Numerical operator method
Algebraic solutions of difference equations - stability of sampled-data control systems - numerical method for determining transients in electric systems excited by complex signals
ELECTRIC NETWORK↗
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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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Inclusive and differential cross-sections for dilepton $t\overline{t}$ production measured in $\sqrt{s}$ = 13 TeV pp collisions with the ATLAS detector
Differential and double-differential distributions of kinematic variables of leptons from decays of top-quark pairs ($t\bar{t}$) are measured using the full LHC Run 2 data sample collected with the ATLAS detector. The data were collected at a pp collision energy of $\sqrt{s}$ = 13 TeV and correspond to an integrated luminosity of 140 fb –1 . The measurements use events containing an oppositely charged e μ pair and b-tagged jets. The results are compared with predictions from several Monte Carlo generators. While no prediction is found to be consistent with all distributions, a better agreement with measurements of the lepton p T distributions is obtained by reweighting the $t\bar{t}$ sample so as to reproduce the top-quark p T distribution from an NNLO calculation. The inclusive top-quark pair production cross-section is measured as well, both in a fiducial region and in the full phase-space. The total inclusive cross-section is found to be $σ_{t\bar{t}}=$ 829 ± 1 (stat) ± 13 (syst) ± 8 (lumi) ± 2 (beam) pb, where the uncertainties are due to statistics, systematic effects, the integrated luminosity and the beam energy. This is in excellent agreement with the theoretical expectation.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Hanford SMART System: Calculation of Radionuclide Emissions, Ambient Air Concentrations and Error Propagation (Final Report)
This document, authored by Radiological Assessment Corporation (RAC), details the calculations used to convert laboratory radiological analytical sample data and field measurement data for both ambient air samplers and stack air samples to concentration values with associated uncertainty. The RAC supported an effort by Mission Support Alliance (MSA) to replace the Automated Bar Coding of All Samples at Hanford (ABCASH) and Environmental Release Summary (ERS) database software with a commercial off-the-shelf (COTS) data management software system. The ABCASH and ERS databases were not compatible with the Hanford system standards Windows 10 Operating System deployed in calendar year 2018. The replacement software, Sample Management and Analytical Results Tracking (SMART), is used for environmental data collection, analyses, and regulatory reporting for the Hanford Environmental Surveillance and Effluent Monitoring programs.
54 ENVIRONMENTAL SCIENCES↗
Vibration-Based Sensor Design: A Grey-Box Approach
Knowledge of the internal structure of an object or device under investigation proceeds from the basic idea of constructing its dynamic behavioral relations governed by a set of differential/algebraic equations that characterize its response. These equations can be partial differential equations leading to finite element or finite difference relations requiring a complex numerical solution on a super computer or ordinary differential equations requiring sophisticated numerical integration techniques to obtain the desired solution. Discrete dynamic systems evolving from digitized data acquisition are typically captured by sampled-data (continuous-to-discrete) representations characterized by a set of difference equations specifying the underlying system dynamics. In any case, with a mathematical description in hand, Grey-Box modeling techniques have evolved, concerned with the estimation of model parameters embedded in a prescribed set of equations (the system) governing its behavior, while capturing the underlying physical phenomenology of the problem at hand.
97 MATHEMATICS AND COMPUTING↗
VLSI system for synthetic aperture radar /SAR/ processing
The paper discusses an SAR problem based on actual requirements set forth by NASA for a spaceborne application. The requirements for high resolution and high quality necessitate a data sampling rate of 7.5 MHz. For each data value 1,025 4-bit complex multiply + add operations are needed, which is equivalent to 7.7 GHz complex multiply + add operation rate. Since this rate is much too high for general purpose systems, a special-purpose device was sought. This paper discusses two architectures based on parallel operation of 1,025 identical cells, each of which is capable of performing arithmetic, storage, and several control operations. The operation rate in each device is only 7.5 MHz, which is quite manageable, especially with the help of a substantial degree of pipelining. A computational-mathematical analysis is used as a primary tool for evaluating the design and some of its tradeoffs. Two different approaches are discussed and compared; both are based on having 1,025 identical cells working in parallel, but differ in their dual approaches to the flow of data.
Cohen, D.↗
Sample selection in foreign similarity regions for multicrop experiments
The selection of sample segments in the U.S. foreign similarity regions for development of proportion estimation procedures and error modeling for Argentina, Australia, Brazil, and USSR in AgRISTARS is described. Each sample was chosen to be similar in crop mix to the corresponding indicator region sample. Data sets, methods of selection, and resulting samples are discussed.
Malin, J. T.↗
The large impact process inferred from the geology of lunar multiring basins
The nature of the impact process has been inferred through the study of the geology of a wide variety of impact crater types and sizes. Some of the largest craters known are the multiring basins found in ancient terrains of the terrestrial planets. Of these features, those found on the Moon possess the most extensive and diverse data coverage, including morphological, geochemical, geophysical, and sample data. The study of the geology of lunar basins over the past 10 years has given us a rudimentary understanding of how these large structures have formed and evolved. The topics covered include basin morphology, basin ejecta, basin excavation, and basin ring formation.
