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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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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

On Development of Three-Dimensional Visualization Capabilities in Glenn Research Center Communication Analysis Suite

With NASA’s upcoming mission to return to the Moon sustainably by 2024 and using that success as a means to step onto the barren world of Mars, it remains more important than ever to conduct research and planning as thoroughly and efficiently as possible. In a mission as complex as landing humans onto another celestial body, a network of orbiting satellites and ground stations must accurately and reliably communicate with each other, enabling crucial data communications throughout the mission. Visualizing this important data communication increases the understanding of the data and can accelerate analyses efforts. The purpose of this software development is to create an interactive visualization with data taken MATLAB® scripts in the GRC Communication Analysis Suite that is easy to understand, can show all necessary data, and display the data accurately. The main types of data to visualize are from the State Propagation, Line of Sight and Dynamic Link Margin scripts. These all show positions and orbits of satellites and ground stations, while the Line of Sight data shows when they have the ability to communicate with each other based on their respective antenna positions and fields of view. Additionally, the Dynamic Link Margin mode color-codes the communication link performance onto the Line of Sight access lines. Visualization requires a graphics language that is easily accessible, has the needed features, and able to easily read data produced by the GRC Communication Analysis Suite MATLAB® scripts. ThreeJS, a graphics library for Web Graphics Library, coded in JavaScript was selected for the visualization. The next part of the software development was to move the data from MATLAB® to the JavaScript. The best way to accomplish this was to implement a MATLAB® function converting the output data of the scripts to a JavaScript Object Notation file. A key part of the development was creating the visualization within JavaScript and ThreeJS to visualize any combination of planets, moons, orbits, satellites, ground stations, line of sight links, and handle future features without changing major parts of the code. The current visualization capability runs directly from MATLAB®, and can dynamically create any scene. This software development currently supports the lunar communications analysis underway by NASA, and can be easily expanded upon in the future to aid any analysis requirements to help plan current and future space missions.

Visualization↗
NASA NTRS2020

Dynamic IT Security Database and Analytics for Launch Control Systems Software

During the Summer 2020 session, I worked with intern Destani S. Van Arsdalen of EGS Software. Together, we co-created a tool to aid the dynamic investigation, updated over time,of the security compliance of LCS COTS and open source software. We originally planned touse spreadsheet software for management and analysis, but through this exploratoryproject, chose to use Python and JSON after receiving feedback on our project’s current anddesired capabilities at that time.At first, the project was solely designed to help on-board new COTS software, based on aquestionnaire that could be filled out for each software package. This, combined with usingthe spreadsheet application’s web-query capabilities to fetch information from the NVD,allowed presentation and analytics cells to automatically populate as elements of themanually-filled questionnaire changed. While this system was promising, we decided tochange technologies for a few reasons. In the spreadsheet, single cells could not hold complexdata like arrays and objects. The automatic population of cells and dynamic updates made itdifficult to manage and add new features. And finally, it had limited extensibility sinceadding new software required significant understanding of how both the spreadsheet wasconstructed, and the more obscure, proprietary scripting languages packaged with it.The pivot to a standard computer science database language of JSON, aided by thescripting capabilities of Python, greatly helped to improve the project’s functionality. First,and most importantly, the script’s import and analysis of database data is easilyreproducible. Additional data analysis can be modularly added without requiringmodification of the script and is capable of routine scheduling. The revised process can besplit into three parts. First, the conversion of LCS asset and software documentation into theJSON hierarchical database format. Second, the merging of this database with the NVD,forming a new data structure, using CPEs of the CVE object as a linking element betweenthem. And third, the automatically performed analytics and analysis of the combined data,in a modular and extensible format, to produce better informed business decisions. The outputted graphs, for example, are automatically generated by the Python script inconnection with the combined database. This allows updated graphs and any analytics to be re-rendered automatically following updates to the LCS’s initial asset documentation. Afinal report can then be programmatically and easily constructed from these sources to allow fully reproducible metrics for heavily evidenced risk management decisions.

