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At least 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
NASA NTRS2010

Platform for Post-Processing Waveform-Based NDE

Signal- and image-processing methods are commonly needed to extract information from the waves, improve resolution of, and highlight defects in an image. Since some similarity exists for all waveform-based nondestructive evaluation (NDE) methods, it would seem that a common software platform containing multiple signal- and image-processing techniques to process the waveforms and images makes sense where multiple techniques, scientists, engineers, and organizations are involved. NDE Wave & Image Processor Version 2.0 software provides a single, integrated signal- and image-processing and analysis environment for total NDE data processing and analysis. It brings some of the most useful algorithms developed for NDE over the past 20 years into a commercial-grade product. The software can import signal/spectroscopic data, image data, and image series data. This software offers the user hundreds of basic and advanced signal- and image-processing capabilities including esoteric 1D and 2D wavelet-based de-noising, de-trending, and filtering. Batch processing is included for signal- and image-processing capability so that an optimized sequence of processing operations can be applied to entire folders of signals, spectra, and images. Additionally, an extensive interactive model-based curve-fitting facility has been included to allow fitting of spectroscopy data such as from Raman spectroscopy. An extensive joint-time frequency module is included for analysis of non-stationary or transient data such as that from acoustic emission, vibration, or earthquake data.

Roth, Don J.↗
NASA NTRS2014

iPAS: AES Flight System Technology Maturation for Human Spaceflight

In order to realize the vision of expanding human presence in space, NASA will develop new technologies that can enable future crewed spacecraft to go far beyond Earth orbit. These technologies must be matured to the point that future project managers can accept the risk of incorporating them safely and effectively within integrated spacecraft systems, to satisfy very challenging mission requirements. The technologies must also be applied and managed within an operational context that includes both on-board crew and mission support on Earth. The Advanced Exploration Systems (AES) Program is one part of the NASA strategy to identify and develop key capabilities for human spaceflight, and mature them for future use. To support this initiative, the Integrated Power Avionics and Software (iPAS) environment has been developed that allows engineers, crew, and flight operators to mature promising technologies into applicable capabilities, and to assess the value of these capabilities within a space mission context. This paper describes the development of the integration environment to support technology maturation and risk reduction, and offers examples of technology and mission demonstrations executed to date.

Othon, William L.↗
NASA NTRS1991

TADPLOT program, version 2.0: User's guide

The TADPLOT Program, Version 2.0 is described. The TADPLOT program is a software package coordinated by a single, easy-to-use interface, enabling the researcher to access several standard file formats, selectively collect specific subsets of data, and create full-featured publication and viewgraph quality plots. The user-interface was designed to be independent from any file format, yet provide capabilities to accommodate highly specialized data queries. Integrated with an applications software network, data can be assessed, collected, and viewed quickly and easily. Since the commands are data independent, subsequent modifications to the file format will be transparent, while additional file formats can be integrated with minimal impact on the user-interface. The graphical capabilities are independent of the method of data collection; thus, the data specification and subsequent plotting can be modified and upgraded as separate functional components. The graphics kernel selected adheres to the full functional specifications of the CORE standard. Both interface and postprocessing capabilities are fully integrated into TADPLOT.

Hammond, Dana P.↗
DOE OSTI2020

Reconstruction of Charged Particle Tracks in Realistic Detector Geometry Using a Vectorized and Parallelized Kalman Filter Algorithm

