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Results for “high explosives, simulations, modeling”

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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Effects of the Venusian atmosphere on incoming meteoroids and the impact crater population

The dense atmosphere on Venus prevents craters smaller than about 2 km in daimater from forming and also causes formation of several crater fields and multiple-floored craters (collectively referred to as multiple impacts). A model has been constructed that simulates the behavior of a meteoroid in a dense planetary atmosphere. This model was then combined with an assumed flux of incoming meteoroids in an effort to reproduce the size-frequency distribution of impact craters and several aspects of the population of the crater fields and multiple-floored craters on Venus. The modeling indicates that it is plausible that the observed rollover in the size-frequency curve for Venus is due entirely to atmospheric effects on incoming meteoroids. However, there must be substantial variation in the density and behavior of incoming meteoroids in the atmosphere. Lower-density meteoroids must be less likely to survive atmospheric passage than simple density differences can account for. Consequently, it is likely that the percentage of craters formed by high-density meteoroids is very high at small crater diameters, and this percentage decreases substantially with increasing crater diameter. Overall, high-density meteoroids created a disproportionately large percentage of the impact craters on Venus. Also, our results indicate that a process such as meteoroid flattening or atmospheric explosion of meteoroids must be invoked to prevent craters smaller than the observed minimum diameter (2 km) from forming. In terms of using the size-frequency distribution to age-date the surface, the model indicates that the observed population has at least 75% of the craters over 32 km in diameter that would be expected on an atmosphereless Venus; thus, this part of the curve is most suitable for comparison with calibrated curves for the Moon.

Herrick, Robert R.↗
DOE OSTI2023

Effect of surface roughness on phase transition timing in megaampere pulsed-power–driven exploding conductors

An understanding of material phase transitions in megaampere pulsed-power–driven exploding conductors is important for predicting the growth of hydrodynamic instabilities in magneto-inertial fusion concepts. Here, this study analyzes phase transitions in electrical conductor explosions using 1D Lagrangian and 2D arbitrary Lagrangian–Eulerian resistive magnetohydrodynamic simulations to show that micrometer-scale surface roughness can lead to the electrothermal instability (ETI), a feedback effect that concentrates resistive heating and leads to early melting and ablation. Simulations of the Mykonos electrothermal instability II (METI-II) experiment show melting begins 19% sooner for machined rods with micrometer-scale surface roughness than for rods without these features. The surface magnetic field is 41 T around the initial region of melt, representing a lower magnitude than both the 86 T from 1D simulations and the 85 T threshold reported elsewhere. In 2D simulations with micrometer-scale surface roughness, temperature measurements indicate the critical point temperature of aluminum is reached 17% faster in comparison with 1D simulations. Values from 2D simulations with surface roughness align with predictions from ETI theory, and the observed temperature redistribution further supports the ETI as an underlying mechanism. Simulation results are validated against experimental photonic Doppler velocimetry data. This study shows 1D simulations are adequate to model conductors with sub-micrometer-scale surface roughness in this high-energy-density regime; however, 2D or 3D simulations are required to capture the full range of physics for accurately describing phase transitions in conductors with micrometer-scale or larger surface roughness.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

3D optical diagnostics for explosively driven deformation and fragmentation

High-speed, optical imaging diagnostics are presented for three-dimensional (3D) quantification of explosively driven metal fragmentation. At early times after detonation, Digital Image Correlation (DIC) provides non-contact measures of 3D case velocities, strains, and strain rates, while a proposed stereo imaging configuration quantifies in-flight fragment masses and velocities at later times. Experiments are performed using commercially obtained RP-80 detonators from Teledyne RISI, which are shown to create a reproducible fragment field at the benchtop scale. DIC measurements are compared with 3D simulations, which have been ‘leveled’ to match the spatial resolution of DIC. Overall, results demonstrate improved ability to identify predicted quantities-of-interest that fall outside of measurement uncertainty and shot-to-shot variability. Similarly, video measures of fragment trajectories and masses allow rapid experimental repetition and provide correlated fragment size-velocity measurements. Measured and simulated fragment mass distributions are shown to agree within confidence bounds, while some statistically meaningful differences are observed between the measured and predicted conditionally averaged fragment velocities. Together these techniques demonstrate new opportunities to improve future model validation.