Spudis, Paul D.↗
A Control Chart Approach for Representing and Mining Data Streams with Shape Based Similarity
The mining of data streams for online condition monitoring is a challenging task in several domains including (electric) power grid system, intelligent manufacturing, and consumer science. Considering a power grid application in which thousands of sensors, called the phasor measurement units, are deployed on the power grid network to continuously collect streams of digital data for real-time situational awareness and system management. Depending on design, each sensor could stream between ten and sixty data samples per second. The myriad of sensory data captured could convey deeper insights about sequence of events in real-time and before major damages are done. However, the timely processing and analysis of these high-velocity and high-volume data streams is a challenge. Hence, a new data processing and transformation approach, based on the concept of control charts, for representing sequence of data streams from sensors is proposed. In addition, an application of the proposed approach for enhancing data mining tasks such as clustering using real-world power grid data streams is presented. The results indicate that the proposed approach is very efficient for data streams storage and manipulation.
big data↗
NOvA Recent Results with Neutrino+Antineutrino Data
NOvA is a long-baseline neutrino oscillation experiment using Fermilab's 700 kW NuMI muon neutrino beam. Two functionally identical scintillator detectors are placed off the beam axis, separated by 810 km oscillation baseline. Both detectors have high active material fractions and are finely segmented allowing for precise identification and analysis of neutrino interactions. By observing both the disappearance of muon (anti)neutrinos and appearance of electron (anti)neutrinos in the beam, NOvA can impose constraints on the yet undetermined parameters of neutrino oscillation phenomenon, such as the neutrino mass ordering, CP violation and the octant of the large mixing angle. NOvA also studies neutral-current neutrino interactions, thus extending its scope beyond the standard three-flavor paradigm. This paper presents the latest NOvA results with the complete neutrino data sample up to date and first antineutrino data collected since February 2017.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Femtosecond Laser Ablation Multicollector ICPMS Analysis of Uranium Isotopes in NIST Glass
We have utilized femtosecond laser ablation coupled to multi-collector inductively couple plasma mass spectrometry to measure the uranium isotopic content of NIST 61x (x=0,2,4,6) glasses. The uranium content of these glasses is a linear two-component mixing between isotopically natural uranium and the isotopically depleted spike used in preparing the glasses. Laser ablation results match extremely well, generally within a few ppm, with solution analysis following sample dissolution and chemical separation. In addition to isotopic data, sample utilization efficiency measurements indicate that over 1% of ablated uranium atoms reach a mass spectrometer detector, making this technique extremely efficient. Laser sampling also allows for spatial analysis and our data indicate that rare uranium concentration inhomogeneities exist in NIST 616 glass.
Duffin, Andrew M.↗
Developing an Air Quality Index for Microgravity Indoor Environments/Space Missions
Indoor pollution sources (on Earth) that release gases or particles into the air are the primary cause of air quality problems in indoor environments. The development of an adequate tool to understand pollution levels in a certain location is of high importance. This tool must be able to inform about the levels of pollution in a simple and understandable way but also, used to take a series of predetermined measures to protect the health of the exposed population. One of the most useful and up to date approaches for characterizing air pollution is the Air Quality Index (AQI). It is an easily-calculated powerful data-driven tool, that summarizes a complex phenomenon, such as air pollution, in straightforward indicators. The AQI system has been developed in different countries around the world, mainly for outdoor environments, based on the results of risk assessments, epidemiology studies, and current local air pollution regulations and standards.Air quality in microgravity indoor environments is of fundamental importance to crew health, with concerns encompassing both gaseous contaminants and particulate matter. Although the concentration of gases in the microgravity indoor environment is well studied, aerosols remain one of the major pollutants that affect air quality and has reported adverse health effects and hasn't been reported under these unique conditions. Earth-based AQIs can't be extrapolated to microgravity indoor environments due to different aerosol characteristics and altered lung deposition in low gravity.Concurrent with the aerosol-focused AQI effort, we assess and document how the process would apply for combining particles & gases into a composite index, with the ability to query each AQI independently. All this information can be combined in a spacecraft-specific AQI for future space missions and habitats. The objective of this work are to determine what areas of expertise will contribute, what research and data will be required, and explore the scope of effort needed to formulate a spacecraft AQI in addition to analyzing ISS aerosol sampling data and incorporate results from both aerosol Sampling experiments (the only relevant data available from space).
