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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Stagnation Point Convective Heating Correlations for Entry Into H2/He Atmospheres

New convective heating correlations have been developed over a broad range of entry conditions into H2/He atmospheres. The correlations are based on calculations of stagnation point convective heat fluxes over a large range of velocities, densities, and effective nose radii. The heat fluxes and corresponding flowfields are computed using NASA’s hypersonic computational fluid dynamics code, DPLR. Cases in this study have been computed using both a temperaturelimited, radiative equilibrium wall and a cold wall temperature boundary condition. The results for the scaled heat flux, as a function of the difference in freestream and wall enthalpies, show a clear deviation from the linear trend predicted by the method of Sutton and Graves. Therefore, updated non-linear correlations are proposed for the prediction of stagnation point convective heat fluxes. Generally, these updated correlations predict lower heat loads and therefore smaller required TPS thicknesses when compared to previous correlations for a range of test cases in the Neptune, Saturn, and Uranus atmospheres.

Alex T. Carroll↗
NASA NTRSDate not supplied

Stagnation Point Convective Heating Correlations for Entry Into H2/He Atmospheres

New convective heating correlations have been developed over a broad range of entry conditions into H2/He atmospheres. The correlations are based on calculations of stagnation point convective heat fluxes over a large range of velocities, densities, and effective nose radii. The heat fluxes and corresponding flow fields are computed using NASA’s hypersonic computational fluid dynamics code, DPLR. Cases in this study have been computed using both a temperature limited, radiative equilibrium wall and a cold wall temperature boundary condition. The results for the scaled heat flux, as a function of the difference in freestream and wall enthalpies, show a clear deviation from the linear trend predicted by the method of Sutton and Graves. Therefore, updated non-linear correlations are proposed for the prediction of stagnation point convective heat fluxes. Generally, these updated correlations predict lower heat loads and therefore smaller required TPS thicknesses when compared to previous correlations for a range of test cases in the Neptune, Saturn, and Uranus atmospheres.

Alex T. Carroll↗
NASA NTRS2005

Design of a Mach-15 Total-Enthalpy Nozzle with Non-Uniform Inflow Using Rotational MOC

A new computer program to design nozzles with non-uniform idow has been developed using the rotational method of characteristics (MOC). This program has been used to design a nozzle for the NASA's HYPULSE shock-expansion tunnel for use in scramjet engine tests at a Mach-15 flight-enthalpy condition. The nozzle has an area ratio of 9.5:l that expands the inflow from Mach 6 along the centerline to Mach 8.7. Although the density and Mach number vary radially at the exit due to the non-uniformities of the inflow, the MOC procedure produces exit flow that is parallel and has uniform static pressure. The design has been verified with CFD which compares favorably with the MOC solution.

Gaffney, Richard L., Jr.↗
NASA NTRS2004

Design of a Mach-15 Total-Enthalpy Nozzle With Non-uniform Inflow Using Rotational MOC

A new computer program to design nozzles with non-uniform inflow has been developed using the rotational method of characteristics (MOC). This program has been used to design a nozzle for the NASA's HYPULSE shock-expansion tunnel for use in scramjet engine tests at a Mach-15 flight-enthalpy condition. The nozzle has an area ratio of 9.5:1 that expands the inflow from Mach 6 along the centerline to Mach 8.7. Although the density and Mach number vary radially at the exit due to the non-uniformities of the inflow, the MOC procedure produces exit flow that is parallel and has uniform static pressure. The design has been verified with CFD which compares favorably with the MOC solution.

