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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

Real-time data reduction capabilities at the Langley 7 by 10 foot high speed tunnel

The 7 by 10 foot high speed tunnel performs a wide range of tests employing a variety of model installation methods. To support the reduction of static data from this facility, a generalized wind tunnel data reduction program had been developed for use on the Langley central computer complex. The capabilities of a version of this generalized program adapted for real time use on a dedicated on-site computer are discussed. The input specifications, instructions for the console operator, and full descriptions of the algorithms are included.

Fox, C. H., Jr.↗
DOE OSTI2024

Physics-Informed Learning Machines for Multiscale and Multiphysics Problems (PHILMS) (Technical Report)

The research work at University of California Santa Barbara (UCSB) resulted in several new developments in the areas of scientific machine learning, numerical analysis, and practical methods for data-driven modeling, prediction, reductions, and simulation. Many of the projects were carried out in collaboration with members of the national laboratories at Sandia National Laboratories (SNL), Pacific Northwestern National Laboratories (PNNL), and other institutions. Results included developing new scientific machine learning methods, related theory and mathematical frameworks for analysis and training, data-driven numerical solvers, and related tools and software for scientific computation. During the support period, over 16+ papers were submitted for publication, and 4 open-source software packages were developed and released (available at http://atzberger.org/). In addition, 7+ students and 2 post-docs were mentored in collaboration with the laboratory staff for future careers in academia, government labs, and industry.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1992

The FAST Hipparcos data reduction consortium - Overview of the reduction software

The main features of the data analysis methods adopted by FAST in the calibration and processing of the Hipparcos data are discussed. The structure of the data reduction software is examined, and the actual processing and evaluation are presented. Attention is given to the first look task, the calibration task, data preparation, attitude determination, the great circle reduction, synthesis treatment, iterations, data management and command software, and follow-up and evaluation activities.

Kovalevsky, J.↗
NASA NTRS2024

The CapiSorb Visible System (CVS) Demonstrations on ISS

Falling liquid film amine sorbent reactors have been successfully employed to scrub CO 2 aboard submarines for decades. However, applying such proven methods aboard orbiting and coast spacecraft is significantly challenged by the nearly weightless environment, where liquid sprays and films do not fall, and vapor bubbles and gases do not rise. The Capillary Sorbent (CapiSorb) Visible System (CVS) is a technology demonstration experiment performed aboard the ISS April 18 – 21, 2023. The system establishes stable steady thin liquid film flows in Contactor (absorber) and Degasser (desorber/stripper) replacing the passive role of gravity with the combined passive roles of surface tension, wetting, and system geometry. A TOX-0 fructose ersatz liquid sorbent is employed enabling ‘transparent’ experiments performed and filmed by the crew safely in the open cabin of the ISS. Completed objectives include demonstrations of stable passive ‘massively’ parallel planar thin film capillary flows across atmospheric pressure Contactor and sealed heated Degasser. The impacts of varying flow rate, flow direction, heat input, viscosity, positive and negative Degasser pressures, condensate collection and return, fluid distribution, interfacial stability, and others are reported. At least 49 diagnostics are recorded for digitization and subsequent thermal-fluids model validation by a single HD video downlink during the nearly 22 hours of operations. An overview of the flight hardware including description of the components, diagnostics, crew procedures, flight operations, and summary of accomplishments is reported in Ref. 1. Further details of the diagnostics, tests performed, and data reduction is reported in Ref. 2. This report collects both1,2 into a single report adding methods of data digitization, reduction, and archive along with analyses and discussions of technology impacts.

microgravity↗
NASA NTRS1994

A new algorithm for five-hole probe calibration, data reduction, and uncertainty analysis

A new algorithm for five-hole probe calibration and data reduction using a non-nulling method is developed. The significant features of the algorithm are: (1) two components of the unit vector in the flow direction replace pitch and yaw angles as flow direction variables; and (2) symmetry rules are developed that greatly simplify Taylor's series representations of the calibration data. In data reduction, four pressure coefficients allow total pressure, static pressure, and flow direction to be calculated directly. The new algorithm's simplicity permits an analytical treatment of the propagation of uncertainty in five-hole probe measurement. The objectives of the uncertainty analysis are to quantify uncertainty of five-hole results (e.g., total pressure, static pressure, and flow direction) and determine the dependence of the result uncertainty on the uncertainty of all underlying experimental and calibration measurands. This study outlines a general procedure that other researchers may use to determine five-hole probe result uncertainty and provides guidance to improve measurement technique. The new algorithm is applied to calibrate and reduce data from a rake of five-hole probes. Here, ten individual probes are mounted on a single probe shaft and used simultaneously. Use of this probe is made practical by the simplicity afforded by this algorithm.

