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VERA 3.6 Release

CASL has developed a formalized process to release the Virtual Environment for Reactor Applications (VERA) to non-CASL users through the Radiation Shielding Information Computational Center (RSICC). This milestone represents a major release of VERA with updates that significantly reduce computational resources required and introduce new capabilities related to fuel performance integration. This release will also be used by CASL Test Stands and training activities. VERA 3.6 represents an incremental release, with improvements to core component capabilities, significant performance improvements, and updated documentation. This release followed a significantly revised release process, with formal documentation, testing, readiness reviews, and release authorization. The major tasks that were completed as part of this milestone were: 1) Revision of the VERA RSICC Release Process and Procedures; 2) Identification of the VERA release components; 3) Creation of a Release Candidate; 4) Independent evaluation of the Release Candidate by the Advanced Modeling Applications (AMA) Focus Area; 5) A Release Candidate Readiness Review; 6) Development and execution of a System Test Plan; 7) Updates of manuals and other required documentation; 8) Export Control reviews; 9) A Release Readiness Review; and 10) Delivery of the release package to RSICC. Synopses of the work done to complete each of these major tasks are summarized in Section 2 below. Supporting details are provided in the PHI Kanban ticket #4424 Support VERA 3.6 Release Activities and its child tickets.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A bootstrapping approach to social media quantification

Abstract This work considers the use of classifiers in a downstream aggregation task estimating class proportions, such as estimating the percentage of reviews for a movie with positive sentiment. We derive the bias and variance of the class proportion estimator when taking classification error into account to determine how to best trade off different error types when tuning a classifier for these tasks. Additionally, we propose a method for constructing confidence intervals that correctly adjusts for classification error when estimating these statistics. We conduct experiments on four document classification tasks comparing our methods to prior approaches across classifier thresholds, sample sizes, and label distributions. Prior approaches have focused on providing the most accurate point estimate while this work focuses on the creation of correct confidence intervals that appropriately account for classifier error. Compared to the prior approaches, our methods provide lower error and more accurate confidence intervals.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Hypercube matrix computation task

A major objective of the Hypercube Matrix Computation effort at the Jet Propulsion Laboratory (JPL) is to investigate the applicability of a parallel computing architecture to the solution of large-scale electromagnetic scattering problems. Three scattering analysis codes are being implemented and assessed on a JPL/California Institute of Technology (Caltech) Mark 3 Hypercube. The codes, which utilize different underlying algorithms, give a means of evaluating the general applicability of this parallel architecture. The three analysis codes being implemented are a frequency domain method of moments code, a time domain finite difference code, and a frequency domain finite elements code. These analysis capabilities are being integrated into an electromagnetics interactive analysis workstation which can serve as a design tool for the construction of antennas and other radiating or scattering structures. The first two years of work on the Hypercube Matrix Computation effort is summarized. It includes both new developments and results as well as work previously reported in the Hypercube Matrix Computation Task: Final Report for 1986 to 1987 (JPL Publication 87-18).

Calalo, Ruel H.↗

Localized Fault Recovery for Nested Fork-Join Programs

Nested fork-join programs scheduled using work stealing can automatically balance load and adapt to changes in the execution environment. In this paper, we design an approach to efficiently recover from faults encountered by these programs. Specifically, we focus on localized recovery of the task space in the presence of fail-stop failures. We present an approach to efficiently track, under work stealing, the relationships between the work executed by various threads. This information is used to identify and schedule the tasks to be re-executed without interfering with normal task execution. The algorithm precisely computes the work lost, incurs minimal re-execution overhead, and can recover from an arbitrary number of failures. Experimental evaluation demonstrates low overheads in the absence of failures, recovery overheads on the same order as the lost work, and much lower recovery costs than alternative strategies.

