Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “ignition prediction”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Asymptotic Analysis of Premixed N-alkane Cool Flame Propagation

A simplified chemical-kinetic cool-flame mechanism for n-alkanes developed recently is applied to premixed laminar cool-flame deflagrations. The present contribution derives the structure of the associated freely propagating cool premixed flame controlled by the low-temperature chemistry and develops formulas for calculating the corresponding laminar burning velocity. Application of activation-energy asymptotics reveals finite-rate chemistry without heat release occurring throughout the preheat zone and leakage of both fuel and oxygen through the thin heat-release zone, there being zones of consumption of an intermediate species on each side of the heat-release zone, thicker than that zone but still thin compared with the preheat-zone thickness. Predicted laminar burning velocities are compared with recently reported measurements for n-dodecane, performed in a newly deigned high-pressure ignition apparatus, resulting in reasonable agreement.

cool flames↗
NASA NTRS1986

Further shock tunnel studies of scramjet phenomena

Scramjet phenomena were studied using the shock tunnel T3 at the Australian National University. Simple two dimensional models were used with a combination of wall and central injectors. Silane as an additive to hydrogen fuel was studied over a range of temperatures and pressures to evaluate its effect as an ignition aid. The film cooling effect of surface injected hydrogen was measured over a wide range of equivalence. Heat transfer measurements without injection were repeated to confirm previous indications of heating rates lower than simple flat plate predictions for laminar boundary layers in equilibrium flow. The previous results were reproduced and the discrepancies are discussed in terms of the model geometry and departures of the flow from equilibrium. In the thrust producing mode, attempts were made to increase specific impulse with wall injection. Some preliminary tests were also performed on shock induced ignition, to investigate the possibility in flight of injecting fuel upstream of the combustion chamber, where it could mix but not burn.

Morgan, R. G.↗
DOE OSTI2025

Investigating performance and variability of NIF ICF experiments with deep learning

The parameter space involved in designing an inertial confinement fusion shot at the National Ignition Facility (NIF) is massively multi-dimensional and the cost of a single shot makes a comprehensive set of sensitivity studies in the laboratory impractical. The use of machine learning to overcome these challenges has gained popularity and has had several successful applications by the scientific community. We extend on these efforts by training a neural network (NN) on information about the experimental design, engineering elements, and drive asymmetry to predict with uncertainty the neutron yield of an experiment. We find the measured and model predicted values are in good agreement, with an R 2 value of 0.91 for a randomly selected test dataset. Almost all the predicted 95% credible intervals contain the corresponding measured value for both training and test datasets. We identify correlations picked up by the NN between the shot design, yield, and variability and use them to motivate shot sensitivity studies. The first shot to exceed the Lawson-like ignition criteria (N210808) was conducted at the NIF and subsequent shots studied the design’s robustness. In a follow-up shot to N210808, our model predicts capsule quality to be the main performance degradation mechanism that prevented the shot from repeating previous performance levels. Shot N221204 was the first shot to exceed a target energy gain of 1. Our model predicts increased yield with reduced coast time for a N221204 study and greater variability for designs with lower peak powers at constant yield. The model’s fast prediction speed and uncertainty prediction are useful for identifying interesting design paths that could warrant further investigation with conventional simulations to search for robust high yield designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1982

Computer program for prediction of capture maneuver probability for an on-off reaction controlled upper stage

A FORTRAN coded computer program which computes the capture transient of a launch vehicle upper stage at the ignition and/or separation event is presented. It is for a single degree-of-freedom on-off reaction jet attitude control system. The Monte Carlo method is used to determine the statistical value of key parameters at the outcome of the event. Aerodynamic and booster induced disturbances, vehicle and control system characteristics, and initial conditions are treated as random variables. By appropriate selection of input data pitch, yaw and roll axes can be analyzed. Transient response of a single deterministic case can be computed. The program is currently set up on a CDC CYBER 175 computer system but is compatible with ANSI FORTRAN computer language. This routine has been used over the past fifteen (15) years for the SCOUT Launch Vehicle and has been run on RECOMP III, IBM 7090, IBM 360/370, CDC6600 and CDC CYBER 175 computers with little modification.

