A Software Architecture for Automating Operations Processes
The Operations Engineering Lab at JPL has developed a software architecture based on an integrated toolkit approach for simplifying and automating mission operations tasks.
software↗
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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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New Data on the Topside Electron Density Distribution
The existing uncertainties about the electron density profiles in the topside ionosphere, i.e., in the height region from hmF2 to approx. 2000 km, require the search for new data sources. The ISIS and Alouette topside sounder satellites from the sixties to the eighties recorded millions of ionograms and most were not analyzed in terms of electron density profiles. In recent years an effort started to digitize the analog recordings to prepare the ionograms for computerized analysis. As of November 2001 about 350,000 ionograms have been digitized from the original 7-track analog tapes. These data are available in binary and CDF format from the anonymous ftp site of the National Space Science Data Center. A search site and browse capabilities on CDAWeb assist the scientific usage of these data. All information and access links can be found at http://nssdc.gsfc.nasa.gov/space/isis/isis-status.html. This paper describes the ISIS data restoration effort and shows how the digital ionograms are automatically processed into electron density profiles from satellite orbit altitude (1400 km for ISIS-2) down to the F peak. Because of the large volume of data an automated processing algorithm is imperative. The automatic topside ionogram scaler with true height algorithm TOPIST software developed for this task is successfully scaling approx.70 % of the ionograms. An 'editing process' is available to manually scale the more difficult ionograms. The automated processing of the digitized ISIS ionograms is now underway, producing a much-needed database of topside electron density profiles for ionospheric modeling covering more than one solar cycle. The ISIS data restoration efforts are supported through NASA's Applied Systems and Information Research Program.
Huang, Xue-Qin↗
Automating the process of estimating spacecraft mass
To help prevent the problem of mass reduction late in a spacecraft development program, the process of estimating spacecraft mass has been formulated in algorithmic form and incorporated in software that will allow trained users to interface with the integral design parameters data base interactively. The software will use historical data to extrapolate future values of a given time-dependent parameter and be manipulated by a dynamic graphics configuration builder. Future expansions of this work promise to automate the entire conceptual mission design process.
Skinner, D. L.↗
Atmosphere Processing Module Automation and Catalyst Durability Analysis for Mars ISRU Pathfinder
The Mars In-Situ Resource Utilization Pathfinder was designed to create fuel using components found in the planet’s atmosphere and regolith for an ascension vehicle to return a potential sample return or crew return vehicle from Mars. The Atmosphere Processing Module (APM), a subunit of the pathfinder, uses cryocoolers to isolate and collect carbon dioxide from Mars simulant gas. The carbon dioxide is fed with hydrogen into a Sabatier reactor where methane is produced. The APM is currently undergoing the final stages of testing at Kennedy Space Center prior to process integration testing with the other subunits of the pathfinder. The automation software for the APM cryocoolers was tested and found to perform nominally. The catalyst used for the Sabatier reactor was investigated to determine the factors contributing to catalyst failure. The results from the catalyst testing require further analysis, but it appears that the rapid change in temperature during reactor start up or the elevated operating temperature is responsible for the changes observed in the catalyst.
