Search NASA⌕ Search

SEARCH · Search NASA

Results for “Sensitive data”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 433 records · Page 24

Constraining the neutron-matter equation of state with gravitational waves

We demonstrate how observations of gravitational waves from binary neutron star (BNS) mergers over the next few years can be combined with insights from nuclear physics to obtain useful constraints on the equation of state (EoS) of dense matter. In particular, the neutron-matter EoS between 1 and 2 times the nuclear saturation density $n_0$ ≈ 0.16 fm –3 can be constrained to within 20%, given the simulated data from about 15 merger events. Using Fisher information methods, we combine observational constraints from simulated BNS merger events drawn from various population models with independent measurements of the neutron star radii expected from x-ray astronomy [the Neutron Star Interior Composition Explorer observations in particular] to directly constrain nuclear physics parameters. To parametrize the nuclear EoS, we use a different approach, expanding from pure nuclear matter rather than from symmetric nuclear matter to make use of recent quantum Monte Carlo calculations. This method eschews the need to invoke the so-called parabolic approximation to extrapolate from symmetric nuclear matter, allowing us to directly constrain the neutron-matter EoS. Using a principal component analysis, we identify the combination of parameters most tightly constrained by observational data. We discuss sensitivity to various effects such as different component masses through population-model sensitivity, phase transitions in the core EoS, and large deviations from the central parameter values.

79 ASTRONOMY AND ASTROPHYSICS↗

Low-mass dark matter search with CDMSlite

The SuperCDMS experiment is designed to directly detect WIMPs (Weakly Interacting Massive Particles) that may constitute the dark matter in our galaxy. During its operation at the Soudan Underground Laboratory, germanium detectors were run in the CDMSlite (Cryogenic Dark Matter Search low ionization threshold experiment) mode to gather data sets with sensitivity specifically for WIMPs with masses ${<}10$ GeV/$c^2$. In this mode, a large detector-bias voltage is applied to amplify the phonon signals produced by drifting charges. This paper presents studies of the experimental noise and its effect on the achievable energy threshold, which is demonstrated to be as low as 56 eV$_{\text{ee}}$ (electron equivalent energy). The detector biasing configuration is described in detail, with analysis corrections for voltage variations to the level of a few percent. Detailed studies of the electric-field geometry, and the resulting successful development of a fiducial parameter, eliminate poorly measured events, yielding an energy resolution ranging from ${\sim}$9 eV$_{\text{ee}}$ at 0 keV to 101 eV$_{\text{ee}}$ at ${\sim}$10 keV$_{\text{ee}}$. New results are derived for astrophysical uncertainties relevant to the WIMP-search limits, specifically examining how they are affected by variations in the most probable WIMP velocity and the galactic escape velocity. These variations become more important for WIMP masses below 10 GeV/$c^2$. Finally, new limits on spin-dependent low-mass WIMP-nucleon interactions are derived, with new parameter space excluded for WIMP masses ${\lesssim}$3 GeV/$c^2$.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Multifidelity validation of digital surrogates using variable-density turbulent mixing models

In this study, ensembles of experimental data are presented and utilized to compare and validate two models used in the simulation of variable-density (Atwood = 0.22), compressible turbulent mixing. Though models of this kind (Reynolds averaged NavierStokes and large-eddy simulations) have been validated extensively with more canonical flows in previous studies, here the present approach offers novelty in the complexity of the geometry, the ensemble-based validation, and the uniformity of the computational framework on which the models are tested. Moreover, all experimental and computational tasks were completed by the authors which has led to a tightly coupled experimental configuration with its “digital twin.” The experimental divergent-shock-tube facility and its data acquisition methods are described and replicated in simulation space. A 2D Euler model which neglects the turbulent mixing at the interface is optimized to experimental data using a Gaussian process. This model then serves as the basis for both the 2D RANS and 3D LES studies that make comparisons to the mixing-layer data from the experiment. A relatively simple RANS model is shown to produce good agreement with experimental data only at late flow development times. The LES ensembles generally show good agreement with experimental data but display sensitivity to the characterization of initial conditions. Resolution-dependent behavior is also observed for certain higher-order statistics of interest. Overall, the LES model successfully captures the effects of divergent geometry, compressibility, and combined nonlinear instabilities inherent to the problem. The successful prediction of mixing width and its growth rate highlight the existence of three distinct regimes in the development of the instability, each with similarities to previously studied instabilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Local atomic structure of thin and ultrathin films via rapid high-energy X-ray total scattering at grazing incidence

