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At least 973 records · Page 54

All sources NASA NTRS DOE OSTI

NASA NTRS2015

A Summary of Proposed Changes to the Current ICARTT Format Standards and their Implications to Future Airborne Studies

The Atmospheric Science Data Center (ASDC) at NASA Langley Research Center is responsible for the ingest, archive, and distribution of NASA Earth Science data in the areas of radiation budget, clouds, aerosols, and tropospheric chemistry. The ASDC specializes in atmospheric data that is important to understanding the causes and processes of global climate change and the consequences of human activities on the climate. The ASDC currently supports more than 44 projects and has over 1,700 archived data sets, which increase daily. ASDC customers include scientists, researchers, federal, state, and local governments, academia, industry, and application users, the remote sensing community, and the general public.

Northup, Emily↗

NASA NTRS2015

Toolsets for Airborne Data (TAD): Improving Machine Readability for ICARTT Data Files

Early, Amanda Benson↗

NASA NTRS2017

Representing Water Scarcity in Future Agricultural Assessments

Globally, irrigated agriculture is both essential for food production and the largest user of water. A major challenge for hydrologic and agricultural research communities is assessing the sustainability of irrigated croplands under climate variability and change. Simulations of irrigated croplands generally lack key interactions between water supply, water distribution, and agricultural water demand. In this article, we explore the critical interface between water resources and agriculture by motivating, developing, and illustrating the application of an integrated modeling framework to advance simulations of irrigated croplands. We motivate the framework by examining historical dynamics of irrigation water withdrawals in the United States and quantitatively reviewing previous modeling studies of irrigated croplands with a focus on representations of water supply, agricultural water demand, and impacts on crop yields when water demand exceeds water supply. We then describe the integrated modeling framework for simulating irrigated croplands, which links trends and scenarios with water supply, water allocation, and agricultural water demand. Finally, we provide examples of efforts that leverage the framework to improve simulations of irrigated croplands as well as identify opportunities for interventions that increase agricultural productivity, resiliency, and sustainability.

Irrigated Agriculture; Crop Model; Hydrologic Mode↗

DOE OSTI2023

R “SHINY” GUI DEVELOPMENT FOR URANIUM ISOTOPIC ANALYSIS WITH MATRIX-ASSISTED IONIZATION MASS SPECTROMETRY

The international nuclear safeguards community continues to seek rapid, accurate, and precise characterization capabilities for the in-field measurement of uranium isotopic compositions in nuclear facilities. Mass spectrometry (MS) is considered the “gold standard” for analysis of relatively long-lived actinides such as uranium (U) and plutonium; however, conventional MS analysis often requires time consuming sample preparation and complex analytical methodologies that are difficult to perform in-field or in-facility. Matrix assisted ionization (MAI) is a novel ambient ionization MS technique (i.e., MAI-MS) that potentially addresses these challenges due to the relative simplicity of the ionization phenomenon and ruggedness of ambient MS instrumentation. Savannah River National Laboratory (SRNL, USA) has demonstrated this technique for nanogram-level 235U/238U isotope ratio measurements within seconds, with percent-level analytical uncertainties capable of discriminating depleted, natural, and low-enriched uranium. Current experimental work on developing MAI methods for uranium isotopic analysis has been enabled by parallel development of a comprehensive MAI-MS data analysis suite at SRNL. Development of this bespoke data analysis software was necessary because commercially available ambient MS software is poorly suited for uranium isotope ratio measurement. The effort leverages the power of R, a popular open-source programming language, and Shiny, an R package providing tools for graphical user interface (GUI) and web interface coding. This software allows researchers without any programming experience to harness and utilize R’s considerable data analysis/visualization power.