Knauber, R. N.↗
DOE OSTI2020

What fuel properties enable higher thermal efficiency in spark-ignited engines?

The Co-Optimization of Fuels and Engines (Co-Optima) initiative from the US Department of Energy aims to co-develop fuels and engines in an effort to maximize energy efficiency and the utilization of renewable fuels. Many of these renewable fuel options have fuel chemistries that are different from those of petroleum-derived fuels. Because practical market fuels need to meet specific fuel-property requirements, a chemistry-agnostic approach to assessing the potential benefits of candidate fuels was developed using the Central Fuel Property Hypothesis (CFPH). The CFPH states that fuel properties are predictive of the performance of the fuel, regardless of the fuel's chemical composition. In order to use this hypothesis to assess the potential of fuel candidates to increase efficiency in spark-ignition (SI) engines, the individual contributions towards efficiency potential in an optimized engine must be quantified in a way that allows the individual fuel properties to be traded off for one another. This review article begins by providing an overview of the historical linkages between fuel properties and engine efficiency, including the two dominant pathways currently being used by vehicle manufacturers to reduce fuel consumption. Then, a thermodynamic-based assessment to quantify how six individual fuel properties can affect efficiency in SI engines is performed: research octane number, octane sensitivity, latent heat of vaporization, laminar flame speed, particulate matter index, and catalyst light-off temperature. The relative effects of each of these fuel properties is combined into a unified merit function that is capable of assessing the fuel property-based efficiency potential of fuels with conventional and unconventional compositions.

42 ENGINEERING↗
DOE OSTI2022

Octane Requirements of Lean Mixed-Mode Combustion in a Direct-Injection Spark-Ignition Engine

Here, this study investigates the octane requirements of a hybrid flame propagation and controlled autoignition mode referred to as mixed-mode combustion (MMC), which allows for strong control over combustion parameters via a spark-initiated deflagration phase. Due to the throughput limitations associated with both experiments and 3-D computational fluid dynamics calculations, a hybrid 0-D and 1-D modeling methodology was developed, supported by experimental validation data. This modeling approach relied on 1-D, two-zone engine simulations to predict bulk in-cylinder thermodynamic conditions over a range of engine speeds, compression ratios, intake pressures, trapped residual levels, fueling rates, and spark timings. Those predictions were then transferred to a 0-D chemical kinetic model, which was used to evaluate the autoignition behavior of fuels when subjected to temperature–pressure trajectories of interest. Finally, the predicted autoignition phasings were screened relative to the progress of the modeled deflagration-based combustion in order to determine if an operating condition was feasible or infeasible due to knock or stability limits. The combined modeling and experimental results reveal that MMC has an octane requirement similar to modern stoichiometric spark-ignition engines in that fuels with high research octane number (RON) and high octane sensitivity (S) enable higher loads. Experimental trends with varying RON and S were well predicted by the model for 1000 and 1400 rpm, confirming its utility in identifying the compatibility of a fuel’s autoignition behavior with an engine configuration and operating strategy. However, the model was not effective in predicting (nor designed to predict) operability limits due to cycle-to-cycle variations, which experimentally inhibited operation of some fuels at 2000 rpm. Putting the operable limits and efficiency from MMC in the context of a state-of-the-art engine, the MMC showed superior efficiencies over the range investigated, demonstrating the potential to further improve fuel economy.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Model-based compositional predictions for a differential scanning calorimetry/thermogravimetric analysis-mass spectrometry system used for heat of vaporization measurements

