Results for “gui” — Page 38

NASA NTRS2024

Automation of the ICME Workflow Incorporating Material Digital Twins at Different Length Scales Within a Robust Information Management System

Recent successes in Integrated Computational Materials Engineering (ICME) have demonstrated the potential in designing ‘fit-for-purpose’ materials for a given application in a cost and time efficient manner. However, the material design process must contain a level of judicious automation in the material decision process; that is implementing some optimization algorithms to truly enable the benefits of ICME, particularly when considering materials at multiple length and time scales. Furthermore, the ability to effectively store developed material models, experimental data used for validation, and link models at multiple length and time scales must be implemented to ensure traceability across the material design process, such that the data gathered can be leveraged towards efficient material design. To enable such an optimization scheme a robust framework must exist: (1) that can capture changes made at a given length scale, (2) automatically propagate changes upstream to the highest scale, and (3) evaluate the material’s performance at the structural level. In this work, a developed framework for tracking material changes, automatically running the necessary simulations to determine the properties at the next highest scale, and saving each iteration of the design process to maintain the application’s digital thread is presented for polymer matrix composites (PMCs). The Automated Information Management Across Organizations and Scales (AIMAOS) program offers users an interactive graphical user interface (GUI) for defining constituent materials, building lamina and laminates, and applying effective laminate properties to finite element and composite optimization third party software. At each length scale, the necessary input files are automatically written, and subsequent analysis tools are called to solve for effective properties at the next scale, which are then read by the AIMAOS tool and displayed to the user. As changes are made to the material at lower length scales, information is automatically propagated upstream to higher length scales, and changes made are automatically tracked and versioned to maintain traceability during the design process. The AIMAOS tools serves as the first step in enabling optimized design of composites from the nano to the macroscale for a given application.

Brandon L Hearley↗

NASA NTRSDate not supplied

RadLab: A Comprehensive Database and Graphical and Programming Interfaces for Space Radiation Data

RadLab, a component of the NASA Open Science Data Repository (OSDR), is a database of radiation measurements from multiple instruments and spacecraft that provides visual and programmatic interfaces for interrogation and retrieval of these data. The attributes of data available through RadLab include spacecraft, types of radiation sensing instruments, locations within the spacecraft (e.g. ISS modules), associated celestial bodies, trajectories, and spacecraft coordinates; the primary type of data is the absorbed dose rate, as well as flux and dose equivalent rate where available. The application programming interface (API) implements a request syntax for retrieval of timestamped data filtered by various combinations of such attributes; the graphical user interface (GUI) extends this functionality with visualizations (time series plots, comparison plots, geospatial visualizations) which provide easy means to assess data availability, iteratively refine search parameters, interactively inspect the data, and export target data subsets. Datasets are continuously being added to the RadLab database as part of the rolling release process. Investigators from multiple countries, including the US, Canada, Germany, Bulgaria, Hungary, Italy, Japan, Russia and the Czech Republic, have committed to provide data from their instruments in and beyond low Earth orbit. The current release contains datasets provided by US and international collaborators and includes readings from multiple modules of the ISS, the BioSentinel CubeSat, Chang’e 4, the Lunar Reconnaissance Orbiter, the ExoMars Orbiter, and the Curiosity rover. Datasets are associated with respective RadLab knowledgebase articles which include instrument descriptions and provide bibliographical references. RadLab aims to provide a comprehensive, dynamic compendium of space radiation data, enabling the scientific community to perform analyses of data from multiple detectors and to determine the radiation environment of research missions and experiments. Some of its applications include inference of absorbed radiation dose for NASA GeneLab payloads, and training predictive models as part of the 2024 FDL-X challenge. The platform is actively expanding and seeking additional data, with plans to also cover past (e.g. Shuttle, Mir) and future (e.g. Artemis) missions. The RadLab Working Group has been created to aid in this process as well as to foster collaborations among data contributors and users, to develop standards for data harmonization, and to guide the development of the platform, with the goal to establish the use of RadLab in space radiation research and to advance our understanding of the radiation environment in outer space.

Kirill Grigorev↗

NASA NTRSDate not supplied

RadLab: A Comprehensive Database and Graphical and Programming Interfaces for Biologically Relevant Space Radiation Data

