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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.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Prediction of Launch Vehicle Ignition Overpressure and Liftoff Acoustics

The LAIOP (Launch Vehicle Ignition Overpressure and Liftoff Acoustic Environments) program predicts the external pressure environment generated during liftoff for a large variety of rocket types. These environments include ignition overpressure, produced by the rapid acceleration of exhaust gases during rocket-engine start transient, and launch acoustics, produced by turbulence in the rocket plume. The ignition overpressure predictions are time-based, and the launch acoustic predictions are frequency-based. Additionally, the software can predict ignition overpressure mitigation, using water-spray injection into the rocket exhaust stream, for a limited number of configurations. The framework developed for these predictions is extensive, though some options require additional relevant data and development time. Once these options are enabled, the already extensively capable code will be further enhanced. The rockets, or launch vehicles, can either be elliptically or cylindrically shaped, and up to eight strap-on structures (boosters or tanks) are allowed. Up to four engines are allowed for the core launch vehicle, which can be of two different types. Also, two different sizes of strap-on structures can be used, and two different types of booster engines are allowed. Both tabular and graphical presentations of the predicted environments at the selected locations can be reviewed by the user. The output includes summaries of rocket-engine operation, ignition overpressure time histories, and one-third octave sound pressure spectra of the predicted launch acoustics. Also, documentation is available to the user to help him or her understand the various aspects of the graphical user interface and the required input parameters.

Casiano, Matthew↗
DOE OSTI2021

Autoignition of Premixed Liquefied Petroleum Gas in a Rapid Compression Machine: Experimental Results and Chemical Kinetic Mechanism Reduction

Liquefied petroleum gas (LPG) has many properties that make it an attractive alternative fuel such as lower cost than conventional fuels and an established distribution infrastructure. The development of high efficiency, spark ignited LPG engines is currently limited by engine knock and misfire. The knock and misfire limits are further complicated by the wide range of chemical reactivity in LPG, particularly in international markets. In this study, a rapid compression machine (RCM) was used to characterize the effects of variation in LPG fuel reactivity, equivalence ratio, and exhaust gas recirculation (EGR) on autoignition of LPG/oxidizer/inert/EGR blends. Experiments were conducted with 100% propane (C3H8) and blends of propane with propene, ethane, isobutane, and n-butane. EGR was simulated with mixtures of Ar, CO2, CO, and NO at substitution percentages from 0 to 30 mass percent. Equivalence ratio was varied from 0.75 to 1.5. Ignition delay period under homogeneous autoignition conditions was measured at compressed pressures and temperatures of 23 to 25 bar and 701 to 921 K, respectively. Zero-dimensional simulations of the RCM experiments were performed using Chemkin with several detailed chemical kinetic mechanisms to determine their suitability at predicting ignition delay periods. Multiple reduced chemical kinetic mechanisms were created from the NUIGMech1.1 mechanism to determine the optimal balance between accuracy and computational efficiency for future three-dimensional, time-dependent spark-ignited engine computations.

42 ENGINEERING↗
NASA NTRS2012

Development of Modeling Capabilities for Launch Pad Acoustics and Ignition Transient Environment Prediction

This paper presents development efforts to establish modeling capabilities for launch vehicle liftoff acoustics and ignition transient environment predictions. Peak acoustic loads experienced by the launch vehicle occur during liftoff with strong interaction between the vehicle and the launch facility. Acoustic prediction engineering tools based on empirical models are of limited value in efforts to proactively design and optimize launch vehicles and launch facility configurations for liftoff acoustics. Modeling approaches are needed that capture the important details of the plume flow environment including the ignition transient, identify the noise generation sources, and allow assessment of the effects of launch pad geometric details and acoustic mitigation measures such as water injection. This paper presents a status of the CFD tools developed by the MSFC Fluid Dynamics Branch featuring advanced multi-physics modeling capabilities developed towards this goal. Validation and application examples are presented along with an overview of application in the prediction of liftoff environments and the design of targeted mitigation measures such as launch pad configuration and sound suppression water placement.

