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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Interpretation of Dynamics Explorer far UV images of the quiet time thermosphere

A selected set of far ultra violet images of Earth have been analyzed quanitatively to establish their validity for studying thermospheric weather. The set of images chosen for the study was restricted to mostly geomagnetically quiet conditions in order to obtain a baseline understanding of the relationship between the observations and thermospheric phenomenology. The images included low to modrerate solar activity levels. A new model was developed to generate global dayglow images using first principles methods. The mass Spectrometer/incoherent scatter (MSIS-86) model was used to predict the thermospheric concentrations. The analyses of thermospheric images observed in the 123 to 160-nm nominal passband show that the spectral composition for observations on the projected earth disk is dominated by O I 130.4-nm radiation (85-90%), with concentrations from O I 135.6-nm and N2 Lyman-Birge-Hopefield (LBH) bands of about 5-8% each. The synthetic images reproduce the global features of the observed images rather well. Differences between the model and the data are attributed to real atmospheric effects, such as atomic oxygen depletions which are not well reproduced by the MSIS model when geomagnetic activity is elevated. The absoute values recorded were 38-54% higher than predicted. We attribute this discrepancy to low values of the solar extreme ultraviolet irradiances used in the model. Images obtained in the 136 to 165-nm nominal passband are a factor of 2.7 greater than the model. The excess signal observed is most likely due to a long wavelength tail in the instrument sensitivity which allowed Rayleigh scattered sunlight between 180and 250nm to be detected. The understanding of the Dynamics Explorer (DE 1) images gained by this study provides the basis for future work on the global response of the theremosphere to geomagnetic forcing.

Meier, R. R.↗
NASA NTRS2016

Pitfalls and Precautions When Using Predicted Failure Data for Quantitative Analysis of Safety Risk for Human Rated Launch Vehicles

Launch vehicle reliability analysis is largely dependent upon using predicted failure rates from data sources such as MIL-HDBK-217F. Reliability prediction methodologies based on component data do not take into account risks attributable to manufacturing, assembly, and process controls. These sources often dominate component level reliability or risk of failure probability. While consequences of failure is often understood in assessing risk, using predicted values in a risk model to estimate the probability of occurrence will likely underestimate the risk. Managers and decision makers often use the probability of occurrence in determining whether to accept the risk or require a design modification. Due to the absence of system level test and operational data inherent in aerospace applications, the actual risk threshold for acceptance may not be appropriately characterized for decision making purposes. This paper will establish a method and approach to identify the pitfalls and precautions of accepting risk based solely upon predicted failure data. This approach will provide a set of guidelines that may be useful to arrive at a more realistic quantification of risk prior to acceptance by a program.

Hatfield, Glen S.↗
NASA NTRSDate not supplied

HLPW-4/GMGW-3: Overview and Workshop Summary

The Fourth AIAA CFD High Lift Prediction Workshop and the Third Geometry and Mesh Generation Workshop were held collaboratively with the common goal of assessing the numerical prediction capability of current-generation computational fluid dynamics (CFD) technology for swept, medium/high-aspect-ratio wings in high-lift configurations. A key aspect of this joint endeavor was the use of Technology Focus Groups, an innovative new approach for workshops involving close collaboration between participants. These groups, which included both mesh generation and flow solver experts, worked to accelerate advancements for their particular methodologies by addressing key questions of importance {\em prior} to the workshop. The high-lift version of the NASA Common Research Model (CRM-HL) configuration was the focus of this workshop. Measured experimental wind tunnel data were available for comparison. The workshop also included a two-dimensional turbulence model verification exercise based on the CRM-HL wing shape. Altogether, 44 participants submitted a total of 184 data sets of CFD results. This paper provides a high-level summary of the results and conclusions from the workshop. Like at past workshops, fixed-grid Reynolds-averaged Navier-Stokes continued to be inaccurate and inconsistent for high lift. However, mesh adaptation definitively brought more consistency. Scale-resolving methods appeared most promising for predicting high-lift flow physics.

