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Artificial Intelligence (AI) Methods for Automating the Impact Tool Evidence Library

INTRODUCTION: The development of the Evidence Library for use with the IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces) probability risk assessment tool involved a multilayered, time intensive process of data collection and analysis by subject matter experts from the Exploration Medical Capability (ExMC) Element Clinical and Science Team to produce clinical findings forms (CliFFs) for 120 medical conditions. Artificial Intelligence Large Language Models (LLMs) can be leveraged to facilitate this process, thus reducing labor and time. TOPIC: CliFFs contain information about medical conditions as they pertain to spaceflight. This includes condition definitions, incidence data, crew task impairment estimates caused by conditions, treatment protocols and references to literature used for gathering condition evidence. Guided by the Evidence Library Methods document and the CliFF development instructions, a team has leveraged Microsoft Azure AI services and open-source documentation to construct an AI-assisted automated pipeline for CliFF development. This process is designed to search, retrieve, and evaluate the applicable data, and ultimately generate a completed CliFF. The LLM evaluates the relevance of each of the source materials to spaceflight, either as direct evidence or as an analog. The model extracts keywords and generates brief summaries to enhance search and retrieval in later stages of CliFF development. For instance, it can calculate epidemiological statistical data, such as incidence rates and the likelihood of best or worst-case scenarios. APPLICATION: Large Language Models (LLMs) can efficiently summarize large amounts of text. Leveraging this technology will automate data retrieval and evidence gathering for medical databases, like the IMPACT tool, by aiding in the labor-intensive process of analyzing large bodies of literature and organizing it into a formatted document like a CliFF. This added efficiency will enable expeditious expansion of the Evidence Library with additional medical conditions and update previous CLiFFs as new technology becomes available.

Ali Al↗
DOE OSTI2019

Challenges in Long-Term Records Preservation and Access - 19549

The US Department of Energy Office of Legacy Management (LM) mission includes preserving records and information about the nation's Cold War-era weapons projects and making that information available for years to come. As LM assumes responsibility for each project, records documenting operations and cleanup activities are absorbed into a central recordkeeping system. Each record category is governed by a federal retention requirement. Routine administrative records are kept just a few years, while the most important records have 'permanent' retention requirements and are transferred to the National Archives typically within 25 years of creation. It is relatively easy for LM to meet retention requirements for these routine and permanent records. LM's big preservation challenge is with records with tremendously long retention requirements. Records with 75-year retention requirements are common, and a small subset of LM records pertaining to waste disposal requires 150-year retention periods. LM must consider the best format for maintaining each of its records collections. Should physical records be boxed up for long-term storage, or should they be digitized? Each option has associated benefits, costs, and risks. Keeping records in paper format avoids digitizing expense and preserves the original media, but the paper must be maintained in a certified storage facility. A vermin infestation or sprinkler malfunction at a certified facility may be rare but could easily destroy records. Keeping the paper and making reference or backup electronic copies reduces the risk of loss but requires diligence and resources to keep the physical records and electronic versions synchronized. This becomes an overwhelming task in a database with millions of records. Entirely replacing paper records with digitized versions as electronic records introduces the risk that records could be lost due to a cybersecurity incident or made inaccessible by evolving technology. LM's early electronic records management efforts were limited to documents saved to PDF format. More recently, LM has embraced the benefits of maintaining records in native formats. (A spreadsheet includes formulas and other details lost when converted to a PDF file.) But whether the file is saved as a Microsoft Excel spreadsheet or PDF document, how do we ensure the file is readable in 75 or 150 years when these records meet their retention requirement? We have no way of knowing for sure from our 2019 vantage point-no more than we would expect to get good technology advice from someone 150 years ago. We cannot predict the technological future, but we can make sure our current electronic records environment is healthy and future ready. This includes making sure the electronic recordkeeping system is built on a modern platform and ensuring that each record in the system is saved in a current format. Quality standards are critical for electronic records to be future ready. Implementing quality involves an organization-wide approach to having consistently formatted file names and complete and descriptive metadata. Quality PDF documents are scanned to settings that ensure characters are machine-readable (with optical character recognition, or OCR). LM is currently replacing its electronic recordkeeping system and simultaneously modernizing its organizational approach to data management; it is replacing a traditional electronic records repository with a system that also manages records stored anywhere across the computer network. This new records management approach will require new thinking in how LM manages a dramatically increased volume of information across the network while not losing focus on its responsibility for long-term records preservation and access. (author)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Model reduction for hypersonic aerodynamics via conservative LSPG projection and hyper-reduction

