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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Effects of Replacing Treadmill Running with Alternative Exercise Countermeasures During Long-Duration Spaceflight

INTRODUCTION: Current exercise countermeasures on the International Space Station (ISS) include treadmill running, cycle ergometry, and resistive exercise, which are used to protect crewmember health and performance during long-duration spaceflight. However, exploration vehicles for Artemis and beyond will have volume and power restrictions, requiring exercise hardware to have a smaller footprint and use fewer resources. Thus, recent efforts have focused on developing exercise devices (such as the European Enhanced Exploration Exercise Device [E4D]) that provide both aerobic and resistive training on one platform without including a treadmill. It is critical to validate the efficacy of exploration-focused exercise modalities to preserve muscle strength, aerobic fitness, bone density, and sensorimotor performance. Thus, the aim of this study is to determine the physiological effects of spaceflight that occur with nominal ISS exercise prescriptions compared to exploration-forward exercise modalities to determine if a treadmill is required to maintain current levels of protection during long-duration missions. METHODS: Crewmembers will be assigned to one of three groups: 1) Control Group (n ≥ 40), who will partake in nominal exercise on the ISS, including running on the Treadmill with Vibration Isolation and Stabilization 2 (T2), ergometry on the Cycle Ergometer with Vibration Isolation and Stabilization (CEVIS) device, and strength training on the Advanced Resistive Exercise Device (ARED); 2) Active Group 1, who will partake in CEVIS and ARED exercise only (n = 8); and 3) Active Group 2, who will partake in aerobic and resistive exercise on the E4D only (n = 8). For Active Group 1, nominal aerobic exercise on T2 will be replaced with corresponding exercise on CEVIS. For Active Group 2, a dedicated exercise prescription will be designed to maximize the capabilities of the E4D to include resistive exercise, cycle ergometry, rowing, and rope pulling. Crewmembers in both active groups will not be permitted to perform treadmill exercise. Health and performance markers including bone mineral density (dual-energy x-ray absorptiometry [DXA]), body composition (DXA), cardiovascular fitness (cycle VO2peak), muscle strength and endurance (isometric/isokinetic testing, power endurance testing), sensorimotor performance (sit-to-stand, obstacle course), postural control (computerized dynamic posturography), and blood and urine biochemical markers of bone metabolism will be assessed before, during, and following spaceflight. RESULTS: Thirteen subjects (3 Active [CEVIS + ARED], 10 Control) have been recruited for this study. Data collection is currently in progress. CONCLUSIONS: This study will assess the efficacy of exploration exercise modalities, including the effects of removing the treadmill exercise capability or of exclusively using the E4D, compared to nominal ISS exercise across an entire mission on bone, muscle, aerobic, and sensorimotor health and performance. Findings from this study will help provide a recommendation on whether these exploration exercise modalities can sufficiently protect against physiological deconditioning during spaceflight or whether a treadmill may be required to maintain current levels of protection during future exploration class spaceflight missions.

A.N. Varanoske↗
NASA NTRSDate not supplied

Effects of Replacing Treadmill Running with Alternative Exercise Countermeasures During Long-Duration Spaceflight

