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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Direct numerical simulation of a turbulent methane/air flame impinged by a sub-breakdown electric field

Here, the effects of an external electric field on a turbulent methane/air diffusion flame are analyzed in this work using direct numerical simulations. The analyzed configuration consists of a temporally evolving mixing layer of air and a mixture of methane and nitrogen at 1 atm that is impinged by an electric field in the direction normal to the mean mixing plane. The combustion and chemi-ionization reactions involved in the flow are modeled using finite-rate chemistry and a reduced reaction scheme consisting of 26 species and 134 reactions. The mass diffusion and ion-wind effects are modeled using a detailed description of the diffusion coefficients and electric mobilities based on kinetic theory. The presented calculations show that the turbulence generated within the mixing layer is mostly unaffected by the applied electric field for the configuration under exam. In fact, the electric body force is developed away from the mixing region where the flow is uniform. Conversely, the turbulence is able to introduce very high intermittency in the electrically charged species concentration and, consequently, in the electric body force. Such intermittency will constitute a challenge in the future formulation of combustion models that take into account ion-wind effects.

09 BIOMASS FUELS↗
DOE OSTI2021

Plasma-catalyst modeling for materials selection: challenges and opportunities in nitrogen oxidation

Reliable kinetic models are essential to rationalize observations and to guide the selection of appropriate plasma-catalyst combinations. Kinetic models coupling plasma- and heterogeneous-catalytic-chemistries, however, are primitive. Here, we combine reduced plasma chemistries and density functional theory parameterized surface reactions to model NO formation from N2 oxidation, an alternative nitrogen fixation process. We first show plasma excited species can enhance turnover frequencies of both Pt and Au. The enhancing potential is a function of plasma species and their densities. We then compare NO production between plasma/Pt and plasma/Au with an integral reactor model and explore the dependence of NO production as a function of plasma conditions, reactor configurations and chemical compositions. Plasma/Pt generates more NO than plasma/Au under most thermal and plasma parametric conditions. Plasma/Au outperforms plasma/Pt under high plasma excitations at low temperatures. Furthermore, these results highlight that selection of plasma-catalyst combinations should consider the properties of plasmas, materials and the coupling of the two.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2012

AdapChem

AdapChem software enables high efficiency, low computational cost, and enhanced accuracy on computational fluid dynamics (CFD) numerical simulations used for combustion studies. The software dynamically allocates smaller, reduced chemical models instead of the larger, full chemistry models to evolve the calculation while ensuring the same accuracy to be obtained for steady-state CFD reacting flow simulations. The software enables detailed chemical kinetic modeling in combustion CFD simulations. AdapChem adapts the reaction mechanism used in the CFD to the local reaction conditions. Instead of a single, comprehensive reaction mechanism throughout the computation, a dynamic distribution of smaller, reduced models is used to capture accurately the chemical kinetics at a fraction of the cost of the traditional single-mechanism approach.

Oluwole, Oluwayemisi O.↗
NASA NTRS2006

Development of Comprehensive Reduced Kinetic Models for Supersonic Reacting Shear Layer Simulations

Large-scale simulations of multi-dimensional unsteady turbulent reacting flows with detailed chemistry and transport can be computationally extremely intensive even on distributed computing architectures. With the development of suitable reduced chemical kinetic models, the number of scalar variables to be integrated can be decreased, leading to a significant reduction in the computational time required for the simulation with limited loss of accuracy in the results. A general MATLAB-based automated mechanism reduction procedure is presented to reduce any complex starting mechanism (detailed or skeletal) with minimal human intervention. Based on the application of the quasi steady-state (QSS) approximation for certain chemical species and on the elimination of the fast reaction rates in the mechanism, several comprehensive reduced models, capable of handling different fuels such as C2H4, CH4 and H2, have been developed and thoroughly tested for several combustion problems (ignition, propagation and extinction) and physical conditions (reactant compositions, temperatures, and pressures). A key feature of the present reduction procedure is the explicit solution of the concentrations of the QSS species, needed for the evaluation of the elementary reaction rates. In contrast, previous approaches relied on an implicit solution due to the strong coupling between QSS species, requiring computationally expensive inner iterations. A novel algorithm, based on the definition of a QSS species coupling matrix, is presented to (i) introduce appropriate truncations to the QSS algebraic relations and (ii) identify the optimal sequence for the explicit solution of the concentration of the QSS species. With the automatic generation of the relevant source code, the resulting reduced models can be readily implemented into numerical codes.

