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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A Multi-Branch Decoder Network Approach to Adaptive Temporal Data Selection and Reconstruction for Big Scientific Simulation Data

A key challenge in scientific simulation is that the simulation outputs often require intensive I/O and storage space to store the results for effective post hoc analysis. This article focuses on a quality-aware adaptive temporal data selection and reconstruction problem where the goal is to adaptively select simulation data samples at certain key timesteps in situ and reconstruct the discarded samples with quality assurance during post hoc analysis. This problem is motivated by the limitation of current solutions that a significant amount of simulation data samples are either discarded or aggregated during the sampling process, leading to inaccurate modeling of the simulated phenomena. Two unique challenges exist: 1) the sampling decisions have to be made in situ and adapted to the dynamics of the complex scientific simulation data; 2) the reconstruction error must be strictly bounded to meet the application requirement. To address the above challenges, we develop DeepSample , an error-controlled convolutional neural network framework, that jointly integrates a set of coherent multi-branch deep decoders to effectively reconstruct the simulation data with rigorous quality assurance. The results on two real-world scientific simulation applications show that DeepSample significantly outperforms other state-of-the-art methods on both sampling efficiency and reconstructed simulation data quality.

Zhang, Yang↗
DOE OSTI2015

Prospects of charmonium studies in the Belle-II experiment

TheBelle-II experiment at the SuperKEKB super-B factorywill begin data acquisition in 2016, the expected integrated luminosity being 50 ab{sup -1}. A statistical data sample of record volume 50 times as large as that of the statistical data sample accumulated earlier at the Belle detector will make it possible to measure precisely the parameters of new exotic states discovered recently at B factories and to clarify the origin of these states.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Site-level Foliar C, N, delta13C data from samples collected during field survey associated with NEON AOP survey, East River, CO 2018

Carbon (C) and nitrogen (N) weight percent concentrations were obtained from the bulk foliar samples collected across East River, Washington Gulch, Slate River, and Coal Creek watersheds in Gunnison, Colorado during the summer of 2018. These samples were collected from sun-lit leaves of meadow, shrub, and tree vegetation types within 72 hours of the National Ecological Observatory Network Airborne Observation Platform (NEON AOP) hyperspectral survey. These samples were dried and then run on an elemental analyzer coupled to a mass spectrometer for C and N concentrations and delta13C. The intention of these data were to provide ground truth data to develop foliar nutrient models across the imaging spectroscopy domain. Additional associated site metadata and vegetation fractional cover information can be found in the associated data releases (DOI: 10.15485/1618130). Here we provide site level C, N, and delta 13C data in the CN_Results_Foliar.csv. All of these samples were also registered with IGSN codes, and the details from that registration with metadata for the samples is included in foliar_sample_igsn_metadata.csv.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1997

Accelerometer Data Analysis and Presentation Techniques

The NASA Lewis Research Center's Principal Investigator Microgravity Services project analyzes Orbital Acceleration Research Experiment and Space Acceleration Measurement System data for principal investigators of microgravity experiments. Principal investigators need a thorough understanding of data analysis techniques so that they can request appropriate analyses to best interpret accelerometer data. Accelerometer data sampling and filtering is introduced along with the related topics of resolution and aliasing. Specific information about the Orbital Acceleration Research Experiment and Space Acceleration Measurement System data sampling and filtering is given. Time domain data analysis techniques are discussed and example environment interpretations are made using plots of acceleration versus time, interval average acceleration versus time, interval root-mean-square acceleration versus time, trimmean acceleration versus time, quasi-steady three dimensional histograms, and prediction of quasi-steady levels at different locations. An introduction to Fourier transform theory and windowing is provided along with specific analysis techniques and data interpretations. The frequency domain analyses discussed are power spectral density versus frequency, cumulative root-mean-square acceleration versus frequency, root-mean-square acceleration versus frequency, one-third octave band root-mean-square acceleration versus frequency, and power spectral density versus frequency versus time (spectrogram). Instructions for accessing NASA Lewis Research Center accelerometer data and related information using the internet are provided.

Rogers, Melissa J. B.↗
NASA NTRS1988

Multirate digital control system design

Methods for multirate digital control system design are discussed. A simple method for sampling rate selection based on control bandwidths is proposed. Methods for generating a discrete-time state model of a sampled-data plant and a discrete-time equivalent to an analog cost function for a sampled-data plant are described. The succesive loop closures and linear quadratic Gaussian synthesis methods are reviewed, and a constrained optimization synthesis method is introduced. The proposed sampling rate selection, discretization, and synthesis methods are applied to two example design problems. Multirate and single-rate compensators synthesized by the different methods are compared, based on closed-loop responses, with compensators having the same real-time computation load.

