SEARCH · Search NASA

Results for “graphic user interface”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 163 records · Page 9

All sources NASA NTRS DOE OSTI

DOE OSTI2020

Updated Primers Generated for SCALE 6.2 for KENO V.a and KENO-VI

Primers were developed and published for the use of the KENO V.a and KENO-VI codes in 2005 and 2008, respectively. These primers were both developed for SCALE 5 using the GeeWiz graphical user interface (GUI). Many new capabilities have been added to the transport codes since the release of these primers. The GUI was also changed to Fulcrum with the release of SCALE 6.2. For these reasons, updated versions of both primers were developed for a planned released in September 2020. The KENO V.a and KENO-VI codes are almost always run within the associated CSAS5 and CSAS6 sequences within SCALE, so the primers use the sequences and do not address running the codes in stand-alone mode.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2020

Updated Primers Generated for SCALE 6.2 for KENO V.a and KENO-VI [Slides]

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1997

Interactive Educational Tool for Turbofan and Afterburning Turbojet Engines

A workstation-based, interactive educational computer program has been developed at the NASA Lewis Research Center to aid in the teaching and understanding of turbine engine design and analysis. This tool has recently been extended to model the performance of two-spool turbofans and afterburning turbojets. The program solves for the flow conditions through the engine by using classical one-dimensional thermodynamic analysis found in various propulsion textbooks. Either an approximately thermally perfect or calorically perfect gas can be used in the thermodynamic analysis. Students can vary the design conditions through a graphical user interface; engine performance is calculated immediately. A variety of graphical formats are used to present results, including numerical results, moving bar charts, and student-generated temperature versus entropy (Ts), pressure versus specific volume (pv), and engine performance plots. The package includes user-controlled printed output, restart capability, online help screens, and a browser that displays teacher-prepared lessons in turbomachinery. The program runs on a variety of workstations or a personal computer using the UNIX operating system and X-based graphics. It is being tested at several universities in the midwestern United States; the source and executables are available free from the author.

Benson, Thomas J.↗

DOE OSTI2022

Big Data Analytics for Long-Term Meteorological Observations at Hanford Site

A growing number of physical objects with embedded sensors with typically high volume and frequently updated data sets has accentuated the need to develop methodologies to extract useful information from big data for supporting decision making. This study applies a suite of data analytics and core principles of data science to characterize near real-time meteorological data with a focus on extreme weather events. To highlight the applicability of this work and make it more accessible from a risk management perspective, a foundation for a software platform with an intuitive Graphical User Interface (GUI) was developed to access and analyze data from a decommissioned nuclear production complex operated by the U.S. Department of Energy (DOE, Richland, USA). Exploratory data analysis (EDA), involving classical non-parametric statistics, and machine learning (ML) techniques, were used to develop statistical summaries and learn characteristic features of key weather patterns and signatures. The new approach and GUI provide key insights into using big data and ML to assist site operation related to safety management strategies for extreme weather events. Specifically, this work offers a practical guide to analyzing long-term meteorological data and highlights the integration of ML and classical statistics to applied risk and decision science.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2020

LaRC SmartLab Apps For Instrument Control And Data Processing: Optical Micrometer Data Visualizer

The LaRC Smart Lab applications are a series of software tools to greatly enhance researcher efficiency by streamlining and automating workflows. Python scripts and applications are increasingly being used in scientific workflows, including for instrument control and data processing. Interactive Python scripting environments such as Jupyter Lab provide powerful tools for using Python. In some use cases, the development of standalone applications with dedicated graphical user interfaces (GUIs) can enhance the utility of the code and open it up to more users, including non-programmers. Here, we describe a GUI based optical micrometer data visualization application developed as part of the LaRC SmartLab project. We highlight its use in visualizing experimental data and briefly discuss its implementation to give pointers to programmers who wish develop work based on this application's or similar co de.