Atmosphere Processing Module↗
Precursor Analysis Report: Blackmatter Ransomware Attack on New Cooperative 2021
The BlackMatter Ransomware Attack on New Cooperative 2021 Precursor Analysis Report leverages publicly available information about the New Cooperative cyber attack and catalogs anomalous observables for each technique employed in the attack. This analysis is based upon the methodology of the Cybersecurity for the Operational Technology Environment (CyOTE) program. The BlackMatter ransomware was first identified in July 2021 and is reported to have infected more than 50 corporations around the world. , The Iowa-based grain cooperative, New Cooperative, was impacted by the BlackMatter ransomware on or before 18 September 2021. The adversary likely resided on New Cooperative’s networks for 15 days prior to encrypting its network and demanding New Cooperative pay $5.9 million in ransom by 25 September to unlock systems and prevent 1 terabyte (TB) of sensitive data from being publicly released. It is not clear if New Cooperative paid the ransom. The full impact of the ransomware attack is not known; however, according to New Cooperative’s general manager, the attack caused the company’s automated processes to revert back to processes used in the 1970s. , As of 6 October, only 50 percent of New Cooperative’s operations were utilizing automated processes. The company took eight weeks to rebuild the entire network and information technology (IT) systems from the ground up, which puts the date of fully recovery around 13 November. Researchers and analysts identified 20 unique techniques utilized during the attack with a total of 404 observables using MITRE ATT&CK® for Industrial Control Systems. The CyOTE program assesses observables accompanying techniques used prior to the triggering event to identify opportunities to detect malicious activity. If observables accompanying the attack techniques are perceived and investigated prior to the triggering event, earlier comprehension of malicious activity can take place. Seventeen of the identified techniques used during the New Cooperative cyber attack were precursors to the triggering event. Analysis identified 360 observables associated with these precursor techniques, 284 of which were assessed to have an increased likelihood of being perceived in the 15 days preceding the triggering event. The response and comprehension time could have been reduced if the observables had been identified earlier. The information gathered in this report contributes to a library of observables tied to a repository of artifacts, data sources, and technique detection references for practitioners and developers to support the comprehension of indicators of attack. Asset owners and operators can use these products if they experience similar observables or to prepare for comparable scenarios.
45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
Edge processing for automated facility monitoring
Explore the source record for details and available documents.
99 GENERAL AND MISCELLANEOUS↗
Edge processing for automated facility monitoring
Explore the source record for details and available documents.
99 GENERAL AND MISCELLANEOUS↗
Automating the Processing of Earth Observation Data
NASA s vision for Earth science is to build a "sensor web": an adaptive array of heterogeneous satellites and other sensors that will track important events, such as storms, and provide real-time information about the state of the Earth to a wide variety of customers. Achieving this vision will require automation not only in the scheduling of the observations but also in the processing of the resulting data. To address this need, we are developing a planner-based agent to automatically generate and execute data-flow programs to produce the requested data products.
Golden, Keith↗
Electron Density Profiles of the Topside Ionosphere
The existing uncertainties about the electron density profiles in the topside ionosphere, i.e., in the height region from h,F2 to - 2000 km, require the search for new data sources. The ISIS and Alouette topside sounder satellites from the sixties to the eighties recorded millions of ionograms but most were not analyzed in terms of electron density profiles. In recent years an effort started to digitize the analog recordings to prepare the ionograms for computerized analysis. As of November 2001 about 350000 ionograms have been digitized from the original 7-track analog tapes. These data are available in binary and CDF format from the anonymous ftp site of the National Space Science Data Center. A search site and browse capabilities on CDAWeb assist the scientific usage of these data. All information and access links can be found at http://nssdc.gsfc.nasa.gov/space/isis/isis- status.htm1. This paper describes the ISIS data restoration effort and shows how the digital ionograms are automatically processed into electron density profiles from satellite orbit altitude (1400 km for ISIS-2) down to the F peak. Because of the large volume of data an automated processing algorithm is imperative. The TOPside Ionogram Scaler with True height algorithm TOPIST software developed for this task is successfully scaling - 70% of the ionograms. An < > is available to manually scale the more difficult ionograms. The automated processing of the digitized ISIS ionograms is now underway, producing a much-needed database of topside electron density profiles for ionospheric modeling covering more than one solar cycle.
Huang, Xue-Qin↗
Automated Data Processing as an AI Planning Problem
NASA s vision for Earth Science is to build a "sensor web"; an adaptive array of heterogeneous satellites and other sensors that will track important events, such as storms, and provide real-time information about the state of the Earth to a wide variety of customers. Achieving his vision will require automation not only in the scheduling of the observations but also in the processing af tee resulting data. Ta address this need, we have developed a planner-based agent to automatically generate and execute data-flow programs to produce the requested data products. Data processing domains are substantially different from other planning domains that have been explored, and this has led us to substantially different choices in terms of representation and algorithms. We discuss some of these differences and discuss the approach we have adopted.