Berg, Martin C.↗
DOE OSTI2015

Study of Z production in PbPb and pp collisions at $ \sqrt{s_{\mathrm{NN}}}=2.76 $ TeV in the dimuon and dielectron decay channels

We found that the production of Z bosons is studied in the dimuon and dielectron decay channels in PbPb and pp collisions at √s NN =2.76 TeV, using data collected by the CMS experiment at the LHC. The PbPb data sample corresponds to an integrated luminosity of about 166 μb -1 , while the pp data sample collected in 2013 at the same nucleon-nucleon centre-of-mass energy has an integrated luminosity of 5.4 pb -1 . The Z boson yield is measured as a function of rapidity, transverse momentum, and collision centrality. The ratio of PbPb to pp yields, scaled by the number of inelastic nucleon-nucleon collisions, is found to be 1.06 ± 0.05 (stat) ± 0.08 (syst) in the dimuon channel and 1.02 ± 0.08 (stat) ± 0.15 (syst) in the dielectron channel, for centrality-integrated Z boson production. Finally, this binary collision scaling is seen to hold in the entire kinematic region studied, as expected for a colourless probe that is unaffected by the hot and dense QCD medium produced in heavy ion collisions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Machine learning at the energy and intensity frontiers of particle physics

Our knowledge of the fundamental particles of nature and their interactions is summarized by the standard model of particle physics. Advancing our understanding in this field has required experiments that operate at ever higher energies and intensities, which produce extremely large and information-rich data samples. The use of machine-learning techniques is revolutionizing how we interpret these data samples, greatly increasing the discovery potential of present and future experiments. Here we summarize the challenges and opportunities that come with the use of machine learning at the frontiers of particle physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Measurement of e + e - → $D\bar{D}$ cross sections at the ψ(3770) resonance

Here, we report new measurements of the cross sections for the production of $D\bar{D}$ final states at the ψ(3770) resonance. Our data sample consists of an integrated luminosity of 2.93 fb -1 of e + e - annihilation data produced by the BEPCII collider and collected and analyzed with the BESIII detector. We exclusively reconstruct three D 0 and six D + hadronic decay modes and use the ratio of the yield of fully reconstructed $D\bar{D}$ events ("double tags") to the yield of all reconstructed D or $\bar{D}$ mesons ("single tags") to determine the number of D 0 $\bar{D}$ 0 and D + D - events, benefiting from the cancellation of many systematic uncertainties. Combining these yields with an independent determination of the integrated luminosity of the data sample, we find the cross sections to be σ(e + e - → D 0 $\bar{D}$ 0 ) nb and σ(e + e - → D + D - ) = (2.830 ± 0.011 ± 0.026) nb, where the uncertainties are statistical and systematic, respectively.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Evidence for the decay B 0 → η π 0

In this work, we report a search for the charmless hadronic decay B 0 → η π 0 with a data sample corresponding to an integrated luminosity of 694 fb - 1 containing 753 × 1 0 6 B B ¯ pairs. The data were collected by the Belle experiment running on the Υ ( 4 S ) resonance at the KEKB e + e - collider. We measure a branching fraction B ( B 0 → η π 0 ) = ( 4. 1 - 1.5 - 0.7 + 1.7 + 0.5 ) × 1 0 - 7 , where the first uncertainty is statistical and the second is systematic. Our measurement gives an upper limit of B ( B 0 → η π 0 ) < 6.5 × 1 0 - 7 at 90% confidence level. Finally, the signal has a significance of 3.0 standard deviations and constitutes the first evidence for this decay mode.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1980

A Fourier transform with speed improvements for microprocessor applications

A fast Fourier transform algorithm for the RCA 1802microprocessor was developed for spacecraft instrument applications. The computations were tailored for the restrictions an eight bit machine imposes. The algorithm incorporates some aspects of Walsh function sequency to improve operational speed. This method uses a register to add a value proportional to the period of the band being processed before each computation is to be considered. If the result overflows into the DF register, the data sample is used in computation; otherwise computation is skipped. This operation is repeated for each of the 64 data samples. This technique is used for both sine and cosine portions of the computation. The processing uses eight bit data, but because of the many computations that can increase the size of the coefficient, floating point form is used. A method to reduce the alias problem in the lower bands is also described.