Kestor, Gokcen↗

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↗

Monitoring Human Performance on Future Deep Space Missions Abstract

NASA and the commercial spacecraft community are working diligently to put the first woman on the moon in the 2024 timeframe. At the same time, NASA researchers are thinking about how to solve the even larger challenges that future deep space missions will bring. Space travel itself is difficult, but astronauts on deep space missions will face obstacles and unknowns never before experienced. In addition to the altered gravity and hostile/closed environment of a spacecraft, deep space crews will face increased radiation, isolation, and distance from Earth. During Extravehicular Activity (EVA, or “spacewalk”) operations, crew will experience increased physical and cognitive workload due to extended types, frequencies and durations of tasks performed on exploration missions in partial gravity environments. All of these stressors will impact crew physical and mental health and performance in difficult-to-anticipate ways. Crew autonomy may be one of the biggest challenges faced. Communication delays and blackouts will occur, and in those situations, the crew may not have access to the Mission Control Center (MCC). They may be forced to be solely dependent on each other and the available information onboard to stay alive, healthy, and achieve the mission. The only conceivable way to meet the challenges of Earth independence is to enable the crew to monitor their own health and performance -- preferably unobtrusively as they perform their duties. Technologies and techniques must be developed to aid the crew in these assessments. A deep space mission is expected to have relatively short periods of high cognitive demand, stress, and fatigue, alongside potentially long periods of cognitive underload during the transit, where boredom, loneliness, and depression can set in. Both ends of this spectrum are dangerous. Crew must be made aware when their task performance drops significantly, when their cognitive workload is too high, when they have lost situation awareness, or when they are too stressed or too fatigued to perform well. They must be able to identify these risks, and then mitigate them with countermeasures available onboard. A number of self-monitoring technologies are presently being explored by NASA to advance crew state determination capabilities. These range from real-time, physiological workload and situation awareness assessments, to crew health measurements determining physical and mental fitness for duty, to task performance metrics such as suit resource expenditures. For EVA tasks during surface exploration missions, biomedical information such as metabolic rate may be provided to crewmembers for situational awareness related to task performance efficiency. In addition, translation distances, hydration, nutrition, inspired CO2 exposure and other consumables usage rates may be useful input metrics for modeling individualized performance during tasks to inform crew or provide estimates of work efficiency. Oculomotor metrics such as gaze dwell time, pupilometry, and eye tracking collected in advanced helmet mounted displays could potentially be used to characterize crew situation awareness. This paper highlights some of these projects, and provides broader discussion about the need for advanced monitoring and smart technologies, as NASA takes the leap into the next generation of space exploration.

Kritina Holden↗

IEA Wind Task 49: Reference Site Conditions for Floating Wind Arrays

The commercial-scale deployment of floating offshore wind (FOW) projects is expected to take place in a diverse range of sites that may differ significantly from existing fixed-bottom projects. FOW farms are particularly sensitive to the water depth and the meteorological and oceanographic (metocean) and geotechnical conditions at the project site due to the wave-induced system motions and loads as well as the anchoring system constraints imposed by the seafloor conditions. Uncertainty around the site conditions will permeate through all aspects of project design, leading to suboptimal and overly conservative designs, increased costs, and adversely affected performance. As FOW expands into a global industry, metocean and geotechnical conditions will increasingly vary for projects located in different geographic regions or in far-from-shore, deep-water sites. This study represents the outputs of work package 1 of International Energy Agency Wind Task 49, which focuses on the integrated design of floating wind arrays. The primary goal of this study is to establish the type of parameters and constraints required to characterize FOW array reference sites; provide a realistic and publicly available set of reference site conditions to the FOW community as a baseline set of data for individual research projects; identify and categorize any critical gaps in the existing data or methodologies required to define reference site characteristics; and inform and support the design of reference FOW arrays. A building block concept was developed for synthesizing reference sites for the design of FOW arrays. The building blocks include three classes of site conditions focusing on the techno-economic design of FOW projects: metocean conditions, seabed conditions, and coastal infrastructure. All reference site data produced and collected in this study are publicly available.

17 WIND ENERGY↗

Nitric-glycolic flowsheet evaluation with the slurry-fed melt rate furnace

The Savannah River National Laboratory (SRNL) was tasked to support validation of the Defense Waste Processing Facility (DWPF) melter offgas flammability model for the nitric-glycolic (NG) flowsheet. The work supports Deliverable 4 of the DWPF & Saltstone Facility Engineering Technical Task Request (TTR)1 and is supplemental to the Cold Cap Evaluation Furnace (CEF) testing conducted in 2014.2 The Slurry-fed Melt Rate Furnace (SMRF) was selected for the supplemental testing as it requires significantly less resources than the CEF and could provide a tool for more rapid analysis of melter feeds in the future. The SMRF platform has been used previously to evaluate melt rate behavior of DWPF glasses, but was modified to accommodate analysis of the offgas stream. Additionally, the Melt Rate Furnace (MRF) and Quartz Melt Rate Furnace (QMRF) were utilized for evaluations. MRF data was used exclusively for melt behavior observations and REDuction/OXidation (REDOX) prediction comparisons and will be briefly discussed in conjunction with its support of the SMRF testing. The QMRF was operated similarly to the SMRF for the same TTR task, but will be discussed in a separate future report. The overall objectives of the SMRF testing were to; 1) Evaluate the efficacy of the SMRF as a platform for steady state melter testing with continuous feeding and offgas analysis; and 2) Generate supplemental melter offgas flammability data to support the melter offgas flammability modelling effort for DWPF implementation of the NG flowsheet.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Advanced Signal Processing Methods Applied to Digital Mammography