A Differential Scanning Calorimetry/Thermogravimetric Analysis (DSC/TGA) procedure for determination of Heat of Vaporization (HOV) of fuel and surrogate fuel mixtures has been previously utilized for evaluation of oxygenate impacts on spark ignition fuels. This analysis has been further leveraged with mass spectrometry (MS) to elucidate vapor phase compositional changes during evaporation. In this study we focus on a simple system of three compounds (ethanol, n-hexane, and n-octane) to provide a model-based understanding of the evaporation process under these experimental conditions. An Aspen Plus model was set up to provide liquid and vapor phase concentration predictions during mixture evaporation using the initial mixture composition, and measured temperature and mass loss profiles from DSC/TGA experiments. Agreements between the trends of the MS ion count profiles and model composition predictions provide a degree of validation of this modeling approach that can allow the interpretation and extrapolation of DSC/TGA measurements for more complex fuel mixtures.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

On the importance of species immiscibility in mixing-layer dynamics at supercritical pressures

The mixing dynamics of injected propellants is a key factor in determining the ignition performance and combustion-instability response of rocket engines, internal combustion engines, and gas turbines. A key source of uncertainty in the prediction of phase-exchange dynamics is the immiscibility of the injected propellants at supercritical pressure conditions, which induces liquid/vapor phase separation and surface-tension dynamics. While experimental observations indicate the presence of liquid/vapor interfacial structures, this interfacial dynamics is typically neglected in numerical analyses. To address this issue, the objective of the present study is to systematically evaluate the importance of species immiscibility on the phase-exchange dynamics of cryogenic LOX/GH2 mixing layers at typical rocket engine injection conditions. This is accomplished by comparing simulations of (i) a recently developed interface-capturing Regularized-Interface Method (RIM) formulation, and (ii) the commonly employed Diffuse-Interface Method (DIM) formulation. Analysis shows that the interfacial dynamics significantly impact the atomization and mixing of the propellants in the near-injector region, which is not captured by the DIM formulation. The findings of this study extend to other immiscible injection systems, such as LOX/kerosene and hydrocarbon-fuel/air, thereby highlighting the importance of resolving species immiscibility in simulating high-pressure combustion engines.

diffused-interface method↗
NASA NTRS1972

Apollo 14 mission report. Supplement 5: Descent propulsion system final flight evaluation

The performance of the LM-8 descent propulsion system during the Apollo 14 mission was evaluated and found to be satisfactory. The average engine effective specific impulse was 0.1 second higher than predicted, but well within the predicted l sigma uncertainty. The engine performance corrected to standard inlet conditions for the FTP portion of the burn at 43 seconds after ignition was as follows: thrust, 9802, lbf; specific impulse, 304.1 sec; and propellant mixture ratio, 1603. These values are + or - 0.8, -0.06, and + or - 0.3 percent different respectively, from the values reported from engine acceptance tests and were within specification limits.

Avvenire, A. T.↗
NASA NTRS2012

Failure Mode Analysis of V-Shaped Pyrotechnically Actuated Valves

Current V-shaped stainless steel pyrovalve initiators have rectified many of the deficiencies of the heritage Y-shaped aluminum design. However, a credible failure mode still exists for dual simultaneous initiator (NSI) firings in which low temperatures were detected at the booster cap and less consistent ignition was observed than when a single initiator was fired. In order to asses this issue, a numerical framework has been developed for predicting the flow through pyrotechnically actuated valves. This framework includes a fully coupled solution of the gas-phase equation with a non-equilibrium dispersed phase for solid particles as well as the capability to model conjugate gradient heat transfer to the booster cap. Through a hierarchy of increasingly complex simulations, a hypothesis for the failure mode of the nearly simultaneous dual NSI firings has been proven. The simulations indicate that the failure mode for simultaneous dual NSI firings may be caused by flow interactions between the flame channels. The shock waves from each initiator interact in the booster cavity resulting in a high pressure that prevents the gas and particulate velocity from rising in the booster cap region. This impedes the bulk of the particulate phase from impacting the booster cap and reduces the heat transfer to the booster cap since the particles do not impact it. Heat transfer calculations to the solid metal indicate that gas-phase convective heat transfer may not be adequate by itself and that energy transfer from the particulate phase may be crucial for the booster cap burn through.