Introduction: Current exercise countermeasures on the International Space Station (ISS), including treadmill running, cycle ergometry, and resistive exercise, are used to protect crewmember health and performance during long-duration spaceflight. However, exploration vehicles for Artemis and beyond will have volume and power restrictions, requiring exercise hardware to have a smaller footprint and use fewer resources. Thus, recent efforts have focused on developing exercise devices that provide both aerobic and resistive training on one platform without including a treadmill, such as the European Enhanced Exploration Exercise Device (E4D). It is critical to validate the efficacy of exploration-focused exercise modalities to preserve muscle strength, aerobic fitness, bone density, and sensorimotor performance. Thus, the aim of this study is to determine the physiological effects of spaceflight that occur with nominal ISS exercise prescriptions compared to exploration-forward exercise modalities to determine if a treadmill is required to maintain current levels of protection during long-duration missions. Methods: Crewmembers will be assigned to one of three groups: 1) Control Group (n ≥ 40) who will partake in nominal exercise on the ISS, including running on the treadmill with vibration isolation system 2 (T2), ergometry on the cycle ergometer with vibration isolation and stabilization device (CEVIS), and strength training on the advanced resistive exercise device (ARED); 2) Active Group 1, who will partake in CEVIS and ARED exercise only (n = 8); and 3) Active Group 2, who will partake in aerobic and resistive exercise on the E4D only (n = 8). For Active Group 1, nominal aerobic exercise on T2 will be replaced with corresponding exercise on CEVIS. For Active Group 2, a dedicated exercise prescription will be designed to maximize the capabilities of the E4D to include resistive exercise, cycle ergometry, rowing, and rope pulling. Crewmembers in both active groups will not be permitted to perform treadmill exercise. Health and performance markers including bone mineral density (dual-energy x-ray absorptiometry [DXA]), body composition (DXA), cardiovascular fitness (cycle VO2peak), muscle strength and endurance (isometric/isokinetic testing, power endurance testing), sensorimotor performance (sit-to-stand, obstacle course), postural control (computerized dynamic posturography), and blood and urine biochemical markers of bone metabolism will be assessed before, during, and following spaceflight. Results: Data collection for this study is currently in progress. Conclusions: This study will assess the efficacy of exploration exercise modalities, including the effects of removing the treadmill exercise capability or of exclusively using the E4D, compared to nominal ISS exercise across an entire mission on bone, muscle, aerobic, and sensorimotor health and performance. Findings from this study will help provide a recommendation on whether these exploration exercise modalities can sufficiently protect against physiological deconditioning during spaceflight or whether a treadmill may be required to maintain current levels of protection during future exploration class spaceflight missions.

A.N. Varanoske↗
DOE OSTI2023

Bridging Place-Based Astrobiology Education with Genomics, Including Descriptions of Three Novel Bacterial Species Isolated from Mars Analog Sites of Cultural Relevance

Democratizing genomic data science, including bioinformatics, can diversify the STEM workforce and may, in turn, bring new perspectives into the space sciences. In this respect, the development of education and research programs that bridge genome science with “place” and world-views specific to a given region are valuable for Indigenous students and educators. Through a multi-institutional collaboration, we developed an ongoing education program and model that includes Illumina and Oxford Nanopore sequencing, free bioinformatic platforms, and teacher training workshops to address our research and education goals through a place-based science education lens. High school students and researchers cultivated, sequenced, assembled, and annotated the genomes of 13 bacteria from Mars analog sites with cultural relevance, 10 of which were novel species. Students, teachers, and community members assisted with the discovery of new, potentially chemolithotrophic bacteria relevant to astrobiology. This joint education-research program also led to the discovery of species from Mars analog sites capable of producing N-acyl homoserine lactones, which are quorum-sensing molecules used in bacterial communication. Whole genome sequencing was completed in high school classrooms, and connected students to funded space research, increased research output, and provided culturally relevant, place-based science education, with participants naming three novel species described here. Students at St. Andrew's School (Honolulu, Hawai‘i) proposed the name Bradyrhizobium prioritasuperba for the type strain, BL16A T , of the new species (DSM 112479 T = NCTC 14602 T ). The nonprofit organization Kauluakalana proposed the name Brenneria ulupoensis for the type strain, K61 T , of the new species (DSM 116657 T = LMG = 33184 T ), and Hawai‘i Baptist Academy students proposed the name Paraflavitalea speifideiaquila for the type strain, BL16E T , of the new species (DSM 112478 T = NCTC 14603 T ).

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2010

Development of an Integrated Countermeasure Device for Long Duration Space Flight and Exploration Missions