The work reported here is on the extension of the earlier proposal of the same title, August 1994-June 1996. The report for that work is also being submitted. The work reported there forms the foundation for this work from January 1997 to September 1997. After the earlier work was completed there were a few items that needed to be completed prior to submission of a new and more comprehensive proposal for further research. Those tasks have been completed and two new proposals have been submitted, one to NASA, and one to Health & Human Services WS). The main purpose of this extension was to refine some of the techniques that lead to automatic large scale evaluation of full mammograms. Progress on each of the proposed tasks follows. Task 1: A multiresolution segmentation of background from breast has been developed and tested. The method is based on the different noise characteristics of the two different fields. The breast field has more power in the lower octaves and the off-breast field behaves similar to a wideband process, where more power is in the high frequency octaves. After the two fields are separated by lowpass filtering, a region labeling routine is used to find the largest contiguous region, the breast. Task 2: A wavelet expansion that can decompose the image without zero padding has been developed. The method preserves all properties of the power-of-two wavelet transform and does not add appreciably to computation time or storage. This work is essential for analysis of the full mammogram, as opposed to selecting sections from the full mammogram. Task 3: A clustering method has been developed based on a simple counting mechanism. No ROC analysis has been performed (and was not proposed), so we cannot finally evaluate this work without further support. Task 4: Further testing of the filter reveals that different wavelet bases do yield slightly different qualitative results. We cannot provide quantitative conclusions about this for all possible bases without further support. Task 5: Better modeling does indeed make an improvement in the detection output. After the proposal ended, we came up with some new theoretical explanations that helps in understanding when the D4 filter should be better. This work is currently in the review process. Task 6: N/A. This no longer applies in view of Tasks 4-5. Task 7: Comprehensive plans for further work have been completed. These plans are the subject of two proposals, one to NASA and one to HHS. These proposals represent plans for a complete evaluation of the methods for identifying normal mammograms, augmented with significant further theoretical work.

Stauduhar, Richard P.↗

Supplier's Status for Critical Solid Propellants, Explosive, and Pyrotechnic Ingredients

In the early 1970's a program was initiated at the Naval Surface Warfare Center/Indian Head Division (NSWC/IHDIV) to address the well-known problems associated with availability and suppliers of critical ingredients. These critical ingredients are necessary for preparation of solid propellants and explosives manufactured by the Navy. The objective of the program was to identify primary and secondary (or back-up) vendor information for these critical ingredients, and to develop suitable alternative materials if an ingredient is unavailable. In 1992 NSWC/IHDIV funded Chemical Propulsion Information Agency (CPIA) under a Technical Area Task (TAT) to expedite the task of creating a database listing critical ingredients used to manufacture Navy propellant and explosives based on known formulation quantities. Under this task CPIA provided employees that were 100 percent dedicated to the task of obtaining critical ingredient suppliers information, selecting the software and designing the interface between the computer program and the database users. TAT objectives included creating the Explosive Ingredients Source Database (EISD) for Propellant, Explosive and Pyrotechnic (PEP) critical elements. The goal was to create a readily accessible database, to provide users a quick-view summary of critical ingredient supplier's information and create a centralized archive that CPIA would update and distribute. EISD funding ended in 1996. At that time, the database entries included 53 formulations and 108 critical used to manufacture Navy propellant and explosives. CPIA turned the database tasking back over to NSWC/IHDIV to maintain and distribute at their discretion. Due to significant interest in propellant/explosives critical ingredients suppliers' status, the Propellant Development and Characterization Subcommittee (PDCS) approached the JANNAF Executive committee (EC) for authorization to continue the critical ingredient database work. In 1999, JANNAF EC approved the PDCS panel task. This paper is designed to emphasize the necessity of maintaining a JANNAF community supported database, which monitors PEP critical ingredient suppliers' status. The final product of this task is a user friendly, searchable database that provides a quick-view summary of critical ingredient supplier's information. This database must be designed to serve the needs of JANNAF and the propellant and energetic commercial manufacturing community as well. This paper provides a summary of the type of information to archive each critical ingredient.

