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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Enhanced Atmospheric Research at the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) (Final Report)

The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) was an international scientific expedition into the central Arctic sea ice to study the changing atmosphere-ice-ocean system and its key physical, chemical, and biological processes in a way that will support improved understanding and modeling of Arctic climate. The US Department of Energy’s Atmospheric Research Measurement (ARM) Program operated its second ARM Mobile Facility (AMF2) as a major contribution to the expedition, and the Atmospheric System Research (ASR) program supported this project to maximize the success of DOE’s involvement in MOSAiC. This project has enabled the successful collection of data through support of field operations plans, in-field operational implementation, oversight of real-time data quality, and representing DOE’s interests within the broader international MOSAiC endeavor. The project has promoted scientific research by facilitating and leading a number of efforts to develop value-added products that will support research, including products related to aerosol properties, trace gases, cloud properties, snowfall, the surface energy budget, and a merged product designed for model assessment. These products and related analyses have also contributed to numerous scientific publications on related themes as well as direct model evaluation. Lastly, the project has engaged in a great deal of communication and outreach activities that help to publicize and promote both MOSAiC and DOE’s specific contribution to a broad audience that includes the scientific community, program management, policy makers, and the general public.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Thermal simulation of the EIC HSR interconnect module - RF fingers

The Electron Ion Collider (EIC) Hadron Storage Ring (HSR) will reuse most of the existing superconducting magnets from the RHIC storage ring. However, the existing beam vacuum chamber and stripline BPMs will not be compatible with the planned EIC hadron bunches that will have a 3x higher intensity and be 10x shorter, and some operational scenarios with large radial offsets of the beam in the vacuum chamber. To address these challenges, a copper coated beam screen will be implemented, the existing RHIC stripline BPMs will be shielded and an interconnect module design, including new BPM will be installed adjacent to the existing BPMs. A thermal analysis of the new arc BPM interconnect housing has been conducted to assess the heating caused by beam induced resistive wall heating and electron cloud heating. An analysis of the BPM module has been made and reported separately. This report will focus on the other side of the interconnect module, containing the RF fingers.

43 PARTICLE ACCELERATORS↗
NASA NTRS1981

Computation of averaged monthly zonal albedo utilizing the solar zenith angle, properties of clear and cloudy atmospheres

The zonal temporal averages of albedos at the top of the atmosphere were considered as a function of the length of the day. The length of the day were used to determine the average daily values of mu sub 0(=Cos of the solar zenith angle, theta sub 0). Polynominal fits of the slope and intercept functions of A sub s (cloud-free albedo) and A sub c(cloud albedo) as function of Cos theta sub 0 were obtained by using the sample values of albedo corresponding to solar zenith angles from 0 to 90 deg with interval of 5 deg. The daily zonal values of mu sub 0 and the surface albedos were used to compute the daily zonal values of albedos at the top of the clear and cloudy atmosphere. The monthly zonal cloud fractions were used to compute planetary albedo A at the top of the atmosphere. The global values of monthly albedos A sub s, A sub c and A were computed by using the weighting function defined as the difference of the sins of zonal values of latitudes. The computer program implementation is also described.

Dhuria, H.↗
NASA NTRS1991

A hotspot model for leaf canopies

The hotspot effect, which provides important information about canopy structure, is modeled using general principles of environmental physics as driven by parameters of interest in remote sensing, such as leaf size, leaf shape, leaf area index, and leaf angle distribution. Specific examples are derived for canopies of horizontal leaves. The hotspot effect is implemented within the framework of the model developed by Suits (1972) for a canopy of leaves to illustrate what might occur in an agricultural crop. Because the hotspot effect arises from very basic geometrical principles and is scale-free, it occurs similarly in woodlands, forests, crops, rough soil surfaces, and clouds. The scaling principles advanced are also significant factors in the production of image spatial and angular variance and covariance which can be used to assess land cover structure through remote sensing.

