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NASA NTRS2015

NASA Ames Sustainability Initiatives: Aeronautics, Space Exploration, and Sustainable Futures

In support of the mission-specific challenges of aeronautics and space exploration, NASA Ames produces a wealth of research and technology advancements with significant relevance to larger issues of planetary sustainability. NASA research on NexGen airspace solutions and its development of autonomous and intelligent technologies will revolutionize both the nation's air transporation systems and have applicability to the low altitude flight economy and to both air and ground transporation, more generally. NASA's understanding of the Earth as a complex of integrated systems contributes to humanity's perception of the sustainability of our home planet. Research at NASA Ames on closed environment life support systems produces directly applicable lessons on energy, water, and resource management in ground-based infrastructure. Moreover, every NASA campus is a 'city'; including an urbanscape and a workplace including scientists, human relations specialists, plumbers, engineers, facility managers, construction trades, transportation managers, software developers, leaders, financial planners, technologists, electricians, students, accountants, and even lawyers. NASA is applying the lessons of our mission-related activities to our urbanscapes and infrastructure, and also anticipates a leadership role in developing future environments for living and working in space.

Planetary futures↗
NASA NTRS2015

Data Processing And Machine Learning Methods For Multi-Modal Operator State Classification Systems

This document is intended as an introduction to a set of common signal processing learning methods that may be used in the software portion of a functional crew state monitoring system. This includes overviews of both the theory of the methods involved, as well as examples of implementation. Practical considerations are discussed for implementing modular, flexible, and scalable processing and classification software for a multi-modal, multi-channel monitoring system. Example source code is also given for all of the discussed processing and classification methods.

Machine learning↗
NASA NTRS2016

OpenSim Model Improvements to Support High Joint Angle Resistive Exercising

Long duration space travel to Mars or to an asteroid will expose astronauts to extended periods of reduced gravity. Since gravity is not present to aid loading, astronauts will use resistive and aerobic exercise regimes for the duration of the space flight to minimize the loss of bone density, muscle mass and aerobic capacity that occurs during exposure to a reduced gravity environment. Unlike the International Space Station (ISS), the area available for an exercise device in the next generation of spacecraft is limited. Therefore, compact resistance exercise device prototypes are being developed. The Advanced Resistive Exercise Device (ARED) currently on the ISS is being used as a benchmark for the functional performance of these new devices. Rigorous testing of these proposed devices in space flight is difficult so computational modeling provides an estimation of the muscle forces and joint loads during exercise to gain insight on the efficacy to protect the musculoskeletal health of astronauts. The NASA Digital Astronaut Project (DAP) is supporting the Advanced Exercise Concepts (AEC) Project, Exercise Physiology and Countermeasures (ExPC) project and the National Space Biomedical Research Institute (NSBRI) funded researchers by developing computational models of exercising with these new advanced exercise device concepts

Bioengineering↗
NASA NTRS2016

Squat Biomechanical Modeling Results from Exercising on the Hybrid Ultimate Lifting Kit

Long duration space travel will expose astronauts to extended periods of reduced gravity. Since gravity is not present to aid loading, astronauts will use resistive and aerobic exercise regimes for the duration of the space flight to minimize loss of bone density, muscle mass and aerobic capacity that occurs during exposure to a reduced gravity environment. Unlike the International Space Station (ISS), the area available for an exercise device in the next generation of spacecraft is limited and therefore compact resistance exercise device prototypes are being developed. The Advanced Resistive Exercise Device (ARED) currently on the ISS is being used as a benchmark for the functional performance of these new devices. Biomechanical data collection and computational modeling aid the device design process by quantifying the joint torques and the musculoskeletal forces that occur during exercises performed on the prototype devices. The computational models currently under development utilize the OpenSim software, an open source code for musculoskeletal modeling, with biomechanical input data from test subjects for estimation of muscle and joint loads. The subjects are instrumented with reflective markers for motion capture data collection while exercising on the Hybrid Ultimate Lifting Kit (HULK) prototype device. Ground reaction force data is collected with force plates under the feet and device loading is recorded through load cells internal to the HULK. Test variables include applied device load, narrow or wide foot stance, slow or fast cadence and the harness or long bar interface between the test subject and the device. Data is also obtained using free weights for a comparison to the resistively loaded exercise device. This data is input into the OpenSim biomechanical model, which has been scaled to match the anthropometrics of the test subject, to calculate the body loads. The focus of this presentation is to summarize the results from the full squat exercises across the different test variables.

