Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “gui”

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.

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

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Bifacial_Radiance v0.4.2 [SWR-18-03]

The bifacial_radiance software contains a series of Python wrapper functions to make working with RADIANCE easier, particularly for the PV researcher interested in bifacial PV performance. For more information, check out our documentation, Tutorials in the form of Jupyter Notebooks, or refer to our Wiki and Issues page. Installation https://youtu.be/4A9GocfHKyM This video shows how to install the bifacial_radiance software and all associated software needed. More info on the Wiki. Instructions are also shown below. For detailed instructions of how to install bifacial_radiance, you can also refer to the installation guide. A GUI has been added in version 3.0. The GUI reads/writes all input parameters necessary to run a simulation, and runs the specified simulation by calling the correct functions with the specified parameters. So no need to use a journal or a script! But you still need to install following the procedure below.

Deline, Chris↗
DOE OSTI2025

sourcePy

Pollutant source identification techniques (of which there are many variations) are either locked behind researchers writing their own code for each use case or GUI platforms that are easy to use but inflexible and opaque. The Python package sourcePy brings together many of the pollutant source identification algorithms, giving the user full control out of the box. It aims to create a platform for source identification experiments where the full analysis from beginning to end can be done in Python, with a level of specificity in design that isn't available in the GUI options. sourcePy provides users with a few key features: -A Python interface with HYSPLIT, which can be used to generate trajectories and concentration plumes -Several Python classes which standardize the preparation and processing of data related to source identification experiments -Example scripts and notebooks that allow even new python users to get started with their own experiments quickly -Visualization methods

Arseneau, Isaac [Oak Ridge National Laboratory (OR↗
DOE OSTI2020

SAM Plug-in Development (Phase I Final Report)

The DOE Office of Nuclear Energy (NE) has created an extensive set of advanced modeling and simulation tools for nuclear engineering analysis. The advanced capabilities of these newer analysis codes require more in-depth training, skills, and knowledge in order to effectively utilize them for the design, analysis, and licensing of advanced nuclear systems and experiments. A high learning curve for inexperienced users may deter organizations from incorporating these tools into their internal processes. This project involved development of a plug-in to the Symbolic Nuclear Analysis Package (SNAP) for the System Analysis Module (SAM) tool. SAM is an advanced system analysis tool for reactor transient analyses being developed at Argonne National Laboratory under the U.S. DOE Office of Nuclear Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. SAM utilizes an object-oriented application framework (MOOSE), and its underlying meshing and finite-element library (libMesh) and linear and non-linear solvers (PETSc), to leverage modern advanced software environments and numerical methods. SNAP provides a highly flexible framework for creating, modifying and documenting input for engineering analysis codes such as SAM as well as extensive functionality for submitting, monitoring, and interacting with the codes through an intuitive graphical user interface (GUI). The common user interface provided by SNAP minimizes the learning curve for engineers starting with a new analysis code and provides an intuitive framework for transitioning between different analysis codes. SNAP provides a powerful but intuitive interface to facilitate access to advanced modeling and simulation tools for inexperienced users. Unlike many “form based” GUI’s, SNAP maps each engineering code’s component input to an internal database which manages all component input parameters along with component interconnections. This level of abstraction permits SNAP to support several advanced capabilities such as renodalization, model validation and consistency checks, embedded documentation, model notebook generation, data ownership and reviewer tracking, and variable assignment for inputs to name a few. SNAP includes a built-in Python interpreter and is interfaced to several commercial and open source packages including CPython, MATLAB/OCTAVE, Microsoft Office, Open Office, and SANDIA’s DAKOTA package which provides Uncertainty Quantification analysis through the SNAP plug-ins. Phase I of this project involved development a fully functional basic SAM plug-in to SNAP. This plug-in provides the ability to import existing models, graphically construct, edit and submit models using SNAP’s extensive functionality.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

SimpleMass (Version 2.0.1 Report)

SimpleMass v2 is an updated GUI version of the SimpleMass Excel spreadsheet. It was developed using Python 3.7 and wxPython, a cross-platform GUI toolkit. The program was developed on Windows 10 and tested on macOS Catalina. In theory, the program should work on Linux based operating systems such as Ubuntu, but this has not been tested. Executable versions of the code were built using PyInstaller. The version described in this report is an alpha version that is still in development. It has only been tested by the developer.