Atomic pair distribution function (PDF) analysis is the most powerful technique to study the structure of condensed matter on the length scale from short- to long-range order. Today, the PDF approach is an integral part of research on amorphous, nanocrystalline and disordered materials from bulk to nanoparticle size. Thin films, however, demand specific experimental strategies for enhanced surface sensitivity and sophisticated data treatment to obtain high-quality PDF data. The approach described here is based on the surface high-energy X-ray diffraction technique applying photon energies above 60 keV at grazing incidence. In this way, reliable PDFs were extracted from films of thicknesses down to a few nanometres. Compared with recently published reports on thin-film PDF analysis from both transmission and grazing-incidence geometries, this work brought the minimum detectable film thickness down by about a factor of ten. Depending on the scattering power of the sample, the data acquisition on such ultrathin films can be completed within fractions of a second. Hence, the rapid-acquisition grazing-incidence PDF method is a major advancement in thin-film technology that opens unprecedented possibilities for in situ and operando PDF studies in complex sample environments. By uncovering how the structure of a layered material on a substrate evolves and transforms in terms of local and average ordering, this technique offers new opportunities for understanding processes such as nucleation, growth, morphology evolution, crystallization and the related kinetics on the atomic level and in real time.

36 MATERIALS SCIENCE↗

WinnowML: Stable feature selection for maximizing prediction accuracy of time-based system modeling

Online deep learning (ODL) has become an important methodology for modeling time-based performance of computer systems. An open problem is the intelligent selection of features from raw workload traces of computer systems. The best methods are overly sensitive to noisy data, causing frequent feature changes and re-training. Using all available features inflates training time and introduces model artifacts if some features should have been dropped. We present WinnowML, a method for automatically determining the most relevant feature subset for a predictive time-series model. WinnowML combines existing feature ranking algorithms and a history of each feature's ranking to iteratively rank a feature set to lower prediction error and maximize long term relevance. From this ranked feature set, the most relevant and stable subset is selected to train a model. Experimentally, we show how WinnowML can lower a model's mean absolute relative error up to 42% on average compared to the closest performing approach. Additionally, we lower the fluctuation in feature ranking and selection up to 65%. We also demonstrate how to combine WinnowML and a model search tool to provide improvements in performance of up to 14.5% when compared to using all the feature available.

Bel, Oceane MS↗

Coordinated Inverter Control to Increase Dynamic PV Hosting Capacity: A Real-Time Optimal Power Flow Approach

High penetrations of distributed photovoltaics (PV) could cause adverse grid impacts, such as voltage violations. The recent development in inverter technologies provides the opportunity to develop control systems to realize effective PV governance and thus to improve dynamic PV hosting capacity for distribution grids. In this paper, a novel distributed energy resource management system (DERMS) solution is proposed by adopting the real-time optimal power flow (OPF) approach for coordinated control of the distributed PV inverters. The proposed approach eliminates the dependence on load knowledge via measurement feedback correction, and it can be implemented in real time. One challenge is that the technique is sensitive to the data availability and integrity of voltage measurements. Therefore, a decentralized DERMS approach is developed by leveraging the concepts of state estimation. The framework and the effectiveness of the solution approach are numerically demonstrated on a real distribution feeder in Southern California.