Bioengineering↗
NASA NTRS2017

Biomechanical Modeling Analysis of Loads Configuration for Squat Exercise

INTRODUCTION: Long duration space travel will expose astronauts to extended periods of reduced gravity. Since gravity is not present to assist loading, astronauts will use resistive and aerobic exercise regimes for the duration of the space flight to minimize loss of bone density, muscle mass and aerobic capacity that occurs during exposure to a reduced gravity environment. Unlike the International Space Station (ISS), the area available for an exercise device in the next generation of spacecraft for travel to the Moon or to Mars is limited and therefore compact resistance exercise device prototypes are being developed. The Advanced Resistive Exercise Device (ARED) currently on the ISS is being used as a benchmark for the functional performance of these new devices. Biomechanical data collection and computational modeling aid the device design process by quantifying the joint torques and the musculoskeletal forces that occur during exercises performed on the prototype devices. METHODS The computational models currently under development utilize the OpenSim [1] software platform, consisting of open source code for musculoskeletal modeling, using biomechanical input data from test subjects for estimation of muscle and joint loads. The OpenSim Full Body Model [2] is used for all analyses. The model incorporates simplified wrap surfaces, a new knee model and updated lower body muscle parameters derived from cadaver measurements and magnetic resonance imaging of young adults. The upper body uses torque actuators at the lumbar and extremity joints. The test subjects who volunteer for this study are instrumented with reflective markers for motion capture data collection while performing squat exercising on the Hybrid Ultimate Lifting Kit (HULK) prototype device (ZIN Technologies, Middleburg Heights, OH). Ground reaction force data is collected with force plates under the feet, and device loading is recorded through load cells internal to the HULK. Test variables include the applied device load and the dual cable long bar or single cable T-bar interface between the test subject and the device. Data is also obtained using free weights with the identical loading for a comparison to the resistively loaded exercise device trials. The data drives the OpenSim biomechanical model, which has been scaled to match the anthropometrics of the test subject, to calculate the body loads. RESULTS Lower body kinematics, joint moments, joint forces and muscle forces are obtained from the OpenSim biomechanical analysis of the squat exercises under different loading conditions. Preliminary results from the model for the loading conditions will be presented as will hypotheses developed for follow on work.

Human Factors Engineering↗
NASA NTRS2018

Influence of Load Profile on Biomechanics of the Squat and Deadlift

Long duration space travel will expose astronauts to extended periods of reduced gravity. Since gravity is not present to assist loading, astronauts will use resistive and aerobic exercise regimes for the duration of the space flight to counteract the effect reduced gravity has on the body. Astronauts will exercise on a flywheel based device on the second Orion Exploration Mission (EM2). The effect that the flywheel load profile has on biomechanics is unknown when compared to free weights or a simulated free weight profile. The purpose of this evaluation is to compare the differences in lower body kinematics and kinetics between the flywheel and free weight profile. Test subjects were instrumented with reflective markers for motion capture data collection while exercising on the Device for Aerobic and Resistive Training (DART) prototype developed by TDA Research, Inc. of Wheat Ridge, CO. Exercises performed were either the squat while wearing a harness or deadlift while grasping a T-bar, both of which interfaced with the DART through a rope cable. The DART, a motorized device controlled via software, is capable of producing different load profiles. Profiles include simulated free weights with adjustable eccentric overload capability and flywheel. Test variables included the applied device load and the load profile, both set through the DART software interface. Motion capture data was collected with a 12 camera system (Smart-DX, BTS Bioengineering, Brooklyn, NY). Bilateral ground reaction force data were collected with force plates (P6000, BTS Bioengineering). DART cable force was recorded through an internal load cell. Data was collected from a total of four test subjects. The three repetition maximum was determined for each test subject for both squat and deadlift. High, medium and low loads were determined based on this maximum. The test subject performed five repetitions of each exercise at each load and each test trial was repeated twice. Cadence was controlled during exercising. Biomechanical data were used to drive the models utilizing the OpenSim software platform. Subject specific models were scaled to match the anthropometrics of the test subjects and used to estimate the peak joint angle, joint range of motion, the peak joint moment and the joint moment impulse of the lower extremity joints and the lumbar joint.These are preliminary results because the data analysis is ongoing. There was a lot of inter-subject variability, however, in general, there was a greater peak lumbar flexion angle for the flywheel squat exercise. There was a trend towards a greater range of motion at the hip for the squat exercise with free weight. There was also a greater hip extension, lumbar extension and ankle plantar flexion impulse moment during the squat exercise with free weight. During the deadlift exercise, the peak knee flexion angle and peak knee extension moment were greater when using the free weight profile. For deadlift, the hip extension, lumbar extension and ankle plantar flexion impulse moment tended to be greater with the free weight profile. Overall, the kinematic and kinetic outcomes for the flywheel profile were either statistically the same as free weight profile in many cases, significantly reduced in a few cases, and rarely higher.

