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NASA NTRS2014

Propulsion System Simulation Using the Toolbox for the Modeling and Analysis of Thermodynamic System T-MATS

A simulation toolbox has been developed for the creation of both steady-state and dynamic thermodynamic software models. This paper describes the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS), which combines generic thermodynamic and controls modeling libraries with a numerical iterative solver to create a framework for the development of thermodynamic system simulations, such as gas turbine engines. The objective of this paper is to present an overview of T-MATS, the theory used in the creation of the module sets, and a possible propulsion simulation architecture. A model comparison was conducted by matching steady-state performance results from a T-MATS developed gas turbine simulation to a well-documented steady-state simulation. Transient modeling capabilities are then demonstrated when the steady-state T-MATS model is updated to run dynamically.

gas path dynamics↗

NASA NTRS2014

Propulsion System Simulation Using the Toolbox for the Modeling and Analysis of Thermodynamic System (T-MATS)

A simulation toolbox has been developed for the creation of both steady-state and dynamic thermodynamic software models. This presentation describes the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS), which combines generic thermodynamic and controls modeling libraries with a numerical iterative solver to create a framework for the development of thermodynamic system simulations, such as gas turbine engines. The objective of this presentation is to present an overview of T-MATS, the theory used in the creation of the module sets, and a possible propulsion simulation architecture.

aerothermodynamics↗

NASA NTRS2014

Propulsion System Simulation Using the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS)

aerothermodynamics↗

NASA NTRS2016

Thermodynamic Spectrum of Solar Flares Based on SDO/EVE Observations: Techniques and First Results

The Solar Dynamics Observatory (SDO)/EUV Variability Experiment (EVE) provides rich information on the thermodynamic processes of solar activities, particularly on solar flares. Here, we develop a method to construct thermodynamic spectrum (TDS) charts based on the EVE spectral lines. This tool could potentially be useful for extreme ultraviolet (EUV) astronomy to learn about the eruptive activities on distant astronomical objects. Through several cases, we illustrate what we can learn from the TDS charts. Furthermore, we apply the TDS method to 74 flares equal to or greater than the M5.0 class, and reach the following statistical results. First, EUV peaks are always behind the soft X-ray (SXR) peaks and stronger flares tend to have faster cooling rates. There is a power-law correlation between the peak delay times and the cooling rates, suggesting a coherent cooling process of flares from SXR to EUV emissions. Second, there are two distinct temperature drift patterns, called Type I and Type II. For Type I flares, the enhanced emission drifts from high to low temperature like a quadrilateral, whereas for Type II flares the drift pattern looks like a triangle. Statistical analysis suggests that Type II flares are more impulsive than Type I flares. Third, for late-phase flares, the peak intensity ratio of the late phase to the main phase is roughly correlated with the flare class, and the flares with a strong late phase are all confined. We believe that the re-deposition of the energy carried by a flux rope, which unsuccessfully erupts out, into thermal emissions is responsible for the strong late phase found in a confined flare. Furthermore, we show the signatures of the flare thermodynamic process in the chromosphere and transition region in the TDS charts. These results provide new clues to advance our understanding of the thermodynamic processes of solar flares and associated solar eruptions, e.g., coronal mass ejections.