Musculoskeletal, cardiovascular, and sensorimotor deconditioning have been observed consistently in astronauts and cosmonauts following long-duration spaceflight. Studies in bed rest, a spaceflight analog, have shown that high intensity resistive or aerobic exercise attenuates or prevents musculoskeletal and cardiovascular deconditioning, respectively, but complete protection has not been achieved during spaceflight. Exercise countermeasure hardware used during earlier International Space Station (ISS) missions included a cycle ergometer, a treadmill, and the interim resistive exercise device (iRED). Effectiveness of the countermeasures may have been diminished by limited loading characteristics of the iRED as well as speed restrictions and subject harness discomfort during treadmill exercise. The Advanced Resistive Exercise Device (ARED) and the second generation treadmill were designed to address many of the limitations of their predecessors, and anecdotal reports from ISS crews suggest that their conditioning is better preserved since the new hardware was delivered in 2009. However, several countermeasure devices to protect different physiologic systems will not be practical during exploration missions when the available volume and mass will be severely restricted. The combined countermeasure device (CCD) integrates a suite of hardware into one device intended to prevent spaceflight-induced musculoskeletal, cardiovascular, and sensorimotor deconditioning. The CCD includes pneumatic loading devices with attached cables for resistive exercise, a cycle for aerobic exercise, and a 6 degree of freedom motion platform for balance training. In a proof of concept test, ambulatory untrained subjects increased muscle strength (58%) as well as aerobic capacity (26%) after 12-weeks of exercise training with the CCD (without balance training), improvements comparable to those observed with traditional exercise training. These preliminary results suggest that this CCD can concurrently improve musculoskeletal and cardiovascular conditioning in ambulatory subjects, but further work is required to validate its use as countermeasure to spaceflight-induced deconditioning.

Lee, S. M. C.↗
NASA NTRS2018

Field Camp for Astronauts: NASA's Geoscience Training Program for Planetary Exploration

Fifty years ago Apollo astronauts walked on the Moon to explore the geology and collect samples for Earth return. Several authors have discussed the strategic planning and training that enabled the Apollo successes, and assembled recommendations regarding today’s lunar science objectives and astronaut training required to achieve those science goals. Since the 1980s, geoscience training for astronauts focused on observing the Earth from orbit. Today, we are building a geoscience training program to support informed Earth observations as well as the exploration culture for future human missions to the Moon and Mars. Our team partnered with JSC’s crew training and astronaut offices to develop our 4-week geoscience program for the 2017 astronaut class. Because the astronauts have a variety of professional backgrounds, we provide a broad introduction to Earth and planetary sciences. But our prime focus is 2 weeks of intensive field work, a methodology introduced with the 2013 astronaut class. We completed the first half of the training – a field trip to observe hurricane deposits along Galveston Bay; keynotes by Apollo colleagues highlighting Apollo experiences; a tightly-integrated week of introductory geology in the classroom followed by a week of fieldwork in the Rio Grande del Norte National Monument. The classroom included interactive map exercises that allowed the students to progressively build a base map of the field area that they used as a starting point for their week-long mapping exercise. We divided the class into small mapping groups to conduct their observations, mapping and interpretation of the geology. In addition to learning geological field work, our field training provided the platform for practicing expeditionary leadership, a key skill set valued by NASA for astronaut crews. Next summer the capstone fieldwork for the 2017 astronauts will include both mapping and rock sampling. Throughout the mapping, the class will collect additional data to help inform field and sampling decisions using diagnostic field instruments that are being tested in analog settings for their operational efficacy for future planetary exploration.

Evans, Cynthia A.↗
NASA NTRSDate not supplied

Exploration Exercise System (EES) Physiology

Exploration class missions will be required to have an exercise device that is lightweight, has a small footprint, and is capable of providing enough physical stimulus and exercise variability to be an effective countermeasure against muscle, bone, aerobic fitness, and sensorimotor loss that results from the microgravity environment. Ground studies, inflight studies, and results analyses are required to inform Moon2Mars Design Reference Missions (DRMs) and vehicle designs. This activity encompasses two related projects, an evaluation study called Zero T2 and a requirements development for an exploration treadmill (ET). Exploration class missions’ mass/power/volume restrictions have resulted in the development of exercise devices that are motorized and flywheel-based to provide both aerobic and resistive training on one platform. These devices provide a variety of full body resistance exercise options as well as rowing and cycling for aerobic exercise, but do not provide ambulatory exercise via a treadmill. Because a treadmill has been available for use on the ISS since 2001, we do not understand the efficacy of exploration exercise modalities on muscle performance, aerobic fitness, bone health, or sensorimotor performance. A retrospective study was performed to quantify the association between total exercise (including specific contributions of treadmill exercise) and functional performance upon landing. Due to the relatively small variation in treadmill usage inflight, there is a need to do a controlled study where inflight crewmembers will not use the ISS treadmill (called T2) for the duration of their flights. There will be 3 arms to the Zero T2 study: 1) participants use all currently available exercise platforms aboard ISS (control group), 2) participants use only ARED and CEVIS, and 3) participants use only European Enhanced Exploration Device (E4D). (Please see the TechPort Entry for Exploration Exercise System Development for further detail on the E4D.) This study started in Oct 2020 and will continue through Sep 2027. In a parallel effort, a team will be developing requirements for an exploration treadmill. This project will be broken into two phases. Phase 1 will develop and implement energy prediction models based on available in-flight exercise data to quantify energy expenditure during 0g treadmill running. Phase 2 will then use the available biomechanical and metabolic evidence from Phase 1 to determine the hardware specification requirements essential to providing the desired exercise stimulus. Subject Matter Experts (SMEs) will then leverage the Standardized Process for Evaluating Exercise Devices (SPEED) developed by the team to 1) assess available technologies for candidate treadmills which meet defined requirements, 2) perform hands-on evaluations of top candidates, 3) provide evaluation outcomes and recommendations to developers. This project will begin in 2025 and continue through Sep 2030.