High-speed aerospace engineering applications rely heavily on computational fluid dynamics (CFD) models for design and analysis due to the expense and difficulty of flight tests and experiments. This reliance on CFD models necessitates performing accurate and reliable uncertainty quantification (UQ) of the CFD models. However, it is very computationally expensive to run CFD for hypersonic flows due to the fine grid resolution required to capture the strong shocks and large gradients that are typically present. Furthermore, UQ approaches are “many-query” problems requiring many runs with a wide range of input parameters. One way to enable computationally expensive models to be used in such many-query problems is to employ projection-based reduced-order models (ROMs) in lieu of the (high-fidelity) full-order model. In particular, the least-squares Petrov–Galerkin (LSPG) ROM (equipped with hyper-reduction) has demonstrated the ability to significantly reduce simulation costs while retaining high levels of accuracy on a range of problems including subsonic CFD applications. This allows computationally inexpensive LSPG ROM simulations to replace the full-order model simulations in UQ studies, which makes this many-query task tractable, even for large-scale CFD models. This work presents the first application of LSPG to a hypersonic CFD application. In particular, we present results for LSPG ROMs of the HIFiRE-1 in a three-dimensional, turbulent Mach 7.1 flow, showcasing the ability of the ROM to significantly reduce computational costs while maintaining high levels of accuracy in computed quantities of interest.

Fluid Dynamics↗
NASA NTRS1986

A survey of the state of the art and focused research in range systems, task 2

Many communication, control, and information processing subsystems are modeled by linear systems incorporating tapped delay lines (TDL). Such optimized subsystems result in full precision multiplications in the TDL. In order to reduce complexity and cost in a microprocessor implementation, these multiplications can be replaced by single-shift instructions which are equivalent to powers of two multiplications. Since, in general, the obvious operation of rounding the infinite precision TDL coefficients to the nearest powers of two usually yield quite poor system performance, the optimum powers of two coefficient solution was considered. Detailed explanations on the use of branch-and-bound algorithms for finding the optimum powers of two solutions are given. Specific demonstration of this methodology to the design of a linear data equalizer and its implementation in assembly language on a 8080 microprocessor with a 12 bit A/D converter are reported. This simple microprocessor implementation with optimized TDL coefficients achieves a system performance comparable to the optimum linear equalization with full precision multiplications for an input data rate of 300 baud. The philosophy demonstrated in this implementation is dully applicable to many other microprocessor controlled information processing systems.

Yao, K.↗
NASA NTRS2010

Metabolic Costs and Biomechanics of Inclined Ambulation and Exploration Tasks in a Planetary Suit

Observations from Apollo lunar surface extravehicular activities (EVAs) and a few studies conducted in partial-gravity simulation environments have helped us understand suited human performance in reduced-gravity environments. The Constellation Program EVA Systems Project Office initiated a series of tests aimed at increasing our understanding of human performance and suit kinematics under various simulated lunar EVA conditions, including matched unsuited controls, to identify the specific metabolic costs and biomechanics of the prototype Mark III Advanced Spacesuit Technology Demonstrator. A primary goal of the series is to provide evidence-based recommendations for suit mass, center of gravity, pressure, and suit kinematic constraints that optimize human performance in partial-gravity environments. Results will be combined with studies in other lunar analogs to evaluate the effectiveness and limitations of these environments. As our understanding of suited human performance matures, different combinations of variables can be evaluated to determine whether significant interactions exist between parameters. This report provides an overview of key findings of Integrated Suit Test (IST)-2. As future tests are completed, focusing on other suit factors, analog environments, or different suits, study results will be combined and reevaluated. The series of tests comprising IST-2 was conducted from June 13, 2007 through October 24, 2007.