Lokerson, D. C.↗
NASA NTRS2011

Sampling Theorem in Terms of the Bandwidth and Sampling Interval

An approach has been developed for interpolating non-uniformly sampled data, with applications in signal and image reconstruction. This innovation generalizes the Whittaker-Shannon sampling theorem by emphasizing two assumptions explicitly (definition of a band-limited function and construction by periodic extension). The Whittaker- Shannon sampling theorem is thus expressed in terms of two fundamental length scales that are derived from these assumptions. The result is more general than what is usually reported, and contains the Whittaker- Shannon form as a special case corresponding to Nyquist-sampled data. The approach also shows that the preferred basis set for interpolation is found by varying the frequency component of the basis functions in an optimal way.

Dean, Bruce H.↗
DOE OSTI2022

2021 NIRT Mini Drill (After Action Report)

During the summer and fall of 2021, several functional area drills were held that focused on exercising Consequence Management’s (CM) ability to extract and use data from RadResponder for the purpose of answering intermediate-phase questions presented as technical inject requests for information (RFI) in Sandia National Laboratories (SNL) Consequence Management Operational System (COSMOS) software. The scenario chosen was that of Northern Lights 2016 (NL16) which was a large-scale nuclear power plant (NPP) release exercise in the state of Minnesota. The NL16 data was extracted from the Radiological Assessment and Monitoring System (RAMS) event where it was created and was reformatted for implanting to a new RadResponder event. Next, the beta-version of a laboratory sample data simulator was used to generate more sample data that was injected to the event. Five “mini-drills” were devised with each prompt defined by a data-based need. For each drill, a team of assessment and NARAC scientists worked the problem using the drill prompt and the available data in RadResponder. The teams held a kickoff meeting, had several days to work the problem, and then reported their results as well as observations in a hotwash. Several areas for improvement in both the software and process were identified during the course of these drills. This report will document the process of addressing each RFI and the discovered gaps in both software capability and methodology so that they can be considered for future development and investment by the CM and NIRT programs.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2025

Summary of Analytical Services for the Hanford Site Radionuclide NESHAP Program

This document is a summary of the point source analytical requirements used to demonstrate compliance for the Department of Energy (DOE) Hanford Site operations with 40 Code of Federal Regulations (CFR) Part 61, “National Emission Standards for Hazardous Air Pollutants,” (NESHAP) Subpart H, “National Emission Standards for Emissions of Radionuclides Other Than Radon From Department of Energy Facilities,” and the Washington Administrative Code (WAC) 246-247, “Radiation Protection – Air Emissions.” This reference collects information from multiple source documents and is not intended to create, supersede, replace or over-ride any existing contractual, DOE, federal or state statutes, regulations, compliance agreements, orders, permits, licenses or other requirements. The requirement source document governs where any difference may exist. The Hanford Mission Integration Solutions (HMIS) Environmental organization has been contracted by DOE to manage and report data collected from the sampling and monitoring of radioactive air emissions point sources, colloquially called stacks. The Environmental organization coordinates the analyses and reporting of samples collected at various facilities across the Hanford Site. These facilities operate approximately 52 stacks that require sampling, monitoring or estimating radioactive air emissions. The stacks are operated by Bechtel National, Inc. (BNI), Central Plateau Cleanup Company (CPCCo), Hanford Tank Waste Operations & Closure (H2C), Hanford Laboratory Management and Integration (HLMI), and Pacific Northwest National Laboratory (PNNL). Stack samples from CPCCo, HLMI and H2C facilities are collected by the operating contractor staff, delivered to HMIS, and then shipped to an offsite contracted laboratory for analyses. The field and laboratory sample data uploaded into the Sample Management and Analytical Results Tracking (SMART) database are used to calculate sample volumes and concentrations. Sample concentrations are evaluated for compliance with federal and state regulations, permits, and license requirements. The SMART database also calculates total curies released for sampled point sources and stacks. Point source effluent concentrations and releases are published annually in publicly available reports. The BNI and PNNL operate several DOE-Hanford Field Office (HFO) stacks subject to the requirements of 40 CFR 61, Subpart H and WAC 246-247. The concentrations, curies released and dose modeling evaluation for these stacks are included in the DOE-HFO annual radionuclide NESHAP report. The sample collection, analyses and emissions estimates for these stacks are outside the scope of HMIS contracted responsibilities and not addressed further in this document.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1980

A hill-sliding strategy for initialization of Gaussian clusters in the multidimensional space

A hill sliding technique was devised to extract Gaussian clusters from the multivariate probability density estimate of sample data for the first step of iterative unsupervised classification. Each cluster was assumed to posses a unimodal normal distribution. A clustering function proposed distinguished elements of a cluster under formation from the rest in the feature space. Initial clusters were extracted one by one according to the hill sliding tactics. A dimensionless cluster compactness parameter was proposed as a universal measure of cluster goodness and used satisfactorily in test runs with LANDSAT multispectral scanner data. The normalized divergence, defined by the cluster divergence divided by the entropy of the entire sample data, was utilized as a general separability measure between clusters. An overall clustering objective function was set forth in terms of cluster covariance matrices, from which the cluster compactness measure could be deduced. Minimal improvement of initial data partitioning was evaluated by this objective function in eliminating scattered sparse data points. The hill sliding clustering technique developed herein has the potential applicability to decomposition any multivariate mixture distribution into a number of unimodal distributions when an appropriate distribution function to the data set is employed.

