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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Cryogenic Extension of NASA Species Polynomials Using Hydrogen and Oxygen at Stoichiometry

NASA has been conducting research in Rotating Detonation Rocket Engines (RDREs) for several years. A recent test at the Marshall Spaceflight Center has successfully shown operation of a RDRE that ran for 251 seconds which had combustion chamber cryogenic inlet conditions [1]. However, an overall pressure gain was not observed in the performance of the engine. Such an indication could mean an optimal chamber design is yet to be discovered. Such a design could significantly reduce parasitic pressure loses and improve overall engine efficiency beyond that of conventional rockets. To investigate different chamber configurations, new CFD capability is needed to accurately capture cryogenic thermophysical and transport property data. Such an effort is currently part of NASA’s Early Career Initiative (ECI) program. This paper focuses on the thermophysical property mixture model approach that makes use of NASA’s polynomial fits of species and another cryogenic model chosen from NIST’s Refprop program. Presented in this paper are results of a 1D denotation CFD simulation of stoichiometric Hydrogen and Oxygen mixture at a cryogenic upstream condition.

Combustion↗
NASA NTRSDate not supplied

Numerical Predictions of the Flow and Heat Transfer Characteristics in the Film Boiling Regime During Tube Quenching

Cryogenic fluid management plays a major role in refueling of spacecrafts while in space for NASA’s future human space exploration missions. Due to the low boiling points of cryogens, storage, transport and handling of these fluids becomes difficult and may result in inefficient operation of the space propulsion systems. For refueling applications in space, the cryogenic fluids have to be transported across different locations and hence, the transfer of cryogenic fluids through pipes become critical. The cryogenic chill-down process is characterized by different regimes of flow boiling, viz., film boiling, transition boiling and nucleate boiling. The prediction of these regimes in a single CFD framework available in the literature is challenging and the present work attempts to address this challenge by initially modeling the film boiling regime accurately and to incorporate an user-defined function for transition and nucleate boiling at a later stage. Hence, the aim of the present work is to numerically model and validate the film boiling regime of the chilldown curve for liquid nitrogen experiments available in the literature. The validations are carried out at different inlet mass fluxes to have a robust simulation methodology. A dispersed mixture model is used to predict the vapor-liquid interface dynamics with the phase change phenomena modeled using the Lee model.

line chilldown↗
NASA NTRS2007

Identification and Control of Aircrafts using Multiple Models and Adaptive Critics

We compared two possible implementations of local linear models for control: one approach is based on a self-organizing map (SOM) to cluster the dynamics followed by a set of linear models operating at each cluster. Therefore the gating function is hard (a single local model will represent the regional dynamics). This simplifies the controller design since there is a one to one mapping between controllers and local models. The second approach uses a soft gate using a probabilistic framework based on a Gaussian Mixture Model (also called a dynamic mixture of experts). In this approach several models may be active at a given time, we can expect a smaller number of models, but the controller design is more involved, with potentially better noise rejection characteristics. Our experiments showed that the SOM provides overall best performance in high SNRs, but the performance degrades faster than with the GMM for the same noise conditions. The SOM approach required about an order of magnitude more models than the GMM, so in terms of implementation cost, the GMM is preferable. The design of the SOM is straight forward, while the design of the GMM controllers, although still reasonable, is more involved and needs more care in the selection of the parameters. Either one of these locally linear approaches outperform global nonlinear controllers based on neural networks, such as the time delay neural network (TDNN). Therefore, in essence the local model approach warrants practical implementations. In order to call the attention of the control community for this design methodology we extended successfully the multiple model approach to PID controllers (still today the most widely used control scheme in the industry), and wrote a paper on this subject. The echo state network (ESN) is a recurrent neural network with the special characteristics that only the output parameters are trained. The recurrent connections are preset according to the problem domain and are fixed. In a nutshell, the states of the reservoir of recurrent processing elements implement a projection space, where the desired response is optimally projected. This architecture trades training efficiency by a large increase in the dimension of the recurrent layer. However, the power of the recurrent neural networks can be brought to bear on practical difficult problems. Our goal was to implement an adaptive critic architecture implementing Bellman s approach to optimal control. However, we could only characterize the ESN performance as a critic in value function evaluation, which is just one of the pieces of the overall adaptive critic controller. The results were very convincing, and the simplicity of the implementation was unparalleled.