Bioengineering↗
NASA NTRS2019

The Lunar Geophysical Network Mission

Overarching Principles: Must be better than Apollo (coverage, duration, instrument performance); Learn from the Apollo experience. Lunar Geophysical Network (LGN) New Frontiers (NF)-class mission, as part of the NF-5 call. “This mission consists of several identical landers distributed across the lunar surface, each carrying geophysical instrumentation. The primary science objectives are to characterize the Moon’s internal structure, seismic activity, global heat flow budget, bulk composition, & magnetic field.” Global distribution of multiple stations. Each station should contain a seismometer, heat flow probe, electromagnetic sounder, laser retroreflector (lunar nearside). Each station must be long-lived (e.g., approximately10 years)to allow other stations (from other countries?) to be integrated with the anchor nodes to form the International Lunar Network. Why LGN? Planetary Science: Moon represents an end-member in planetary evolution (large small body, small rocky planet); Primary planetary differentiation preserved; Key to understanding terrestrial planet initial differentiation. Lunar Science: Heat flow probes yield crustal heat budget estimates; Combined with EMS (ElectroMagnetic Sounding), the temperature profile of the deep interior can be modeled along with mineralogy; Seismic and LLR (Lunar Laser Ranging) data also yield structure and compositional information of the lunar interior; High fidelity data from LGN would enhance the usefulness of the GRAIL (Gravity Recovery and Interior Laboratory) and SELENE (Selenological and Engineering Explorer) gravity data. Human Exploration: LGN must be established prior to renewed human lunar activity - we do not know the exact locations or causes of the shallow moonquakes (SMQs) - the largest magnitude seismic events recorded by Apollo (1 event per year of magnitude greater than or equal to 5); Establishing surface infrastructure near SMQ epicenters must be avoided.

Neal, C. R.↗
NASA NTRS2018

Impact of Powder Variability on the Microstructure and Mechanical Behavior of Selective Laser Melted (SLM) Alloy 718

Nickel Alloy 718 has found wide use in high-temperature aerospace applications (up to 700°C), due to a combination of good mechanical properties, environmental resistance, and workability at moderate cost. These properties have led Alloy 718 to early adoption by selective laser melting (SLM) additive manufacturing. This presentation will share results from a comprehensive industry survey of 718 powder feedstock for SLM. The survey focuses on the impact of variability in powder characteristics on build quality, microstructure, tensile and high cycle fatigue in the as-fabricated and machined surface conditions. The investigation includes sixteen powder lots from eight suppliers that are produced by gas atomization or rotary atomization in argon or nitrogen. This research was previously presented and published at the 9th International Symposium on Superalloy 718 & Derivatives and was funded by NASA Space Launch System Liquid Engine Office with the Human Exploration Operations Mission Directorate.

Sudbrack, Chantal↗
NASA NTRSDate not supplied

Artemis Lunar Surface VR/ARGOS Trainer

This proposal aims to provide insight by identifying potential risks and unknowns of lander egress and surface operations through a Mixed Reality (MR) planning, training, and analysis capability that integrates Virtual Reality (VR) simulations and the Active Response Gravity Offload System (ARGOS) in support of Artemis missions to the moon. The VR simulation will incorporate lunar digital elevation map data and imagery to provide accurate terrain of the south pole and Shackleton Crater. Date specific ephemerides will used to simulate the extreme lighting environment. Virtual representations of a lunar lander vehicle will be represented with a physical mockup of the porch and ladder assembly. Human-in-the-loop engineering test runs within ARGOS will be used to refine performance of the Mixed Reality interface with the mockup platform and define procedures for training.