Wang, Yuming↗

NASA NTRSDate not supplied

CFD and Thermodynamic Model Predictions of No-Vent Tank Filling in Microgravity

Cryogenic Fluid Management (CFM) of propellant fluids under low gravity conditions present an important challenge in the pursuit of NASA’s future long-duration space missions. Success of these missions relies to a large extent on the ability to store and transfer the cryogenic liquid fuels efficiently and safely. To this end, the Zero-Boil-Off Tank Filling and Transfer Experiment (ZBOT-FT) undertaken by University of Bremen in collaboration with Case Western Reserve University aims at studying two phase flow tank-to-tank transfer operations in microgravity using a simulant fluid, Perfluoro-n-pentane (PNP). As part of this effort, in this work, we present a system level homogeneous thermodynamic model and a two-phase Computational Fluid Dynamics (CFD) model of a no-vent cylindrical tank filling in microgravity. Both 2D axisymmetric and 3D parametric simulations case studies are performed to show the detailed physics of the filling process and the evolution of tank pressure for filling flow rates between 1.0 and 1.65 mL/s. A zero-dimensional homogeneous thermodynamic model is also developed to predict the final steady state tank pressure analytically. Comparison of the 2D and 3D CFD predictions of final pressures to the steady state thermodynamic results displays very good agreement. However, it is shown that the 2D axisymmetric model predicts a maxima in tank pressure before reaching steady state. It is indicted that this pressure maxima is caused by the constraints inherent in the axisymmetric model and is absent in the 3D and thermodynamic pressure predictions.

Two Phase Flow↗

NASA NTRS1973

Thermodynamic Properties of Nitrogen Including Liquid and Vapor Phases from 63K to 2000K with Pressures to 10,000 Bar

Tables of thermodynamic properties of nitrogen are presented for the liquid and vapor phases for temperatures from the freezing line to 2000K and pressures to 10,000 bar. The tables include values of density, internal energy, enthalpy, entropy, isochoric heat capacity, isobaric heat capacity velocity of sound, the isotherm derivative, and the isochor derivative. The thermodynamic property tables are based on an equation of state, P=P (p,T), which accurately represents liquid and gaseous nitrogen for the range of pressures and temperatures covered by the tables. Comparisons of property values calculated from the equation of state with measured values for P-p-T, heat capacity, enthalpy, latent heat, and velocity of sound are included to illustrate the agreement between the experimental data and the tables of properties presented here. The coefficients of the equation of state were determined by a weighted least squares fit to selected P-p-T data and, simultaneously, to isochoric heat capacity data determined by corresponding states analysis from oxygen data, and to data which define the phase equilibrium criteria for the saturated liquid and the saturated vapor. The vapor pressure equation, melting curve equation, and an equation to represent the ideal gas heat capacity are also presented. Estimates of the accuracy of the equation of state, the vapor pressure equation, and the ideal gas heat capacity equation are given. The equation of state, derivatives of the equation, and the integral functions for calculating derived thermodynamic properties are included.

Thermodynamic properties↗

NASA NTRS2020

A Machine Learning-Based Cloud Detection and Thermodynamic Phase Classification Algorithm using Passive Spectral Observations

We trained two Random Forest (RF) machine-learning models for cloud mask and cloud thermodynamic phase detection using spectral observations from VIIRS on Suomi NPP (SNPP). Observations from CALIOP were carefully selected to provide reference labels. The two RF models were trained for all-day and daytime-only conditions using a 4-year collocated VIIRS/CALIOP dataset from 2013 to 2016. Due to the orbit difference, the collocated CALIOP and SNPP VIIRS training samples cover a broad viewing zenith angle range, which is a great benefit to overall model performance. The all-day model uses 3 VIIRS infrared (IR) bands (8.6,11, and 12 μm) and the daytime model uses 5 Near-IR (NIR) and Shortwave-IR (SWIR) bands (0.86, 1.24, 1.38, 1.64 and 2.25 μm) together with the 3 IR bands to detect clear, liquid water, and ice cloud pixels. Up to 7 surface types, namely, ocean/water, forest, cropland, grassland, snow/ice, barren/desert, and shrubland, were considered separately to enhance performance for both models. Detection of cloudy pixels and thermodynamic phase with the two RF models were compared against collocated CALIOP products from 2017. It is shown that, with a conservative screening process that excludes the most challenging cloudy pixels for passive remote sensing, the two RF models have high accuracy rates in comparison with the CALIOP reference for both cloud detection and thermodynamic phase. Other existing SNPP VIIRS and Aqua MODIS cloud mask and phase products are also evaluated, with results showing that the two RF models and the MODIS MYD06 optical property phase product are the top 3 algorithms with respect to lidar observations during the daytime. During the nighttime, the RF all-day model works best for both cloud detection and phase, in particular for pixels over snow/ice surfaces. The present RF models can be extended to other similar passive instruments if training samples can be collected from CALIOP or other lidars. However, the quality of reference labels and potential sampling issues that may impact model performance would need further attention.

