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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A redox model for NO oxidation, NH 3 oxidation and high temperature standard SCR over Cu-SSZ-13

A kinetic model is developed to predict the influence of temperature and hydrothermal aging on the redox of active Cu sites under standard SCR, NO oxidation and NH 3 oxidation conditions over a practically relevant fully-formulated Cu-SSZ-13 catalyst. NO 2 /N 2 production during NO/NH 3 titration of Cu II sites is utilized to identify rate parameters associated with NO-only RHC (reduction half cycle) and NH 3 -only RHC respectively. Integral N 2 formation during subsequent NO + NH 3 titration is consistent with the production of one NO 2 per two CuII sites reduced during NO-only RHC and one N 2 per six Cu II sites reduced during NH 3 -only RHC. Decreased reduction of Cu II sites by NO/NH 3 upon hydrothermal aging, along with the production of one NO 2 per two CuII sites during NO-only RHC, is accordant with the involvement of proximal ZCuOH and oxygen-bridged dimeric Cu II sites. Oxidation of partially solvated and framework coordinated ZCu (Cu I ) sites occurs in presence of O 2 , does not produce N 2 and can lead to the consumption of Brønsted acid sites. A global OHC kinetic model is developed to predict transient and integral N 2 formation during exposure of CuI sites to a mixture of NO and O 2 . The resulting redox kinetic model quantitatively predicts NO and NH 3 consumption during isothermal transient response Cu redox (TRCR) protocols, along with temperature and age dependent steady-state standard SCR and oxidation conditions. The redox model presented in this work synthesizes recent kinetic, spectroscopic and computational findings to provide a foundational description of active site redox during standard SCR, NO oxidation and NH3 oxidation over Cu-SSZ-13.

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

Autonomous Molecular Structure Imaging with High-Resolution Atomic Force Microscopy for Molecular Mixture Discovery

Due to its single-molecule sensitivity, high-resolution atomic force microscopy (HR-AFM) has proved to be a valuable and uniquely advantageous tool to study complex molecular mixtures, which hold promise for developing clean energy and achieving environmental sustainability. However, significant challenges remain to achieve the full potential of the sophisticated and time-consuming experiments. Automation combined with machine learning (ML) and artificial intelligence (AI) is key to overcoming these challenges. Here we present Auto-HR-AFM, an AI tool to automatically collect HR-AFM images of petroleum-based mixtures. In this study, we trained an instance segmentation model to teach Auto-HR-AFM how to recognize features in HR-AFM images. Auto-HR-AFM then uses that information to optimize the imaging by adjusting the probe-molecule distance for each molecule in the run. Auto-HR-AFM is the initial tool that will lead to fully automated scanning probe microscopy (SPM) experiments, from start to finish. This automation will allow SPM to become a mainstream characterization technique for complex mixtures, an otherwise unattainable target.

36 MATERIALS SCIENCE↗
NASA NTRS1974

Nonequilibrium boundary layer at a stagnation point for a hydrogen-helium stream over ablating graphite

The nonequilibrium axisymmetric stagnation point boundary layer over an ablating graphite surface is considered. The external stream is a high temperature mixture of hydrogen and helium. Variable thermodynamic and transport properties are assumed. Lennard-Jones potential model is used to calculate the transport coefficients of each species. Although the mixture rules for viscosity of the gas mixture are used, the weighting functions are more sophisticated than those commonly employed. For the conductivity of the mixture, generalized Wassiljewa coefficients are used. Seven species with 28 dissociation/recombination reactions are considered. Hansen's model for the dissociation rate constants is employed. The recombination rate constants are obtained by invoking detailed balance principles assisted by the JANAF thermodynamic data and the Hansen-Pearson thermodynamic data for C3.