Aerospace environments↗
DOE OSTI2023

Rapid AI-based Dissection of Ashes using Raman and XRF Spectroscopy (RADAR-X)

Waste-to-energy (WTE) facilities incinerate ~35 million tons of municipal solid waste annually in the United States. The incineration process reduces the mass and the volume of the waste fraction by over 75 and 95%, respectively. The fraction left after incineration remains as ash residues and is referred to as WTE ash, compromising of bottom and fly ash. In the United States, ~10 million tons of WTE ashes are generated annually and predominantly landfilled because of the lack of secondary end-use pathways. This incurs a significant financial burden (landfilling costs) on U.S. WTE facilities and also results in the loss of materials to the landfill. The primary objective of this research is to understand better the elemental and mineralogical composition of WTE ashes from diverse origins and find composition dependent upcycling pathways for diverting these ashes from landfills. This primary objective was addressed through three research tasks –(Task I) An AI-led Multi-Modal Approach for Compositional Analysis, (Task II) Developing a Dissolution-Based Test for Real Time Analysis, and (Task III) Establishing composition-dependent end uses. The chemical composition of WTE ash is dependent on two factors, i.e., the input waste composition and the operational parameters of a WTE facility (combustion conditions). Amongst these two factors, the input waste composition will likely show spatial and temporal variation. As a result, the chemical composition of WTE ash will also fluctuate. To understand the spatial and temporal variation in WTE ash composition, in Task I, we collected 128 ash samples (62 bottom ash and 66 fly ash samples) from 11 WTE facilities located in 11 U.S. states and characterized them via X-ray Fluorescence, powder X-ray Diffraction, and Raman Spectroscopy. The findings from this extensive characterization work indicated that the key elements in WTE fly ashes are Ca, Cl (greater than 10 wt. %), Si, S, K, Zn ( between 1 and 10 wt. %), Mg, Al, P, Ti, Fe, Cu, Br, and Pb (between 0.1 and 1 wt. %). Similarly, the key elements in WTE bottom ash fraction finer than 45μm are Ca (greater than 10 wt. %), Mg, Al, Si, S, Cl, K, Ti, Fe, Zn (between 1 and 10 wt. %), P, V, Cr, Mn, Cu, Br, and Pb (between 0.1 and 1 wt. %). Here, we note that the dominant fraction of WTE bottom ash is the coarse fraction. The coarse WTE bottom ash fraction (rich in silicon) was not characterized in this study because of excessive grinding requirements and their unsuitability as a supplementary cementitious material due to their coarse nature. The elements in WTE bottom ashes are present as calcite, anhydrite, vaterite, hydroxyapatite, quartz, bassanite, gehlenite, akermanite, hydrocalumite, and portlandite. Similarly, the mineralogical species present in WTE fly ashes are calcium chloride hydroxide, halite, calcite, anhydrite, sylvite, hydrocalumite, vaterite, hannebachite, quartz, and bassanite. Temporal variation in ash composition may also result in significant fluctuations in chemical compositions. Therefore, a WTE facility may need to monitor the ash composition (elemental and mineralogical composition) in real time. In Task I, we evaluated the possibility of using a portable X-ray fluorescence (XRF) spectrometer to monitor the elemental composition in real-time. Specifically, we collected XRF data on identical specimens via a portable XRF spectrometer (low-end) and a lab-based benchtop XRF spectrometer (high-end). The collected data was used to train an A.I. algorithm (portable XRF data as an input and benchtop XRF data as an output) to predict accurate elemental composition using portable XRF data. Finally, we developed a 2-minute photobleaching protocol to monitor the mineralogical characteristics of WTE ashes via Raman spectroscopy. Overall, the activities in Task I improved our understanding of ash composition and developed techniques to monitor elemental and mineralogical composition in near real-time. Based on the findings of Task I, we find that WTE ashes exhibit wide variability in mineralogy. For ICP-based elemental analysis, all the mineralogical species in WTE ashes must be brought into solution. This is traditionally accomplished with acid digestion using a combination of multiple acids. However, acid digestion with multiple acids is time-consuming and often fails to ensure complete digestion of the ash matrix. To address this limitation, in Task II, we developed an alkali-fusion-based digestion protocol using a combination of lithium tetraborate, lithium metaborate, and their combinations as possible alkali fluxes for digesting WTE ashes entirely and rapidly. The validity of the developed method was evaluated on two standard ash specimens, i.e., SRM 1633c coal fly ash and BCR-176R incineration fly ash specimen. The findings suggest that the developed protocol can ensure complete digestion of elements such as Al, Ba, Ca, Cr, Cu, Mg, Mn, P, Sr, V, Zn, Be, K, and rare earth elements. The recent changes in the energy market towards renewables and increased metal recycling have resulted in reduced supplies of supplementary cementitious materials (coal fly ash and slag). Therefore, in Task III, we evaluated the possibility of employing WTE ashes as SCMs. As the chemical composition of WTE ashes varies temporally (on an hourly basis), there was also a need to develop tests that can evaluate the suitability of material to act as supplementary cementitious material rapidly, i.e., in a few minutes. Therefore, in Task II, we also developed a rapid test to assess the suitability of a material to act as an SCM in 5 minutes. This represents a significant advance over the state-of-the-art R 3 test, which takes ~144 hours. This test was initially validated on amorphous aluminosilicates, such as calcined clays, and could be extended to evaluate other industrial by-products, such as WTE ashes. In Task III, we evaluated the possibility of employing WTE ashes for two applications, i.e., as an SCM and a lime substitute for clay stabilization. The findings from Task I indicated that WTE ashes are enriched in chlorine and, therefore, cannot be used directly as an SCM due to corrosion-related risks and altered hydration kinetics. Accordingly, we developed an ash treatment protocol to reduce the solubility of chlorine-containing species in WTE ashes. The developed treatment protocol also immobilized lead in certain mineral forms. As a result of the treatment, WTE ashes can be used as SCMs without any corrosion or heavy metal leaching concerns. The second application examined in this study was clay stabilization. WTE ashes are calcium-rich and can be an adequate lime replacement for clay stabilization. Our findings reveal that the sum of the concentrations of Ca(OH) 2 and CaClOH controls the clay stabilization capability of WTE ashes. In summary, in this work, we evaluated the elemental and mineralogical characteristics of U.S. WTE ashes from diverse origins and developed tests to evaluate the chemical characteristics of these ashes in real time through a portable XRF and a benchtop Raman spectrometer. Based on the chemical characteristics of these ashes, we developed an ash treatment process to enable the use of WTE ashes as an SCM and also evaluated the possibility of employing these ashes for clay stabilization. Overall, the findings from this work enables the diversion of WTE ashes from landfills for multiple end-uses, i.e., as an SCM or a lime substitute for clay stabilization.