42 ENGINEERING↗
NASA NTRS1994

Damage Mechanisms and Controlled Crack Propagation in a Hot Pressed Silicon Nitride Ceramic

The subcritical growth of cracks from pre-existing flaws in ceramics can severely affect the structural reliability of a material. The ability to directly observe subcritical crack growth and rigorously analyze its influence on fracture behavior is important for an accurate assessment of material performance. A Mode I fracture specimen and loading method has been developed which permits the observation of stable, subcritical crack extension in monolithic and toughened ceramics. The test specimen and procedure has demonstrated its ability to generate and stably propagate sharp, through-thickness cracks in brittle high modulus materials. Crack growth for an aluminum oxide ceramic was observed to be continuously stable throughout testing. Conversely, the fracture behavior of a silicon nitride ceramic exhibited crack growth as a series of subcritical extensions which are interrupted by dynamic propagation. Dynamic initiation and arrest fracture resistance measurements for the silicon nitride averaged 67 and 48 J/sq m, respectively. The dynamic initiation event was observed to be sudden and explosive. Increments of subcritical crack growth contributed to a 40 percent increase in fracture resistance before dynamic initiation. Subcritical crack growth visibly marked the fracture surface with an increase in surface roughness. Increments of subcritical crack growth loosen ceramic material near the fracture surface and the fracture debris is easily removed by a replication technique. Fracture debris is viewed as evidence that both crack bridging and subsurface microcracking may be some of the mechanisms contributing to the increase in fracture resistance. A Statistical Fracture Mechanics model specifically developed to address subcritical crack growth and fracture reliability is used together with a damaged zone of material at the crack tip to model experimental results. A Monte Carlo simulation of the actual experiments was used to establish a set of modeling input parameters. It was demonstrated that a single critical parameter does not characterize the conditions required for dynamic initiation. Experimental measurements for critical crack lengths, and the energy release rates exhibit significant scatter. The resulting output of the model produces good agreement with both the average values and scatter of experimental measurements.

Calomino, Anthony Martin↗
DOE OSTI2021

Effects of non-thermal termolecular chemistry on detonation development in hydrogen (H2) / methane (CH4) - air mixtures

In combustion simulations, it is usually assumed that highly-energized collision complexes (either radical or stable species) formed in exothermic reactions are always under thermal equilibrium as they evolve through competing networks of reactions. However, in practical flames, non-trivial amounts of reactive radicals such as H, O and OH are present apart from O2. As a result, collisions of these reactive species with the energized collision complexes have been shown in recent studies to induce non-thermal reactivity. These studies have also demonstrated that such non-thermal reactions can be suitably represented in macroscopic kinetics models as chemically termolecular reactions. The present work was focused on identifying and quantifying the effects of including such reactions on the evolution of an initial deflagration front to a developing detonation in H2/CH4-air mixtures under boosted internal combustion (IC) engine conditions. Specifically, fully resolved simulations, with and without non-thermal reactivity, were performed for a constant volume reactor containing stoichiometric H2/CH4-air mixture. It was found that inclusion of termolecular chemistry resulted in a delayed onset of end-gas auto-ignition. Concurrently, the developing detonation intensity was observed to be significantly higher. Chemical explosive mode analysis (CEMA) was performed to identify the dominant species/reactions responsible for the observed variation in the results.

Detonation↗
DOE OSTI2022

A phase transition for finding needles in nonlinear haystacks with LASSO artificial neural networks

To fit sparse linear associations, a LASSO sparsity inducing penalty with a single hyperparameter provably allows to recover the important features (needles) with high probability in certain regimes even if the sample size is smaller than the dimension of the input vector (haystack). More recently learners known as artificial neural networks (ANN) have shown great successes in many machine learning tasks, in particular fitting nonlinear associations. Small learning rate, stochastic gradient descent algorithm and large training set help to cope with the explosion in the number of parameters present in deep neural networks. Yet few ANN learners have been developed and studied to find needles in nonlinear haystacks. Driven by a single hyperparameter, our ANN learner, like for sparse linear associations, exhibits a phase transition in the probability of retrieving the needles, which we do not observe with other ANN learners. To select our penalty parameter, we generalize the universal threshold of Donoho and Johnstone (Biometrika 81(3):425–455, 1994) which is a better rule than the conservative (too many false detections) and expensive cross-validation. In the spirit of simulated annealing, we propose a warm-start sparsity inducing algorithm to solve the high-dimensional, non-convex and non-differentiable optimization problem. We perform simulated and real data Monte Carlo experiments to quantify the effectiveness of our approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Beyond Magic Barrels: Digital manufacturing for crystallization, process development and optimization of explosive materials: Part II Resveratrol Exemplar