Sachdev, Jai S.↗
DOE OSTI2020

Sooting tendencies of 20 bio-derived fuels for advanced spark-ignition engines

The sooting tendencies of 20 bio-derived fuels indicated as potential blendstocks for spark-ignition engines by the Co-Optimization of Fuels & Engines (Co-Optima) Initiative are studied. The Yield Sooting Index (YSI) is used to quantify the sooting tendencies. The Co-Optima Chemical Model is used to predict the numerical YSIs for all test fuels, and these results are compared with measurements. Experimental YSIs are newly measured for 2 furans and are taken from our previous work for the other compounds. Overall, the predicted YSIs agree well with measurements, within the experimental uncertainties, except for 2,5-dimethylfuran (2,5-DMF). It is found that Polycyclic Aromatic Hydrocarbons (PAH) growth reactions have little influence on the relative soot production from each fuel and therefore on YSI predictions. A modified sensitivity coefficient formulation is proposed to evaluate reaction sensitivities specifically for YSI. This formulation is applied to the 2,5-DMF-doped flame, and six 2,5-DMF initial decomposition reactions, which lead to different major soot precursors, are identified as the most sensitive reactions. The impact of the chemical kinetic uncertainties embedded in these reactions is quantified by randomly perturbing their reaction rates within a factor of two. The resulting prediction uncertainty in the 2,5-DMF-doped flame is found to be ± 8 YSI units (±11%), which demonstrates that the test-fuel-specific decomposition reactions indeed have considerable influence on its YSI prediction. Our research suggests that more accurate kinetic parameters for fuel initial decomposition reactions can potentially improve YSI predictions effectively, without altering the YSI predictions of other fuels with significantly different molecular structures.

09 BIOMASS FUELS↗
NASA NTRS2020

Ignition and Burn in a Hybrid Nuclear Fuel for a Pulsed Rocket Engine

This work explores the parameter space of a cylindrical hybrid nuclear fuel in support of a z-pinch driven pulsed fission-fusion (PuFF) engine. 0D power balance and 1D burn wave calculations have been performed to explore the parameter space of hybrid cylindrical nuclear fuels. The boundary of minimal initial conditions needed to reach breakeven are found within the context of the model. The effects of initial conditions upon the yield at the end of burn wave expansion are also determined. The model is used to examine the minimum initial energies predicted to result in yields of a few MJ. The goal of this work is to guide fuel design, inform future models and experiments as well as look for the most efficient parameter space for ignition in a z-pinch driven hybrid nuclear reaction. The impact of initial parameters upon ignition, burn, and gain are discussed. It is found that a hybrid cylindrical target may breakeven with initial energy near the axis of approximately 4 to 6 MJ in lithium deuteride/uranium 235 fuel. It is also found that magnetic field can lower the threshold further of which the magnitude changes across the parameter space. The dual fusion/fission reactions are found to boost each other leading to lower initial driving energies needed to reach breakeven in the hybrid cylindrical nuclear fuel.

fission↗
NASA NTRS1984

A comprehensive model to determine the effects of temperature and species fluctuations on reaction rates in turbulent reaction flows

The use of silane (SiH4) as an effective ignitor and flame stabilizing pilot fuel is well documented. A reliable chemical kinetic mechanism for prediction of its behavior at the conditions encountered in the combustor of a SCRAMJET engine was calculated. The effects of hydrogen addition on hydrocarbon ignition and flame stabilization as a means for reduction of lengthy ignition delays and reaction times were studied. The ranges of applicability of chemical kinetic models of hydrogen-air combustors were also investigated. The CHARNAL computer code was applied to the turbulent reaction rate modeling.