RadLab, a new component of the NASA Open Science Data Repository (OSDR), comprises a database of radiation measurements relevant to space biology, and visual and programmatic interfaces for interrogation and retrieval of these data. The attributes of data available through RadLab include spacecraft, types of radiation sensing instruments, locations within the spacecraft (e.g. modules of the ISS), associated celestial bodies, trajectories, and spacecraft coordinates. The application programming interface (API) implements a request syntax for retrieval of timestamped data filtered by various combinations of such attributes; the graphical user interface (GUI) extends this functionality with visualizations, such as spacecraft schematics, time series plots, geospatial visualizations, and provides easy means to iteratively refine search parameters, inspect the data on the fly, and download target subsets. The release of RadLab currently available to the public contains datasets provided by US and international collaborators and focuses on data recorded on the ISS. Investigators from multiple countries, including the US, Canada, Germany, Bulgaria, Hungary, Italy, Japan, Russia and the Czech Republic, have committed to provide data from their instruments in and beyond low Earth orbit; RadLab will also soon expand to include past (e.g. Shuttle and Mir) and future (e.g. Artemis) data. RadLab will provide a comprehensive, dynamic compendium of space radiation data, enabling the scientific community to perform analyses of data from multiple detectors and to determine the radiation environment of research missions and experiments. The RadLab Working Group has been formed to foster collaborations among data contributors and users, to identify data sources, to put in place standards for data harmonization, and to guide the development of the platform, with the goal to establish the use of RadLab in space radiation research and to advance our understanding of the space radiation environment in human habitats.

database↗

NASA NTRSDate not supplied

RadLab: A Comprehensive Database and Graphical and Programming Interfaces for Space Radiation Data

RadLab, a component of the NASA Open Science Data Repository (OSDR), is a database of radiation measurements from multiple instruments and spacecraft that provides visual and programmatic interfaces for interrogation and retrieval of these data. The attributes of data available through RadLab include spacecraft, types of radiation sensing instruments, locations within the spacecraft (e.g. ISS modules), associated celestial bodies, trajectories, and spacecraft coordinates; the primary type of data is the absorbed dose rate, as well as flux and dose equivalent rate where available. The application programming interface (API) implements a request syntax for retrieval of timestamped data filtered by various combinations of such attributes; the graphical user interface (GUI) extends this functionality with visualizations (time series plots, comparison plots, geospatial visualizations) which provide easy means to assess data availability, iteratively refine search parameters, interactively inspect the data, and export target data subsets. Datasets are continuously being added to the RadLab database as part of the rolling release process. Investigators from multiple countries, including the US, Canada, Germany, Bulgaria, Hungary, Italy, Japan, Russia and the Czech Republic, have committed to provide data from their instruments in and beyond low Earth orbit. The current release contains datasets provided by US and international collaborators and includes readings from multiple modules of the ISS, the BioSentinel CubeSat, Chang’e 4, the Lunar Reconnaissance Orbiter, the ExoMars Orbiter, and the Curiosity rover. Datasets are associated with respective RadLab knowledgebase articles which include instrument descriptions and provide bibliographical references. RadLab aims to provide a comprehensive, dynamic compendium of space radiation data, enabling the scientific community to perform analyses of data from multiple detectors and to determine the radiation environment of research missions and experiments. Some of its applications include inference of absorbed radiation dose for NASA GeneLab payloads, and training predictive models as part of the 2024 FDL-X challenge. The platform is actively expanding and seeking additional data, with plans to also cover past (e.g. Shuttle, Mir) and future (e.g. Artemis) missions. The RadLab Working Group has been created to aid in this process as well as to foster collaborations among data contributors and users, to develop standards for data harmonization, and to guide the development of the platform, with the goal to establish the use of RadLab in space radiation research and to advance our understanding of the radiation environment in outer space.

Kirill Grigorev↗

NASA NTRSDate not supplied

STARscan: Spatial Targeting and Alignment Rig for Scanning

The Spatial Targeting and Alignment Rig for Scanning (STARScan) is a 3D photogrammetry system developed at NASA Ames Research Center to address bottlenecks in pre/post-test scanning of arcjet test articles. It reduces scan time from 15 minutes with handheld laser scanners to under 2 minutes, while maintaining high accuracy (±0.2-0.5 mm). STARScan integrates an array of cameras, a 3D-printed rack, turntable, and LED light panels, all controlled via a user-friendly graphical user interface (GUI). The system offers tools for scan visualization, mesh analysis, and data export, automating tasks such as alignment of pre/post-test scans, material recession measurements, surface roughness assessment, and curvature analysis. By integrating scanning, imaging, and post-processing into one application, STARScan significantly improves efficiency in scanning and analyzing arcjet test samples.

Ablation↗

DOE OSTI2015

Stonix, Version 0.x

STONIX is a program for configuring UNIX and Linux computer operating systems. It applies configurations based on the guidance from publicly accessible resources such as: NSA Guides, DISA STIGs, the Center for Internet Security (CIS), USGCB and vendor security documentation. STONIX is written in the Python programming language using the QT4 and PyQT4 libraries to provide a GUI. The code is designed to be easily extensible and customizable.

Source record↗

DOE OSTI2015

WarpVisit

WarpVisit is an insitu simulation application that integrates the Warp laser plasma accelerator simulation framework with Visit a parallel visualization application. WarpVisit is written in python and supports interactive or live mode where user can connect to Warp with the Visit GUI and batch mode for batch for non-interactive use on high-performance computing resources.

