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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 955 records · Page 53
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Search for supersymmetry in events with at least one photon, missing transverse momentum, and large transverse event activity in proton-proton collisions at $ \sqrt{s}=13 $ TeV

A search for physics beyond the standard model in final states with at least one photon, large transverse momentum imbalance, and large total transverse event activity is presented. Such topologies can be produced in gauge-mediated supersymmetry models in which pair-produced gluinos or squarks decay to photons and gravitinos via short-lived neutralinos. The data sample corresponds to an integrated luminosity of 35.9 fb$^{−1}$ of proton-proton collisions at $ \sqrt{s}=13 $ TeV recorded by the CMS experiment at the LHC in 2016. No significant excess of events above the expected standard model background is observed. The data are interpreted in simplified models of gluino and squark pair production, in which gluinos or squarks decay via neutralinos to photons. Gluino masses of up to 1.50-2.00 TeV and squark masses up to 1.30-1.65 TeV are excluded at 95% confidence level, depending on the neutralino mass and branching fraction.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Gamma-Ray Emitting Radionuclides Concentrations and Decontamination Factors of ATR Loop Liquid Samples Cycle 171B

This report contains the gamma-ray emitting radionuclides concentration and decontamination factor results from gamma-ray spectrometry measurements of ATR loop liquid samples by the Radiation Measurements Laboratory (RML) for ATR Cycle 171B Jun. 20, 2023, to Sep. 27, 2023. This report consists of five subsections, one for each loop. Each subsection contains the results for each sampling of the loop along with the date and time of sampling, spectral data identifications, sample type, and reactor power (MW). The results are reported in units of disintegrations per minute per milliliter of sample. The results are obtained with the gamma-ray spectral data analysis routines of the RML computer. Some of this report is also generated by RML data storage and handling routines.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Gamma-Ray Emitting Radionuclides Concentrations and Decontamination Factors of ATR Loop Liquid Samples: Cycle 172A

This report contains the gamma-ray emitting radionuclides concentration and decontamination factor results from gamma-ray spectrometry measurements of ATR loop liquid samples by the Radiation Measurements Laboratory (RML) for ATR Cycle 172A running March 2, 2024, to March 16, 2024. This report consists of five subsections, one for each loop. Each subsection contains the results for each sampling of the loop along with the date and time of sampling, spectral data identifications, sample type, and reactor power (MW). The results are reported in units of disintegrations per minute per milliliter of sample. The results are obtained with the gamma-ray spectral data analysis routines of the RML computer. Some of this report is also generated by RML data storage and handling routines.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Gamma-Ray Emitting Radionuclides Concentrations and Decontamination Factors of ATR Loop Liquid Samples Cycle 173A Revision 0

This report contains the gamma-ray emitting radionuclides concentration and decontamination factor results from gamma-ray spectrometry measurements of ATR loop liquid samples by the Radiation Measurements Laboratory (RML) for ATR Cycle 173A running May 3, 2024, to July 6, 2024. This report consists of five subsections, one for each loop. Each subsection contains the results for each sampling of the loop along with the date and time of sampling, spectral data identifications, sample type, and reactor power (MW). The results are reported in units of disintegrations per minute per milliliter of sample. The results are obtained with the gamma-ray spectral data analysis routines of the RML computer. Some of this report is also generated by RML data storage and handling routines.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1981

Deconvolution of wide field-of-view radiometer measurements of earth-emitted radiation. II - Analysis of first year of Nimbus 6 ERB data

The theory of deconvolution considered by Smith and Green (1981) is applied to Nimbus 6 data in order to interpret the data with the maximum obtainable resolution. Attention is given to the data sample, sun-contaminated measurements, the measurement model, the deconvolution, the degree variance, the spherical harmonic coefficients, the geographical distribution of longwave radiation, time histories of zonal coefficients, and the effect of a grid system. Degree variance plots for 12 months of longwave radiation data show that the limit for a spherical harmonic representation of the Nimbus 6 wide field-of-view longwave data is 12th degree. The degree variance plots also reveal that most of the power is in the lower degree terms. Contour maps of the radiation field show the geographical distribution of earth emitted radiant exitance for each month.