36 MATERIALS SCIENCE↗
NASA NTRS2017

Flight Deck Surface Trajectory-Based Operations (STBO): A Four-Dimensional Trajectory (4DT) Simulation

Within human factors there is burgeoning interest in the Human-Autonomy Teaming (HAT) concept as away to address the challenges of interacting with complex, increasingly autonomous systems. The HAT concept comes out of an aspiration to interact with increasingly autonomous automation as a team member, rather than simply use automation as a tool. The authors, and others, have proposed core tenets for HAT that include bi-directional communication, automation and system transparency, and advanced coordination between human and automated teammates via predefined, dynamic task sequences known as plays (Shively et al., 2017). It is believed that, with proper implementation, HAT should foster appropriate teamwork, thus increasing trust and reliance on the system, which in turn will reduce workload, increase situation awareness, and improve performance. To this end, HAT has been demonstrated and/or studied in multiple applications including search and rescue operations (Nourbakhsh et al., 2005), healthcare and medicine (Tsui Yanco, 2007), autonomous vehicles (Parasuraman, Barnes, Cosenzo, Mulgund, 2007), photography (Lachter, Brandt, Sadler, Shively, in press), and aviation (Shively et al., in press). The current paper presents one such effort to apply HAT. It details the design of a R-HAT Agent developed as part of a NASA Research Agreement awarded to Human-Autonomy Teaming Solutions Inc. (HATS Inc), and developed in collaboration with the Human-Autonomy Teaming Laboratory at NASA Ames Research Center. The role of this Agent is to mediate interaction between the automation and the human operator of an advanced ground dispatch station, with this mediation based upon previously mentioned core tenets for HAT and the many lessons learned from the HAT research literature. This dispatch station was developed to support a NASA project investigating a concept called Reduced Crew Operations (RCO; Lachter, Brandt, Battiste, Matessa, Johnson, in press). Part of the RCO concept involves a ground operator providing enhanced support to a large number of aircraft with a single pilot on the flight deck. When assisted by the Agent, operators can monitor and support or manage a large number of aircraft and use plays to respond in real-time to complicated, workload-intensive events (e.g., an airport closure). A play is a plan that encapsulates goals, tasks, and a task allocation strategy appropriate for a particular situation. In the current implementation, when a play is initiated by a user, the Agent determines what tasks need to be done and has the ability to autonomously execute them (e.g., determining diversion options and uplinking new routes to aircraft) when it is safe and appropriate. The R-HAT Agent has been designed to both support end users and research in RCO and HAT. Additionally, the Agent and its underlying architecture were developed with generalizability in mind as a modular piece of software applicable outside of RCO aviation in domains such as those mentioned above. This paper will also discuss future further development and testing of the R-HAT Agent.