97 MATHEMATICS AND COMPUTING↗
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↗
DOE OSTI2020

NMDQi Thermal-hydraulic Optimization, Analysis, and Scoping Tool (TOAST)

The Thermal-hydraulic Optimization, Analysis, and Scoping Tool (TOAST) is developed to support the thermal-hydraulic aspects for the design of optimal irradiation vehicles for the Nuclear Materials Discovery and Qualification initiative (NMDQi). TOAST is currently a MATLAB-based tool that utilizes a simplified steady-state analytical model where a radial thermal resistance circuit is utilized to account for conduction through up to 2 capsules, a gas gap, a thermal bond, a sample cladding, and a sample, as well as the convection from a water coolant outside the capsules. The geometry is discretized axially along the user-defined height of a basket with a user-defined number of points/nodes, essentially turning TOAST into a semi-2D heat transfer analysis utility for cylindrical irradiation vehicles with practically any configuration, solving for temperatures radially at multiple axial locations. TOAST utilizes a Graphical User Interface (GUI) in-which a user can define the geometrical layout, the materials utilized for each component, the coolant characteristics, and the required solution. The user can define the geometry by inputting the diameters, thicknesses, and heights for each component, whereas the materials are defined via the user-provided constant or variable thermal conductivities. The user can select the coolant's inlet temperature, pressure, and the pressure drop across the height of the problem (which is used to calculate the velocity of the flow). Finally, the user can choose to solve for a sample heat generation rate limit by inputting temperature limits for the sample and capsules or can choose to purely solve for the axial temperature distributions of each component by inputting a pre-selected heat generation rate. Either way, TOAST provides the user with axial temperature distributions of all the components including the coolant, and the heat generation rate limit as well as the maximum outlet coolant temperature. The user can also choose to do one of 6 sensitivity analyses in TOAST. The sensitivity analyses yield plots of the sensitivity of the heat generation rate limit, the maximum coolant temperature, and the pressure limit for the annular components due to perturbations in 1-2 unknown variables based on the selected sensitivity analysis. Benchmarks between computations in TOAST and equivalent 2D axis symmetric ABAQUS models are presented, showing that TOAST results are within less than 3% of ABAQUS results in most cases, and a maximum of 8% difference in some cases. The benchmarks also revealed that this uncertainty is tied to the selection of an appropriate Nusselt number correlation and appropriate thermal conductivities, which the user can do from the GUI. Regardless, TOAST is demonstrated as a computationally efficient, highly accessible, and accurate utility for optimization and scoping s of studies different irradiation vehicles.

42 ENGINEERING↗
DOE OSTI2021

NEAMS Workbench MOOSE Integration Update

The Nuclear Energy Advanced Modeling and Simulation (NEAMS) Workbench is a graphical user interface (GUI) that provides a common analysis environment for the accelerated use of the NEAMS toolkit. To improve design and analysis of current and future nuclear energy systems, the NEAMS Workbench provides an integrated development environment for model creation, review, execution, output review, and visualization for integrated tools. In addition to a GUI, the NEAMS Workbench provides the Workbench Analysis Sequence Processor, an open-source tool set that facilitates input-content assistance for supported domain-specific input languages and user-friendly syntaxes. These supported syntaxes enable accelerated development and deployment of enhanced user inputs and workflows. The Multiphysics Object-Oriented Simulation Environment (MOOSE) has been supported in the NEAMS Workbench since 2016 and receives continuous updates. Efforts to improve MOOSE-based tool integration in the NEAMS Workbench are ongoing. This document details the current and planned enhancements of the NEAMS Workbench and the MOOSE framework to improve integration and usability of MOOSE-based applications within the NEAMS Workbench.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

FY22 Progress Report: SRNL Analysis of ICCWR LCM and WAMS Data for Corrosion and Cracking

Algorithms for machine learning and data analysis for the 3013 Surveillance Program are being developed in an ongoing collaborative effort by the Savannah River National Laboratory (SRNL) and the University of South Carolina (USC). To detect the presence of corrosion and cracking, data is collected from large binary files generated by a Laser Confocal Microscope (LCM) or Wide Area 3D Measurement System (WAMS). Software is being developed to use the physical attributes in the data files (e.g., height, color, and grayscale values; all as functions of a location in a plane projection) to detect the presence of surface corrosion and cracking. A user-friendly Matlab Graphical User Interface (GUI) that reads data from either LCM or WAMS files was developed to integrate input data with software developed for processing and evaluation. The GUI can selectively download binary data, interrogate data attributes, label data for training ML algorithms, flag significant features, execute Machine Learning (ML) algorithms, output parameters from trained ML algorithms, report ML model accuracy with respect to labeled data, and generate graphical representations for various analyses. Surface defects can be called out by setting user-specified thresholds, feature based analysis or machine learning algorithms. Enhancements to data labeling capability have been developed to address this essential precursor to application of ML routines. Efficient labeling is particularly important in view of the very large volume of data required to train ML algorithms.