Bess, T. D.↗
DOE OSTI2024

Comparison of source-location algorithms for atmospheric samplers

Numerous algorithms have been developed to determine the source characteristics for an atmospheric release, e.g., (Bieringer et al., 2017). This study compares three models that have been applied to the data collected by the International Monitoring System operated by the Comprehensive Nuclear-Test-Ban Treaty Preparatory Commission to estimate source event parameters. Each model uses a different approach to estimate the parameters. A deterministic model uses a possible source region (PSR) approach (Ringbom et al., 2014) that is based on the correlation between predicted and measured sample values. An unnamed model developed at Pacific Northwest National Laboratory (herein called BAYEST) uses a Bayesian formulation (Eslinger et al., 2019; Eslinger et al., 2020; Eslinger and Schrom, 2016). The FREAR model uses a different Bayesian formulation (De Meutter and Hoffman, 2020; De Meutter et al., 2021; Pieter De Meutter, 2021). The performance of the three source-location models is evaluated with 100 synthetic release cases for the single xenon isotope, 133 Xe. The release cases resulted in detections in a fictitious network with 120 noble gas samplers. All three source-location models use the same sampling data. The two Bayesian models yield more accurate location estimates than the deterministic PSR model, with FREAR having slightly better location performance than BAYEST. Samplers with collection periods of 3, 6, 8, 12, and 24-h were used. Results from BAYEST show that location accuracy improves with each reduction in sample collection length. The BAYEST model is slightly better for estimating the start time of the release. The PSR model has about the same spread in start times as the FREAR model, but the PSR results have a better average start time. The Bayesian source-location algorithms give more accurate results than the PSR approach, and provide release magnitude estimates, while the base PSR model does not estimate the release magnitude. This investigation demonstrates that a reasonably dense sampling grid will sometimes yield poor location and time estimates regardless of the model. The poor estimates generally coincide with cases where there is a much larger distance between the release point and the first detecting sampler than the average sampler spacing.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2020

TuckerMPI: A Parallel C++/MPI Software Package for Large-scale Data Compression via the Tucker Tensor Decomposition

With this study, our goal is compression of massive-scale grid-structured data, such as the multi-terabyte output of a high-fidelity computational simulation. For such data sets, we have developed a new software package called TuckerMPI, a parallel C++/MPI software package for compressing distributed data. The approach is based on treating the data as a tensor, i.e., a multidimensional array, and computing its truncated Tucker decomposition, a higher-order analogue to the truncated singular value decomposition of a matrix. The result is a low-rank approximation of the original tensor-structured data. Compression efficiency is achieved by detecting latent global structure within the data, which we contrast to most compression methods that are focused on local structure. In this work, we describe TuckerMPI, our implementation of the truncated Tucker decomposition, including details of the data distribution and in-memory layouts, the parallel and serial implementations of the key kernels, and analysis of the storage, communication, and computational costs. We test the software on 4.5 and 6.7 terabyte data sets distributed across 100 s of nodes (1,000 s of MPI processes), achieving compression ratios between 100 and 200,000×, which equates to 99--99.999% compression (depending on the desired accuracy) in substantially less time than it would take to even read the same dataset from a parallel file system. Moreover, we show that our method also allows for reconstruction of partial or down-sampled data on a single node, without a parallel computer so long as the reconstructed portion is small enough to fit on a single machine, e.g., in the instance of reconstructing/visualizing a single down-sampled time step or computing summary statistics. The code is available at https://gitlab.com/tensors/TuckerMPI.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Search for electroweak production of charginos and neutralinos in WH events in proton-proton collisions at $ \sqrt{s}=13 $ TeV