Lee K Bingham↗
NASA NTRSDate not supplied

U.S. Spacesuit Knowledge Capture – Creation, Curation, and Dissemination

The U.S. spacesuit is a special system that has intrigued and fascinated the world since Neil Armstrong set foot on the Moon in 1969. With over 50 years since that momentous achievement, NASA is planning to land the first woman and next man on the Moon in the near future. This goal begets the need to build a new spacesuit, a spacesuit created from the legacy knowledge of the Extravehicular Mobility Unit (EMU), combined with knowledge gained from technology development over the decades. As NASA transitions to its new horizon, the U.S. Spacesuit Knowledge Capture (SKC) Program is poised to help. The SKC Program’s primary function has been to capture, curate, and disseminate spacesuit-related knowledge among scientists, engineers, and technicians. The SKC Program was created in 2007 to capture knowledge primarily from spacesuit subject-matter experts (SMEs) who were retiring from NASA. These SMEs had 30 to 50 years of spacesuit knowledge. Over the years, the SKC Program has evolved and expanded its scope with a current focus on complementing the buildup of the Exploration EMU (xEMU) at the Johnson Space Center. As part of this focus, the SKC Program recently teamed with the xEMU Community of Practice (CoP) for knowledge sharing. The xEMU CoP provides a forum where early career engineers, professionals new to human spaceflight, and the xEMU community can come together regularly to seek guidance, share knowledge, meet their peers, discover resources, and ask questions. The CoP created an environment where the knowledge can be easily and routinely captured and recorded. The recorded events are archived and curated in an SKC Program library and disseminated as appropriate. This paper details the roles that the SKC Program and CoP play in the xEMU buildup, along with the navigation of the creation, curation, and dissemination processes.

Cinda Chullen↗
NASA NTRSDate not supplied

Leveraging Nurse Informaticists for Development of the Impact Tool

The American Nurses Association (ANA) defines nursing informatics as the integration of “nursing science, computer science, and information science to manage and communicate data, information, knowledge, and wisdom in nursing practice. [1]” In additional to nursing education and clinical experience, this field requires additional education in areas of data analysis, database management, and clinical information systems. Nursing informaticists help bridge the communication gap between clinical and technical stakeholders which help align common goals. NASA is currently developing a new medical system trade analysis and decision support tool called IMPACT (Informing Mission Planning via Analysis of Complex Tradespaces). The development team is comprised of multiple specialties including but not limited to clinicians (pharmacists, physicians, and nurse informaticists), software and program developers, human factors experts, and engineers. The nurse informaticists play a significant role in the development, operation, and results interpretation of IMPACT. Their expert knowledge and skills in both clinical nursing, information science, and database management place them in a unique position to collaborate and integrate with the clinical, engineering, and software development members of the team to achieve a cohesive, functional, and user-friendly model.

Lynn Boley↗
NASA NTRS2023

Research and Technology Challenges for Human Data Analysts in Future Safety Management Systems

Enabling new and novel concepts of operations for Advanced Air Mobility poses an important need to evolve current safety management systems (SMS) and is posited to be realized through advances in Machine Learning (ML) Data Sciences and Artificial Intelligence. The “In-time Aviation Safety Management System” (IASMS) concept of operations supports the need to evolve today’s SMS to become more tailorable, scalable, and interoperable in response to forecasted changes expected for the future airspace system. Key to IASMS is integration of proactive and predictive ML algorithms trained to provide “in time” detection and mitigation of hazards and emergent risks through new methods and novel data types. IASMS research and technology development includes human factors design considerations for these systems to include human-system teaming, innovations in human interfaces and management of complex digital data information, human-system interaction/model-based system engineering, and verification and validation for data assurance and trust.