Magnotti, F.↗
NASA NTRS2005

Transient Catalytic Combustor Model With Detailed Gas and Surface Chemistry

In this work, we numerically investigate the transient combustion of a premixed gas mixture in a narrow, perfectly-insulated, catalytic channel which can represent an interior channel of a catalytic monolith. The model assumes a quasi-steady gas-phase and a transient, thermally thin solid phase. The gas phase is one-dimensional, but it does account for heat and mass transfer in a direction perpendicular to the flow via appropriate heat and mass transfer coefficients. The model neglects axial conduction in both the gas and in the solid. The model includes both detailed gas-phase reactions and catalytic surface reactions. The reactants modeled so far include lean mixtures of dry CO and CO/H2 mixtures, with pure oxygen as the oxidizer. The results include transient computations of light-off and system response to inlet condition variations. In some cases, the model predicts two different steady-state solutions depending on whether the channel is initially hot or cold. Additionally, the model suggests that the catalytic ignition of CO/O2 mixtures is extremely sensitive to small variations of inlet equivalence ratios and parts per million levels of H2.

Struk, Peter M.↗
DOE OSTI2025

ELM2.1-XGBfire1.0: improving wildfire prediction by integrating a machine learning fire model in a land surface model

Wildfires have shown increasing trends in both frequency and severity across the contiguous United States (CONUS). However, process-based fire models have difficulties in accurately simulating the burned area over the CONUS due to a simplification of the physical process and cannot capture the interplay among fire, ignition, climate, and human activities. The deficiency of burned area simulation deteriorates the description of fire impact on energy balance, water budget, and carbon fluxes in the Earth system models (ESMs). Alternatively, fire models based on machine learning (ML), which capture statistical relationships between the burned area and environmental factors, have shown promising burned area predictions and corresponding fire impact simulation. We develop a hybrid framework (ELM2.1-XGBFire1.0) that integrates an eXtreme Gradient Boosting (XGBoost) wildfire model with the Energy Exascale Earth System Model (E3SM) land model (ELM) version 2.1. A Fortran–C–Python deep learning bridge is adapted to support online communication between ELM and the ML fire model. Specifically, the burned area predicted by the ML-based wildfire model is directly passed to ELM to adjust the carbon pool and vegetation dynamics after disturbance, which are then used as predictors in the ML-based fire model in the next time step. Evaluated against the historical burned area from Global Fire Emissions Database 5 from 2001–2019, the ELM2.1-XGBFire1.0 outperforms process-based fire models in terms of spatial distribution and seasonal variations. The ELM2.1-XGBFire1.0 has proven to be a new tool for studying vegetation–fire interactions and, more importantly, enables seamless exploration of climate–fire feedback, working as an active component of E3SM.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Improving North American Wildfire Prediction by Integrating a Machine-Learning Fire Model in a Land Surface Model

Wildfires have shown increasing trends in both frequency and severity across the Contiguous United States (CONUS). However, process-based fire models have difficulties in accurately simulating the burned area over the CONUS due to a simplification of the physical process and cannot capture the interplay among fire, ignition, climate, and human activities. The deficiency of burned area simulation deteriorates the description of fire impact on energy balance, water budget, and carbon fluxes in the Earth System Models (ESMs). Alternatively, machine learning (ML) based fire models, which capture statistical relationships between the burned area and environmental factors, have shown promising burned area predictions and corresponding fire impact simulation. We develop a hybrid framework (ML4Fire-XGB) that integrates a pretrained eXtreme Gradient Boosting (XGBoost) wildfire model with the Energy Exascale Earth System Model (E3SM) land model (ELM) version 2.1. A Fortran-C-Python deep learning bridge is adapted to support online communication between ELM and the ML fire model. Specifically, the burned area predicted by the ML-based wildfire model is directly passed to ELM to adjust the carbon pool and vegetation dynamics after disturbance, which are then used as predictors in the ML-based fire model in the next time step. Evaluated against the historical burned area from Global Fire Emissions Database 5 from 2001-2020, the ML4Fire-XGB model outperforms process-based fire models in terms of spatial distribution and seasonal variations. Sensitivity analysis confirms that the ML4Fire-XGB well captures the responses of the burned area to rising temperatures. The ML4Fire-XGB model has proved to be a new tool for studying vegetation-fire interactions, and more importantly, enables seamless exploration of climate-fire feedback, working as an active component in E3SM.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2024