Loring, Burlen↗

DOE OSTI2016

ROSSTEP v1.3

ROSSTEP is a system for sequentially running roslaunch, rosnode, and bash scripts automatically, for use in Robot Operating System (ROS) applications. The system consists of YAML files which define actions and conditions. A python file parses the code and runs actions sequentially using the sys and subprocess python modules. Between actions, it uses various ROS-based code to check conditions required to proceed, and only moves on to the next action when all the necessary conditions have been met. Included is rosstep-creator, a QT application designed to create the YAML files required for ROSSTEP. It has a nearly one-to-one mapping from interface elements to YAML output, and serves as a convenient GUI for working with the ROSSTEP system.

Allevato, Adam↗

DOE OSTI2016

Pole Figure Explorer v. 1.8

This software is employed for 3D visualization of X-ray diffraction (XRD) data with functionality for slicing, reorienting, isolating and plotting of 2D color contour maps and 3D renderings of large datasets. The program makes use of the multidimensionality of textured XRD data where diffracted intensity is not constant over a given set of angular positions (as dictated by the three defined dimensional angles of phi, chi, and two-theta). Datasets are rendered in 3D with intensity as a scaler which is represented as a rainbow color scale. A GUI interface and scrolling tools along with interactive function via the mouse allow for fast manipulation of these large datasets so as to perform detailed analysis of diffraction results with full dimensionality of the diffraction space.

Van Benthem, Mark H.↗

DOE OSTI2016

Responsive Image Inline Filter

RIIF is a contributed module for the Drupal php web application framework (drupal.org). It is written as a helper or sub-module of other code which is part of version 8 "core Drupal" and is intended to extend its functionality. It allows Drupal to resize images uploaded through the user-facing text editor within the Drupal GUI (a.k.a. "inline images") for various browser widths. This resizing is already done foe other images through the parent "Responsive Image" core module. This code extends that functionality to inline images.

Freeman, Ian↗

DOE OSTI2017

Chemical detection system and related methods

A chemical detection system includes a frame, an emitter coupled to the frame, and a detector coupled to the frame proximate the emitter. The system also includes a shielding system coupled to the frame and positioned at least partially between the emitter and the detector, wherein the frame positions a sensing surface of the detector in a direction substantially parallel to a plane extending along a front portion of the frame. A method of analyzing composition of a suspect object includes directing neutrons at the object, detecting gamma rays emitted from the object, and communicating spectrometer information regarding the gamma rays. The method also includes presenting a GUI to a user with a dynamic status of an ongoing neutron spectroscopy process. The dynamic status includes a present confidence for a plurality of compounds being present in the suspect object responsive to changes in the spectrometer information during the ongoing process.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2018

The Fermilab Test Beam Facility Data Acquisition System Based on $otsdaq$

The Real-Time Systems Engineering Department of the Scientific Computing Division at Fermilab has deployed set of customizations to our Off-The-Shelf Data Acquisition solution (otsdaq) at the Fermilab Test Beam Facility (FTBF) to read out the beamline instrumentation in support of FTBF users. In addition to reading out several detectors which use various detection technologies and readout hardware, the FTBF Data Acquisition system (DAQ) can perform basic track reconstruction through the facility in real time and provide data to facility users. An advanced prototype smart coincidence module, known as the NIM+, performs trigger distribution and throttling, allowing the beamline instrumentation to be read out at different rates. Spill data are saved to disk for studies of the facility performance, and hit data are also made available on the FTBF network for experiments' use. A web-based run control and configuration GUI are provided, and the online monitoring snapshots created after each beam spill are viewable from any computer connected to the Fermilab network. The integrated DAQ system for the facility provides users with high-precision tracking data along the beamline and a single location for obtaining data from the facility detectors, which set the baseline for testing their own detectors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2019

Systems and methods of generating color saturated data marks in data visualizations

A method of displaying data visualizations includes retrieving a dataset from a multidimensional database, where the dataset includes a plurality of fields, including first and second fields, and the first field is a data hierarchy that includes multiple subfields. The method further includes displaying a GUI with a first region displaying the plurality of fields (with the first field in a collapsed state), a second region with a plurality of shelves, and a third region. In response to receiving a user action to display the first field in an expanded state, the method displays the first field and the multiple subfields in a hierarchical structure. The method receives additional user actions to: (i) associate a first subfield of the plurality with a first shelf, and (ii) associate the second field with a second shelf, and then displays, in accordance with the user actions, a data visualization in the third region.

