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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 1,783 records · Page 99
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Dose-Dependent Cortical Thinning After Partial Brain Irradiation in High-Grade Glioma

Purpose: Radiation-induced cognitive deficits may be mediated by tissue damage to cortical regions. Volumetric changes in cortex can be reliably measured using high-resolution magnetic resonance imaging (MRI). We used these methods to study the association between radiation therapy (RT) dose and change in cortical thickness in high-grade glioma (HGG) patients. Methods and Materials: We performed a voxel-wise analysis of MRI from 15 HGG patients who underwent fractionated partial brain RT. Three-dimensional MRI was acquired pre- and 1 year post RT. Cortex was parceled with well-validated segmentation software. Surgical cavities were censored. Each cortical voxel was assigned a change in cortical thickness between time points, RT dose value, and neuroanatomic label by lobe. Effects of dose, neuroanatomic location, age, and chemotherapy on cortical thickness were tested using linear mixed effects (LME) modeling. Results: Cortical atrophy was seen after 1 year post RT with greater effects at higher doses. Estimates from LME modeling showed that cortical thickness decreased by −0.0033 mm (P<.001) for every 1-Gy increase in RT dose. Temporal and limbic cortex exhibited the largest changes in cortical thickness per Gy compared to that in other regions (P<.001). Age and chemotherapy were not significantly associated with change in cortical thickness. Conclusions: We found dose-dependent thinning of the cerebral cortex, with varying neuroanatomical regional sensitivity, 1 year after fractionated partial brain RT. The magnitude of thinning parallels 1-year atrophy rates seen in neurodegenerative diseases and may contribute to cognitive decline following high-dose RT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS2006

UID.. .Now That's Gonna Leave A Mark

Since 1975 bar codes on products at the retail counter have been accepted as the standard for entering product identity for price determination. Since the beginning of the 21st century, the Data Matrix symbol has become accepted as the bar code format that is marked directly on a part, assembly or product that is durable enough to identify that item for its lifetime. NASA began the studies for direct part marking Data Matrix symbols on parts during the Return to Flight activities after the Challenger Accident. Over the 20 year period that has elapsed since Challenger, a mountain of studies, analyses and focused problem solutions developed by and for NASA have brought about world changing results. NASA Technical Standard 6002 and NASA Handbook 6003 for Direct Part Marking Data Matrix Symbols on Aerospace Parts have formed the basis for most other standards on part marking internationally. NASA and its commercial partners have developed numerous products and methods that addressed the difficulties of collecting part identification in aerospace operations. These products enabled the marking of Data Matrix symbols in virtually every situation and the reading of symbols at great distances, severe angles, under paint and in the dark without a light. Even unmarkable delicate parts now have a process to apply a chemical mixture, recently trademarked as Nanocodes, that can be converted to Data Matrix information through software. The accompanying intellectual property is protected by ten patents, several of which are licensed. Direct marking Data Matrix on NASA parts dramatically decreases data entry errors and the number of parts that go through their life cycle marked, two major threats to sound configuration management and flight safety. NASA is said to only have people and stuff with information connecting them. Data Matrix is one of the most significant improvements since Challenger to the safety and reliability of that connection.

Schramm, Fred↗
NASA NTRS2008

UID...Now That's Gonna Leave a Mark

Since 1975 bar codes on products at the retail counter have been accepted as the standard for entering product identity for price determination. Since the beginning of the 21st century, the Data Matrix symbol has become accepted as the bar code format that is marked directly on a part, assembly or product that is durable enough to identify that item for its lifetime. NASA began the studies for direct part marking Data Matrix symbols on parts during the Return to Flight activities after the Challenger Accident. Over the 20 year period that has elapsed since Challenger, a mountain of studies, analyses and focused problem solutions developed by and for NASA have brought about world changing results. NASA Technical Standard 6002 and NASA Handbook 6003 for Direct Part Marking Data Matrix Symbols on Aerospace Parts have formed the basis for most other standards on part marking internationally. NASA and its commercial partners have developed numerous products and methods that addressed the difficulties of collecting part identification in aerospace operations. These products enabled the marking of Data Matrix symbols in virtually every situation and the reading of symbols at great distances, severe angles, under paint and in the dark without a light. Even unmarkable delicate parts now have a process to apply a chemical mixture, recently trademarked as Nanocodes, that can be converted to Data Matrix information through software. The accompanying intellectual property is protected by ten patents, several of which are licensed. Direct marking Data Matrix on NASA parts dramatically decreases data entry errors and the number of parts that go through their life cycle unmarked, two major threats to sound configuration management and flight safety. NASA is said to only have people and stuff with information connecting them. Data Matrix is one of the most significant improvements since Challenger to the safety and reliability of that connection.