LaRC SmartLab↗

DOE OSTI2020

WHONDRS-GUI: a web application for global survey of surface water metabolites

Background The Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) is a consortium that aims to understand complex hydrologic, biogeochemical, and microbial connections within river corridors experiencing perturbations such as dam operations, floods, and droughts. For one ongoing WHONDRS sampling campaign, surface water metabolite and microbiome samples are collected through a global survey to generate knowledge across diverse river corridors. Metabolomics analysis and a suite of geochemical analyses have been performed for collected samples through the Environmental Molecular Sciences Laboratory (EMSL). The obtained knowledge and data package inform mechanistic and data-driven models to enhance predictions of outcomes of hydrologic perturbations and watershed function, one of the most critical components in model-data integration. To support efforts of the multi-domain integration and make the ever-growing data package more accessible for researchers across the world, a Shiny/R Graphical User Interface (GUI) called WHONDRS-GUI was created. Results The web application can be run on any modern web browser without any programming or operational system requirements, thus providing an open, well-structured, discoverable dataset for WHONDRS. Together with a context-aware dynamic user interface, the WHONDRS-GUI has functionality for searching, compiling, integrating, visualizing and exporting different data types that can easily be used by the community. The web application and data package are available at https://data.ess-dive.lbl.gov/view/doi:10.15485/1484811 , which enables users to simultaneously obtain access to the data and code and to subsequently run the web app locally. The WHONDRS-GUI is also available for online use at Shiny Server ( https://xmlin.shinyapps.io/whondrs/ ).

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2020

LaRC SmartLab Apps For Instrument Control and Data Processing: Laboratory Environment Monitor

The LaRC SmartLab applications are a series of software tools to greatly enhance researcher efficiency by streamlining and automating workflows. Python scripts and applications are increasingly being used in scientific workflows, including for instrument control and data processing. Interactive Python scripting environments such as JupyterLab provide powerful tools for using Python. In some use cases, the development of standalone applications with dedicated graphical user interfaces can enhance the utility of the code and open it up to more users, including non-programmers. Here, we describe a Python based application for communicating with, and displaying data from, iTHX Temperature, Humidity, and Dew Point probes. We discuss the set up and use of the application as well as its implementation. We also highlight the use of Simulated probes to enable users and developers to familiarize with or debug the application, even when they do not have access to the physical hardware in the laboratory.

LaRC SmartLab↗

NASA NTRS1997

A Comparison of Two Control Display Unit Concepts on Flight Management System Training

One of the biggest challenges for a pilot in the transition to a 'glass' cockpit is understanding the flight management system (FMS). Because of both the complex nature of the FMS and the pilot-FMS interface, a large portion of transition training is devoted to the FMS. The current study examined the impact of the primary pilot-FMS interface, the control display unit (CDU), on FMS training. Based on the hypothesis that the interface design could have a significant impact on training, an FMS simulation with two separate interfaces was developed. One interface was similar to a current-generation design, and the other was a multiwindows CDU based on graphical user interface techniques. For both application and evaluation reasons, constraints were applied to the graphical CDU design to maintain as much similarity as possible with the conventional CDU. This preliminary experiment was conducted to evaluate the interface effects on training. Sixteen pilots with no FMS experience were used in a between-subjects test. A time-compressed, airline-type FMS training environment was simulated. The subjects were trained to a fixed-time criterion, and performance was measured in a final, full-mission simulation context. This paper describes the technical approach, simulation implementation, and experimental results of this effort.

Abbott, Terence S.↗

DOE OSTI2024

The Pixel Anomaly Detection Tool : a user-friendly GUI for classifying detector frames using machine-learning approaches

Data collection at X-ray free electron lasers has particular experimental challenges, such as continuous sample delivery or the use of novel ultrafast high-dynamic-range gain-switching X-ray detectors. This can result in a multitude of data artefacts, which can be detrimental to accurately determining structure-factor amplitudes for serial crystallography or single-particle imaging experiments. Here, a new data-classification tool is reported that offers a variety of machine-learning algorithms to sort data trained either on manual data sorting by the user or by profile fitting the intensity distribution on the detector based on the experiment. This is integrated into an easy-to-use graphical user interface, specifically designed to support the detectors, file formats and software available at most X-ray free electron laser facilities. The highly modular design makes the tool easily expandable to comply with other X-ray sources and detectors, and the supervised learning approach enables even the novice user to sort data containing unwanted artefacts or perform routine data-analysis tasks such as hit finding during an experiment, without needing to write code.

