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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 1,747 records · Page 97
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Jitter model and signal processing techniques for pulse width modulation optical recording

A jitter model and signal processing techniques are discussed for data recovery in Pulse Width Modulation (PWM) optical recording. In PWM, information is stored through modulating sizes of sequential marks alternating in magnetic polarization or in material structure. Jitter, defined as the deviation from the original mark size in the time domain, will result in error detection if it is excessively large. A new approach is taken in data recovery by first using a high speed counter clock to convert time marks to amplitude marks, and signal processing techniques are used to minimize jitter according to the jitter model. The signal processing techniques include motor speed and intersymbol interference equalization, differential and additive detection, and differential and additive modulation.

Liu, Max M.-K.↗
NASA NTRS2010

Test Rack Development for Extended Operation of Advanced Stirling Convertors at NASA Glenn Research Center

The U.S. Department of Energy, Lockheed Martin Space Systems Company, Sunpower Inc., and NASA Glenn Research Center (GRC) have been developing an Advanced Stirling Radioisotope Generator (ASRG) for use as a power system on space science missions. This generator will make use of free-piston Stirling convertors to achieve higher conversion efficiency than with currently available alternatives. One part of NASA GRC's support of ASRG development includes extended operation testing of Advanced Stirling Convertors (ASCs) developed by Sunpower Inc. and GRC. The ASC consists of a free-piston Stirling engine integrated with a linear alternator. NASA GRC has been building test facilities to support extended operation of the ASCs for several years. Operation of the convertors in the test facility provides convertor performance data over an extended period of time. One part of the test facility is the test rack, which provides a means for data collection, convertor control, and safe operation. Over the years, the test rack requirements have changed. The initial ASC test rack utilized an alternating-current (AC) bus for convertor control; the ASRG Engineering Unit (EU) test rack can operate with AC bus control or with an ASC Control Unit (ACU). A new test rack is being developed to support extended operation of the ASC-E2s with higher standards of documentation, component selection, and assembly practices. This paper discusses the differences among the ASC, ASRG EU, and ASC-E2 test racks.

Dugala, Gina M.↗
DOE OSTI2021

PLANC: Parallel Low-rank Approximation with Nonnegativity Constraints

In this work, we consider the problem of low-rank approximation of massive dense nonnegative tensor data, for example, to discover latent patterns in video and imaging applications. As the size of data sets grows, single workstations are hitting bottlenecks in both computation time and available memory. We propose a distributed-memory parallel computing solution to handle massive data sets, loading the input data across the memories of multiple nodes, and performing efficient and scalable parallel algorithms to compute the low-rank approximation. We present a software package called Parallel Low-rank Approximation with Nonnegativity Constraints, which implements our solution and allows for extension in terms of data (dense or sparse, matrices or tensors of any order), algorithm (e.g., from multiplicative updating techniques to alternating direction method of multipliers), and architecture (we exploit GPUs to accelerate the computation in this work). We describe our parallel distributions and algorithms, which are careful to avoid unnecessary communication and computation, show how to extend the software to include new algorithms and/or constraints, and report efficiency and scalability results for both synthetic and real-world data sets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Rod Internal Pressure Distribution and Uncertainty Analysis Using FRAPCON

The discharge rod internal pressure (RIP) and cladding hoop stress (CHS) distributions are quantified for Watts Bar Nuclear Unit 1 (WBN1) fuel rods by modeling core cycle design data, operation data, and as-built fuel enrichments and densities of each fuel rod in FRAPCON-3.5. A methodology is developed that tracks intercycle assembly movements and assembly batch fabrication information to build individual FRAPCON inputs for each evaluated WBN1 fuel rod. An alternate model for the amount of helium released from the zirconium diboride (ZrB 2 ) integral fuel burnable absorber (IFBA) layer is derived and applied to FRAPCON output data to quantify the RIP and CHS for these types of fuel rods. SCALE/Polaris is used to quantify fuel rod–specific spectral quantities and the amount of gaseous fission products produced in the fuel for use in FRAPCON inputs. Fuel rods with ZrB 2 IFBA layers (i.e., IFBA rods) are determined to have RIP predictions that are elevated when compared to fuel rods without IFBA layers (i.e., standard rods) despite the fact that IFBA rods often have reduced fill pressures and annular fuel pellets. The primary contributor to elevated RIP predictions at burnups less than and greater than 30 GWd/tonne U is determined to be the total fuel rod void volume and the amount of released fission gas in the fuel rod, respectively. Cumulative distribution functions (CDFs) are prepared from the distribution of RIP and CHS predictions for all standard and IFBA rods. The provided CDFs allow for the determination of the portion of WBN1 fuel rods that exceeds a specified RIP or CHS limit. Results are separated into IFBA and standard rods so that the two groups may be analyzed individually. FRAPCON results are provided in sufficient detail to enable the recalculation of the RIP while considering any desired plenum gas temperature, total void volume, or total amount of gas present in the void volume. A method to predict the CHS from a determined or assumed RIP is also proposed that is based on the approximately linear relationship between the CHS and the RIP. Finally, improvements to the computational methodology of FRAPCON are proposed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Data-Driven Strategies for Accelerated Materials Design