West, Jeff↗
DOE OSTI2023

Investigating boosted decision trees as a guide for inertial confinement fusion design

Inertial confined fusion experiments at the National Ignition Facility have recently entered a new regime approaching ignition. Improved modeling and exploration of the experimental parameter space were essential to deepening our understanding of the mechanisms that degrade and amplify the neutron yield. The growing prevalence of machine learning in fusion studies opens a new avenue for investigation. Here in this paper, we have applied the Gradient-Boosted Decision Tree machine-learning architecture to further explore the parameter space and find correlations with the neutron yield, a key performance indicator. We find reasonable agreement between the measured and predicted yield, with a mean absolute percentage error on a randomly assigned test set of 35.5%. This model finds the characteristics of the laser pulse to be the most influential in prediction, as well as the hohlraum laser entrance hole diameter and an enhanced capsule fabrication technique. We used the trained model to scan over the design space of experiments from three different campaigns to evaluate the potential of this technique to provide design changes that could improve the resulting neutron yield. While these data-driven model cannot predict ignition without examples of ignited shots in the training set, it can be used to indicate that an unseen shot design will at least be in the upper range of previously observed neutron yields.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Autoignition Delay Time Measurements and Chemical Kinetic Modeling of Hydrogen/Ammonia/Natural Gas Mixtures

Abstract In recent years, hydrogen-carrying compounds have accrued interest as an alternative to traditional fossil fuels due to their function as zero-emission fuels. As such, there is interest in investigating hydrogen-carrying compounds to improve understanding of the fuels’ characteristics for use in high-pressure systems. In the current study, the oxidation of ammonia/natural gas/hydrogen mixtures was carried out to study CO formation profiles as well as the ignition delay times behind reflected shock waves in order to refine chemical kinetic models. Experiments were carried out in the University of Central Florida’s shock tube facility by utilizing chemiluminescence to obtain OH* emission and laser absorption spectroscopy to obtain CO profiles. Experimental results were then compared with the GRI 3.0 mechanism, as well as the proprietary UCF 2022 mechanism utilizing CHEMKIN-Pro software. In general, both models were able to capture the trend in autoignition delay times and CO time histories for natural gas and ammonia mixtures. However, for ammonia-hydrogen mixtures, GRI 3.0 failed to predict ignition delay times whereas the UCF 2022 mechanism was able to capture the IDTs within the uncertainty limits of the experiments. A sensitivity analysis was conducted for different mixtures to understand the important reactions at the experimental conditions. Finally, a reaction pathway analysis was carried out to understand important ammonia decomposition pathways in the presence of hydrogen and natural gas.

Baker, Jessica B.↗
DOE OSTI2020

An extended methodology for automated calculations of non-Boltzmann kinetic sequences: H + C 2 H 2 + X and combustion impact

It is generally assumed in phenomenological kinetic models that bimolecular reactions only occur between species whose rovibrational energy follows a Boltzmann (thermal) distribution. That is, any complexes initially formed in non-Boltzmann distributions are assumed to be thermalized by energy-transferring collisions prior to bimolecular reactions. Given the high mole fractions of reactive species, X, in combustion environments, reactive collisions of the complexes with X often occur on the same timescale as energy-transferring collisions – yielding sequences proceeding through non-Boltzmann intermediates across multiple potential energy surfaces. Recent studies have shown that such non-Boltzmann kinetic sequences can have substantial impact on the global reactivity in combustion systems. Simulations of these non-Boltzmann reaction sequences, which can be described in phenomenological kinetic models via chemically termolecular reactions, require that rovibrational excitation from one potential energy surface be carried over to the next. Here this paper presents an extended theoretical and computational methodology that couples multiple master equations and derives rate constants for phenomenological reactions describing the conversion of thermal reactants to thermal products for use in phenomenological kinetic schemes. The methodology is then implemented using in-house scripts for non-Boltzmann sequences involving C2H$^*_3$ + X (with X = O 2 , H, and OH) where C 2 H$^*_3$ is formed via H + C 2 H 2 association – which were identified as having strong potential for influencing combustion predictions in a recent study. The results reveal that non-Boltzmann reaction sequences for X = O 2 (the primary focus of this paper) significantly alters the total conversion rate from H + C 2 H 2 to products and product branching fractions from those of thermal sequential pathways. Furthermore, the present results demonstrate that non-Boltzmann reaction sequences have significant impact – as high as an order of magnitude – on predicted ignition delay times. Similarly, they yield significantly different dependence of ignition delay times with temperature and O 2 mole fraction – yielding signatures that are likely observable experimentally.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