Bakowski, Deborah L.↗
NASA NTRS2013

Mobile Thread Task Manager

The Mobile Thread Task Manager (MTTM) is being applied to parallelizing existing flight software to understand the benefits and to develop new techniques and architectural concepts for adapting software to multicore architectures. It allocates and load-balances tasks for a group of threads that migrate across processors to improve cache performance. In order to balance-load across threads, the MTTM augments a basic map-reduce strategy to draw jobs from a global queue. In a multicore processor, memory may be "homed" to the cache of a specific processor and must be accessed from that processor. The MTTB architecture wraps access to data with thread management to move threads to the home processor for that data so that the computation follows the data in an attempt to avoid L2 cache misses. Cache homing is also handled by a memory manager that translates identifiers to processor IDs where the data will be homed (according to rules defined by the user). The user can also specify the number of threads and processors separately, which is important for tuning performance for different patterns of computation and memory access. MTTM efficiently processes tasks in parallel on a multiprocessor computer. It also provides an interface to make it easier to adapt existing software to a multiprocessor environment.

Clement, Bradley J.↗
DOE OSTI2016

Well Integrity for Natural Gas Storage in Depleted Reservoirs and Aquifers

Introduction Motivation The 2015-2016 Aliso Canyon/Porter Ranch natural gas well blowout emitted approximately 100,000 tonnes of natural gas (mostly methane, CH 4 ) over four months. The blowout impacted thousands of nearby residents, who were displaced from their homes. The high visibility of the event has led to increased scrutiny of the safety of natural gas storage at the Aliso Canyon facility, as well as broader concern for natural gas storage integrity throughout the country. Federal Review of Well Integrity In April of 2016, the U.S. Department of Energy (DOE), in conjunction with the U.S. Department of Transportation (DOT) through the Pipeline and Hazardous Materials Safety Administration (PHMSA), announced the formation of a new Interagency Task Force on Natural Gas Storage Safety. The Task Force enlisted a group of scientists and engineers at the DOE National Laboratories to review the state of well integrity in natural gas storage in the U.S. The overarching objective of the review is to gather, analyze, catalogue, and disseminate information and findings that can lead to improved natural gas storage safety and security and thus reduce the risk of future events. The “Protecting our Infrastructure of Pipelines and Enhancing Safety Act of 2016’’ or the ‘‘PIPES Act of 2016,’’which was signed into law on June 22, 2016, created an Aliso Canyon Natural Gas Leak Task Force led by the Secretary of Energy and consisting of representatives from the DOT, Environmental Protection Agency (EPA), Department of Health and Human Services, Federal Energy Regulatory Commission (FERC), Department of Commerce and the Department of Interior. The Task Force was asked to perform an analysis of the Aliso Canyon event and make recommendations on preventing similar incidents in the future. The PIPES Act also required that DOT/PHMSA promulgate minimum safety standards for underground storage that would take effect within two years. Background on the DOE National Laboratories Well Integrity Work Group One of the primary areas that the Task Force is studying is integrity of natural gas wells at storage facilities. The DOE Office of Fossil Energy (FE) took the lead in this area and asked scientists and engineers from the National Energy Technology Laboratory (NETL), Lawrence Livermore National Laboratory (LLNL), Sandia National Laboratories (SNL), and Lawrence Berkeley National Laboratory (LBNL)) to form a Work Group to address this area. This Work Group is an expansion of the original “Lab Team” comprising scientists and engineers from SNL, LLNL, and LBNL which was formed to support the State of California’s response to the Aliso Canyon incident and operated under the Governor of California’s Aliso Canyon Emergency Order (1/6/2016). The Lab Team played a key role in advising the State of California’s Department of Conservation (DOC) in its oversight of SoCalGas during and after the incident.