Results are reported from a search for physics beyond the standard model in proton-proton collision events with a charged lepton (electron or muon), two jets identified as originating from a bottom quark decay, and significant imbalance in the transverse momentum. The search was performed using a data sample corresponding to 35.9 fb$^{−1}$, collected by the CMS experiment in 2016 at $ \sqrt{s}=13 $ TeV. Events with this signature can arise, for example, from the electroweak production of gauginos, which are predicted in models based on supersymmetry. The event yields observed in data are consistent with the estimated standard model backgrounds. Limits are obtained on the cross sections for chargino-neutralino $ \left({\tilde{\chi}}_1^{\pm }{\tilde{\chi}}_2^0\right) $ production in a simplified model of supersymmetry with the decays $ {\chi}_1^{\pm}\to {\mathrm{W}}^{\pm }{\tilde{\chi}}_1^0\kern0.5em \mathrm{and}\kern0.5em {\tilde{\chi}}_2^0\to \mathrm{H}{\chi}_1^0 $ . Values of $ {m}_{{\tilde{\chi}}_1^{\pm }} $ between 220 and 490 GeV are excluded at 95% confidence level by this search when the $ {\tilde{\chi}}_1^0 $ is massless, and values of $ {m}_{{\tilde{\chi}}_1^0} $ are 1 excluded up to 110 GeV for $ {m}_{{\tilde{\chi}}_1^{\pm }}\approx 450 $ GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Understanding Generative AI Content with Embedding Models

The construction of high-quality numerical features is critical to any quantitative data analysis. Feature engineering has been historically addressed by carefully hand-crafting data representations based on domain expertise. This work views the internal representations of modern deep neural networks (DNNs), called embeddings, as an implicit form of traditional feature engineering. For trained DNNs, we show that these embeddings can reveal interpretable, high-level concepts in unstructured sample data. We use these embeddings in natural language and computer vision tasks to uncover both inherent heterogeneity in the underlying data and human-understandable explanations for it. In particular, we find empirical evidence that there is inherent separability between real data and those generated from AI models.

Vargas, Max↗
NASA NTRS1984

A laser velocimeter system for large-scale aerodynamic testing

A unique laser velocimeter was developed that is capable of sensing two orthogonal velocity components from a variable remote distance of 2.6 to 10 m for use in the 40- by 80-Foot and 80- by 120-Foot Wind Tunnels and the Outdoor Aerodynamic Research Facility at Ames Research Center. The system hardware, positioning instrumentation, and data acquisition equipment are described in detail; system capabilities and limitations are discussed; and expressions for systematic and statistical accuracy are developed. Direct and coupled laboratory measurements taken with the system are compared with measurements taken with a laser velocimeter of higher spatial resolution, and sample data taken in the open circuit exhaust flow of a 1/50-scale model of the 80- by 120-Foot Wind Tunnel are presented.

Reinath, M. S.↗
NASA NTRS1989

Parametric study of statistical bias in laser Doppler velocimetry

Analytical studies have often assumed that LDV velocity bias depends on turbulence intensity in conjunction with one or more characteristic time scales, such as the time between validated signals, the time between data samples, and the integral turbulence time-scale. These parameters are presently varied independently, in an effort to quantify the biasing effect. Neither of the post facto correction methods employed is entirely accurate. The mean velocity bias error is found to be nearly independent of data validation rate.

Gould, Richard D.↗
NASA NTRS1992

High temporal resolution velocity estimates from the NASA 50 MHz wind profiler

A three-point medium filter for wind profiling radar has been found which, when applied to successive spectral data, effectively eliminates most spurious echoes from the data while improving SNRs. When combined with velocity calculations using a first guess, the result is a robust system that can extract high-quality wind profiles at three-minute intervals. The velocity computation methodology is described and its performance is illustrated using two sample data sets taken during very different synoptic regimes. Operational considerations are discussed.