Sims, B. L.↗

Resilient Operation of Networked Community Microgrids with High Solar Penetration

This project, funded by the US Department of Energy’s Solar Energy Technologies Office (SETO), focused on the operation of microgrids as a coordinated network. The primary objective, which was successfully achieved, was to develop both control strategies and hardware solutions to support the resilient and efficient operation of networked microgrids with high solar penetration. The work was structured around the following four main tasks: • Development of distributed and scalable optimization algorithms for AC-coupled networked microgrids. • Design and implementation of a novel DC interconnection hardware to enable precise power exchange between microgrids. • Laboratory operational validation of the developed technologies using 480 V testbeds and commercially available hardware. • Field operational validation of the complete solution in Adjuntas, Puerto Rico, interconnecting two kW-scale, split-phase microgrids of Casa Pueblo’s microgrids. This project addressed multiple technical challenges across the domains of optimization, control, hardware interconnection, and protection. One of its key contributions was delivering tangible, real-world solutions for networking microgrids. In contrast to purely theoretical or simulation-based work, this project included full-scale hardware operational validation both in the lab and in the field. The work conducted as part of this project—in collaboration with the University of Puerto Rico; the University of Tennessee, Knoxville; the University of Central Florida; and Casa Pueblo—has advanced the state of the art in networked microgrids. Key contributions include the development of distributed control strategies, practical solutions for real-world implementation challenges, and the introduction of a novel DC interlink approach for microgrid interconnection. The project featured both laboratory and field validation using commercial off-the-shelf components. The field deployment successfully validated that a group of microgrids can operate in a coordinated manner, enabling precise power flow between systems and mutual support during extreme events. This project resulted in 15 journal publications and 15 conference papers; 5 graduate students and 15 undergraduate students were supported. The codes of distributed optimization and forecasting were made open-source through OSTI.gov for distributed optimization and forecasting. All the publications are available in the ORNL-hosted project landing page. The DC interlink with state-of-charge balancing control was operationally validated in Adjuntas by interconnecting two real-world, 240 V split-phase microgrids. To the best knowledge of the team, this represents the first operational validation of AC microgrids interconnected via DC-interlinks. As a culmination of this project, a follow-on grant was awarded to support the technology transfer of the distributed optimization framework to a commercial microgrid controller, Stellar Edge, developed by the California-based company New Sun Road.

14 SOLAR ENERGY↗

Exploring Cognitive States: Methods for Detecting Physiological Temporal Fingerprints

Cognitive state detection and its relationship to observable physiologically telemetry has been utilized for many human-machine and human-cybernetic applications. This paper aims at understanding and addressing if there are unique psychophysiological patterns over time, a ”physiological temporal fingerprint”, that is associated with specific cognitive states. This preliminary work involves commercial airline pilots completing experimental benchmark task inductions of three cognitive states: 1) Channelized Attention (CA); 2) High Workload (HW); and 3) Low Workload (LW). We approach this objective by modeling these "fingerprints" through the use of Hidden Markov Models and Entropy analysis to evaluate if the transitions over time are complex or rhythmic/predictable by nature. Our results indicate that cognitive states do have unique complexity of physiological sequences that are statistically different from other cognitive states. More specifically, CA has a significantly higher temporal psychophysiological complexity than HW and LW in EEG and ECG telemetry signals. With regards to respiration telemetry, CA has a lower temporal psychophysiological complexity than HW and LW. Through our preliminary work, addressing this unique underpinning can inform whether these underlying dynamics can be utilized to understand how humans transition between cognitive states and for improved detection of cognitive states.

Napoli, Nicholas J.↗

Offshore Code Comparison Collaboration, Continuation: Phase II Results of a Floating Semisubmersible Wind System: Preprint

Offshore wind turbines are designed and analyzed using comprehensive simulation tools that account for the coupled dynamics of the wind inflow, aerodynamics, elasticity, and controls of the turbine, along with the incident waves, sea current, hydrodynamics, and foundation dynamics of the support structure. The Offshore Code Comparison Collaboration (OC3), which operated under the International Energy Agency (IEA) Wind Task 23, was established to verify the accuracy of these simulation tools [1]. This work was then extended under the Offshore Code Comparison Collaboration, Continuation (OC4) project under IEA Wind Task 30 [2]. Both of these projects sought to verify the accuracy of offshore wind turbine dynamics simulation tools (or codes) through code-to-code comparison of simulated responses of various offshore structures. This paper describes the latest findings from Phase II of the OC4 project, which involved the analysis of a 5-MW turbine supported by a floating semisubmersible. Twenty-two different organizations from 11 different countries submitted results using 24 different simulation tools. The variety of organizations contributing to the project brought together expertise from both the offshore structure and wind energy communities. Twenty-one different load cases were examined, encompassing varying levels of model complexity and a variety of metocean conditions. Differences in the results demonstrate the importance and accuracy of the various modeling approaches used. Significant findings include the importance of mooring dynamics to the mooring loads, the role nonlinear hydrodynamic terms play in calculating drift forces for the platform motions, and the difference between global (at the platform level) and local (at the member level) modeling of viscous drag. The results from this project will help guide development and improvement efforts for these tools to ensure that they are providing the accurate information needed to support the design and analysis needs of the offshore wind community.