Christopher L Rumsey↗
DOE OSTI2020

Analysis of the Impurity MgOHCl in Molten Chloride Salts Toward its Electrochemical Removal from CSP Plants During Operation

The work presented here is a study of the impurity MgOHCl in molten chloride salts, toward the eventual goal of electrochemically removing it from operational molten-chloride-based concentrating solar power (CSP) plants.1,2 Implementation of molten chloride salts as a heat transfer fluid is among the most promising pathways for decreasing the levelized cost of energy (LCOE) of CSP systems because its high thermal stability allows higher operating temperatures, and thus, greater efficiency. However, this impurity - formed when MgCl2 salts are exposed to air and moisture - cause significant corrosion of containment alloys.1 Therefore, we have developed and validated in a laboratory setting: 1) a method for the formation of MgOHCl for controlled impurity spike in molten salt for its further sensing, evaluation, and reduction; 2) evaluated its diffusion in the molten salt, and 3) began assessing its electrochemical properties. Our findings allow us to propose solutions for efficiently and instantly removing MgOHCl from an operational CSP plant.

concentrated solar power↗
DOE OSTI2023

Accurate Prediction of Algal Biomass Lipid, Protein, and Carbohydrate Composition with Machine Learning Regression Modelling of Near-IR Spectra

During large scale algal biomass cultivation, it is difficult to reliably control relative composition to target levels. Rapid determination of chemical composition is feasible by using near infrared (NIR) spectral data. We sought to build and improve on reliable high-throughput screening prediction method based on partial least squares regression (PLSR) by the application of artificial neural networks (ANN) and associated optimization strategies. The algal biomass sample set was designed and created in an iterative process of culturing in physiologically diverse conditions at the GAI field site, followed by compositional analyses at NREL. The workflow allowed us to identify gaps in compositional space for informing the subsequent cultivation and sampling efforts and generated a high quality set of 210 unique samples with chemical analysis results, spectral scanning data, and cultivation metadata. We observed a significant improvement in the performance of carbohydrate content predictions using an optimized ANN model compared to PLSR, with > 16% reduction in mean absolute percent error (MAPE) when tested on the same set of reserved data. The optimized ANN models for FAME and protein prediction performed exceptionally well with 5.99% and 5.09% MAPE, respectively. Application of these methods to detection and quantification of minor biomass constituents that are relevant to certain product streams has shown positive preliminary results, opening the possibility for extensions to the outputs of this powerful data type. All models are accompanied by prediction uncertainties and unsupervised spectral outlier detection to alert an operator to unreliable spectral data. These tools can be deployed for rapid determination of algal culture status, and cultivation and biomass quality improvement.

algal biofuels↗
NASA NTRS1976

Series-parallel method of direct solar array regulation

A 40 watt experimental solar array was directly regulated by shorting out appropriate combinations of series and parallel segments of a solar array. Regulation switches were employed to control the array at various set-point voltages between 25 and 40 volts. Regulation to within + or - 0.5 volt was obtained over a range of solar array temperatures and illumination levels as an active load was varied from open circuit to maximum available power. A fourfold reduction in regulation switch power dissipation was achieved with series-parallel regulation as compared to the usual series-only switching for direct solar array regulation.

Gooder, S. T.↗
NASA NTRS2013

Development and Implementation of Efficiency-Improving Analysis Methods for the SAGE III on ISS Thermal Model Originating

The Stratospheric Aerosol and Gas Experiment III (SAGE III) instrument is the fifth in a series of instruments developed for monitoring aerosols and gaseous constituents in the stratosphere and troposphere. SAGE III will be delivered to the International Space Station (ISS) via the SpaceX Dragon vehicle in 2015. A detailed thermal model of the SAGE III payload has been developed in Thermal Desktop (TD). Several novel methods have been implemented to facilitate efficient payload-level thermal analysis, including the use of a design of experiments (DOE) methodology to determine the worst-case orbits for SAGE III while on ISS, use of TD assemblies to move payloads from the Dragon trunk to the Enhanced Operational Transfer Platform (EOTP) to its final home on the Expedite the Processing of Experiments to Space Station (ExPRESS) Logistics Carrier (ELC)-4, incorporation of older models in varying unit sets, ability to change units easily (including hardcoded logic blocks), case-based logic to facilitate activating heaters and active elements for varying scenarios within a single model, incorporation of several coordinate frames to easily map to structural models with differing geometries and locations, and streamlined results processing using an Excel-based text file plotter developed in-house at LaRC. This document presents an overview of the SAGE III thermal model and describes the development and implementation of these efficiency-improving analysis methods.