14 SOLAR ENERGY↗

Modeling Imperfect Generator Behavior in Power System Operation Models

A key component in power system operations is the use of computer models to quickly study and analyze different operating conditions and futures in an efficient manner. The output of these models are sensitive to the data used in them as well as the assumptions made during their execution. One typical assumption is that generators and load assets perfectly follow operator control signals. While this is a valid simulation assumption, generators may not always accurately follow control signals. This imperfect response of generators could impact cost and reliability metrics. This paper proposes a generator model that capture this imperfect behavior and examines its impact on production costs and reliability metrics using a steady-state power system operations model. Preliminary analysis shows that while costs remain relatively unchanged, there could be significant impacts on reliability metrics.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Redox chemistry of plutonium and plutonium surrogates in vitrified nuclear wastes

Lanthanide borosilicate glasses containing Pu and the analog element, Ce, were subjects of an X-ray absorption spectroscopy investigation to quantify the +3/+4 ratio of the redox-sensitive element. The data show that the dominant oxidation states are +4 for Pu and +3 for Ce. The data also indicate that the reductive potential of glasses can be quantified, although allowances must be made for glass composition, from a solution chemistry method adapted to glass chemistry. These data can therefore be used to formulate glass compositions and processing schedules that lead to knowledge of the oxidation state of Pu in melts. Furthermore, the data show that Ce is a poor analog for Pu behavior in melt and that the suitability of surrogates can be evaluated by this method. The methods demonstrated in this paper can be used to estimate the oxidation states of a range of multi-valent elements as functions of temperature and composition with data from only a single redox couple.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Precision measurement and interpretation of inclusive W + W - Z /γ* production cross sections with the ATLAS detector

High-precision measurements by the ATLAS Collaboration are presented of inclusive W + →ℓ + νW + →ℓ - $\bar{v}$ and Z/γ*→ℓℓ (ℓ = e,μ) Drell-Yan production cross sections at the LHC. The data were collected in proton–proton collisions at s√=7 TeV with an integrated luminosity of 4.6 fb -1 . Differential W + W - cross sections are measured in a lepton pseudorapidity range |η ℓ | <2.5. Differential Z/γ* cross sections are measured as a function of the absolute dilepton rapidity, for |y ℓℓ |<3.6, for three intervals of dilepton mass, m ℓℓ , extending from 46 to 150 GeV. The integrated and differential electron- and muon-channel cross sections are combined and compared to theoretical predictions using recent sets of parton distribution functions. The data, together with the final inclusive e ± p scattering cross-section data from H1 and ZEUS, are interpreted in a next-to-next-to-leading-order QCD analysis, and a new set of parton distribution functions, ATLAS-epWZ16, is obtained. The ratio of strange-to-light sea-quark densities in the proton is determined more accurately than in previous determinations based on collider data only, and is established to be close to unity in the sensitivity range of the data. Lastly, a new measurement of the CKM matrix element |V cs | is also provided.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Addressing delayed case reporting in infectious disease forecast modeling

Infectious disease forecasting is of great interest to the public health community and policymakers, since forecasts can provide insight into disease dynamics in the near future and inform interventions. Due to delays in case reporting, however, forecasting models may often underestimate the current and future disease burden. In this paper, we propose a general framework for addressing reporting delay in disease forecasting efforts with the goal of improving forecasts. We propose strategies for leveraging either historical data on case reporting or external internet-based data to estimate the amount of reporting error. We then describe several approaches for adapting general forecasting pipelines to account for under- or over-reporting of cases. We apply these methods to address reporting delay in data on dengue fever cases in Puerto Rico from 1990 to 2009 and to reports of influenza-like illness (ILI) in the United States between 2010 and 2019. Through a simulation study, we compare method performance and evaluate robustness to assumption violations. Our results show that forecasting accuracy and prediction coverage almost always increase when correction methods are implemented to address reporting delay. Some of these methods required knowledge about the reporting error or high quality external data, which may not always be available. Provided alternatives include excluding recently-reported data and performing sensitivity analysis. This work provides intuition and guidance for handling delay in disease case reporting and may serve as a useful resource to inform practical infectious disease forecasting efforts.