From electronic structure to model application of key reactions for gasoline/alcohol combustion: Hydrogen-atom abstraction by $CH_3O\dot{O}$ radicals

Hydrogen atom abstraction by methyl peroxy ($CH_3O\dot{O}$) radicals can play an important role in gasoline/ethanol interacting chemistry for fuels that produce high concentrations of methyl radicals. Detailed kinetic reactions for hydrogen atom abstraction by $CH_3O\dot{O}$ radicals from the components of FGF-LLNL (a gasoline surrogate) including cyclopentane, toluene, 1-hexene, n -heptane, and isooctane have been systematically studied in this work. Here, the M06-2X/6-311 ++ G(d,p) level of theory was used to obtain the optimized structure and vibrational frequency for all stationary points and the low-frequency torsional modes. The 1-D hindered rotor treatment for low-frequency torsional modes was treated at M06-2X/6-31G level of theory. The UCCSD(T)-F12a/cc-pVDZ-F12 and QCISD(T)/CBS level of theory were used to calculate single point energies for all species. High pressure limiting rate constants for all hydrogen atom abstraction channels were performed using conventional transition state theory with unsymmetric tunneling corrections. Individual rate constants are reported in the temperature range from 298.15 to 2000 K. Our computed results show that the abstraction of allylic hydrogen atoms from 1-hexene is the fastest at low temperatures. When the temperature increases, the hydrogen atom abstraction reaction channel at the primary alkyl site gradually becomes dominant. Thermodynamics properties for all stable species and high-pressure limiting rate constants for each reaction pathway obtained in this work were incorporated into the latest gasoline surrogate/ethanol model to investigate the influence of the rate constants calculated here on model predicted ignition delay times.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1974

The role of thermal contact resistance in pyrotechnic ignition

This paper describes a pyrotechnic ignition model based on transient heat conduction from a heated bridgewire to a pyrotechnic that is placed in contact with it. The boundary condition used at the interface was a thermal contact conductance estimated at 31,200 W per sq m-K between the wire and the pyrotechnic. Ignition was assumed to occur when a 2.5-micron layer of pyrotechnic next to the bridgewire reached a critical ignition temperature. The times to ignition predicted by this model for constant current firings were in good agreement with experimentally observed times to fire at 3.5- and 5-ampere current levels and ambient temperatures from 144 K to 366 K.

Sernas, V.↗
DOE OSTI2025

Toward an improved nonlocal thermodynamic equilibrium model for more predictive simulations of ignition scale hohlraums

Recently, nonlocal thermodynamic equilibrium (NLTE) modeling has been identified as the primary reason for discrepant predictions of the peak neutron production time in indirectly driven inertial confinement fusion (ICF) platforms. It has also been observed that predictions of collisional excitation rates differ by as much as 50% from measurements. Theoretical uncertainties in dielectronic recombination rates have also been posited as possibly contributing to errors in NLTE predictions. This work examines the impact of multipliers on collisional excitation and dielectronic recombination rates on simulations of a directly driven gold sphere and an indirect drive ICF implosion. It is found that multipliers on the collisional excitation rates have a strong impact on radiant intensity and electron temperature and a weaker impact on ionization state, whereas multipliers on dielectronic recombinations rates strongly impact ionization state with a smaller impact on radiant intensity and electron temperature. A self-consistent NLTE model which places multipliers on differing transitions, as motivated by experimental measurements and more detailed atomic physics predictions, improves agreement but does not completely eliminate discrepancies with measurements of the radiant intensity within the 2–4 keV spectral range.

