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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A statistical model to predict ignition probability

Ignition capability is a critical design constraint for aeronautical gas turbines. However the current trend toward overall lean burn is detrimental to the engine ignition and relight and the ignition system must be adapted to ensure a fast and reliable light-round in all circumstances. As ignition is a stochastic phenomenon, the optimization of an ignition system requires to build ignition probability maps, which is difficult and costly with either experiment or numerical simulation as both require many tests. Here, this work proposes a model to predict the ignition probability map, knowing only flow statistics in non-reacting conditions, i.e., with only one test. The originality of the model is to construct statistics of the flame kernel trajectory, which are then combined with local flow indicators to evaluate the ignition probability at the considered sparking location. Application to a swirled burner operated in premixed, non-premixed and spray combustion modes illustrates the model concepts and demonstrates its ability to recover the experimental ignition map with good accuracy.

42 ENGINEERING↗
NASA NTRSDate not supplied

Particle Impact Simulation and Ignition Prediction

An experimentally calibrated tool is needed to predict if a system is susceptible to failure by particle impact ignition (PI) based on use conditions, materials, and flow geometry. This tool will accelerate new components, evaluating existing hardware, and help disposition anomalies. Conduct particle impact testing with in-situ diagnostics and complementary simulations on subset of key engineering materials (IN718, M400, 316L, 6061, Ti64, Zr) to develop a proof-of-concept predictive tool for assessing the risk of PI for idealized geometries (spherical particles) in realistic environments. Assess particle/target interactions (coefficient of restitution, ignition, kindling) using instrumented particle impact rigs while systematically varying key parameters (materials, particle size, environment, target configuration). Determine key field variables (temperature, strain, stress) in particle impacts using Multiphysics finite element and hydrocode simulations validated through comparison with experimental measurements and observations. Synthesize experiments and simulations into constitutive models for PI that can be integrated with existing computational fluid dynamics (CFD) and Debris Transport Analysis (DTA) tools in future efforts

particle impact↗
NASA NTRS2024

Particle Impact Simulation and Ignition Prediction

An experimentally calibrated tool is needed to predict if a system is susceptible to failure by particle impact ignition (PI) based on use conditions, materials, and flow geometry. This tool will accelerate new components, evaluating existing hardware, and help disposition anomalies. - Conduct particle impact testing with in-situ diagnostics and complementary simulations on subset of key engineering materials (IN718, M400, 316L, 6061, Ti64, Zr) to develop a proof-of-concept predictive tool for assessing the risk of PI for idealized geometries (spherical particles) in realistic environments. - Assess particle/target interactions (coefficient of restitution, ignition, kindling) using instrumented particle impact rigs while systematically varying key parameters (materials, particle size, environment, target configuration). - Determine key field variables (temperature, strain, stress) in particle impacts using Multiphysics finite element and hydrocode simulations validated through comparison with experimental measurements and observations. - Synthesize experiments and simulations into constitutive models for PI that can be integrated with existing computational fluid dynamics (CFD) and Debris Transport Analysis (DTA) tools in future efforts.

Jonathan Tylka↗
DOE OSTI2021

The impact of the third O 2 addition reaction network on ignition delay times of neo-pentane

In this work, we studied the oxidation of neo-pentane by combining experiments, theoretical calculations, and mechanistic developments to elucidate the impact of the 3rd O 2 addition reaction network on ignition delay time predictions. The experiments are based on photoionization mass spectrometry in jet-stirred and time-resolved flow reactors allowing for sensitive detection of the keto-hydroperoxide (KHP) and keto-dihydroperoxide (KDHP) intermediates. With neo-pentane exhibiting a unique symmetric molecular structure, which consequently results only in single KHP and KDHP isomers, theoretical calculations of ionization and fragment appearance energies and of absolute photoionization cross sections enabled the unambiguous identification and quantification of the KHP intermediate. Its temperature and time-resolved profiles together with calculated and experimentally observed KHP-to-KDHP signal ratios were compared to simulation results based on a newly developed mechanism that describes the 3rd O 2 addition reaction network. A satisfactory agreement has been observed between the experimental data points and the simulation results, thus adding confidence to the model's overall performance. Finally, this mechanism was used to predict ignition delay times reported previously in shock tube and rapid compression machine experiments (J. Bugler et al., Combust. Flame 163 (2016) 138–156). While the model accurately reproduces the experimental data, simulations with and without the 3rd O 2 addition reaction network included reveal only a negligible effect on the predicted ignition delay times at 10 and 20 atm. According to model calculations, low temperatures and high pressures promote the importance of the 3rd O2 addition reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1974