Liu, T.-M.↗
NASA NTRS2011

Hazards Induced by Breach of Liquid Rocket Fuel Tanks: Conditions and Risks of Cryogenic Liquid Hydrogen-Oxygen Mixture Explosions

We analyze the data of purposeful rupture experiments with LOx and LH2 tanks, the Hydrogen-Oxygen Vertical Impact (HOVI) tests that were performed to clarify the ignition mechanisms, the explosive power of cryogenic H2/Ox mixtures under different conditions, and to elucidate the puzzling source of the initial formation of flames near the intertank section during the Challenger disaster. We carry out a physics-based analysis of general explosions scenarios for cryogenic gaseous H2/Ox mixtures and determine their realizability conditions, using the well-established simplified models from the detonation and deflagration theory. We study the features of aerosol H2/Ox mixture combustion and show, in particular, that aerosols intensify the deflagration flames and can induce detonation for any ignition mechanism. We propose a cavitation-induced mechanism of self-ignition of cryogenic H2/Ox mixtures that may be realized when gaseous H2 and Ox flows are mixed with a liquid Ox turbulent stream, as occurred in all HOVI tests. We present an overview of the HOVI tests to make conclusion on the risk of strong explosions in possible liquid rocket incidents and provide a semi-quantitative interpretation of the HOVI data based on aerosol combustion. We uncover the most dangerous situations and discuss the foreseeable risks which can arise in space missions and lead to tragic outcomes. Our analysis relates to only unconfined mixtures that are likely to arise as a result of liquid propellant space vehicle incidents.

Osipov, Viatcheslav↗
DOE OSTI2026

Reduced Order Models for Liquid Hydrogen Pooling and Vaporization Supported by Experiments

In the event of a leak of liquid hydrogen, a pool can form that vaporizes, disperses, and eventually dilutes to a non-flammable mixture. In this work, we describe fast-running models for the pooling and vaporization of liquid hydrogen in a steady cross-wind. Several pooling models from the literature are compared to solve for the flow and extent of the pool. The size of the pool can serve as the source for a separate dispersion model, which builds upon the existing one-dimensional Gaussian plume model in HyRAM+. Additional terms for the effects of a cross-wind on momentum and entrainment were added so that the model could handle the effects of a cross-wind on a low-speed flow. The models are compared to experimental data on pooling extent and downwind dispersion for steady flow rates of liquid hydrogen in a steady cross-wind. In the two compared experiments, liquid flow rates of 15 and 45 g/s were spilled onto concrete in cross-winds of approximately 1.8 m/s. The rate of growth of the pool and the downwind concentration boundaries are compared to the models, showing good agreement, although additional tuning is needed. These models can contribute to the advancement of codes and standards for liquid hydrogen systems.

dispersion↗
NASA NTRS1989

Infrared Emission from Comets

A brief discussion of the infrared observations from 4 to 20 micrometers of seven comets is presented. The observed infrared emission from comets depends primarily on their heliocentric distance. A model based on grain populations composed of a mixture of silicate and amorphous carbon particles in the mass ratio of about 40 to 1, with a power-law size distribution similar to that inferred for comet Halley, is applied to the observations. The model provides a good match to the observed heliocentric variation of both the 10 micrometers feature and the overall thermal emission from comets West and Halley. Matches to the observations of comet IRAS-Araki-Alcock and the antitail of comet Kohoutek require slightly larger grains. While the model does not match the exact profile and position of the 3.4 micrometers feature discovered in comet Halley, it does produce a qualitative fit to the observed variation of the feature's strength as a function of heliocentric distance. The calculations predict that the continuum under the 3.4 micrometers feature is due primarily to thermal emission from the comet dust when the comet is close to the Sun and to scattered solar radiation at large heliocentric distances, as is observed. A brief discussion of the determination of cometary grain temperatures from the observed infrared emission is presented. It is found that the observed shape of the emission curve from about 4 to 8 micrometers provides the best spectral region for estimating the cometary grain temperature distribution.

