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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Status of Research Activities on LVDTs: Modeling and Simulation Development and Performance Characterization of Commercial LVDTs

FY-22 research focused on two major areas. The first area was modeling and simulation with linked testing that will advance the Linear Variable Differential Transformers (LVDT) technology for use by stakeholders requiring LVDTs in upcoming irradiation tests. The second area focused on testing LVDTs purchased from U.S. suppliers that were investigated in FY-21. These cross-cutting development activities will ensure stakeholders have the current state-of-the-art LVDT-based technologies for deployment in future irradiation tests. Two stand-alone reports are included in the appendixes. The purpose of this report is to provide a convenient body of work to access the reports and to evaluate the data and conclusions provided. Appendix A, “Testing of the RDP Translation Transducer,” contains a complete evaluation of an RDP Electrosense linear transducer that has the capability of replicating the form, fit, and function of LVDTs currently being used at Idaho National Laboratory (INL). Appendix B is an extract from the report, “Advanced Sensors and Instrumentation Program at Boise State University (BSU), August 2022, Linear Variable Differential Transformers.” This report contains modeling and testing results conducted at BSU and INL.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2016

WE-AB-207B-10: On Spinal Nerve Toxicity from Single-Session SAbR in Pigs and the Translation of Small Animal NTCP Models

Purpose: The incidence of peripheral neuropathy has risen with increased utilization of SAbR. There is no consensus regarding the dose-tolerance of the peripheral nervous system. In 2015, we commenced an investigation to test the hypotheses that single-session irradiation to the pig spinal nerves exhibit a similar dose-tolerance as that of the spinal cord and that a dose-length effect exists. This work evaluates the direct application of small animal NTCP models to both large animal spinal cord and preliminary peripheral nerve data. Methods: To date, 16 of 25 Yucatan minipigs have received single-session SAbR to a 1.5cm length and 4 of 25 have received irradiation to a 0.5cm length of left-sided C6-C8 spinal nerves. Toxicity related gait change has been observed in 13 animals (9 from the long length group and 4 from the short). This preliminary data is overlaid on several dose-response models which have been fit to rodent spinal cord tolerance experiments. Model parameters define a toxicity profile between a completely serial or parallel behaving organ. Adequacy of model application, including how length effects are handled, to published minipig spinal cord dose-response data and to preliminary peripheral nerve response data was evaluated through residual analysis. Results: No rodent-derived dose-response models were directly applicable to all pig data for the different lengths irradiated. Several models fit the long-length irradiated spinal cord data well, with the more serial-like models fitting best. Preliminary data on the short-length irradiation suggests no length effect exists, disproving our hypothesis. Conclusion: Direct application of small-animal NTCP models to pig data suggests dose-length effect predictions from small animal data may not translate clinically. However, the small animal models used have not considered dose heterogeneity and it is expected that including the low-to-mid dose levels in the penumbral region will improve this match. This work was funded by the Cancer Prevention Research Institute of Texas (CPRIT).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Comparison of MCNP thermal scattering laws to inelastic neutron scattering data

Neutron transport computations employ thermal scattering laws (TSLs) to account for the influence of material structure and collective excitations at low energy (≲ 10 eV). Recent work has been undertaken to improve TSL accuracy and expand the number of available materials in the Evaluated Nuclear Data File (ENDF). However, comparison of TSL to measured data is often sparse. In this work, we present a method to evaluate TSL accuracy in the Monte Carlo N-Particle (MCNP) code by simulating inelastic neutron scattering (INS) measurement and comparing to data. The method is briefly described with example application to the recently released ENDF-VIII TSL library for polyethylene as well as a cryogenic PE TSL we are separately developing.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Nuclear Data Sheets for A=194