59 BASIC BIOLOGICAL SCIENCES↗

Evaluation of Station Performance of the Idaho National Laboratory Seismic Monitoring Network Using Network Detection Thresholds

The Idaho National Laboratory (INL) Seismic Monitoring Network is located in eastern Idaho and monitors a portion of the intermountain seismic belt. It has been in place for 50 yr and has undergone several major changes, the most recent of which has been the transition to the Antelope real‐time acquisition system and the implementation of automatic phase picking algorithms to aid in analysis. This study discusses the efforts to evaluate the performance of the INL seismic monitoring network (and other surrounding stations) using the new real‐time acquisition system. The method outlined by Wilson et al. (2021) is used to develop an empirical relationship between the observability of local earthquakes as a function of magnitude and distance. This relationship is used to produce detection thresholds for Pwaves for all stations of interest. The INL seismic network has two main goals: monitor tectonic‐and volcanic‐related events and measure ground motions for input into seismic hazard analysis. Because of these two overall objectives, several seismic stations have been installed near critical facilities and, therefore, are not as quiet as stations that are used primarily for earthquake detection. This is reflected in their detection thresholds, which are much smaller for stations away from facilities. This study shows that the INL Seismic Monitoring Network is able to detect earthquakes near INL facilities with M L > 1.2, with redundancies built in to ensure this sensitivity even if data became unavailable from some stations. This study also shows “holes” in the monitoring network where the detection of smaller earthquakes is highly dependent on sparsely placed seismic stations. In conclusion, the results of this study will be used to govern plans for expansion of earthquake monitoring in Idaho and the surrounding region and to fine‐tune the detection thresholds for individual stations.

58 - GEOSCIENCES↗

SEARCH FOR THE STANDARD MODEL HIGGS BOSON IN ITS ASSOCIATED PRODUCTION WITH A W VECTOR BOSON IN pp COLLISIONS AT p s = 1:96TEV

In this dissertation, results from a search for the Standard Model (SM) Higgs boson is shown. The SM is the theoretical framework which describes particles of matter and force carrier gauge bosons. To solve the mass problem in the SM, the Higgs mechanism was introduced in 1963. The Higgs mechanism causes an electroweak symmetry breaking and a new massive scalar boson was postulated. This particle is the Higgs boson. A search for the Higgs boson has been ongoing at the Tevatron where protons and antiprotons were allowed to collide at a center-of-mass energy of 1:96 TeV. For a low mass Higgs, that is a Higgs with a mass lower than 135 GeV, the dominant decay mode is Higgs to a pair of b-quarks (H ! bb ). This work concentrated on a Higgs whose mass is in the range of 100 150 GeV, with a W vector boson produced with the Higgs boson. The final state chosen is the one which contains a lepton a neutrino and a pair of b-quarks. This study used data provided by the DZERO experiment. Results presented here are the outcome of analyzing 5:3 fb􀀀1 of data from RunII period. The analysis used different techniques to increase the sensitivity of the study. Data were subdivided based on lepton flavor, number of jets in sample, jets identified as b-jets and dates of collected data. A multivariate analysis technique based on boosted decision trees were used to separate signal from background processes, physical and instrumental. A good agreement between data and simulated events was observed. An observed (expected) upper limit of 4:5 (4:8) for a Higgs of mass 115 GeV was set on the ratio of the Higgs production to its decay branching ratio at the 95% confidence level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Enabling Predictive Simulation and UQ of Complex Multiphysics PDE Systems by the Development of Goal-Oriented Variational Sensitivity Analysis and a-Posteriori Error Estimation Methods

This project addressed the challenge of predictive computational analysis of strongly coupled, highly nonlinear multiphysics systems characterized by multiple physical phenomena that span a large range of length- and time-scales. Specifically, the project was focused on computational estimation of numerical error and sensitivity analysis of computational solutions with respect to variations in parameters and data. In addition, the project investigated the use of accurate computational estimates to guide efficient adaptive discretization. The project developed, analyzed and evaluated new variational adjoint-based techniques for integration, model, and data error estimation/control and sensitivity analysis, in evolutionary multiphysics multiscale simulations.