03 NATURAL GAS↗
DOE OSTI2023

What’s the Difference? The Potential for Convolutional Neural Networks for Transient Detection without Template Subtraction

Abstract We present a study of the potential for convolutional neural networks (CNNs) to enable separation of astrophysical transients from image artifacts, a task known as “real–bogus” classification, without requiring a template-subtracted (or difference) image, which requires a computationally expensive process to generate, involving image matching on small spatial scales in large volumes of data. Using data from the Dark Energy Survey, we explore the use of CNNs to (1) automate the real–bogus classification and (2) reduce the computational costs of transient discovery. We compare the efficiency of two CNNs with similar architectures, one that uses “image triplets” (templates, search, and difference image) and one that takes as input the template and search only. We measure the decrease in efficiency associated with the loss of information in input, finding that the testing accuracy is reduced from ∼96% to ∼91.1%. We further investigate how the latter model learns the required information from the template and search by exploring the saliency maps. Our work (1) confirms that CNNs are excellent models for real–bogus classification that rely exclusively on the imaging data and require no feature engineering task and (2) demonstrates that high-accuracy (>90%) models can be built without the need to construct difference images, but some accuracy is lost. Because, once trained, neural networks can generate predictions at minimal computational costs, we argue that future implementations of this methodology could dramatically reduce the computational costs in the detection of transients in synoptic surveys like Rubin Observatory's Legacy Survey of Space and Time by bypassing the difference image analysis entirely.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2015

NASA's Functional Task Test: Providing Information for an Integrated Countermeasure System

Exposure to the microgravity conditions of spaceflight causes astronauts to experience alterations in multiple physiological systems. These physiological changes include sensorimotor disturbances, cardiovascular deconditioning, and loss of muscle mass and strength. Some or all of these changes might affect the ability of crewmembers to perform critical mission tasks immediately after landing on a planetary surface. The goals of the Functional Task Test (FTT) study were to determine the effects of spaceflight on functional tests that are representative of critical exploration mission tasks and to identify the key physiological factors that contribute to decrements in performance. The FTT was comprised of seven functional tests and a corresponding set of interdisciplinary physiological measures targeting the sensorimotor, cardiovascular and muscular changes associated with exposure to spaceflight. Both Shuttle and ISS crewmembers participated in this study. Additionally, we conducted a supporting study using the FTT protocol on subjects before and after 70 days of 6 head-down bed rest. The bed rest analog allowed us to investigate the impact of body unloading in isolation on both functional tasks and on the underlying physiological factors that lead to decrements in performance, and then to compare them with the results obtained in our spaceflight study. Spaceflight data were collected on three sessions before flight, on landing day (Shuttle only) and 1, 6 and 30 days after landing. Bed rest subjects were tested three times before bed rest and immediately after getting up from bed rest as well as 1, 6, and 12 days after reambulation. We have shown that for Shuttle, ISS and bed rest subjects, functional tasks requiring a greater demand for dynamic control of postural equilibrium (i.e. fall recovery, seat egress/obstacle avoidance during walking, object translation, jump down) showed the greatest decrement in performance. Functional tests with reduced requirements for postural stability (i.e. hatch opening, ladder climb, manual manipulation of objects and tool use) showed little reduction in performance. These changes in functional performance were paralleled by similar decrements in sensorimotor tests designed to specifically assess postural equilibrium and dynamic gait control. Bed rest subjects experienced similar deficits both in functional tests with balance challenges and in sensorimotor tests designed to evaluate postural and gait control as spaceflight subjects indicating that body support unloading experienced during spaceflight plays a central role in post-flight alteration of functional task performance. To determine how differences in body-support loading experienced during in-flight treadmill exercise affect postflight functional performance, the loading history for each subject during in-flight treadmill (T2) exercise was correlated with postflight measures of performance. ISS crewmembers who walked on the treadmill with higher pull-down loads had enhanced post-flight performance on tests requiring mobility. Taken together the spaceflight and bed rest data point to the importance of supplementing inflight exercise countermeasures with balance and sensorimotor adaptability training. These data also support the notion that inflight treadmill exercise performed with higher body loading provides sensorimotor benefits leading to improved performance on functional tasks that require dynamic postural stability and mobility.

