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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Geochemistry of Pallasite Olivines and the Origin of Main-Group Pallasites

Main-group pallasites (PMG) are mixtures of iron-nickel metal and magnesian olivine thought to have been formed at the core-mantle boundary of an asteroid [1]. Some have anomalous metal compositions (PMG-am) and a few have atypically ferroan olivines (PMG-as) [2]. PMG metal is consistent with an origin as a late fractionate of the IIIAB iron core [2]. Most PMG olivines have very similar Fe/Mg ratios, likely due to subsolidus redox reaction with the metal [3]. In contrast, minor and trace elements show substantial variation, which may be explained by either: (i) PMG were formed at a range of depths in the parent asteroid; the element variations reflect variations in igneous evolution with depth, (ii) the pallasite parent asteroid was chemically heterogeneous; the heterogeneity partially survived igneous processing, or (iii) PMG represent the core-mantle boundaries of several distinct parent asteroids [4, 5]. We have continued doing major, minor and trace elements by EMPA and INAA on a wider suite of PMG olivines, and have begun doing precise oxygen isotope analyses to test these hypotheses. Manganese is homologous with Fe(2+), and can be used to distinguish between magmatic and redox processes as causes for Fe/Mg variations. PMG olivines have a range in molar 1000*Mn/Mg of 2.3-4.6 indicating substantial igneous fractionation in olivines with very similar Fe/Mg (0.138-0.148). The Mg-Mn-Fe distributions can be explained by a fractional crystallization-reduction model; higher Mn/Mg ratios reflect more evolved olivines while Fe/Mg is buffered by redox reactions with the metal. There is a positive association between Mn/Mg and Sc content that is consistent with igneous fractionation. However, most PMG olivines fall within a narrow Mn/Mg range (3.0-3.6), but these show a substantial range in Sc (1.00-2.29 micro-g/g). Assuming fractional crystallization, this Sc range could have resulted from approx.65% crystallization of an ultramafic magma. This is inconsistent with formation at the core-mantle boundary of a single asteroid [4]. One alternative is that the PMG are fragments of several asteroids, and these could have had different initial Sc contents, Mn/Mg and differences in igneous history. Our preliminary O isotope data and those of [6, 7] do not support this, although the coverage of PMG olivines is incomplete. The PMG-as Springwater is not easily fit in any scenario. Its olivine has among the highest Mn/Mg suggesting it is one of the most evolved, but the lowest Sc content suggesting it is the least evolved. The O isotopic composition of Springwater olivine is the same as that of other PMG. Thus there is no indication that it represents a distinct parent asteroid. Our preliminary O isotopic data favor a single PMG parent asteroid. In this case, the olivines are more likely melt-residues, and that the parent asteroid was initially heterogeneous in chemical, but not isotopic, composition.

Mittlefehldt, D. W.↗
NASA NTRS2007

Adaptive Modeling of the International Space Station Electrical Power System

Software simulations provide NASA engineers the ability to experiment with spacecraft systems in a computer-imitated environment. Engineers currently develop software models that encapsulate spacecraft system behavior. These models can be inaccurate due to invalid assumptions, erroneous operation, or system evolution. Increasing accuracy requires manual calibration and domain-specific knowledge. This thesis presents a method for automatically learning system models without any assumptions regarding system behavior. Data stream mining techniques are applied to learn models for critical portions of the International Space Station (ISS) Electrical Power System (EPS). We also explore a knowledge fusion approach that uses traditional engineered EPS models to supplement the learned models. We observed that these engineered EPS models provide useful background knowledge to reduce predictive error spikes when confronted with making predictions in situations that are quite different from the training scenarios used when learning the model. Evaluations using ISS sensor data and existing EPS models demonstrate the success of the adaptive approach. Our experimental results show that adaptive modeling provides reductions in model error anywhere from 80% to 96% over these existing models. Final discussions include impending use of adaptive modeling technology for ISS mission operations and the need for adaptive modeling in future NASA lunar and Martian exploration.