Liles, Kaitlin↗
DOE OSTI2022

Improving Peptide-Level Mass Spectrometry Analysis via Double Competition

A critical statistical task in the analysis of shotgun proteomics data involves controlling the false discovery rate (FDR) among the reported set of discoveries. This task is most commonly solved at the peptide-spectrum match (PSM) level by using target-decoy competition (TDC), in which a set of observed spectra are searched against a database containing a mixture of real (target) and decoy peptides. The PSM-level procedure can be adapted to the peptide level by selecting the top-scoring PSM per peptide prior to FDR estimation. Here, we investigate both PSM-level and peptide-level FDR control methods and come to two conclusions. First, although the TDC procedure is provably correct under certain assumptions, we observe that one of these assumptions - that incorrect PSMs are independent of one another - is frequently violated. Hence, we empirically demonstrate that TDC-based PSM-level FDR estimates can be liberally biased. Further, we propose that researchers avoid PSM-level results and instead focus on peptide-level analysis. Second, we investigate three ways to carry out peptide level TDC and show that the most common method ("PSM-only") offers the lowest statistical power in practice. The most powerful method, peptide-level FDR with PSM competition ("PSM-and-peptide"), carries out competition first at the PSM level and then again at the peptide level. In our experiments, this approach yields an average increase of 17% more discovered peptides at a1% FDR threshold relative to the PSM-only method.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Construction of linearly independent non-orthogonal AGP states

We show how to construct a linearly independent set of antisymmetrized geminal power (AGP) states, which allows us to rewrite our recently introduced geminal replacement models as linear combinations of non-orthogonal AGPs. Furthermore, this greatly simplifies the evaluation of matrix elements and permits us to introduce an AGP-based selective configuration interaction method, which can reach arbitrary excitation levels relative to a reference AGP, balancing accuracy and cost as we see fit.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Using heterogeneous data to identify signatures of dengue outbreaks at fine spatio-temporal scales across Brazil

Dengue virus remains a significant public health challenge in Brazil, and seasonal preparation efforts are hindered by variable intra- and interseasonal dynamics. Here, we present a framework for characterizing weekly dengue activity at the Brazilian mesoregion level from 2010–2016 as time series properties that are relevant to forecasting efforts, focusing on outbreak shape, seasonal timing, and pairwise correlations in magnitude and onset. In addition, we use a combination of 18 satellite remote sensing imagery, weather, clinical, mobility, and census data streams and regression methods to identify a parsimonious set of covariates that explain each time series property. The models explained 54% of the variation in outbreak shape, 38% of seasonal onset, 34% of pairwise correlation in outbreak timing, and 11% of pairwise correlation in outbreak magnitude. Regions that have experienced longer periods of drought sensitivity, as captured by the “normalized burn ratio,” experienced less intense outbreaks, while regions with regular fluctuations in relative humidity had less regular seasonal outbreaks. Both the pairwise correlations in outbreak timing and outbreak trend between mesoresgions were best predicted by distance. Our analysis also revealed the presence of distinct geographic clusters where dengue properties tend to be spatially correlated. Forecasting models aimed at predicting the dynamics of dengue activity need to identify the most salient variables capable of contributing to accurate predictions. Our findings show that successful models may need to leverage distinct variables in different locations and be catered to a specific task, such as predicting outbreak magnitude or timing characteristics, to be useful. This advocates in favor of “adaptive models” rather than “one-size-fits-all” models. The results of this study can be applied to improving spatial hierarchical or target-focused forecasting models of dengue activity across Brazil.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