Park, J. K.↗
DOE OSTI2025

Generative learning of densities on manifolds

A generative modeling framework is proposed that combines diffusion models and manifold learning to efficiently sample data densities on manifolds. The approach utilizes Diffusion Maps to uncover possible low-dimensional underlying (latent) spaces in the high-dimensional data (ambient) space. Two approaches for sampling from the latent data density are described. The first is a score-based diffusion model, which is trained to map a standard normal distribution to the latent data distribution using a neural network. The second one involves solving an Itô stochastic differential equation in the latent space. Additional realizations of the data are generated by lifting the samples back to the ambient space using Double Diffusion Maps , a recently introduced technique typically employed in studying dynamical system reduction; here the focus lies in sampling densities rather than system dynamics. The proposed approaches enable sampling high dimensional data densities restricted to low-dimensional, a priori unknown manifolds. The efficacy of the proposed framework is demonstrated through a benchmark problem and a material with multiscale structure.

Double diffusion maps↗
DOE OSTI2017

Evaluation of a Class of Simple and Effective Uncertainty Methods for Sparse Samples of Random Variables and Functions

When very few samples of a random quantity are available from a source distribution of unknown shape, it is usually not possible to accurately infer the exact distribution from which the data samples come. Under-estimation of important quantities such as response variance and failure probabilities can result. For many engineering purposes, including design and risk analysis, we attempt to avoid under-estimation with a strategy to conservatively estimate (bound) these types of quantities -- without being overly conservative -- when only a few samples of a random quantity are available from model predictions or replicate experiments. This report examines a class of related sparse-data uncertainty representation and inference approaches that are relatively simple, inexpensive, and effective. Tradeoffs between the methods' conservatism, reliability, and risk versus number of data samples (cost) are quantified with multi-attribute metrics use d to assess method performance for conservative estimation of two representative quantities: central 95% of response; and 10 -4 probability of exceeding a response threshold in a tail of the distribution. Each method's performance is characterized with 10,000 random trials on a large number of diverse and challenging distributions. The best method and number of samples to use in a given circumstance depends on the uncertainty quantity to be estimated, the PDF character, and the desired reliability of bounding the true value. On the basis of this large data base and study, a strategy is proposed for selecting the method and number of samples for attaining reasonable credibility levels in bounding these types of quantities when sparse samples of random variables or functions are available from experiments or simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

PPI DataHub Project Data Package: S. elongatus PCC 7942 Limited Proteolysis and Thermal Proteome Profiling Structural Proteomics (JM-PB-DP3)

The purpose of this experiment was to investigate structural alterations in proteins involved in central carbon metabolism and photosynthetic electron transfer pathways in Synechococcus elongatus PCC 7942. Sample data was obtained from S. elongatus cell lysates using three complementary mass spectrometry (MS) techniques using limited proteolysis (LiP-MS), thermal proteome profiling (TPP-MS), and redox enrichment (Redox-MS) in evaluating alterations solvent accessibility and structural stability caused by light perturbation at the molecular level. Experimentally processed sample data for LiP and TPP proteomic datasets were derived from the same cell culture stock, prepared simultaneously in parallel, and acquired by mass spectrometry. Processed datasets are openly accessible from the download button and contain secondary processed proteomic results files, computed outputs, and supporting metadata materials. Experimental samples processed for LiP-MS label-free quantification (LFQ) or TPP-MS tandem mass tag (TMT) 10-plex were acquired using a Q-Exactive HF-X mass spectrometer and processed/compiled using either MSGF+ (v2024.03.26) or ​​​​PlexedPiper for proteome evaluation. Additional software supporting downstream proteomic analysis include FragPipe (v.4.0), MSFragger (v.22.1), and an adapted Microbial Isolate LiP Analysis Workflow (located at Zenodo). Processed proteomic data downloads include a sample naming key, normalized quantification results files, and processed protein annotated abundance files.

59 BASIC BIOLOGICAL SCIENCES↗