Farmer, W. A. [Lawrence Livermore National Laborat↗
DOE OSTI2024

Understanding the deficiency in inertial confinement fusion hohlraum x-ray flux predictions using experiments at the National Ignition Facility

The predicted implosion performance of deuterium-tritium fuel capsules in indirect-drive inertial confinement fusion experiments relies on precise calculations of the x-ray drive in laser-heated cavities (hohlraums). This requires accurate, spectrally dependent simulations of laser to x-ray conversion efficiencies and x-ray absorption losses to the hohlraum wall. A set of National Ignition Facility experiments have identified a cause for the long-standing hohlraum “drive deficit” as the overprediction of gold emission at ~2.5 keV in nonlocal thermodynamic equilibrium coronal plasma regions within the hohlraum. Finally, reducing the emission and absorption opacity in this spectral region by ~20% brings simulations into agreement with measured x-ray fluxes and spectra.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Cookoff of Powdered and Pressed Explosives using a Micromechanics Pressurization Model

Cookoff experiments of powdered and pressed TATB-based plastic bonded explosives (PBXs) have been modeled using a pressure-dependent universal cookoff model (UCM) in combination with a micromechanics pressurization (MMP) model described in a companion paper. The MMP model is based on the accumulation of decomposition gases at nucleation sites that load the surrounding TATB crystals and binder. This is the first cookoff model to use an analytical mechanics solution for compressibility and thermal expansion to describe internal pressurization caused by both temperature and decomposition occurring within closed-pore explosives. This approach produces more accurate predictions of ignition time and pressurization within high-density explosives than simple equation-of-state models. The current paper gives details of the reaction chemistry, model parameters, predicted uncertainty, and validation using experiments from multiple laboratories with errors less than 6 %. The UCM/MMP model framework gives more accurate thermal ignition predictions for high density explosives that are initially impermeable to decomposition gases.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

Machine learning and artificial intelligence for wildfire prediction

Wildfire ignition, intensity, and spread rates are tightly linked with water cycle extremes. The science of wildfire prediction has traditionally encompassed the use of physical and empirical models to quantify the direction and speed of fire spread, plume injection and fire-aerosol impacts on atmospheric composition, predictions of fire season severity on subseasonal-to-seasonal (S2S) time scales, and assessment of the spatial and temporal patterns of fire risk across landscapes. Together with expanding observation networks, machine learning and artificial intelligence (AI) have the potential to revolutionize the application of such models for fire science, saving lives, protecting critical infrastructure, and providing more accurate estimates of wildfire-climate feedbacks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Data-driven prediction of scaling and ignition of inertial confinement fusion experiments

Recent advances in inertial confinement fusion (ICF) at the National Ignition Facility (NIF), including ignition and energy gain, are enabled by a close coupling between experiments and high-fidelity simulations. Neither simulations nor experiments can fully constrain the behavior of ICF implosions on their own, meaning pre- and postshot simulation studies must incorporate experimental data to be reliable. Linking past data with simulations to make predictions for upcoming designs and quantifying the uncertainty in those predictions has been an ongoing challenge in ICF research. We have developed a data-driven approach to prediction and uncertainty quantification that combines large ensembles of simulations with Bayesian inference and deep learning. The approach builds a predictive model for the statistical distribution of key performance parameters, which is jointly informed by past experiments and physics simulations. The prediction distribution captures the impact of experimental uncertainty, expert priors, design changes, and shot-to-shot variations. We have used this new capability to predict a 10× increase in ignition probability between Hybrid-E shots driven with 2.05 MJ compared to 1.9 MJ, and validated our predictions against subsequent experiments. We describe our new Bayesian postshot and prediction capabilities, discuss their application to NIF ignition and validate the results, and finally investigate the impact of data sparsity on our prediction results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1987

Spark Ignition of Monodisperse Fuel Sprays

A study of spark ignition energy requirements was conducted with a monodisperse spray system allowing independent control of droplet size, equivalent ratio, and fuel type. Minimum ignition energies were measured for n-heptane and methanol sprays characterized at the spark gap in terms of droplet diameter, equivalence ratio (number density) and extent of prevaporization. In addition to sprays, minimum ignition energies were measured for completely prevaporized mixtures of the same fuels over a range of equivalence ratios to provide data at the lower limit of droplet size. Results showed that spray ignition was enhanced with decreasing droplet size and increasing equivalence ratio over the ranges of the parameters studied. By comparing spray and prevaporized ignition results, the existence of an optimum droplet size for ignition was indicated for both fuels. Fuel volatility was seen to be a critical factor in spray ignition. The spray ignition results were analyzed using two different empirical ignition models for quiescent mixtures. Both models accurately predicted the experimental ignition energies for the majority of the spray conditions. Spray ignition was observed to be probabilistic in nature, and ignition was quantified in terms of an ignition frequency for a given spark energy. A model was developed to predict ignition frequencies based on the variation in spark energy and equivalence ratio in the spark gap. The resulting ignition frequency simulations were nearly identical to the experimentally observed values.