Zambon, A. C.↗
NASA NTRS2021

Intercomparison of the representations of the atmospheric chemistry of pre-industrial methane and ozone in earth system and other global chemistry-transport models

An intercomparison has been set up to study the representation of the atmospheric chemistry of the pre-industrial troposphere in earth system and other global tropospheric chemistry-transport models. The intercomparison employed a constrained box model and utilised tropospheric trace gas composition data for the pre-industrial times at ninety mid-latitude surface locations. Incremental additions of four organic compounds: methane, ethane, acetone and propane, were used to perturb the constrained box model and generate responses in hydroxyl radicals and tropospheric ozone at each location and with each chemical mechanism. Although the responses agreed well across the chemical mechanisms from the selected earth system and other global tropospheric chemistry-transport models, there were differences in the detailed responses between the chemical mechanisms that could be tracked down by sensitivity analysis to differences in the representation of C1–C3 chemistry. Inter-mechanism ranges in NOx compensation points were about 0.17 ± 0.12 when expressed relative to the inter-mechanism average. Monte Carlo uncertainty analysis carried out with a single chemical mechanism put the intra-mechanism range a factor of three higher at 0.50 ± 0.12. Similar differences between inter-mechanism and intra-mechanism ranges were found for hydroxyl radical depletion but were up to a factor of six wider for ozone formation from incremental additions of organic compounds. The cause of the discrepancies between the inter- and intra-mechanism ranges was found to be the large uncertainties that are present in the laboratory determinations of the rate coefficients and product channel branching ratios of some key chemical reactions involving organic peroxy radicals and hydroperoxides. Whilst these large uncertainties are present in the laboratory determinations, there will be irreducible uncertainties in the predictions from the earth system and other chemistry-transport models of methane and tropospheric ozone trends since pre-industrial times and hence their contributions to the radiative forcing of climate change. Further definitive laboratory studies of the reaction rates and product yields of the reactions of the simple organic peroxy radicals and hydroperoxides are required to resolve and reduce current uncertainties in earth system and chemistry-transport model predictions.

atmospheric chemistry↗
DOE OSTI2023

Simulation of a rapid compression machine for evaluation of ignition chemistry and soot formation using gasoline/ethanol blends

Due to the projected decline of demand for gasoline in light duty engines and the advent of ethanol as a green fuel, the use of gasoline/ethanol blend fuels in heavy duty applications are being investigated as they are projected to have lower cost and lower lifecycle green house gas (GHG) emissions. In heavy duty engines, the primary mode of combustion is mixing controlled combustion where wide range of mixture conditions (equivalence ratio) exist. Soot emissions of these fuels in richer conditions are not well understood. The goal of this research is to evaluate some commercially available soot modeling codes for the particulate matter emissions from gasoline/ethanol fuel blends, especially at fuel rich conditions. A Rapid Compression Machine (RCM) is modeled in a three-dimensional numerical simulation using CONVERGE computational software using a reduced chemical kinetic mechanism with SAGE chemistry solver and a RANS k-ϵturbulence model with a sector model including the creviced piston. The creviced piston is used in the experimental setup to reduce boundary layer effects and to maintain a homogeneous core in the reaction cylinder. Computational fluid dynamics simulations are conducted for different gasoline-ethanol fuel blends from E10 (10% ethanol v/v) to E100. The fuel blend is modeled as a surrogate mixture of toluene, iso-octane, n-heptane for gasoline content, and ethanol. The computational results were validated against experimental results using pressure measurements and laser extinction diagnostics. Different soot models are investigated to evaluate their capability of predicting the sooting tendencies of fuel blends, especially in richer conditions experienced during mixing-controlled combustion. The experimental combustion characteristics such as the ignition delay of different blends of fuel are reasonably well predicted. The Particulate Size Mimic (PSM) model accurately predicts the soot generation characteristics of the different fuels, but the Hiroyasu-NSC model falls short in this regard. For accurate prediction of soot with the PSM model, the thermodynamic conditions during combustion must be accurately modeled. While the current computational modeling tools can produce accurate results for the prediction of particulate matter emissions, there is much work to be done in improving our understanding of the underlying fundamental processes.