Experimental nuclear structure and decay data are evaluated for all of 14 known nuclides of mass 194 (Ta, W, Re, Os, Ir, Pt, Au, Hg, Tl, Pb, Bi, Po, At, Rn). Detailed evaluated spectroscopic information is presented for each reaction and decay experiment, and by combining all the available data, recommended values are provided for energies, spins and parities and half-lives of levels, together with energies, branching ratios and multipolarities of gamma radiations from the levels, and characteristics of beta and alpha radiations in radioactive decays. No excited states have yet been identified in 194 Ta, 194 W, and 194 Rn. Only limited spectroscopic data are available for 194 Re, with a 45–μs isomer identified, but its absolute energy yet to be determined. Only two levels at unknown absolute energies are reported for 194 At, both of which are isomeric but neither can be unambiguously identified as the ground state. Data are scarce for 194 Os, 194 Bi and 194 Po, while 194 Pt, 194 Au, 194 Hg, 194 Tl and 194 Pb are well studied through decays and reactions. For 194 Ir, although a major (n, γ), E=thermal study and two particle-transfer studies provide large amounts of spectral data, still several problematic issues are found in the assignment of multipolarities for the secondary gamma transitions in the (n, γ) study by 2008Ba25, 1998Ba85 and 1998Ba42, all from the same group. Some issues have been resolved by the evaluators, but we suggest that further experimental work is needed on 194 Ir structure to resolve standing issues, and verify the conclusions made by 2008Ba25. Furthermore, our attempt to contact the prime authors of the 2008Ba25 paper was not successful. The present work supersedes all the earlier evaluations of A=194 nuclides by 2006Si17, 1996Br26, 1989Si01 and 1972Au11.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1982

Method for evaluating moisture tensions of soils using spectral data

A method is disclosed which permits evaluation of soil moisture utilizing remote sensing. Spectral measurements at a plurality of different wavelengths are taken with respect to sample soils and the bidirectional reflectance factor (BRF) measurements produced are submitted to regression analysis for development therefrom of predictable equations calculated for orderly relationships. Soil of unknown reflective and unknown soil moisture tension is thereafter analyzed for bidirectional reflectance and the resulting data utilized to determine the soil moisture tension of the soil as well as providing a prediction as to the bidirectional reflectance of the soil at other moisture tensions.

Peterson, John B.↗
DOE OSTI2017

The NJOY Nuclear Data Processing System, Version 2016

The NJOY Nuclear Data Processing System, version 2016, is a comprehensive computer code package for producing pointwise and multigroup cross sections and related quantities from evaluated nuclear data in the ENDF-4 through ENDF-6 legacy card-image formats. NJOY works with evaluated files for incident neutrons, photons, and charged particles, producing libraries for a wide variety of particle transport and reactor analysis codes.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Cath Lab Robotics: Paradigm Change in Interventional Cardiology?

Purpose of Review: To review the contemporary evidence for robotic-assisted percutaneous coronary and vascular interventions, discussing its current capabilities, limitations, and potential future applications. Recent Findings: Robotic-assisted cardiovascular interventions significantly reduce radiation exposure and orthopedic strains for interventionalists, while maintaining high rates of device and clinical success. The PRECISE and CORA-PCI studies demonstrated the safety and efficacy of robotic-assisted percutaneous coronary intervention (PCI) in increasingly complex coronary lesions. The RAPID study demonstrated similar findings in peripheral vascular interventions (PVI). Subsequent studies have demonstrated the safety and efficacy of second-generation devices, with automations mimicking manual PCI techniques. While innovations such as telestenting continue to bring excitement to the field, major limitations remain—particularly the lack of randomized trials comparing robotic-assisted PCI with manual PCI. Summary: Robotic technology has successfully been applied to multiple cardiovascular procedures. There are limited data to evaluate outcomes with robotic-assisted PCI and other robotic-assisted cardiovascular procedures, but existing data show some promise of improving the precision of PCI while decreasing occupational hazards associated with radiation exposure.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2020

Modeling Spatial Heterogeneity in Surface Turbulent Heat Flux in the U.S. Southern Great Plains

