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NASA NTRS1988

Space information systems in the Space Station era; Proceedings of the AIAA/NASA International Symposium on Space Information Systems, Washington, DC and Greenbelt, MD, June 22, 23, 1987

Technological and planning issues for data management, processing, and communication on Space Station Freedom are discussed in reviews and reports by U.S., European, and Japanese experts. The space-information-system strategies of NASA, ESA, and NASDA are discussed; customer needs are analyzed; and particular attention is given to communication and data systems, standards and protocols, integrated system architectures, software and automation, and plans and approaches being developed on the basis of experience from past programs. Also included are the reports from workshop sessions on design to meet customer needs, the accommodation of growth and new technologies, and system interoperability.

Gerard, Mireille↗

NASA NTRS1992

A simple node and conductor data generator for SINDA

This paper presents a simple, automated method to generate NODE and CONDUCTOR DATA for thermal match modes. The method uses personal computer spreadsheets to create SINDA inputs. It was developed in order to make SINDA modeling less time consuming and serves as an alternative to graphical methods. Anyone having some experience using a personal computer can easily implement this process. The user develops spreadsheets to automatically calculate capacitances and conductances based on material properties and dimensional data. The necessary node and conductor information is then taken from the spreadsheets and automatically arranged into the proper format, ready for insertion directly into the SINDA model. This technique provides a number of benefits to the SINDA user such as a reduction in the number of hand calculations, and an ability to very quickly generate a parametric set of NODE and CONDUCTOR DATA blocks. It also provides advantages over graphical thermal modeling systems by retaining the analyst's complete visibility into the thermal network, and by permitting user comments anywhere within the DATA blocks.

Gottula, Ronald R.↗

NASA NTRS1998

The Design and Evaluation of "CAPTools"--A Computer Aided Parallelization Toolkit

Writing applications for high performance computers is a challenging task. Although writing code by hand still offers the best performance, it is extremely costly and often not very portable. The Computer Aided Parallelization Tools (CAPTools) are a toolkit designed to help automate the mapping of sequential FORTRAN scientific applications onto multiprocessors. CAPTools consists of the following major components: an inter-procedural dependence analysis module that incorporates user knowledge; a 'self-propagating' data partitioning module driven via user guidance; an execution control mask generation and optimization module for the user to fine tune parallel processing of individual partitions; a program transformation/restructuring facility for source code clean up and optimization; a set of browsers through which the user interacts with CAPTools at each stage of the parallelization process; and a code generator supporting multiple programming paradigms on various multiprocessors. Besides describing the rationale behind the architecture of CAPTools, the parallelization process is illustrated via case studies involving structured and unstructured meshes. The programming process and the performance of the generated parallel programs are compared against other programming alternatives based on the NAS Parallel Benchmarks, ARC3D and other scientific applications. Based on these results, a discussion on the feasibility of constructing architectural independent parallel applications is presented.

Yan, Jerry↗

NASA NTRS2007

A Web 2.0 and OGC Standards Enabled Sensor Web Architecture for Global Earth Observing System of Systems

This paper will describe the progress of a 3 year research award from the NASA Earth Science Technology Office (ESTO) that began October 1, 2006, in response to a NASA Announcement of Research Opportunity on the topic of sensor webs. The key goal of this research is to prototype an interoperable sensor architecture that will enable interoperability between a heterogeneous set of space-based, Unmanned Aerial System (UAS)-based and ground based sensors. Among the key capabilities being pursued is the ability to automatically discover and task the sensors via the Internet and to automatically discover and assemble the necessary science processing algorithms into workflows in order to transform the sensor data into valuable science products. Our first set of sensor web demonstrations will prototype science products useful in managing wildfires and will use such assets as the Earth Observing 1 spacecraft, managed out of NASA/GSFC, a UASbased instrument, managed out of Ames and some automated ground weather stations, managed by the Forest Service. Also, we are collaborating with some of the other ESTO awardees to expand this demonstration and create synergy between our research efforts. Finally, we are making use of Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) suite of standards and some Web 2.0 capabilities to Beverage emerging technologies and standards. This research will demonstrate and validate a path for rapid, low cost sensor integration, which is not tied to a particular system, and thus be able to absorb new assets in an easily evolvable, coordinated manner. This in turn will help to facilitate the United States contribution to the Global Earth Observation System of Systems (GEOSS), as agreed by the U.S. and 60 other countries at the third Earth Observation Summit held in February of 2005.