47 OTHER INSTRUMENTATION↗

NASA NTRS2025

PACE Water Resources: Demonstrating the Use of NASA's PACE Hyperspectral Ocean Color Instrument Data for Enhanced Coastal Management

This project developed tools to support the future use of Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) hyperspectral imagery in water resource monitoring and research by NASA DEVELOP teams and members of the PACE applications community. We sought to address a need for support in processing and visualizing hyperspectral PACE Ocean Color Instrument (OCI) data among researchers and decision-makers working in coastal water quality management and harmful algal bloom (HAB) monitoring. To supplement the day of simulated PACE imagery available, we used Aqua MODIS earth observations with Level 3 processing from March 2022 to build a Python graphical user interface (GUI) for visualizing ocean biogeochemical parameters relevant to the early detection and monitoring of HABs. We used simulated PACE OCI Level 2 data derived from the Python Top of Atmosphere Simulation Tool (PyTOAST) to build Jupyter Notebooks for band subset and selection. The Level 3 PACE Viewer components support users with quick visualizations as well as the creation of geoTIFFs and time-series. The Level 2 Jupyter Notebooks address users’ concerns over the volume and complexity of hyperspectral imagery. The PACE Viewer is useful for visual inspection and netCDF data processing but should not be used for geospatial analysis. Once PACE launches, this tool will alleviate the technical burdens of working with hyperspectral data and support the early detection and monitoring of HABs using PACE satellite imagery.

Python Top of Atmosphere Simulation Tool↗

NASA NTRS1995

The Evaluation of Two CDU Concepts and Their Effects on FMS Training

One of the biggest challenges for a pilot in the transition to a "glass" cockpit is understanding the Flight Management System (FMS). This is due to both the complex nature of the FMS and to the pilot-FMS interface. For these reasons, a large portion of transition training is devoted to the FMS. The intent of the current study was to examine the impact of the primary pilot-FMS interface, the Control Display Unit (CDU), on FMS training. The hypothesis of this study was that the interface design could have a significant impact on training. An FMS simulation was developed with two separate interfaces. One interface was similar to a current-generation design and the other was a multi-windows CDU based on graphical user interface techniques. For both application and evaluation reasons, constraints were applied to the graphical CDU design to maintain as much similarity as possible with the conventional CDU.

Abbott, Terence S.↗

NASA NTRS2000

Interactive Software System Developed to Study How Icing Affects Airfoil Performance (Phase 1 Results)

SmaggIce (Surface Modeling and Grid Generation for Iced Airfoils), which is being developed at the NASA Glenn Research Center at Lewis Field, is an interactive software system for data probing, boundary smoothing, domain decomposition, and structured grid generation and refinement. All these steps are required for aerodynamic performance prediction using structured, grid-based computational fluid dynamics (CFD), as illustrated in the following figure. SmaggIce provides the underlying computations to perform these functions, as well as a graphical user interface to control and interact with them, and graphics to display the results.

Choo, Yung K.↗

NASA NTRS2008

The Interim: Until You Achieve an Operationally Responsive Ground System

Everyone wants to achieve a 'Responsive' Ground Data System (GDS), but that takes time. What do you do in the interim? Our group, called the Integration, Test and Deployment Team (ITD), is a group of responsive engineers whose primary focus is to assist JPL projects to successfully adapt, test, integrate and deploy their ground data system. The team configures and adapts the GDS for a project, so that analysts, engineers and scientist do not need to be experts in the GDS to operate it. The team has developed a human interface to accommodate all types of users. It provides Graphical User Interfaces (GUI's) for those that want GUI's, command line interfaces for those that want control, and selection button interfaces for other users. The cornerstone of a responsive Ground Data System is responsive people. Without individuals who can be aware of a project's changing needs and requirements, how can the GDS become responsive?.