Advances in numerical modeling of cloud dynamics are driving a need for improved land model prediction at convective storm scales. Here, satellite and ground-based vegetation remote sensing data were combined with land model experiments to more accurately characterize land surface spatial heterogeneity in the Community Land Model (CLM4.0). The new subgrid classification of plant functional types (PFT) and leaf area index (LAI) enables consistent comparison between models and ground-based flux measurements in the U.S. southern Great Plains. Errors in vegetation data sets (inferred from comparison between 250 m satellite and ground-based LAI), while large, had less impact on the simulated characteristics of spatial heterogeneity compared to errors in model representation of surface energy partitioning (between latent and sensible heat flux) and its relationship to LAI. Predicted spatial heterogeneity in surface energy partitioning was enhanced after replacing soil and stomatal resistance parameters with a new set that better predicts the observed relationship to LAI. These modifications increase the number of smaller (mesoscale) dry land patches having higher sensible heat flux. The parameter experiments suggest that vegetation state and processes (transpiration) act to broaden the size spectrum of surface heat flux heterogeneity, which can influence clouds and convective initiation. Moreover, improvements in vegetation input data and model parameters had partially compensating effects on surface flux heterogeneity, indicating the importance of evaluating input data and parameterizations together to improve prediction at higher spatial resolutions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

The generation of 68 Gbps quantum random number by measuring laser phase fluctuations

The speed of a quantum random number generator is essential for practical applications, such as high-speed quantum key distribution systems. Here, we push the speed of a quantum random number generator to 68 Gbps by operating a laser around its threshold level. To achieve the rate, not only high-speed photodetector and high sampling rate are needed but also a very stable interferometer is required. A practical interferometer with active feedback instead of common temperature control is developed to meet the requirement of stability. Phase fluctuations of the laser are measured by the interferometer with a photodetector and then digitalized to raw random numbers with a rate of 80 Gbps. The min-entropy of the raw data is evaluated by modeling the system and is used to quantify the quantum randomness of the raw data. The bias of the raw data caused by other signals, such as classical and detection noises, can be removed by Toeplitz-matrix hashing randomness extraction. The final random numbers can pass through the standard randomness tests. Our demonstration shows that high-speed quantum random number generators are ready for practical usage.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Risk Importance Ranking of Fire Data Parameters to Enhance Fire PRA Model Realism