This SAND report summarizes work supported by an Engineering Sciences Research Foundation (ESRF) Lab Directed Research and Development (LDRD) project entitled “Beyond Magic Barrels: Digital manufacturing for crystallization, process development and optimization of explosive materials.” This SAND report is written in two parts with Part 1 discusses recrystallization of our explosive exemplar and Part 2 summarizing our work with recrystallization of resveratrol. We have studied resveratrol recrystallization with a multiscale approach combining experiments, modeling and simulation. At the single crystal scale, microscopy experiments illuminate crystal time-dependent growth rates using advanced image analysis. Bench scale experiments were carried out to look at growth of multiple particles in a small reactor creating thousands of particles and analyzing the results with microscopy and μCT. For the modeling we combine kinetic Monte Carlo (kMC) models with subscale information from density functional theory (DFT) or molecular dynamics. This work is discussed in Part 1 and can also be found in a paper from the project discussing a coarse-grained kMC model specifically developed for resveratrol. For well-mixed systems, we have population balance equations (PBE) linked with species mass conservation forming a set of ordinary differential equations that can be solved quickly. For more complicated geometries, such as the vat crystallization used throughout the complex, a coupled computational fluid dynamic (CFD)/PBE method was developed to account for gradients in temperature and concentration and differences in crystallization rates throughout the domain. These simulations are more complex and require high performance computing. We present results for two cases: 5% seed fast cool with parameters fit to the well-mixed case and 5% seed slow cool using the same parameters. We show reasonable agreement with experiments though are particles are significantly larger than the experiments.

36 MATERIALS SCIENCE↗
NASA NTRS2012

Analysis of Satellite-Derived Arctic Tropospheric BrO Columns in Conjunction with Aircraft Measurements During ARCTAS and ARCPAC

We derive tropospheric column BrO during the ARCTAS and ARCPAC field campaigns in spring 2008 using retrievals of total column BrO from the satellite UV nadir sensors OMI and GOME-2 using a radiative transfer model and stratospheric column BrO from a photochemical simulation. We conduct a comprehensive comparison of satellite-derived tropospheric BrO column to aircraft in-situ observations ofBrO and related species. The aircraft profiles reveal that tropospheric BrO, when present during April 2008, was distributed over a broad range of altitudes rather than being confined to the planetary boundary layer (PBL). Perturbations to the total column resulting from tropospheric BrO are the same magnitude as perturbations due to longitudinal variations in the stratospheric component, so proper accounting of the stratospheric signal is essential for accurate determination of satellite-derived tropospheric BrO. We find reasonably good agreement between satellite-derived tropospheric BrO and columns found using aircraft in-situ BrO profiles, particularly when satellite radiances were obtained over bright surfaces (albedo> 0.7), for solar zenith angle < 80 and clear sky conditions. The rapid activation of BrO due to surface processes (the bromine explosion) is apparent in both the OMI and GOME-2 based tropospheric columns. The wide orbital swath of OMI allows examination of the evolution of tropospheric BrO on about hourly time intervals near the pole. Low surface pressure, strong wind, and high PBL height are associated with an observed BrO activation event, supporting the notion of bromine activation by high winds over snow.