Chad L Stephens↗
NASA NTRSDate not supplied

Durability of Geopolymer Lunar Concrete From Exposure in Low Earth Orbit

Constructing infrastructure autonomously with concrete materials through additive manufacturing techniques on the lunar surface is a feasible option. The environmental and exposure conditions that the lunar concrete material will undergo are more extreme than on Earth and studying the durability aspect is important to scaling up the implementation of such materials. Conditions that the material will be exposed to include a hard vacuum, extreme temperatures, and ultraviolet radiation. To that end, geopolymer lunar concrete and ordinary portland cement paste samples were placed outside the International Space Station (ISS) for an approximate six-month exposure period. The samples were part of the 15th Materials International Space Station Experiment (MISSE-15) mission and were mounted in the zenith direction. After the exposure time, results for the samples exhibited discoloration, microstructural cracking, and an overall reduction in volume compared to data collected beforehand. The intent of this work was to characterize geopolymer lunar concrete durability in terms of the lunar environmental conditions in LEO and potential exposure scenarios from a simulated subscale rocket engine plume. To understand the durability of samples in space environment conditions, samples were placed outside the International Space Station (ISS) for a six-month period on the MISSE-FF. Additionally, to test the material's durability if implemented for use in a landing pad, samples were created for an experiment that mimics the exposure of the material to a rocket engine associated with the human lander system. This work is essential to progressing and scaling up geopolymer lunar concrete for implementation as the material's durability is assessed.

Peter J Collins↗
NASA NTRSDate not supplied

Volumetric Assessment of UPRITE Exercises From Marker-Based Motion Capture

BACKGROUND Lack of volumetric data on full-body movement of exercises presents a challenge to ensuring the fit of crew member’s full range of motion on the International Space Station (ISS). The Upright Proprioception Retention via In-flight Training and Evaluation (UPRITE) is a sensorimotor countermeasure device designed for maintaining crew members’ proprioception in a microgravity environment. A footplate—attached to a static base—rotates in two degrees of freedom (pitch and roll) up to a 20 deg angle. An initial volumetric assessment assuming an upright standing posture produced a cone-like shape with a narrow bottom and wide top. Such general volumetric assessments risk creating an overly conservative volume estimate, taking up more space than is necessary on the already limited interior space of the ISS, and neglecting necessary volume due to oversimplifying assumptions. Rather, higher-fidelity volumetric assessments offer more comprehensive insights in an environment where every area counts. The main objective of this work is to provide the spatial parameters of exercises on the UPRITE such that it is placed on the ISS according to its volumetric demands or that usage is adjusted to fit the available space. METHODS In 2023, a data collection was performed originally to inform loads and dynamics of system use and was recently leveraged for volumetric assessment. Three human subjects representing different body types (~63-76 inches in stature) performed a variety of board manipulations using UPRITE with body weight offload. The test collected the 3D positional data of a modified full-body Plug-in Gait marker set [1] via a 16-camera OptiTrack MoCap system. After processing – filling marker gaps and trimming data – in OptiTrack Motive, the recorded marker location data, which included device markers, was exported to a readable trajectory file. To accurately represent the full volume defining landmarks, additional markers were digitally added to an unscaled Modified Full Body Model [2]. The model was then scaled according to its subject parameters upon which an inverse kinematics analysis was performed. A custom plugin yielded model marker location data files. Volumetric analyses were performed on the recorded trajectory and model trajectory files using a custom Python-built tool that extracted the marker location data and plotted it in a 3D space. Concerned with only the maximum volume of the motion, a 3D convex hull analysis was applied to the plot, extracting the vertices or external points of the eventual 3D CAD output, dubbed aptly as a “volume shell”. This overall approach was based on guidance in a NASA-STD-3001 Technical Brief [3]. RESULTS AND DISCUSSION Batch volumetric assessment on the exercises for each subject was performed, producing high-fidelity volume shells in minimal time. Preliminary results highlighted the value in higher-fidelity volumes based on collected data when possible. For example, revolving a single posture in the cone assessment would not have sufficiently captured a single leg stance; rather, it would need to involve swinging the leg both forward and back. Additional observations and the maximal dimensions of the volumes, including those based on scaled data for ISS anthropometric requirements, will be presented at the Human Research Program Investigator’s Workshop. CONCLUSIONS While this work’s primary objective was for the UPRITE-to-ISS integration, the tool built to conduct this analysis has wide applications for future exercise systems as an informational tool for optimal device placement. The tool and its findings also have implications for exercise device design and spacecraft interior considerations on Gateway, the Lunar Pressurized Rover, and beyond. REFERENCES [1] Bell, C. A., et al. (2023) Recent Improvements and Verification of a Full Body Model in OpenSim. NASA Human Research Program Investigator’s Workshop. https://ntrs.nasa.gov/citations/20230001080 [2] Lostroscio, K., et al (2023) The Digital Astronaut Simulation. AHFE International Conference on Human Factors in Design, Engineering, and Computing for All. [3] Exercise Overview. (2023) NASA-STD-3001 Technical Brief. https://www.nasa.gov/wp-content/uploads/2023/12/ochmo-tb-031-exercise-overview.pdf?emrc=9d454c?emrc=9d454c