Golden, Keith↗
The evolution of automated launch processing
The NASA Launch Processing System (LPS) to which attention is presently given has arrived at satisfactory solutions for the distributed-computing, good user interface and dissimilar-hardware interface, and automation-related problems that emerge in the specific arena of spacecraft launch preparations. An aggressive effort was made to apply the lessons learned in the 1960s, during the first attempts at automatic launch vehicle checkout, to the LPS. As the Space Shuttle System continues to evolve, the primary contributor to safety and reliability will be the LPS.
Tomayko, James E.↗
Flexible manufacturing for photonics device assembly
The assembly of photonics devices such as laser diodes, optical modulators, and opto-electronics multi-chip modules (OEMCM), usually requires the placement of micron size devices such as laser diodes, and sub-micron precision attachment between optical fibers and diodes or waveguide modulators (usually referred to as pigtailing). This is a very labor intensive process. Studies done by the opto-electronics (OE) industry have shown that 95 percent of the cost of a pigtailed photonic device is due to the use of manual alignment and bonding techniques, which is the current practice in industry. At Lawrence Livermore National Laboratory, we are working to reduce the cost of packaging OE devices through the use of automation. Our efforts are concentrated on several areas that are directly related to an automated process. This paper will focus on our progress in two of those areas, in particular, an automated fiber pigtailing machine and silicon micro-technology compatible with an automated process.
Lu, Shin-Yee↗
Qualification of the gritblast assembly and process for the inside diameter of the RSRM forward and aft domes
This gritblast assembly shall be used when refurbishing the Inside Diameter (ID) of RSRM forward and aft domes. Initial blasting is used to remove corrosion and adhesive not removed during the insulation washout. Final blasting is conducted just prior to part finalization in order to remove residual contamination and prepare the ID surface for bonding. The media used in this gritblaster is DuPont Zirclean Blasting Abrasive. It is possible to use other media in this gritblast assembly, however the only facility that has the control capability for this assembly is the Zirclean blast booth. This blast booth can not use other media without the occurrence of contamination. This automated process shall replace the manually controlled gritblasting that is currently in operation. Manual gritblasting does not provide the consistency, control, and safety that an automated process is capable of delivering.
Nolan, Michael J.↗
Automated space processing payloads study. Volume 2, book 2: Technical report, appendices A through E
Experiment hardware and operational requirements for space shuttle experiments are discussed along with payload and system concepts. Appendixes are included in which experiment data sheets, chamber environmental control and monitoring, method for collection and storage of electrophoretically-separated samples, preliminary thermal evaluation of electromagnetic levitation facilities L1, L2, and L3, and applicable industrial automation equipment are discussed.