Choi, S.↗
DOE OSTI2026

On the Importance of the Convective Urca Process in 3D Simulations of a Simmering White Dwarf

Type Ia supernovae are bright thermonuclear explosions that are important to numerous areas of astronomy. However, the origins of these events are poorly understood. One proposed setting is that of a near Chandrasekhar mass white dwarf that undergoes runaway carbon burning in the core. During the thousand years leading up to the explosion, the white dwarf undergoes a simmering phase where slow carbon burning heats the core and drives convection. A poorly understood aspect of this phase is the convective Urca process, which links convection with weak nuclear reactions. We use the low Mach number code MAESTROeX to perform full 3D simulations as is required to accurately capture the turbulent convection. We present simulations with and without the A=23 convective Urca process, which have relaxed to a steady state. We characterize the effects of the convective Urca process on the neutrino losses, the nuclear energy generation, and the convective boundary. We find that the size of the convection zone is substantially reduced by the convective Urca process, though convection still extends past the Urca shell. Our findings on the structure of the convective zone and the compositional changes can be used to inform 1D stellar models that track the longer-timescale evolution.

FOS: Physical sciences↗
DOE OSTI2026

Characterization of runaway electron impact on instrumented sacrificial limiters on DIII-D

Instrumented sacrificial limiter heads, both domed (proud) and flat (flush) are used in DIII-D runaway electron (RE) wall strikes to study the wall impact dynamics with high spatial and time resolution. The approximate structure of the RE wetted area and heating depth on the domed limiter heads were predicted qualitatively using orbit-tracking simulations, although a strong left–right asymmetry (about the magnetic field direction) was not captured well by the simulations. It is hypothesized that this difference is perhaps due to the local 3D magnetic field perturbation of the dome limiter head. The average kinetic energy K and pitch angle θ of REs striking the limiter head were estimated from the spatial distribution of local HXR emission and were estimated to be roughly K ≈ 4 MeV and θ ≈ 0.2 rad. These values are roughly consistent with in-plasma values estimated before the loss event, indicating that RE kinetic energy and pitch angle are not drastically altered when transporting to the wall. Large shot–shot variations (1–10 kJ) in energy deposition into the limiter head were observed and were explained by shot–shot variations in locked magneto-hydrodynamics mode toroidal phase. For the largest deposited energies (10 kJ), graphite material failure and explosive dust release was observed, and the depth of material failure at higher energy deposition was successfully reproduced using modelling of volumetric energy deposition and brittle failure. The presence of energetic (keV) level ion impact during the RE wall strike was confirmed by three different surface analysis techniques. The ratio of energetic ion to RE flux appears to be larger on flat surfaces within the RE wetted area, although the energetic ion flux and total energy flux due to energetic ions have not yet been quantified.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

The Progenitors of Superluminous Type Ia Supernovae

Abstract Recent observations of type Ia supernovae (SNe Ia) have discovered a subclass of “super-Chandrasekhar” SNe Ia (SC SNe Ia) whose high luminosities and low ejecta velocities suggest that they originate from the explosions of white dwarfs (WDs) with masses that exceed the Chandrasekhar mass limit. Different models have been proposed to explain the progenitors of these explosions, including a “magnetized WD” model and a “WD merger” model. To test the robustness of these models, we conduct a 1D numerical parameter survey of WD explosions using these models as initial conditions. We follow the explosions using the hydrodynamics code Castro and then use the radiation transport code SuperNu to create light curves and spectra for the models. We find that while both classes of models fall within the range of SC SNe Ia observations on the light-curve width–luminosity relation, only the WD merger models reproduce the observed low ejecta velocities. The light curves of our merger models are more similar photometrically to observations than our magnetized models. Given this, we discuss possible explanations for the brightest SC SNe Ia observations that cannot be reproduced with our WD merger models. This study provides the basis for future SC SNe Ia observations and higher-dimensional numerical models.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2019

A Model for Energy Buildup and Eruption Onset in Coronal Mass Ejections

Coronal mass ejections (CMEs) and eruptive flares (EFs) are the most energetic explosions in the solar system. Their underlying origin is the free energy that builds up slowly in the sheared magnetic field of a filament channel. We report the first end-to-end numerical simulation of a CME/EF, from zero-free-energy initial state through filament channel formation to violent eruption, driven solely by the magnetic-helicity condensation process. Helicity is the topological measure of linkages between magnetic flux systems, and is conserved in the corona, building up inexorably until it is ejected into interplanetary space. Numerous investigations have demonstrated that helicity injected by small-scale vortical motions, such as those observed in the photosphere, undergoes an inverse cascade from small scales to large, “condensing” at magnetic-polarity boundaries. Our new results verify that this process forms a filament channel within a compact bipolar region embedded in a background dipole field, and show for the first time that a fast CME eventually occurs via the magnetic-breakout mechanism. We further show that the trigger for explosive eruption is reconnection onset in the flare current sheet that develops above the polarity inversion line: this reconnection forms flare loops below the sheet and a CME flux rope above, and initiates high-speed outward flow of the CME. Our findings have important implications for magnetic self organization and explosive behavior in solar and other astrophysical plasmas, as well as for understanding and predicting explosive solar activity.