Schramm, Harry F.↗
NASA NTRS2008

UID....Now That's Gonna Leave A Mark

Since 1975 bar codes on products at the retail counter have been accepted as the standard for entering product identity for price determination. Since the beginning of the 21 st century, the Data Matrix symbol has become accepted as the bar code format that is marked directly on a part, assembly or product that is durable enough to identify that item for its lifetime. NASA began the studies for direct part marking Data Matrix symbols on parts during the Return to Flight activities after the Challenger Accident. Over the 20 year period that has elapsed since Challenger, a mountain of studies, analyses and focused problem solutions developed by and for NASA have brought about world changing results. NASA Technical Standard 6002 and NASA Handbook 6003 for Direct Part Marking Data Matrix Symbols on Aerospace Parts have formed the basis for most other standards on part marking internationally. NASA and its commercial partners have developed numerous products and methods that addressed the difficulties of collecting part identification in aerospace operations. These products enabled the marking of Data Matrix symbols in virtually every situation and the reading of symbols at great distances, severe angles, under paint and in the dark without a light. Even unmarkable delicate parts now have a process to apply a chemical mixture, recently trademarked as Nanocodes, that can be converted to Data Matrix information through software. The accompanying intellectual property is protected by ten patents, several of which are licensed. Direct marking Data Matrix on NASA parts dramatically decreases data entry errors and the number of parts that go through their life cycle unmarked, two major threats to sound configuration management and flight safety. NASA is said to only have people and stuff with information connecting them. Data Matrix is one of the most significant improvements since Challenger to the safety and reliability of that connection.

Schramm, Harry F., Jr.↗
NASA NTRS2008

UID...Leaving Its Mark on the Universe

Since 1975 bar codes on products at the retail counter have been accepted as the standard for entering product identity for price determination. Since the beginning of the 21 st century, the Data Matrix symbol has become accepted as the bar code format that is marked directly on a part, assembly or product that is durable enough to identify that item for its lifetime. NASA began the studies for direct part marking Data Matrix symbols on parts during the Return to Flight activities after the Challenger Accident. Over the 20 year period that has elapsed since Challenger, a mountain of studies, analyses and focused problem solutions developed by and for NASA have brought about world changing results. NASA Technical Standard 6002 and NASA Handbook 6003 for Direct Part Marking Data Matrix Symbols on Aerospace Parts have formed the basis for most other standards on part marking internationally. NASA and its commercial partners have developed numerous products and methods that addressed the difficulties of collecting part identification in aerospace operations. These products enabled the marking of Data Matrix symbols in virtually every situation and the reading of symbols at great distances, severe angles, under paint and in the dark without a light. Even unmarkable delicate parts now have a process to apply a chemical mixture, recently trademarked as Nanocodes, that can be converted to Data Matrix information through software. The accompanying intellectual property is protected by ten patents, several of which are licensed. Direct marking Data Matrix on NASA parts dramatically decreases data entry errors and the number of parts that go through their life cycle unmarked, two major threats to sound configuration management and flight safety. NASA is said to only have people and stuff with information connecting them. Data Matrix is one of the most significant improvements since Challenger to the safety and reliability of that connection.

Schramm, Harry F., Jr.↗
NASA NTRS2008

Robot Electronics Architecture

An electronics architecture has been developed to enable the rapid construction and testing of prototypes of robotic systems. This architecture is designed to be a research vehicle of great stability, reliability, and versatility. A system according to this architecture can easily be reconfigured (including expanded or contracted) to satisfy a variety of needs with respect to input, output, processing of data, sensing, actuation, and power. The architecture affords a variety of expandable input/output options that enable ready integration of instruments, actuators, sensors, and other devices as independent modular units. The separation of different electrical functions onto independent circuit boards facilitates the development of corresponding simple and modular software interfaces. As a result, both hardware and software can be made to expand or contract in modular fashion while expending a minimum of time and effort.