Kent Lawrence Kalogera↗
DOE OSTI2026

An interactive machine learning platform for analyzing multi-particle coincidence data from cold target recoil ion momentum spectroscopy

We present SCULPT (Supervised Clustering and Uncovering Latent Patterns with Training), a comprehensive software platform for analyzing tabulated high-dimensional multi-particle coincidence data from Cold Target Recoil Ion Momentum Spectroscopy (COLTRIMS) experiments. The software addresses critical challenges in modern momentum spectroscopy by integrating advanced machine learning techniques with physics-informed analysis in an interactive web-based environment. SCULPT implements uniform manifold approximation and projection for non-linear dimensionality reduction to reveal correlations in high-dimensional data. We also discuss potential extensions to deep autoencoders for feature learning and genetic programming for automated discovery of physically meaningful observables. A novel adaptive confidence scoring system provides quantitative reliability assessments by evaluating user-selected clustering quality metrics with predefined weights that reflect each metric’s robustness. The platform features configurable molecular profiles for different experimental systems, interactive visualization with selection tools, and comprehensive data filtering capabilities. Utilizing a subset of SCULPT’s capabilities, we analyze photo-double-ionization data measured using the COLTRIMS method for three-body dissociation of the D 2 O molecule, revealing distinct fragmentation channels and their correlations with physics parameters. The software’s modular architecture and web-based implementation make it accessible to the broader atomic and molecular physics community, significantly reducing the time required for complex multi-dimensional analyses. This opens the door to finding and isolating rare events exhibiting non-linear correlations on the fly during experimental measurements, which can help steer exploration and improve the efficiency of experiments.

Artificial neural networks↗
DOE OSTI2026

Lessons learned from the development and implementation of a workforce training curriculum for advanced controls for high performance HVAC systems

Over the past decade, academic research on advanced controls has slowly transitioned into new software platforms, giving rise to various companies developing and deploying these innovative products, including solutions for light commercial HVAC systems. However, the current workforce remains widely unprepared to install, maintain and operate these systems, particularly complex software-based control platforms, as most workforce training programs still focus on traditional building automation for large commercial buildings. This paper presents the development and piloting of curriculum for three key types of professionals: ● Technicians (trade-level): installing and maintaining modern high-performance HVAC systems and controls ● Programmers (undergrad-level): developing and implementing advanced controls ● Engineers and energy professionals (undergrad/grad-level): managing and evaluating system performance We share details of the material developed including training videos, open-source software, instruction manuals. We also present the results of a pilot implementation of the training materials with real students.