Energy & Fuels↗
NASA NTRS2019

Detection of Propadiene on Titan

The atmosphere of Titan, the largest moon of Saturn, is rich in organic molecules, and it has been suggested that the moon may serve as an analog for the pre-biotic Earth due to its highly reducing chemistry and existence of global hazes. Photochemical models of Titan have predicted the presence of propadiene (historically referred to as allene), CH2CCH2, an isomer of the well-measured propyne (also called methylacetylene) CH3CCH, but its detection has remained elusive due to insufficient spectroscopic knowledge of the molecule. This has recently been remedied with an updated spectral line list. Here we present the first unambiguous detection of the molecule in any astronomical object, observed with the Texas Echelle Cross Echelle Spectrograph on the NASA Infrared Telescope Facility in 2017 July. We model its emission line near 12 μm and measure a volume mixing ratio of (6.9 ± 0.8) × 10(exp −10) at 175 km, assuming a vertically increasing abundance profile as predicted in photochemical models. Cassini measurements of propyne made during 2017 April indicate that the abundance ratio of propyne to propadiene is 8.2 ± 1.1 at the same altitude. This initial measurement of the molecule in Titan's stratosphere paves the way toward constraining the amount of atomic hydrogen available on Titan, as well as future mapping of propadiene on Titan from 8 m and larger ground-based observatories, and future detection on other planetary bodies.

Propadiene or allene↗
DOE OSTI2023

Prediction of alkaline earth metal ion adsorption on goethite for various background electrolytes with the CD-MUSIC model

As water scarcity drives the use of more saline water sources, contaminant fate and transport models must capture the impact of high concentrations of alkaline earth metal ions (AEMs) and background electrolytes in these more complex waters. By utilizing macroscopic adsorption data from various electrolyte systems, a Charge Distribution – Multisite Complexation (CD-MUSIC) model, capable of incorporating electrolyte adsorption, was able to accurately simulate the adsorption behavior of alkaline earth metal ions onto goethite. The modeling effort was guided by previous spectroscopic and surface complexation modeling of alkaline earth metal adsorption and built on previous CD-MUSIC modeling that accounted for changes in crystal face contributions to the surface site density as a function of specific surface area. Further, the model was constrained to consider only two dominant surface complex species for each metal ion adsorption reaction. These two species were selected from 44 possible species through objective curve fitting of single-solute macroscopic adsorption data. While most of the alkaline earth metal surface complexes formed outer-sphere complexes at the goethite surface, an inner-sphere species was utilized for Mg 2+ . With the surface complex species and equilibrium constants obtained from this study, the calibrated model successfully predicted alkaline earth metal ion adsorption over a wide range of solution and surface conditions; the model predictions encompassed a wide range of pH (5–11), solute/solid ratio (1.37 × 10 -5 – 8.33 × 10 -4 mol -solute /g -solid ), ionic strengths (0.01 M – 0.7 M), and background electrolytes (Na + , Cs + , Rb + , Cl - , and NO 3 - ) using the same crystal face contribution methodology for site density, capacitance values, and surface acidity constants adopted for proton and cadmium adsorption in previous work (Han and Katz, 2019). Model simulations for a range of background water chemistries demonstrated the potential for Mg 2+ to reduce Cd 2+ adsorption to goethite in model seawater and oil- and gas-produced waters.

42 ENGINEERING↗
DOE OSTI2024

Determining the N -Representability of a Reduced Density Matrix via Unitary Evolution and Stochastic Sampling

The N-representability problem consists in determining whether, for a given p-body matrix, there exists at least one N-body density matrix from which the p-body matrix can be obtained by contraction, that is, if the given matrix is a p-body reduced density matrix (p-RDM). The knowledge of all necessary and sufficient conditions for a p-body matrix to be N-representable allows the constrained minimization of a many-body Hamiltonian expectation value with respect to the p-body density matrix and, thus, the determination of its exact ground state. However, the number of constraints that complete the N-representability conditions grows exponentially with system size, and hence, the procedure quickly becomes intractable for practical applications. This work introduces a hybrid quantum-stochastic algorithm to effectively replace the N-representability conditions. The algorithm consists of applying to an initial N-body density matrix a sequence of unitary evolution operators constructed from a stochastic process that successively approaches the reduced state of the density matrix on a p-body subsystem, represented by a p-RDM, to a target p-body matrix, potentially a p-RDM. The generators of the evolution operators follow the well-known adaptive derivative-assembled pseudo-Trotter method (ADAPT), while the stochastic component is implemented by using a simulated annealing process. The resulting algorithm is independent of any underlying Hamiltonian, and it can be used to decide whether a given p-body matrix is N-representable, establishing a criterion to determine its quality and correcting it. We apply the proposed hybrid ADAPT algorithm to alleged reduced density matrices from a quantum chemistry electronic Hamiltonian, from the reduced Bardeen–Cooper–Schrieffer model with constant pairing, and from the Heisenberg XXZ spin model. In all cases, the proposed method behaves as expected for 1-RDMs and 2-RDMs, evolving the initial matrices toward different targets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Quasi-Classical Trajectory Calculation of Rate Constants Using an Ab Initio Trained Machine Learning Model (aML-MD) with Multifidelity Data