Garrett, Michael↗
NASA NTRSDate not supplied

Development of Physics-Based Transition Models for Unstructured-Mesh CFD Codes Using Deep Learning Models

Predicting transition locations over a vehicle surface is of fundamental importance for many engineering applications. With the transition information, the Reynolds-averaged Navier-Stokes (RANS) computations can turn on the turbulence model at the right locations so that drag, lift and other aerodynamic quantities can be accurately predicted. In contrast to the popularity of RANS-based transition modeling in which transition onset is governed by the turbulence equations, physics-based transition models that account for instability waves within the boundary layer, thus more compliant to flow physics, only gained more attention in recent years. This paper describes the development of a new physics-based transition model based on either the linear stability theory (LST) or parabolized stability equations (PSE). The model is designed to communicate with a structured or unstructured-mesh RANS solver back and forth in order to more accurately compute transition fronts over a three-dimensional body. In the developed model, the Python suite of interface codes in conjunction with the LASTRAC software can be executed autonomously to produce transition onset locations for a given laminar or RANS-computed transitional state. In addition, as a proof of concept, the tool set consists of a deep learning neural network model that has been designed and trained to predict instability wave evolutions inside the boundary layer for various instability wave mechanisms across a selected speed range. A machine-learned intelligent profile interpolation model has also been devised to enable reliable instability-wave spectra predictions with just a few points in the mean flow profiles.

Transition Modeling↗
DOE OSTI2023

Deployment of Dynamic Neural Network Optimization to Minimize Heat Rate During Ramping for Coal Power Plants (Final Technical Report)

Much success was achieved throughout the course of this project. A successful implementation of Dynamic Neural Network Optimization (D-NNO) was coupled with Adaptive Predictive Controls (APC) and a novel hardware installation comprised of an advanced sensor network (ASN) measuring mass-weighted averages of flue gas constituents above the horizontal superheater of a coal-fired utility boiler. From 2019 through 2023 (including an extension due to COVID delays), the team was able to prototype, evaluate, deploy, iterate, and ultimately finalize an advanced closed-loop control D-NNO system which demonstrated the ability to: •improve unit efficiency ~2.0% relative to unoptimized operation (represented as total fuel fired per MWh generated) •improve unit NOx emission rates 10%+ beyond static optimization baselines •improve unit temperature stability as much as 58% and on average 12% •improve operating load stability as much as 35% The culmination of this project has generated an advanced methodology of deploying specially designed recurrent neural networks (long short-term memory, gated recurrent unit, encoder-decoder networks, transformers, etc.), customized trajectory planning and closed-loop optimization modules capable of adapting to live electric grid responses and demands, self-tuning and adaptive expert controls constantly adjusting prediction parameters to real-time unit behavior, and a hardware/software package able to reliably calculate net unit heat rate (NUHR) in real-time using flue gas constituents, machine learning, and known combustion relationships. Through this real-time NUHR value, immediate feedback on system adjustments relative to operating efficiency was available, allowing for rapid improvements to system performance. In addition to development and deployment of the advanced D-NNO system, the approach methodology has been readily commercialized through the project platform Griffin Open Systems, LLC, the D-NNO software platform host. Similar methodologies to those developed by this project have already been deployed at 5 other units across the United States, with another 6 implementations scheduled, and more expected. Over the course of the project, multiple academic papers were submitted and accepted for publication within esteemed academic journals, and PhD students were trained and graduated, as well as undergraduate students becoming involved and participating to project objectives.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Demonstrating Advanced Sensors for In-Situ Monitoring Towards Qualification of Nuclear Relevant Components

The U.S. Department of Energy’s Office of Nuclear Energy Advanced Materials and Manufacturing Technologies (AMMT) program is pursuing qualification of laser powder bed fusion (LPBF) components for nuclear applications. A major focus of this effort is the use of in situ process monitoring and machine learning–based tools to establish real-time quality assurance. The primary objective of this report is to identify and evaluate the most relevant in situ sensor systems for LPBF, and to document the deployment of these systems across platforms critical to the AMMT program. This work demonstrates how in situ monitoring can detect process anomalies, track geometry-dependent flaws, and identify limiting combinations of processing parameters—particularly those related to energy density and complex geometries (e.g., overhanging structures). To support this goal, a diverse suite of sensor modalities was evaluated across LPBF platforms, including visible and near-infrared (NIR) imaging, fringe projection profilometry, long-wavelength infrared (LWIR) thermography, and high-speed photodiode/pyrometry systems. These sensor streams were integrated with Peregrine, a machine-agnostic software platform that, among other capabilities, can generate real-time process anomaly classification. This report documents sensor deployments on multiple AMMT flagship platforms, including the Concept Laser M2 and Renishaw AM400/AM250 systems. Calibration builds with complex, flaw-prone geometries such as unsupported overhangs, stepped features, and thin walls, were used to evaluate how well Peregrine and its associated sensors could detect process anomalies and other instabilities under varied energy densities. It will be shown how Peregrine reliably identifies common process anomalies such as recoater streaking, superelevation, etc., and can be used in post-build analysis for anomaly spatial distributions throughout the build height to better understand the impact of geometry and processing parameter choice on the build. This work demonstrates measurable progress toward the vision that components can be born-qualified by establishing a real-time monitoring framework, identifying limiting process conditions, and laying the foundation for sensor fusion–enabled prediction pipelines that are scalable across platforms and applicable to nuclear-relevant components.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1987