cloud detection↗

NASA NTRS2021

Machine Learning the COSMO Model for Predicting Thermodynamics of Electrolyte Mixtures

Bottom-up design of electrolyte mixtures for battery systems requires predicting macro thermodynamic properties from molecular constituents. For instance, molten salt electrolyte batteries require conditions far above room temperature to operate. Therefore, discovering mixtures with increasingly lower eutectic melting points is desirable. A model that can approximate chemical activity is a valuable tool to search through the vast compositional design space. Machine learning can predict properties of materials such as vibrational free energies, electronic energy gaps, and thermal conductivities. Moreover, they can learn physical models such as interatomic potentials. The COSMO-SAC model uses theory and empirical parameterization to predict liquid-vapor and liquid-solid properties using first-principles calculations. However, obtaining activity coefficients required for parameterizing the COSMO-SAC model is costly and limited to a select chemical space. In this work, we explored if machine learning methods could improve the COSMO-SAC model and bridge density functional theory calculations to liquid phase thermodynamic properties. Our data-driven approach uses existing databases for sigma-profiles of organic solvents and reconciles their methodological differences via ensemble averaging. First, an optimal machine learning model is constructed for each dataset. Our machine learning algorithms use the sigma-profile as an input feature to predict binary mixtures' activity coefficients using multi-output regression. Each dataset uses different choices of functionals, methods, and basis sets. Therefore, our ensemble model attempts to predict corrected activity coefficients given the combination of all the model outputs. The activity coefficients used for training are generated using the COSMO-SAC model. This approach enables the extraction of meaningful information from the existing datasets to improve the COSMO-SAC model for obtaining thermodynamic properties of electrolyte mixtures. With the liquid phase activities, we can identify electrolyte mixtures that meet desired phase equilibria conditions.

Thermodynamics↗

NASA NTRS2021

Evaluation and Applications of Multi-Instrument Boundary-Layer Thermodynamic Retrievals

Recent reports have highlighted the need for improved observations of the boundary layer. In this study, we explore the combination of ground-based active and passive remote sensors deployed for thermodynamic profiling to analyze various boundary-layer observation strategies. Optimal-estimation retrievals of thermodynamic profiles from Atmospheric Emitted Radiance Interferometer (AERI) observed spectral radiance are compared with and without the addition of active sensor observations from a May–June 2017 observation period at the Atmospheric Radiation Measurement–Southern Great Plains Site. In all, three separate thermodynamic retrievals are considered here: retrievals including AERI data only, retrievals including AERI data and Vaisala water vapour differential absorption lidar data, and retrievals including AERI data and Raman lidar data. First, the three retrievals are compared to each other and to reference radiosonde data over the full observation period to get a bulk understanding of their differences and characterize the impact of clouds on these retrieved profiles. These analyses show that the most significant differences are in the water vapour field, where the active sensors are better able to represent the moisture gradient in the entrainment zone near boundary layer top. We also explore how differences in retrievals may impact results of applied analyses including land–atmosphere coupling, convection indices, and severe storm environmental characterization. Overall, adding active sensors to the optimal-estimation retrieval showed some added information, particularly in the moisture field. Given the costs of such platforms, the value of that added information must be weighed for the application at hand.

boundary-layer observation↗

NASA NTRS1972

Polynomial approximations of thermodynamic properties of arbitrary gas mixtures over wide pressure and density ranges

Computer programs for flow fields around planetary entry vehicles require real-gas equilibrium thermodynamic properties in a simple form which can be evaluated quickly. To fill this need, polynomial approximations were found for thermodynamic properties of air and model planetary atmospheres. A coefficient-averaging technique was used for curve fitting in lieu of the usual least-squares method. The polynomials consist of terms up to the ninth degree in each of two variables (essentially pressure and density) including all cross terms. Four of these polynomials can be joined to cover, for example, a range of about 1000 to 11000 K and 0.00001 to 1 atmosphere (1 atm = 1.0133 x 100,000 N/m sq) for a given thermodynamic property. Relative errors of less than 1 percent are found over most of the applicable range.