One of the most computationally challenging problems expected for the High-Luminosity Large Hadron Collider (HL-LHC) is finding and fitting particle tracks during event reconstruction. Algorithms used at the LHC today rely on Kalman filtering, which builds physical trajectories incrementally while incorporating material e ects and error estimation. Recognizing the need for faster computational throughput, we have adapted Kalman-filterbased methods for highly parallel, many-core SIMD and SIMT architectures that are now prevalent in high-performance hardware. Previously we observed significant parallel speedups, with physics performance comparable to CMS standard tracking, on Intel Xeon, Intel Xeon Phi, and (to a limited extent) NVIDIA GPUs. While early tests were based on artificial events occurring inside an idealized barrel detector, we showed subsequently that our mkFit software builds tracks successfully from complex simulated events (including detector pileup) occurring inside a geometrically accurate representation of the CMS-2017 tracker. Here, we report on advances in both the computational and physics performance of mkFit, as well as progress toward integration with CMS production software. Recently we have improved the overall eciency of the algorithm by preserving short track candidates at a relatively early stage rather than attempting to extend them over many layers. Moreover, mkFit formerly produced an excess of duplicate tracks; these are now explicitly removed in an additional processing step. We demonstrate that with these enhancements, mkFit becomes a suitable choice for the first iteration of CMS tracking, and eventually for later iterations as well. We plan to test this capability in the CMS High Level Trigger during Run 3 of the LHC, with an ultimate goal of using it in both the CMS HLT and oine reconstruction for the HL-LHC CMS tracker.

Cerati, Giuseppe↗
NASA NTRS2017

Medical Data Architecture Project Capabilities and Design

Mission constraints will challenge the delivery of medical care on a long-term, deep space exploration mission. This type of mission will be restricted in the availability of medical knowledge, skills, procedures and resources to prevent, diagnose, and treat in-flight medical events. Challenges to providing medical care are anticipated, including resource and resupply constraints, delayed communications and no ability for medical evacuation. The Medical Data Architecture (MDA) project will enable medical care capability in this constrained environment. The first version of the system, called "Test Bed 1," includes capabilities for automated data collection, data storage and data retrieval to provide information to the Crew Medical Officer (CMO). Test Bed 1 seeks to establish a data architecture foundation and develop a scalable data management system through modular design and standardized interfaces. In addition, it will demonstrate to stakeholders the potential for an improved, automated, flow of data to and from the medical system over the current methods employed on the International Space Station (ISS). It integrates a set of external devices, software and processes, and a Subjective, Objective, Assessment, and Plan (SOAP) note commonly used by clinicians. Medical data like electrocardiogram plots, heart rate, skin temperature, respiration rate, medications taken, and more are collected from devices and stored in the Electronic Medical Records (EMR) system, and reported to crew and clinician. Devices integrated include the Astroskin biosensor vest and IMED CARDIAX electrocardiogram (ECG) device with INEED MD ECG Glove, and the NASA-developed Medical Dose Tracker application. The system is designed to be operated as a standalone system, and can be deployed in a variety of environments, from a laptop to a data center. The system is primarily composed of open-source software tools, and is designed to be modular, so new capabilities can be added. The software components and integration methods will be discussed.