LaBone, Elizabeth D.↗

DOE OSTI2023

Biological and Environmental Research Network Requirements Review (Final Report)

The Energy Sciences Network (ESnet) is the high-performance network user facility for the US Department of Energy (DOE) Office of Science (SC) and delivers highly reliable data transport capabilities optimized for the requirements of data-intensive science. In essence, ESnet is the circulatory system that enables the DOE science mission by connecting all its laboratories and facilities in the US and abroad. ESnet is funded and stewarded by the Advanced Scientific Computing Research (ASCR) program and managed and operated by the Scientific Networking Division at Lawrence Berkeley National Laboratory (LBNL). ESnet is widely regarded as a global leader in the research and education (R&E) networking community. Between August 2022 and April 2023, ESnet and the Office of Biological and Environmental Research (BER) of the DOE SC organized an ESnet requirements review of BER-supported activities. Preparation for these events included identification of key stakeholders: program and facility management, research groups, and technology providers. Each stakeholder group was asked to prepare formal case study documents about its relationship to the BER ESS program to build a complete understanding of the current, near-term, and long-term status, expectations, and processes that will support the science going forward. A series of pre-planning meetings better prepared case study authors for this task, along with guidance on how the review would proceed in a virtual fashion.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

End-User Perspectives on Using Quantitative Real-Time PCR and Genomic Sequencing in the Field

Quantitative real-time PCR and genomic sequencing have become mainstays for performing molecular detection of biological threat agents in the field. There are notional assessments of the benefits, disadvantages, and challenges that each of these technologies offers according to findings in the literature. However, direct comparison between these two technologies in the context of field-forward operations is lacking. Most market surveys, whether published in print form or provided online, are directed to product manufacturers who can address their respective specifications and operations. One method for comparing these technologies is surveying end-users who are best suited for discussing operational capabilities, as they have hands-on experience with state-of-the-art molecular detection platforms and protocols. These end-users include operators in military defense and first response, as well as various research scientists in the public sector such as government and service laboratories, private sector, and civil society such as academia and nonprofit organizations performing method development and executing these protocols in the field. Our objective was to initiate a survey specific to end-users and their feedback. We developed a questionnaire that asked respondents to (1) determine what technologies they currently use, (2) identify the settings where the technologies are used, whether lab-based or field-forward, and (3) rate the technologies according to a set list of criteria. Of particular interest are assessments of sensitivity, specificity, reproducibility, scalability, portability, and discovery power. This article summarizes the findings from the end-user perspective, highlighting technical and operational challenges.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1996

Quantitative Measures for Software Independent Verification and Validation

As software is maintained or reused, it undergoes an evolution which tends to increase the overall complexity of the code. To understand the effects of this, we brought in statistics experts and leading researchers in software complexity, reliability, and their interrelationships. These experts' project has resulted in our ability to statistically correlate specific code complexity attributes, in orthogonal domains, to errors found over time in the HAL/S flight software which flies in the Space Shuttle. Although only a prototype-tools experiment, the result of this research appears to be extendable to all other NASA software, given appropriate data similar to that logged for the Shuttle onboard software. Our research has demonstrated that a more complete domain coverage can be mathematically demonstrated with the approach we have applied, thereby ensuring full insight into the cause-and-effects relationship between the complexity of a software system and the fault density of that system. By applying the operational profile we can characterize the dynamic effects of software path complexity under this same approach We now have the ability to measure specific attributes which have been statistically demonstrated to correlate to increased error probability, and to know which actions to take, for each complexity domain. Shuttle software verifiers can now monitor the changes in the software complexity, assess the added or decreased risk of software faults in modified code, and determine necessary corrections. The reports, tool documentation, user's guides, and new approach that have resulted from this research effort represent advances in the state of the art of software quality and reliability assurance. Details describing how to apply this technique to other NASA code are contained in this document.

Lee, Alice↗

NASA NTRS2014

Anticipated Changes in Conducting Scientific Data-Analysis Research in the Big-Data Era