Principe, Jose C.↗
NASA NTRS2014

Combined Uncertainty and A-Posteriori Error Bound Estimates for CFD Calculations: Theory and Implementation

Simulation codes often utilize finite-dimensional approximation resulting in numerical error. Some examples include, numerical methods utilizing grids and finite-dimensional basis functions, particle methods using a finite number of particles. These same simulation codes also often contain sources of uncertainty, for example, uncertain parameters and fields associated with the imposition of initial and boundary data,uncertain physical model parameters such as chemical reaction rates, mixture model parameters, material property parameters, etc.

CFD↗
NASA NTRS1982

Analysis of lithology: Vegetation mixes in multispectral images

Discrimination and identification of lithologies from multispectral images is discussed. Rock/soil identification can be facilitated by removing the component of the signal in the images that is contributed by the vegetation. Mixing models were developed to predict the spectra of combinations of pure end members, and those models were refined using laboratory measurements of real mixtures. Models in use include a simple linear (checkerboard) mix, granular mixing, semi-transparent coatings, and combinations of the above. The use of interactive computer techniques that allow quick comparison of the spectrum of a pixel stack (in a multiband set) with laboratory spectra is discussed.

Adams, J. B.↗
NASA NTRSDate not supplied

Overview of Predictive Simulation Capability Development for Crater Evolution and Ejecta in Continuum/Rarefied Flows

As part of the Game Changing Development (GCD) Program funded by NASA’s Space Technology Mission Directorate (STMD), the development of simulation capability for the prediction of extra-terrestrial plume surface interaction (PSI) environments has been undertaken by the Fluid Dynamics Branch at NASA/MSFC. The Predictive Simulation Capability (PSC) Element is focused on creating simulation capability for the reliable and accurate prediction of PSI in Martian (~650 Pa) and Lunar (vacuum) ambient environments. In this paper, an overview and brief status on one area of capability development through this GCD PSI project, capturing the effects of mixed continuum/rarefied flow on crater development and ejecta sheets, is presented with respect to capability enhancements, predictive tool maturation, and validation of the Loci/GGFS tool against PSI data in Martian and Lunar environments. Axisymmetric modeling, overset mesh/moving mesh, and multiple-species mixture modeling capabilities are verified against Loci/CHEM, and a demonstration of the capabilities is presented for the Apollo Lunar Module.

Andrew Weaver↗
NASA NTRS2012

Particle Filtering for Model-Based Anomaly Detection in Sensor Networks

A novel technique has been developed for anomaly detection of rocket engine test stand (RETS) data. The objective was to develop a system that postprocesses a csv file containing the sensor readings and activities (time-series) from a rocket engine test, and detects any anomalies that might have occurred during the test. The output consists of the names of the sensors that show anomalous behavior, and the start and end time of each anomaly. In order to reduce the involvement of domain experts significantly, several data-driven approaches have been proposed where models are automatically acquired from the data, thus bypassing the cost and effort of building system models. Many supervised learning methods can efficiently learn operational and fault models, given large amounts of both nominal and fault data. However, for domains such as RETS data, the amount of anomalous data that is actually available is relatively small, making most supervised learning methods rather ineffective, and in general met with limited success in anomaly detection. The fundamental problem with existing approaches is that they assume that the data are iid, i.e., independent and identically distributed, which is violated in typical RETS data. None of these techniques naturally exploit the temporal information inherent in time series data from the sensor networks. There are correlations among the sensor readings, not only at the same time, but also across time. However, these approaches have not explicitly identified and exploited such correlations. Given these limitations of model-free methods, there has been renewed interest in model-based methods, specifically graphical methods that explicitly reason temporally. The Gaussian Mixture Model (GMM) in a Linear Dynamic System approach assumes that the multi-dimensional test data is a mixture of multi-variate Gaussians, and fits a given number of Gaussian clusters with the help of the wellknown Expectation Maximization (EM) algorithm. The parameters thus learned are used for calculating the joint distribution of the observations. However, this GMM assumption is essentially an approximation and signals the potential viability of non-parametric density estimators. This is the key idea underlying the new approach.

Solano, Wanda↗
NASA NTRS1988

Important changes in microwave scattering properties of young snow-covered sea ice as indicated from dielectric modelling

Winter measurements of the properties of young snow-covered fast ice are input into a mixture model to calculate the complex dielectric constant. Large changes in the electromagnetic properties of the medium occur over the 46 day period of measurements. This early evolution of the surface is shown to have an important impact upon predicted radar backscattering properties at GHz frequencies. This has consequences for the unambiguous identification of young ice forms from synthetic aperture or side-looking airborne radar images.