Sorek-Hamer, Meytar↗
Predicting critical heat flux with uncertainty quantification and domain generalization using conditional variational autoencoders and deep neural networks
Deep generative models (DGMs) can generate synthetic data samples that closely resemble the original dataset, addressing data scarcity. In this work, we developed a conditional variational autoencoder (CVAE) to augment critical heat flux (CHF) data used for the 2006 Groeneveld lookup table. To compare with traditional methods, a fine-tuned deep neural network (DNN) regression model was evaluated on the same dataset. Both models achieved small mean absolute relative errors, with the CVAE showing more favorable results. Uncertainty quantification (UQ) was performed using repeated CVAE sampling and DNN ensembling. The DNN ensemble improved performance over the baseline, while the CVAE maintained consistent results with less variability and higher confidence. Both models achieved small errors inside and outside the training domain, with slightly larger errors outside. Altogether, the CVAE performed better than the DNN in predicting CHF and exhibited better uncertainty behavior.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Machine Learning Toolkit for Extreme Scale
Support Vector Machines (SVM) is a popular machine learning technique, which has been applied to a wide range of domains such as science, finance, and social networks for supervised learning. MaTEx undertakes the challenge of designing a scalable parallel SVM training algorithm for large scale systems, which includes commodity multi-core machines, tightly connected supercomputers and cloud computing systems. Several techniques are proposed for improved speed and memory space usage including adaptive and aggressive elimination of samples for faster convergence , and sparse format representation of data samples. Several heuristics for earliest possible to lazy elimination of non-contributing samples are considered in MaTEx. In many cases, where an early sample elimination might result in a false positive, low overhead mechanisms for reconstruction of key data structures are proposed. The proposed algorithm and heuristics are implemented and evaluated on various publicly available datasets
Source record↗
Machine Learning Toolkit for Extreme Scale
Support Vector Machines (SVM) is a popular machine learning technique, which has been applied to a wide range of domains such as science, finance, and social networks for supervised learning. MaTEx undertakes the challenge of designing a scalable parallel SVM training algorithm for large scale systems, which includes commodity multi-core machines, tightly connected supercomputers and cloud computing systems. Several techniques are proposed for improved speed and memory space usage including adaptive and aggressive elimination of samples for faster convergence , and sparse format representation of data samples. Several heuristics for earliest possible to lazy elimination of non-contributing samples are considered in MaTEx. In many cases, where an early sample elimination might result in a false positive, low overhead mechanisms for reconstruction of key data structures are proposed. The proposed algorithm and heuristics are implemented and evaluated on various publicly available datasets
Source record↗
Measurement of branching fraction and search for C P violation in B → ϕ ϕ K
Not Available
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Amplitude analysis of B + → J / ψ Φ K + decays
The first full amplitude analysis of B + →J/ψΦK + with J/ψ→μ + μ – , Φ→K + K – decays is performed with a data sample of 3 fb –1 of pp collision data collected at √s = 7 and 8 TeV with the LHCb detector. The data cannot be described by a model that contains only excited kaon states decaying into ΦK + , and four J/ψΦ structures are observed, each with significance over 5 standard deviations. The quantum numbers of these structures are determined with significance of at least 4 standard deviations. The lightest has mass consistent with, but width much larger than, previous measurements of the claimed X(4140) state. The model includes significant contributions from a number of expected kaon excitations, including the first observation of the K*(1680) + →ΦK + transition.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Observation of J / ψ ϕ Structures Consistent with Exotic States from Amplitude Analysis of B + → J / ψ ϕ K + Decays
The first full amplitude analysis of B + → J/ψϕK + with J/ψ → μ + μ - , ϕ → K + K - decays is performed with a data sample of 3 fb -1 of pp collision data collected at $\sqrt{s}$ =7 and 8 TeV with the LHCb detector. The data cannot be described by a model that contains only excited kaon states decaying into ϕK + , and four J/ψϕ structures are observed, each with significance over 5 standard deviations. The quantum numbers of these structures are determined with significance of at least 4 standard deviations. The lightest has mass consistent with, but width much larger than, previous measurements of the claimed X(4140) state.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
Design of an Open Smart Energy Gateway for Smart Meter Data Management
With the widespread deployment of electronic interval meters, commonly known as smart meters, came the promise of real-time data on electric energy consumption. Recognizing an opportunity to provide consumers access to their near real-time energy consumption data directly from their installed smart meter, we designed a mechanism for capturing those data for consumer use via an open smart energy gateway (OpenSEG). By design, OpenSEG provides a clearly defined boundary for equipment and data ownership. OpenSEG is an open-source data management platform to enable better data management of smart meter data. Effectively, it is an information architecture designed to work with the ZigBee Smart Energy Profile 1.x (SEP 1.x). It was specifically designed to reduce cyber-security risks and provide secure information directly from smart meters to consumers in near real time, using display devices already owned by the consumers. OpenSEG stores 48 hours of recent consumption data in a circular cache using a format consistent with commonly available archived (not real-time) consumption data such as Green Button, which is based on the Energy Services Provider Interface (ESPI) data standard. It consists of a common XML format for energy usage information and a data exchange protocol to facilitate automated data transfer upon utility customer authorization. Included in the design is an application program interface by which users can acquire data from OpenSEG for further post processing. A sample data display application is included in the initial software product. The data display application demonstrates that OpenSEG can help electricity use data to be retrieved from a smart meter and ported to a wide variety of user-owned devices such as cell phones or a user-selected database. This system can be used for homes, multi-family buildings, or small commercial buildings in California.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