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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Evaluation of SNS Beamline Shielding Configurations using MCNPX Accelerated by ADVANTG

Shielding analyses for the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory pose significant computational challenges, including highly anisotropic high-energy sources, a combination of deep penetration shielding and an unshielded beamline, and a desire to obtain well-converged nearly global solutions for mapping of predicted radiation fields. The majority of these analyses have been performed using MCNPX with manually generated variance reduction parameters (source biasing and cell-based splitting and Russian roulette) that were largely based on the analyst's insight into the problem specifics. Development of the variance reduction parameters required extensive analyst time, and was often tailored to specific portions of the model phase space. We previously applied a developmental version of the ADVANTG code to an SNS beamline study to perform a hybrid deterministic/Monte Carlo analysis and showed that we could obtain nearly global Monte Carlo solutions with essentially uniform relative errors for mesh tallies that cover extensive portions of the model with typical voxel spacing of a few centimeters. The use of weight window maps and consistent biased sources produced using the FW-CADIS methodology in ADVANTG allowed us to obtain these solutions using substantially less computer time than the previous cell-based splitting approach. While those results were promising, the process of using the developmental version of ADVANTG was somewhat laborious, requiring user-developed Python scripts to drive much of the analysis sequence. In addition, limitations imposed by the size of weight-window files in MCNPX necessitated the use of relatively coarse spatial and energy discretization for the deterministic Denovo calculations that we used to generate the variance reduction parameters. We recently applied the production version of ADVANTG to this beamline analysis, which substantially streamlined the analysis process. We also tested importance function collapsing (in space and energy) capabilities in ADVANTG. These changes, along with the support for parallel Denovo calculations using the current version of ADVANTG, give us the capability to improve the fidelity of the deterministic portion of the hybrid analysis sequence, obtain improved weight-window maps, and reduce both the analyst and computational time required for the analysis process.

43 PARTICLE ACCELERATORS↗
NASA NTRSDate not supplied

Variance Decomposition of MEDLI2 Reconstructed Heating Using Neural Networks

The Mars Entry, Descent, and Landing Instrumentation (MEDLI2) sensor suite collected data during entry of the Mars 2020 Perseverance rover into Mars’ atmosphere. An inverse estimation of the backshell and heatshield surface aeroheating was performed, using the data from the MEDLI2 Instrumented Sensor Plugs, a network of thermocouples embedded within the thermal protection system across the aeroshell. Monte Carlo analysis was conducted to assess the sensitivity of the surface heat rate, temperature, and heat load to uncertainties in thermocouple depth and material properties. In this paper, a variance decomposition method using Sobol indices was employed to understand the relative contributions of each uncertainty parameter. Performing this analysis using results from the inverse analysis tool FIAT_Opt was found to require incredibly high computation time, and thus machine learning models were trained and evaluated as a surrogate model for FIAT_Opt. This paper demonstrates that machine learning models can be an efficient, accurate alternative to state-of-the-art inverse analysis tools like FIAT_Opt, especially for computationally-expensive processes. Using these models, the sensitivity analysis showed that uncertainties in heat capacity and thermal conductivity were the main drivers for the overall uncertainty in peak reconstructed heating and heat load.

H S Alpert↗
DOE OSTI2014

On the equivalence of the RTI and SVM approaches to time correlated analysis

Recently two papers on how to perform passive neutron auto-correlation analysis on time gated histograms formed from pulse train data, generically called time correlation analysis (TCA), have appeared in this journal [1,2]. For those of us working in international nuclear safeguards these treatments are of particular interest because passive neutron multiplicity counting is a widely deployed technique for the quantification of plutonium. The purpose of this letter is to show that the skewness-variance-mean (SVM) approach developed in [1] is equivalent in terms of assay capability to the random trigger interval (RTI) analysis laid out in [2]. Mathematically we could also use other numerical ways to extract the time correlated information from the histogram data including for example what we might call the mean, mean square, and mean cube approach. The important feature however, from the perspective of real world applications, is that the correlated information extracted is the same, and subsequently gets interpreted in the same way based on the same underlying physics model.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1972

An auditory display in a dual-axis tracking task.