Wilfong, Timothy L.↗
DOE OSTI2019

A data-driven framework for sparsity-enhanced surrogates with arbitrary mutually dependent randomness

The challenge of quantifying uncertainty propagation in real-world systems is rooted in the high-dimensionality of the stochastic input and the frequent lack of explicit knowledge of its probability distribution. Traditional approaches show limitations for such problems, especially when the size of the training data is limited. To address these diculties, we have developed a general framework of constructing surrogate models on spaces of stochastic input with arbitrary probability measure irrespective of the mutual dependencies between individual components of the random inputs and the analytical form. The present Data-driven Sparsity-enhancing Rotation for Arbitrary Randomness (DSRAR) framework includes a data-driven construction of multivariate polynomial basis for arbitrary mutually dependent probability measure and a sparsity enhancement rotation procedure. This sparsity-enhancing rotation method was initially proposed in our previous work [1] for Gaussian density distributions, which may not be feasible for non-Gaussian distributions due to the loss of orthogonality after the rotation. To remedy such diculties, we developed a new data-driven approach to construct orthonormal polynomials for polynomials for arbitrary mutually dependent (amdP) randomness, ensuring the constructed basis maintains the orthogonality/near-orthogonality with respect to the density of the rotated random vector, where directly applying the regular polynomial chaos including arbitrary polynomial chaos (aPC) [2] shows limitations due to the assumption of the mutual independence between the components of the random inputs. The developed DSRAR framework leads to accurate recovery, with only limited training data, of a sparse representation of the target functions. The eectiveness of our method is demonstrated in challenging problems such as PDEs and realistic molecular systems within high-dimensional conformational space (O(10)) where the underlying density is implicitly represented by a large collection of sample data, as well as systems with explicitly given non-Gaussian probabilistic measures.

Lei, Huan↗
DOE OSTI2024

Operational Analytics Studies for ATLAS Distributed Computing: Data Popularity Forecast and Utilization of the WLCG Centers

Operational analytics is the direction of research related to the analysis of the current state of computing processes and the prediction of future states in order to anticipate imbalances and take timely measures to stabilize a complex system. There are two relevant areas in ATLAS Distributed Computing that are currently the focus of studies: user physics analysis including the forecast of popularity of data samples among users, and evaluating WLCG centers for their readiness to process user analysis payloads. Studying these areas is challenging due to the complexity involved, as it requires a comprehensive understanding of numerous boundary conditions typically found in large-scale distributed computing infrastructures. Forecasts of data popularity are problematic without the categorization of user tasks by their types (data transformation or physics analysis), which do not always appear on the surface but may induce noise, which introduces significant distortions for predictive analysis. Evaluating the WLCG resources by their analysis workloads is also a challenging task as it is necessary to find a balance between the workload of the resource, its performance, the waiting time for jobs on it, as well as the volume of jobs that it processes. This is especially difficult in a heterogeneous computing environment, where legacy resources are used along with modern high-performance machines. We will look at these areas of research in detail and discuss what tools and methods are used in our work, demonstrating results already obtained.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

The three-MM ultimate Mopra Milky Way Survey. I. Survey overview, Initial data releases, and first results

We describe a new mm-wave molecular-line mapping survey of the southern Galactic Plane and its first data releases. The Three-mm Ultimate Mopra Milky Way Survey (ThrUMMS) maps a 60° × 2° sector of our Galaxy’s fourth quadrant, using a combination of fast mapping techniques with the Mopra radio telescope, simultaneously in the J=1→0 lines of {sup 12}CO, {sup 13}CO, C{sup 18}O, and CN near 112 GHz at ∼arcminute and ∼0.3 km s{sup −1} resolution, with ∼2 K channel{sup −1} sensitivity for {sup 12}CO and ∼1 K channel{sup −1} for the other transitions. The calibrated data cubes from these observations are made available to the community after processing through our pipeline. Here, we describe the motivation for ThrUMMS, the development of new observing techniques for Mopra, and how these techniques were optimized to the objectives of the survey. We showcase some sample data products and describe the first science results on CO-isotopologue line ratios. These vary dramatically across the Galactic Plane, indicating a very wide range of optical depth and excitation conditions, from warm and translucent to cold and opaque. The population of cold clouds in particular have optical depths for {sup 12}CO easily exceeding 100. We derive a new, nonlinear conversion law from {sup 12}CO integrated intensity to column density, N{sub CO}∝I{sub CO}{sup 1.38}, which suggests that the molecular mass traced by CO in the Galactic disk may have been substantially underestimated. This further suggests that some global relationships in disk galaxies, such as star formation laws, may need to be recalibrated. The large ThrUMMS team is proceeding with several other science investigations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Performance of algorithms that reconstruct missing transverse momentum in $\sqrt{s}=8$ TeV proton–proton collisions in the ATLAS detector

