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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Lawrence Livermore National Laboratory Environmental Report 2021

The purposes of the Lawrence Livermore National Laboratory Environmental Report 2021 are to record Lawrence Livermore National Laboratory’s (LLNL’s) compliance with environmental standards and requirements, describe LLNL’s environmental protection and remediation programs, and present the results of environmental monitoring at the two LLNL sites—the Livermore Site and Site 300. The report is prepared for the U.S. Department of Energy (DOE) by LLNL’s Environmental Functional Area. Submittal of the report satisfies requirements under DOE Order 231.1B, “Environment, Safety and Health Reporting,” and DOE Order 458.1, “Radiation Protection of the Public and Environment.” The report is distributed electronically and is available at https://saer.llnl.gov/, the website for the LLNL annual environmental report. Previous LLNL annual environmental reports beginning with 1994 are also on the website. Some references in the electronic report text are underlined, which indicates that they are clickable links. Clicking on one of these links will open the related document, data workbook, or website. Sampling location maps throughout this report were created using ArcGIS® software by Esri. The report begins with an executive summary, which provides the purpose of the report and an overview of LLNL’s compliance and monitoring results. The first three chapters provide background information: Chapter 1 is an overview of the location, meteorology, and hydrogeology of the two LLNL sites; Chapter 2 is a summary of LLNL’s compliance with environmental regulations; and Chapter 3 is a description of LLNL’s environmental programs with an emphasis on the Environmental Management System including pollution prevention. The majority of the report covers LLNL’s environmental monitoring programs and monitoring data for 2021: effluent and ambient air monitoring and dose assessment (Chapter 4); waters, including wastewater, storm water runoff, surface water, rain, and groundwater (Chapter 5); and terrestrial, including soil, sediment, vegetation, foodstuff, ambient radiation, and special status wildlife and plants (Chapter 6). The remaining two chapters discuss LLNL’s groundwater remediation program (Chapter 7), and quality assurance for the environmental monitoring programs (Chapter 8). Complete monitoring data, which are summarized in the body of the report, are provided in Appendix A. The report uses Système International units, consistent with the federal Metric Conversion Act of 1975 and Executive Order 12770, “Metric Usage in Federal Government Programs” (1991). For ease of comparison to environmental reports issued prior to 1991, dose values and many radiological measurements are given in both metric and U.S. customary units. A conversion table is provided in the glossary. The report is the responsibility of LLNL’s Environmental Functional Area. Monitoring data were obtained through the combined efforts of the Environmental Functional Area; Environmental Restoration Department; Physical and Life Sciences Environmental Monitoring Radiological Laboratory; and the Radiation Protection Functional Area.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Solvent-Producing Clostridia Revisited

The review provides an overview of the current status of the solvent-producing clostridia. The origin and development of industrial clostridial species, as well as the history of the industrial Acetone Butanol Ethanol fermentation process, is reexamined, and the recent resurgence of interest in the production of biobutanol is reviewed. Over 300 fully sequenced genomes for solvent-producing and closely related clostridial species are currently available in public databases. These include 270 genomes sourced from the David Jones culture collection. These genomes were allocated arbitrary DJ codes, and a conversion table to identify the species and strains has now been provided. The expanded genomic database facilitated new comparative genomic and phylogenetic analysis. A synopsis of the common features, molecular taxonomy, and phylogeny of solvent-producing clostridia and the application of comparative phylogenomics are evaluated. A survey and analysis of resident prophages in solvent-producing clostridia are discussed, and the discovery, occurrence, and role of novel R-type tailocins are reported. Prophage genomes with R-type tailocin-like features were detected in all 12 species investigated. The widespread occurrence of tailocins in Gram-negative species is well documented; this survey has indicated that they may also be widespread in clostridia.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1982

NASA education briefs for the classroom. Metrics in space

The use of metric measurement in space is summarized for classroom use. Advantages of the metric system over the English measurement system are described. Some common metric units are defined, as are special units for astronomical study. International system unit prefixes and a conversion table of metric/English units are presented. Questions and activities for the classroom are recommended.