Gaffney, Richard L., Jr.↗
DOE OSTI2020

Reactants, products, and transition states of elementary chemical reactions based on quantum chemistry

Reaction times, activation energies, branching ratios, yields, and many other quantitative attributes are important for precise organic syntheses and generating detailed reaction mechanisms. Often, it would be useful to be able to classify proposed reactions as fast or slow. However, quantitative chemical reaction data, especially for atom-mapped reactions, are difficult to find in existing databases. Therefore, we used automated potential energy surface exploration to generate 12,000 organic reactions involving H, C, N, and O atoms calculated at the ω B97X-D3/def2-TZVP quantum chemistry level. We report the results of geometry optimizations and frequency calculations for reactants, products, and transition states of all reactions. Additionally, we extracted atom-mapped reaction SMILES, activation energies, and enthalpies of reaction. We believe that this data will accelerate progress in automated methods for organic synthesis and reaction mechanism generation—for example, by enabling the development of novel machine learning models for quantitative reaction prediction.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1982

A method to model latent heat for transient analysis using NASTRAN

A sample heat transfer analysis is demonstrated which includes the heat of fusion. The method can be used to analyze a system with nonconstant specific heat. The enthalpy is introduced as an independent degree of freedom at each node. The user input consists of a curve of temperature as a function of enthalpy, which may include a constant temperature phase change. The basic NASTRAN heat transfer capability is used to model the effects of latent heat with existing direct matrix output and nonlinear load data cards. Although some user care is required, the numerical stability of the integration is quite good when the given recommendations are followed. The theoretical equations used and the NASTRAN techniques are shown.

Harder, R. L.↗
NASA NTRS1971

Finite difference solution to the three-dimensional, incompressible thermal energy boundary-layer equation

An implicit numerical method has been adopted for the solution to the three-dimensional, energy boundary-layer equation. The energy equation is written in terms of a dimensionless temperature function, the relative stagnation-enthalpy difference, and transformed by the introduction of a Blasius-type transformation of coordinates as well as dimensionless stream functions. The method is applied to the problem consisting of an infinite cylinder joined with its axis perpendicular to a thin, flat, heated plate. A Prandtl number equal to one is simply considered.

Fillo, J. A.↗
NASA NTRS1972

Analysis of flight test transition and turbulent heating data. Part 2: Turbulent heating results

The results of three turbulent heating predictions (Van Driest II, Spalding-Chi, and Walker Eckert reference enthalpy) have been compared to the data of several re-entry vehicles. Details and comparisons of each technique with the data are presented. The data analyzed cover a range of local Mach numbers of 3.3 to 15.2, wall to boundary layer edge temperature ratio of 0.46 to 2.6 and local Reynolds number of 7 times 10 to the 6th power to 5.3 times 10 to the 8th power. Data were transformed to an incompressible plane, using the prediction methods above, and compared with the Colburn and von Karman forms of the Reynolds analogy. The results indicate that the reference enthalpy technique best fits the data when the Colburn analogy was used; whereas, the Van Driest II method agrees with both forms of the Reynolds analogy. The Spalding-Chi method tends to under predict the data. Finally, there does not appear to be any significant difference when comparing the incompressible Stanton number as a function of Renolds number based on either wetted length or momentum thickness.

Laganelli, A. L.↗
DOE OSTI2025

Leveraging Natural Language Processing and Generative Models in Molecular Chemistry: Property Prediction and Novel Compound Generation

The accurate prediction of molecular properties is important for the rational design and the advancement of green chemistry and sustainable materials research. However, the predictive power of traditional computational chemistry methods is limited due to computational restrictions. Here, in this study, we examine an alternative approach to the accurate prediction of properties of organic compounds: natural language processing (NLP)-based molecular embedding. Using viscosity, partition coefficient (log P), and enthalpy of vaporization as test properties through a survey of comprehensive datasets comprising 5695 data points for viscosity, 25 870 data points for log P, and 2296 data points for enthalpy of vaporization. These are important properties for the design of greener, safer, and sustainable chemical processes. Models were trained using NLP methods such as Mol2vec and fine-tuned ChemBERTa, and results were compared with traditional input featurization techniques such as Morgan fingerprints and quantum chemistry derived sigma profiles and DFT features. Among the various machine learning models, Mol2vec demonstrated superior predictive capabilities, achieving the highest correlation coefficient (R 2 = 0.945) and lowest RMSE (0.106 mPa s) for viscosity, as well as high accuracy for log P and enthalpy of vaporization predictions. These findings establish the Mol2vec featurization technique, graph-convolutional neural networks (GCNN), and fine-tuned ChemBERTa model as powerful tools for predictive modeling of organic compounds properties, offering a significant improvement over previously used featurization techniques and opening up strategies for very-high-throughput computational screening. Finally, we integrated ML models with hybrid language-model-based generative adversarial networks (LM-GAN) to generate novel molecular sequences with desirable properties for different research applications. The ability to computationally design solvents with lower viscosity, lower log P, and lower enthalpy of vaporization offers a data-driven route to accelerating the discovery of sustainable alternatives to traditionally toxic solvents.