A Big-Data environment is one that is capable of orchestrating quick-turnaround analyses involving large volumes of data for numerous simultaneous users. Based on our experiences with a prototype Big-Data analysis environment, we anticipate some important changes in research behaviors and processes while conducting scientific data-analysis research in the near future as such Big-Data environments become the mainstream. The first anticipated change will be the reduced effort and difficulty in most parts of the data management process. A Big-Data analysis environment is likely to house most of the data required for a particular research discipline along with appropriate analysis capabilities. This will reduce the need for researchers to download local copies of data. In turn, this also reduces the need for compute and storage procurement by individual researchers or groups, as well as associated maintenance and management afterwards. It is almost certain that Big-Data environments will require a different "programming language" to fully exploit the latent potential. In addition, the process of extending the environment to provide new analysis capabilities will likely be more involved than, say, compiling a piece of new or revised code.We thus anticipate that researchers will require support from dedicated organizations associated with the environment that are composed of professional software engineers and data scientists. A major benefit will likely be that such extensions are of higherquality and broader applicability than ad hoc changes by physical scientists. Another anticipated significant change is improved collaboration among the researchers using the same environment. Since the environment is homogeneous within itself, many barriers to collaboration are minimized or eliminated. For example, data and analysis algorithms can be seamlessly shared, reused and re-purposed. In conclusion, we will be able to achieve a new level of scientific productivity in the Big-Data analysis environments.

Kuo, Kwo-Sen↗

NASA NTRS1984

Pilot climate data system user's guide

Instructions for using the Pilot Climate Data System (PCDS), an interactive, scientific data management system for locating, obtaining, manipulating, and displaying climate-research data are presented. The PCDS currently provides this supoort for approximately twenty data sets. Figures that illustrate the terminal displays which a user sees when he/she runs the PCDS and some examples of the output from this system are included. The capabilities which are described in detail allow a user to perform the following: (1) obtain comprehensive descriptions of a number of climate parameter data sets and the associated sensor measurements from which they were derived; (2) obtain detailed information about the temporal coverage and data volume of data sets which are readily accessible via the PCDS; (3) extract portions of a data set using criteria such as time range and geographic location, and output the data to tape, user terminal, system printer, or online disk files in a special data-set-independent format; (4) access and manipulate the data in these data-set-independent files, performing such functions as combining the data, subsetting the data, and averaging the data; and (5) create various graphical representations of the data stored in the data-set-independent files.

Reph, M. G.↗

DOE OSTI2024

Project Assessment for Biological and Environmental Research: Report from the BER Advisory Committee

The construction, operation, and stewardship of large-scale scientific user facilities and cutting edge capabilities have been integral to the mission of the U.S. Department of Energy (DOE) Office of Science from its earliest days. To help identify and prioritize new or upgraded facilities critical to scientific innovation over the next 10 years, the Office of Science director issued a charge to the federal advisory committees of six of its program offices in December 2023, including the Biological and Environmental Research (BER) program. The charge letter (see p. ii) asked the advisory committees to: 1. Consider what new or upgraded facilities will be necessary to position the Office of Science at the forefront of scientific discovery. 2. Deliver a short letter report describing each facility in terms of two criteria: (a) the potential to contribute to world-leading science in the next decade and (b) the readiness for construction.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS2016

Applications for ICESat-2 Data

NASA;s Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) mission, scheduled to launch no later than April 2018 (and currently slated for October 2017), is being developed to continue the multiyear observations of the earths surface elevation, ice, and clouds started by ICESat. To increase the use of the satellite data after launch, the ICESat-2 mission invested in an applications program aimed at innovatively applying the data in a variety of fields. The program provides a framework for building a broad and well-defined user community during the prelaunch period to maximize the use of data products after launch and to provide early insight into the range of potential uses of the mission data. Ideas and research on how altimetry data will be used for decision making arise from the end users; there-fore, the ICESat-2 mission is extending itself through its applications program.