Data architecture↗
NASA NTRS2019

Medical Data Architecture (MDA) Project Status

The Medical Data Architecture (MDA) project supports the Exploration Medical Capability (ExMC) risk to minimize or reduce the risk of adverse health outcomes and decrements in performance due to in-flight medical capabilities on human exploration missions. To mitigate this risk, the ExMC MDA project addresses the technical limitations identified in ExMC Gap Med 07: We do not have the capability to comprehensively process medically-relevant information to support medical operations during exploration missions. This gap identifies that the current in-flight medical data management includes a combination of data collection and distribution methods that are minimally integrated with on-board medical devices and systems. Furthermore, there are a variety of data sources and methods of data collection. For an exploration mission, the seamless management of such data will enable a more medically autonomous crew than the current paradigm. The medical system requirements are being developed in parallel with the exploration mission architecture and vehicle design. ExMC has recognized that in order to make informed decisions about a medical data architecture framework, current methods for medical data management must not only be understood, but an architecture must also be identified that provides the crew with actionable insight to medical conditions. This medical data architecture will provide the necessary functionality to address the challenges of executing a self-contained medical system that approaches crew health care delivery without assistance from ground support. Hence, the products supported by current prototype development will directly inform exploration medical system requirements.In fiscal year 2018, the MDA project developed Test Bed 2, the second iteration in a series of prototypes with functionality focused on data security through role-based access control and encryption, integration with One Portal exercise software and ingestion of an ultrasound Digital Imaging and Communications in Medicine (DICOM) file and image display. Test Bed 2 advances the medical data system architecture framework by providing these functionalities in a scalable system that maintained a layered, modular design. The architecture framework uses a data services approach with role-based access to data in a customized medical record system suitable for space exploration. These functionalities were demonstrated as part of the Next Space Technologies for Exploration Partnerships (NextSTEP) ground test demonstrated at the NASA Johnson Space Center Integrated Power, Avionics and Software (iPAS) facility. Interfacing to a Core Flight Software (CFS) system, the MDA system, using Consultative Committee for Space Data Systems (CCSDS) protocol, transferred an exercise file from the simulated flight MDA system to a mirrored MDA system on the ground through the CFS system. The selection of data sources and demonstrations enabled the team to address stakeholder concerns throughout the development process. In the next iteration, the MDA team will work with stakeholders to identify additional relevant functionalities to further advance system data models, standards and principles that will inform the medical system requirements development.

medical data architecture↗
NASA NTRS2001

Non-Deterministic, Non-Traditional Methods (NDNTM)

The review effort identified research opportunities related to the use of nondeterministic, nontraditional methods to support aerospace design. The scope of the study was restricted to structural design rather than other areas such as control system design. Thus, the observations and conclusions are limited by that scope. The review identified a number of key results. The results include the potential for NASA/AF collaboration in the area of a design environment for advanced space access vehicles. The following key points set the context and delineate the key results. The Principal Investigator's (PI's) context for this study derived from participation as a Panel Member in the Air Force Scientific Advisory Board (AF/SAB) Summer Study Panel on 'Whither Hypersonics?' A key message from the Summer Study effort was a perceived need for a national program for a space access vehicle whose operating characteristics of cost, availability, deployability, and reliability most closely match the NASA 3rd Generation Reusable Launch Vehicle (RLV). The Panel urged the AF to make a significant joint commitment to such a program just as soon as the AF defined specific requirements for space access consistent with the AF Aerospace Vision 2020. The review brought home a concurrent need for a national vehicle design environment. Engineering design system technology is at a time point from which a revolution as significant as that brought about by the finite element method is possible, this one focusing on information integration on a scale that far surpasses current design environments. The study therefore fully supported the concept, if not some of the details of the Intelligent Synthesis Environment (ISE). It became abundantly clear during this study that the government (AF, NASA) and industry are not moving in the same direction in this regard, in fact each is moving in its own direction. NASA/ISE is not yet in an effective leadership position in this regard. However, NASA does have complementary software interoperability efforts that should be a part of any major ISE program. Software standards that assure interoperability of data systems and modeling representations are enabling for the proposed research advocated herein and should be a major element in the ISE initiative. The international standard for data interchange is known by the acronym 'STEP.' The NASA participation and lead for that effort is at the Goddard Space Flight Center. NASA/GRC is leading an effort to define CAD geometry standards through the Object Management Group (OMG). To enable the design environment so necessary to the above national vision for a unique space vehicle will require an integrating software environment with interoperability standards that allow the development and widespread deployment of tools and toolsets, rather than traditional "shrink-wrapped" software used by engineers today.