Swamy, K. S. Krishna↗
NASA NTRS1997

Strain-Rate-Free Diffusion Flames: Initiation, Properties, and Quenching

For about a half century, the stabilization of a steady planar deflagration on a heat-sink-type flat-flame burner has been of extraordinary service for the theoretical modeling and diagnostic probing of combusting gaseous mixtures. However, most engineering devices and most unwanted fire involve the burning of initially unmixed reactants. The most vigorous burning of initially separated gaseous fuel and oxidizer is the diffusion flame. In this useful idealization (limiting case), the reactants are converted to product at a mathematically thin interface, so no interpenetration of fuel and oxidizer occurs. This limit is of practical importance because it often characterizes the condition of optimal performance (and sometimes environmentally objectionable operation) of a combustor. A steady planar diffusion flame is most closely approached in the laboratory in the counterflow apparatus. The utility of this simple-strain-rate flow for the modeling and probing of diffusion flames was noted by Pandya and Weinberg 35 years ago, though only in the last decade or so has its use become internationally common place. However, typically, as the strain rate a is reduced below about 20 cm(exp -1), and the diffusion-flame limit (reaction rate much faster than the flow rate) is approached, the burning is observed to become unstable in earth gravity. The advantageous steady planar flow is not available in the diffusion-flame limit in earth gravity. This is unfortunate because the typical spatial scale in a counterflow is (k/a)(sup 1/2), where k denotes a characteristic diffusion coefficient; thus, the length scale becomes large, and the reacting flow is particularly amenable to diagnostic probing, as the diffusion-flame limit is approached. The disruption of planar symmetry is owing the fact that, as the strain rate a decreases, the residence time (l/a) of the throughput in the counterflow burner increases. Observationally, when the residence time exceeds about 50 msec, the inevitably present convective (Rayleigh-Benard) instabilities, associated with hot-under-cold (flame-under-fresh-reactant) stratification of fluid in a gravitational field, have time to grow to finite amplitude during transit of the burner.

Fendell, Francis↗
NASA NTRS1987

Mixing levels, the Apennine Front soil component, and compositional trends in the Apollo 15 soils

New compositional data (by INAA) for 29 samples of Apollo 15 soil fractions are presented along with data for six depth intervals of the bottom half of the double drive tube at station 2 on the Apennine Front. The compositional trends in the Apollo 15 soils are discussed in terms of four techniques used to determine the important components of the regolith: graphical techniques, factor analysis, chemical analysis of individual soil particles, and mixing models. The concept of 'mixing levels' is introduced, which states that a sample of lunar regolith can be considered as a mixture on several different compositional levels (I, igneous rock types; II, local rock types; III, soils), and it is shown that most attempts at modeling lunar soils as mixtures have been directed at level II. It is argued that only four components are required to account for the variation in concentrations of lithophile elements in the Apollo 15 samples: mare basalt, KREEP basalt, green glass, and Apennine front soil (best represented by the station 2 samples).

Korotev, Randy L.↗
NASA NTRS2024

Simplified Structure Models for Premixed n-Alkane Cool Flames

The chemical kinetics of cool flames in mixtures of normal alkanes, oxygen, and nitrogen recently have been reduced to obtain simplified asymptotic flame-structure models that can be used to compare theoretical predictions with experimental measurements. A key step that affects flame structures strongly, namely the abstraction of a hydrogen atom from the alkyl radical by an oxygen molecule, had not been taken into account in those models. This deficiency has now been remedied for diffusion flames. The present contribution reports the corresponding remedy for premixed-flame analyses. In the new model, non-zero chemical reaction rates are restricted to narrow regions in the vicinity of the maximum temperature, whereas previously they extended throughout the preheat zone. Comparisons of the new predictions with experimental burning-velocity measurements seem favorable.

premixed cool flames↗
DOE OSTI2021

Modeling and simulation of vascular tumors embedded in evolving capillary networks