Allison, D. O.↗

NASA NTRS1973

FORTRAN 4 computer program for calculation of thermodynamic and transport properties of complex chemical systems

A FORTRAN IV computer program for the calculation of the thermodynamic and transport properties of complex mixtures is described. The program has the capability of performing calculations such as:(1) chemical equilibrium for assigned thermodynamic states, (2) theoretical rocket performance for both equilibrium and frozen compositions during expansion, (3) incident and reflected shock properties, and (4) Chapman-Jouguet detonation properties. Condensed species, as well as gaseous species, are considered in the thermodynamic calculation; but only the gaseous species are considered in the transport calculations.

Svehla, R. A.↗

NASA NTRS1973

Thermodynamic properties of UF sub 6 measured with a ballistic piston compressor

From experiments performed with a ballistic piston compressor, certain thermodynamic properties of uranium hexafluoride were investigated. Difficulties presented by the nonideal processes encountered in ballistic compressors are discussed and a computer code BCCC (Ballistic Compressor Computer Code) is developed to analyze the experimental data. The BCCC unfolds the thermodynamic properties of uranium hexafluoride from the helium-uranium hexafluoride mixture used as the test gas in the ballistic compressor. The thermodynamic properties deduced include the specific heat at constant volume, the ratio of specific heats for UF6, and the viscous coupling constant of helium-uranium hexafluoride mixtures.

Sterritt, D. E.↗

NASA NTRS1974

Canonical fluid thermodynamics

The space-time integral of the thermodynamic pressure plays in a certain sense the role of the thermodynamic potential for compressible adiabatic flow. The stability criterion can be converted into a variational minimum principle by requiring the molar free-enthalpy and temperature to be generalized velocities. In the fluid context, the definition of proper-time differentiation involves the fluid velocity expressed in terms of three particle identity parameters. The pressure function is then converted into a functional which is the Lagrangian density of the variational principle. Being also a minimum principle, the variational principle provides a means for comparing the relative stability of different flows. For boundary conditions with a high degree of symmetry, as in the case of a uniformly expanding spherical gas box, the most stable flow is a rectilinear flow for which the world-trajectory of each particle is a straight line. Since the behavior of the interior of a freely expanding cosmic cloud may be expected to be similar to that of the fluid in the spherical box of gas, this suggests that the cosmic principle is a consequence of the laws of thermodynamics, rather than just an ad hoc postulate.

Schmid, L. A.↗

NASA NTRS1976

Correlations for determining thermodynamic properties of hydrogen-helium gas mixtures at temperatures from 7,000 to 35,000 K

Simple relations for determining the enthalpy and temperature of hydrogen-helium gas mixtures were developed for hydrogen volumetric compositions from 1.0 to 0.7. These relations are expressed as a function of pressure and density and are valid for a range of temperatures from 7,000 to 35,000 K and pressures from 0.10 to 3.14 MPa. The proportionality constant and exponents in the correlation equations were determined for each gas composition by applying a linear least squares curve fit to a large number of thermodynamic calculations obtained from a detailed computer code. Although these simple relations yielded thermodynamic properties suitable for many engineering applications, their accuracy was improved significantly by evaluating the proportionality constants at postshock conditions and correlating these values as a function of the gas composition and the product of freestream velocity and shock angle. The resulting equations for the proportionality constants in terms of velocity and gas composition and the corresponding simple realtions for enthalpy and temperature were incorporated into a flow field computational scheme. Comparison was good between the thermodynamic properties determined from these relations and those obtained by using a detailed computer code to determine the properties. Thus, an appreciable savings in computer time was realized with no significant loss in accuracy.