Casillas, Armando↗
DOE OSTI2025

Reinforcement Learning Control for Buildings Co-Optimizing Energy, Comfort, and Indoor Air Quality: An Annual Assessment

Efficient control of Heating, Ventilation, and Air Conditioning (HVAC) systems is crucial for optimizing energy use and maintaining indoor comfort in buildings. Traditional control methods, such as PID control, cannot handle energy use trade-offs among multiple components in the building energy system at a supervisory level. Reinforcement learning (RL) presents a promising solution, offering adaptive and data-driven control strategies that optimize performance over time. However, RL also faces several challenges, including the conflicts encountered in co-optimizing energy savings, occupant comfort, and indoor air quality, and the requirement for extensive interactions with the environment in training. We proposed a flexible simulation platform that integrates a hybrid model for RL training and designed an RL agent to control the entire central HVAC system, focusing on co-optimizing energy consumption, thermal comfort, and indoor air quality ($\text{CO}_{2}$ and PM2.5 concentrations). Finally, we evaluated the RL agent's performance over an annual cycle. Our findings indicate that the RL agent can effectively manage the HVAC system with 14.7 % energy savings annually and balance multiple objectives, which demonstrates significant potential for improving HVAC system control and sustainability in buildings.

Guo, Fangzhou↗
DOE OSTI2019

Optimization of Workload Distribution of Data Centers Based on a Self-Learning In Situ Adaptive Tabulation Model

Data center cooling typically involves non-uniform airflow and temperature distributions, which are affected by the IT workload distribution. It is helpful to simulate the airflow and temperature to optimize the workload distribution. Traditional computational fluid dynamics (CFD) simulation is usually time-consuming while conventional reduced order models (ROMs), though computationally fast, may generate inaccurate results even after being fully trained. In Situ Adaptive Tabulation (ISAT), contracting to conventional ROM, can make prediction with error lower than a user-specified tolerance. To demonstrate using of ISAT for optimal workload distribution in data center, this paper presents a preliminary study of an ISAT-based genetic algorithm optimization platform. The ISAT is trained offline by using the results from CFD simulations using a hypothetical simple data center. The optimal workload distribution determined by the platform leads to approximately 6.8% of energy savings when compared to the benchmark with a uniform workload distribution. We note that the time cost for the entire optimization process, including the training of ISAT is about 4 hours, which is acceptable in the design phase.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Analyzing inference workloads for spatiotemporal modeling

Ensuring power grid resiliency, forecasting climate conditions, and optimization of transportation infrastructure are some of the many application areas where data is collected in both space and time. Spatiotemporal modeling is about modeling those patterns for forecasting future trends and carrying out critical decision-making by leveraging machine learning/deep learning. Once trained offline, field deployment of trained models for near real-time inference could be challenging because performance can vary significantly depending on the environment, available compute resources and tolerance to ambiguity in results. Users deploying spatiotemporal models for solving complex problems can benefit from analytical studies considering a plethora of system adaptations to understand the associated performance-quality trade-offs. To facilitate the co-design of next-generation hardware architectures for field deployment of trained models, it is critical to characterize the workloads of these deep learning (DL) applications during inference and assess their computational patterns at different levels of the execution stack. In this paper, we develop several variants of deep learning applications that use spatiotemporal data from dynamical systems. We study the associated computational patterns for inference workloads at different levels, considering relevant models (Long short-term Memory, Convolutional Neural Network and Spatio-Temporal Graph Convolution Network), DL frameworks (Tensorflow and PyTorch), precision (FP16, FP32, AMP, INT16 and INT8), inference runtime (ONNX and AI Template), post-training quantization (TensorRT) and platforms (Nvidia DGX A100 and Sambanova SN10 RDU). Overall, our findings indicate that although there is potential in mixed-precision models and post-training quantization for spatiotemporal modeling, extracting efficiency from contemporary GPU systems might be challenging. Instead, co-designing custom accelerators by leveraging optimized High Level Synthesis frameworks (such as SODA High-Level Synthesizer for customized FPGA/ASIC targets) can make workload-specific adjustments to enhance the efficiency.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Factors affecting variability in PM2.5 exposure concentrations in a metro system