VERA Enhancements for Cross Section Shielding and Geometry Capabilities

Two tasks were undertaken in FY22 that focus on VERA enhancements. The first task involved improvements to the new cross section shielding capability that was added to VERA in FY21. This cell-based capability solves the slowing down problem for each pin cell using Dancoff factors calculated from the whole-core problem. The Dancoff factors are determined for each subgroup level for important sets of materials such as fuel rods, control rods, fuel rods loaded with gad, etc. The cross-section shielding is then performed for each cell using a 1D cylindrical collision probabilities (CP) calculation to obtain the equivalence cross sections required for the core transport calculations. The advantage of this method over the whole-core subgroup calculations is efficiency, since far fewer sweeps of the entire core are required.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Measuring the Density Fields around Bright Quasars at z ~ 6 with XQR-30 Spectra

Measuring the density of the intergalactic medium using quasar sight lines in the epoch of reionization is challenging due to the saturation of Ly α absorption. Near a luminous quasar, however, the enhanced radiation creates a proximity zone observable in the quasar spectra where the Ly α absorption is not saturated. In this study, we use 10 high-resolution ( R ≳ 10,000) z ~ 6 quasar spectra from the extended XQR-30 sample to measure the density field in the quasar proximity zones. We find a variety of environments within 3 pMpc distance from the quasars. We compare the observed density cumulative distribution function (CDF) with models from the Cosmic Reionization on Computers simulation and find a good agreement between 1.5 and 3 pMpc from the quasar. This region is far away from the quasar hosts and hence approaching the mean density of the universe, which allows us to use the CDF to set constraints on the cosmological parameter σ 8 = 0.6 ± 0.3. The uncertainty is mainly due to the limited number of high-quality quasar sight lines currently available. Utilizing the more than 200 known quasars at z ≳ 6, this method will allow us to tighten the constraint on σ 8 to the percent level in the future. In the region closer to the quasar within 1.5 pMpc, we find that the density is higher than predicted in the simulation by 1.23 ± 0.17, suggesting that the typical host dark matter halo mass of a bright quasar ( M 1450 < -26.5) at z ~ 6 is .

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1978

Study of communications data compression methods

A simple monochrome conditional replenishment system was extended to higher compression and to higher motion levels, by incorporating spatially adaptive quantizers and field repeating. Conditional replenishment combines intraframe and interframe compression, and both areas are investigated. The gain of conditional replenishment depends on the fraction of the image changing, since only changed parts of the image need to be transmitted. If the transmission rate is set so that only one fourth of the image can be transmitted in each field, greater change fractions will overload the system. A computer simulation was prepared which incorporated (1) field repeat of changes, (2) a variable change threshold, (3) frame repeat for high change, and (4) two mode, variable rate Hadamard intraframe quantizers. The field repeat gives 2:1 compression in moving areas without noticeable degradation. Variable change threshold allows some flexibility in dealing with varying change rates, but the threshold variation must be limited for acceptable performance.

Jones, H. W.↗
NASA NTRS1989

Space station Simulation Computer System (SCS) study for NASA/MSFC. Volume 4: Conceptual design report

The Simulation Computer System (SCS) is the computer hardware, software, and workstations that will support the Payload Training Complex (PTC) at Marshall Space Flight Center (MSFC). The PTC will train the space station payload scientists, station scientists, and ground controllers to operate the wide variety of experiments that will be onboard the Space Station Freedom. In the first step of this task, a methodology was developed to ensure that all relevant design dimensions were addressed, and that all feasible designs could be considered. The development effort yielded the following method for generating and comparing designs in task 4: (1) Extract SCS system requirements (functions) from the system specification; (2) Develop design evaluation criteria; (3) Identify system architectural dimensions relevant to SCS system designs; (4) Develop conceptual designs based on the system requirements and architectural dimensions identified in step 1 and step 3 above; (5) Evaluate the designs with respect to the design evaluation criteria developed in step 2 above. The results of the method detailed in the above 5 steps are discussed. The results of the task 4 work provide the set of designs which two or three candidate designs are to be selected by MSFC as input to task 5-refine SCS conceptual designs. The designs selected for refinement will be developed to a lower level of detail, and further analyses will be done to begin to determine the size and speed of the components required to implement these designs.