it↗
NASA NTRSDate not supplied

Derivation of Effective Properties Based on Porous Scale Simulations Using Filtering Techniques

This study presents a method for derivation of effective properties at the interface and in-depth of porous materials. The method defines a Representative Elementary Volume (REV) and applies filtering techniques to computer effective properties such as porosity and flow quantities, such as velocity and pressure. The script, developed to process the data was tested on the VTK type files that contain the mesh information and the flow solution. The method allows to choose between two types of filters, such as cellular and top-hat and define the size of the REV and number of samples along the domain. Extraction of the REV from the domain is performed to exact boundaries requested for the user. This is done using a triangulation technique and cutting through the cells to comply to the requested boundaries of the volume. The method can be applied to both structured and unstructured meshes. Filtering the material porosity and flow quantities involves integration of the numerical data. The algorithm provides three integration methods, such as Riemann sum, Monte Carlo and Quadrature rule to perform the integration. The Monte-Carlo technique permits the use of either uniform or linearly spaced distribution of points. The Quadrature rule is currently applicable to tetrahedral element types. The Monte Carlo and Quadrature rule methods require interpolation of the flow quantities at the sample points. For interpolation, two methods were tested and are readily available, Gaussian interpolation and re-sampling. It has been shown that re-sampling method has better consistency and acceptable accuracy in interpolation of the data. The algorithm was written in Python language and uses a number of modules. The major module besides numpy is PyVista. It is used to process the computational domain, clip the REV and interpolate the data. Quadrature rule integration was performed using a quadpy module. ParaView software was used externally to convert the flow solution to the VTK (or more specifically VTU) format. Integration of ParaView in the same environment with PyVista encountered problems and could not be implemented in this work. The developed algorithm is expected to be applicable to unstructured meshes and more complex porous structures as soon as the data can be passed in VTK type format. With the report is provided Python script for filtering the solution and a Matlab script for simple generation and processing of 2-D and 3-D porous channel geometries. The two scripts don't communicate.

Alexsander Zibitsker↗
DOE OSTI2016

Early Market Opportunity MHK Energy Site Identification - Wave and Tidal Resources

This data was compiled for the 'Early Market Opportunity Hot Spot Identification' project. The data and scripts included were used in the 'MHK Energy Site Identification and Ranking Methodology' Reports (see resources below). The Python scripts will generate a set of results--based on the Excel data files--some of which were described in the reports. The scripts depend on the 'score_site' package, and the score site package depends on a number of standard Python libraries (see the score_site install instructions).

16 TIDAL AND WAVE POWER↗
DOE OSTI2016

SU-F-P-18: Development of the Technical Training System for Patient Set-Up Considering Rotational Correction in the Virtual Environment Using Three-Dimensional Computer Graphic Engine

Purpose: Patient set-up skills in radiotherapy treatment room have a great influence on treatment effect for image guided radiotherapy. In this study, we have developed the training system for improving practical set-up skills considering rotational correction in the virtual environment away from the pressure of actual treatment room by using three-dimensional computer graphic (3DCG) engine. Methods: The treatment room for external beam radiotherapy was reproduced in the virtual environment by using 3DCG engine (Unity). The viewpoints to perform patient set-up in the virtual treatment room were arranged in both sides of the virtual operable treatment couch to assume actual performance by two clinical staffs. The position errors to mechanical isocenter considering alignment between skin marker and laser on the virtual patient model were displayed by utilizing numerical values expressed in SI units and the directions of arrow marks. The rotational errors calculated with a point on the virtual body axis as the center of each rotation axis for the virtual environment were corrected by adjusting rotational position of the body phantom wound the belt with gyroscope preparing on table in a real space. These rotational errors were evaluated by describing vector outer product operations and trigonometric functions in the script for patient set-up technique. Results: The viewpoints in the virtual environment allowed individual user to visually recognize the position discrepancy to mechanical isocenter until eliminating the positional errors of several millimeters. The rotational errors between the two points calculated with the center point could be efficiently corrected to display the minimum technique mathematically by utilizing the script. Conclusion: By utilizing the script to correct the rotational errors as well as accurate positional recognition for patient set-up technique, the training system developed for improving patient set-up skills enabled individual user to indicate efficient positional correction methods easily.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-458: Tracking Trends of TG-142 Parameters Via Analysis of Data Recorded by 2D Chamber Array