Jupp, David L. B.↗
DOE OSTI2020

Acquisition and Implementation of a Comprehensive Environmental Permits Linking Tool at Savannah River Site - 20234

Historically, Savannah River Nuclear Solutions LLC (SRNS) tracked environmental regulatory commitments and the requirements from hundreds of permits at the Savannah River Site (SRS) using several separate methods, making integrated compliance assurance cumbersome and labor-intensive. When SRNS experienced an increase in environmental issues in 2017, SRNS management and U.S. Department of Energy - Savannah River (DOE-SR) management decided a single, proactive approach was needed to capture environmental permit information (including regulations, Consent Orders, DOE Orders, and any other state or federally issued statement of requirements), track the tasks necessary to ensure compliance with these requirements, and thereby mitigate the risk of noncompliance. SRNS developed a list of mandatory objectives that the tool must meet to function as a Comprehensive Environmental Permits Linking Tool (CEPLT). A key requirement was the ability to map Site permits to their governed locations and display the associated requirements at the compliance point (e.g., outfall, stack, waste unit, etc.). Several options included modifying existing onsite resources, building a custom onsite solution, purchasing an off-the-shelf solution, and contracting an offsite developer to build a custom solution. SRNS concluded an off-the-shelf solution with configuration and customization options would provide the flexibility to fit the unique needs of Savannah River Site (SRS) while taking advantage of industry-tested software and providing a reduced deployment timeline. SRNS chose Gensuite{sup R} a, a cloud-based solution that offers numerous a la carte applications in the environmental, health, and safety arenas, as the best candidate. SRNS selected three (3) integrated applications (Compliance Calendar, Permit Manager, and Mapper) to function as the CEPLT. The Compliance Calendar module allows for creation and tracking of regulatory commitment tasks assigned to responsible environmental professionals. Permit Manager organizes permits and other requirement documents, linking the commitments in each to Compliance Calendar tasks and/or implementing procedures. Mapper provides GIS capability for mapping the data from the other two modules to their physical onsite locations. The CEPLT was configured to allow for other SRS Site Tenants to eventually utilize the applications. Additionally, DOE-SR uses the CEPLT to provide an overview of contractor environmental compliance activities and to organize DOE-specific documents and tasks. The CEPLT fulfilled the requirement of meeting current compliance needs as well as providing the ability to grow as new organizations are incorporated and functionality is expanded. SRNS now uses the CEPLT to more effectively manage permit requirements, improve knowledge transfer, and increase the Site's overall protection of the environment, the Site worker, and the public. Possible future uses of the system include integration of mobile applications for timely communication of potential non-compliant conditions and DOE complex-wide deployment allowing for enhanced DOE site and Head Quarters oversight. Implementation of CEPLT will result in cost savings, both in terms of dollars and man-hours. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1992

Adaptation of the University of Wisconsin High Spectral Resolution Lidar for Polarization and Multiple Scattering Measurements

A new implementation of the High Spectral Resolution Lidar (HSRL) in an instrument van which allows measurements during field experiments is described. The instrument was modified to provide measurements of depolarization. In addition, both the signal amplitude and depolarization variations with receiver field of view are simultaneously measured. These modifications allow discrimination of ice clouds from water clouds and observation of multiple scattering contributions to the lidar return.

Eloranta, E. W.↗
NASA NTRS1999

HALOE Algorithm Improvements for Upper Tropospheric Sounding

This report details the ongoing efforts by GATS, Inc., in conjunction with Hampton University and University of Wyoming, in NASA's Mission to Planet Earth UARS Science Investigator Program entitled "HALOE Algorithm Improvements for Upper Tropospheric Soundings." The goal of this effort is to develop and implement major inversion and processing improvements that will extend HALOE measurements further into the troposphere. In particular, O3, H2O, and CH4 retrievals may be extended into the middle troposphere, and NO, HCl and possibly HF into the upper troposphere. Key areas of research being carried out to accomplish this include: pointing/tracking analysis; cloud identification and modeling; simultaneous multichannel retrieval capability; forward model improvements; high vertical-resolution gas filter channel retrievals; a refined temperature retrieval; robust error analyses; long-term trend reliability studies; and data validation. The current (first-year) effort concentrates on the pointer/tracker correction algorithms, cloud filtering and validation, and multi-channel retrieval development. However, these areas are all highly coupled, so progress in one area benefits from and sometimes depends on work in others.