Highlights: • Door-side PM{sub 2.5} concentrations typically increase when train doors open. • Train in-cabin PM{sub 2.5} concentrations are lower than ambient PM{sub 2.5} concentration. • Underground metro train in-cabin PM{sub 2.5} concentrations are higher than above-ground. • Ambient PM{sub 2.5} infiltration into cabins is higher for above-ground than underground. • Non-ambient sources contributed around half of PM{sub 2.5} inside the underground metro. The objectives of this study were to: (1) evaluate PM{sub 2.5} inflow to metro train cabins when doors open at stations; (2) assess the spatial and temporal variability in PM{sub 2.5} exposure concentration; and (3) quantify the relationship between in-cabin concentration versus outdoor and non-ambient PM{sub 2.5}. We measured in-cabin PM{sub 2.5} concentrations using portable monitors at the door-side and center of a train cabin simultaneously on a Hong Kong metro line. In addition, platform and in-cabin pollutant concentrations near a train door were simultaneously measured. Short-term spikes in PM{sub 2.5} concentrations typically occur near train doors when doors open, related to inflow of ambient air aboveground and tunnel air underground. In-cabin PM{sub 2.5} exposure concentrations are typically lower away from the doors when the doors open. PM{sub 2.5} concentrations inside train cabins and on station platform operating above-ground are more influenced, compared to underground, by outdoor PM{sub 2.5}. Moreover, non-ambient sources contribute approximately 50% of train in-cabin and station platform PM{sub 2.5} concentrations during underground operation. The results help more accurately quantify commuting PM{sub 2.5} exposure on a metro system, and can be used to improve population-based exposure simulation models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2015

Developing a Business Intelligence Process for a Training Module in SharePoint 2010

Prior to this project, training information for the employees of the National Center for Critical Processing and Storage (NCCIPS) was stored in an array of unrelated spreadsheets and SharePoint lists that had to be manually updated. By developing a content management system through a web application platform named SharePoint, this training system is now highly automated and provides a much less intensive method of storing training data and scheduling training courses. This system was developed by using SharePoint Designer and laying out the data structure for the interaction between different lists of data about the employees. The automation of data population inside of the lists was accomplished by implementing SharePoint workflows which essentially lay out the logic for how data is connected and calculated between certain lists. The resulting training system is constructed from a combination of five lists of data with a single list acting as the user-friendly interface. This interface is populated with the courses required for each employee and includes past and future information about course requirements. The employees of NCCIPS now have the ability to view, log, and schedule their training information and courses with much more ease. This system will relieve a significant amount of manual input and serve as a powerful informational resource for the employees of NCCIPS in the future.

Schmidtchen, Bryce↗
NASA NTRS2009

Training Modalities to Increase Sensorimotor Adaptability

During the acute phase of adaptation to novel gravitational environments, sensorimotor disturbances have the potential to disrupt the ability of astronauts to perform required mission tasks. The goal of our current series of studies is develop a sensorimotor adaptability (SA) training program designed to facilitate recovery of functional capabilities when astronauts transition to different gravitational environments. The project has conducted a series of studies investigating the efficacy of treadmill training combined with a variety of sensory challenges (incongruent visual input, support surface instability) designed to increase adaptability. SA training using a treadmill combined with exposure to altered visual input was effective in producing increased adaptability in a more complex over-ground ambulatory task on an obstacle course. This confirms that for a complex task like walking, treadmill training contains enough of the critical features of overground walking to be an effective training modality. SA training can be optimized by using a periodized training schedule. Test sessions that each contain short-duration exposures to multiple perturbation stimuli allows subjects to acquire a greater ability to rapidly reorganize appropriate response strategies when encountering a novel sensory environment. Using a treadmill mounted on top of a six degree-of-freedom motion base platform we investigated locomotor training responses produced by subjects introduced to a dynamic walking surface combined with alterations in visual flow. Subjects who received this training had improved locomotor performance and faster reaction times when exposed to the novel sensory stimuli compared to control subjects. Results also demonstrate that individual sensory biases (i.e. increased visual dependency) can predict adaptive responses to novel sensory environments suggesting that individual training prescription can be developed to enhance adaptability. These data indicate that SA training can be effectively integrated with treadmill exercise and optimized to provide a unique system that combines multiple training requirements in a single countermeasure system. Learning Objectives: The development of a new countermeasure approach that enhances sensorimotor adaptability will be discussed.