Mandl, Daniel↗

NASA NTRS1999

Reprocessing Microflare Data

The report concerns work on detecting and cataloging solar microflares using an automated. An accompanying figure represents the solar microflare distribution during the period of April 1991 to November 1992, the height of solar activity after the launch of CGRO. It also shows the distribution extending below the distribution obtained at GSFC by manual means. We have implemented significant refinements in the search algorithm. The algorithm in its simplest form searches for transient events and based upon the distribution of the signal among the different BATSE detectors, we can assign it to be of solar origin if the signal distribution conforms to what one expects from a burst or transient from that direction. One of the major problems in an earlier effort was to search for microflares and large flares simultaneously. The requirement for a dynamic range of almost 10(exp 4) resulted in ambiguous identifications at the low side of the distribution. We have since restricted the search to events with peak count rates under 2000/s. Larger events are easily identified in the manual search, so we have chosen not to duplicate that work. The second problem was that missing counts existed below channel 0 in the BATSE Large Area Detector (LAD) data. These have been recovered and are now included in the search process. This provides data below 20 keV, and as we get closer to the thermal part of the spectrum, it provides greater sensitivity. The third problem was that too many BATSE detectors were used in the search. Detectors with pointing directions far from the Sun, although detecting the event, had poorly known responses. Detectors greater than approximately 60 degrees off the Sun are no longer included in the search process. By reducing the systematic errors with the large off-axis detectors we can conduct more rigorous statistical tests of a candidate event to ascertain whether it originated from the solar direction. We have reprocessed the period in the early mission that covers solar maximum and constructed the microflare distribution shown in the figure. The results of the automated search start to deviate from the manual search results below about 1000/s. Not only do we now have this distribution but we have a database of solar microflares that was used to construct the distribution. This database contains the signal at higher energy channels as well as that in channel zero (and below). From this one can, using software at GSFC, construct a photon spectrum for some of the larger microflares. It can also be used in other solar studies, especially those that correlate the X-ray flux with emission at other wavelengths. With some additional effort we hope to integrate this database into the corresponding one residing at the Solar Data Analysis Center at GSFC. The entire CGRO mission's data can now be reprocessed to obtain the microflare distribution at all phases of the solar cycle. This work is in progress. The results of this work will be presented in forthcoming scientific workshops and conferences.

Ryan, James M.↗

NASA NTRS2024

SMAnalytics Automated Shape Memory Test Analysis Software User's Manual: UCFTC, UPER, and DSC Test Methods, Version 1.0.2

Over the course of 60 years of shape memory alloy research and development, the properties of these alloys have been measured using various testing methods, which are often customized by the organization performing the test. However, commercial adoption of shape memory alloys in aeronautic actuator applications requires reducing property uncertainty through standardizing test methods. Historically, differential scanning calorimetry (DSC) has been used to measure transformation temperatures under stress-free conditions. This testing method is well established, and tests are run under the applicable standard, ASTM F2004-17: Standard Test Method for Transformation Temperature of Nickel-Titanium Alloys by Thermal Analysis. Two other test methods for measuring strains and transformation temperatures under constant load or free recovery after prestraining have only recently been standardized—ASTM E3097: Standard Test Method for Mechanical Uniaxial Constant Force Thermal Cycling of SMAs (UCFTC) and ASTM E3098: Standard Test Method for Mechanical Uniaxial Pre-Strain and Thermal Free Recovery of SMAs (UPFR). These standards represent a critical step forward in producing reliable material property data for the use of these alloys in aeronautics and other commercial areas. However, no standard programs or software packages were previously available for postprocessing UCFTC- and UPFR-type test data to extract property data. Each organization that performed the testing analyzed data using its own custom manual methods, such as using a plot and a straight edge, spreadsheet plotting methods, or custom code routines, to extract the required values for strains, stresses, and transformation temperatures. SMAnalytics represents the first publicly available uniform software package for processing data generated using the DSC, UCFTC, and UPFR test methods, as well as many modifications of these methods, including loading in martensite versus austenite and performing multiple thermal cycles at stress. In doing so, it provides a tool for reducing potential error or variability in the measured values due to the precision of the technique used and person-to-person variability. It is also expected that this automated data-parsing tool can accelerate the data analysis phase of the test campaign, especially for large data files. This User’s Manual describes how the SMAnalytics software works and the method for its use.