Heat transfer model for predicting squib ignition times

A squib ignition model based on transient heat condition from the hot bridgewire to the pyrotechnic is described. No Arrhenius-type chemical reaction is included. Instead, a thermal contact resistance is postulated to exist between the hot bridgewire and the pyrotechnic. Ignition is assumed to occur when a 2.5 micron layer of pyrotechnic next to the bridgewire reaches a characteristic ignition temperature for that pyrotechnic. This model was applied to the JPL squib, which uses a 50 micron (0.002-in.) diameter Tophet A bridgewire to ignite a boron, potassium perchlorate mix. A computer program was utilized that solves the transient heat condition problem with the boundary conditions stipulated by the model. The thermal contact conductance at the interface was determined by trial and error so that the experimentally determined ignition time for one firing condition would be properly predicted by the model. The agreement was quite good for tests run between -129 C and +93.3 C at current levels of 3.5 and 5 A. Axial heat conduction along the bridgewire is shown to be negligible.

Sernas, V.↗
DOE OSTI2022

Prospects and Limitations of Predicting Fuel Ignition Properties from Low-Temperature Speciation Data

Using chemical kinetic modeling and statistical analysis, we investigate the possibility of correlating key chemical “markers”–typically small molecules–formed during very lean (φ ~ 0.001) oxidation experiments with near-stoichiometric (φ ~ 1) fuel ignition properties. One goal of this work is to evaluate the feasibility of designing a fuel-screening platform, based on small laboratory reactors that operate at low temperatures and use minimal fuel volume. Buras et al. [Combust. Flame2020,216, 472–484] have shown that convolutional neural net (CNN) fitting can be used to correlate first-stage ignition delay times (IDTs) with OH/HO2 measurements during very lean oxidation in low-T flow reactors with better than factor-of-2 accuracy. In this work, we test the limits of applying this correlation-based approach to predict the low-temperature heat release (LTHR) and total IDT, including the sensitivity of total IDT to the equivalence ratio, φ. We demonstrate that first-stage IDT can be reliably correlated with very lean oxidation measurements using compressed sensing (CS), which is simpler to implement than CNN fitting. LTHR can also be predicted via CS analysis, although the correlation quality is somewhat lower than for first-stage IDT. In contrast, the accuracy of total IDT prediction at φ = 1 is significantly lower (within a factor of 4 or worse). Furthermore, these results can be rationalized by the fact that the first-stage IDT and LTHR are primarily determined by low-temperature chemistry, whereas total IDT depends on low-, intermediate-, and high-temperature chemistry. Oxidation reactions are most important at low temperatures, and therefore, measurements of universal molecular markers of oxidation do not capture the full chemical complexity required to accurately predict the total IDT even at a single equivalence ratio. As a result, we find that φ-sensitivity of ignition delay cannot be predicted at all using solely correlation with lean low-T chemical speciation measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Predicting fusion ignition at the National Ignition Facility with physics-informed deep learning

Here, an inertial confinement fusion experiment, carried out at the National Ignition Facility, has achieved ignition by generating fusion energy exceeding the laser energy that drove the experiment. Prior to the experiment, a generative machine learning model that combines radiation hydrodynamics simulations, deep learning, experimental data, and Bayesian statistics was used to predict, with a probability greater than 70%, that ignition was the most likely outcome for this shot.