Fire is historically and analytically a significant contributor to nuclear power plant risk. The level of fire risk and the methods, tools and data for modeling this risk is highly debated by experts. One area of debate is the input data used in fire modeling and how to deal with this data’s high uncertainty. This report outlines initial work performed for determining the key parameters causing this uncertainty and how it propagates into nuclear power plant models. This research paves the way for the development of methods to reduce fire data uncertainty used in modeling. The Nuclear Regulatory Commission has mandated that nuclear power plants perform fire risk modeling. However, there are several issues with the current risk modeling implementation that affect the results. Approved modeling methods can be overly conservative and often do not match plant experience. Also, the data used in the modeling can have high uncertainties and is influenced by expert judgement. To evaluate input data uncertainty, researchers performed an initial review of several fire experiments done at Sandia National Laboratories. Uncertainties for fire data can come from many sources, such as experiment design constraints, environmental conditions, or other plant-specific aspects. There are many different significant and insignificant parameters driving the uncertainty. Additionally, the uncertainty of the different input data used in the fire modeling could have a significant or insignificant effect on the entire plant risk. A four-step methodology was developed to perform Integrated Probabilistic Risk Assessment Importance Ranking. A demonstration case using these steps was set up and three of the four steps were completed in fiscal year (FY) 2019 and the fourth step done FY 2020. These steps are: 1. The qualitative analysis of potential sources was conducted with the following items identified for the demonstration. • Maximum heat release rate • Time to maximum heat release rate • Duration of max heat release rate • Time to decay • Thermal conductivity of concrete • Specific heat of concrete • Density of concrete • Cable jacket thickness 2. A quantitative characterization of dominant sources of uncertainty was performed. A list of distributions and determined values of the dominant sources is shown in Appendix A. 3. A quantitative screening of the potential sources of uncertainty using Morris Elementary Effects Analysis was completed. An experimental model using the physics-based fire modeling tool Fire Dynamics Simulator was developed and coupled with the Risk Analysis Virtual Environment. The Morris analysis identified at least two parameters that can be eliminated as significant contributors (specific heat of concrete and cable jacket thickness). 4. Global importance measure (Global IM) analysis to generate a comprehensive ranking based on their influence on the plant risk. In this research, a moment-independent Global IM is used since it can address (a) uncertainty in the input parameters of the fire model, (b) uncertainty in the risk outputs, and (c) non-linearity and interactions among input parameters in the fire model, more accurately than the correlation-based and variance-based global methods. The observations from the research showed that, depending on the initial and boundary conditions of the fire scenarios, fire-induced damage could have a very small probability and could be dominated by the tail of the uncertainty distribution; hence, the accuracy of the correlation-based and variance-based methods is questionable. The moment-independent Global IM analysis in this research provides a better understanding of how experimental uncertainty data affects industry’s plant models and where improvements in that data will have the largest benefit for improving fire modeling accuracy in causing core damage. Among the five unscreened parameters obtained from the Morris EE analysis, the Global IM analysis results for the case study indicated that max heat release rate and fire location are the most important parameters. The report also outlines benefits of using a unified computational platform that integrates the underlying simulations (e.g., a fire progression model), quantitative screening (using the Morris EE method), and the Global IM analysis. A unified platform can (i) facilitate the ranking of input parameters considering multiple key fire scenarios simultaneously, rather than considering one scenario at a time, (ii) contribute to more explicit and accurate treatment of dependencies at multiple levels of Fire PRA, (iii) facilitate the sampling-based uncertainty quantification for Fire PRA, and (iv) help generating both “industry-wide” and "plant-specific" ranking of uncertainty sources in Fire PRA. Future research should be done to include additional parameters such as detection/suppression or cable fire spread. Adding a PRA software such as SAPHIRE to the RAVEN platform would help with plant model integration and improve treatment of fire-induced dependency. The I-PRA risk importance ranking methodology offered in this report can provide valuable information for efficiently (a) enhancing the realism of Fire PRA for existing plants and (b) supporting the development of Dynamic Fire PRA for advanced reactors and new plants.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Beowulf v2.5.3 User Guide: Revision 5

This document is a user guide for the Beowulf (rebranding of Watchmen) tool. It describes how operators can access and utilize the application's functionality. Beowulf is a research software application developed by Pacific Northwest National Laboratory (PNNL) that incorporates the scientific and operational expertise for reviewing data from treaty monitoring radionuclide stations. These stations are part of a worldwide network to monitor for nuclear explosions, and the data they produce are critical to make the determination of whether a sample is from a nuclear explosion or some other source (i.e., nuclear reactor or medical isotope production facility). Stations deliver their measurements and system status to the International Monitoring System (IMS), which forwards it via email to all subscribers. Beowulf is capable of processing data from several radioxenon station types and development is in progress on a solution for particulate stations. Screening of data in Beowulf may be done by a number of different users such as radionuclide analysts, evaluators, and data quality experts. This guide is provided to assist those users in navigating the application. The term Beowulf is used generically throughout this document to refer to any of the various components in the software application. The user interface that is viewed with a web browser is the primary focus of this user guide. Other components include a database to store measurements and state of health (SOH) data; and the data loader that monitors incoming emails, parses the data, populates the database, does the initial analysis, and routes data for review.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Assessing the Dynamics and Complexity of Disease Pathogenicity Using 4-Dimensional Immunological Data