Flight problem evaluation for Space Shuttle Orbiter

The flight problems experienced with the reusable Space Shuttle Orbiter have decreased during subsequent flights of each vehicle. By comparison to first flights of previous vehicles, the problems encountered on the initial flight of each new vehicle entering the fleet decreased. This improvement in turn has reduced the turnaround time between flights significantly and thus greatly enhanced the increased Space Shuttle launch frequency. The reusable manned space vehicle concept necessitated the development of a flight problem recognition and resolution system which would enable a thorough and timely vehicle turnaround flow. Flight evaluation, testing, and repair of manned spacecraft to enhance reliability and to ensure mission success is a unique activity. Real-time recognition of the flight problem, prompt isolation of the cause, and timely implementation of the corrective action are the keys to maintaining an operational fleet. Examples of flight problems that have been encountered as well as the corrective actions implemented during the first 24 Space Shuttle missions are presented. The corrective actions taken to preclude problem recurrence include modifications of hardware designs, manufacturing processes, flight software, test methods, and operational procedures.

Mechelay, Joseph E.↗
NASA NTRS1994

Lyndon B. Johnson Space Center (JSC) proposed dual-use technology investment program in intelligent robots

This paper presents an overview of the proposed Lyndon B. Johnson Space Center (JSC) precompetitive, dual-use technology investment project in robotics. New robotic technology in advanced robots, which can recognize and respond to their environments and to spoken human supervision so as to perform a variety of combined mobility and manipulation tasks in various sectors, is an obejective of this work. In the U.S. economy, such robots offer the benefits of improved global competitiveness in a critical industrial sector; improved productivity by the end users of these robots; a growing robotics industry that produces jobs and profits; lower cost health care delivery with quality improvements; and, as these 'intelligent' robots become acceptable throughout society, an increase in the standard of living for everyone. In space, such robots will provide improved safety, reliability, and productivity as Space Station evolves, and will enable human space exploration (by human/robot teams). The proposed effort consists of partnerships between manufacturers, universities, and JSC to develop working production prototypes of these robots by leveraging current development by both sides. Currently targeted applications are in the manufacturing, health care, services, and construction sectors of the U.S. economy and in the inspection, servicing, maintenance, and repair aspects of space exploration. But the focus is on the generic software architecture and standardized interfaces for custom modules tailored for the various applications allowing end users to customize a robot as PC users customize PC's. Production prototypes would be completed in 5 years under this proposal.

Erikson, Jon D.↗
NASA NTRS1994

Lyndon B. Johnson Space Center (JSC) proposed dual-use technology investment program in intelligent robotics

This paper presents an overview of the proposed Lyndon B. Johnson Space Center (JSC) precompetitive, dual-use technology investment project in robotics. New robotic technology in advanced robots, which can recognize and respond to their environments and to spoken human supervision so as to perform a variety of combined mobility and manipulation tasks in various sectors, is an objective of this work. In the U.S. economy, such robots offer the benefits of improved global competitiveness in a critical industrial sector; improved productivity by the end users of these robots; a growing robotics industry that produces jobs and profits; lower cost health care delivery with quality improvements; and, as these 'intelligent' robots become acceptable throughout society, an increase in the standard of living for everyone. In space, such robots will provide improved safety, reliability, and productivity as Space Station evolves, and will enable human space exploration (by human/robot teams). The proposed effort consists of partnerships between manufacturers, universities, and JSC to develop working production prototypes of these robots by leveraging current development by both sides. Currently targeted applications are in the manufacturing, health care, services, and construction sectors of the U.S. economy and in the inspection, servicing, maintenance, and repair aspects of space exploration. But the focus is on the generic software architecture and standardized interfaces for custom modules tailored for the various applications allowing end users to customize a robot as PC users customize PC's. Production prototypes would be completed in 5 years under this proposal.