Source record↗
Optimized Carbon Fiber Intermediate Development to Enable High-Volume Manufacturing of Lightweight Automotive Composites
The ongoing pursuit of improved fuel economy and reduced greenhouse gas emissions has resulted in sustained interest for lightweight materials technologies. In this context, carbon fiber composites have captured the imagination of automotive engineers due to the potential to achieve substantial mass reduction when compared to traditional steel construction. That stated, the use of carbon fiber composites in automotive has been limited for the most part to premium supercars and other derivative platforms. In these cases, manufacturing costs are less of an obstacle to implementation, and the performance benefits of carbon fiber have enabled production of structures offering more than 50% weight savings. In practice, translating these low-volume demonstrations onto high-volume vehicle platforms has remained challenging. This can be attributed to several factors, with the absence of suitable high throughput production methodologies being a key impediment. To date, structural, crash critical components have relied upon manufacturing techniques born out of the aerospace industry. This has created a disconnect between automotive production systems that are accustomed to manufacturing multiple parts per minute and the aerospace technologies that have cycle times in the order of hours. Consequently, the focus of this project is the development of manufacturing process technology for carbon fiber composites that can support a mainstream vehicle program at an assumed throughput of 100,000 vehicles per year. In practice, this translates to a part-to-part cycle time of less than 3 minutes. Project participation included contributions from a broad range of academic, industrial and national lab partners. The primary scope of work, being the development of new carbon fiber epoxy compounds that are stable at room temperature and suited to high throughput automated processing. For project management, the work streams were divided into six key areas, with the lead organization in parentheses. • Carbon fiber/epoxy materials formulation development and scale up (Dow) • Simulation of discontinuous near isotropic meso-structure intermediates (Purdue) • Simulation of mechanical performance of compression molded components (Purdue) • Meso-Scale morphological analysis and correlation with structural performance (UTK) • Paint and adhesion durability analysis (MSU) • Demonstrator part design, prototype production, and validation testing (Ford). The primary goal at the commencement of the project was development of a chopped carbon fiber sheet molding compound (SMC) that offered a three times improvement in tensile modulus over a comparable glass-based SMC. In addition to meeting mechanical performance targets, the resin kinetics were modified to achieve a processing cycle time of less than 3 minutes. Other critical-to-quality (CTQ) specifications were also stipulated to account for a broad range of materials and processing characteristics. To achieve the above, staff scientists at Dow Chemical created an extensive series of new epoxy blends for testing and validation. Throughout this development, a key challenge was attaining material performance goals without impacting processing behavior and paintability of finished components. The latter required a new internal mold release system being developed by Dow that was designed to complement the kinetics of the rapid cure epoxy. As a complement to work studies at the industrial partners, the teams from academia executed a series of analytical and experimental studies to investigate potential factors influencing CF-SMC performance. Unit cell models were developed to capture the meso-scale representations of the fiber matrix architecture. Results of this analysis and subsequent morphological investigations led to the design of a novel composite derivative comprising carbon fiber platelets embedded in an epoxy matrix; the platelet size and aspect ratio playing significant role in final composite properties. This approach was a departure from previous research in CF-SMC development whereby bulk filamentization or disassembly of the carbon fiber rovings had been considered the most effective means of achieving both fiber wet through and wet-out. As the course of the academia studies progressed, the aspect ratio of the fiber constituents was further optimized before finalizing material attributes and processing conditions. For the purposes of technology validation, the Ford team led a work stream devoted to the design, fabrication and testing of demonstration components. The carbon fiber SMC material has the potential to displace numerous stampings and castings on an automotive structure but ultimately vehicle closure applications were selected to showcase the abilities of the CF-SMC to achieve both mass reduction and business case for large complex structures. Using target properties established by the Dow staff scientists, the complete closure system for a full-size sedan decklid and a mid-size wagon liftgate were engineered. Prototypes for both applications were fabricated using production representative processing methods to allow for physical testing and performance validation of the CF-SMC structures. Following completion of a testing program that concluded with a FMVSS301 55 mph offset rear crash, the CF-SMC formulation was declared by the Ford team to have met all engineering requirements. To summarize, the joint development activities during this project led to significant technical breakthroughs and achievement of all milestones. The result was the development of a novel, tack-free carbon fiber molding compound that is suited to automated processing. This combined room temperature stability, fast cure kinetics, and internal mold release system facilitates cycle times that are conducive to high-volume production. The VORAFUSE M6400 successfully passed technology validation at Ford and is now eligible for consideration on future production commercial vehicle programs.