Machine learning (ML) provides a great opportunity for the construction of models with improved accuracy in classical molecular dynamics (MD). However, the accuracy of a ML trained model is limited by the quality and quantity of the training data. Generating large sets of accurate ab initio training data can require significant computational resources. Furthermore, inconsistent or incompatible data with different accuracies obtained using different methods may lead to biased or unreliable ML models that do not accurately represent the underlying physics. Recently, transfer learning showed its potential for avoiding these problems as well as for improving the accuracy, efficiency, and generalization of ML models using multifidelity data. In this work, ab initio trained ML-based MD (aML-MD) models are developed through transfer learning using DFT and multireference data from multiple sources with varying accuracy within the Deep Potential MD framework. Further, the accuracy of the force field is demonstrated by calculating rate constants for the H + HO 2 → H 2 + 3 O 2 reaction using quasi-classical trajectories. We show that the aML-MD model with transfer learning can accurately predict the rate constants while reducing the computational cost by more than five times compared to the use of more expensive quantum chemistry training data sets. Hence, the aML-MD model with transfer learning shows great potential in using multifidelity data to reduce the computational cost involved in generating the training set for these potentials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2000

NCC: A Physics-Based Design and Analysis Tool for Combustion Systems

The National Combustion Code (NCC) is an integrated system of computer codes for physics-based design and analysis of combustion systems. It uses unstructured meshes and runs on parallel computing platforms. The NCC is composed of a set of distinct yet closely related modules. They are: (1) a gaseous flow module solving 3-D Navier-Stokes equations; (2) a turbulence module containing the non-linear k-epsilon models; (3) a chemistry module using either the conventional reduced kinetics approach of solving species equations or the Intrinsic Low Dimensional Manifold (ILDM) kinetics approach of table looking up in conjunction with solving the equations of the progressive variables; (4) a turbulence-chemistry interaction module including the option of solving the joint probability density function (PDF) for species and enthalpy; and (5) a spray module for solving the liquid phase equations. In early 1995, an industry-government team was formed to develop the NCC. In July 1998, the baseline beta version was completed and presented in two NCC sessions at the 34th AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit, July 1998. An overview of this baseline beta version was presented at the NASA HPCCP/CAS Workshop 98, August 1998. Since then, the effort has been focused on the streamlining, validation, and enhancement of the th baseline beta version. The progress is presented in two NCC sessions at the AIAA 38 Aerospace Sciences Meeting & Exhibit, January 2000. At this NASA HPCCP/CAS Workshop 2000, an overview of the NCC papers presented at the AIAA 38 th Aerospace Sciences Meeting & Exhibit is presented, with emphasis on the reduction of analysis time of simulating the (gaseous) reacting flows in full combustors. In addition, results of NCC simulation of a modern turbofan combustor will also be reported.

Liu, Nan-Suey↗
NASA NTRS2018

CFD Predictions of N+3 Cycle Emissions for a Three-Cup Gas-Turbine Combustor

The National Combustion Code (OpenNCC) was used to perform non-reacting and two-phase reacting flow computations for a unique pre-filming type LDI-3 fuel injector for a three-cup, nineteen-element flametube configuration. All computations were performed with a consistent approach of mesh-generation, spray modeling, reduced finite-rate kinetics and turbulence-chemistry interaction, as developed for CFD analysis of single-element and multi-element LDI-3 designs with OpenNCC. Emissions and flowfield characteristics were predicted for a generic NASA N+3 engine cycle, with particular focus on the 7% and 30% ICAO power operating conditions. For both the conditions studied, the CFD analysis provided very good predictions for EINOx when compared with experimental data measured at NASA Glenn Research Center.