3013 Corrosion↗
DOE OSTI2023

Athena-I CUBIT Journal Files

The Monte Carlo N-Particle (MCNP)1 transport code version 6 (also known as MCNP6) has the capability for tracking particles on unstructured mesh (UM) geometry models embedded into con structive solid geometry (CSG) cells. This feature has been developed for performing calculations of complex geometry models because manually creating CSG models is a time-consuming and error prone process as the complexities of geometries increase. The UM capability was originally designed to work with UM models created with the Abaqus software and ASCII input files that it generates. The MCNP code version 6.0 and later can process UM models formatted as Abaqus input files. Starting with version 6.3, MCNP can also process HDF5 mesh input files. External codes must be used to generate Abaqus input files for MCNP UM calculations. CUBIT, the Sandia National Laboratory automated mesh generation toolkit, can generate a UM model formatted as an Abaqus input file. However, the Abaqus input files exported from CUBIT cannot be used for MCNP simulations because it lacks the proper syntax. A Python script was developed to convert an Abaqus file created by CUBIT to an Abaqus file format that MCNP can process. Creating UM models for complex geometries is not an easy task. The process of creating UM models in CUBIT for MCNP simulations is detailed in. CUBIT provides several user interface options including a graphical user interface (GUI) and a command line interface. A GUI provides an easy way to use CUBIT without learning the CUBIT command syntax. When using CUBIT with either interface option, command lines are written into an ASCII file known as a journal file; this journal file can be edited and archived so that it can be played back in CUBIT to automatically generate a UM model. This report describes the CUBIT journal files of the UM models developed for Athena-I. The Athena platform, an energy-tuning assembly, was developed to spectrally shape the National Ignition Facility (NIF) deuterium-tritium fusion neutron source to a thermonuclear (fusion) plus prompt fission neutron spectrum with capability to act as a short-pulse neutron source. MCNP6 was used for the Athena experiment design analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

FY25 Mid-Year Report: FNCL Enhancements Implementation

During the first half of FY25 the FNCL team has made consistent progress toward the completion of our project goals. The FNCL prototype panel design has been successfully applied to a fully instrumented 3-panel system which is actively under construction. The FNCL Demonstrator System contains solid scintillators instrumented with SiPMs, which operate on an updated CAEN digitizer, requires no high-voltage, and has a smaller overall footprint. The onboard software will include the LLNL-developed GMM-PSD signal processing. Later this year the system will be experimentally tested alongside the baseline FNCL instrument at LLNLs ISSA facility. In addition to a full systems test, the performance of a DD generator for active interrogation measurements compared to the standard AmLi source will be established for both systems. The data collected at the ISSA facility will be used to experimentally validate the FNCL-Fast Isotopic Fuel Assay’s (FIFA) capability to measure U-235 loading and to predict gadolinium poison content with passive interrogation. The FNCL-FIFA modal was benchmarked with simulation-based data and a user-friendly GUI was added earlier this year. Three separate codes have been submitted to the LLNL ESW system for review prior to their transfers. These include the Predictive Modeling Response toolkit, GMM-PSD firmware beta version, and the FNCL-FIFA analysis package with GUI and user documentation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
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↗
DOE OSTI2022

Robust High-Throughput Phenotyping with Deep Segmentation Enabled by a Web-Based Annotator

The abilities of plant biologists and breeders to characterize the genetic basis of physiological traits are limited by their abilities to obtain quantitative data representing precise details of trait variation, and particularly to collect this data at a high-throughput scale with low cost. Although deep learning methods have demonstrated unprecedented potential to automate plant phenotyping, these methods commonly rely on large training sets that can be time-consuming to generate. Intelligent algorithms have therefore been proposed to enhance the productivity of these annotations and reduce human efforts. We propose a high-throughput phenotyping system which features a Graphical User Interface (GUI) and a novel interactive segmentation algorithm: Semantic-Guided Interactive Object Segmentation (SGIOS). By providing a user-friendly interface and intelligent assistance with annotation, this system offers potential to streamline and accelerate the generation of training sets, reducing the effort required by the user. Our evaluation shows that our proposed SGIOS model requires fewer user inputs compared to the state-of-art models for interactive segmentation. As a case study of the use of the GUI applied for genetic discovery in plants, we present an example of results from a preliminary genome-wide association study (GWAS) of in planta regeneration in Populus trichocarpa (poplar). We further demonstrate that the inclusion of a semantic prior map with SGIOS can accelerate the training process for future GWAS, using a sample of a dataset extracted from a poplar GWAS of in vitro regeneration. The capabilities of our phenotyping system surpass those of unassisted humans to rapidly and precisely phenotype our traits of interest. The scalability of this system enables large-scale phenomic screens that would otherwise be time-prohibitive, thereby providing increased power for GWAS, mutant screens, and other studies relying on large sample sizes to characterize the genetic basis of trait variation. Our user-friendly system can be used by researchers lacking a computational background, thus helping to democratize the use of deep segmentation as a tool for plant phenotyping.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

Transportable Applications Environment (TAE) Plus - A NASA productivity tool used to develop graphical user interfaces

The Transportable Applications Environment (TAE) Plus, developed at NASA's Goddard Space Flight Center, is an advanced portable user interface development environment which simplifies the process of creating and managing complex application graphical user interfaces (GUIs), supports prototyping, allows applications to be oported easily between different platforms, and encourages appropriate levels of user interface consistency between applications. This paper discusses the capabilities of the TAE Plus tool, and how it makes the job of designing and developing GUIs easier for the application developers. The paper also explains how tools like TAE Plus provide for reusability and ensure reliability of UI software components, as well as how they aid in the reduction of development and maintenance costs.