The ongoing revolution of the natural sciences by the advent of machine learning and artificial intelligence sparked significant interest in the material science community in recent years. The intrinsically high dimensionality of the space of realizable materials makes traditional approaches ineffective for large-scale explorations. Modern data science and machine learning tools developed for increasingly complicated problems are an attractive alternative. An imminent climate catastrophe calls for a clean energy transformation by overhauling current technologies within only several years of possible action available. Tackling this crisis requires the development of new materials at an unprecedented pace and scale. For example, organic photovoltaics have the potential to replace existing silicon-based materials to a large extent and open up new fields of application. In recent years, organic light-emitting diodes have emerged as state-of-the-art technology for digital screens and portable devices and are enabling new applications with flexible displays. Reticular frameworks allow the atom-precise synthesis of nanomaterials and promise to revolutionize the field by the potential to realize multifunctional nanoparticles with applications from gas storage, gas separation, and electrochemical energy storage to nanomedicine. In the recent decade, significant advances in all these fields have been facilitated by the comprehensive application of simulation and machine learning for property prediction, property optimization, and chemical space exploration enabled by considerable advances in computing power and algorithmic efficiency. In this Account, we review the most recent contributions of our group in this thriving field of machine learning for material science. We start with a summary of the most important material classes our group has been involved in, focusing on small molecules as organic electronic materials and crystalline materials. Specifically, we highlight the data-driven approaches we employed to speed up discovery and derive material design strategies. Subsequently, our focus lies on the data-driven methodologies our group has developed and employed, elaborating on high-throughput virtual screening, inverse molecular design, Bayesian optimization, and supervised learning. We discuss the general ideas, their working principles, and their use cases with examples of successful implementations in data-driven material discovery and design efforts. Furthermore, we elaborate on potential pitfalls and remaining challenges of these methods. Finally, we provide a brief outlook for the field as we foresee increasing adaptation and implementation of large scale data-driven approaches in material discovery and design campaigns.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Federation of UML models for cyber physical use cases

This method employs the concept of federation, which is defined as the use of existing models that represent aspects of a system in specific domains (such as physical and cyber security domains) and building interfaces to link all of domain models. Federation seeks to build on existing bodies of work. Some examples include the Common Information Models (CIM) maintained by the International Electrotechnical Commission Technical Committee 57 (IEC TC 57) for the electric power industry. Another relevant model is the CIM maintained by the Distributed Management Task Force (DMTF)? this CIM defines a representation of the managed elements in an Information Technology (IT) environment. The power system is an example of a cyber-physical system, where the cyber systems, consisting of computing infrastructure such as networks and devices, play a critical role in the operation of the underlying physical electricity delivery system. Measurements from remote field devices are relayed to control centers through computer networks, and the data is processed to determine suitable control actions. Control decisions are then relayed back to field devices. It has been observed that threat actors may be able to successfully compromise this cyber layer in order to impact power system operation. Therefore, future control center applications must be wary of potentially compromised measurements coming from field devices. In order to ensure the integrity of the field measurements, these applications could make use of compromise indicators from alternate sources of information such as cyber security. Thus, modern control applications may require access to data from sources that are not defined in the local information model. In such cases, software application interfaces will require integration of data objects from cross-domain data models. When incorporating or federating different domains, it is important to have subject matter experts work together, recognizing that not everyone has the same knowledge, responsibilities, focus, or skill set.