Source record↗
NASA NTRS2012

Advances in the RXTE Proportional Counter Array Calibration: Nearing the Statistical Limit

During its 16 years of service Rossi X-ray Timing Explorer (RXTE) mission has provided an extensive archive of data, which will serve as a primary source of high cadence observation of variable X-ray sources for fast timing studies. It is, therefore, very important to have the most reliable calibration of RXTE instruments. The Proportional Counter Array (PCA) is the primary instrument on-board RXTE which provides data in 2-50 keY with higher than millisecond time resolution in up to 256 energy channels. In 2009 RXTE team revised the response residual minimization method used to derive the parameters of the PCA physical model. The procedure is now based on the residual minimization between the model spectrum for Crab nebula emission and a calibration data set consisting of a number of spectra from the Crab and the on-board Am241 calibration source, uniformly covering a whole RXTE span. The new method led to a much more effective model convergence and allowed for better understanding of the behavior of the PCA energy-to-channel relationship. It greatly improved the response matrix performance. We describe the new version of the RXTE/PCA response generator PCARMF vll.7 along with the corresponding energy-to-channel conversion table (version e05v04) and their difference from the previous releases of PCA calibration. The new PCA response adequately represents the spectrum of the calibration sources and successfully predicts the energy of the narrow iron emission line in Cas-A throughout the RXTE mission.

Shaposhnikov, Nikolai↗
NASA NTRS2012

Restoration and Reexamination of Data from the Apollo 11, 12, 14, and 15 Dust, Thermal and Radiation Engineering Measurements Experiments

As part of an effort by the Lunar Data Node (LDN) we are restoring data returned by the Apollo Dust, Thermal, and Radiation Engineering Measurements (DTREM) packages emplaced on the lunar surface by the crews of Apollo 11, 12, 14, and 15. Also commonly known as the Dust Detector experiments, the DTREM packages measured the outputs of exposed solar cells and thermistors over time. They operated on the surface for up to nearly 8 years, returning data every 54 seconds. The Apollo 11 DTREM was part of the Early Apollo Surface Experiments Package (EASEP), and operated for a few months as planned following emplacement in July 1969. The Apollo 12, 14, and 15 DTREMs were mounted on the central station as part of the Apollo Lunar Surface Experiments Package (ALSEP) and operated from deployment until ALSEP shutdown in September 1977. The objective of the DTREM experiments was to determine the effects of lunar and meteoric dust, thermal stresses, and radiation exposure on solar cells. The LDN, part of the Geosciences Node of the Planetary Data System (PDS), operates out of the National Space Science Data Center (NSSDC) at Goddard Space Flight Center. The goal of the LDN is to extract lunar data stored on older media and/or in obsolete formats, restore the data into a usable digital format, and archive the data with PDS and NSSDC. For the DTREM data we plan to recover the raw telemetry, translate the raw counts into appropriate output units, and then apply calibrations. The final archived data will include the raw, translated, and calibrated data and the associated conversion tables produced from the microfilm, as well as ancillary supporting data (metadata) packaged in PDS format.

McBride, Marie J.↗
DOE OSTI2016

Obtaining correct compile results by absorbing mismatches between data types representations

Methods and a system are provided. A method includes implementing a function, which a compiler for a first language does not have, using a compiler for a second language. The implementing step includes generating, by the compiler for the first language, a first abstract syntax tree. The implementing step further includes converting, by a converter, the first abstract syntax tree to a second abstract syntax tree of the compiler for the second language using a conversion table from data representation types in the first language to data representation types in the second language. When a compilation error occurs, the implementing step also includes generating a special node for error processing in the second abstract syntax tree and storing an error token in the special node. When unparsing, the implementing step additionally includes outputting the error token, in the form of source code written in the first language.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Obtaining correct compile results by absorbing mismatches between data types representations

Methods and a system are provided. A method includes implementing a function, which a compiler for a first language does not have, using a compiler for a second language. The implementing step includes generating, by the compiler for the first language, a first abstract syntax tree. The implementing step further includes converting, by a converter, the first abstract syntax tree to a second abstract syntax tree of the compiler for the second language using a conversion table from data representation types in the first language to data representation types in the second language. When a compilation error occurs, the implementing step also includes generating a special node for error processing in the second abstract syntax tree and storing an error token in the special node. When unparsing, the implementing step additionally includes outputting the error token, in the form of source code written in the first language.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Obtaining correct compile results by absorbing mismatches between data types representations

Methods and a system are provided. A method includes implementing a function, which a compiler for a first language does not have, using a compiler for a second language. The implementing step includes generating, by the compiler for the first language, a first abstract syntax tree. The implementing step further includes converting, by a converter, the first abstract syntax tree to a second abstract syntax tree of the compiler for the second language using a conversion table from data representation types in the first language to data representation types in the second language. When a compilation error occurs, the implementing step also includes generating a special node for error processing in the second abstract syntax tree and storing an error token in the special node. When unparsing, the implementing step additionally includes outputting the error token, in the form of source code written in the first language.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Transportation Energy Data Book: Edition 38