Source record↗
NASA NTRS1989

Fourier transform methods in local gravity modeling

New algorithms were derived for computing terrain corrections, all components of the attraction of the topography at the topographic surface and the gradients of these attractions. These algoriithms utilize fast Fourier transforms, but, in contrast to methods currently in use, all divergences of the integrals are removed during the analysis. Sequential methods employing a smooth intermediate reference surface were developed to avoid the very large transforms necessary when making computations at high resolution over a wide area. A new method for the numerical solution of Molodensky's problem was developed to mitigate the convergence difficulties that occur at short wavelengths with methods based on a Taylor series expansion. A trial field on a level surface is continued analytically to the topographic surface, and compared with that predicted from gravity observations. The difference is used to compute a correction to the trial field and the process iterated. Special techniques are employed to speed convergence and prevent oscillations. Three different spectral methods for fitting a point-mass set to a gravity field given on a regular grid at constant elevation are described. Two of the methods differ in the way that the spectrum of the point-mass set, which extends to infinite wave number, is matched to that of the gravity field which is band-limited. The third method is essentially a space-domain technique in which Fourier methods are used to solve a set of simultaneous equations.

Harrison, J. C.↗
NASA NTRS2004

Using Trained Pixel Classifiers to Select Images of Interest

We present a machine-learning-based approach to ranking images based on learned priorities. Unlike previous methods for image evaluation, which typically assess the value of each image based on the presence of predetermined specific features, this method involves using two levels of machine-learning classifiers: one level is used to classify each pixel as belonging to one of a group of rather generic classes, and another level is used to rank the images based on these pixel classifications, given some example rankings from a scientist as a guide. Initial results indicate that the technique works well, producing new rankings that match the scientist's rankings significantly better than would be expected by chance. The method is demonstrated for a set of images collected by a Mars field-test rover.

Mazzoni, D.↗
NASA NTRS2007

Numerical Technique for Analyzing Rotating Rake Mode Measurements in a Duct With Passive Treatment and Shear Flow

A technique is presented for the analysis of measured data obtained from a rotating microphone rake system. The system is designed to measure the interaction modes of ducted fans. A Fourier analysis of the data from the rotating system results in a set of circumferential mode levels at each radial location of a microphone inside the duct. Radial basis functions are then least-squares fit to this data to obtain the radial mode amplitudes. For ducts with soft walls and mean flow, the radial basis functions must be numerically computed. The linear companion matrix method is used to obtain both the eigenvalues of interest, without an initial guess, and the radial basis functions. The governing equations allow for the mean flow to have a boundary layer at the wall. In addition, a nonlinear least-squares method is used to adjust the wall impedance to best fit the data in an attempt to use the rotating system as an in-duct wall impedance measurement tool. Simulated and measured data are used to show the effects of wall impedance and mean flow on the computed results.

Dahl, Milo D.↗
DOE OSTI2022

A Self-learning Neural Network Approach for Radio Frequency Interference Detection and Removal in Radio Astronomy

In this work, we present a novel neural network (NN) method for the detection and removal of radio frequency interference (RFI) from the raw digitized signal in the signal processing chain of a typical radio astronomy experiment. The main advantage of our method is that it does not require a training set. Instead, our method relies on the fact that the true signal of interest coming from astronomical sources is thermal and therefore described as a Gaussian random process, which cannot be compressed. We employ a variational encoder/decoder network to find the compressible information in the data stream that can explain the most variance with the fewest degrees of freedom. We demonstrate it on a set of toy problems and stored ring buffers from the Baryon Mapping eXperiment prototype. We find that the RFI subtraction is effective at cleaning simulated time streams: While we find that the power spectra of the RFI-cleaned time streams output by the NN suffer from extra signal consistent with additive noise, we find that it is generally around percent level across the band and sub 10% in contaminated spectral channels even when RFI power is an order of magnitude larger than the signal. We discuss the advantages and limitations of this method and possible implementation in the front end of future radio experiments.

79 ASTRONOMY AND ASTROPHYSICS↗