ChemBERTa↗
DOE OSTI2026

Approximation of refrigerant thermophysical properties using neural networks to speed up transient thermofluid simulations

Accurate and efficient evaluations of refrigerant thermophysical properties and their partial derivatives are essential for transient simulations of thermofluid systems, where several computations need to be executed at each integration time step. Since the utilization of an Equation of State for retrieving properties based on a pair of independent inputs typically involves numerical iterations in solution procedures, when the input variables differ from the refrigerant state variables employed in dynamic models, a variety of approaches including lookup table interpolation and curve fitting have been developed to explicitly approximate these properties based on the state variables, and consequently eliminate internal iterations. This paper presents an alternative method that exploits derivative-informed neural networks to model refrigerant properties explicitly from inputs of pressure and enthalpy, while ensuring consistent partial derivatives generated by differentiating the neural networks. Computational speed and accuracy of the proposed approach are demonstrated via transient simulations of a discretized heat exchanger model in Modelica, and comparisons against other property evaluation routines. Simulation results indicate that the proposed approach can realize a significant speedup with negligible discrepancies in predicted transients. The method is implemented in an open-source Modelica library.

Ma, Jiacheng↗
DOE OSTI2021

Molecular dynamics and experimental study on the adhesion mechanism of polyvinyl alcohol (PVA) fiber in alkali-activated slag/fly ash

This paper aims to study the adhesion mechanism of polyvinyl alcohol (PVA) fiber within alkali-activated slag/fly ash (AASF) matrix using molecular dynamics (MD) simulation in combination with systematic experimental characterization. The adhesion of PVA to C-(N-)A-S-H gel with different Ca/(Si+Al) and Al/Si ratios was modeled using MD simulation, with the related adsorption enthalpy calculated and the adhesion mechanism explored. The experimentally attained chemical bonding energy of PVA fiber in AASF coincides well with the simulation results. In both cases, the adhesion enhances primarily with increasing Ca/(Si+Al) ratio of C-(N-)A-S-H gel. Additionally, MD simulation indicates preferential element distributions of Ca around PVA molecule, which was confirmed experimentally by the detection of the Ca-rich C-(N-)A-S-H gel in the interfacial transition zone (ITZ). }This study provides further insights into the adhesion mechanism of PVA fiber to C-(N-)A-S-H gel formed in AASF, which is particularly valuable for the future development of PVA-based high-performance alkali-activated composites.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Energy of Fluid (EOF) Simulation of Large-Scale Densification and Solidification of Hydrogen

The current research develops a finite volume-based Computation Fluid Dynamic (CFD) model utilizing an Energy of Fluid (EOF) approach to generate a simulation of the densification of liquid hydrogen (LH2) in the Integrated Refrigeration and Storage (IRAS) experimental tank for the Ground Operations Demonstration Unit for Liquid Hydrogen Project (GODU-LH2) at the Kennedy Space Center (KSC). The computational code will integrate a commercial software pressure-based model with User Defined Functions (UDF) generated and added to the model. The modified model will solve the energy equation in terms of internal energy and provide temperature and pressure calculations for a given tank geometry. This method will decrease computational time when compared to the built-in commercially available Enthalpy solvers. Currently the research focused on utilizing User Defined Scalars (UDS) compared to the enthalpy model and a lumped node analysis to show the written UDS is as accurate as the built-in solvers, and the models will be verified using known solutions for solidification and validated with the experimental results from the Cryogenics Test Laboratory (CTL) at KSC for the IRAS densification process.