L D Quinto↗
DOE OSTI2024

Digitalization mapping and assessment process supporting ION strategic transformation activities

The existing fleet of commercial nuclear power plants (NPPs) are an important asset in the nation’s portfolio of electrical generating resources. Their continued safe and reliable operation are critical to providing a large source of carbon-free electricity to power the nation’s economy. The United States Department of Energy’s (DOE) Light Water Reactor Sustainability (LWRS) Program develops the scientific bases, methods, and tools, for the continued safe and economical operation of the nation's commercial NPPs. The Plant Modernization Pathway within LWRS Program focuses on providing guidance to industry on the full-scale implementation of modernization solutions for NPPs that significantly reduce the technical and financial risks associated with modernization. This research is focused on helping the nuclear industry understand how to digitize and digitalize their NPPs so that they can design their modernization solutions to be scalable, sustainable, and integrated both laterally and horizontally within their organization. That is, this research creates a digital transformation in NPPs by reshaping cultural mindsets and by identifying business efficiencies. In partnership with industry, and using four previously established guiding principles for digitalization, this research supported NPP modernization through assessing readiness for digitalization as a means to achieve integrated operations for nuclear. Specifically, this research created an assessment to review an entire organization’s work processes to gather information about the digitalization health of the plant. The assessment tools were administered to plant employees, and the results were used to develop a digitalization plan. The survey assessment identified the optimal candidate processes that would most benefit from a digitalization initiative which were revealed through analytical frameworks. One analysis calculated mean digitalization health indicator scores for all endorsed activities which allowed the researchers to rank and color code the results for easy identification. Individual health indicator scores are also provided, should our industry partner wish to understand these findings according to their own organizational priorities, business considerations and desired end-state. The results were also analyzed from the perspective that organizations are comprised of different types of innovators (e.g., generators, optimizers, conceptualizers, and implementers), which differentially affects the organization’s ability to comprehend and adapt to change (i.e., opportunities to innovate). Understanding the relative composition of innovator types at an NPP allows them to gather insights into the strengths and weaknesses they have in innovating how work is performed. For the utility that partnered with this research team, the results showed that implementers make up the largest portion of respondents and conceptualizers the smallest portion. Knowing the proportion of innovator types gave this organization insights on how they can effectively implement their innovation solutions. Additionally, the results were analyzed from a technical, economic, and risk perspective to identify and quantify work reduction opportunities (WROs). Recognizing that not all cost-saving opportunities are the same, a Technical, Economic and Risk Assessment (TERA) was performed to evaluate WROs to identify areas of greatest potential and lowest risk. The key results from TERA included a digitalization opportunity score for each activity, and a calculation of potential cost savings. These two outputs formed the bases for calculating a priority index and rank for the activities/processes assessed. From the prioritization calculations, TERA can then help the utility 1) decide what digitalization priorities to invest money in implementing and then 2) calculates how much should be invested in the digitalization initiatives selected to achieve cost savings and/or an acceptable return on investment. Last, onsite interviews revealed several inefficiencies in the standard work processes that occur cross-departmentally that are due to the absence of digitized and digitalized processes. Examples of these include time spent scanning paper documents and then uploading the documents electronically, obtaining signatures, and searching for desired information. This represents a digital but not digitalized process. Over 15 opportunities to improve work processes were identified through this multi-method digitalization assessment. The various analytical assessments used (e.g., TERA, digitalization health indicator scores), as well as discussions with the utility partner, corroborated that all the opportunities identified had a strong potential to make work processes more efficient and to improve overall performance of the NPP.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Insights from Surrogate Industries on Remote Operations for Advanced Reactors

With development of advanced reactors, understanding the human factors considerations related to remote operations remains an important topic. This work presents insights captured from reviewing relevant surrogate industries with remote operations, as they may apply to advanced reactor development. This work provides insights into important human factors considerations for remote operations to ensure safe and reliable adoption of these prospective reactor technologies.

99 - GENERAL AND MISCELLANEOUS↗