Here in this work, we present a coupled 3D–1D model of solid tumor growth within a dynamically changing vascular network to facilitate realistic simulations of angiogenesis. Additionally, the model includes erosion of the extracellular matrix, interstitial flow, and coupled flow in blood vessels and tissue. We employ continuum mixture theory with stochastic Cahn–Hilliard type phase-field models of tumor growth. The interstitial flow is governed by a mesoscale version of Darcy’s law. The flow in the blood vessels is controlled by Poiseuille flow, and Starling’s law is applied to model the mass transfer in and out of blood vessels. The evolution of the network of blood vessels is orchestrated by the concentration of the tumor angiogenesis factors (TAFs); blood vessels grow towards the increasing TAFs concentrations. This process is not deterministic, allowing random growth of blood vessels and, therefore, due to the coupling of nutrients in tissue and vessels, makes the growth of tumors stochastic. We demonstrate the performance of the model by applying it to a variety of scenarios. Numerical experiments illustrate the flexibility of the model and its ability to generate satellite tumors. Simulations of the effects of angiogenesis on tumor growth are presented as well as sample-independent features of cancer.

3D–1D coupled blood flow models↗
DOE OSTI2020

BioSTEAMDevelopmentGroup/thermosteam

BioSTEAM is a fast and flexible package for the design, simulation, and techno-economic analysis of biorefineries under uncertainty. BioSTEAM’s framework is built to streamline and automate early-stage technology evaluations and to enable rigorous sensitivity and uncertainty analyses. Complete biorefinery configurations are available at the Bioindustrial-Park GitHub repository, BioSTEAM’s premier repository for biorefinery models and results. The long-term growth and maintenance of BioSTEAM is supported through both community-led development and the research institutions invested in BioSTEAM. Through the open-source and community-lead platform, BioSTEAM aims to foster communication and transparency within the biorefinery research community for an integrated effort to expedite the evaluation of candidate biofuels and bioproducts. Additionally, an agile life cycle assessment (LCA) platform has been designed to interface with BioSTEAM, BioSTEAM-LCA. This open-source, installable package allows users to perform streamlined LCAs of biorefineries. The focus of BioSTEAM-LCA is to streamline and automate early-stage environmental impact analyses of processes and technologies, and to enable rigorous sensitivity and uncertainty analyses linking process design, performance, economics, and environmental impacts. ThermoSTEAM is a standalone thermodynamic engine capable of estimating mixture properties, solving thermodynamic phase equilibria, and modeling stoichiometric reactions. ThermoSTEAM builds upon chemicals, the chemical properties component of the Chemical Engineering Design Library, with a robust and flexible framework that facilitates the creation of property packages. The Biorefinery Simulation and Techno-Economic Analysis Modules (BioSTEAM) is dependent on ThermoSTEAM for the simulation of unit operations.

Cortes-Peña, Yoel↗
NASA NTRS1978

Theoretical models for Mars and their seismic properties

Theoretical seismic properties of the planet Mars are investigated on the basis of the various models which have been proposed for the internal composition of the planet. The latest interpretation of gravity-field data, assuming a lower value of the moment of inertia, would require a less dense mantle and a larger core than previous models. If Mars is chondritic in composition, the most reasonable models are an incompletely differentiated H-chondrite or a mixture of H-chondrites and carbonaceous chondrites. Seismic profiles, travel times, and free oscillation periods are computed for various models, with the aim of establishing which seismic data is crucial for deciding among the alternatives. A detailed discussion is given of the seismic properties which could - in principle - help answer the questions of whether Mars' core is liquid or solid and whether Mars has a partially molten asthenosphere in its upper mantle.