Thomas, Justin Ray↗
NASA NTRS2020

Application of Quasi-Static Modal Analysis to an Orion Multi-Purpose Crew Vehicle Test

Bolted structural joints often exhibit load-dependent stiffness and energy dissipation that leads to nonlinear, amplitude dependent frequency and damping in the structure. As an alternative to direct integration of the nonlinear equations of motion, quasi-static modal analysis (QSMA) determines the dependence of frequency and damping on response amplitude using loading behavior from nonlinear static analyses. QSMA has previously been demonstrated to substantially reduce computational cost and maintain accuracy relative to full nonlinear dynamic simulation. This work explores the applicability of QSMA to a complex, large-scale aerospace structure. QSMA is employed to analyze a nonlinear model of test hardware developed to support the Orion Multi-Purpose Crew Vehicle program, which exhibited nonlinear behavior during dynamic testing at flight-like load levels. In addition to the extraction of amplitude-dependent frequency and damping curves, a Bouc-Wen hysteresis model was used in conjunction with the quasi-static results to develop nonlinear, uncoupled, time-domain modal equations of motion for the structure. Excellent agreement was observed between the reduced and full-order nonlinear models, encouraging future employment of QSMA to support accurate and efficient model reduction of structures with bolted joint nonlinearities.

QSMA↗
NASA NTRSDate not supplied

Emissions Characterization and Smoke Transport of A Prescribed Fire

Under the background of climate change, vast regions of the world will face a hotter and probably drier future that favors ignition and spread of wildfires. This poses additional challenges to the communities who are fighting the ever-larger wildfires. Fire and smoke models are valuable tools to fire managers and decision-makers to mitigate the impact of fires. Existing fire modeling systems bear large uncertainties due to the difficulty in collecting data to characterize fire behavior and smoke transport. More observations are urgently needed for improvement of fire modeling and reduction in model uncertainty. The coordinated prescribed burn experiment, such as the Fire and Smoke Model and Measurement Evaluation Experiment (FSMMEE), will allow the concurrent collection of critical measurements of fuel, fire behavior, smoke, and meteorology to better understand and model fires. In this preliminary investigation, we employed the data from the prescribed burn experiment at Langdon Mountain, Utah, in November 2019, to reconstruct the fire emissions and characterize the smoke transport. The NASA Unified Weather Research and Forecasting Model (NU-WRF) was utilized to assist in identifying the potential pre-fire remote sensing capabilities, such as fuel load, moisture, and fire radiative power, which are helpful to model development and advancement. Along the way, two sets of NU-WRF experiments would be done by applying either a default fire emissions inventory (i.e., NASA’s Quick Fire Emissions Dataset, QFED) or reconstructed fire emissions using the data collected from the prescribed fire. The results would help answer the questions such as “How do reconstructed emissions compare to QFED emissions and their impact on plume transport”.

NU-WRF↗
NASA NTRS2010

The Role of Hierarchy in Response Surface Modeling of Wind Tunnel Data

This paper is intended as a tutorial introduction to certain aspects of response surface modeling, for the experimentalist who has started to explore these methods as a means of improving productivity and quality in wind tunnel testing and other aerospace applications. A brief review of the productivity advantages of response surface modeling in aerospace research is followed by a description of the advantages of a common coding scheme that scales and centers independent variables. The benefits of model term reduction are reviewed. A constraint on model term reduction with coded factors is described in some detail, which requires such models to be well-formulated, or hierarchical. Examples illustrate the consequences of ignoring this constraint. The implication for automated regression model reduction procedures is discussed, and some opinions formed from the author s experience are offered on coding, model reduction, and hierarchy.