Cruse, Thomas A.↗
NASA NTRS2013

Software for Generating Troposphere Corrections for InSAR Using GPS and Weather Model Data

Atmospheric errors due to the troposphere are a limiting error source for spaceborne interferometric synthetic aperture radar (InSAR) imaging. This software generates tropospheric delay maps that can be used to correct atmospheric artifacts in InSAR data. The software automatically acquires all needed GPS (Global Positioning System), weather, and Digital Elevation Map data, and generates a tropospheric correction map using a novel algorithm for combining GPS and weather information while accounting for terrain. Existing JPL software was prototypical in nature, required a MATLAB license, required additional steps to acquire and ingest needed GPS and weather data, and did not account for topography in interpolation. Previous software did not achieve a level of automation suitable for integration in a Web portal. This software overcomes these issues. GPS estimates of tropospheric delay are a source of corrections that can be used to form correction maps to be applied to InSAR data, but the spacing of GPS stations is insufficient to remove short-wavelength tropospheric artifacts. This software combines interpolated GPS delay with weather model precipitable water vapor (PWV) and a digital elevation model to account for terrain, increasing the spatial resolution of the tropospheric correction maps and thus removing short wavelength tropospheric artifacts to a greater extent. It will be integrated into a Web portal request system, allowing use in a future L-band SAR Earth radar mission data system. This will be a significant contribution to its technology readiness, building on existing investments in in situ space geodetic networks, and improving timeliness, quality, and science value of the collected data

Moore, Angelyn W.↗
DOE OSTI2023

Final Report for ARPA-E LOCOMOTIVES Advanced Locomotive Technology and Rail Infrastructure Optimization System (ALTRIOS) Project

The Advanced Locomotive Technology and Rail Infrastructure Optimization System (ALTRIOS) is a unique, fully integrated, open-source software tool used to evaluate strategies for cost-effectively deploying advanced locomotive technologies and associated infrastructure. ALTRIOS simulates freight-demand-driven train scheduling, mainline meet-pass planning, locomotive dynamics, train dynamics, energy conversion efficiencies, and energy storage dynamics of line-haul train operations. Because new locomotives represent a significant long-term capital investment and new technologies must be thoroughly demonstrated before deployment, this tool provides guidance on the risk/reward trade-offs and operation integration of different technology rollout strategies. An open, integrated simulation tool is valuable for identifying future research needs and making decisions on technology development, routes, and train selection. This final report details the ALTRIOS software architecture, major modules and components, and data validation process. It demonstrates the software's utility through a 30-year rollout case study targeting high penetration of advanced powertrain technologies by 2050 for two BNSF Railway routes: loaded taconite ore trains from Hibbing, Minnesota, to Superior, Wisconsin, and mixed-freight trains from Superior to Minneapolis, Minnesota.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2016

Simulation of the outdoor energy efficiency of an autonomous solar kit based on meteorological data for a site in Central Europe

This contribution analyzes the energy provided by a solar kit dedicated to autonomous usage and installed in Central Europe (Longitude 6.10°; Latitude 49.21° and Altitude 160 m) by using the simulation software PVSYST. We focused the analysis on the effect of temperature and solar irradiation on the I-V characteristic of a commercial PV panel. We also consider in this study the influence of charging and discharging the battery on the generator efficiency. Meteorological data are integrated into the simulation software. As expected, the solar kit provides an energy varying all along the year with a minimum in December. In the proposed approach, we consider this minimum as the lowest acceptable energy level to satisfy the use. Thus for the other months, a lost in the available renewable energy exists if no storage system is associated.

14 SOLAR ENERGY↗
DOE OSTI2021

FY21 Progress Report: SRNL Analysis of ICCWR LCM and WAMS data for Corrosion and Cracking