Bloomberg, J. J.↗
NASA NTRS1979

Design, processing and testing of LSI arrays: Hybrid microelectronics task

Mathematical cost factors were generated for both hybrid microcircuit and printed wiring board packaging methods. A mathematical cost model was created for analysis of microcircuit fabrication costs. The costing factors were refined and reduced to formulae for computerization. Efficient methods were investigated for low cost packaging of LSI devices as a function of density and reliability. Technical problem areas such as wafer bumping, inner/outer leading bonding, testing on tape, and tape processing, were investigated.

Himmel, R. P.↗
DOE OSTI2018

A Scalable HPC Insider Threat Monitoring System

Cyber Equations, Inc. is reporting on the results of its DOE SBIR Phase I project for the development of a Scalable HPC Insider Threat Monitoring System. This final report to the Department of Energy for Task DE-FOA-0001618 covers the period from 02/21/2017 to 02/20/2018 and summarizes the larger research accomplishments, which can be divided in theoretical and laboratory experiments. One of the many challenges for the U.S. Department of Energy (DOE) is the support of the high-performance computing (HPC) centers while providing quality information services, strategic vision, leadership, technical expertise, and capabilities necessary to enable the DOE to deliver effective, efficient, economical, and secure HPC services. In order to realize a secure DOE laboratory enterprise, DOE facilities operations must counter a wide range of cyber insider threats, from unsophisticated adversaries up to advanced, nation state sponsored actors. The DOE laboratories also presents an enormous insider attack surface of an ever-growing number of computers, networks, and devices all running a myriad of software. In addition, the DOE laboratories are connected to a variety of external organizations which multiplies the possibility of insider threat. During this SBIR project Cyber Equations developed a strategic combination of supervised and unsupervised machine learning techniques to control scale and classify whether entities, such as hosts, actors, or documents, are showing suspicious insider behavior. We conducted experiments using real cyber data to show that changes in observable behavior (e.g., changes in outbound traffic patterns) are indicative of attacks executing (e.g., insiders exfiltrating data, bots calling home, or an attack spreading). The features and methods we use, have been used in the anomaly detection research and development community for a significant amount of time and robust implementations are openly available. K-Means clustering, Decision Trees, and Support Vector Machine based classifiers are readily available through the R language and open source H20 machine learning framework. The Cyber Equations approach is novel in its use of these classifiers combined with Hadoop based parallel processing technology. The five stages of processing used by CyberInsider improve scalability and reduce the high number of false positives normally associated with network anomaly detection. In summary, the Cyber Equations has successfully accomplished all of its Phase I tasks and demonstrated the feasibility of the Insider Threat Monitoring System.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Recurrent neural network-based multiaxial plasticity model with regularization for physics-informed constraints

We report a recurrent neural network (RNN) based model is developed as a surrogate to predict nonlinear plastic response under multiaxial loading. The RNN-based model is trained and tested on stress versus strain curves generated using a numerical solution based on the classical radial return method. Besides simply learning the basic constitutive relationship, a novel approach is taken to enforce certain physical conditions. Specifically, regularization is employed to maintain non-negative plastic power density throughout the loading history thereby ensuring monotonically increasing plastic work and thermodynamic consistency. Enforcing physics in this manner permits coupling of the data-driven RNN approach with physics-based knowledge and laws. This has the effect of reducing the necessary amount of data and ensuring known physical laws are not violated. Since, once trained, the model need not perform the expensive task of solving nonlinear equations, its efficiency is orders of magnitude greater than its numerical counterpart. The RNN-based model has been trained on varied sets of data and the accuracy on test datasets validated. The developed model is general and robust and has widespread application such as in the simulation of metal forming, large scale plasticity, and part life prediction.