Erickson, Jon D.↗
NASA NTRS2014

Simulation and Control Lab Development for Power and Energy Management for NASA Manned Deep Space Missions

The development of distributed hierarchical and agent-based control systems will allow for reliable autonomous energy management and power distribution for on-orbit missions. Power is one of the most critical systems on board a space vehicle, requiring quick response time when a fault or emergency is identified. As NASAs missions with human presence extend beyond low earth orbit autonomous control of vehicle power systems will be necessary and will need to reliably function for long periods of time. In the design of autonomous electrical power control systems there is a need to dynamically simulate and verify the EPS controller functionality prior to use on-orbit. This paper presents the work at NASA Glenn Research Center in Cleveland, Ohio where the development of a controls laboratory is being completed that will be utilized to demonstrate advanced prototype EPS controllers for space, aeronautical and terrestrial applications. The control laboratory hardware, software and application of an autonomous controller for demonstration with the ISS electrical power system is the subject of this paper.

Space Flight↗
DOE OSTI2017

Improving plant efficiency through the installation of TecSOLCEP online monitoring system - 362

In February 2016, Nuclear Energy Institute (NEI) launched its 'Delivering the Nuclear Promise (DNP)' strategic plan with the objective of reducing electric generating costs by 30% across the nuclear power industry by 2018. Improving efficiency has been addressed as one of the strategic focus areas in the plan. In nuclear power plants (NPPs) there is room for improvement in main components efficiency and TecSOLCEP is a software tool that has proved its value for that purpose. TecSOLCEP is a software tool for monitoring, diagnosing and quantifying performance deviations in Power Plants. It faithfully follows the methodology of ASME standards. Over 15 years of success stories in more than 50 electric power plants of different technologies worldwide, justify the benefits for the plants. The implicit concept in TecSOLCEP is 'Benefit based Maintenance' (BbM) as complementary to usual maintenance strategies like time-based, condition-based or predictive. These maintenance strategies are oriented to obtain the Safety and Reliability goals shared by all the electricity generation technologies. BbM is oriented to get the maximum economic benefit by Efficiency care, which historically has not been a priority, especially in nuclear plants. BbM applied with the help of performance monitoring tools like TecSOLCEP, is called to play an important role to improve efficiency which, in plants mainly operating at full power, is equivalent to increase the maximum power. Nuclear power plants that intend to extend their lives may also take advantage of identifying and quantifying inefficiencies in equipment to better address necessary investments. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Micromachined ceramic-based chipless LC resonator for high-temperature wireless sensing applications in harsh environments

The primary objective of this work was the fabrication and testing of a wireless LC resonator based on micro-patterned electroceramic materials for the monitoring of high-temperature systems. The twodimensional planar LC resonator sensors were designed and simulated using ANSYS Maxwell software, and these sensors were then fabricated from electrically conductive La 2 NiO 4 /Al 2 O 3 particulate inks. Initially, the phases of La 2 NiO 4 /Al 2 O 3 composite were evaluated by XRD. The patterning and deposition of the ink were completed using a novel micro-casting process onto Al 2 O 3 ceramic substrates, and the final pattern was bonded onto the substrate at 1200 °C for 2 h. The features and the reliability were analyzed by SEM microscopy. The frequency shift with respect to temperature was measured, which is directly related to changes in the sensor’s dielectric permittivity and pattern dimensions. The sensors were characterized at 500 °C–1000 °C in an ambient atmosphere with an RF signal ranging from 10–80 MHz at 175 kHz·s –1 sweep rate. The sensors showed a sensitivity of ~350 kHz °C –1 from 500 °C–1000 °C. Here, a new robust and adaptive signal processing approach was introduced to increase the degree of freedom for analyzing wireless sensors.