C. Mahony↗
DOE OSTI2022

IMPROVING THE ACCURACY OF COMPOSITE METHODS: A G4MP2 METHOD WITH G4-LIKE ACCURACY AND IMPLICATIONS FOR MACHINE LEARNING

G4MP2 theory has proven to be a reliable and accurate quantum chemical composite method for the calculation of molecular energies using an approximation based on second-order perturbation theory to lower computational costs compared to G4 theory. However, it has been found to have significantly increased errors when applied to larger organic molecules with 10 or more nonhydrogen atoms. We report here on an investigation of the cause of the failure of G4MP2 theory for such larger molecules. One source of error is found to be the "higher-level correction (HLC)", which is meant to correct for deficiencies in correlation contributions to the calculated energies. This is because the HLC assumes that the contribution is independent of the element and the type of bonding involved, both of which become more important with larger molecules. We address this problem by adding an atom-specific correction, dependent on atom type but not bond type, to the higher-level correction. We find that a G4MP2 method that incorporates this modification of the higher-level correction, referred to as G4MP2A, becomes as accurate as G4 theory (for computing enthalpies of formation) for a test set of molecules with less than 10 nonhydrogen atoms as well as a set with 10-14 such atoms, the set of molecules considered here, with a much lower computational cost. The G4MP2A method is also found to significantly improve ionization potentials and electron affinities. Finally, we implemented the G4MP2A energies in a machine learning method to predict molecular energies.

Dandu, Naveen↗
NASA NTRS1994

Conditional statistics in a turbulent premixed flame derived from direct numerical simulation

The objective of this paper is to briefly introduce conditional moment closure (CMC) methods for premixed systems and to derive the transport equation for the conditional species mass fraction conditioned on the progress variable based on the enthalpy. Our statistical analysis will be based on the 3-D DNS database of Trouve and Poinsot available at the Center for Turbulence Research. The initial conditions and characteristics (turbulence, thermo-diffusive properties) as well as the numerical method utilized in the DNS of Trouve and Poinsot are presented, and some details concerning our statistical analysis are also given. From the analysis of DNS results, the effects of the position in the flame brush, of the Damkoehler and Lewis numbers on the conditional mean scalar dissipation, and conditional mean velocity are presented and discussed. Information concerning unconditional turbulent fluxes are also presented. The anomaly found in previous studies of counter-gradient diffusion for the turbulent flux of the progress variable is investigated.

Mantel, Thierry↗
DOE OSTI2021

Operational Limits of Redox Metal Oxides Performing Thermochemical Water Splitting

Solar thermochemical hydrogen production is an attractive technology that stores intermittent solar energy in the form of chemical bonds. Efficient operation requires the identification of a redox-active metal oxide (MO x ) material that can achieve high conversion of water to hydrogen at minimal energy input. Water splitting occurs by consecutive reduction and reoxidation reactions of MO x . MO x is reduced to MO x-δ and, in the second step, is reoxidized by water recovering the initial MO x and generate H 2 . The material must reduce at temperatures achievable in concentrated solar receiver/reactors, while maintaining a thermodynamic driving force to split water. At equilibrium, extent of reduction depends on temperature and oxygen partial pressure, and in this analysis, a set of thermodynamic properties, namely, enthalpy and entropy of oxygen vacancy formation, is sufficient to represent MO x . Herein, a method to easily classify materials based on these thermodynamic properties under any condition of oxygen partial pressure and temperature is presented. This method is based on fundamental thermodynamic principles and is applicable for any redox material with known thermodynamic properties. Despite the simplicity of the method, it is believed that this analysis will support future research in targeting thermodynamic properties of redox-active metal oxides.