injectors↗
DOE OSTI2022

Modeling of the effects of non-equilibrium excitation and electrode geometry on H 2 /air ignition in a nanosecond plasma discharge

In this work, we present the results of two-dimensional modeling of the effects of non-equilibrium excitation and electrode geometry on H 2 /air ignition in a nanosecond plasma discharge. A multiscale adaptive reduced chemistry solver for plasma assisted combustion (MARCS-PAC) based on PASSKEy discharge modeling package and compressible multi-component reactive flow solver ASURF+ is developed and validated. This model is applied to simulate the impact of non-equilibrium plasma excitation and electrode geometry and heat loss on the dynamics of the discharge from streamer to spark and ignition kernel development in a H 2 /air mixture with a pair of cylindrical electrodes. The results show that the plasmagenerated species (N 2 (A), N 2 (B), N 2 (a'), N 2 (C), O( 1 D), O and H) in the spark and afterglow significantly accelerate the ignition kernel development. The increase of discharge voltage at the same total discharge energy promotes the non-equilibrium active species production. It is found that the production of electronically excited species at higher reduced electric field strength is more efficient in enhancing ignition in comparison to the vibrational excitation and heating. Moreover, the 2D simulation clearly reveals that the electric field and active species distribution are highly non-uniform. The streamers are initiated at the sharp outer edges of the negative and positive electrodes by a strong electric field while the electric field is much weaker at the centerline of the electrodes. Furthermore, the simulations reveal that the ignition enhancement is sensitive to the variation of electrode shape, diameter, and gap size due to the changes of electric field distribution and location of streamer formation. A cylindrical electrode produces a larger discharge volume and ignition kernel than the parabolic and spherical electrodes, when the discharge is localized near the axis of the gap. It is found that there is a non-monotonic dependence of ignition kernel size on the electrode diameter and inter-electrode distance. The increase of electrode diameter and gap size above the optimal conditions leads to the reduction of ignition kernel volume, due to the decrease of active species concentration and gas temperature. At a larger electrode surface area and electrode diameter as well as smaller electrode gap size, the heat loss to electrode plays a greater role in reducing the ignition kernel size and slowing ignition kernel development. This work provides insights and guidance to understand the kinetic enhancement of non-equilibrium plasma and the effects of electrode geometries on ignition for the optimization ignitors in advanced engines.

42 ENGINEERING↗
DOE OSTI2022

Modeling rarefied gas chemistry with QuiPS, a novel quasi-particle method

The goal of this work is to build up the capability of quasi-particle simulation (QuiPS), a novel flow solver, such that it can adequately model the rarefied portion of an atmospheric reentry trajectory. Direct simulation Monte Carlo (DSMC) is the conventional solver for such conditions, but struggles to resolve transient flows, trace species, and high-level internal energy states due to stochastic noise. Quasi-particle simulation (QuiPS) is a novel Boltzmann solver that describes a system with a discretized, truncated velocity distribution function. The resulting fixed-velocity, variable weight quasi-particles enable smooth variation of macroscopic properties. The distribution function description enables the use of a variance-reduced collision model, greatly minimizing expense near equilibrium. This work presents the addition of a neutral air chemistry model to QuiPS and some demonstrative 0D simulations. The explicit representation of internal distributions in QuiPS reveals some of the flaws in existing physics models. Overall, variance reduction, a key feature of QuiPS, can greatly reduce expense of multi-dimensional calculations, but is only cheaper when the gas composition is near chemical equilibrium.