filaments↗
DOE OSTI2022

An Improved Method for Coupling Hydrodynamics with Astrophysical Reaction Networks

Reacting astrophysical flows can be challenging to model, because of the difficulty in accurately coupling hydrodynamics and reactions. This can be particularly acute during explosive burning or at high temperatures where nuclear statistical equilibrium is established. We develop a new approach, based on the ideas of spectral deferred corrections (SDC) coupling of explicit hydrodynamics and stiff reaction sources as an alternative to operator splitting, that is simpler than the more comprehensive SDC approach we demonstrated previously. We apply the new method to a double-detonation problem with a moderately sized astrophysical nuclear reaction network and explore the time step size and reaction network tolerances, to show that the simplified-SDC approach provides improved coupling with decreased computational expense compared to traditional Strang operator splitting. This is all done in the framework of the Castro hydrodynamics code, and all algorithm implementations are freely available.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRSDate not supplied

Flare Ribbon Signatures of Plasmoids

Solar flares are explosive space weather events that rapidly convert stored magnetic energy into bulk motion, plasma heating, and particle acceleration. Understanding the structure and dynamics of the magnetic reconnection that powers flares is critical for predicting the energy release. In particular, the amount of energy transferred to energetic particles is thought to be highly dependent on whether the reconnection is primarily turbulent (e.g., plasmoid dominated) or instead laminar. We present new high-resolution MHD simulations of three-dimensional reconnection in an eruptive flare and compare the results to recent data. Although flare reconnection is challenging to observe directly in the corona, highly detailed constraints on its dynamics can be obtained from observations of flare ribbons that track the chromospheric footpoints of newly reconnected field lines. The analogues of flare ribbons in our simulations are identified by tracking discontinuous changes in field-line magnetic connectivity due to the reconnection. In our highest-resolution calculations, we find that these ribbon analogues are highly structured and exhibit many ‘whorl’ patterns that are linked to turbulent plasmoids in the reconnecting current sheet. Such flare ribbon fine structure therefore reveals crucial information about the fundamental turbulent vs. laminar nature of the reconnection. Plasmoid-driven particle acceleration models would therefore predict co-location of energetic particle signatures with plasmoid-associated ribbon fine structure.

J T Dahlin↗
DOE OSTI2024

Kilonova light-curve interpolation with neural networks

Kilonovae are the electromagnetic transients created by the radioactive decay of freshly synthesized elements in the environment surrounding a neutron star merger. To study the fundamental physics in these complex environments, kilonova modeling requires, in part, the use of radiative transfer simulations. The microphysics involved in these simulations results in high computational cost, prompting the use of emulators for parameter inference applications. Utilizing a training set of 22 248 high-fidelity simulations (composed of 412 unique ejecta parameter combinations evaluated at 54 viewing angles), we use a neural network to efficiently train on existing radiative transfer simulations and predict light curves for new parameters in a fast and computationally efficient manner. Our neural network can generate millions of new light curves in under a minute. We discuss our emulator's degree of off-sample reliability and parameter inference of the AT2017gfo observational data. Finally, we discuss tension introduced by multiband inference in the parameter inference results, particularly with regard to the neural network's recovery of viewing angle. Published by the American Physical Society 2024