Szczur, Martha R.↗
NASA NTRS1994

Program Simulates Spacecraft Communication Scenarios

Dynamic Environment Communications Alalysis Testbed (DECAT) computer program is modular simulation program. Computes effects of motion, antenna radiation patterns, noise, interference, and other phenomena. Flexibility enables users to analyze many communications scenarios quickly and easily, eliminating need for users to create specific computer programs. Users create simulations involving any number of vehicles, receivers, transmitters, and antennas via graphical user interface (GUI). DECAT GUI implemented by use of software tool called "Transportable Applications Environment Plus" (TAE Plus). Written in C language. Graphical user interface requires TAE Plus, Version 5.1 package available from COSMIC (GSC-13463).

Land, Kenneth P.↗
NASA NTRS1993

Development and operations of the Astrophysics Data System

The main effort in October 1992 was for the development and of the Astrophysics Data System (ADS) 3.1 graphical interface (GUI) and the preparation for its release. The beta-release for the GUI was made available to the nodes for testing. Development of the Abstract Server progressed satisfactorily. A test version was prepared for the ADASS meeting. Another major effort was the preparation for the user and nodes meetings on 5 and 6 November and for the ADASS conference on 2-4 November. February 1993 was highlighted by the preparation for the update release and its associated problems. We have the okay from the Commerce Department to export ADS. Foreign users can now sign on and receive the software. The main event during June was the AAS meeting. In the summer, the project decided on a new release schedule. The next major release is scheduled for January 1994 and will include major architectural improvements. In late spring 1994, a major release will include the new networking software.

Murray, S. S.↗
NASA NTRS1993

Enhanced networks operations using the X Window System

We propose an X Window Graphical User Interface (GUI) which is tailored to the operations of NASA GSFC's Network Control Center (NCC), the NASA Ground Terminal (NGT), the White Sands Ground Terminal (WSGT), and the Second Tracking and Data Relay Satellite System (TDRSS) Ground Terminal (STGT). The proposed GUI can also be easily extended to other Ground Network (GN) Tracking Stations due to its standardized nature.

Linares, Irving↗
NASA NTRS1993

XRTD: An X-Windows based, real-time radiometric display and analysis system

XRTD is a graphical user interface (GUI) based tool for monitoring real time radiometric spacecraft data. The tool is designed to allow the navigation analyst to both view and analyze the characteristics of Doppler and ranging data. This capability is critical if ground personnel wish to verify the correct performance of ongoing maneuvers. The raw tracking data is transferred from Deep Space Network (DSN) computers to a local workstation, where the predicted value for the observable is subtracted from the actual observed value to create a residual. The tool then allows the navigation analyst to rescale and replot the data using simple GUI techniques. The navigator may then perform a number of data analysis and modeling techniques on the resulting residuals to allow for the real time characterization of spacecraft events. These techniques include the modeling of maneuvers, the compression and differencing of data, and Fast Fourier transforms of the data. This tool has shortened the amount of time required for initial characterization of spacecraft maneuvers from several hours to a few minutes.

Pollmeier, Vincent M.↗
NASA NTRS1995

PLATSIM: An efficient linear simulation and analysis package for large-order flexible systems

PLATSIM is a software package designed to provide efficient time and frequency domain analysis of large-order generic space platforms implemented with any linear time-invariant control system. Time domain analysis provides simulations of the overall spacecraft response levels due to either onboard or external disturbances. The time domain results can then be processed by the jitter analysis module to assess the spacecraft's pointing performance in a computationally efficient manner. The resulting jitter analysis algorithms have produced an increase in speed of several orders of magnitude over the brute force approach of sweeping minima and maxima. Frequency domain analysis produces frequency response functions for uncontrolled and controlled platform configurations. The latter represents an enabling technology for large-order flexible systems. PLATSIM uses a sparse matrix formulation for the spacecraft dynamics model which makes both the time and frequency domain operations quite efficient, particularly when a large number of modes are required to capture the true dynamics of the spacecraft. The package is written in MATLAB script language. A graphical user interface (GUI) is included in the PLATSIM software package. This GUI uses MATLAB's Handle graphics to provide a convenient way for setting simulation and analysis parameters.

Maghami, Periman↗