Shape Memory Alloy↗

NASA NTRS1996

Automation of Data Analysis Programs Used in the Cryogenic Characterization of Superconducting Microwave Resonators

Knowledge of the microwave properties at cryogenic temperatures of components fabricated using High-Temperature-Superconductors (HTS) is useful in the design of HTS-based microwave circuits. Therefore, fast and reliable characterization techniques have been developed to study the aforementioned properties. In this paper, we discuss computer analysis techniques employed in the cryogenic characterization of HTS-based resonators. The revised data analysis process requires minimal user input. and organizes the data in a form that is easily accessible by the user for further examination. These programs retrieve data generated during the cryogenic characterization at microwave frequencies of HTS based resonators and use it to calculate parameters such as the loaded and unloaded quality factors (Q and Q(sub o), respectively), the resonant frequency (f(sub o)), and the coupling coefficient (k), which are important quantities in the evaluation of HTS resonators. While the data are also stored for further use, the programs allow the user to obtain a graphical representation of any of the measured parameters as a function of temperature soon after the completion of the cryogenic measurement cycle. Although these programs were developed to study planar HTS-based resonators operating in the reflection mode, they could also be used in the cryogenic characterization of two ports (i.e., reflection/transmission) resonators.

Creason, A. S.↗

DOE OSTI2025

Leveraging artificial intelligence and advanced food processing techniques for enhanced food safety, quality, and security: a comprehensive review

Artificial intelligence is emerging as a transformative force in addressing the multifaceted challenges of food safety, food quality, and food security. This review synthesizes advancements in AI-driven technologies, such as machine learning, deep learning, natural language processing, and computer vision, and their applications across the food supply chain, based on a comprehensive analysis of literature published from 1990 to 2024. AI enhances food safety through real-time contamination detection, predictive risk modeling, and compliance monitoring, reducing public health risks. It improves food quality by automating defect detection, optimizing shelf-life predictions, and ensuring consistency in taste, texture, and appearance. Furthermore, AI addresses food security by enabling resource-efficient agriculture, yield forecasting, and supply chain optimization to ensure the availability and accessibility of nutritious food resources. This review also highlights the integration of AI with advanced food processing techniques such as high-pressure processing, ultraviolet treatment, pulsed electric fields, cold plasma, and irradiation, which ensure microbial safety, extend shelf life, and enhance product quality. Additionally, the integration of AI with emerging technologies such as the Internet of Things, blockchain, and AI-powered sensors enables proactive risk management, predictive analytics, and automated quality control. By examining these innovations' potential to enhance transparency, efficiency, and decision-making within food systems, this review identifies current research gaps and proposes strategies to address barriers such as data limitations, model generalizability, and ethical concerns. These insights underscore the critical role of AI in advancing safer, higher-quality, and more secure food systems, guiding future research and fostering sustainable food systems that benefit public health and consumer trust.

AI↗

DOE OSTI2020

From smart homes to smart laboratories: connected instruments for materials science

The current focus on artificial intelligence and machine learning in the scientific community has the potential to greatly speed up discovery. In this article, we explore what a “smart facility” would mean for materials science. We propose to capture meta-data at every step of an experiment, including materials synthesis, sample production and characterization, simulation, and the analysis software used to extract information. Although most of this information is captured in various institutional systems and staff logbooks, more insight could be obtained by connecting this information through a system that allows automation. AI-enabled processes built on such a system would have the potential of making experiment planning easier and minimize the time between experiment and publication.

Doucet, Mathieu↗

DOE OSTI2020

Characterization and differentiation of aluminum powders used in improvised explosive devices – Part 1: Proof of concept of the utility of particle micromorphometry