Spears, Brian K. [Lawrence Livermore National Labo↗
NASA NTRS2010

Computation of Unsteady Flow in Flame Trench For Prediction of Ignition Overpressure Waves

Computational processes/issues for supporting mission tasks are discussed using an example from launch environment simulation. Entire CFD process has been discussed using an existing code; STS-124 conditions were revisited to support wall repair effort for STS-125 flight; when water bags were not included, computed results indicate that IOP waves with the peak values have been reflected from SRB s own exhaust hole; ARES-1X simulations show that there is a shock wave going through the unused exhaust hole, however, it plays a secondary role; all three ARES-1X cases and STS-1 simulations showed very similar IOP magnitudes and patters on the vehicle; with the addition of water bags and water injection, it will further diminish the IOP effects.

Kwak, Dochan↗
NASA NTRS1990

Transverse liquid fuel jet breakup, burning, and ignition

An analytical study of the breakup, burning, and ignition of liquid fuels injected transversely into a hot air stream is conducted. The non-reacting liquid jet breakup location is determined by the local sonic point criterion. Two models, one employing analysis of an elliptical jet cross-section and the other employing a two-dimensional blunt body to represent the transverse jet, were used for sonic point calculations. An auxiliary criterion based on surface tension stability is used as a separate means of determining the breakup location. For the reacting liquid jet problem, a diffusion flame supported by a one-step chemical reaction within the gaseous boundary layer is solved along the ellipse surface in subsonic cross flow. Typical flame structures and concentration profiles were calculated for various locations along the jet cross-section as a function of upstream Mach numbers. The integration reaction rate along the jet cross-section is used to predict ignition position, which is found to be situated near the stagnation point. While a multi-step reaction is needed to represent the ignition process more accurately, the present calculation does yield reasonable predictions concerning ignition along a curved surface.

Li, Hsi-Shang↗
DOE OSTI2021

An Experimental Study of Uncertainty Considerations Associated with Predicting Auto-ignition Timing using Livengood-Wu Integral Method

The application of the Livengood-Wu (LW) integral method as a tool to estimate knock onset in spark ignited (SI) engines and combustion phasing in advanced compression ignition (ACI) engines has been demonstrated through simulations several times. In this study, the effect of uncertainties associated with parameters required for the LW integral method, when used as a tool for model based control of ignition timing in an ACI engine, were experimentally studied using five full boiling range gasoline fuels. As a first step, the method was applied to experimental data from a rapid compression machine and it was found that the ability of the LW integral method to predict ignition timing was very sensitive to the performance of the chemical kinetic model of each fuel. The method was subsequently applied to experimental data from a single-cylinder gasoline engine with simple approximations for the LW integral input parameters, and it was found that the predicted time of ignition was significantly different from the actual start of combustion. Systematic evaluation of various parametric uncertainties conducted thereafter showed that the uncertainty in cylinder charge temperature has the greatest influence. Improved methods of estimating cylinder charge temperature are proposed to account for the previously determined corrections, to enable the use of the LW integral method for model based control of ignition timing.

Compression Ignition↗
NASA NTRS2026

Proactive Wildfire Management: A Remote Sensing and Multimodal CNN-MLP Architecture for Ignition Risk Forecasting