17 WIND ENERGY↗

Case-Based Capture and Reuse of Aerospace Design Rationale

The goal of this project is to apply artificial intelligence techniques to facilitate capture and reuse of aerospace design rationale. The project applies case-based reasoning (CBR) and concept mapping (CMAP) tools to the task of capturing, organizing, and interactively accessing experiences or "cases" encapsulating the methods and rationale underlying expert aerospace design. As stipulated in the award, Indiana University and Ames personnel are collaborating on performance of research and determining the direction of research, to assure that the project focuses on high-value tasks. In the first five months of the project, we have made two visits to Ames Research Center to consult with our NASA collaborators, to learn about the advanced aerospace design tools being developed there, and to identify specific needs for intelligent design support. These meetings identified a number of task areas for applying CBR and concept mapping technology. We jointly selected a first task area to focus on: Acquiring the convergence criteria that experts use to guide the selection of useful data from a set of numerical simulations of high-lift systems. During the first funding period, we developed two software systems. First, we have adapted a CBR system developed at Indiana University into a prototype case-based reasoning shell to capture and retrieve information about design experiences, with the sample task of capturing and reusing experts' intuitive criteria for determining convergence (work conducted at Indiana University). Second, we have also adapted and refined existing concept mapping tools that will be used to clarify and capture the rationale underlying those experiences, to facilitate understanding of the expert's reasoning and guide future reuse of captured information (work conducted at the University of West Florida). The tools we have developed are designed to be the basis for a general framework for facilitating tasks within systems developed by the Advanced Design Technologies Testbed (ADTT) project at ARC. The tenets of our framework are (1) that the systems developed should leverage a designer's knowledge, rather than attempting to replace it; (2) that learning and user feedback must play a central role, so that the system can adapt to how it is used, and (3) that the learning and feedback processes must be as natural and as unobtrusive as possible. In the second funding period we will extend our current work, applying the tools to capturing higher-level design rationale.

Leake, David B.↗

Operational Lessons Learned from NASA Analog Missions

National Aeronautics and Space Administration s (NASA) efforts in human space flight are currently focused on the Space Shuttle and International Space Station (ISS) programs, with efforts beginning on the future exploration opportunities. Both the Space Shuttle and ISS programs are important to the development of a capability for human exploration beyond Low Earth Orbit (LEO). The ISS provides extensive research capabilities to determine how the human body reacts to long duration stays in space. Also, the ISS and Shuttle can serve as a limited testbed for equipment or entire systems that may be used on missions to the Moon, Mars, or to a near-Earth asteroid. It has been nearly 35 years since the Apollo astronauts visited the Moon. Future space explorers will have to re-learn how to work and live on planetary surfaces, and how to do that for extended periods of time. Exploration crews will perform a wide assortment of scientific tasks, including material sampling and emplacement of automated instruments. Surface mission operations include the activities of the crew living and working, mission support from the Earth, and the operation of robotic and other remotely commanded equipment on the surface and in planetary orbit. Other surface activities will include the following: exploring areas surrounding a habitat; using rovers to collect rock and soil samples; setting up experiments on the surface to monitor the radiation environment and any seismic or thermal activity; and conducting scientific analyses and experiments inside a habitat laboratory. Of course, the astronauts will also have to spend some of their surface time "doing chores" and maintaining their habitat and other systems. In preparation for future planetary exploration, NASA must design the answers to many operational questions. What will the astronauts do on the surface? How will they accomplish this? What tools will they require for their tasks? How will robots and astronauts work together? What vehicle and system capabilities are required to support the activities? How will the crew and the Earth-based mission control team interact? During the initial phases of manned planetary exploration, one challenge in particular is virtually the same as during the Apollo program: How can scientific return be maximized during a relatively short surface mission? Today, NASA is investigating solutions to these challenges by conducting analog missions. These Earth-based missions possess characteristics that are analogous to missions on the Moon or Mars. These missions are excellent for testing operational concepts, and the design, configuration, and functionality of spacesuits, robots, rovers, and habitats. Analog mission crews test specific techniques and procedures for surface field geology, biological sample collection, and planetary protection. The process of actually working an analog mission reveals a myriad of small details, which either contribute to or impede efficient operations, many of which would never have been thought about otherwise. It also helps to define the suite of tools, containers, and other small equipment that surface explorers will use. This paper focuses on how analog missions have addressed selected operational considerations for future planetary missions.