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). 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, flag significant features, execute Machine Learning (ML) algorithms, output parameters for trained ML algorithms, report ML model accuracy with respect to labeled data, and generate graphical representations for various analyses. Features can be called out by user-specified thresholds, manual labeling or machine learning algorithms when they have been completed. The ability to rapidly label data is important because of the volume of data required for training machine learning algorithms. The GUI has the flexibility to allow addition of improved ML algorithms, methods for data visualization, and statistical computations. Statistical analyses via the GUI include areas of pits within a defined range of pit depths, correlations between Red-Green-Blue (RGB) or grayscale intensity and relative surface height, covariances between values associated with features, and feature histograms. The development of supervised machine learning algorithms, however, has been hindered by a lack of training data. The machine learning algorithms for crack identification are being refined but require improvements to the true positive rate for crack detection. This shortcoming is an artifact of the limited training data currently available, perhaps more so than the structure of the neural networks. At present, the best results are had from a consensus over an ensemble of randomly generated Deep Neural Network (DNN) or Convolutional Neural Network (CNN) algorithms. Although the consensus accuracy method has yielded optimum true positive and true negative rates in excess of 80%, additional validation testing is necessary. In addition to the suite of LCM data that was initially used, and which represents the majority of the work presented in this report, WAMS image data was also reviewed at a preliminary level. The review included a comparison between image resolution and dynamic range for each method. WAMS (ZON file) image data was found to have a pixel pitch of 3.69μm compared to 1 μm for the LCM (vk4 file) data, which implies a lower resolution for the WAMS images. Conversely, the ratio of dynamic range of the WAMS data to the LCM data was approximately 41:20 for height data, suggesting that information from WAMS should more accurately determine the depth of pits. At present, the significance of the greater dynamic range of the WAMS data relative to the LCM data has not yet been evaluated.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1986

Automation of electromagnetic compatability (EMC) test facilities

Efforts to automate electromagnetic compatibility (EMC) test facilities at Marshall Space Flight Center are discussed. The present facility is used to accomplish a battery of nine standard tests (with limited variations) deigned to certify EMC of Shuttle payload equipment. Prior to this project, some EMC tests were partially automated, but others were performed manually. Software was developed to integrate all testing by means of a desk-top computer-controller. Near real-time data reduction and onboard graphics capabilities permit immediate assessment of test results. Provisions for disk storage of test data permit computer production of the test engineer's certification report. Software flexibility permits variation in the tests procedure, the ability to examine more closely those frequency bands which indicate compatibility problems, and the capability to incorporate additional test procedures.

Harrison, C. A.↗
DOE OSTI2014

Computation Annual Report (2013)

Computation provides the intellectual electricity that helps make Lawrence Livermore National Laboratory (LLNL) a thriving and innovative research and development (R&D) institution. Our hardware, software, and discipline experts are integrated into almost every field of research at LLNL. Our in-house programs, software applications, and support initiatives help achieve mission-critical national-security objectives for the U.S. Departments of Energy, Homeland Security, and Defense, as well as other federal and state agencies. We deliver comprehensive support to a wide set of scientific disciplines that include physical sciences (materials modeling, fluid dynamics), biology (genomic sequencing), mathematics (scalable algorithms), and computer sciences (parallel processing, real-time control systems). This year, we have expanded our outreach with high performance computing (HPC) collaborations and made great strides in our capabilities related to mathematical computation, control systems, and computation infrastructure, many of them in concert with partners in industry and academia. The Computation workforce remains highly motivated and passionate about melding computational expertise with cutting-edge science and technology to enable breakthroughs. 2013 has once again proven that Computation provides the foundation and support that are essential for productivity at LLNL. Every scientific discipline and program leverages the tools and expertise provided by our staff. We remain at the forefront of HPC moving towards exascale and have developed the infrastructure and proficiency to make this an achievable goal. Our researchers repeatedly deliver outstanding research, attracting collaborations with the biggest names in academia and industry, while joining forces with other national laboratories to further push the bounds of what is scientifically possible. Computation’s mission is echoed by the President of the United States in his assertion that “our future depends on reaffirming America’s role as the world’s engine of scientific discovery and technological innovation.” Driven by this lofty goal, we employ our state-of-the-art computational capabilities to ensure LLNL’s position as a global science and technology leader.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Method and application of data integration at a nuclear power plant. Light Water Reactor Sustainability Program report