Okal, E. A.↗
DOE OSTI2026

HARMONY: Large-Scale Architecture Search for Efficient Hybrid Language Models

As large language models scale to trillions of parameters, their computational and memory requirements present critical challenges for efficient training and deployment. While Mixture of Experts (MoE) architectures enable efficient scaling through sparse parameter activation, and state-space models like Mamba offer linear-time complexity, principled methods for combining these paradigms remain undeveloped. We introduce HARMONY (Hybrid Architecture Research for Mamba, Optimized with Neural efficiencY), a multi-objective evolutionary neural architecture search framework for discovering efficient hybrid language models that integrate Transformer attention mechanisms, Mixture-of-Experts routing, and Mamba state-space components. Through large-scale distributed search using 16,384 MI250X GPUs on the Frontier supercomputer, HARMONY explores a comprehensive design space encompassing six attention variants (MHA, MQA, GQA, MLA, SWA, and Mamba-2), variable MoE configurations with both routed and shared experts, and extensive Mamba hyperparameters. Our framework discovers heterogeneous architectures that balance training performance with computational efficiency through multi-objective optimization incorporating latency penalties and fitness-based selection. Analysis of discovered architectures reveals that optimal hybrid designs favor heterogeneous component mixing rather than homogeneous patterns, with Mamba-2 and Multi-Head Latent Attention (MLA) emerging as preferred mechanisms. Discovered architectures demonstrate superior training efficiency: our best configuration achieves a final perplexity of 1.0874 with 2.38B parameters while processing 4,320 tokens/second, outperforming significantly larger manually designed models. Full-scale evaluation shows HARMONY's top architectures achieve better loss trajectories than equivalently-sized models using state-of-the-art configurations including Mixtral, Jamba, and Samba. Additionally, we demonstrate 91% weak scaling efficiency when training discovered 36B-parameter models across 1,024 GPUs. HARMONY is released as an open framework with comprehensive tools for building and training hybrid models using expert-data-pipeline parallelism, democratizing access to automated architecture design for next-generation language models.

Herron, Emily [ORNL] (ORCID:0000000273008172)↗
DOE OSTI2025

HIGH-FIDELITY SIMULATION OF SOOT FORMATION AND THERMAL RADIATION IN A LABORATORY-SCALE RICH-QUENCH-LEAN BURNER

High-fidelity simulations of a swirl-stabilized turbulent spray flame in a laboratory-scale aero-combustor have been performed to evaluate the predictability of state-of-the-art models in capturing soot formation. The simulations employ a complex chemical mechanism developed for Jet-A with PAH chemistry, coupled with the Hybrid Method of Moments (HMOM) soot model, and a Lagrangian dilute spray model for the fuel injection. Two simulations are performed to compare the results when thermal radiation is neglected or included in the solution with a mean spectral model. Modeling closures for the soot differential diffusion effects in mixture fraction space, as well as turbulence-radiation interaction are also evaluated using the data generated by the simulations. Given the degree of complexity of the simulation, the results showed good agreement with experimental measurements of the spatial distribution of the soot volume fraction ensemble average. A closer agreement with the experiment is observed when thermal radiation is included in the solution. Thermal radiation is observed to reduce the flame temperature and increase the flame intermittency, denoted by the increase in the temperature standard deviation in mixture fraction space. The reduction in temperature also leads to a reduction in PAH production and soot volume fraction. Turbulence is observed to have different effects on radiative emission depending on the mixture fraction. Turbulent scalar fluctuations significantly enhance radiative emission in fuel lean mixtures and can also play a role for fuel rich conditions. The statistical description of the turbulence-radiation interaction, previously proposed in the literature, was observed to correctly reproduce the high-fidelity results. Model coefficients were provided for swirl-stabilized flames. The soot differential diffusion model, previously proposed in the literature, based on the residual between the exact term and its model approximation, was also evaluated. The residual correction term further improved the agreement with exact differential diffusion term evaluated with the high-fidelity simulation data in mixture fraction space. The results suggest that the effective turbulent Lewis number can be equal to unity in simulations of turbulent non-premixed recirculating flames.