water splitting↗
DOE OSTI2022

Evidence for Dissociation and Ionization in Shock Compressed Nitrogen to 800 GPa

Triple bonding in the nitrogen molecule (N 2 ) is among the strongest chemical bonds with a dissociation enthalpy of 9.8 eV/molecule. Nitrogen is therefore an excellent test bed for theoretical and numerical methods aimed at understanding how bonding evolves under the influence of the extreme pressures and temperatures of the warm dense matter regime. Here, we report laser-driven shock experiments on fluid molecular nitrogen up to 800 GPa and 4.0 g/cm 3 . Line-imaging velocimetry measurements and impedance matching method with a quartz reference yield shock equation of state data of initially precompressed nitrogen. Comparison with numerical simulations using path integral Monte Carlo and density functional theory molecular dynamics reveals clear signatures of chemical dissociation and the onset of L-shell ionization. Furthermore, combining data along multiple shock Hugoniot curves starting from densities between 0.76 and 1.29 g/cm 3 , our study documents how pressure and density affect these changes in chemical bonding and provides benchmarks for future theoretical developments in this regime, with applications for planetary interior modeling, high energy density science, and inertial confinement fusion research.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS2011

The Vaporization of B2O3(l) to B2O3(g) and B2O2(g)

The vaporization of B2O3 in a reducing environment leads to formation of both B2O3(g) and B2O2(g). While formation of B2O3(g) is well understood, many questions about the formation of B2O2(g) remain. Previous studies using B(s) + B2O3(l) have led to inconsistent thermodynamic data. In this study, it was found that after heating, B(s) and B2O3(l) appear to separate and variations in contact area likely led to the inconsistent vapor pressures of B2O2(g). To circumvent this problem, an activity of boron is fixed with a two-phase mixture of FeB and Fe2B. Both second and third law enthalpies of formation were measured for B2O2(g) and B2O3(g). From these the enthalpies of formation at 298.15 K are calculated to be -479.9 +/- 41.5 kJ/mol for B2O2(g) and -833.4 +/- 13.1 kJ/mol for B2O3(g). Ab initio calculations to determine the enthalpies of formation of B2O2(g) and B2O3(g) were conducted using the W1BD composite method and show good agreement with the experimental values.

Jacobson, Nathan S.↗
DOE OSTI2025

Theoretical and experimental quantification of Suzuki segregation enthalpy and strengthening mechanisms in a binary alloy

Solute segregation to planar defects in metallic alloys has been shown to drastically alter mechanical properties. While various works using first-principles and thermodynamic calculations have studied the fundamental driving forces for solute segregation via the Suzuki criterion, planar defect energy, or a comparison of energies of the HCP-like phase and FCC matrix, a quantitative experimental and computational comparison of equilibrium composition and segregation enthalpies has not yet been reported. In this work, we predict the equilibrium composition and segregation enthalpy to intrinsic stacking faults in a Ni-60Co (at.%) alloy and compare the results to two independent experimental methods. We observed that Co segregates to the innermost two planes of the intrinsic stacking fault, and we found that the experimental segregation enrichment, measured from transmission electron microscopy energy dispersive X-ray spectroscopy, of the faults is 6.8 at.% Co, which is 2.2 at.% less than the predicted value at the same temperature. We also find that the segregation enthalpy measured from the composition profile is −21.1 ± 6.4 meV/atom and separately from differential scanning calorimetry segregation enthalpy is −33.2 meV/atom, whereas the predicted enthalpy is −31 ± 1 meV/atom. Based on these results, we determine that segregation occurs very rapidly, within 8 min at temperatures as low as 36% of the homologous solidus temperature. Furthermore, this analysis provides an overview of the possible dislocation mechanisms responsible for strengthening effects due to solute segregation, and concludes that changes in room temperature hardness from local phase transformation is likely tied to post-segregation room temperature equilibrium partial separation distance.

Ab initio calculation↗