovae

Observations of X-ray binaries indicate a dearth of compact objects in the mass range from $\sim 2-5$ $M_{\odot}$ and the existence of this (first mass) gap has been used to advance our understanding of the engines behind core-collapse supernovae. LIGO/Virgo observations provide an independent measure of binary compact remnant masses and several candidate first mass gap objects (either NS or BH) were observed in the O3 science run. We study the formation of BH-NS mergers in the framework of isolated classical binary evolution. We use population synthesis method to evolve binary stars (Population I and II) across cosmic time. The predicted BH-NS mergers from the isolated classical binary evolution are sufficiently abundant ($\sim 0.4-10$ $Gpc^{-3} yr^{-1}$) in the local Universe ($z\approx0$) to produce the observed LIGO/Virgo candidates. We present results on the NS to BH mass ratios ($q=M_{\rm NS}/M_{\rm BH}$ ) in merging systems, showing that although systems with a mass ratio as low as $q=0.02$ can exist, only a small fraction ($\sim 0.05\%-5\%$) of LIGO/Virgo detectable BH-NS mergers have mass ratios below $q=0.05$. We find that with appropriate constraints on the (delayed) supernova engine $\sim 30-40\%$ of LIGO/Virgo BH-NS mergers may host at least one compact object in the gap. The uncertainties in the processes behind compact object formation imply that the fraction of BH-NS systems ejecting mass during the merger is $\sim 0-9\%$. In our reference we find that only $\sim 0.2\%$ of BH-NS mergers will have any mass ejection, and about the same percentage would produce kilonova bright enough to have a chance to be detected even with a large (Subaru-class) $8$m telescope. Interestingly, all these mergers will have both BH and NS in the first mass gap.Comment: 14 pages, 12 figure

Progress Toward Affordable High Fidelity Combustion Simulations Using Filtered Density Functions for Hypersonic Flows in Complex Geometries

Significant progress has been made in the development of subgrid scale (SGS) closures based on a filtered density function (FDF) for large eddy simulations (LES) of turbulent reacting flows. The FDF is the counterpart of the probability density function (PDF) method, which has proven effective in Reynolds averaged simulations (RAS). However, while systematic progress is being made advancing the FDF models for relatively simple flows and lab-scale flames, the application of these methods in complex geometries and high speed, wall-bounded flows with shocks remains a challenge. The key difficulties are the significant computational cost associated with solving the FDF transport equation and numerically stiff finite rate chemistry. For LES/FDF methods to make a more significant impact in practical applications a pragmatic approach must be taken that significantly reduces the computational cost while maintaining high modeling fidelity. An example of one such ongoing effort is at the NASA Langley Research Center, where the first generation FDF models, namely the scalar filtered mass density function (SFMDF) are being implemented into VULCAN, a production-quality RAS and LES solver widely used for design of high speed propulsion flowpaths. This effort leverages internal and external collaborations to reduce the overall computational cost of high fidelity simulations in VULCAN by: implementing high order methods that allow reduction in the total number of computational cells without loss in accuracy; implementing first generation of high fidelity scalar PDF/FDF models applicable to high-speed compressible flows; coupling RAS/PDF and LES/FDF into a hybrid framework to efficiently and accurately model the effects of combustion in the vicinity of the walls; developing efficient Lagrangian particle tracking algorithms to support robust solutions of the FDF equations for high speed flows; and utilizing finite rate chemistry parametrization, such as flamelet models, to reduce the number of transported reactive species and remove numerical stiffness. This paper briefly introduces the SFMDF model (highlighting key benefits and challenges), and discusses particle tracking for flows with shocks, the hybrid coupled RAS/PDF and LES/FDF model, flamelet generated manifolds (FGM) model, and the Irregularly Portioned Lagrangian Monte Carlo Finite Difference (IPLMCFD) methodology for scalable simulation of high-speed reacting compressible flows

Comparison of Several Global Mixing Performance Metrics for High-Speed Fuel Injectors

To experimentally assess and compare the mixing performance of high-speed fuel injectors for scramjet engines, quantitative global metrics are needed. The one-dimensional metric most commonly used to assess the degree of mixing completeness at a given downstream station is the mixing efficiency parameter. The experimental determination of the mixing efficiency parameter requires measurement of the spatial distributions of both the fuel mass fraction and the mass flux. Standard in-stream gas sampling techniques can be used to measure the fuel mass fraction distribution, however the mass flux distribution is not easily determined experimentally because it requires the measurement of three independent aerothermodynamic variables in addition to the mixture composition. For this reason, several metrics that can be calculated from the fuel distribution alone are commonly used to assess mixing performance. Because these other metrics do not provide a mass flux-weighted measure of the local degree of mixing completeness, they may not correlate well with the mixing efficiency parameter. Therefore, if the substitute metrics are to be used to compare the mixing performance of candidate fuel injector concepts, it is important to understand their relationships to the mixing efficiency parameter in a representative scramjet combustor flowfield. This work investigates the relationships between the mixing efficiency parameter and several substitute metrics that are able to be measured with the current experimental setup of the Enhanced Injection and Mixing Project at the NASA Langley Research Center for baseline strut and ramp injectors. The results of these comparisons have revealed that it is possible to glean different (i.e., incorrect) conclusions about which injector is the better mixer when the substitute mixing performance metrics are used instead of the mixing efficiency parameter, thereby highlighting the importance of mass flux-weighted mixing performance metrics

A Priori Analysis of a Compressible Flamelet Model using RANS Data for a Dual-Mode Scramjet Combustor

In an effort to make large eddy simulation of hydrocarbon-fueled scramjet combustors more computationally accessible using realistic chemical reaction mechanisms, a compressible flamelet/progress variable (FPV) model was proposed that extends current FPV model formulations to high-speed, compressible flows. Development of this model relied on observations garnered from an a priori analysis of the Reynolds-Averaged Navier-Stokes (RANS) data obtained for the Hypersonic International Flight Research and Experimentation (HI-FiRE) dual-mode scramjet combustor. The RANS data were obtained using a reduced chemical mechanism for the combustion of a JP-7 surrogate and were validated using avail- able experimental data. These RANS data were then post-processed to obtain, in an a priori fashion, the scalar fields corresponding to an FPV-based modeling approach. In the current work, in addition to the proposed compressible flamelet model, a standard incompressible FPV model was also considered. Several candidate progress variables were investigated for their ability to recover static temperature and major and minor product species. The effects of pressure and temperature on the tabulated progress variable source term were characterized, and model coupling terms embedded in the Reynolds- averaged Navier-Stokes equations were studied. Finally, results for the novel compressible flamelet/progress variable model were presented to demonstrate the improvement attained by modeling the effects of pressure and flamelet boundary conditions on the combustion