DeLoach, Richard↗
NASA NTRS2009

Development and Validation of a Model for Hydrogen Reduction of JSC-1A

Hydrogen reduction of lunar regolith has been proposed as a viable technology for oxygen production on the moon. Hydrogen reduces FeO present in the lunar regolith to form metallic iron and water. The water may be electrolyzed to recycle the hydrogen and produce oxygen. Depending upon the regolith composition, FeO may be bound to TiO2 as ilmenite or it may be dispersed in glassy substrates. Some testing of hydrogen reduction has been conducted with Apollo-returned lunar regolith samples. However, due to the restricted amount of lunar material available for testing, detailed understanding and modeling of the reduction process in regolith have not yet been developed. As a step in this direction, hydrogen reduction studies have been carried out in more detail with lunar regolith simulants such as JSC-1A by NASA and other organizations. While JSC-1A has some similarities with lunar regolith, it does not duplicate the wide variety of regolith types on the moon, for example, it contains almost no ilmenite. Nonetheless, it is a good starting point for developing an understanding of the hydrogen reduction process with regolith-like material. In this paper, a model utilizing a shrinking core formulation coupled with the reactor flow is described and validated against experimental data on hydrogen reduction of JSC-1A.

Hegde, U.↗
NASA NTRS1978

Procedures for generation and reduction of linear models of a turbofan engine

A real time hybrid simulation of the Pratt & Whitney F100-PW-F100 turbofan engine was used for linear-model generation. The linear models were used to analyze the effect of disturbances about an operating point on the dynamic performance of the engine. A procedure that disturbs, samples, and records the state and control variables was developed. For large systems, such as the F100 engine, the state vector is large and may contain high-frequency information not required for control. This, reducing the full-state to a reduced-order model may be a practicable approach to simplifying the control design. A reduction technique was developed to generate reduced-order models. Selected linear and nonlinear output responses to exhaust-nozzle area and main-burner fuel flow disturbances are presented for comparison.

Seldner, K.↗
DOE OSTI2024

Data-Efficient Dimensionality Reduction and Surrogate Modeling of High-Dimensional Stress Fields

Tensor datatypes representing field variables like stress, displacement, velocity, etc., have increasingly become a common occurrence in data-driven modeling and analysis of simulations. Numerous methods [such as convolutional neural networks (CNNs)] exist to address the meta-modeling of field data from simulations. As the complexity of the simulation increases, so does the cost of acquisition, leading to limited data scenarios. Modeling of tensor datatypes under limited data scenarios remains a hindrance for engineering applications. Here, in this article, we introduce a direct image-to-image modeling framework of convolutional autoencoders enhanced by information bottleneck loss function to tackle the tensor data types with limited data. The information bottleneck method penalizes the nuisance information in the latent space while maximizing relevant information making it robust for limited data scenarios. The entire neural network framework is further combined with robust hyperparameter optimization. We perform numerical studies to compare the predictive performance of the proposed method with a dimensionality reduction-based surrogate modeling framework on a representative linear elastic ellipsoidal void problem with uniaxial loading. The data structure focuses on the low-data regime (fewer than 100 data points) and includes the parameterized geometry of the ellipsoidal void as the input and the predicted stress field as the output. The results of the numerical studies show that the information bottleneck approach yields improved overall accuracy and more precise prediction of the extremes of the stress field. Additionally, an in-depth analysis is carried out to elucidate the information compression behavior of the proposed framework.

artificial intelligence↗
NASA NTRS1989

Stochastic model of the NASA/MSFC ground facility for large space structures with uncertain parameters: The maximum entropy approach, part 2

A validated technology data base is being developed in the areas of control/structures interaction, deployment dynamics, and system performance for Large Space Structures (LSS). A Ground Facility (GF), in which the dynamics and control systems being considered for LSS applications can be verified, was designed and built. One of the important aspects of the GF is to verify the analytical model for the control system design. The procedure is to describe the control system mathematically as well as possible, then to perform tests on the control system, and finally to factor those results into the mathematical model. The reduction of the order of a higher order control plant was addressed. The computer program was improved for the maximum entropy principle adopted in Hyland's MEOP method. The program was tested against the testing problem. It resulted in a very close match. Two methods of model reduction were examined: Wilson's model reduction method and Hyland's optimal projection (OP) method. Design of a computer program for Hyland's OP method was attempted. Due to the difficulty encountered at the stage where a special matrix factorization technique is needed in order to obtain the required projection matrix, the program was successful up to the finding of the Linear Quadratic Gaussian solution but not beyond. Numerical results along with computer programs which employed ORACLS are presented.

