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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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DOE OSTI2023

Unfolding Cross Sections: A Brief Introduction

Unfolding Cross Sections has been around forever, so there is nothing new in this report. I only authored this report because I fear that the current generation of ENDF data creators and users may not be familiar with this concept. This will be a brief introduction to unfolding, so I will only present one example, namely, ENDF/B-VIII U235. Let me stress that in selecting this example it was only because of the obvious importance of U235. In this selection I am not making any judgement as to the quality of this evaluation. Indeed, as I will keep reminding readers throughout this report, in my opinion the evaluators did an excellent job, and this evaluation meets the needs of many users. But it does violate ENDF-102 [1] that states MT=5 can be used for complex reactions at high energy. This evaluation uses MT=5 all the way down to the traditional ENDF lower energy limit at 1.0e-5 eV. There are no complex reactions at 1.0e-5 eV and this is certainly not high energy. To illustrate unfolding I will start from what I call their current U235 BEST physics evaluation and present what I call my BEST engineering evaluation, that better meets my needs – and more importantly the needs of the codes I use to process and use ENDF data. You, the reader, are free to select either – or neither – for your personal use. ENDF has been such a GREAT success because of the close bond between data producers and data users, who have supplied user feedback to improve the next generation of ENDF data. Here I am merely one of those users, and this is my feedback.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS2016

Earthdata Search Usability Study Process

User experience (UX) design is the process of enhancing user satisfaction by improving various aspects of the user's interaction with an application or website. One aspect of UX design is usability, or the extent to which an application can be used to to accomplish tasks efficiently, effectively, and with satisfaction. NASA's Earthdata Search Client recently underwent a focused usability testing project to measure usability and gain valuable user feedback and insights to increase usability for its end-users. This presentation focuses on the process by which the usability tests were administered and the lessons learned throughout the process.

UI↗

DOE OSTI2024

Assessment and validation of NEAMS tools for high-fidelity multiphysics transient modeling of microreactors: Application of NEAMS codes to perform multiphysics modeling analyses of micro-reactor concepts

The NEAMS Multiphysics Applications team aims at providing assessment of code useability and functionality for microreactor design and analyses, together with demonstration of their capabilities to properly capture the steady-state and time-dependent behavior of different microreactor concepts. In FY-24, significant progress was achieved in improving multi-physics models of several microreactors systems: HP-MR, GC-MR and KRUSTY. These efforts focused on solving more complex multiphysics problems enabled by enhanced tools capability, verifying and validating results obtained, providing feedback to developers for suggested improvements, and sharing these models to facilitate user training. A series of new multiphysics transients were completed on the HP-MR (using Griffin/BISON/Sockeye) with core startup transient, control drum inadvertent rotation accident, and hydrogen leakage from hydride moderator (also including SWIFT). On the GC-MR, a new full-core model was developed and analyzed through a series of new multiphysics (Griffin/BISON/SAM) transients to simulate moderator leakage (also including SWIFT), flow blockage and coolant depressurization. Additional and updated TRISO failure analyses were completed on the HP-MR unit-cell and GC-MR assembly models leveraging improved TRISO modeling capabilities. The amount of SiC failure following accidental transients at end-of-life was null. However, GC-MR assembly TRISO analysis highlighted Pd penetration rate can be problematic and may require design changes on the studied microreactor concept. The neutronics discrepancies observed on the KRUSTY model in previous years were resolved using hybrid set of Monte Carlo/Deterministic cross-sections. The multiphysics (Griffin neutronics / BISON thermal-mechanics) 15₵ insertion transient simulation displayed good agreement when comparing with experimental data. Initial modeling of the 30 ₵ reactivity insertion also displays promising results. Such close agreement provides important validation data that can be leveraged by the NEAMS program and by microreactor vendors to support licensing of their technology. Finally, important experience was gathered with the NEAMS tools leading to several user feedback shared with tools developers, especially with regards to MOOSE mesh generator and Griffin. This project led to many publications demonstrating modeling capabilities, and to three models shared on the Virtual Test Bed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRSDate not supplied

Using OPeNDAP In The Cloud to Connect NASA Data Centers and Support Open Data Access

NASA DAACs (Distributed Active Archive Centers), including the Goddard Earth Sciences Data Information and Services Center (GES DISC), are currently transitioning from on-premises servers to a shared Earthdata Cloud in order to build more interoperability, cross-collaboration, and streamlined services between their data centers. Migrating its on-premises OPeNDAP service to the cloud is a critical component of making this interconnectedness between NASA DAACs possible. To improve their cloud services, GES DISC is leveraging open-source platforms like Github to collect user feedback, create use cases, and develop resources to enable real-time learning for users about OPeNDAP in the cloud. This presentation gives an overview of the OPeNDAP in the cloud, resources developed to access this service, and considerations for improved user guidance and experience to further support NASA's commitment to the Open-Source Science Initiative (OSSI).