Source record↗
NASA NTRS1990

General upper bound on single-event upset rate

A technique of predicting an upper bound on the rate at which single-event upsets due to ionizing radiation occur in semiconducting memory cells is described. The upper bound on the upset rate, which depends on the high-energy particle environment in earth orbit and accelerator cross-section data, is given by the product of an upper-bound linear energy-transfer spectrum and the mean cross section of the memory cell. Plots of the spectrum are given for low-inclination and polar orbits. An alternative expression for the exact upset rate is also presented. Both methods rely only on experimentally obtained cross-section data and are valid for sensitive bit regions having arbitrary shape.

Chlouber, Dean↗
NASA NTRS2002

Turbulence Measurements of Separate Flow Nozzles with Mixing Enhancement Features

Comparison of turbulence data taken in three separate flow nozzles, two with mixing enhancement features on their core nozzle, shows how the mixing enhancement features modify turbulence to reduce jet noise. The three nozzles measured were the baseline axisymmetric nozzle 3BB, the alternating chevron nozzle, 3A12B, with 6-fold symmetry, and the flipper tab nozzle 3T24B also with 6-fold symmetry. The data presented show the differences in turbulence characteristics produced by the geometric differences in the nozzles, with emphasis on those characteristics of interest in jet noise. Among the significant findings: the enhanced mixing devices reduce turbulence in the jet mixing region while increasing it in the fan/core shear layer, the ratios of turbulence components are significantly altered by the mixing devices, and the integral lengthscales do not conform to any turbulence model yet proposed. These findings should provide guidance for modeling the statistical properties of turbulence to improve jet noise prediction.

Bridges, James↗
DOE OSTI2019

Hybridizing Classifiers and Collection Systems to Maximize Intelligence and Minimize Uncertainty in National Security Data Analytics Applications

There are numerous applications that combine data collected from sensors with machine-learning based classification models to predict the type of event or objects observed. Both the collection of the data itself and the classification models can be tuned for optimal performance, but we hypothesize that additional gains can be realized by jointly assessing both factors together. Through this research, we used a seismic event dataset and two neural network classification models that issued probabilistic predictions on each event to determine whether it was an earthquake or a quarry blast. Real world applications will have constraints on data collection, perhaps in terms of a budget for the number of sensors or on where, when, or how data can be collected. We mimicked such constraints by creating subnetworks of sensors with both size and locational constraints. We compare different methods of determining the set of sensors in each subnetwork in terms of their predictive accuracy and the number of events that they observe overall. Additionally, we take the classifiers into account, treating them both as black-box models and testing out various ways of combining predictions among models and among the set of sensors that observe any given event. We find that comparable overall performance can be seen with less than half the number of sensors in the full network. Additionally, a voting scheme that uses the average confidence across the sensors for a given event shows improved predictive accuracy across nearly all subnetworks. Lastly, locational constraints matter, but sometimes in unintuitive ways, as better-performing sensors may be chosen instead of the ones excluded based on location. This being a short-term research effort, we offer a lengthy discussion on interesting next-steps and ties to other ongoing research efforts that we did not have time to pursue. These include a detailed analysis of the subnetwork performance broken down by event type, specific location, and model confidence. This project also included a Campus Executive research partnership with Texas A&M University. Through this, we worked with a professor and student to study information gain for UAV routing. This was an alternative way of looking at the similar problem space that includes sensor operation for data collection and the resulting benefit to be gained from it. This work is described in an Appendix.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Welded and Hydrogen Charged Zircaloy-4 and Welded Stainless Steel 347 Property Data and Microstructures for the Target Solution Vessel and Support Lines of SHINE

SHINE Medical Technologies is developing a facility that will produce molybdenum-99 for medical isotope procedures. As part of this facility, a metal tank, called the target solution vessel (TSV), will hold a uranyl sulfite solution. The TSV must withstand neutron irradiation near room temperature and potential corrosion from the aqueous solution. The large cylindrical TSV will be fabricated by welding and will have numerous pipes and connections also attached via welding. The vessel and those pipes will have varying thicknesses so both gas tungsten arc welding (GTAW) and flux-cored arc welding (FCAW) will be necessary to fabricate different sections. The original material under consideration for the TSV was Zircaloy-4 (Zry-4), but it is known to form a hydride which can degrade its mechanical properties. Thus, some investigation here is focused on the effects of hydrogen uptake in the Zry-4. Additionally, the alternative material being considered is AISI 347, a stainless steel. Both materials have little existing data for their neutron irradiation behavior below 100°C, and both have open questions on the weld behavior under neutron irradiation. Testing has focused on characterizing their weld properties with tensile tests and performing neutron irradiation of samples in the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL).