Reliable Ignition of LOX-LCH4 Propellants

No cryogenic Reaction Control System (RCS) has ever flown in space. Cryogenic propellants are baselined by HLS and CLPS partners and are the key use case for future ISRU manufactured propellants. A reliable LOX/LCH 4 RCS is an enabling technology for human Lunar and Mars exploration. In previous thermal vacuum (<275 F, <10 torr) testing at NASA GRC Plum Brook, the team uncovered anomalous LOX/LCH4 engine ignition phenomena where flame kernels quenched at these ultra cold hardware temperatures, leading to many pulses where the engines would not light. In 2022, the project was able to recreate the no light condition with an upgraded Frost-Mint test stand at JSC. This project implemented test stand improvements and procured propellants and follow on engine components for a hot fire campaign beginning in November 2024 which will attempt to ignite the RCS engine at ultra cold vacuum conditions by modifying the engine mixture ratio. New modeling techniques were implemented to account for past no lights and are an enabling method to make lunar surface go no go predictions based on hardware conditions. This was enabled by significant improvements to the Frost Mint system, which reduced moisture build up and leaks, increased propellant availability, leading to more attempts at thermal vacuum hot-fires.

Propulsion↗
DOE OSTI2024

LES and RANS Spray Combustion Analysis of OME 3-5 and n-Dodecane

Clean-burning oxygenated and synthetic fuels derived from renewable power, so-called e-fuels, are a promising pathway to decarbonize compression–ignition engines. Polyoxymethylene dimethyl ethers (PODEs or OMEs) are one candidate of such fuels with good prospects. Their lack of carbon-to-carbon bonds and high concentration of chemically bound oxygen effectively negate the emergence of polycyclic aromatic hydrocarbons (PAHs) and even their precursors like acetylene (C 2 H 2 ), enabling soot-free combustion without the soot-NO x trade-off common for diesel engines. The differences in the spray combustion process for OMEs and diesel-like reference fuels like n-dodecane and their potential implications on engine applications include discrepancies in the observed ignition delay, the stabilized flame lift-off location, and significant deviations in high-temperature flame morphology. For CFD simulations, the accurate modeling and prediction of these differences between OMEs and n-dodecane proved challenging. This study investigates the spray combustion process of an OME 3 − 5 mixture and n-dodecane with advanced optical diagnostics, Reynolds-Averaged Navier–Stokes (RANS), and Large-Eddy Simulations (LESs) within a constant-volume vessel. Cool-flame and high-temperature combustion were measured simultaneously via high-speed (50 kHz) imaging with formaldehyde (CH 2 O) planar laser-induced fluorescence (PLIF) representing the former and line-of-sight OH* chemiluminescence the latter. Both RANS and LES simulations accurately describe the cool-flame development process with the formation of CH 2 O. However, CH 2 O consumption and the onset of high-temperature reactions, signaled by the rise of OH* levels, show significant deviations between RANS, LES, and experiments as well as between n-dodecane and OME. A focus is set on the quality of the simulated results compared to the experimentally observed spatial distribution of OH*, especially in OME fuel-rich regions. The influence of the turbulence modeling is investigated for the two distinct ambient temperatures of 900 K and 1200 K within the Engine Combustion Network Spray A setup. The capabilities and limitations of the RANS simulations are demonstrated with the initial cool-flame propagation and periodic oscillations of CH 2 O formation/consumption during the quasi-steady combustion period captured by the LES.

CFD↗