42 ENGINEERING↗
NASA NTRSDate not supplied

Aerothermal Analysis of the Dragonfly Titan Entry

The Dragonfly mission will send a rotorcraft lander to the surface of Saturn’s moon Titan as part of the New-Frontiers program. This will be the first spacecraft to land on Titan since the Huygens probe’s descent in January of 2005 and only the second spacecraft to enter Titan’s atmosphere. The Dragonfly entry capsule is significantly larger than the Huygens probe and will experience higher aerothermal environments. This poster will provide an overview of the aerothermodynamic models used in the Dragonfly aeroshell design process. Titan provides a unique entry environment that has several fundamental differences from the environments at the more common entry destinations of Earth and Mars. The lack of atmospheric oxygen significantly reduces heatshield recession (expected to be negligible), which simplifies material response analysis but also reduces the efficiency of the thermal protection system. The atmos-phere is composed of mostly nitrogen and trace amounts of methane. During hypersonic entry this methane dissociates and leads to the formation of the molecule CN, which is known to radiate strongly in the shock layer. Current Dragonfly heating predictions estimate that radiation contributes about 50% of the total heat flux along the forebody and up to 90% on the aftbody, making radiation a key element of aerothermal analysis. To properly address the importance of radiation, a unique radiative-heating correlation was developed that incorporates normal-shock equilibrium chemistry predictions based on work from the Mars 2020 program. These new heating correlations agree well with Computational Fluid Dynamics (CFD) predictions and enable large-scale trajectory analyses by providing rapid heating predictions along candidate trajectories. Dragonfly aerothermal environments are generated with the Data Parallel Line Relaxation (DPLR) finite-volume Navier-Stokes solver alongside the Nonequilibrium Radiative Transport and Spectra (NEQAIR) radiation transport code. DPLR produces shock-aligned flowfields that incorporate the effects of both chemical and thermal nonequilibrium while NEQAIR solves the radiation transport equations along lines-of-sight through the flowfield solutions to predict the radiative heating on the aeroshell. Titan’s atmosphere produces complex thermal and chemical nonequilibria and so classical radiation approximations that extrapolate from a single line-of-sight, such as the Tangent-Slab method, were found to overpredict peak radiative heat fluxes by 10-20%. Therefore, all radiative heating is directly calculated using 3-D transport for both the forebody and aftbody to reduce unnecessary conservatism. A 21-species finite-rate chemistry model, including electrons and ionized species, is used in the CFD to ensure accurate vehicle heating predictions (the level of ionization is particularly for accurate radiative flux predictions). This poster will cover: 1) The models and assumptions used to simulate entry into Titan’s atmosphere, 2) Dragonfly aerothermal engineering correlations alongside statistical heating values, and 3) Driving aerothermal considerations for a Titan entry such as CN formation and radiation-flowfield coupling.

EDL↗
NASA NTRS2011

Seasonal Variations of Stratospheric Age Spectra in GEOSCCM

There are many pathways for an air parcel to travel from the troposphere to the stratosphere, each of which takes different time. The distribution of all the possible transient times, i.e. the stratospheric age spectrum, contains important information on transport characteristics. However, it is computationally very expensive to compute seasonally varying age spectra, and previous studies have focused mainly on the annual mean properties of the age spectra. To date our knowledge of the seasonality of the stratospheric age spectra is very limited. In this study we investigate the seasonal variations of the stratospheric age spectra in the Goddard Earth Observing System Chemistry Climate Model (GEOSCCM). We introduce a method to significantly reduce the computational cost for calculating seasonally dependent age spectra. Our simulations show that stratospheric age spectra in GEOSCCM have strong seasonal cycles and the seasonal cycles change with latitude and height. In the lower stratosphere extratropics, the average transit times and the most probable transit times in the winter/early spring spectra are more than twice as old as those in the summer/early fall spectra. But the seasonal cycle in the subtropical lower stratosphere is nearly out of phase with that in the extratropics. In the middle and upper stratosphere, significant seasonal variations occur in the sUbtropics. The spectral shapes also show dramatic seasonal change, especially at high latitudes. These seasonal variations reflect the seasonal evolution of the slow Brewer-Dobson circulation (with timescale of years) and the fast isentropic mixing (with timescale of days to months).

Li, Feng↗
NASA NTRSDate not supplied

Validated Reduced Computational Methods for Realistic RDC Injection Modeling

This paper outlines a simplified computational method without chemistry for single and multi-injector performance for rotating detonation combustion (RDC) environment as well as relevant performance metrics. For non-reactive cases, an unsteady pressure profile from a Method of Characteristics (MOC) simulation was used to simulate an RDC combustion wave travelling around the annulus. In reactive cases, a pre-mixed stoichiometric mixture of hydrogen and air is injected into a 2D unwrapped combustion chamber with a specified injector area. The performance is evaluated based on several performance metrics including unsteady discharge coefficient, average mass flux coming into the combustor, and percentage time obstructed. Finally, the computational method was validated through an experimental RDC test setup with a single element injector in a hydrogen-air detonation driver environment.

Propulsion↗