McHugh, Martin J.↗
NASA NTRS2000

HALOE Algorithm Improvements for Upper Tropospheric Soundings

This report details the ongoing efforts by GATS, Inc., in conjunction with Hampton University and University of Wyoming, in NASA's Mission to Planet Earth UARS Science Investigator Program entitled "HALOE Algorithm Improvements for Upper Tropospheric Sounding." The goal of this effort is to develop and implement major inversion and processing improvements that will extend HALOE measurements further into the troposphere. In particular, O3, H2O, and CH4 retrievals may be extended into the middle troposphere, and NO, HCl and possibly HF into the upper troposphere. Key areas of research being carried out to accomplish this include: pointing/tracking analysis; cloud identification and modeling; simultaneous multichannel retrieval capability; forward model improvements; high vertical-resolution gas filter channel retrievals; a refined temperature retrieval; robust error analyses; long-term trend reliability studies; and data validation. The current (first year) effort concentrates on the pointer/tracker correction algorithms, cloud filtering and validation, and multichannel retrieval development. However, these areas are all highly coupled, so progress in one area benefits from and sometimes depends on work in others.

Thompson, Robert E.↗
NASA NTRS2001

HALOE Algorithm Improvements for Upper Tropospheric Sounding

This report details the ongoing efforts by GATS, Inc., in conjunction with Hampton University and University of Wyoming, in NASA's Mission to Planet Earth UARS Science Investigator Program entitled "HALOE Algorithm Improvements for Upper Tropospheric Sounding." The goal of this effort is to develop and implement major inversion and processing improvements that will extend HALOE measurements further into the troposphere. In particular, O3, H2O, and CH4 retrievals may be extended into the middle troposphere, and NO, HCl and possibly HF into the upper troposphere. Key areas of research being carried out to accomplish this include: pointing/tracking analysis; cloud identification and modeling; simultaneous multichannel retrieval capability; forward model improvements; high vertical-resolution gas filter channel retrievals; a refined temperature retrieval; robust error analyses; long-term trend reliability studies; and data validation. The current (first year) effort concentrates on the pointer/tracker correction algorithms, cloud filtering and validation, and multichannel retrieval development. However, these areas are all highly coupled, so progress in one area benefits from and sometimes depends on work in others.

Thompson, Robert E.↗
DOE OSTI2022

Traceability of Surface Longwave Irradiance Measurements to SI Using the IRIS Radiometers: Preprint

The World Radiation Center at PMOD/WRC is operated on behalf of the WMO. The Infrared Radiometry Section of the WRC (WRC-IRS) provides traceability of downwelling atmospheric longwave radiation measured with pyrgeometers by comparison to the World Infrared Standard Group (WISG) [1]. As has been discussed previously [2], the current implementation of the WISG measures lower longwave irradiances than the two candidate reference radiometers IRIS (Infrared Integrating Sphere Radiometer) and the ACP (Absolute Cavity Pyrgeometer). To validate the findings reported in [2], additional measurements since that publication in 2014 have been performed and are discussed in this paper. Specifically, Measurements during cloud-free nights at PMOD/WRC between the WISG and IRIS radiometers, A field campaign at the Atmospheric Radiation Monitoring Site (ARM) at Southern Great Plains, Oklahoma with IRIS, ACP, AERI (Atmospheric Emittance Radiance Interferometer) and WISG traceable pyrgeometers, Laboratory comparison between the reference blackbody of PMOD/WRC with the hemispherical blackbody developed by PTB.

ACR↗
NASA NTRS2012

The Invasive Species Forecasting System (ISFS): An iRODS-Based, Cloud-Enabled Decision Support System for Invasive Species Habitat Suitability Modeling

The Invasive Species Forecasting System (ISFS) is an online decision support system that allows users to load point occurrence field sample data for a plant species of interest and quickly generate habitat suitability maps for geographic regions of interest, such as a national park, monument, forest, or refuge. Target customers for ISFS are natural resource managers and decision makers who have a need for scientifically valid, model- based predictions of the habitat suitability of plant species of management concern. In a joint project involving NASA and the Maryland Department of Natural Resources, ISFS has been used to model the potential distribution of Wavyleaf Basketgrass in Maryland's Chesapeake Bay Watershed. Maximum entropy techniques are used to generate predictive maps using predictor datasets derived from remotely sensed data and climate simulation outputs. The workflow to run a model is implemented in an iRODS microservice using a custom ISFS file driver that clips and re-projects data to geographic regions of interest, then shells out to perform MaxEnt processing on the input data. When the model completes, all output files and maps from the model run are registered in iRODS and made accessible to the user. The ISFS user interface is a web browser that uses the iRODS PHP client to interact with the ISFS/iRODS- server. ISFS is designed to reside in a VMware virtual machine running SLES 11 and iRODS 3.0. The ISFS virtual machine is hosted in a VMware vSphere private cloud infrastructure to deliver the online service.