The reconstruction and calibration algorithms used to calculate missing transverse momentum (E miss T ) with the ATLAS detector exploit energy deposits in the calorimeter and tracks reconstructed in the inner detector as well as the muon spectrometer. Various strategies are used to suppress effects arising from additional proton–proton interactions, called pileup, concurrent with the hard-scatter processes. Tracking information is used to distinguish contributions from the pileup interactions using their vertex separation along the beam axis. The performance of the E miss T reconstruction algorithms, especially with respect to the amount of pileup, is evaluated using data collected in proton–proton collisions at a centre-of-mass energy of 8 TeV during 2012, and results are shown for a data sample corresponding to an integrated luminosity of 20.3fb –1 . The simulation and modelling of E miss T in events containing a Z boson decaying to two charged leptons (electrons or muons) or a W boson decaying to a charged lepton and a neutrino are compared to data. The acceptance for different event topologies, with and without high transverse momentum neutrinos, is shown for a range of threshold criteria for E miss T , and estimates of the systematic uncertainties in the E miss T measurements are presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Simple Example of Backtest Overfitting (SEBO)

In the field of mathematical finance, a "backtest" is the usage of historical market data to assess the performance of a proposed trading strategy. It is a relatively simple matter for a present-day computer system to explore thousands, millions or even billions of variations of a proposed strategy, and pick the best performing variant as the "optimal" strategy "in sample" (i.e., on the input dataset). Unfortunately, such an "optimal" strategy often performs very poorly "out of sample" (i.e. on another dataset), because the parameters of the invest strategy have been oversit to the in-sample data, a situation known as "backtest overfitting". While the mathematics of backtest overfitting has been examined in several recent theoretical studies, here we pursue a more tangible analysis of this problem, in the form of an online simulator tool. Given a input random walk time series, the tool develops an "optimal" variant of a simple strategy by exhaustively exploring all integer parameter values among a handful of parameters. That "optimal" strategy is overfit, since by definition a random walk is unpredictable. Then the tool tests the resulting "optimal" strategy on a second random walk time series. In most runs using our online tool, the "optimal" strategy derived from the first time series performs poorly on the second time series, demonstrating how hard it is not to overfit a backtest. We offer this online tool, "Simple Example of Backtest Overfitting (SEBO)", to facilitate further research in this area.

Wu, K. John↗
DOE OSTI2012

2011 Annual Industrial Wastewater Reuse Report for the Idaho National Laboratory Site's Advanced Test Reactor Complex Cold Waste Pond

This report describes conditions, as required by the state of Idaho Industrial Wastewater Reuse Permit (LA 000161 01, Modification B), for the wastewater land application site at the Idaho National Laboratory Site's Advanced Test Reactor Complex Cold Waste Pond from November 1, 2010 through October 31, 2011. The report contains the following information: Facility and system description Permit required effluent monitoring data and loading rates Groundwater monitoring data Status of compliance activities Noncompliance and other issues Discussion of the facility's environmental impacts During the 2011 permit year, approximately 166 million gallons of wastewater were discharged to the Cold Waste Pond. This is well below the maximum annual permit limit of 375 million gallons. As shown by the groundwater sampling data, sulfate and total dissolved solids concentrations are highest near the Cold Waste Pond and decrease rapidly as the distance from the Cold Waste Pond increases. Although concentrations of sulfate and total dissolved solids are elevated near the Cold Waste Pond, both parameters were below the Ground Water Quality Rule Secondary Constituent Standards in the down gradient monitoring wells.

2011 Annual Industrial Wastewater Reuse Report↗