Brown, Molly E.↗

NASA NTRSDate not supplied

NASA GeneLab Multi-study Visualization Portal

NASA GeneLab has helped advance the field of Space Biology by providing a public repository where researchers can store, share, analyze and visualize the results of space flight related omics experiments. The GeneLab data visualization portal allows any user, regardless of bioinformatics knowledge or access to computational resources, to interact with the experimental data, draw their own conclusions, and gain insights about the effects of space on living systems. These tools help democratize scientific research and foster the NASA Open Science initiative. The new multi-study feature of the GeneLab visualization platform allows users to mine study metadata from RNA sequencing (RNA-seq) experiments to identify samples of interest by filtering datasets based on organism, tissue, assay technology type, and/or factor. Once samples are selected from multiple datasets, users can combine and normalize the sample data, then utilize the visualization displays, including Principal Component Analysis (PCA) plots, to assess sample distributions. Finally, users can perform differential gene expression analysis on the combined data and visualize the results through PCA plots, Volcano plots, Pair plots, Heatmap, Ideogram and Gene Set Enrichment Analysis. All user-generated results and visualizations will be available for download. Here, we present a biological study using samples from multiple GeneLab RNA-seq datasets and analyzed using the multi-study visualization platform to demonstrate inter- and intra-study variability, as well as commonly differentially expressed genes between spaceflight and ground control conditions across datasets. This new feature opens a wide range of possibilities and opportunities for further development including combining other assay technology types and integration with batch effect correction techniques and machine learning applications. Overall, this tool allows users to increase the statistical power of individual experiments, validate hypothesis, identify patterns, and opens the door to new and exciting research.

space biology↗

NASA NTRSDate not supplied

Studying the 2019 Australian Bushfires Disaster using NASA Data: A Data-Driven Storytelling Approach

The 2019-2020 Australian fire season was particularly devastating, with millions of acres of land burned and impacts affecting Australian ecology, local populations and air quality, and the atmosphere. Australia saw unprecedented heat waves, with temperatures reaching 120 F (49.1 C) in January across central and eastern Australia. The fires gave rise to a host of atmospheric phenomenon, including smoke transport and lofting generated by storm-induced by fires, known as pyrocumulonimbus, reaching the stratosphere. NASA’s satellites not only tracked the event in real time, but also gathered data to further inform forecasting and response methods in the future. To better assist the public in understanding the lead up, impacts, and aftermath effects of these fires, the Science Outreach Team at NASA Langley Research Center’s Atmospheric Science Data Center (ASDC) Distributed Active Archive Center (DAAC) used Esri’s storymap tool to guide users through understanding relevant phenomenon, contributing factors, the effects this event has had on global atmospheric composition, and the science behind researching the tie between disasters and public health. The storymap uses data from the ASDC-supported NASA missions Measurements Of Pollution In The Troposphere (MOPITT), Cloud-Aerosol and Infrared Pathfinder Satellite Observation (CALIPSO), Clouds and the Earth’s Radiant Energy System (CERES), the Stratospheric Aerosol and Gas Experiment (SAGE III), and Multi-angle Imaging SpectroRadiometer (MISR). By using data-driven storytelling to communicate impacts of a large fire event, we hope to provide an accessible, engaging science outreach tool format.

Sanjana Paul↗

NASA NTRS2023

Simulations of Zero Boiloff, Densification, and Solidification in a Large-Scale Liquid Hydrogen Tank

The current research utilizes an Energy of Fluid (EOF) approach to develop a finite volume-based Computation Fluid Dynamic (CFD) model to create a benchmark simulation of the densification of liquid hydrogen (LH2) in an experimental Integrated Refrigeration and Storage (IRAS) tank at the Kennedy Space Center (KSC). The computational code will incorporate the FLUENT pressure-based model with User Defined Functions (UDF) to implement the EOF model. The enhanced model will solve the energy equation in terms of internal energy and provide temperature and pressure calculations for a given tank geometry. Specifically, a convection term will be added to an already existing code for a more accurate simulation of LH2 densification. However, currently the research focuses on utilizing User Defined Scalars (UDS) with FLUENT to show the built-in solvers are as accurate as the written UDS. This will reduce the computational time down significantly by utilizing an already built in solver for the momentum equation. A custom UDF has been written to solve transient and steady state conduction, and results obtained using the UDF agree with results obtained using the built-in FLUENT solver. Currently, a convection UDF is being added and will be verified using known solutions for solidification and validated with the experimental results from the Cryogenics Test Laboratory (CTL) at KSC for the IRAS densification process.