Purpose: With increasing QA demands of medical physicists in clinical radiation oncology, the need for an effective method of tracking clinical data has become paramount. A tool was produced which scans through data automatically recorded by a 2D chamber array and extracts relevant information recommended by TG-142. Using this extracted information a timely and comprehensive analysis of QA parameters can be easily performed enabling efficient monthly checks on multiple linear accelerators simultaneously. Methods: A PTW STARCHECK chamber array was used to record several months of beam outputs from two Varian 2100 series linear accelerators and a Varian NovalisTx−. In conjunction with the chamber array, a beam quality phantom was used to simultaneously to determine beam quality. A minimalist GUI was created in MatLab that allows a user to set the file path of the data for each modality to be analyzed. These file paths are recorded to a MatLab structure and then subsequently accessed by a script written in Python (version 3.5.1) which then extracts values required to perform monthly checks as outlined by recommendations from TG-142. The script incorporates calculations to determine if the values recorded by the chamber array fall within an acceptable threshold. Results: Values obtained by the script are written to a spreadsheet where results can be easily viewed and annotated with a “pass” or “fail” and saved for further analysis. In addition to creating a new scheme for reviewing monthly checks, this application allows for able to succinctly store data for follow up analysis. Conclusion: By utilizing this tool, parameters recommended by TG-142 for multiple linear accelerators can be rapidly obtained and analyzed which can be used for evaluation of monthly checks.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2016

SU-F-T-476: Performance of the AS1200 EPID for Periodic Photon Quality Assurance

Purpose: To assess the dosimetric performance of a new amorphous silicon flat-panel electronic portal imaging device (EPID) suitable for high-intensity, flattening-filter-free delivery mode. Methods: An EPID-based QA suite was created with automation to periodically monitor photon central-axis output and two-dimensional beam profile constancy as a function of gantry angle and dose-rate. A Varian TrueBeamTM linear accelerator installed with Developer Mode was used to customize and deliver XML script routines for the QA suite using the dosimetry mode image acquisition for an aS1200 EPID. Automatic post-processing software was developed to analyze the resulting DICOM images. Results: The EPID was used to monitor photon beam output constancy (central-axis), flatness, and symmetry over a period of 10 months for four photon beam energies (6x, 15x, 6xFFF, and 10xFFF). EPID results were consistent to those measured with a standard daily QA check device. At the four cardinal gantry angles, the standard deviation of the EPID central-axis output was <0.5%. Likewise, EPID measurements were independent for the wide range of dose rates (including up to 2400 mu/min for 10xFFF) studied with a standard deviation of <0.8% relative to the nominal dose rate for each energy. Also, profile constancy and field size measurements showed good agreement with the reference acquisition of 0° gantry angle and nominal dose rate. XML script files were also tested for MU linearity and picket-fence delivery. Using Developer Mode, the test suite was delivered in <60 minutes for all 4 photon energies with 4 dose rates per energy and 5 picket-fence acquisitions. Conclusion: Dosimetry image acquisition using a new EPID was found to be accurate for standard and high-intensity photon beams over a broad range of dose rates over 10 months. Developer Mode provided an efficient platform to customize the EPID acquisitions by using custom script files which significantly reduced the time. This work was funded in part by Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-TeP4-06: An Integrated Application for Radiation Therapy Treatment Plan Directives, Management, and Reporting