Christopher Battisto↗

NASA NTRSDate not supplied

Informing NLP Learning Tasks by Tracking User Features: An ASRS Use Case using Kaona

There has been growing interest in utilizing natural language processing (NLP) algorithms in Aviation Safety. This interest has extended to leveraging the decades of records publicly available on the Aviation Safety Reporting System (ASRS). While related literature has given more emphasis in lessons learned from the narratives, our prior work has focused on using NLP to support narrative search in the ASRS. Specifically, we evaluated if the use of alternative search mechanisms to keyword search, such as the retrieval of related narratives even without matching keywords could improve narrative discovery. A difficulty in experimenting alternative search mechanisms in any information retrieval task is the lack of ground truth. To address this limitation, we propose Kaona, a lightweight interface which enables the prototyping of alternative search retrieval tasks, by tracking user experience both explicitly (user-specified feedback), or implicitly (user navigation through interface affordances). Differently from distracting requests for feedback during user navigation, Kaona collects explicit feedback from users by mapping them to affordances which support the user workflow, while obtaining ground truth information for learning tasks.

human-computer-interaction↗

NASA NTRSDate not supplied

Game Based Learning For Earth Science Applications Training

Current NASA Earth capacity development programs employ mechanisms ranging from online resource sharing, and virtual and in-person trainings to share knowledge. While these programs are highly successful at engaging individuals around the world – in 2018, over 8000 individuals and over 2000 institutions from all 50 US states and over 140 countries were engaged through over 150 projects and trainings – user feedback has highlighted the desire for expanded hands-on, practical experiences in incorporating NASA EO insights with localized data and actions. We aim to address this gap by leveraging the benefits of game-based learning to build user skills in integrating NASA and local EO data to guide decisions for climate resiliency and hazard planning. This project is being executed as a two-phase crowdsourced challenge: 1) Phase 1 will require a well-researched product concept that reflects an understanding of NASA’s Earth data and tools and user needs, and proposes an innovative and interactive game or extended reality experience to train users in identifying relevant NASA data and applying insights to their climate resiliency decisions; 2) Winners of Phase 1 will be provided seed funding to develop a working prototype of the product. We aim to award 1-3 final winners to support the development of more than one game, thereby ensuring that NASA's diverse audiences around the world can access training games that best suit their needs and capabilities. This EO training game project fits in the NASA Earth Science Applied Sciences Program’s Capacity Development Program, contributing to the program mission of “helping people around the world better understand [NASA’s Earth] data and find ways to use them” (https://appliedsciences.nasa.gov/what-we-do/capacity-building). The final training game will complement existing programmatic activities of workforce development, trainings, and collaborative projects, while providing the unique value of providing interactive experiences to users and collecting real-time data and feedback to improve NASA’s Earth applications’ products and services related to climate resilience.

Human centered design↗

NASA NTRS1989

The telerobot workstation testbed for the shuttle aft flight deck: A project plan for integrating human factors into system design

The human factors design process in developing a shuttle orbiter aft flight deck workstation testbed is described. In developing an operator workstation to control various laboratory telerobots, strong elements of human factors engineering and ergonomics are integrated into the design process. The integration of human factors is performed by incorporating user feedback at key stages in the project life-cycle. An operator centered design approach helps insure the system users are working with the system designer in the design and operation of the system. The design methodology is presented along with the results of the design and the solutions regarding human factors design principles.

Sauerwein, Timothy↗

NASA NTRSDate not supplied

Advancements in Blowing Dust Detection at Night via Machine Learning

This presentation introduces operational users to a machine-learning based Dust Probability product developed by the NASA SPoRT program for the application of detecting and monitoring blowing dust plumes at night. Advances in earth observing satellites has improved monitoring and detection of dust both day and night through derived imagery such as the Dust RGB. However, limitations of the RGB at night result in less contrast between dust and land surface features, as seen by the user. A Machine Learning (ML) model has been developed and applied to GOES-16 ABI to overcome this limitation and improve nighttime dust detection. The ML capability is a subset of Artificial Intelligence methods. In this case the Dust ML model was developed using a simple Random Forest (RF) model, typically used to solve classification challenges (or to provide regression type output). The goal was to leverage the strengths of the RF model to learn how to identify blowing dust, and hence, overcome the limitation of a user trying to detect blowing dust within the satellite imagery by eye alone. A brief description of the ML model development will be provided. However, the focus of the presentation will be on the initial user feedback from the assessment of this tool for the 2022 blowing dust events of March through April. During this time several users across the U.S. Southwest collaborated to apply this Dust ML product at night as a complement to the existing Dust RGB in order to determine if it provided greater operational efficiency and value.