Abstract Aluminum (Al) powders are commonly used in improvised explosive devices as metallic fuels, a component of explosive mixtures. These powders can be obtained readily from industrial‐scale and consumer products, and produced using unsophisticated “kitchen chemistry” techniques. This research demonstrates the potential of automated particle micromorphometry for comparisons between known source and questioned Al powders recovered from IEDs, as well as for insight into the method of Al powder manufacture. Al powder samples were obtained from legitimate manufacturers, and 56 samples were produced “in‐house” from Al‐containing spray paints and ball‐milled Al foils. Transmitted light microscope images of Al powder particles were acquired using an automated stage with automated z‐focus; 17 size and shape parameters were measured for all particles. Approximately 37,000–2,500,000 particles/sample were analyzed using an open‐source statistical package with customized code. Dimensionality reduction was required for processing the large datasets: eight of the 17 measured variables were selected based on inspection of the correlation matrix. Data from four subsamples from each of the 56 samples produced using “in‐house” methods were analyzed using ANOVA to assess the within‐ and between‐sample variation. High within‐sample variation was noted; however, ANOVA and post‐hoc Tukey's honestly significant difference (HSD) tests demonstrated that the between‐sample variation was substantially larger than the within‐sample variation. Each sample could be differentiated from all other samples in the test set. Future experiments will focus on ways to reduce the within‐sample variation, and additional statistical and microanalytical methods to classify sources and confidently constrain the method of Al powder manufacture.

Baldaino, JenaMarie↗

DOE OSTI2026

Python-EPICS RF Conditioning Automatic Control System at the Spallation Neutron Source

The RF Test Facility (RFTF) at the Spallation Neutron Source (SNS) is used for the conditioning of RF compo-nents such as ceramic vacuum windows and power cou-plers prior to their installation in the H- ion linear accel-erator. This process exposes components to high-power RF fields and thermal cycling to improve performance and remove surface impurities. To automate and optimize this process, a Python-based EPICS control system was developed alongside targeted hardware upgrades. The system enables real-time monitoring and control of RF power levels, temperature, and vacuum pressure. A user-friendly graphical interface was implemented using CS-Studio (Phoebus), allowing operators to adjust parameters and collect data efficiently. The system integrates a High-Power Protection Module (HPM) for interlocks based on vacuum and arc detection, ensuring safe operation. These upgrades have significantly improved the efficiency, accuracy, and safety of RF conditioning at the SNS RFTF. This paper describes the updated RF conditioning sys-tem, highlighting the software and hardware develop-ments and their application in support of the Proton Pow-er Upgrade (PPU) project.

Lee, Sung-Woo [ORNL] (ORCID:000000030915835X)↗

NASA NTRS1994

Dual-Use Space Technology Transfer Conference and Exhibition, Volume 1

This document contains papers presented at the Dual-Use Space Technology Transfer Conference and Exhibition held at the Johnson Space Center February 1-3, 1994. Possible technology transfers covered during the conference were in the areas of information access; innovative microwave and optical applications; materials and structures; marketing and barriers; intelligent systems; human factors and habitation; communications and data systems; business process and technology transfer; software engineering; biotechnology and advanced bioinstrumentation; communications signal processing and analysis; new ways of doing business; medical care; applications derived from control center data systems; human performance evaluation; technology transfer methods; mathematics, modeling, and simulation; propulsion; software analysis and decision tools systems/processes in human support technology; networks, control centers, and distributed systems; power; rapid development perception and vision technologies; integrated vehicle health management; automation technologies; advanced avionics; ans robotics technologies. More than 77 papers, 20 presentations, and 20 exhibits covering various disciplines were presented b experts from NASA, universities, and industry.

Kumar Krishen↗

NASA NTRS2003

Automated CFD Database Generation for a 2nd Generation Glide-Back-Booster

A new software tool, AeroDB, is used to compute thousands of Euler and Navier-Stokes solutions for a 2nd generation glide-back booster in one week. The solution process exploits a common job-submission grid environment using 13 computers located at 4 different geographical sites. Process automation and web-based access to the database greatly reduces the user workload, removing much of the tedium and tendency for user input errors. The database consists of forces, moments, and solution files obtained by varying the Mach number, angle of attack, and sideslip angle. The forces and moments compare well with experimental data. Stability derivatives are also computed using a monotone cubic spline procedure. Flow visualization and three-dimensional surface plots are used to interpret and characterize the nature of computed flow fields.

Chaderjian, Neal M.↗

NASA NTRS2007

Emergency Response Fire-Imaging UAS Missions over the Southern California Wildfire Disaster

Objectives include: Demonstrate capabilities of UAS to overfly and collect sensor data on widespread fires throughout Western US. Demonstrate long-endurance mission capabilities (20-hours+). Image multiple fires (greater than 4 fires per mission), to showcase extendable mission configuration and ability to either linger over key fires or station over disparate regional fires. Demonstrate new UAV-compatible, autonomous sensor for improved thermal characterization of fires. Provide automated, on-board, terrain and geo-rectified sensor imagery over OTH satcom links to national fire personnel and Incident commanders. Deliver real-time imagery (within 10-minutes of acquisition). Demonstrate capabilities of OTS technologies (GoogleEarth) to serve and display mission-critical sensor data, coincident with other pertinent data elements to facilitate information processing (WX data, ground asset data, other satellite data, R/T video, flight track info, etc).