Results of a study in which subjects were presented concurrently with the primary task of controlling a second-order plant and the secondary task of controlling a first-order plant. The plant errors for the two tasks were shown on separate visual displays. An auditory display, whose output varied in frequency and volume with the error, was used to supplement the secondary task in half of the runs. To study the effects of the auditory display, two performance measures were obtained: (1) the integral of the squared error (ISE) and (2) the describing functions of the human operator. Statistical analysis of the ISE measures indicated that when the secondary task was supplemented with an auditory display, there was a significant improvement in performance on the secondary task. The performance on the primary task improved on the average, but not significantly. The variances of the ISE values decreased for both the tasks, indicating a more consistent behavior with the auditory display. The describing function analysis showed that supplementing the secondary task with the auditory display increased the low frequency gain of the human operator for this task. The describing functions for the primary task did not show any apparent changes.

Mirchandani, P. B.↗
DOE OSTI2022

Decay Dose Shielding Analysis with Hybrid Unstructured Mesh/Constructive Solid Geometry Monte Carlo Calculation and ADVANTG Acceleration

The Oak Ridge National Laboratory (ORNL) Second Target Station (STS) neutron production facility is an accelerator driven pulsed neutron source that is currently being actively developed at ORNL. The neutrons are produced by proton-induced spallation reactions. A proton beam of 700 kW power is delivered to a spallation target in short, less than 1 µs long pulses, with 15 Hz repetition rate. The spallation target of ORNL STS is a rotating water-cooled tungsten target with tantalum cladding housed in a stainless-steel shroud. It is divided into 21 segments. These segments become highly activated due to spallation reactions or nuclei transmutation by the emitted neutrons. The radioactive nuclides continue to decay after ceasing operation. The decay dose rates generated from the target segments once they are removed from their operational location within the core vessel must be accurately quantified to determine the shielding configurations of remote handling tools and transport casks and to aid in planning maintenance events. To determine the shielding configurations needed for an activated target segment after ceasing operation, both the hybrid unstructured mesh (UM)/constructive solid geometry (CSG) approach that was previously utilized for STS analyses [1] and the ADVANTG code [2] were used. Even though the ADVANTG code does not include UM capability, the utilization of its advanced variance reduction technique was crucial to accelerate the extremely difficult final photon transport calculation in this analysis. This paper also describes the procedures taken to mitigate the convergence issues that occur when ADVANTG uses a source definition that does not match the source of the final Monte Carlo (MC) calculation. These convergence issues often occur because of inconsistencies between source and transport biasing parameters.

Ibrahim, Ahmad↗
NASA NTRS1973

Engineering studies related to geodetic and oceanographic remote sensing using short pulse techniques

For the Skylab S-193 radar altimeter, data processing flow charts and identification of calibration requirements and problem areas for defined S-193 altimeter experiments are presented. An analysis and simulation of the relationship between one particular S-193 measurement and the parameter of interest for determining the sea surface scattering cross-section are considered. For the GEOS-C radar altimeter, results are presented for system analyses pertaining to signal-to-noise ratio, pulse compression threshold behavior, altimeter measurement variance characteristics, desirability of onboard averaging, tracker bandwidth considerations, and statistical character of the altimeter data in relation to harmonic analysis properties of the geodetic signal.