Reichert, Bruce A.↗
DOE OSTI2024

Solving differential‐algebraic equations in power system dynamic analysis with quantum computing

Abstract Power system dynamics are generally modeled by high dimensional non‐linear differential‐algebraic equations (DAEs) given a large number of components forming the network. These DAEs' complexity can grow exponentially due to the increasing penetration of distributed energy resources, whereas their computation time becomes sensitive due to the increasing interconnection of the power grid with other energy systems. This paper demonstrates the use of quantum computing algorithms to solve DAEs for power system dynamic analysis. We leverage a symbolic programming framework to equivalently convert the power system's DAEs into ordinary differential equations (ODEs) using index reduction methods and then encode their data into qubits using amplitude encoding. The system non‐linearity is captured by Hamiltonian simulation with truncated Taylor expansion so that state variables can be updated by a quantum linear equation solver. Our results show that quantum computing can solve the power system's DAEs accurately with a computational complexity polynomial in the logarithm of the system dimension. We also illustrate the use of recent advanced tools in scientific machine learning for implementing complex computing concepts, that is, Taylor expansion, DAEs/ODEs transformation, and quantum computing solver with abstract representation for power engineering applications.

computational complexity↗
DOE OSTI2024

Exploration with Scalable Gaussian Process Reinforcement Learning

Exploration is a challenging problem in reinforcement learning (RL), especially in environments with sparse rewards. Quantifying and utilizing the parametric uncertainty has been shown to be paramount for successful exploration [Osband et al., 2018]. Bayesian, or approximately Bayesian, methods present a principled means of estimating the parametric uncertainty in RL problems. Gaussian processes, nonparametric Bayesian models, are often impractical due to poor scalability and computational bottlenecks. We introduce a scalable Gaussian process RL (GPRL) method which directly induces sparsity in the covariance matrix to facilitate faster computation. This is a departure from previous GPRL methods which instead rely on data reduction and subsampling. We compare various covariance-based exploration techniques (Thompson sampling, upper confidence bound, and probabilistic maximum variance) which leverage our scalable GP framework in sparse reward environments. Finally, we show favorable comparison against the bootstrapped deep Q-Network.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1969

Mass spectograph analysis

Computer program provides a means of rapid data reduction of mass spectrograph data. The methods used are suited to mechanization on a digital computer since they consist of the systematic search of a large amount of tabular data and the unknown.

Shores, J. P.↗
NASA NTRS1972

Boundary cooled rocket engines for space storable propellants

An evaluation of an existing analytical heat transfer model was made to develop the technology of boundary film/conduction cooled rocket thrust chambers to the space storable propellant combination oxygen difluoride/diborane. Critical design parameters were identified and their importance determined. Test reduction methods were developed to enable data obtained from short duration hot firings with a thin walled (calorimeter) chamber to be used quantitatively evaluate the heat absorbing capability of the vapor film. The modification of the existing like-doublet injector was based on the results obtained from the calorimeter firings.

Kesselring, R. C.↗
NASA NTRS1975

Pressure Contact Sounding Data for NASA's Atmospheric Variability Experiment (AVE 3)

The basic rawinsonde data are described at each pressure contact from the surface to sounding termination for the 41 stations participating in the AVE III measurement program that began at 0000 GMT on February 6 and ended at 1200 GMT on February 7, 1975. Soundings were taken at 3-hour intervals during a large period of the experiment from most stations within the United States east of about 105 degrees west longitude. Methods of data processing, change in reduction scheme since the AVE II pilot experiment, and data accuracy are briefly discussed. An example of contact data is presented, and microfiche cards of all the contact data are included in the appendix. The AVE III project was conducted to better understand and establish the extent of applications for meteorological satellite sensor data through correlative ground truth experiments and to provide basic experimental data for use in studies of atmospheric scales of-motion interrelationships.

Fuelberg, H. E.↗
NASA NTRS1977

An improved lunar moment of inertia determination - A proposed strategy

A strategy for determining an improved lunar moment of inertia is proposed. An improved uncertainty in the lunar inhomogeneity parameter could reduce the core density error from 4.20 gr/cu cm to 0.1 gm/cu cm for the case of a lunar density model having a 300 km core radius. The current error of 0.0025 for the lunar inhomogeneity parameter is mostly due to the uncertainties in the C20 and C22 gravity harmonics. An optimum reduction strategy for obtaining an order of magnitude improvement in the gravity estimates is based on covariance analyses of Doppler data. The long-arc reduction method is shown to provide better results than the short-arc technique, and the use of an orbit with a 7000 km semimajor axis along with certain terms of up to degree and order eight is recommended.

Ananda, M. P.↗
NASA NTRS1978

Comparison of ozone concentrations obtained from Skylab eclipse and ozonesonde measurements

The satellite eclipse technique of ozone measurement is evaluated to determine its accuracy and resolution. The method of obtaining ozone concentrations from ground-based observations of eclipsing satellites is described, the theory of this method is outlined, and the data reduction procedure is summarized. It is shown that the satellite eclipse technique successfully measures the vertical distribution of ozone from 15 to 40 km with precisions ranging from + or - 12% between 20 and 35 km and + or - 25% at both 15 and 40 km. The ozone profile is found to be in good agreement with in situ measurements obtained from an ozonesonde launched near the eclipse tangent point at local sunset, the percent differences being less than 14% from 20 to 40 km.