42 ENGINEERING↗
DOE OSTI2021

A Targeted Sequencing Assay for Serotyping Escherichia coli Using AgriSeq Technology

The gold standard method for serotyping Escherichia coli has relied on antisera-based typing of the O- and H-antigens, which is labor intensive and often unreliable. In the post-genomic era, sequence-based assays are potentially faster to provide results, could combine O-serogrouping and H-typing in a single test, and could simultaneously screen for the presence of other genetic markers of interest such as virulence factors. Whole genome sequencing is one approach; however, this method has limited multiplexing capabilities, and only a small fraction of the sequence is informative for subtyping or identifying virulence potential. A targeted, sequence-based assay and accompanying software for data analysis would be a great improvement over the currently available methods for serotyping. The purpose of this study was to develop a high-throughput, molecular method for serotyping E. coli by sequencing the genes that are required for production of O- and H-antigens, as well as to develop software for data analysis and serotype identification. To expand the utility of the assay, targets for the virulence factors, Shiga toxins ( stx 1 , and stx 2 ) and intimin ( eae ) were included. To validate the assay, genomic DNA was extracted from O-serogroup and H-type standard strains and from Shiga toxin-producing E. coli , the targeted regions were amplified, and then sequencing libraries were prepared from the amplified products followed by sequencing of the libraries on the Ion S5™ sequencer. The resulting sequence files were analyzed via the SeroType Caller™ software for identification of O-serogroup, H-type, and presence of stx 1 , stx 2 , and eae . We successfully identified 169 O-serogroups and 41 H-types. The assay also routinely detected the presence of stx 1a,c,d (3 of 3 strains), stx 2c−e,g (8 of 8 strains), stx 2f (1 strain), and eae (6 of 6 strains). Taken together, the high-throughput, sequence-based method presented here is a reliable alternative to antisera-based serotyping methods for E. coli .

Elder, Jacob R.↗
DOE OSTI2020

Accelerating Hanford Site Cleanup through Operations Research Modeling - 20238

The Hanford Site cleanup effort will require the integration of dozens of unique facilities and processes, many of which will be first-of-a-kind in implementation and design. Each facility will be governed by its own set of operating logic, configured with a unique array of unit operations, and subject to a set of constraints that will affect its behavior. The collection of facilities have multiple points of interface, making the operations of any one facility potentially significant to the operations of other up- or downstream processes. It is therefore highly desirable to accurately predict these operations, as it allows for Site officials to identify and preempt bottlenecks and vulnerabilities before they unexpectedly inhibit the cleanup mission. With the quantity and complexity of the processes that will be on Site, building a pen-and-paper or even a spreadsheet-assisted model of the cleanup mission quickly becomes overwhelming in scope and inaccurate in execution. The Engineering organization for the Site's Tank Operations Contract (TOC) has therefore implemented the use of operations research (OR) modeling to simulate and predict future operations of Site facilities. These models are created using a discrete event simulation tool that allows for the development of detailed, versatile, and robust models. Not only can these models account for complex logical behaviors, but they can also simulate process details down to the level of vessel sizing, labor utilization, equipment reliability, and resource availability. To date, the TOC has developed OR models for several facilities on Site, including for single-shell tank (SST) farms, double-shell tank (DST) farms, the Effluent Treatment Facility (ETF), and the waste transfer system. These models have focused on identifying bottlenecks and operational constraints, and have been used to quantify the effects of implementing process changes. This latter point is particularly valuable, as it allows for several alternatives to be studied in a virtual setting before committing resources to making a change in the field. The decision to develop OR models has gained tremendous support from the Site's stakeholders and the U.S. Department of Energy (DOE) management, and has prompted the use of the tool to support additional internal and external initiatives. Recently, an initiative was proposed to use the models to help identify and provide quantitative backing for risks and opportunities for the TOC. This application of OR could not only help inform how the TOC manages its risks (e.g. quantities and types of spare parts), but could also help drive process improvements whose benefits might otherwise be hard to quantify. The models have also been used to drive the TOC's cloud computing, artificial intelligence (AI), and machine learning (ML) initiatives. These initiatives will not only improve the ability of the TOC to more rapidly respond to the needs of its customers, but it will also aid in the ability of the TOC to analyze and improve the processes it studies. Partnership with two external software development and consulting companies (Lanner and Ynformed) has furthered not only the application of AI and ML within the TOC, but has also spurred the development of new/improved software tools and platforms used by the companies. These partnerships have proven to be mutually beneficial and productive, and have set a precedent for the types of gains that can be made by exploring such options. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2016

Goal Structuring Notation in a Radiation Hardening Assurance Case for COTS-Based Spacecraft

A systematic approach is presented to constructing a radiation assurance case using Goal Structuring Notation (GSN) for spacecraft containing COTS parts. The GSN paradigm is applied to an SRAM single-event upset experiment board designed to fly on a CubeSat in January 2017. A custom software language for development of a GSN assurance case is under development at Vanderbilt. Construction of a radiation assurance case without use of hardened parts or extensive radiation testing is discussed.

Radiation Effects Modeling (REM)↗