Gill, Roger↗
DOE OSTI2015

Exploiting Redundancy and Application Scalability for Cost-Effective, Time-Constrained Execution of HPC Applications on Amazon EC2

The use of clouds to execute high-performance computing (HPC) applications has greatly increased recently. Clouds provide several potential advantages over traditional supercomputers and in-house clusters. The most popular cloud is currently Amazon EC2, which provides fixed-cost and variable-cost, auction-based options. The auction market trades lower cost for potential interruptions that necessitate checkpointing; if the market price exceeds the bid price, a node is taken away from the user without warning. We explore techniques to maximize performance per dollar given a time constraint within which an application must complete. Specifically, we design and implement multiple techniques to reduce expected cost by exploiting redundancy in the EC2 auction market. We then design an adaptive algorithm that selects a scheduling algorithm and determines the bid price. We show that our adaptive algorithm executes programs up to seven times cheaper than using the on-demand market and up to 44 percent cheaper than the best non-redundant, auction-market algorithm. We extend our adaptive algorithm to incorporate application scalability characteristics for further cost savings. In conclusion, we show that the adaptive algorithm informed with scalability characteristics of applications achieves up to 56 percent cost savings compared to the expected cost for the base adaptive algorithm run at a fixed, user-defined scale.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Dynamic Provisioning and Execution of HPC Workflows Using Python

High-performance computing (HPC) workflows over the last several decades have proven to assist in the understanding of scientific phenomena and the production of better products, more quickly, and at reduced cost. However, HPC workflows are difficult to implement and use for a variety of reasons. In this paper, we describe the development of the Python-based cumulus, which addresses many of these barriers. cumulus is a platform for the dynamic provisioning and execution of HPC workflows. cumulus provides the infrastructure needed to build applications that leverage traditional or Cloud-based HPC resources in their workflows. Lastly, we demonstrate the use of cumulus in both web and desktop simulation applications, as well as in an Apache Spark-based analysis application.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

PhytoOracle: Scalable, modular phenomics data processing pipelines

As phenomics data volume and dimensionality increase due to advancements in sensor technology, there is an urgent need to develop and implement scalable data processing pipelines. Current phenomics data processing pipelines lack modularity, extensibility, and processing distribution across sensor modalities and phenotyping platforms. To address these challenges, we developed PhytoOracle (PO), a suite of modular, scalable pipelines for processing large volumes of field phenomics RGB, thermal, PSII chlorophyll fluorescence 2D images, and 3D point clouds. PhytoOracle aims to ( i ) improve data processing efficiency; ( ii ) provide an extensible, reproducible computing framework; and ( iii ) enable data fusion of multi-modal phenomics data. PhytoOracle integrates open-source distributed computing frameworks for parallel processing on high-performance computing, cloud, and local computing environments. Each pipeline component is available as a standalone container, providing transferability, extensibility, and reproducibility. The PO pipeline extracts and associates individual plant traits across sensor modalities and collection time points, representing a unique multi-system approach to addressing the genotype-phenotype gap. To date, PO supports lettuce and sorghum phenotypic trait extraction, with a goal of widening the range of supported species in the future. At the maximum number of cores tested in this study (1,024 cores), PO processing times were: 235 minutes for 9,270 RGB images (140.7 GB), 235 minutes for 9,270 thermal images (5.4 GB), and 13 minutes for 39,678 PSII images (86.2 GB). These processing times represent end-to-end processing, from raw data to fully processed numerical phenotypic trait data. Repeatability values of 0.39-0.95 (bounding area), 0.81-0.95 (axis-aligned bounding volume), 0.79-0.94 (oriented bounding volume), 0.83-0.95 (plant height), and 0.81-0.95 (number of points) were observed in Field Scanalyzer data. We also show the ability of PO to process drone data with a repeatability of 0.55-0.95 (bounding area).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The E3SM Diagnostics Package (E3SM Diags v2.7): a Python-based diagnostics package for Earth system model evaluation