Soriano, Bruno [Sandia National Laboratories (SNL)↗
DOE OSTI2025

Atomistic Insights into Lithium–Glyme Solvate Ionic Liquids: Effects of Chain Length and Anion Coordination

For this study, mixtures of lithium bis(trifluoromethanesulfonyl)imide (LiTFSI) in diglyme (G2), triglyme (G3) and tetraglyme (G4) at solvate ionic liquid (SIL) concentrations were investigated using classical molecular dynamics (cMD) simulations with a physically motivated force-field specifically developed for modeling these systems. The structural and dynamical properties of the mixtures were computed and analyzed. Lithium solvation shells, radial distribution functions, and X-ray structure factors were studied across the different SIL systems. Translational diffusion and rotational relaxation times were also evaluated, exhibiting similar trends with increasing glyme chain length. The results are consistent with experimental data and in good agreement with previous computational studies on G3 and G4. These findings validate the accuracy of the force field in modeling glyme systems and its use for describing the [Li(G2) 4/3 ][TFSI] mixture. Additionally, the thermal and electrochemical stability of these electrolytes were systematically examined. The thermal stability appears to be governed by cooperative interactions among glyme molecules, while the electrochemical stability is primarily influenced by Li + -anion interactions, which vary significantly with glyme chain length. Overall, the study sheds light on the crucial role of the anion in these glyme-based SILs and offers valuable insights into Li + -glyme systems at SIL concentrations, highlighting their promise as potential Li-ion battery electrolytes.

anions↗
DOE OSTI2020

A simple and effective five-equation two-phase numerical model for liquid-vapor phase transition in cavitating flows

Numerical difficulties, notably the non-monotonic behavior of the Wood speed of sound and the volume fraction positivity, associated with the reduced five-equation two-phase flow model of Kapila et al. (2001) [A.K. Kapila, R. Menikoff, J.B. Bdzil, S.F. Son, D.S. Stewart, 2001. Two-phase modeling of deflagration-to-detonation transition in granular materials: reduced equations, Physics of Fluids 13(10), 3002–3024] have been resolved in the past through the introduction of a frozen speed of sound and an algebraic approach for mechanical relaxation afforded by a pressure non-equilibrium six-equation model proposed by [R. Saurel, F. Petitpas, R.A. Berry, 2009. Simple and efficient relaxation methods for interfaces separating compressible fluids, cavitating flows and shocks in multiphase mixture, J. Comput. Phys. 228, 1678–1712]. By contrast, it is explored and demonstrated in this work that these difficulties can in fact still be resolved within the numerical scheme for solving the reduced five-equation model by numerically replacing the Wood speed of sound for the estimates of wave speeds in the approximate Riemann solver HLLC with the monotonic mixture speed of sound for a transport five-equation model. For shock interface (artificial mixture separating pure or nearly pure fluids) interaction problems, with the apparent advantage of monotonic behavior of the speed of sound in the interface, the effect of the numerical replacement is also confined to the interface. Differences other than the behavior of the speed of sound within the interface in the solutions due to the replacement diminish with increasing resolution when reasonable solution can be obtained with Wood speed of sound. For cavitating/expansion problems in physical fluid mixture, it is pointed out and explained why acoustics in the numerical solutions still propagate at the Wood speed of sound (therefore consistent with the reduced five-equation model) even though in some cases a much higher speed of sound like the numerical replacement above for solving the reduced five-equation model or the frozen speed of sound for solving a six-equation model is used for the estimates of wave speeds in the HLLC scheme. A variant of the five-equation two-phase flow model by Saurel et al. (2008) [R. Saurel, F. Petitpas, R. Abgrall, 2008. Modelling phase transition in metastable liquids: application to cavitating and flashing flows, J. Fluid Mech. 607, 313–350] is then constructed for liquid-vapor phase transition in cavitating flows. The relaxation toward thermo-chemical equilibrium during phase transition is achieved by solving a simple system of algebraic equations for the equilibrium state variables for better efficiency, following Pelanti and Shyue (2014) [M. Pelanti, K.-M. Shyue, 2014. A mixture-energy-consistent six-equation two-phase numerical model for fluid with interfaces, cavitation and evaporation waves. J. Comput. Phys. 259, 331–357]. Therefore, the current model retains both the simplicity afforded by the five-equation model and the efficiency of the algebraic relaxation solver. An alternative algebraic approach for handling the non-conservative term (the so-called K∇ · u term) in the reduced five-equation model for mechanical equilibrium of a liquid-vapor mixture is also explored by enforcing the thermal equilibrium at the same time. Finally, numerical results of sample tests in both one and two dimensions in the literature as well as that in three dimensions demonstrate the effectiveness and ability of the proposed model to simulate cavitating flows. An interesting mechanism of shock generation by acoustics in water due to phase transition is then found by the numerical simulations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Static and dynamic properties of multi-ionic plasma mixtures