Purpose: With electronic medical records, patient information for the treatment planning process has become disseminated across multiple applications with limited quality control and many associated failure modes. We present the development of a single application with a centralized database to manage the planning process. Methods: The system was designed to replace current functionalities of (i) static directives representing the physician intent for the prescription and planning goals, localization information for delivery, and other information, (ii) planning objective reports, (iii) localization and image guidance documents and (iv) the official radiation therapy prescription in the medical record. Using the Eclipse Scripting Application Programming Interface, a plug-in script with an associated domain-specific SQL Server database was created to manage the information in (i)–(iv). The system’s user interface and database were designed by a team of physicians, clinical physicists, database experts, and software engineers to ensure usability and robustness for clinical use. Results: The resulting system has been fully integrated within the TPS via a custom script and database. Planning scenario templates, version control, approvals, and logic-based quality control allow this system to fully track and document the planning process as well as physician approval of tradeoffs while improving the consistency of the data. Multiple plans and prescriptions are supported along with non-traditional dose objectives and evaluation such as biologically corrected models, composite dose limits, and management of localization goals. User-specific custom views were developed for the attending physician review, physicist plan checks, treating therapists, and peer review in chart rounds. Conclusion: A method was developed to maintain cohesive information throughout the planning process within one integrated system by using a custom treatment planning management application that interfaces directly with the TPS. Future work includes quantifying the improvements in quality, safety and efficiency that are possible with the routine clinical use of this system. Supported in part by NIH-P01-CA-059827.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

STOMP-W

Fortran 90 source code, example problems, and output conversion scripts for the STOMP-W simulator. STOMP-W is a numerical simulator written in Fortran 90 for solving problems involving fluid flow and solute/species transport in variably saturated geologic media. The zipped file contains five directories: 1) src (the source code), 2) scripts (output conversion scripts written in perl, 3) prb-w-1 (example problem 1), 4) prb-w-2 (example problem 2), and 5) prb-w-3 (example problem 3). After downloading and unzipping the file, the user must create an executable from the files stored in the src directory. Generic instructions for compiling the source code is shown below as a UNIX/Linux command line, with f90 representing the user's Fortran 90 compiler.

White, Mark↗
DOE OSTI2020

ESS-DIVE File Level Metadata Extractor

The File-level Metadata (FLMD) parser is a lightweight python script that can produce a summary of fields based on column headers within a Comma-separated Values (CSV) file. The script enables a way to extract certain metadata fields from CSV data files. An optional configuration file can be used to select specific column headers to extract a smaller subset of values. The script can be used on a single file, or it can be given a directory to process groups of files in bulk. The FLMD parser outputs the metadata as a JSON and can be configured to updated the source file or produce an external companion file.

McNelis, Jack↗
DOE OSTI2020

sbang

sbang lets users run scripts with very long shebang (#!) lines. Many operating systems limit the length and number of possible arguments in shebang lines, making it hard to use interpreters that are deep in the directory hierarchy or require special arguments. To use it, a user puts the long shebang on the second line of their script, and makes sbang the interpreter, like this: #!/bin/sh /path/to/sbang #!/long/path/to/real/interpreter with arguments. sbang will run the real interpreter with the script as its argument.

Gamblin, Todd↗
DOE OSTI2020

XPlacer Machine Learning Guided Data Placement

XPlacer Machine Learning Guided Data Placement uses machine learning model to assist programmers to select the data placement advises for application running on HPC system with Nvidia GPUs. XPlacer Machine Learning Guided Data Placement consists three components: (1) 4 revised benchmarks from Rodinia benchmarks; (2) compiler script and execution script to generate variants, and collect training data for the machine learning model; (3) the scripts to post-process the collected data and generate the machine leaning model.