The Transportation Energy Data Book: Edition 38 is a statistical compendium prepared and published by Oak Ridge National Laboratory (ORNL) under contract with the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office. Designed for use as a desk-top reference, the Data Book represents an assembly and display of statistics and information that characterize transportation activity, and presents data on other factors that influence transportation energy use. The purpose of this document is to present relevant statistical data in the form of tables and graphs. The latest edition of the Data Book is available via the Internet. This edition of the Data Book has 13 chapters which focus on various aspects of the transportation industry. Chapter 1 - focuses on petroleum; Chapter 2 - energy; Chapter 3 - highway vehicles; Chapter 4 - light vehicles; Chapter 5 - heavy vehicles; Chapter 6 - alternative fuel vehicles; Chapter 7 - transit and shared mobility; Chapter 8 - fleet vehicles; Chapter 9 - household vehicles; Chapter 10 - nonhighway modes; Chapter 11 - transportation and the economy; Chapter 12 - greenhouse gas emissions; and Chapter 13 - criteria pollutant emissions. The sources used represent the latest available data. There are also three appendices which include detailed source information for some tables, measures of conversion, and energy tables and figures with electricity generation and distribution taken into account. A glossary of terms is also included for the reader’s convenience.

02 PETROLEUM↗
DOE OSTI2021

Transportation Energy Data Book: Edition 39

The Transportation Energy Data Book: Edition 39 is a statistical compendium prepared and published by Oak Ridge National Laboratory (ORNL) under contract with the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Vehicle Technologies Office. Designed for use as a desk-top reference, the Data Book represents an assembly and display of statistics and information that characterize transportation activity and presents data on other factors that influence transportation energy use. The purpose of this document is to present relevant statistical data in the form of tables and graphs. The latest edition of the Data Book is available via the Internet (tedb.ornl.gov).This edition of the Data Book has 13 chapters which focus on various aspects of the transportation industry. Chapter 1 focuses on petroleum; Chapter 2 – energy; Chapter 3 – highway vehicles; Chapter 4 – light vehicles; Chapter 5 – heavy vehicles; Chapter 6 – alternative fuel vehicles; Chapter 7 – transit and other shared mobility; Chapter 8 – fleet vehicles; Chapter 9 – household vehicles; Chapter 10 – nonhighway modes; Chapter 11 – transportation and the economy; Chapter 12 – greenhouse gas emissions; and Chapter 13 – criteria pollutant emissions. The sources used represent the latest available data. There are also three appendices which include detailed source information for some tables, measures of conversion, and energy tables with electricity generation and distribution. A glossary of terms is also included for the reader’s convenience.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2013

VLBI2010 Receiver Back End Comparison

VLBI2010 requires a receiver back-end to convert analog RF signals from the receiver front end into channelized digital data streams to be recorded or transmitted electronically. The back end functions are typically performed in two steps: conversion of analog RF inputs into IF bands (see Table 2), and conversion of IF bands into channelized digital data streams (see Tables 1a, 1b and 1c). The latter IF systems are now completely digital and generically referred to as digital back ends (DBEs). In Table 2 two RF conversion systems are compared, and in Tables 1a, 1b, and 1c nine DBE systems are compared. Since DBE designs are advancing rapidly, the data in these tables are only guaranteed to be current near the update date of this document.

Petrachenko, Bill↗
DOE OSTI2015

Initial implementation of the conversion from the energy-subtracted CT number to electron density in tissue inhomogeneity corrections: An anthropomorphic phantom study of radiotherapy treatment planning