Miller, L. S.↗
DOE OSTI2021

Machine Learning-Based Classification of Lignocellulosic Biomass from Pyrolysis-Molecular Beam Mass Spectrometry Data

High-throughput analysis of biomass is necessary to ensure consistent and uniform feedstocks for agricultural and bioenergy applications and is needed to inform genomics and systems biology models. Pyrolysis followed by mass spectrometry such as molecular beam mass spectrometry (py-MBMS) analyses are becoming increasingly popular for the rapid analysis of biomass cell wall composition and typically require the use of different data analysis tools depending on the need and application. Here, the authors report the py-MBMS analysis of several types of lignocellulosic biomass to gain an understanding of spectral patterns and variation with associated biomass composition and use machine learning approaches to classify, differentiate, and predict biomass types on the basis of py-MBMS spectra. Py-MBMS spectra were also corrected for instrumental variance using generalized linear modeling (GLM) based on the use of select ions relative abundances as spike-in controls. Machine learning classification algorithms e.g., random forest, k-nearest neighbor, decision tree, Gaussian Naïve Bayes, gradient boosting, and multilayer perceptron classifiers were used. The k-nearest neighbors (k-NN) classifier generally performed the best for classifications using raw spectral data, and the decision tree classifier performed the worst. After normalization of spectra to account for instrumental variance, all the classifiers had comparable and generally acceptable performance for predicting the biomass types, although the k-NN and decision tree classifiers were not as accurate for prediction of specific sample types. Gaussian Naïve Bayes (GNB) and extreme gradient boosting (XGB) classifiers performed better than the k-NN and the decision tree classifiers for the prediction of biomass mixtures. The data analysis workflow reported here could be applied and extended for comparison of biomass samples of varying types, species, phenotypes, and/or genotypes or subjected to different treatments, environments, etc. to further elucidate the sources of spectral variance, patterns, and to infer compositional information based on spectral analysis, particularly for analysis of data without a priori knowledge of the feedstock composition or identity.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2008

On Certain New Methodology for Reducing Sensor and Readout Electronics Circuitry Noise in Digital Domain

NASA Hubble Space Telescope (HST) and upcoming cosmology science missions carry instruments with multiple focal planes populated with many large sensor detector arrays. These sensors are passively cooled to low temperatures for low-level light (L3) and near-infrared (NIR) signal detection, and the sensor readout electronics circuitry must perform at extremely low noise levels to enable new required science measurements. Because we are at the technological edge of enhanced performance for sensors and readout electronics circuitry, as determined by thermal noise level at given temperature in analog domain, we must find new ways of further compensating for the noise in the signal digital domain. To facilitate this new approach, state-of-the-art sensors are augmented at their array hardware boundaries by non-illuminated reference pixels, which can be used to reduce noise attributed to sensors. There are a few proposed methodologies of processing in the digital domain the information carried by reference pixels, as employed by the Hubble Space Telescope and the James Webb Space Telescope Projects. These methods involve using spatial and temporal statistical parameters derived from boundary reference pixel information to enhance the active (non-reference) pixel signals. To make a step beyond this heritage methodology, we apply the NASA-developed technology known as the Hilbert- Huang Transform Data Processing System (HHT-DPS) for reference pixel information processing and its utilization in reconfigurable hardware on-board a spaceflight instrument or post-processing on the ground. The methodology examines signal processing for a 2-D domain, in which high-variance components of the thermal noise are carried by both active and reference pixels, similar to that in processing of low-voltage differential signals and subtraction of a single analog reference pixel from all active pixels on the sensor. Heritage methods using the aforementioned statistical parameters in the digital domain (such as statistical averaging of the reference pixels themselves) zeroes out the high-variance components, and the counterpart components in the active pixels remain uncorrected. This paper describes how the new methodology was demonstrated through analysis of fast-varying noise components using the Hilbert-Huang Transform Data Processing System tool (HHT-DPS) developed at NASA and the high-level programming language MATLAB (Trademark of MathWorks Inc.), as well as alternative methods for correcting for the high-variance noise component, using an HgCdTe sensor data. The NASA Hubble Space Telescope data post-processing, as well as future deep-space cosmology projects on-board instrument data processing from all the sensor channels, would benefit from this effort.