Drinkwater, M. R.↗
NASA NTRS1990

Analysis of generic scramjet external nozzle flowfields employing simulant gases

Experimental and computational results are presented for a generic scramjet nozzle/afterbody model. Mixtures of argon and Freon were employed as simulant scramjet exhaust gases because they correctly model the inviscid simulation parameters of actual scramjet combustion products, allowing test and analysis at significantly reduced temperatures. Air was also employed as an exhaust gas to provide experimental and computational comparisons with simulant gas effects. Several computational aerodynamic analysis codes, employing different levels of theoretical modeling, were applied to compute solutions about the scramjet geometry. The solutions are compared with measured surface static and flowfield pitot pressure data taken in a Mach 6 freestream.

Tatum, Kenneth E.↗
NASA NTRS2005

Accurate Biomass Estimation via Bayesian Adaptive Sampling

The following concepts were introduced: a) Bayesian adaptive sampling for solving biomass estimation; b) Characterization of MISR Rahman model parameters conditioned upon MODIS landcover. c) Rigorous non-parametric Bayesian approach to analytic mixture model determination. d) Unique U.S. asset for science product validation and verification.

Wheeler, Kevin R.↗
NASA NTRS2010

Identifying Aerosol Type/Mixture from Aerosol Absorption Properties Using AERONET

Aerosols are generated in the atmosphere through anthropogenic and natural mechanisms. These sources have signatures in the aerosol optical and microphysical properties that can be used to identify the aerosol type/mixture. Spectral aerosol absorption information (absorption Angstrom exponent; AAE) used in conjunction with the particle size parameterization (extinction Angstrom exponent; EAE) can only identify the dominant absorbing aerosol type in the sample volume (e.g., black carbon vs. iron oxides in dust). This AAE/EAE relationship can be expanded to also identify non-absorbing aerosol types/mixtures by applying an absorption weighting. This new relationship provides improved aerosol type distinction when the magnitude of absorption is not equal (e.g, black carbon vs. sulfates). The Aerosol Robotic Network (AERONET) data provide spectral aerosol optical depth and single scattering albedo - key parameters used to determine EAE and AAE. The proposed aerosol type/mixture relationship is demonstrated using the long-term data archive acquired at AERONET sites within various source regions. The preliminary analysis has found that dust, sulfate, organic carbon, and black carbon aerosol types/mixtures can be determined from this AAE/EAE relationship when applying the absorption weighting for each available wavelength (Le., 440, 675, 870nm). Large, non-spherical dust particles absorb in the shorter wavelengths and the application of 440nm wavelength absorption weighting produced the best particle type definition. Sulfate particles scatter light efficiently and organic carbon particles are small near the source and aggregate over time to form larger less absorbing particles. Both sulfates and organic carbon showed generally better definition using the 870nm wavelength absorption weighting. Black carbon generation results from varying combustion rates from a number of sources including industrial processes and biomass burning. Cases with primarily black carbon showed improved definition in the 870nm wavelength absorption weighting due to the increased absorption in the near-infrared wavelengths, while the 440nm wavelength provided better definition when black carbon mixed with dust. Utilization of this particle type scheme provides necessary information for remote sensing applications, which needs a priori knowledge of aerosol type to model the retrieved properties especially over semi-bright surfaces. In fact, this analysis reveals that the aerosol types occurred in mixtures with varying magnitudes of absorption and requires the use of more than one assumed aerosol mixture model. Furthermore, this technique will provide the aerosol transport model community a data set for validating aerosol type.

Giles, D. M.↗
NASA NTRS1992

Reflectance spectroscopy and GEX simulation of palagonite and iron-rich montmorillonite clay mixtures: Implications for the surface composition of Mars

Because of the power of remote sensing reflectance spectroscopy in determining mineralogy, it has been used as the major method of identifying a possible mineral analogue of the martian surface. A summary of proposed martian surface compositions from reflectance spectroscopy before 1979 was presented by Singer et al. Since that time, iron-rich montmorillonite clay, nanocrystalline or nanophase hematite, and palagonite have been suggested as Mars soil analogue materials. Palagonite in petrological terms is best described as an amorphous, hydrated, ferric iron, silica gel. Montmorillonite is a member of the smectite clay group, and its structure is characterized by an octahedral sheet in coordination with two tetrahedral sheets in which oxygen atoms are shared. The crystal unity of montmorillonite is well defined in contrast to palagonite where it is considered amorphous or poorly crystalline at best. Because of the absence of the diagnostic strong 2.2-micron reflectance band characteristic of clays in the near-infrared (NIR) spectrum of Mars and palagonite and based upon a consideration of wide wavelength coverage (0.3-50 microns), Roush et al. concluded that palagonite is a more likely Mars surface analogue. In spite of the spectral agreement of palagonite and the Mars reflectance spectrum in the 2.2-micron region, palagonite shows poor correspondence with the results of the Viking LR experiment. In contrast, iron-rich montmorillonite clays show relatively good agreement with the results of the Viking LR experiment. This spectral study was undertaken to evaluate the spectral properties of mixtures of palagonite and Mars analogue iron-rich montmorillonite clay (16-18 wt. percent Fe as Fe2O3) as a Mars surface mineralogical model. Mixtures of minerals as Mars surface analogue materials have been studied before, but the mixtures were restricted to crystalline clays and iron oxides.