Liao, Chunhua↗
DOE OSTI2022

MatLab Package for Whispering Gallery Mode Data

Dye-doped whispering gallery mode resonator (WGMR) microspheres yield highly structured emission spectra that are extremely sensitive to their environment and are of intense interest for use in a variety of sensing applications. Efforts to leverage the unique sensitivities of WGMRs have relied on stringent experimental requirements to correlate specific spectral shifts/changes to an analyte/stimulus such as 1) precise positional knowledge, 2) reference spectra for each microsphere, and 3) high mechanical stability. Consequently, these can hinder adequate mixing or incorporation of analytes and creates challenges for remote sensing. The MATLAB codes provided here are to be used in conjunction with a continuous flow technique for measuring WGM spectra of dye-doped microspheres suspended in solution. One MATLAB script, smooths the data, automatically baseline corrects it to isolate the whispering gallery modes (WGM) from the unwanted bulk emission, and assesses the similarity of each spectrum to aid in selecting a set of unique WGM spectra for further analysis. The next script is designed to analyze WGM spectra to determine the size of the resonator and the refractive index (RI) of its local environment without a priori knowledge of the individual microsphere. The final script allows the user to cluster spheres based on the product of their RI and radius and the contrast ratio of the RI of the sphere material and that of its environment by using a shared nearest neighbor spectral clustering algorithm.

Lilley, Laura↗
DOE OSTI2019

slaclab/smurf-server-scripts

This repository contains a set of useful scripts for setting up SMuRF servers, divided in two main categories: (1)Scripts used to setup a SMuRF server from scratch and (2)Scripts used to release docker system in an SMuRF server.

Vasquez, Jesus↗
DOE OSTI2022

RLC4CLR (Reinforcement Learning Controller for Critical Load Restoration Problems)

RLC4CLR demonstrates using a reinforcement learning controller (RLC) to solve a critical load restoration (CLR) problem, which improves the grid resilience after a substation outage event. RLC4CLR consists of two parts. (1) RL environment: This environment encapsulates the CLR problem to be solved and provides interfacing functions to follow the standard OpenAI Gym format. A power system simulator, i.e., OpenDSS, is included to provide the power flow solution. Controller inputs and outputs (RL state and action) as well as the reward are defined in this environment as well. In summary, the RL environment is the problem formulation from which the RL agent can learn. (2) RL training script: The training script enables the RL agent to learn its control policy by interacting with the RL environment. For RL training, an open-sourced RL library, i.e., RLlib, is leveraged which is based on a distributed computing framework (Ray). The training script is designed to be able to be run on both local machine or the NREL HPC system. Other components of RLC4CLR include input data, e.g., grid model (standard IEEE test feeders), and other files used for results analysis.

Zhang, Xiangyu↗
DOE OSTI2022

pnnl/doa

This is a set of Python scripts designed to implement a method of determining the domain of applicability for a trained machine model for molecular property prediction. Additionally, the scripts implement analysis methods to evaluate and explore the results of the method. These scripts are designed to support the submission of a manuscript describing the methods for publication.

Panapitiya, Gihan↗
DOE OSTI2023

pnnl/mlprotein

The molecular graphics program, PyMol, was employed to produce all images in the training/validation/testing datasets. A PyMol script identified the clusters of interest from a list of all proteins containing 1) Fe (III) and Fe (II) ion and 2) FeS, respectively. A PyMol script and a Python webscraper were also used to classify [2Fe-2S] cofactors into three classes: standard, Rieske, and other and to identify iron atoms with four cysteine residues. We also used the pyMol script to rotate amino acids for training

Oostrom, Marjolein↗
DOE OSTI2023

IMG Annotation Pipeline (IMGAP) v5.1.13

The IMG Annotation Pipeline is a collection of Bash and Python scripts to control a workflow for structural and functional annotation of prokaryotic genomes, metagenomes, and metatranscriptomes. The bash scripts in general control the overall workflow and are wrappers around 3rd party executables (not included in repo) that predict features or functions. Whereas the Python scripts do post-processing of raw output in terms of filtering or format transformation and in some cases contain some logic for picking the correct predictions or resolving overlaps. The pipeline is tailored to produce results required by IMG (https://img.jgi.doe.gov/) and is executed on every dataset submitted to IMG via https://img.jgi.doe.gov/submit. These consist of internal genomes, metagenomes and metatranscriptomes sequenced and assembled at the JGI, as well as datasets submitted by external users (non-lab/JGI affiliates).

Huntemann, Marcel↗