Machine Learning↗

NASA NTRS1994

Software interface verifier

A Telos study of 40 recent subsystem deliveries into the DSN at JPL found software interface testing to be the single most expensive and error-prone activity, and the study team suggested creating an automated software interface test tool. The resulting Software Interface Verifier (SIV), which was funded by NASA/JPL and created by Telos, employed 92 percent software reuse to quickly create an initial version which incorporated early user feedback. SIV is now successfully used by developers for interface prototyping and unit testing, by test engineers for formal testing, and by end users for non-intrusive data flow tests in the operational environment. Metrics, including cost, are included. Lessons learned include the need for early user training. SIV is ported to many platforms and can be successfully used or tailored by other NASA groups.

Soderstrom, Tomas J.↗

NASA NTRS1994

A Compositional Relevance Model for Adaptive Information Retrieval

There is a growing need for rapid and effective access to information in large electronic documentation systems. Access can be facilitated if information relevant in the current problem solving context can be automatically supplied to the user. This includes information relevant to particular user profiles, tasks being performed, and problems being solved. However most of this knowledge on contextual relevance is not found within the contents of documents, and current hypermedia tools do not provide any easy mechanism to let users add this knowledge to their documents. We propose a compositional relevance network to automatically acquire the context in which previous information was found relevant. The model records information on the relevance of references based on user feedback for specific queries and contexts. It also generalizes such information to derive relevant references for similar queries and contexts. This model lets users filter information by context of relevance, build personalized views of documents over time, and share their views with other users. It also applies to any type of multimedia information. Compared to other approaches, it is less costly and doesn't require any a priori statistical computation, nor an extended training period. It is currently being implemented into the Computer Integrated Documentation system which enables integration of various technical documents in a hypertext framework.

Mathe, Nathalie↗

NASA NTRSDate not supplied

How GES DISC is Opening Doors to Open Science

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is one of 12 NASA Earth Observing System data centers that document, process, archive, and distribute data from Earth science missions and related projects. GES DISC hosts numerous Earth Science products through various data formats and supports their access with several programming and website tools. The User Needs team at GES DISC is responsible for producing tutorials and resources to teach these tools, collecting and engaging with user feedback, and collaborating with other NASA data centers to enable science creation for everyone. This poster presentation outlines how GES DISC, and the User Needs team, are committed to enabling open science.

Christopher Battisto↗

NASA NTRSDate not supplied

How GES DISC is Opening Doors to Open Science

Christopher Battisto↗

NASA NTRS2018

NASA's Earth Observing Data and Information System - Near-Term Challenges

NASA's Earth Observing System Data and Information System (EOSDIS) has been a central component of the NASA Earth observation program since the 1990's. EOSDIS manages data covering a wide range of Earth science disciplines including cryosphere, land cover change, polar processes, field campaigns, ocean surface, digital elevation, atmosphere dynamics and composition, and inter-disciplinary research, and many others. One of the key components of EOSDIS is a set of twelve discipline-based Distributed Active Archive Centers (DAACs) distributed across the United States. Managed by NASA's Earth Science Data and Information System (ESDIS) Project at Goddard Space Flight Center, these DAACs serve over 3 million users globally. The ESDIS Project provides the infrastructure support for EOSDIS, which includes other components such as the Science Investigator-led Processing systems (SIPS), common metadata and metrics management systems, specialized network systems, standards management, and centralized support for use of commercial cloud capabilities. Given the long-term requirements, and the rapid pace of information technology and changing expectations of the user community, EOSDIS has evolved continually over the past three decades. However, many challenges remain. Challenges addressed in this paper include: growing volume and variety, achieving consistency across a diverse set of data producers, managing information about a large number of datasets, migration to a cloud computing environment, optimizing data discovery and access, incorporating user feedback from a diverse community, keeping metadata updated as data collections grow and age, and ensuring that all the content needed for understanding datasets by future users is identified and preserved.