Danis, Allen M.↗
DOE OSTI2020

Simulated production of OH, HO 2 , CH 2 O, and CO 2 during dilute fuel oxidation can predict 1st-stage ignition delays

Chemical kinetics simulations are used to explore whether detailed measurements of relevant chemical species during the oxidation of very dilute fuels (less than 1 Torr partial pressure) in a high-pressure plug flow reactor (PFR) can predict autoignition propensity. We find that for many fuels the timescale for the onset of spontaneous oxidation in dilute fuel/air mixtures in a simple PFR is similar to the 1st-stage ignition delay time (IDT) at stoichiometric engine-relevant conditions. For those fuels that deviate from this simple trend, the deviation is closely related to the peak rate of production of OH, HO 2 , CH 2 O, and CO 2 formed during oxidation. We use these insights to show that an accurate correlation between simulated profiles of these species in a PFR and 1st-stage IDT can be developed using convolutional neural networks. Our simulations suggest that the accuracy of such a correlation is 10–50%, which is appropriate for rapid fuel screening and may be sufficient for predictive fuel performance modeling.

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

Predictability of Gaseous Impact Ignition Sensitivity from Autoignition Temperature Data

An analysis of cumulative binomial probabilities for a quantal-type test like ASTM G74 indicates that for a probability of reaction in a single trial of 0.05, the probability of obtaining zero reactions in 20 trials is only approximately 36 percent, Because the lack of precision with the ASTM G74 test logic could be potentially misleading, an investigation was conducted to determine if pneumatic impact sensitivity could be predicted more reliably from other, more precise test methods. Pneumatic impact sensitivity tests were conducted following ASTM G74, but employing more rigorous test logics; autoignition temperature tests were conducted per ASTM G72. Polytetrafluoroethylene (PTFE), Viton A, polyethylene, polyoxymethylene polyamide, and silicone were the polymers used. After a fixed number of pneumatic impact tests was performed at set pressures, a plot of reaction frequency over a 3.4 to 24.1 MPa impact pressure range indicated that PTFE, Viton A, and silicone would outperform other polymers. The 50 percent pneumatic impact reactivity level was determined with the Bruceton test method. The data obtained resulted in a strong correlation between the 50 percent reactivity level and the autoignition temperature of polymers, indicating similar ignition mechanisms.

Hirsh, David↗
NASA NTRS1985

Ignition of mixtures of SiH sub 4, CH sub 4, O sub 2, and Ar or N sub 2 behind reflected shock waves

Ignition delay times in mixtures of methane, silane, and oxygen diluted with argon and nitrogen were measured behind reflected shock waves generated in the chemical kinetic shock tube at Langley Research Center. The delay times were inferred from the rapid increase in pressure that occurs at ignition, and the ignition of methane was verified from the emission of infrared radiation from carbon dioxide. Pressures of 1.25 atm and temperatures from 1100 K to 1300 K were generated behind the reflected shocks; these levels are representative of those occurring within a supersonic Ramjet combustor. Expressions for the ignition delay time as a function of temperature were obtained from least squares curve fits to the data for overall equivalence ratios of 0.7 and 1.0. The ignition delay times with argon as the diluent were longer than those with nitrogen as the diluent. The infrared wavelength observations at 4.38 microns for carbon dioxide indicated that silane and methane ignited simultaneously (i.e., within the time resolution of the measurement). A combined chemical kinetic mechanism for mixtures of silane, methane, oxygen, and argon or nitrogen was assembled from one mechanism that accurately predicted the ignition of methane and a second mechanism that accurately predicted silane hydrogen ignition. Comparisons between this combined mechanism and experiment indicated that additional reactions, possibly between silyl and methyl fragments, are needed to develop a good silane methane mechanism.

Mclain, A. G.↗