Mcdougal, D. S.↗
NASA NTRS2014

Compositional Diversity of the Vestan Regolith Derived from Howardite Compositions and Dawn VIR Spectra

Howardite, eucrite and diogenite meteorites likely come from asteroid 4 Vesta [1]. Howardites - physical mixtures of eucrites and diogenites - are of two subtypes: regolithic howardites were gardened in the true regolith; fragmental howardites are simple polymict breccias [2]. The Dawn spacecraft imaged the howarditic surface of Vesta with the visible and infrared mapping spectrometer (VIR) resulting in qualitative maps of the distributions of distinct diogenite-rich and eucrite-rich terranes [3, 4]. We are developing a robust basis for quantitative mapping of the distribution of lithologic types using spectra acquired on splits of well-characterized howardites [5, 6]. Spectra were measured on sample powders sieved to <75 μm in the laboratories of the Istituto di Astrofisica e Planetologia Spaziali and Brown University. Data reduction was done using the methods developed to process Dawn VIR spectra [4]. The band parameters for the ~1 and ~2 μm pyroxene absorption features (hereafter BI and BII) can be directly compared to Dawn VIR results. Regolithic howardites have shallower BI and BII absorptions compared to fragmental howardites with similar compositions. However, there are statistically significant correlations between Al or Ca contents and BI or BII center wavelengths regardless of howardite subtype. Diogenites are poor in Al and Ca while eucrites are rich in these elements. The laboratory spectra can thus be directly correlated with the percentage of eucrite material contained in the howardites. We are using these correlations to quantitatively map Al and Ca distributions, and thus the percentage of eucritic material, in the current regolith of Vesta.

Mittlefehldt, D. W.↗
NASA NTRSDate not supplied

Microwave Interrogation of Woven Straps under Light Loading for Inflatable Applications

NASA uses woven straps for restraint layers in inflatable structures. This work investigates the use of microwaves to measure low level loading in the woven straps. More specifically, microwaves from a linearly polarized antenna are used to investigate four straps composed of Vectran and Kevlar with ratings of 6,000 lbs and 12,000 lbs of force. The straps are all lightly loaded from 2kg to 10kg in 2kg increments. The spectral centroid (SC) technique has been used for the dimensionality reduction method to evaluate the microwave data. The SC method was used to reduce the data from 10001 points to a single point that corresponds to the amount of load on the strap.

Microwave↗
DOE OSTI2024

Manifold Learning: What, How, and Why

Manifold learning (ML), also known as nonlinear dimension reduction, is a set of methods to find the low-dimensional structure of data. Dimension reduction for large, high-dimensional data is not merely a way to reduce the data; the new representations and descriptors obtained by ML reveal the geometric shape of high-dimensional point clouds and allow one to visualize, denoise, and interpret them. This review presents the underlying principles of ML, its representative methods, and their statistical foundations, all from a practicing statistician's perspective. It describes the trade-offs and what theory tells us about the parameter and algorithmic choices we make in order to obtain reliable conclusions.

Mathematics↗
NASA NTRS1982

Photogrammetric aspects of remapping procedures

Photogrammetric control generation is discussed. Techniques in remote sensing data reduction are described. Emphasis is placed on methods of rectification of aerial photography and frame photography. Examples of multispectral band scanner data that were processed are presented.

Mikhail, E. M.↗
DOE OSTI2024

Archetype-based Redshift Estimation for the Dark Energy Spectroscopic Instrument Survey

We present a computationally efficient galaxy archetype-based redshift estimation and spectral classification method for the Dark Energy Survey Instrument (DESI) survey. The DESI survey currently relies on a redshift fitter and spectral classifier using a linear combination of principal component analysis–derived templates, which is very efficient in processing large volumes of DESI spectra within a short time frame. However, this method occasionally yields unphysical model fits for galaxies and fails to adequately absorb calibration errors that may still be occasionally visible in the reduced spectra. Our proposed approach improves upon this existing method by refitting the spectra with carefully generated physical galaxy archetypes combined with additional terms designed to absorb data reduction defects and provide more physical models to the DESI spectra. We test our method on an extensive data set derived from the survey validation (SV) and Year 1 (Y1) data of DESI. Our findings indicate that the new method delivers marginally better redshift success for SV tiles while reducing catastrophic redshift failure by 10%–30%. At the same time, results from millions of targets from the main survey show that our model has relatively higher redshift success and purity rates (0.5%–0.8% higher) for galaxy targets while having similar success for QSOs. These improvements also demonstrate that the main DESI redshift pipeline is generally robust. Additionally, it reduces the false-positive redshift estimation by 5%–40% for sky fibers. We also discuss the generic nature of our method and how it can be extended to other large spectroscopic surveys, along with possible future improvements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