Kizhner, Semion↗
NASA NTRS1995

Assimilation of TOPEX Sea Level Measurements with a Reduced-Gravity, Shallow Water Model of the Tropical Pacific Ocean

Sea surface height variability measured by TOPEX is analyzed in the tropical Pacific Ocean by way of assimilation into a wind-driven, reduced-gravity, shallow water model using an approximate Kalman filter and smoother. The analysis results in an optimal fit of the dynamic model to the observations, providing it dynamically consistent interpolation of sea level and estimation of the circulation. Nearly 80% of the expected signal variance is accounted for by the model within 20 deg of the equator, and estimation uncertainty is substantially reduced by the voluminous observation. Notable features resolved by the analysis include seasonal changes associated with the North Equatorial Countercurrent and equatorial Kelvin and Rossby waves. Significant discrepancies are also found between the estimate and TOPEX measurements, especially near the eastern boundary. Improvements in the estimate made by the assimilation are validated by comparisons with independent tide gauge and current meter observations. The employed filter and smoother are based on approximately computed estimation error covariance matrices, utilizing a spatial transformation and an symptotic approximation. The analysis demonstrates the practical utility of a quasi-optimal filter and smoother.

Fukumori, Ichiro↗
DOE OSTI2016

Interannual variability of the South Indian Countercurrent

In the present work, we investigate the interannual variability of the South Indian Countercurrent (SICC), a major and still understudied current of the Indian Ocean circulation. To characterize the interannual variability of the SICC, four different data sets (altimetry, GLORYS, OFAM3, and SODA) are analyzed using multiple tools, which include Singular Spectrum Analysis and wavelet methods. The quasi-biennial band dominates the SICC low-frequency variance, with the main peak in the 1.5–1.8 year interval. A secondary peak (2.1–2.5 year) is only found in the western basin. Interannual and decadal-type modulations of the quasi-biennial signal are also identified. In addition, limitations of SODA before the 1960s in the SICC region are revealed. Within the quasi-biennial band, the SICC system presents two main patterns with a multiple jet structure. One pattern is characterized by a robust northern jet, while in the other the central jet is well developed and northern jet is weaker. In both patterns, the southern jet has always a strong signature. Further, when the northern SICC jet is stronger, the northern cell of the subtropical gyre has a triangular shape, with its southern limb having a strong equatorward slant. The quasi-biennial variability of the SICC is probably related to the Indian Ocean tropical climate modes that are known to have a strong biennial characteristic.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Tree-ring evidence marks year 2022 as the driest spring season in nearly four centuries in the Western Himalayas

The Hindukush-Karakoram-Himalayan region is a crucial freshwater source for billions across South Asia, yet its climate remains poorly understood due to limited long-term records. Winter and spring precipitation govern snow accumulation and downstream water availability in dry months particularly across the Western Himalayas (WH), but recent decades show intensifying droughts with unclear long-term context. Here, we have reconstructed a nearly four-century-long spring i.e. February to May (FMAM) precipitation for the Lahaul region of the (WH), an area dominated by the Western Disturbances. This record was developed using moisture-sensitive Cedrus deodara (Deodar) tree-rings from three high-elevation sites. A regional composite tree-ring-width chronology, developed through a Nested Principal Component Analysis and modeled with a nonlinear Generalized Additive Model (GAM) that explains 71 % of the variance during the calibration period. We identified the last two decades as the most precipitation deficit phase and the year 2022 showing the driest FMAM on record. The observed rise in the FMAM dry episodes post 1999 CE in our reconstruction, corresponds to the meteorological records. This recent drying is linked to a northward shift of the subtropical westerly jet and reduced moisture transport, both associated with unusual sea surface temperature patterns in the tropical Indian Ocean and the Western Pacific Ocean. Our results provide compelling evidence of long-term hydroclimatic instability in the WH and emphasize the value of tree-ring records in extending precipitation histories beyond the instrumental observations. Such reconstructions can be benchmarks to validate high-resolution climate models and formulate adaptation policies to mitigate future risks.