Colin Philip Mahony↗

DOE OSTI2025

Developing Digital Twin Visualizations: A Methodology and Case Study on Chemical Separation Processing

As advances in digital engineering continue to push the technological boundaries, digital twin (DT) visualizations for diagnostics and safeguards advancement become much more feasible and practical. DTs generate large and complex data streams that require effective user interfaces to provide monitoring and diagnostic capabilities. Unfortunately, while these frameworks exist, there is not much research on the systematic documentation of human–computer interaction (HCI) for DT visualization. This work presents a dual-mode visualization methodology (two dimensional [2D] graphical user interface dashboard and 3D mixed reality) designed to support diagnostic tasks in DT systems and building on a validated framework and applying established HCI principles. The methodology is demonstrated through a case study of aqueous processing at Idaho National Laboratory, using experimental data from the chemical solvent extraction runs. Our interfaces display real-time alerts and monitoring to inform users of safeguards anomalies. The interfaces use immersive 3D mixed-reality visualization for further system and experiment investigation. This work demonstrates how the systematic application of HCI principles can inform DT visualization design for diagnostic and safeguards applications. While formal user evaluation studies remain as future work, this paper documents the systematic design methodology and demonstrates a proof-of-concept implementation.

3D visualization↗

DOE OSTI2023

What Makes Passengers Uncomfortable In Vehicles Today? An Exploratory Study of Current Factors that May Influence Acceptance of Future Autonomous Vehicles

Autonomous vehicles have the potential to transform lives by providing transportation to a wider range of users. However, with this new method of transportation, user acceptance and comfort are critical for widespread adoption. This exploratory study aims to investigate what makes passengers uncomfortable in existing vehicles to inform the design of future autonomous vehicles. In order to predict what may impact user acceptance for a diverse rider population for future autonomous vehicles, it is important to understand what makes a broad range of passengers uncomfortable today. In this study, interviews were conducted for a total of 75 participants from three diverse groups, including 20 automotive engineering graduate students who are building an autonomous concept vehicle, 21 non-technical adults, and 34 senior citizens. The results revealed both topics which made different groups of passengers uncomfortable as well as how these varied between the groups. The leading contributors to the highest discomfort for all groups were being a passenger in situations with a distracted driver, being in a vehicle that is following too closely, being near a vehicle that is following too closely, and being in foggy conditions. In addition, the results showed that passenger discomfort can be attributed to a broad range of factors ranging from behaviors of the driver/vehicle that one is traveling with/in, the behaviors of other surrounding vehicles, the environmental conditions and the vehicle’s interior, all of which may differ between different groups of passengers. This research provides important findings and insights into factors that may influence users’ acceptance and use of future autonomous vehicles.

Mims, Lauren K.↗

NASA NTRS1987

Automating the parallel processing of fluid and structural dynamics calculations

The NASA Lewis Research Center is actively involved in the development of expert system technology to assist users in applying parallel processing to computational fluid and structural dynamic analysis. The goal of this effort is to eliminate the necessity for the physical scientist to become a computer scientist in order to effectively use the computer as a research tool. Programming and operating software utilities have previously been developed to solve systems of ordinary nonlinear differential equations on parallel scalar processors. Current efforts are aimed at extending these capabilities to systems of partial differential equations, that describe the complex behavior of fluids and structures within aerospace propulsion systems. This paper presents some important considerations in the redesign, in particular, the need for algorithms and software utilities that can automatically identify data flow patterns in the application program and partition and allocate calculations to the parallel processors. A library-oriented multiprocessing concept for integrating the hardware and software functions is described.

Arpasi, Dale J.↗

NASA NTRS1987

Automating the parallel processing of fluid and structural dynamics calculations

The NASA Lewis Research Center is actively involved in the development of expert system technology to assist users in applying parallel processing to computational fluid and structural dynamic analysis. The goal of this effort is to eliminate the necessity for the physical scientist to become a computer scientist in order to effectively use the computer as a research tool. Programming and operating software utilities have previously been developed to solve systems of ordinary nonlinear differential equations on parallel scalar processors. Current efforts are aimed at extending these capabilties to systems of partial differential equations, that describe the complex behavior of fluids and structures within aerospace propulsion systems. This paper presents some important considerations in the redesign, in particular, the need for algorithms and software utilities that can automatically identify data flow patterns in the application program and partition and allocate calculations to the parallel processors. A library-oriented multiprocessing concept for integrating the hardware and software functions is described.

Arpasi, Dale J.↗