97 MATHEMATICS AND COMPUTING↗

Muon Neutrino Disappearance in NOvA with a Deep Convolutional Neural Network Classifier

The NuMI Off-axis Neutrino Appearance Experiment (NOvA) is designed to study neutrino oscillation in the NuMI (Neutrinos at the Main Injector) beam. NOvA observes neutrino oscillation using two detectors separated by a baseline of 810 km; a 14 kt Far Detector in Ash River, MN and a functionally identical 0.3 kt Near Detector at Fermilab. The experiment aims to provide new measurements of Δm 2 and θ23 and has potential to determine the neutrino mass hierarchy as well as observe CP violation in the neutrino sector. Essential to these analyses is the classification of neutrino interaction events in NOvA detectors. Raw detector output from NOvA is interpretable as a pair of images which provide orthogonal views of particle interactions. A recent advance in the field of computer vision is the advent of convolutional neural networks, which have delivered top results in the latest image recognition contests. This work presents an approach novel to particle physics analysis in which a convolutional neural network is used for classification of particle interactions. The approach has been demonstrated to improve the signal efficiency and purity of the event selection, and thus physics sensitivity. Early NOvA data has been analyzed (2.74×10 20 POT, 14 kt equivalent) to provide new best- fit measurements of sin 2 (θ23) = 0.43 (with a statistically-degenerate compliment near 0.60) and |Δm2 | = 2.48 × 10 -3 eV 2 .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

2020 State of the Science Report, Chapter 4: Risk to Marine Animals from Underwater Noise Generated by Marine Renewable Energy Devices

In all ocean environments, desirable locations for wave and tidal energy development have multiple natural sources of sound (e.g., waves, wind, and sediment transport), varying levels of anthropogenic and biological noise, and measurement quality challenges (e.g., flow-noise, self-noise). Many marine animals rely on sound for biological functions, including communication, social interaction, orientation, foraging, and evasion. The extent to which marine animals detect and produce sound varies by frequency (spanning roughly four decades from 10 Hz to 100 kHz) and is taxa-specific. Because of the relatively limited data available, hearing sensitivity is often generalized to taxonomic groups (e.g., cetaceans that have low-frequency hearing specialization). https://tethys.pnnl.gov/publications/state-of-the-science-2020-chapter-4-underwater-noise

54 ENVIRONMENTAL SCIENCES↗

FY21 Status Report: Probabilistic SCC Model for SNF Dry Storage Canisters

Stress corrosion cracking (SCC) is an important failure degradation mechanism for storage of spent nuclear fuel. Since 2014, Sandia National Laboratories has been developing a probabilistic methodology for predicting SCC. The model is intended to provide qualitative assessment of data needs, model sensitivities, and future model development. In fiscal year 2021, improvement of the SCC model focused on the salt deposition, maximum pit size, and crack growth rate models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Study of a Proposed fissionTPC Measurement of 233 U(n,f)/ 235 U(n,f) Cross Section Ratio

A review of the available 233 U( n, f )/ 235 U( n, f ) cross section ratio data compared to the ENDF evaluation in the fast neutron energy range, 0.1–20 MeV, shows that discrepancies exist between some of the various measurements and the evaluation. The discrepancies vary and a function of incident neutron energy and range between 1–5%. In this document we review two potential options for performing new measurements of the cross section ratio to potentially resolve these discrepancies. The two options are compared and contrasted in terms of measurement accuracy and cost. The first option would utilize the fissionTPC, which was designed specifically to achieve measurement uncertainties of better than 1% to resolve a similar data–evaluation discrepancy in the 239 Pu( n, f ) cross section. While this would seem to be an ideal option in this case also, there are challenges. The fissionTPC is a complex instrument and the cost of maintenance and operations are significant. Furthermore, some of the fissionTPC equipment is nearing the end of its useful life which presents a risk to completion of a measurement campaign. The second option is to use a dual-fission chamber, which is the more traditional approach to these types of measurements. The cost is estimated to be about half that of a fissionTPC measurement, while the much simpler design of the detector reduces overall risk. The trade-off is the measurement uncertainty, which would be on order of 1–3% with a careful measurement and analysis. This uncertainty however may not be good enough to fully resolve the discrepancies. The objective of a new measurement would be the improvement in the ENDF evaluation with the end goal of improving the accuracy of models and simulations at the end of the nuclear data pipeline. An understanding of the sensitivity of these models to the data uncertainties would help guide the choice of measurement techniques.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