As the frequency and intensity of wildfires increase, with fire seasons now starting earlier and ending later than they have over the past decades, current monitoring systems, such as lookout towers and satellites, are hindered by cloud cover, low-resolution imagery, and static data gaps that fail to track vegetation moisture levels fast enough to catch rapid pre-ignition changes. This report proposes a Machine Learning-enabled Wildfire Ignition Prediction framework that combines satellite monitoring with dynamic and high-resolution remote sensing from Unmanned Aerial Vehicle (UAV) swarms. The method would use multispectral and thermal data from the Landsat program to create a baseline for vegetation health, calculating a two-band Enhanced Vegetation Index (EVI2) and the moisture content of the vegetation. These inputs will later be fused with microscale UAV weather data, including thermal hotspots found through thick canopies, hyperspectral chemical signatures of pre-visual combustion, and local weather streams. The multispectral satellite, multispectral Light Detection and Ranging (LiDAR), and thermal data would then be processed through a Convolutional Neural Network (CNN), alongside a Multilayer Perceptron (MLP) for the micro-weather telemetry. The outputs of these networks would be fused into a single feature representation and passed through a final prediction network to generate real-time ignition risk scores and hotspot alerts. Model performance would be assessed using standard classification metrics, including a Receiver Operating Characteristic - Area Under the Curve (ROC AUC) and F1 score. This system would allow first responders to identify high-risk zones and intervene before ignition occurs, improving emergency response time compared to current approaches.

machine learning↗
DOE OSTI2021

Modeling Nanosecond-Pulsed Spark Discharge and Flame Kernel Evolution

Dilute combustion, either using exhaust gas recirculation or with excess air, is considered a promising strategy to improve the thermal efficiency of internal combustion engines. However, the dilute air-fuel mixture, especially under intensified turbulence and high-pressure conditions, poses significant challenges for ignitability and combustion stability, which may limit the attainable efficiency benefits. In-depth knowledge of the flame kernel evolution to stabilize ignition and combustion in a challenging environment is crucial for effective engine development and optimization. To date, a comprehensive understanding of ignition processes that result in the development of fully predictive ignition models usable by the automotive industry does not yet exist. Spark-ignition consists of a wide range of physics that includes electrical discharge, plasma evolution, joule-heating of gas, and flame kernel initiation and growth into a self-sustainable flame. In this study, an advanced approach is proposed to model spark-ignition energy deposition and flame kernel growth. To decouple the flame kernel growth from the electrical discharge, a nanosecond-pulsed high-voltage discharge is used to trigger spark-ignition in an optically accessible small ignition test vessel with a quiescent mixture of air and methane. Initial conditions for the flame kernel, including its thermodynamic state and species composition, are derived from a plasma-chemical equilibrium calculation. The geometric shape and dimension of the kernel are characterized using a multi-dimensional thermal plasma solver. Here, the proposed modeling approach is evaluated using a high-fidelity computational fluid dynamics procedure to compare the simulated flame kernel evolution against flame boundaries from companion Schlieren images.

42 ENGINEERING↗
NASA NTRS2004

Transition from Ignition to Flame Growth under External Radiation in Three Dimensions (TIGER-3D)

This study focuses on localized ignition by external radiant flux and subsequent flame growth over thin polymeric materials (plastic and paper) in microgravity. Two transition stages were observed. The first transition stage covers the period from the onset of ignition to the formation of stabilized flame near the ignited area. This is followed by the second transition of the flame growth stage from the initial stabilized flame to sustained fire growth away from the ignited area. For the first stage, ignition experiments of thin PMMA sheets were conducted using a CO2 laser as an external source in the 10 s drop tower. The results of front side surface ignition and of backside surface ignition were observed. The effects of imposed flow velocity, sample thickness, and ambient oxygen concentration on ignition are obtained. Numerical study was conducted to investigate to understand and predict ignition behavior observed in the experiments. For the second stage, numerical study is being conducted to describe the effects of gravity on heat release rate of a PMMA sheet. The gravity level was varied from zero to normal gravity. The preliminary results show that the maximum heat release occurs at around 0.02 g.

Kashiwagi, Takashi↗
NASA NTRS2004

Transition from Ignition to Flame Growth under External Radiation in 3D

This study focuses on localized ignition by external radiant flux and subsequent flame growth over thin polymeric materials (plastic and paper) in microgravity. Two transition stages were observed. The first transition stage covers the period from the onset of ignition to the formation of stabilized flame near the ignited area. This is followed by the second transition of the flame growth stage from the initial stabilized flame to sustained fire growth away from the ignited area. For the first stage, ignition experiments of thin PMMA sheets were conducted using a CO2 laser as an external source in the 10 s drop tower. The results of front side surface ignition and of backside surface ignition were observed. The effects of imposed flow velocity, sample thickness, and ambient oxygen concentration on ignition are obtained. Numerical study was conducted to investigate to understand and predict ignition behavior observed in the experiments. For the second stage, numerical study is being conducted to describe the effects of gravity on heat release rate of a PMMA sheet. The gravity level was varied from zero to normal gravity. The preliminary results show that the maximum heat release occurs at around 0.02 g.