42 ENGINEERING↗
DOE OSTI2019

Distributed Wireless Antenna Sensors for Boiler Condition Monitoring

Monitoring the operational conditions of coal-fired boilers is an important task that could bring tremendous benefits, including in-situ process control, real-time health assessment of structural components, improved heat transfer efficiency, reduced downtime, etc. Moreover, in-situ distributed sensing of the boiler conditions would provide large scale in-situ measurement data that will help us gain fundamental understandings of the combustion and heat transfer processes as well as enable the developments of new simulation tools, which could eventually lead to better design and more efficient operation of the boilers. The objectives of this research were to (a) develop wireless passive antenna sensors without electronics; (b) demonstrate multi-modality sensing using a signal antenna sensor; and (c) fabricate the antenna sensor from high-temperature materials. In this project, we have demonstrated that an antenna sensor or sensor array without any electronics can be wirelessly interrogated from a distance. In addition, a low-cost compact wireless sensor interrogator was developed for dynamic interrogation of the passive antenna sensor. We validated that a dual-frequency antenna sensor is capable of simultaneous strain and temperature measurements or temperature and ash accumulation measurements; all parameters are relevant to boiler condition monitoring. By measuring the temperature and ash accumulation height simultaneously, the dielectric constant of the ash as well as its temperature dependency can also be characterized. This capability could lead to potential applications of the antenna sensor for combustion process monitoring based on the ash composition. We also investigated different techniques of fabricating the antenna sensor using high-temperature materials such as alumina substrate and platinum paste and characterized the thermal response of the antenna sensor. A linear relationship between the antenna resonant frequency and the temperature change was validated.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Purification and Concentration of 99 Mo from a UREX raffinate

The medical isotope 99m Tc ( t ½ = 6.0 h) accounts for over 80% of isotopes used in diagnostic nuclear medicine today and is normally derived from its transient equilibrium parent 99 Mo ( t ½ = 66 h). To reduce U.S. dependence on 99 Mo derived from HEU by foreign suppliers, the NNSA/M3 program—under the American Medical Isotope Production Act—has been tasked with facilitating the work of domestic 99 Mo suppliers that do not utilize HEU. Superconducting electron linear accelerators with high-Z converter targets can generate bremsstrahlung photons and neutron fluxes that can induce photonuclear reactions and LEU fission. After sufficient production intervals, targets can be rotated out and processed while another batch is irradiated. The process flow chemistry is shown in Figure 1. The irradiated U 3 O 8 targets are retrieved and dissolved in HNO 3 ; the volatile fission products are expelled and captured during this step. The HNO 3 liquor bearing the uranyl, fission and activation products is injected into the UREX suite of liquid-liquid extraction banks. The uranyl is partitioned in typical fashion using tri-$\textit{n}$-butyl phosphate (TBP) in a hydrocarbon diluent. The raffinate—comprising mainly 99 Mo and fission products—is then injected into the MoLLE (Molybdenum Liquid-Liquid Extraction) flowsheet, where the Mo is selectively extracted by an organophosphorous acid extractant such as di-(2-ethylhexyl phosphoric acid) (HDEHP). Trace amounts of Nb, Zr, Np, I, and Te are co-extracted. The Mo is stripped using acetohydroxamic acid (AHA) and fed onto an anion exchange column. Following a series of hydroxide, HCl, and oxalic acid wash steps, the Mo can be recovered in NaOH/NaCl. A manuscript describing this process chemistry in more detail was recently published.

07 ISOTOPE AND RADIATION SOURCES↗
NASA NTRS1977

Recent developments in photovoltaic energy by ERDA/NASA-LeRC

Application development activities were designed to stimulate the market for photovoltaics so that as costs are reduced there will be an increasing market demand to encourage the expansion of industrial solar array production capacity. Supporting these application development activities are tasks concerned with: (1) establishing standards and methodology for terrestrial solar cell calibration; (2) conducting standard and diagnostic measurements on solar cells and modules; and (3) conducting real time and accelerated testing of solar cell modules and materials of construction under outdoor sunlight conditions.

Deyo, J. N.↗
NASA NTRS1982

Multi-100 kW: Planar low cost solar array development

The development of a 100 kW planar low cost solar array is presented. Tasks are defined, objectives are stated, and test results are given. A study of alternate contact configuration concluded that gridded back contact cells sharply reduced solar absorptance, that copper contacts will require a developmental program before interface can be achieved, and that gridded back contact cells using Ti-Pd-Ag as the contact materials appear to be the most cost-effective design.

Source record↗