The data of a nuclear power plant (NPP) is stored in silos for the various plant tools. A previous study conducted by the LWRS program identified the different data sources that can benefit online monitoring in an NPP. These data have different structures and tools and are therefore used independently. Integrating data from various sources can result in multiple benefits to online monitoring by enhancing the ability to compare data, reduce statistical uncertainty due to a larger data set, increase data heterogeneity in space and time to reveal confounded information, develop intelligent methods, and share data. Data integration can result in direct cost saving by reducing the amount of effort needed to find needed information. It can also enable establishing a data warehouse, the backbone repository of data for an NPP, and is necessary to evolve NPPs to a holistic online monitoring approach and automate labor-intensive activities. Whether within an NPP or for a fleet of NPPs, deploying a data warehouse in a plant or data broker for a fleet of plants requires overcoming multiple challenges, including the lack of a standard form of storing and using data and the lack of integration methods to compare and map the different data sources. This effort demonstrates two methods and applications for data integration through an application integration pilot and a data fusion pilot. The application integration is targeted towards the software interfacing of data and data management. This approach is commonly used by data integrators. The data fusion pilot is targeted towards intelligently mapping or coupling data for optimized data use. The pilots were performed in collaboration with two NPPs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2010

Integrated Budget Office Toolbox

The Integrated Budget Office Toolbox (IBOT) combines budgeting, resource allocation, organizational funding, and reporting features in an automated, integrated tool that provides data from a single source for Johnson Space Center (JSC) personnel. Using a common interface, concurrent users can utilize the data without compromising its integrity. IBOT tracks planning changes and updates throughout the year using both phasing and POP-related (program-operating-plan-related) budget information for the current year, and up to six years out. Separating lump-sum funds received from HQ (Headquarters) into separate labor, travel, procurement, Center G&A (general & administrative), and servicepool categories, IBOT creates a script that significantly reduces manual input time. IBOT also manages the movement of travel and procurement funds down to the organizational level and, using its integrated funds management feature, helps better track funding at lower levels. Third-party software is used to create integrated reports in IBOT that can be generated for plans, actuals, funds received, and other combinations of data that are currently maintained in the centralized format. Based on Microsoft SQL, IBOT incorporates generic budget processes, is transportable, and is economical to deploy and support.

Rushing, Douglas A.↗
DOE OSTI2020

Quality Assurance Plan for Federal Guidance Report 16

Federal Guidance Report No. 16 will provide risk coefficients for use in projecting the probability of cancer morbidity or mortality from exposure to environmental radionuclides. The derivation of nuclide-specific risk coefficients involves multiple steps, with each step relying on the accuracy of the previous step as well as the numerical data utilized within each step. Thus, to ensure the quality of the derived risk coefficients, it is necessary to evaluate and confirm the quality and proper implementation of input data at each step of the derivation. The Oak Ridge National Laboratory (ORNL) dosimetry research team currently has two largely independent software codes for deriving radiation dose estimates, dose coefficients, and cancer risk coefficients for internally deposited radionuclides: DCAL and QCAL. The agreement of derived values based on alternate codes is an important step in quality assurance (QA) of the risk coefficients produced in this project. DCAL is an integration of the dosimetric software and numerical databases developed at ORNL over the past 25 years for the EPA’s Office of Radiation and Indoor Air (ORIA). QCAL was developed in 2015 to serve as a substitute for DCAL while DCAL was undergoing revision and to provide QA for the updated version of DCAL. The complex methodology employed in the derivation of cancer risk coefficients presents a challenge for QA, and as such, this report describes the QA steps used by the ORNL dosimetry team in this process as implemented in DCAL and QCAL for Federal Guidance Report No. 16.

61 RADIATION PROTECTION AND DOSIMETRY↗
NASA NTRS2006

Integrated Modeling Environment

The Integrated Modeling Environment (IME) is a software system that establishes a centralized Web-based interface for integrating people (who may be geographically dispersed), processes, and data involved in a common engineering project. The IME includes software tools for life-cycle management, configuration management, visualization, and collaboration.

Mosier, Gary↗