Arnold, Larissa S.↗

Model-based Hierarchical Reinforcement Learning for Improved Physical Security Design: A Prototype

Prior work in FY24 developed an adversarial AI agent aid in path analysis of physical protection systems. This agent, trained using a model-based reinforcement learning algorithm, was able to successfully learn the most vulnerable path in facilities. It was able to extend the current state of practice for physical protection design by exhibiting dynamic behavior based on current environmental conditions. Whereas PathTrace largely performs a static, graph-based analysis, the AI agent was able to make decisions based on relative position in the facility, current conditions (was the adversarial agnet discovered?), and proximity to secondary targets. The agent demonstrated some novel capabilities, but had limitations that need to be resolved before it can be used for production purposes. For example, the adversarial agent generalizes poorly and takes a relatively long time to train. Nonetheless, there is still considerable promise for developing the adversarial agent further in order to explore even richer, more dynamic behaviors (e.g., adversary motivations, environmental debris, and more). This work considers a complementary idea; development of a planning agent. The planning agent is envisioned as an auto-complete-like tool that can help accelerate security system design by human experts. The agent would respect existing barriers and sensors placed by a human expert while offering cost-effective suggestions (i.e., implicitly balancing effectiveness with cost) to improve the design. The goal is for this agent to be part of an expert’s toolbox, not to totally upend the current state-of-practice, or to displace human experts. The ultimate goal would be concurrent training of both the adversarial and planning agent together, to learn entirely through self-play. This would represent an entirely new way of performing system deign. We selected a hierarchical, model-based reinforcement learning algorithm to serve as the planning agent. This is an extension of concepts used in the prior FY24 adversarial agent work. There, we had a single agent acting an environment. Here, we have two different sub-agents (policies), working together, to form a complete agent. There is a manager policy, which can select abstract goals on slower time scales, and a worker, which performs primitive actions to reach goals selected by the manager. It is worth noting that this class of algorithm is challenging to work with. From our understanding, our work is one of the first successful uses of model-based reinforcement learning (MBRL) in nuclear energy1 , and likely the first hierarchical model-based reinforcement learning application in nuclear energy. Further, this work is one of the first known attempts to apply AI to perform a design tasks in nuclear energy. Consequently, there were significant implementation challenges and the bulk of the work was focused on successful implementation and algorithm design. The results presented here are very low technology readiness level as a consequence of the lack of related literature, but still represent a significant step forward in the pursuit of applied AI for design.

42 ENGINEERING↗

Acceleration Studies

Work to support the NASA MSFC Acceleration Characterization and Analysis Project (ACAP) was performed. Four tasks (analysis development, analysis research, analysis documentation, and acceleration analysis) were addressed by parallel projects. Work concentrated on preparation for and implementation of near real-time SAMS data analysis during the USMP-1 mission. User support documents and case specific software documentation and tutorials were developed. Information and results were presented to microgravity users. ACAP computer facilities need to be fully implemented and networked, data resources must be cataloged and accessible, future microgravity missions must be coordinated, and continued Orbiter characterization is necessary.

Rogers, Melissa J. B.↗

Measurement of Temporal Awareness in Air Traffic Control

Temporal awareness, or level 3 situation awareness, is critical to successful control of air traffic, yet the construct remains ill-defined and difficult to measure. This research sought evidence for air traffic controllers awareness of temporal characteristics of their tasks in data from a high-fidelity system evaluation simulation. Five teams of controllers worked on four scenarios with different traffic load. Several temporal parameters were defined for each task controllers performed during a simulation run and their actions on the tasks were timed relative to them. Controllers showed a strong tendency to prioritize tasks according to a first come, first served principle. This trend persisted as task load increased. Also evident was awareness of the urgency of tasks, as tasks with impending closing of a window of opportunity were performed before tasks that had longer time available before closing of the window.

Rantanen, E.M.↗