Hsia, Wei Shen↗
NASA NTRS1991

Reduction of chemical reaction models

An attempt is made to reconcile the different terminologies pertaining to reduction of chemical reaction models. The approaches considered include global modeling, response modeling, detailed reduction, chemical lumping, and statistical lumping. The advantages and drawbacks of each of these methods are pointed out.

Frenklach, Michael↗
NASA NTRS1975

Hypersonic research engine project. Phase 2: Aerothermodynamic Integration Model (AIM) data reduction computer program, data item no. 54.16

The data reduction program used to analyze the performance of the Aerothermodynamic Integration Model is described. Routines to acquire, calibrate, and interpolate the test data, to calculate the axial components of the pressure area integrals and the skin function coefficients, and to report the raw data in engineering units are included along with routines to calculate flow conditions in the wind tunnel, inlet, combustor, and nozzle, and the overall engine performance. Various subroutines were modified and used to obtain species concentrations and transport properties in chemical equilibrium at each of the internal and external engine stations. It is recommended that future test plans include the configuration, calibration, and channel assignment data on a magnetic tape generated at the test site immediately before or after a test, and that the data reduction program be designed to operate in a batch environment.

Gaede, A. E.↗
DOE OSTI2024

S-OPT: A Points Selection Algorithm for Hyper-Reduction in Reduced Order Models

While projection-based reduced order models can reduce the dimension of full order solutions, the resulting reduced models may still contain terms that scale with the full order dimension. Hyper-reduction techniques are sampling-based methods that further reduce this computational complexity by approximating such terms with a much smaller dimension. The goal of this work is to introduce the points selection algorithm developed by Shin and Xiu as a hyper-reduction method. The selection algorithm was originally proposed as a stochastic collocation method for uncertainty quantification. Since the algorithm aims at maximizing a quantity $\mathcal{S}$ that measures both the column orthogonality and the determinant, we refer to the algorithm as S-OPT. Numerical examples are provided to demonstrate the performance of S-OPT and to compare its performance with a gappy proper orthogonal decomposition (POD) algorithm. Here, we found that using the S-OPT algorithm is shown to predict the full order solutions with higher accuracy than gappy POD especially when the number of sampling points is small, although we note that S-OPT shows slow asymptotic convergence with respect to the number of samples for some applications, e.g., Lagrangian hydrodynamics.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2006

Reducing Centroid Error Through Model-Based Noise Reduction

A method of processing the digitized output of a charge-coupled device (CCD) image detector has been devised to enable reduction of the error in computed centroid of the image of a point source of light. The method involves model-based estimation of, and correction for, the contributions of bias and noise to the image data. The method could be used to advantage in any of a variety of applications in which there are requirements for measuring precise locations of, and/or precisely aiming optical instruments toward, point light sources. In the present method, prior to normal operations of the CCD, one measures the point-spread function (PSF) of the telescope or other optical system used to project images on the CCD. The PSF is used to construct a database of spot models representing the nominal CCD pixel outputs for a point light source projected onto the CCD at various positions incremented by small fractions of a pixel.