36 MATERIALS SCIENCE↗
Intelligent Machines in the 21st Century: Automating the Processes of Inference and Inquiry
The last century saw the application of Boolean algebra toward the construction of computing machines, which work by applying logical transformations to information contained in their memory. The development of information theory and the generalization of Boolean algebra to Bayesian inference have enabled these computing machines. in the last quarter of the twentieth century, to be endowed with the ability to learn by making inferences from data. This revolution is just beginning as new computational techniques continue to make difficult problems more accessible. However, modern intelligent machines work by inferring knowledge using only their pre-programmed prior knowledge and the data provided. They lack the ability to ask questions, or request data that would aid their inferences. Recent advances in understanding the foundations of probability theory have revealed implications for areas other than logic. Of relevance to intelligent machines, we identified the algebra of questions as the free distributive algebra, which now allows us to work with questions in a way analogous to that which Boolean algebra enables us to work with logical statements. In this paper we describe this logic of inference and inquiry using the mathematics of partially ordered sets and the scaffolding of lattice theory, discuss the far-reaching implications of the methodology, and demonstrate its application with current examples in machine learning. Automation of both inference and inquiry promises to allow robots to perform science in the far reaches of our solar system and in other star systems by enabling them to not only make inferences from data, but also decide which question to ask, experiment to perform, or measurement to take given what they have learned and what they are designed to understand.
Knuth, Kevin H.↗
NASA biological and physical sciences databases: who’s the FAIRest of them all?
Conceptual models are a key part of the foundation of scientific study. Scientific data discovery and retrieval are often inaccurate and incomplete because these models are not sufficiently well-incorporated into data retrieval systems. Systems often don’t provide the necessary tools to those producing scientific data to fully and unambiguously annotate them and the result is consumers of the data cannot find them efficiently. The capability of data archives to provide these tools to link data to underlying conceptual models is one of dimensions of the recently developed “FAIR” principles (https://www.go-fair.org/fair-principles/ ), and is key to many automated processes being able to operate on these data, particularly analytics involving artificial intelligence. We used an open-source web service to measure the FAIR compliance of the three data archives operated by NASA for the biological and physical sciences: the Life Sciences Data Archive, the Physical Sciences Informatics database, and GeneLab. The service ingests references to data sets in these archives, and then executes domain-non-specific examinations of these data and metadata that test compliance to the FAIR principles. Of the 22 metrics tested, GeneLab passed 11 (50%), and PSI and LSDA each passed 7 (32%). These data were gathered using only one representative data set from each archive and we anticipate variability in results as we continue to apply these metrics to other data. A preliminary study of the failure traces for each metric suggests there is a wide range of effort and complexity in the enhancements required for each system to elevate FAIR compliance, and this is the subject of continued investigation. This information has been and will likely continue to be important information in planning these enhancements, with the goal of increased readiness of the data for automated processes.
database↗
The Technical, Economic, Risk, and Adoption Assessment for Evaluating Work Reduction Opportunities in the Nuclear Industry
Automation and cost-saving initiatives, such as process automation with advances in artificial intelligence, are gaining traction in modernization efforts across the nuclear industry. As these innovations are increasingly adopted, it becomes crucial to evaluate their impacts comprehensively. Various technical and economic attributes, along with risk and human readiness factors, must be achieved to ensure that innovative projects enabling automation and modernization are successful. However, no systematic or integrated framework exists that allows plants to evaluate these innovative projects. To address this gap, the Technical, Economic, Risk, and Adoption (TERA) assessment offers a structured method to evaluate innovative technologies, ensuring solutions meet both operational and safety standards. The TERA framework integrates the disparate perspectives to assess modernization opportunities in nuclear operations. It combines qualitative and quantitative models to evaluate the relationship between performance and business impacts, while also enabling continuous re-evaluation during project development. This approach helps plant owners identify high-priority opportunities, optimize cost savings, and minimize risks, ensuring projects remain on track to achieve desired returns. By providing a comprehensive, systematic methodology, TERA enables informed, data-driven decisions that support successful modernization efforts, enhancing efficiency, safety, and cost savings across nuclear operations. This paper explains the TERA framework and its benefits for the nuclear industry.
22 - GENERAL STUDIES OF NUCLEAR REACTORS↗