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2026

OpenSAMPL: An Open Source Library for Timing and Synchronization Measurements and Analytics

Today's power grid operators are implementing timing and synchronization solutions that provide resilience to Global Navigation Satellite System (GNSS) vulnerabilities. These vendor-specific solutions often come with additional software applications that are designed to monitor that vendor's synchronization performance data. However, resilient timing architectures often resulting in multi-vendor solutions, including approaches that blend terrestrial clocks with space-based subscription services. In such an environment, collecting, analyzing, and visualizing data from a variety of sources within a single platform was heretofore not possible. To address this need, the US Department of Energy's Center for Alternative Synchronization and Timing (CAST) developed OpenSAMPL, the Open Synchronized Analytics and Monitoring Platform, an open-source Python framework for processing, loading, and observing clock measurement data from distributed devices. OpenSAMPL enables the ingestion of diverse clock-probe sources into a scalable time-series database and applies robust analytics. OpenSAMPL currently supports two vendor data pipelines, and will be extended to more in the near future, enabling seamless monitoring of a variety of timing and synchronization devices in a common environment.

Grant, Josh [ORNL] (ORCID:0000000163475060)↗
DOE OSTI2016

Measurement of the decay B → D ℓ ν ℓ in fully reconstructed events and determination of the Cabibbo-Kobayashi-Maskawa matrix element | V c b |

We present a determination of the magnitude of the Cabibbo-Kobayashi-Maskawa matrix element |Vcb| using the decay B → Dℓν ℓ (ℓ = e,μ) based on 711 fb –1 of e + e – → Υ(4S) data recorded by the Belle detector and containing 772 × 10 6 BB¯ pairs. Here, one B meson in the event is fully reconstructed in a hadronic decay mode, while the other, on the signal side, is partially reconstructed from a charged lepton and either a D + or D 0 meson in a total of 23 hadronic decay modes. The isospin-averaged branching fraction of the decay B → Dℓν ℓ is found to be B(B 0 → D – ℓ + ν ℓ ) = (2.31 ± 0.03(stat) ± 0.11(syst))%. Analyzing the differential decay rate as a function of the hadronic recoil with the parametrization of Caprini, Lellouch, and Neubert and using the form-factor prediction G(1) = 1.0541 ± 0.0083 calculated by FNAL/MILC, we obtain η EW |V cb | = (40.12 ± 1.34) × 10 –3 , where ηEW is the electroweak correction factor. Alternatively, assuming the model-independent form-factor parametrization of Boyd, Grinstein, and Lebed and using lattice QCD data from the FNAL/MILC and HPQCD collaborations, we find η EW |V cb | = (41.10 ± 1.14) × 10 –3 .

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Synchronization of Alternative Models in a Supermodel and the Learning of Critical Behavior

“Supermodeling” climate by allowing different models to assimilate data from one another in run time has been shown to give results superior to those of any one model and superior to any weighted average of model outputs. The only free parameters, connection strengths between corresponding variables in each pair of models, are determined using some form of machine learning. It is demonstrated that supermodeling succeeds because near critical states, interscale interactions are important but unresolved processes cannot be effectively represented diagnostically in any single parameterization scheme. In two examples, a pair of toy quasigeostrophic (QG) channel models of the midlatitudes and a pair of ECHAM5 models of the tropical Pacific atmosphere with a common ocean, supermodels dynamically combine parameterization schemes so as to capture criticality, associated critical structures, and the supporting scale interactions. The QG supermodeling scheme extends a previous configuration in which two such models synchronize with intermodel connections only between medium-scale components of the flow; here the connections are trained against a third “real” model. Intermittent blocking patterns characterize the critical behavior thus obtained, even where such patterns are missing in the constituent models. In the ECHAM-based climate supermodel, the corresponding critical structure is the single ITCZ pattern, a pattern that occurs in neither of the constituent models. In conclusion, for supermodels of both types, power spectra indicate enhanced interscale interactions in frequency or energy ranges of physical interest, in agreement with observed data, and supporting a generalized form of the self-organized criticality hypothesis.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1990

The extragalactic universe - An alternative view

It is argued that the currently popular cosmological model is subject to many doubts based on observational data which suggest that there never was a Big Bang. It is further argued that the observational evidence concerning nonthermal objects with large redshifts leads to the conclusion that these redshifts are largely intrinsic in origin. These objects do not lie at large cosmological distances, but rather much closer with z(c) less than about 0.1. This in turn means that there is no evidence for evolution in the discrete objects, and that what is seen in them are creation events involving the ejection of new matter from the nuclei of galaxies.