Purpose: To achieve accurate tissue inhomogeneity corrections in radiotherapy treatment planning, the authors had previously proposed a novel conversion of the energy-subtracted computed tomography (CT) number to an electron density (ΔHU–ρ{sub e} conversion), which provides a single linear relationship between ΔHU and ρ{sub e} over a wide range of ρ{sub e}. The purpose of this study is to present an initial implementation of the ΔHU–ρ{sub e} conversion method for a treatment planning system (TPS). In this paper, two example radiotherapy plans are used to evaluate the reliability of dose calculations in the ΔHU–ρ{sub e} conversion method. Methods: CT images were acquired using a clinical dual-source CT (DSCT) scanner operated in the dual-energy mode with two tube potential pairs and an additional tin (Sn) filter for the high-kV tube (80–140 kV/Sn and 100–140 kV/Sn). Single-energy CT using the same DSCT scanner was also performed at 120 kV to compare the ΔHU–ρ{sub e} conversion method with a conventional conversion from a CT number to ρ{sub e} (Hounsfield units, HU–ρ{sub e} conversion). Lookup tables for ρ{sub e} calibration were obtained from the CT image acquisitions for tissue substitutes in an electron density phantom (EDP). To investigate the beam-hardening effect on dosimetric uncertainties, two EDPs with different sizes (a body EDP and a head EDP) were used for the ρ{sub e} calibration. Each acquired lookup table was applied to two radiotherapy plans designed using the XiO TPS with the superposition algorithm for an anthropomorphic phantom. The first radiotherapy plan was for an oral cavity tumor and the second was for a lung tumor. Results: In both treatment plans, the performance of the ΔHU–ρ{sub e} conversion was superior to that of the conventional HU–ρ{sub e} conversion in terms of the reliability of dose calculations. Especially, for the oral tumor plan, which dealt with dentition and bony structures, treatment planning with the HU–ρ{sub e} conversion exhibited apparent discrepancies between the dose distributions and dose–volume histograms (DVHs) of the body-EDP and head-EDP calibrations. In contrast, the dose distributions and DVHs of the body-EDP and head-EDP calibrations coincided with each other almost perfectly in the ΔHU–ρ{sub e} conversion for 100–140 kV/Sn. The difference between the V{sub 100}’s (the mean planning target volume receiving 100% of the prescribed dose; a DVH parameter) of the body-EDP and head-EDP calibrations could be reduced to less than 1% using the ΔHU–ρ{sub e} conversion, but exceeded 11% for the HU–ρ{sub e} conversion. Conclusions: The ΔHU–ρ{sub e} conversion can be implemented for currently available TPS’s without any modifications or extensions. The ΔHU–ρ{sub e} conversion appears to be a promising method for providing an accurate and reliable inhomogeneity correction in treatment planning for any ill-conditioned scans that include (i) the use of a calibration EDP that is nonequivalent to the patient’s body tissues, (ii) a mismatch between the size of the patient and the calibration EDP, or (iii) a large quantity of high-density and high-atomic-number tissue structures.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Multi-Angle Snowflake Camera Value-Added Product

The Multi-Angle Snowflake Camera (MASC) addresses a need for high-resolution multi-angle imaging of hydrometeors in freefall with simultaneous measurement of fallspeed. As illustrated in Figure 1, the MASC consists of three cameras, separated by 36°, each pointing at an identical focal point approximately 10 cm away. Located immediately above each camera, a light aims directly at the center of depth of field for its corresponding camera. The focal point at which the cameras are aimed lies within a ring through which hydrometeors fall. The ring houses a system of near-infrared emitter-detector pairs, arranged in two arrays separated vertically by 32 mm. When hydrometeors pass through the lower array, they simultaneously trigger all cameras and lights. Fallspeed is calculated from the time it takes to traverse the distance between the upper and lower triggering arrays. The trigger electronics filter out ambient light fluctuations associated with varying sunlight and shadows. The microprocessor onboard the MASC controls the camera system and communicates with the personal computer (PC). The image data is sent via FireWire 800 line, and fallspeed (and camera control) is sent via a Universal Serial Bus (USB) line that relies on RS232-over-USB serial conversion. See Table 1 for specific details on the MASC located at the Oliktok Point Mobile Facility on the North Slope of Alaska. The value-added product (VAP) detailed in this documentation analyzes the raw data (Section 2.0) using Python: images rely on OpenCV image processing library and derived aggregated statistics rely on some clever averaging. See Sections 4.1 and 4.2 for more details on what variables are computed.

47 OTHER INSTRUMENTATION↗
NASA NTRS1976

Liquid rocket disconnects, couplings, fittings, fixed joints, and seals

State of the art and design criteria for components used in liquid propellant rocket propulsion systems to contain and control the flow of fluids involved are discussed. Particular emphasis is placed on the design of components used in the engine systems of boosters and upper stages, and in spacecraft propulsion systems because of the high pressure and high vibration levels to which these components are exposed. A table for conversion of U.S. customary units to SI units is included with a glossary, and a list of NASA space vehicle design criteria monographs issued to September 1976.

Source record↗
NASA NTRS1982

SUMS calibration test report

Calibration was performed on the shuttle upper atmosphere mass spectrometer (SUMS). The results of the calibration and the as run test procedures are presented. The output data is described, and engineering data conversion factors, tables and curves, and calibration on instrument gauges are included. Static calibration results which include: instrument sensitive versus external pressure for N2 and O2, data from each scan of calibration, data plots from N2 and O2, and sensitivity of SUMS at inlet for N2 and O2, and ratios of 14/28 for nitrogen and 16/32 for oxygen are given.

Robertson, G.↗