Remote Sensing↗

NASA NTRS2007

General Mission Analysis Tool (GMAT) Architectural Specification. Draft

Early in 2002, Goddard Space Flight Center (GSFC) began to identify requirements for the flight dynamics software needed to fly upcoming missions that use formations of spacecraft to collect data. These requirements ranged from low level modeling features to large scale interoperability requirements. In 2003 we began work on a system designed to meet these requirement; this system is GMAT. The General Mission Analysis Tool (GMAT) is a general purpose flight dynamics modeling tool built on open source principles. The GMAT code is written in C++, and uses modern C++ constructs extensively. GMAT can be run through either a fully functional Graphical User Interface (GUI) or as a command line program with minimal user feedback. The system is built and runs on Microsoft Windows, Linux, and Macintosh OS X platforms. The GMAT GUI is written using wxWidgets, a cross platform library of components that streamlines the development and extension of the user interface Flight dynamics modeling is performed in GMAT by building components that represent the players in the analysis problem that is being modeled. These components interact through the sequential execution of instructions, embodied in the GMAT Mission Sequence. A typical Mission Sequence will model the trajectories of a set of spacecraft evolving over time, calculating relevant parameters during this propagation, and maneuvering individual spacecraft to maintain a set of mission constraints as established by the mission analyst. All of the elements used in GMAT for mission analysis can be viewed in the GMAT GUI or through a custom scripting language. Analysis problems modeled in GMAT are saved as script files, and these files can be read into GMAT. When a script is read into the GMAT GUI, the corresponding user interface elements are constructed in the GMAT GUI. The GMAT system was developed from the ground up to run in a platform agnostic environment. The source code compiles on numerous different platforms, and is regularly exercised running on Windows, Linux and Macintosh computers by the development and analysis teams working on the project. The system can be run using either a graphical user interface, written using the open source wxWidgets framework, or from a text console. The GMAT source code was written using open source tools. GSFC has released the code using the NASA open source license.

Hughes, Steven P.↗

NASA NTRSDate not supplied

Developing and Validating Measurement Scales During Pandemic Conditions: A Case Study with the Scale for Habitat Usability

The Scale for Habitat Usability (SHU) is a standardized subjective scale created for collecting user feedback on habitat/vehicle design at NASA. The second phase of the study occurred during COVID-19. The scale developers were unable to collect psychometric data in person. This was challenging because the SHU is meant to collect post-use ratings after users complete a task in a habitat. Non-traditional approaches were employed to evaluate the SHU in terms of validity and reliability.

Ian Robertson↗

NASA NTRS2024

Usability Evaluation of NASA TOPS Open Science 101

This report presents a usability evaluation of NASA’s Open Science 101 (OS101) interface. It offers design recommendations for improving the user experience (UX) and user interface (UI) of the initial self-paced OS101 release. The author initially conducted an independent heuristic evaluation, followed by an analysis of written user feedback to corroborate findings. Overall, the usability evaluation found that the OS101 interface offers a linear and interactive UX, with areas for improvement across five major, three minor, and two cosmetic aspects of usability.

Human-Computer Interaction↗

DOE OSTI2021

A Guide to Using GitHub for Developing and Versioning Data Standards and Reporting Formats

Abstract Data standardization combined with descriptive metadata facilitate data reuse, which is the ultimate goal of the Findable, Accessible, Interoperable, and Reusable (FAIR) principles. Community data or metadata standards are increasingly created through an approach that emphasizes collaboration between various stakeholders. Such an approach requires platforms for collaboration on the development process that centers on sharing information and receiving feedback. Our objective in this study was to conduct a systematic review to identify data standards and reporting formats that use version control for developing data standards and to summarize common practices, particularly in earth and environmental sciences. Out of 108 data standards and reporting formats identified in our review, 32 used GitHub as the version control platform, and no other platforms were used. We found no universally accepted methodology for developing and publishing data standards. Many GitHub repositories did not use key features that could help developers to gather user feedback, or to create and revise standards that build on previous work. We provide guidance for community‐driven standard development and associated documentation on GitHub based on a systematic review of existing practices.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Probabilistic Modeling of Commercial Building Occupancy Patterns Using Location-Based Map Data: Preprint

Considering occupancy patterns is crucial to simulate buildings' energy use. Current energy models use inputs that simplify the actual diversity in occupancy into static occupancy patterns and are not able to represent the numerous variations in occupancy patterns between buildings and across different locations. Recently, inferring occupancy schedules from metered electricity consumption data was used to model occupancy in commercial buildings. However, the translation from metered data to occupancy schedules requires many assumptions that might not capture the reality, and the process is hindered by the availability of data from advanced metering infrastructure. With the development of information technologies, occupancy modeling should not be limited to traditional approaches. The prevalence of social networks and location services with real-time user feedback provides publicly accessible data via Maps Application Programming Interfaces (APIs) such as Google Maps, SafeGraph, Mapbox, Foursquare, etc. This paper presents an automated framework for modeling parametric occupancy patterns using such APIs to calibrate commercial district buildings' energy models. This process includes three main steps: data extraction and processing, parametric schedules generation, and schedules integration. We demonstrated this framework in districts where we used maps API to generate more accurate behavioral patterns for operations and electric vehicle charging events. We used these patterns to determine differences in energy use across key sociodemographic and spatial parameters. The presented method has the potential for worldwide applications. Users can utilize this framework to extract data for selected locations of interest to create more realistic behavioral patterns for commercial facilities across different districts.

building energy modeling↗