Investigating disease pathogenesis and personalized prognostics are major biomedical needs. Because patients sharing the same diagnosis can experience different outcomes, such as survival or death, physicians need new personalized tools, including those that rapidly differentiate several inflammatory phases. To address these topics, a pattern recognition-based method (PRM) that follows an inverse problem approach was designed to assess, in <10 min, eight concepts: synergy , pleiotropy , complexity , dynamics , ambiguity , circularity , personalized outcomes , and explanatory prognostics (pathogenesis). By creating thousands of secondary combinations derived from blood leukocyte data, the PRM measures synergic, pleiotropic, complex and dynamic data interactions, which provide personalized prognostics while some undesirable features—such as false results and the ambiguity associated with data circularity-are prevented. Here, this method is compared to Principal Component Analysis (PCA) and evaluated with data collected from hantavirus-infected humans and birds that appeared to be healthy. When human data were examined, the PRM predicted 96.9 % of all surviving patients while PCA did not distinguish outcomes. Demonstrating applications in personalized prognosis, eight PRM data structures sufficed to identify all but one of the survivors. Dynamic data patterns also distinguished survivors from non-survivors, as well as one subset of non-survivors, which exhibited chronic inflammation. When the PRM explored avian data, it differentiated immune profiles consistent with no, early, or late inflammation. Yet, PCA did not recognize patterns in avian data. Findings support the notion that immune responses, while variable, are rather deterministic: a low number of complex and dynamic data combinations may be enough to, rapidly, unmask conditions that are neither directly observable nor reliably forecasted.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1981

Remote mineralogical analysis using a high-resolution airborne spectroradiometer - Preliminary results of the Mark II system

The 1500-2500-nm region is of particular interest for remote mineralogical analysis since hydroxyl-bearing minerals, such as clays, alunite, muscovite, and pyrophyllite, which are associated with hydrothermally altered rocks, have diagnostic absorption features in this region. The development and successful flight testing of the Mark II instrument are seen as making possible the acquisition of the necessary high-spectral-resolution data for evaluating this approach to the remote sensing of geological features. Preliminary results of an analysis of data gathered in October 1980 using the Mark II system for selected test sites in Nevada are presented. Even though field and laboratory analyses of the data are only in the initial stages, the results are seen as indicating that this system can be used to detect the most diagnostic spectral features of several economically important minerals.

Collins, W.↗
NASA NTRS1984

Data management

The following tasks were prioritized: software acquisition management plan; space station flight data system architectural study; space station user data system interface; automation of software development process; automation of software testing; distributed data base management; ADA (automated data acquisition) evaluation and transition and planning; network operating system software; fault tolerant computer validation methodology for onboard data management system; systems integration; artificial intelligence/expert systems; space station data network concept; space station standard interface protocols; space station data networks systems; integrated software development facility; and language trade studies.

Love, G.↗
NASA NTRS1985

The absolute flux of six hot stars in the ultraviolet (912-1600 A)

Six hot stars were observed on 1984 March 2 from a Black Brant V sounding rocket (NASA 21.085UG). The absolute fluxes from Gamma 2 Vel, Zeta Pup, Alpha CMa ,Gamma Ori, Beta Tau, and Epsilon Per were measured in the spectral region between 912 and 1600 A at 10 A resolution. Comparisons with revised Voyager 1 and Voyager 2 Ultraviolet Spectrometer data and previous sounding rocket data are evaluated. In general, the two sounding rocket experiments are in good agreement, and the revised Voyager data and the sounding rocket data are in agreement except at wavelengths below 1000 A.

Woods, T. N.↗
NASA NTRS1992

The relationship between clear sky water vapor and SST anomalies

The relationship between clear sky water vapor anomalies and the SST anomalies (SSTAs) was investigated with the purpose of providing data for evaluating the clear sky greenhouse effect predicted in many global warming scenarios, by statistically analyzing anomaly data sets of SST and the water vapor anomaly data (obtained by subtracting the mean value of the six years of data for a given month from the observed values). Results show that clear sky water vapor anomalies increase in association with increases in SSTAs. The clear sky water vapor anomalies high in the troposphere were also found to increase with increasing SSTA.

Peterson, Thomas C.↗