Abstract. The E3SM Diagnostics Package (E3SM Diags) is a modern, Python-based Earth system model (ESM) evaluation tool (with Python module name e3sm_diags), developed to support the Department of Energy (DOE) Energy Exascale Earth System Model (E3SM). E3SM Diags provides a wide suite of tools for evaluating native E3SM output, as well as ESM data on regular latitude–longitude grids, including output from Coupled Model Intercomparison Project (CMIP) class models. E3SM Diags is modeled after the National Center for Atmospheric Research (NCAR) Atmosphere Model Working Group (AMWG, 2022) diagnostics package. In its version 1 release, E3SM Diags included a set of core essential diagnostics to evaluate the mean physical climate from model simulations. As of version 2.7, more process-oriented and phenomenon-based evaluation diagnostics have been implemented, such as analysis of the quasi-biennial oscillation (QBO), the El Niño–Southern Oscillation (ENSO), streamflow, the diurnal cycle of precipitation, tropical cyclones, ozone and aerosol properties. An in situ dataset from DOE's Atmospheric Radiation Measurement (ARM) program has been integrated into the package for evaluating the representation of simulated cloud and precipitation processes. This tool is designed with enough flexibility to allow for the addition of new observational datasets and new diagnostic algorithms. Additional features include customizable figures; streamlined installation, configuration and execution; and multiprocessing for fast computation. The package uses an up-to-date observational data repository maintained by its developers, where recent datasets are added to the repository as they become available. Finally, several applications for the E3SM Diags module were introduced to fit a diverse set of use cases from the scientific community.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2006

Satellite Breakup Risk Mitigation

Many satellite breakups occur as a result of an explosion of stored energy on-board spacecraft or rocket-bodies. These breakups generate a cloud of tens or possibly hundreds of thousands of debris fragments which may pose a transient elevated threat to spaceflight crews and vehicles. Satellite breakups pose a unique threat because the majority of the debris fragments are too small to be tracked from the ground. The United States Human Spaceflight Program is currently implementing a risk mitigation strategy that includes modeling breakup events, establishing action thresholds, and prescribing corresponding mitigation actions in response to satellite breakups.

Leleux, Darrin P.↗
NASA NTRS2017

Method for the Collection, Gravimetric and Chemical Analysis of Nonvolatile Residue (NVR) on Surfaces

Nonvolatile residue (NVR), sometimes referred to as molecular contamination is the term used for the total composition of the inorganic and high boiling point organic components in particulates and molecular films deposited on critical surfaces surrounding space structures, with the particulate and NVR contamination originating primarily from pre-launch operations. The "nonvolatile" suggestion from the terminology NVR implies that the collected residue will not experience much loss under ambient conditions. NVR has been shown to have a dramatic impact on the ability to perform optical measurements from platforms based in space. Such contaminants can be detected early by the controlled application of various detection techniques and contamination analyses. Contamination analyses are the techniques used to determine if materials, components, and subsystems can be expected to meet the performance requirements of a system. Of particular concern is the quantity of NVR contaminants that might be deposited on critical payload surfaces from these sources. Subsequent chemical analysis of the contaminant samples by infrared spectroscopy and gas chromatography mass spectrometry identifies the components, gives semi-quantitative estimates of contaminant thickness, indicates possible sources of the NVR, and provides guidance for effective cleanup procedures. In this report, a method for the collection and determination of the mass of NVR was generated by the authors at NASA Langley Research Center. This report describes the method developed and implemented for collecting NVR contaminants, and procedures for gravimetric and chemical analysis of the residue obtained. The result of this NVR analysis collaboration will help pave the way for Langley's ability to certify flight hardware outgassing requirements in support of flight projects such as Stratospheric Aerosol and Gas Experiment III (SAGE III), Clouds and the Earth's Radiant Energy System (CERES), Materials International Space Station Experiment - X (MISSE-X), and Doppler Aerosol Wind Lidar (DAWN).

Gordon, Keith↗
DOE OSTI2021

Real-time Data Analytics for Condition Monitoring of Complex Industrial Systems

Modern industrial systems are now fitted with several sensors for condition monitoring. This is advantageous because these sensors can provide mass amounts of data that have the potential for aiding in tasks such as fault detection, diagnosis, and prognostics. However, the information valuable for performing these tasks is often clouded in noise and must be mined from high-dimensional data structures. Therefore, this dissertation presents a data analytics framework for performing these condition monitoring tasks using high-dimensional data. Demonstrations of this framework are detailed for challenges related to power generation systems in automobiles, power plants, and aircraft engines. These implementations leverage data collected from state-of-the-art, industry class test-rigs. Results indicate the ability of this framework to develop effective methodologies for condition monitoring of complex systems.

Peters, Benjamin↗