Kashiwagi, Takashi↗
DOE OSTI2025

Primordial Black Hole Triggered Type Ia Supernovae. I. Impact on Explosion Dynamics and Light Curves

Primordial black holes (PBHs) in the asteroid-mass window are compelling dark matter candidates, made plausible by the existence of black holes and by the variety of mechanisms of their production in the early Universe. If a PBH falls into a white dwarf (WD), the strong tidal forces can generate enough heat to trigger a thermonuclear runaway explosion, depending on the WD’s mass and the PBH’s orbital parameters. In this work, we investigate the WD explosion triggered by the passage of a PBH. We perform 2D simulations of the WD undergoing thermonuclear explosion in this scenario, with the predicted ignition site as a parameter assuming the deflagration–detonation transition model. We study the explosion dynamics, and predict the associated light curves and nucleosynthesis. We find that the model sequence predicts light curves which align with the Phillips relation (B max versus ΔM 15 ). Our models hint at a unifying approach in triggering Type Ia supernovae without involving two distinctive evolutionary tracks.

Dark matter↗
NASA NTRS2001

Theoretical Prediction of Microgravity Ignition Delay of Polymeric Fuels in Low Velocity Flows

A new flammability apparatus and protocol, FIST (Forced Flow Ignition and Flame Spread Test), is under development. Based on the LIFT (Lateral Ignition and Flame Spread Test) protocol, FIST better reflects the environments expected in spacebased facilities. The final objective of the FIST research is to provide NASA with a test methodology that complements the existing protocol and provides a more comprehensive assessment of material flammability of practical materials for space applications. Theoretical modeling, an extensive normal gravity data bank and a few validation space experiments will support the testing methodology. The objective of the work presented here is to predict the ignition delay and critical heat flux for ignition of solid fuels in microgravity at airflow velocities below those induced in normal gravity. This is achieved through the application of a numerical model previously developed of piloted ignition of solid polymeric materials exposed to an external radiant heat flux. The model predictions will provide quantitative results about ignition of practical materials in the limiting conditions expected in space facilities. Experimental data of surface temperature histories and ignition delay obtained in the KC-135 aircraft are used to determine the critical pyrolysate mass flux for ignition and this value is subsequently used to predict the ignition delay and the critical heat flux for ignition of the material. Surface temperature and piloted ignition delay calculations for Polymethylmethacrylate (PMMA) and a Polypropylene/Fiberglass (PP/GL) composite were conducted under both reduced and normal gravity conditions. It was found that ignition delay times are significantly shorter at velocities below those induced by natural convection.

Fernandez-Pello, A. C.↗
DOE OSTI2022

Experimental Ignition Delay Time Measurements and Chemical Kinetics Modeling of Hydrogen/Ammonia/Natural Gas Fuels

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 carbon monoxide (CO) formation profiles as well as the ignition delay times (IDTs) 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 over a temperature range between 1200 K and 1800 K with an average pressure of 2.2 atm. Experimental mixtures included both neat and combination natural gas/hydrogen with ammonia addition, with all mixtures except one having an equivalence ratio of 1. Results were then compared with the GRI 3.0 mechanism, as well as the newly developed UCF 2022 mechanism utilizing chemkin-pro software. In general, both models were able to capture the trend in auto-ignition 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. Lastly, a reaction pathway analysis was carried out to understand important ammonia decomposition pathways in the presence of hydrogen and natural gas.

33 ADVANCED PROPULSION SYSTEMS↗