Cedrus deodara↗
DOE OSTI2020

Metagenome-assembled genome distribution and key functionality highlight importance of aerobic metabolism in Svalbard permafrost

Permafrost underlies a large portion of the land in the Northern Hemisphere. It is proposed to be an extreme habitat and home for cold-adaptive microbial communities. Upon thaw permafrost is predicted to exacerbate increasing global temperature trend, where awakening microbes decompose millennia old carbon stocks. Yet our knowledge on composition, functional potential and variance of permafrost microbiome remains limited. In this study, we conducted a deep comparative metagenomic analysis through a 2 m permafrost core from Svalbard, Norway to determine key permafrost microbiome in this climate sensitive island ecosystem. To do so, we developed comparative metagenomics methods on metagenomic-assembled genomes (MAG). We found that community composition in Svalbard soil horizons shifted markedly with depth: the dominant phylum switched from Acidobacteria and Proteobacteria in top soils (active layer) to Actinobacteria, Bacteroidetes, Chloroflexi and Proteobacteria in permafrost layers. Key metabolic potential propagated through permafrost depths revealed aerobic respiration and soil organic matter decomposition as key metabolic traits. We also found that Svalbard MAGs were enriched in genes involved in regulation of ammonium, sulfur and phosphate. Here, we provide a new perspective on how permafrost microbiome is shaped to acquire resources in competitive and limited resource conditions of deep Svalbard soils.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Forecasting cosmological constraints from the weak lensing magnification of type Ia supernovae measured by the Nancy Grace Roman Space Telescope

We report that the weak lensing magnification of type Ia supernovae (SNe Ia) is sensitive to the clustering of matter and provides an independent cosmological probe complementary to SN Ia distance measurements. The Nancy Grace Roman Space Telescope is uniquely sensitive to this measurement as it can discover high redshift SNe Ia and measure them with high precision. We present a methodology for reconstructing the probability distribution of the weak lensing magnification μ of SNe Ia, p(μ), from observational data, and using it to constrain cosmological parameters. We find that the reconstructed p(μ) can be fitted accurately by a stretched Gaussian distribution and used to measure the variance of μ, ξ μ , which can be compared to theoretical predictions in a likelihood analysis. Applying our methodology to a set of realistically simulated SNe Ia expected from the Roman Space Telescope, we find that using the weak lensing magnification of the SNe Ia constrains a combination of matter density Ω m and matter clustering amplitude σ 8 . SN Ia distances alone lead to a better than 1% measurement of Ωm. The combination of SN Ia weak lensing magnification and distance measurements result in a ~10 % measurement on σ 8 . The SNe Ia from Roman will be powerful in constraining the cosmological model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Full covariance of CMB and lensing reconstruction power spectra

CMB and lensing reconstruction power spectra are powerful probes of cosmology. However, they are correlated, since the CMB power spectra are lensed, and the lensing reconstruction is constructed using CMB multipoles. This paper discusses how we perform a full analysis of the auto- and cross-covariances, including polarization power spectra and minimum-variance lensing estimators, and compare with simulations of idealized future CMB-S4 observations. Covariances sourced by fluctuations in the unlensed CMB and instrumental noise can largely be removed by using a realization-dependent subtraction of lensing reconstruction noise, leaving a relatively simple covariance model that is dominated by lensing-induced terms and well described by a small number of principal components. The correlations between the CMB and lensing power spectra will be detectable at the level of $\sim 5σ$ for a CMB-S4 mission, and neglecting them could underestimate some parameter error bars by several tens of percent. However, we found that the inclusion of external priors or data sets to estimate parameter error bars can make the impact of the correlations almost negligible.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1978

Seasonal and interannual variations in total ozone revealed by the Nimbus-4 backscattered ultraviolet experiment