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2008

How Very Massive Metal-Free Stars Start Cosmological Reionization

The initial conditions and relevant physics for the formation of the earliest galaxies are well specified in the concordance cosmology. Using ab initio cosmological Eulerian adaptive mesh refinement radiation hydrodynamical calculations, we discuss how very massive stars start the process of cosmological reionization. The models include nonequilibrium primordial gas chemistry and cooling processes and accurate radiation transport in the case B approximation using adaptively ray-traced photon packages, retaining the time derivative in the transport equation. Supernova feedback is modeled by thermal explosions triggered at parsec scales. All calculations resolve the local Jeans length by at least 16 grid cells at all times and as such cover a spatial dynamic range of approx.10(exp 6). These first sources of reionization are highly intermittent and anisotropic and first photoionize the small-scale voids surrounding the halos they form in, rather than the dense filaments they are embedded in. As the merging objects form larger, dwarf-sized galaxies, the escape fraction of UV radiation decreases and the H II regions only break out on some sides of the galaxies, making them even more anisotropic. In three cases, SN blast waves induce star formation in overdense regions that were formed earlier from ionization front instabilities. These stars form tens of parsecs away from the center of their parent DM halo. Approximately five ionizing photons are needed per sustained ionization when star formation in 10(exp 6) stellar Mass halos is dominant in the calculation. As the halos become larger than approx.10(exp 7) Stellar Mass, the ionizing photon escape fraction decreases, which in turn increases the number of photons per ionization to 15-50, in calculations with stellar feedback only. Radiative feedback decreases clumping factors by 25% when compared to simulations without star formation and increases the average temperature of ionized gas to values between 3000 and 10,000 K.

Wise, John H.↗
DOE OSTI2021

A reactive flow model for the 3,3'-diamino-4,4'-azoxyfurazan based plastic bonded explosive (PBX 9701)

Here, this paper describes the calibration of the Arrhenius Wescott–Stewart–Davis (AWSD) reactive flow model for the recently developed high explosive PBX 9701, which consists of 97% 3,3'-diamino-4,4'-azoxyfurazan (DAAF) and 3% FK-800 binder by weight. DAAF-based explosive formulations have several desirable qualities as they are relatively insensitive to non-shock insults but have higher performance than triaminotrinitrobenzene based formulations. Equations of state for the explosive reactants and products are calibrated using a combination of existing and new experimental data and theoretical calculations. The AWSD rate law calibration utilizes both one-dimensional shock-to-detonation and multidimensional rate stick experiments to capture the shock initiation and propagating detonation regimes. Validation of the calibrated model is demonstrated through comparison with recent gas-gun experiments.

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

MACHINE LEARNING BASED CHEMICAL EXPLOSIVE MODE ANALYSIS (ML-CEMA)

The software consists of a Machine Learning based Chemical Explosive Mode Analysis (ML-CEMA) tool for advanced computational flame diagnostics. CEMA, originally based on eigen-analysis of the local thermochemical system, is capable of identifying reaction fronts and limit phenomena such as auto-ignition and extinction in practical combustion systems, such as internal combustion engines and gas turbine combustors. However, the original CEMA is computationally expensive for large reaction mechanisms that are typically needed to describe fuel chemistry of practical large-hydrocarbon fuels. This novel ML-CEMA tool employs a ML technique to accelerate the eigen-analysis of the basic CEMA approach by orders of magnitude, thus making it suitable for practical fuels. In ML-CEMA,zero-dimensional (0D) reactors and one-dimensional (1D) premixed flames are first used to generate a large number of data points for neural network based ML training. The trained ML model is then used to perform CEMA prediction. This ML-CEMA tool has been demonstrated in canonical 0D and 1D configurations as well as highly-transient three-dimensional spray flames exhibiting multi-mode turbulent combustion, showing promising results. ML-CEMA, as a standalone tool, can be used for computationally-efficient diagnostics of massive datasets generated from both experiments and simulations. For example, based on spatially resolved measurements of a small set of reactive scalars(such as temperature, hydroxyl radical and formaldehyde), ML-CEMA can effectively identify flame fronts and rare events. ML-CEMA also provides a robust online or offline flame feature detection tool. When used for on-the-fly simulations, ML-CEMA further enables zone-adaptive combustion modeling, in which the predicted eigenvalue is used as a robust mode indicator for judicious assignment of locally-valid combustion models. This ML-CEMA based zone-adaptive model can lead to substantial computational cost savings when used for large-scale simulations of multi-mode combustion systems. Third Party Code Web Page to Download Code Web Page Location of Third Party License

Xu, Chao↗