Orenberg, J. B.↗
NASA NTRS1967

A study of seeded rotating arcs.

Neutral carrier gas and slightly ionized plasma binary mixture model for nonhomogeneous seeding effects on rotating arc performance

ROTATING FLUID↗
NASA NTRS1991

Darkening in gas-rich ordinary chondrites: Spectral modelling and implications for the regoliths of ordinary chondrite parent bodies

The dark fine grained matrix of gas-rich ordinary chondrites replicates many of the physical, morphological, and spectral characteristics of the highly shocked and optically altered black chondrites. Spectral mixture modeling shows that the darkening and spectral attenuation seen in the dark matrix can be simulated with realistic mass fractions of light host material and black chondritic material. All these factors point to the conclusion that the dark matrix of gas-rich ordinary chondrites is dark due to the same processes that darkens black chondrites, shock distributed small particle size FeNi metal and troilite. Because the darkening is not seen in any of the non-gas-rich light portions and is only seen in the gas rich grains of the meteorite, the shock darkening would have to occur as part of the matrix's exposure to regolith processes. Since all gas-rich grains are darkened, it follows that darkening is not only common, but pervasive in asteroidal regoliths. These results imply that the upper, optically active layer of an ordinary chondrite parent body should have the spectral characteristics of a black chondrite, which are a dark, relatively featureless spectrum with modest red slope in the infrared. These are the characteristics of special type C asteroids.

Britt, Daniel T.↗
NASA NTRS1985

Crop area estimation based on remotely-sensed data with an accurate but costly subsample

Research activities conducted under the auspices of National Aeronautics and Space Administration Cooperative Agreement NCC 9-9 are discussed. During this contract period research efforts are concentrated in two primary areas. The first are is an investigation of the use of measurement error models as alternatives to least squares regression estimators of crop production or timber biomass. The secondary primary area of investigation is on the estimation of the mixing proportion of two-component mixture models. This report lists publications, technical reports, submitted manuscripts, and oral presentation generated by these research efforts. Possible areas of future research are mentioned.

Gunst, R. F.↗
NASA NTRS1993

Spectral mixing models of S-Type asteroids

This paper presents the results of an attempt to determine S-Type asteroid mineralogies with the use of Hapke theory spectral mixing modelling. Previous attempts to understand the spectral variations present in this single class of asteroids have concentrated on spectral parameters such as absorption band center wavelengths, band area ratios, and geometric albedos. The procedure taken here is to utilize the Hapke spectral reflectance model to calculate single scatter albedo as a function of wavelength for a suite of candidate end-member materials. These materials are then mixed linearly in single scatter albedo space, and the mixture is converted, assuming intimate particle mixing, back to reflectance for the spectrum matching routine. A total of 39 S-Type asteroids selected from the Bell et al. survey have been matched with mixture model spectra.

Clark, Beth E.↗
NASA NTRSDate not supplied

Numerical Analysis of Cavitation-Induced Two-Phase Fluid Transients in Cryogenic Feedlines Using Finite Volume Procedure

This article presents a numerical investigation of the cavitation induced fluid transient in cryogenic feedline due to sudden closure of the valve A one dimensional numerical model based on finite volume procedure consisting of nodes and branches using Generalized Fluid System Simulation Program ( has been employed for the prediction of pressure variations The unsteady friction formulation accurately determines wall shear stress, and a homogeneous mixture model is used for two phase flow modeling Numerical results obtained with the present formulation are compared with experimental results and Method of Characteristic ( based results It is observed that low residual in flow variable calculation improves the solution providing numerically stable results GFSSP is able to reproduce the fluid transient peak due to vapor collapse Subsequently, it can retain the shape of pressure wave for two phase fluid transients, but it is dampening faster compared to experiments Further investigation is required with set of experiments to validate the present numerical approach for different experimental data.

Fluid Transient↗