The first two years of Backscattered Ultraviolet (BUV) ozone data from the Nimbus-4 spacecraft were reprocessed. The seasonal variations of total ozone for the period April 1970 to April 1972 are described using daily zonal means to 10 deg latitude zones and a time-latitude cross section. In addition, the BUV data are compared with analyzed Dobson data and with IRIS data also obtained from the Nimbus-4 spacecraft. A harmonic analysis was performed on the daily zonal means. Amplitudes, days of peaks, and percentage of variance were computed for annual and semi-annual waves and for higher harmonics of an annual period for the two years. Asymmetries are found in the annual waves in the two hemispheres, with a subtle interannual difference which may be due to changes in the general circulation. A significant semi-annual component is detected in the tropics for the first year, which appears to result from influences of the annual waves in the two hemispheres.

Hilsenrath, E.↗
NASA NTRS1981

Large-scale variations in observed Antarctic Sea ice extent and associated atmospheric circulation

The 1974 Antarctic large scale sea ice extent is studied from data from Nimbus 2 and 5 and temperature and sea level pressure fields from the Australian Meteorological Data Set. Electrically Scanning Microwave Radiometer data were three-day averaged and compared with 1000 mbar atmospheric pressure and sea level pressure data, also in three-day averages. Each three-day period was subjected to a Fourier analysis and included the mean latitude of the ice extent and the phases and percent variances in terms of the first six Fourier harmonics. Centers of low pressure were found to be generally east of regions which displayed rapid ice growth, and winds acted to extend the ice equatorward. An atmospheric response was also noted as caused by the changing ice cover.

Cavalieri, D. J.↗
NASA NTRS1987

Measurements of the unsteady flow field within the stator row of a transonic axial-flow fan. 1: Measurement and analysis technique

This two-part paper presents laser anemometer measurements of the unsteady velocity field within the stator row of a transonic axial-flow fan. The objective is to provide additional insight into unsteady blade-row interactions within high speed compressors which affect stage efficiency, energy transfer, and other design considerations. Part 1 describes the measurement and analysis techniques used for resolving the unsteady flow field features. The ensemble-average and variance of the measured velocities are used to identify the rotor wake generated and unresolved unsteadiness, respectively. (Rotor wake generated unsteadiness refers to the unsteadiness generated by the rotor wake velocity deficit and the term unresolved unsteadiness refers to all remaining contributions to unsteadiness such as vortex shedding, turbulence, mass flow fluctuations, etc.). A procedure for calculating auto and cross correlations of the rotor wake generated and unresolved unsteady velocity fluctuations is described. These unsteady-velocity correlations have significance since they also result from a decomposition of the Navier-Stokes equations. This decomposition of the Navier-Stokes equations resulting in the velocity correlations used to describe the unsteady velocity field will also be outlined in this paper.

Suder, K. L.↗
NASA NTRS1987

Measurements of the unsteady flow field within the stator row of a transonic axial-flow fan. I - Measurement and analysis technique

This two-part paper presents laser anemometer measurements of the unsteady velocity field within the stator row of a transonic axial-flow fan. The objective is to provide additional insight into unsteady blade-row interactions within highspeed compressors which affect stage efficiency, energy transfer, and other design considerations. Part 1 describes the measurement and analysis techniques used for resolving the unsteady flow field features. The ensemble-average and variance of the measured velocities are used to identify the rotor wake generated and unresolved unsteadiness, respectively. (Rotor wake generated unsteadiness refers to the unsteadiness generated by the rotor wake velocity deficit and the term unresolved unsteadiness refers to all remaining contributions to unsteadiness such as vortex shedding, turbulence, mass flow fluctutions, etc.). A procedure for calculating auto and cross correlations of the rotor wake generated and unresolved unsteady velocity fluctuations is described. These unsteady-velocity correlations have significance since they also result from a decomposition of the Navier-Stokes equations. This decomposition of the Navier-Stokes equations resulting in the velocity correlations used to describe the unsteady velocity field will also be outlined in this paper.

Suder, K. L.↗