Arp, H. C.↗
NASA NTRS1993

High performance FORTRAN without templates: An alternative model for distribution and alignment

Language extensions of FORTRAN are being developed which permit the user to map data structures to the individual processors of distributed memory machines. These languages allow a programming style in which global data references are used. Current efforts are focussed on designing a common basis for such languages, the result of which is known as High Performance Fortran (HPF). One of the central debates in the HPF effort revolves around the concept of templates, introduced as an abstract index space to which data could be aligned. A model for the mapping of data which provides the functionality of High Performance Fortran distributions without the use of templates is presented.

Chapman, Barbara↗
NASA NTRS2011

Experimental and Modeling Studies of the Combustion Characteristics of Conventional and Alternative Jet Fuels. Final Report

The objectives of this project have been to develop a comprehensive set of fundamental data regarding the combustion behavior of jet fuels and appropriately associated model fuels. Based on the fundamental study results, an auxiliary objective was to identify differentiating characteristics of molecular fuel components that can be used to explain different fuel behavior and that may ultimately be used in the planning and design of optimal fuel-production processes. The fuels studied in this project were Fischer-Tropsch (F-T) fuels and biomass-derived jet fuels that meet certain specifications of currently used jet propulsion applications. Prior to this project, there were no systematic experimental flame data available for such fuels. One of the key goals has been to generate such data, and to use this data in developing and verifying effective kinetic models. The models have then been reduced through automated means to enable multidimensional simulation of the combustion characteristics of such fuels in real combustors. Such reliable kinetic models, validated against fundamental data derived from laminar flames using idealized flow models, are key to the development and design of optimal combustors and fuels. The models provide direct information about the relative contribution of different molecular constituents to the fuel performance and can be used to assess both combustion and emissions characteristics.

Meeks, Ellen↗
DOE OSTI2025

Atacama Cosmology Telescope: DR6 gravitational lensing and SDSS BOSS cross-correlation measurement and constraints on gravity with the 𝐸 𝐺 statistic

We derive new constraints on the 𝐸 𝐺 statistic as a test of gravity, combining the cosmic microwave background (CMB) lensing map estimated from Data Release 6 (DR6) of the Atacama Cosmology Telescope with Sloan Digital Sky Survey III Baryon Oscillation Spectroscopic Survey (SDSS BOSS) CMASS and LOWZ galaxy data. We develop an analysis pipeline to measure the cross-correlation between CMB lensing maps and galaxy data, following a blinding policy and testing the approach through null and consistency checks. By testing the equivalence of the spatial and temporal gravitational potentials, the 𝐸 𝐺 statistic can distinguish Λ⁢ CDM from alternative models of gravity. We find 𝐸 𝐺 ⁡(𝑧 eff = 0.555) = 0.3⁢1$^{+0.06}_{−0.05}$ for Atacama Cosmology Telescope (ACT) and CMASS data at 68.28% confidence level, and 𝐸 𝐺 ⁡(𝑧 eff = 0.316) = 0.4⁢9$^{+0.14}_{−0.11}$ for the ACT and LOWZ. Systematic errors are estimated to be 3% and 4%, respectively. Including CMB lensing information from Planck PR4 results in 𝐸 𝐺 ⁡(𝑧 eff = 0.555) = 0.3⁢4$^{+0.05}_{−0.05}$ with CMASS and 𝐸 𝐺 ⁡(𝑧 eff = 0.316) = 0.4⁢3$^{+0.11}_{−0.09}$ with LOWZ. These are consistent with predictions for the Λ⁢ CDM model that best fits the Planck CMB anisotropy and SDSS BOSS baryon acoustic oscillations (BAO), where 𝐸$^{GR}_{𝐺⁡}$(𝑧 eff =0.555) =0.401 ± 0.005 for CMB lensing combined with CMASS and 𝐸$^{GR}_{𝐺}$⁡(𝑧 eff = 0.316) = 0.452 ± 0.005 combined with LOWZ. We also find 𝐸 𝐺 to be scale independent, with probability to exceed >5%, as predicted by general relativity. The methods developed in this work are also applicable to improved future analyses with upcoming spectroscopic galaxy samples and CMB lensing measurements.

79 ASTRONOMY AND ASTROPHYSICS↗