Bloomberg, J. J.↗
NASA NTRS2015

Portable Virtual Training Units

The Mission Operations Lab initiated a project to design, develop, deliver, test, and validate a unique training system for astronaut and ground support personnel. In an effort to keep training costs low, virtual training units (VTUs) have been designed based on images of actual hardware and manipulated by a touch screen style interface for ground support personnel training. This project helped modernized the training system and materials by integrating them with mobile devices for training when operators or crew are unavailable to physically train in the facility. This project also tested the concept of a handheld remote device to control integrated trainers using International Space Station (ISS) training simulators as a platform. The portable VTU can interface with the full-sized VTU, allowing a trainer co-located with a trainee to remotely manipulate a VTU and evaluate a trainee's response. This project helped determine if it is useful, cost effective, and beneficial for the instructor to have a portable handheld device to control the behavior of the models during training. This project has advanced NASA Marshall Space Flight Center's (MSFC's) VTU capabilities with modern and relevant technology to support space flight training needs of today and tomorrow.

Malone, Reagan↗
NASA NTRS2011

Leveraging Gaming Technology to Deliver Effective Training

The best way to engage a soldier is to present them with training content consistent with their learning preference. Blended Interactive Multimedia Instruction (IMI) can be used to leach soldiers what they need to do, how to do each step, and utilize a COTS game engine to actually practices the skills learned. Blended IMI provides an enjoyable experience for the soldier, thereby increasing retention rates and motivation while decreasing the time to subject mastery. And now mobile devices have emerged as an exciting new platform, literally placing the training into the soldier's hands. In this paper, we will discuss how we leveraged commercial game engine technology, tightly integrated with the Blended IMI, to train soldiers on both laptops and mobile devices. We will provide a recent case study of how this training is being utilized, benefits and student/instructor feedback.

Cimino, James D.↗
DOE OSTI2023

Capturing dynamical correlations using implicit neural representations

Abstract Understanding the nature and origin of collective excitations in materials is of fundamental importance for unraveling the underlying physics of a many-body system. Excitation spectra are usually obtained by measuring the dynamical structure factor, S ( Q , ω ), using inelastic neutron or x-ray scattering techniques and are analyzed by comparing the experimental results against calculated predictions. We introduce a data-driven analysis tool which leverages ‘neural implicit representations’ that are specifically tailored for handling spectrographic measurements and are able to efficiently obtain unknown parameters from experimental data via automatic differentiation. In this work, we employ linear spin wave theory simulations to train a machine learning platform, enabling precise exchange parameter extraction from inelastic neutron scattering data on the square-lattice spin-1 antiferromagnet La 2 NiO 4 , showcasing a viable pathway towards automatic refinement of advanced models for ordered magnetic systems.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Retrospective on decadal progress of the NOAA/NPS ocean noise reference station network

The National Oceanic and Atmospheric Administration (NOAA), in partnership with the U.S. National Park Service (NPS), established the Ocean Noise Reference Station Network (NRS) in 2014 as a foundational component of NOAA’s Ocean Noise Strategy. This long-term effort aims to characterize baseline ocean ambient sound conditions across diverse marine environments and to inform management of noise impacts on protected species and habitats within U.S. waters. The NRS is now composed of 13 autonomous passive acoustic monitoring stations strategically positioned across the U.S. Exclusive Economic Zone (EEZ), extending from Arctic regions to tropical waters in depths ranging from 33 to 4,790 m. These locations include several National Marine Sanctuaries and National Parks, such as the recently designated Chumash Heritage National Marine Sanctuary off the coast of California. Each station is equipped to continuously sample low-frequency underwater sound at five kHz, enabling the detection of anthropogenic, geophysical, and biological acoustic signals. To date the network has sampled over 72 years of calibrated acoustic data. The spatial breadth and consistent methodology of the NRS allow for comparative acoustic assessments across diverse marine ecosystems. In addition to applied research functions, the NRS has served as a platform for education and training, offering opportunities for students to develop skills for marine science and data analysis. Looking forward, the NRS project team is focused on network expansion, improved data delivery, and broader integration with collaborative scientific initiatives. NRS recordings are being archived in partnership with NOAA’s National Centers for Environmental Information to enhance accessibility and long-term utility. Efforts are underway to develop standardized metadata and summary products to accompany raw audio files, making the data more usable for a wide range of stakeholders in the ocean science community. The NRS is evolving into a fully integrated national framework for ocean sound monitoring that supports scientific inquiry, management decision-making, national security interests, and public engagement with ocean acoustic environments.

Long-term monitoring↗