Stolte, Chris↗

DOE OSTI2021

GRIP: Constraint-based Explanation of Missing Answers for Graph Queries

Abstract: A useful feature in graph query engines is to clarify “Why certain entities (nodes, attribute values or edges) are missing” in query answers. This task is even more challenging when the relevant data is already missing in the underlying data source. Missing data, on the other hand, can be inferred by enforcing data constraints for graphs. We demonstrate GRIP, a system that exploits data constraints to clarify missing answers for graph queries. (1) Constraint-based ex- planation. Given a desired yet missing entity in the query answer, GRIP ensures to generate finite and minimal sequences of data con- strains (an “explanation”) that should be consecutively enforced to ?? to ensure its occurrence for the same query. (2) Answering “why” and“how” questions. Users can query GRIP with both“Why”(“Why” the element is missing) and “How” questions (“How” to refine the graph to include the missing answer). GRIP engine supports run- time generation of explanations by incrementally maintaining a set of bi-directional search trees. (3) Interactive exploration. GRIP provides a user-friendly GUI to support interactive ad visual exploration of explanations, including both automated generation and step-by-step inspection of graph manipulations.

graphs↗

DOE OSTI2022

FLASSH 1.0: Thermal Scattering Law Evaluation and Cross Section Generation

The Full Law Analysis Scattering System Hub ( FLASSH ) is an advanced code which evaluates the thermal scattering law (i.e. TSL, S(α,β)) for thermal scattering cross sections and resonance Doppler broadening. The ability to accurately capture these two key cross section features is dependent on accurate, high fidelity TSL evaluations. FLASSH 1.0 provides advanced physics capabilities resulting in an improved, generalized TSL to most accurately represent the lattice dynamics within any material. This improved TSL will allow for consistent analysis in both the thermal and epithermal energy ranges. The features for TSL analysis are packaged within the FLASSH GUI for easy user interface along with data output in many file formats including ENDF File 7 and ACE files.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

Virtual Engineering Software Framework for Integrated Biomass Conversion Modeling

This presentation covers the design and implementation of a software tool to systematically connect computational models of unit operations to simulate an integrated process of low-temperature conversion of biomass to fuel. This virtual engineering (VE) software was designed with the overarching goal of connecting unit models written in various programming languages and requiring different computational resources within a single, flexible framework. The models and features currently considered for the VE library include mechanistic models for pretreatment, enzymatic hydrolysis, and aerobic bioreaction; high-fidelity computational fluid dynamics (CFD) simulations for enzymatic hydrolysis and aerobic bioreaction; and the capability to perform techno-economic analyses (TEA) using Aspen Plus, a commercial software package. The CFD models require access to high-performance computing (HPC) resources, so in addition to handling multiple programming languages and interfaces, the VE software must also be capable of interacting with an HPC scheduler to submit, run, and post-process jobs. Using the Python programming language, a new VE software package has been developed that contains functionality to manage the input-output communication between various unit models, schedule simulations to run on NREL's HPC and analyze those results, and interface with existing TEA software workflows. A Jupyter-notebook GUI was also created to solicit user input and provide documentation. In cases where multiple models for a particular unit-operation exist, selection between models is accomplished through a simple checkbox, with the appropriate inputs and outputs being parsed and converted seamlessly in the background. Each operation makes use of a different programming language, but the flow of information from pretreatment to enzymatic hydrolysis to bioreaction is managed with an intuitive, centralized file-communication strategy. In this talk, the programming approach and implementation details of the notebook are presented for multiple possibilities of the conversion process, including a demonstration of the ability to manage HPC resources. Additionally, an example of a sensitivity study of treatment parameters governing the overall conversion outcome is shown which highlights the ease of defining new problems using the VE Notebook workflow and leads into a discussion of ongoing work to enable outer-loop optimization studies.

biofuel↗

DOE OSTI2023

The Fermilab SSR1 and HB650 Synoptic and EPICS remote cryogenic control system

The 325MHz Single Spoke Resonator 1 (SSR1) Cryomodule (CM) has a 5.3-meter length, and it has 288-liter liquid helium @ 4.5K mode. The High Beta 650 MHz (HB650) CM contains six elliptical cavity cryomodules, has a 9.9-meter overall length and it has 530-liter liquid helium. The SSR1 and HB650 CM had been tested at Fermilab Cryomodule Test Facility (CMTF). Their cryogenic control system includes the Siemens Process Control System S7-400, Automation Direct DL205 PLC, and remote synoptic HMI/EPICS Phoebus GUI. This paper presents a method which has been successfully used by Fermilab PIP2 IT cryogenic remote on-line, real-time control systems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Linkages Between NREL's dGen, REopt, and SAM Models

This webinar describes linkages between NREL's dGen, SAM, and REopt tools that were developed as a part of the RiDER project, including specifying utility rates in the SAM GUI and using them in dGen adoption analysis, and using REopt to determine optimal system sizes for dGen agents.

dGen↗