Zoby, E. V.↗

NASA NTRS1977

Thermodynamic properties of gaseous fluorocarbons and isentropic equilibrium expansions of two binary mixtures of fluorocarbons and argon

Equations and computer code are given for the thermodynamic properties of gaseous fluorocarbons in chemical equilibrium. In addition, isentropic equilibrium expansions of two binary mixtures of fluorocarbons and argon are included. The computer code calculates the equilibrium thermodynamic properties and, in some cases, the transport properties for the following fluorocarbons: CCl2F, CCl2F2, CBrF3, CF4, CHCl2F, CHF3, CCL2F-CCl2F, CCLF2-CClF2, CF3-CF3, and C4F8. Equilibrium thermodynamic properties are tabulated for six of the fluorocarbons(CCl3F, CCL2F2, CBrF3, CF4, CF3-CF3, and C4F8) and pressure-enthalpy diagrams are presented for CBrF3.

Talcott, N. A., Jr.↗

NASA NTRS1978

Chemical weathering on Mars - Thermodynamic stabilities of primary minerals /and their alteration products/ from mafic igneous rocks

Chemical weathering on Mars is examined theoretically from the standpoint of thermodynamic equilibrium between primary rock-forming minerals and the atmospheric gases O2, H2O, and CO2. The primary minerals considered are those common to mafic igneous rocks and include olivine, pyroxene, plagioclase, magnetite, troilite, pyrrhotite, and apatite. The importance of kinetics and reaction mechanisms in controlling possible weathering processes on Mars is discussed within the limits of currently available data, and the possible influence of liquid water on Martian weathering processes is evaluated where appropriate. For gas-solid weathering of mafic igneous rocks at the Martian surface, it is concluded that upon attainment of thermodynamic equilibrium: (1) oxides and carbonates should dominate the mineral assemblage of weathering products; (2) hematite rather than goethite should be the stable mineral form of Fe (III); (3) FeSO4 or FeSO4.H2O could be the stable weathering product of iron sulfides in the absence of liquid water; and (4) kaolinite is apparently the only clay mineral that should be thermodynamically stable over all ranges of temperature and water-vapor abundance at the Martian surface.

Gooding, J. L.↗

NASA NTRS1981

Thermodynamic limits to the efficiency of solar energy conversion by quantum devices

The second law of thermodynamics imposes a strict limitation to the energy converted from direct solar radiation to useful work by a quantum device. This limitation requires that the amount of energy converted to useful work (energy in any form other than heat) can be no greater than the change in free energy of the radiation fields. Futhermore, in any real energy conversion device, not all of this available free energy in the radiation field can be converted to work because of basic limitations inherent in the device itself. A thermodynamic analysis of solar energy conversion by a completely general prototypical quantum device is presented. This device is completely described by two parameters, its operating temperature T sub R and the energy threshold of its absorption spectrum. An expression for the maximum thermodynamic efficiency of a quantum solar converter was derived in terms of these two parameters and the incident radiation spectrum. Efficiency curves for assumed solar spectral irradiance corresponding to air mass zero and air mass 1.5 are presented.

Buoncristiani, A. M.↗

NASA NTRS1982

He I lines in B stars - Comparison of non-local thermodynamic equilibrium models with observations

Profiles of He gamma-gamma 4026, 4387, 4471, 4713, 5876, and 6678 have been obtained in 17 stars of spectral type B0-B5. Parameters of the nonlocal thermodynamic equilibrium models appropriate to each star are determined from the Stromgren index and fits to H-alpha line profiles. These parameters yield generally good fits to the observed He I line profiles, with the best fits being found for the blue He I lines where departures from local thermodynamic equilibrium are relatively small. For the two red lines it is found that, in the early B stars and in stars with log g less than 3.5, both lines are systematically stronger than predicted by the nonlocal thermodynamic equilibrium models.

Heasley, J. N.↗