Complex plasma mixtures with three or more components are often encountered in astrophysics or in inertial confinement fusion (ICF) experiments. For mixtures containing species with large differences in atomic number Z, the modeling needs to consider at the same time the kinetic theory for low-Z elements combined with the theory of strongly coupled plasma for high-Z elements, as well as all the intermediate situations that can appear in multi-component systems. For such cases, we study the pair distribution functions, self-diffusions, mutual diffusion and viscosity for ternary mixtures at extreme conditions. These quantities can be produced from first principles using orbital free molecular dynamics at the computational expense of very intensive simulations to reach good statistics. Utilizing the first-principles results as reference data, we assess the merit of a global analytic model for transport coefficients, "Pseudo-Ions in Jellium" (PIJ), based on an iso-electronic assumption (iso-n e ). With a multi-component hypernetted-chain integral equation, we verify the quality of the iso-n e prescription for describing the static structure of the mixtures. This semi-analytical modeling compares well with the simulation results and allows one to consider plasma mixtures not accessible to simulations. Further, applications are given for the mix of materials in ICF experiments. A reduction of a multicomponent mixture to an effective binary mixture is also established in the hydrodynamic limit and compared with PIJ estimations for ICF relevant mixtures.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Uncertainty quantification of a deep learning fuel property prediction model

Deep learning models are being widely used in the field of combustion. Given the black-box nature of typical neural network based models, uncertainty quantification (UQ) is critical to ensure the reliability of predictions as well as the training datasets, and for a principled quantification of noise and its various sources. Deep learning surrogate models for predicting properties of chemical compounds and mixtures have been recently shown to be promising for enabling data-driven fuel design and optimization, with the ultimate goal of improving efficiency and lowering emissions from combustion engines. In this study, UQ is performed for a multi-task deep learning model that simultaneously predicts the research octane number (RON), Motor Octane Number (MON), and Yield Sooting Index (YSI) of pure components and multicomponent blends. The deep learning model is comprised of three smaller networks: Extractor 1, Extractor 2, and Predictor, and a mixing operator. The molecular fingerprints of individual components are encoded via Extractor 1 and Extractor 2, the mixing operator generates fingerprints for mixtures/blends based on linear mixing operation, and the predictor maps the fingerprint to the target properties. Two different classes of UQ methods, Monte Carlo ensemble methods and Bayesian neural networks (BNNs), are employed for quantifying the epistemic uncertainty. Combinations of Bernoulli and Gaussian distributions with DropConnect and DropOut techniques are explored as ensemble methods. All the DropConnect, DropOut and Bayesian layers are applied to the predictor network. Aleatoric uncertainty is modeled by assuming that each data point has an independent uncertainty associated with it. The results of the UQ study are further analyzed to compare the performance of BNN and ensemble methods. Although this study is confined to UQ of fuel property prediction, the methodologies are applicable to other deep learning frameworks that are being widely used in the combustion community.

33 ADVANCED PROPULSION SYSTEMS↗