Ground Data System (GDS)↗

NASA NTRS2008

The Interim : until you achieve an operationally responsive ground system

ground data system (GDS)↗

NASA NTRS1992

AXAF user interfaces for heterogeneous analysis environments

The AXAF Science Center (ASC) will develop software to support all facets of data center activities and user research for the AXAF X-ray Observatory, scheduled for launch in 1999. The goal is to provide astronomers with the ability to utilize heterogeneous data analysis packages, that is, to allow astronomers to pick the best packages for doing their scientific analysis. For example, ASC software will be based on IRAF, but non-IRAF programs will be incorporated into the data system where appropriate. Additionally, it is desired to allow AXAF users to mix ASC software with their own local software. The need to support heterogeneous analysis environments is not special to the AXAF project, and therefore finding mechanisms for coordinating heterogeneous programs is an important problem for astronomical software today. The approach to solving this problem has been to develop two interfaces that allow the scientific user to run heterogeneous programs together. The first is an IRAF-compatible parameter interface that provides non-IRAF programs with IRAF's parameter handling capabilities. Included in the interface is an application programming interface to manipulate parameters from within programs, and also a set of host programs to manipulate parameters at the command line or from within scripts. The parameter interface has been implemented to support parameter storage formats other than IRAF parameter files, allowing one, for example, to access parameters that are stored in data bases. An X Windows graphical user interface called 'agcl' has been developed, layered on top of the IRAF-compatible parameter interface, that provides a standard graphical mechanism for interacting with IRAF and non-IRAF programs. Users can edit parameters and run programs for both non-IRAF programs and IRAF tasks. The agcl interface allows one to communicate with any command line environment in a transparent manner and without any changes to the original environment. For example, the authors routinely layer the GUI on top of IRAF, ksh, SMongo, and IDL. The agcl, based on the facilities of a system called Answer Garden, also has sophisticated support for examining documentation and help files, asking questions of experts, and developing a knowledge base of frequently required information. Thus, the GUI becomes a total environment for running programs, accessing information, examining documents, and finding human assistance. Because the agcl can communicate with any command-line environment, most projects can make use of it easily. New applications are continually being found for these interfaces. It is the authors' intention to evolve the GUI and its underlying parameter interface in response to these needs - from users as well as developers - throughout the astronomy community. This presentation describes the capabilities and technology of the above user interface mechanisms and tools. It also discusses the design philosophies guiding the work, as well as hopes for the future.

Mandel, Eric↗

DOE OSTI2020

SRNL Analysis of ICCWR LCM and WAMS data for Corrosion and Cracking (FY2020 Progress Report)

The development of algorithms for machine learning and data analysis for the 3013 Surveillance Program is a collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). For corrosion detection, Laser Confocal Microscope (LCM) or Wide Area 3D Measurement System (WAMS) data is extracted from large binary files, with software written to convert the data to physical attributes (e.g. height, color and grayscale values; all as functions of a location in a plane projection). It is the objective of this project to produce a user-friendly interface that incorporated all operations needed to perform surface examination. For this reason, a Matlab-based Graphical User Interface (GUI) was created to integrate data input with software developed for processing and evaluation. In summary, the GUI permits selective downloading of binary data, interrogation of attributes, data labeling, flagging of significant features, execution of Machine Learning (ML) algorithms, output of parameters for trained ML algorithms, reports of ML model accuracy with respect to labeled data, and generation of graphical representations of various analyses.

3013 corrosion↗

NASA NTRS2014

Intuitive Tools for the Design and Analysis of Communication Payloads for Satellites

In an effort to make future communications satellite payload design more efficient and accessible, two tools were created with intuitive graphical user interfaces (GUIs). The first tool allows payload designers to graphically design their payload by using simple drag and drop of payload components onto a design area within the program. Information about each picked component is pulled from a database of common space-qualified communication components sold by commerical companies. Once a design is completed, various reports can be generated, such as the Master Equipment List. The second tool is a link budget calculator designed specifically for ease of use. Other features of this tool include being able to access a database of NASA ground based apertures for near Earth and Deep Space communication, the Tracking and Data Relay Satellite System (TDRSS) base apertures, and information about the solar system relevant to link budget calculations. The link budget tool allows for over 50 different combinations of user inputs, eliminating the need for multiple spreadsheets and the user errors associated with using them. Both of the aforementioned tools increase the productivity of space communication systems designers, and have the colloquial latitude to allow non-communication experts to design preliminary communication payloads.

communication↗

NASA NTRS2004

Tower Mesonetwork Climatology and Interactive Display Tool

Forecasters at the 45th Weather Squadron and Spaceflight Meteorology Group use data from the tower network over the Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) to evaluate Launch Commit Criteria, and issue and verify forecasts for ground operations. Systematic biases in these parameters could adversely affect an analysis, forecast, or verification. Also, substantial geographical variations in temperature and wind speed can occur under specific wind directions. To address these concerns, the Applied Meteorology Unit (AMU) developed a climatology of temperatures and winds from the tower network, and identified the geographical variation and significant tower biases. The mesoclimate is largely driven by the complex land-water interfaces across KSC/CCAFS. Towers with close proximity to water typically had much warmer nocturnal temperatures and higher wind speeds throughout the year. The strongest nocturnal wind speeds occurred from October to March whereas the strongest mean daytime wind speeds occurred from February to May. These results of this project can be viewed by forecasters through an interactive graphical user interface developed by the AMU. The web-based interface includes graphical and map displays of mean, standard deviation, bias, and data availability for any combination of towers, variables, months, hours, and wind directions.

Case, Jonathan L.↗