Lee, Shinhak↗
DOE OSTI2025

Godiva IV Thermal Neutron Dosimetry Modeling and Variance Reduction

The transfer of the Godiva IV experiment from the Los Alamos Critical Experiments Facility (LACEF) to the National Critical Experiments Research Center (NCERC) introduced a vastly different experiment room return to the neutron flux. The contribution of the background to the burst neutron energy spectrum is significant in the thermal and epithermal neutron energies. Target materials may be placed in various locations in the Godiva room, or outside of the room, for thermal neutron activation. Modeling of this dosimetry problem in Monte Carlo N-Particle (MCNP) presented a novel challenge compared to previous Godiva IV glory hole irradiation simulations. An advanced dosimetry modeling framework for high efficiency calculations in locations far from the Godiva IV fission source was desired. The mesh-based weight windows and point detector advanced variance reduction techniques in MCNP were implemented and tested using adaptations of the critical experiment benchmark model of the Godiva IV problem. The models were validated against measured activations of Nickel, Indium, Scandium, and Cobalt foils at locations 2 meters from the Godiva IV core. Dosimetry measurements were performed in collaboration with Sandia National Laboratory. The weight windows and point detector variance reduction coupled method resulted in the highest problem efficiency.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Kinetic Model of HoxEFU reduction by NADH [SWR-26-087]

This repository is used to release code generated for manuscripts on the Photosynthetic Energy Transduction core program. This code simulates the reduction of HoxEFU by NADH. The electro transfer rate constants for the simulation are specified in the .csv files. The two .csv files correspond tot he two models described in Dawson et al. Cell. Rep. Phys. Sci. 2026. The code utilizes a chemical master equation, a set of differential equations, defining the time evolution of the oxidation and reduction kinetics of NAD+, NADH, a FMN flavin, and a set of iron sulfur clusters. The kinetics of HoxEFU reduction by NADH are evaluated by numerical integration of the chemical master equation using a variable-time-step Runge-Kutta algorithm.

Dahl, Peter [National Laboratory of the Rockies (N↗
NASA NTRS1995

An a priori model for the reduction of nutation observations: KSV(1994.3) nutation series

We discuss the formulation of a new nutation series to be used in the reduction of modern space geodetic data. The motivation for developing such a series is to develop a nutation series that has smaller short period errors than the IAU 1980 nutation series and to provide a series that can be used with techniques such as the Global Positioning System (GPS) that have sensitivity to nutations but can directly separate the effects of nutations from errors in the dynamical force models that effect the satellite orbits. A modern nutation series should allow the errors in the force models for GPS to be better understood. The series is constructed by convolving the Kinoshita and Souchay rigid Earth nutation series with an Earth response function whose parameters are partly based on geophysical models of the Earth and partly estimated from a long series (1979-1993) of very long baseline interferometry (VLBI) estimates of nutation angles. Secular rates of change of the nutation angles to represent corrections to the precession constant and a secular change of the obliquity of the ecliptic are included in the theory. Time dependent amplitudes of the Free Core Nutation (FCN) that is most likely excited by variations in atmospheric pressure are included when the geophysical parameters are estimated. The complex components of the prograde annual nutation are estimated simultaneously with the geophysical parameters because of the large contribution to the nutation from the S(sub 1) atmospheric tide. The weighted root mean square (WRMS) scatter of the nutation angle estimates about this new model are 0.32 mas and the largest correction to the series when the amplitudes of the ten largest nutations are estimated is 0.18 +/- 0.03 mas for the in phase component of the prograde 18. 6 year nutation.

Herring, T. A.↗
NASA NTRS1983

Alternatives for jet engine control

Tensor model order reduction, recursive tensor model identification, input design for tensor model identification, software development for nonlinear feedback control laws based upon tensors, and development of the CATNAP software package for tensor modeling, identification and simulation were studied. The last of these are discussed.

Sain, M. K.↗
NASA NTRS1992

Enhanced Method Of Reduction Of Dynamical Models

Enhanced projection-and-assembly method is recent product of efforts to model mathematically dynamics of vibrations of large, flexible structures. In projection-and-assembly method modes contributing significantly to control input and output points selected at system (overall structure) level, then projected (in abstract mathematical sense) onto components of system. In enhanced version, static correction modes capture static contributions of those modes neglected in reduced-order model. Reduced models for suppressing vibrations of structures made more accurate.

Lee, Allan Y.↗