Cobleigh, Brent R.↗

NASA NTRS2008

Emergency Response Fire-Imaging UAS Missions over the Southern California Wildfire Disaster

DelFrate, John H.↗

NASA NTRS2012

Mass Analyzers Facilitate Research on Addiction

The famous go/no go command for Space Shuttle launches comes from a place called the Firing Room. Located at Kennedy Space Center in the Launch Control Center (LCC), there are actually four Firing Rooms that take up most of the third floor of the LCC. These rooms comprise the nerve center for Space Shuttle launch and processing. Test engineers in the Firing Rooms operate the Launch Processing System (LPS), which is a highly automated, computer-controlled system for assembly, checkout, and launch of the Space Shuttle. LPS monitors thousands of measurements on the Space Shuttle and its ground support equipment, compares them to predefined tolerance levels, and then displays values that are out of tolerance. Firing Room operators view the data and send commands about everything from propellant levels inside the external tank to temperatures inside the crew compartment. In many cases, LPS will automatically react to abnormal conditions and perform related functions without test engineer intervention; however, firing room engineers continue to look at each and every happening to ensure a safe launch. Some of the systems monitored during launch operations include electrical, cooling, communications, and computers. One of the thousands of measurements derived from these systems is the amount of hydrogen and oxygen inside the shuttle during launch.

Source record↗

DOE OSTI2025

An In Situ , Automated High-Explosives Aging Method Utilizing Two-Dimensional Gas Chromatography–Mass Spectrometry

Understanding chemical changes that occur in high explosives as they age is of great importance to the safe employment and storage of these compounds. Traditional methods of aging high explosives even under accelerated aging conditions are time intensive with durations on the order of months to years. The nature of traditional aging analyses reduces each sample to a snapshot data point often separated widely in time, requiring many assumptions as to how the degradation products develop. Further complicating matters, several analytical techniques are typically employed for each sample analysis in order to ascertain an entire picture of the decomposition pathways. To address these shortcomings with existing methods, a new method of accelerated aging of high explosives utilizing comprehensive two-dimensional gas chromatography coupled to high-resolution mass spectrometry (GC × GC-HRMS) was developed using 2,4,6,8,10,12-hexanitro-2,4,6,8,10,12-hexaazaisowurtzitane (CL-20) as a model compound for method development. This in situ automated method reduces the time scale of aging to a matter of hours using the inlet of the GC × GC as the aging vessel. GC × GC in combination with HRMS allowed for the collection of both evolved gases and other decomposition products produced during the entire aging process in real time with HRMS providing far greater certainty in identification of explosives aging products. Additionally, this method allowed for a higher throughput of samples with greatly simplified sample preparation. Chemometric analysis of the GC × GC-HRMS data set via the alteration analysis (ALA) enabled discovery of statistically significant chemical changes providing insight into the variation of decomposition pathways with varying aging temperatures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2004

Improvements to the Two-Thickness Method for Deriving Acoustic Properties of Materials

The characteristic impedance and other derivative acoustic properties of a material can be derived from impedance tube data using the specific impedance measured from samples with two different thicknesses. In practice, samples are chosen so that their respective thicknesses differ by a factor of 2. This simplifies the solution of the equations relating the properties of the two samples so that the computation of the characteristic impedance is straightforward. This approach has at least two drawbacks. One is that it is often difficult to acquire or produce samples with precisely a factor of 2 difference in thickness. A second drawback is that the phase information contained in the imaginary part of the propagation constant must be unwrapped before subsequent computations are performed. For well-behaved samples, this is not a problem. For ill behaved samples of unknown properties, the phase unwrapping process can be tedious and difficult to automate. Two alternative approaches have been evaluated which remove the factor-of-2 sample thickness requirement and directly compute unwrapped phase angles. One uses a Newton-Raphson approach to solve for the roots of the samples' simultaneous equations. The other produces a wave number space diagram in which the roots are clearly discernable and easily extracted. Results are presented which illustrate the flexibility of analysis provided by the new approaches and how this can be used to better understand the limitations of the impedance tube data.

Palumbo, Daniel L.↗