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At least 505 records · Page 28

Microbiome dynamics in the congregate environment of U.S. Army Infantry training

Within military training and operational environments, individuals from diverse backgrounds share common spaces, follow structured routines and diets, and engage in physically demanding tasks. While there has been interest in leveraging microbiome features to predict and improve military health and performance, the longitudinal convergence of microbiomes in such constrained environments has not been established. To assess the degree of microbiome convergence, we performed shotgun metagenomic sequencing on swab samples from a military trainee cohort. Samples were taken across four different body sites, three timepoints, and two spatially distinct platoons. We observed evidence of convergence in one platoon, whereby similarity in microbiome composition increased over time, with numerous differentially abundant species. We found no indication of strain transfer between individuals, suggesting that convergence was influenced by external environmental factors, diet, and lifestyle. Microbial shifts observed in the convergence process included a decrease in fungal species, such as Malassezia restricta in nasal cavities, and a decrease in Prevotella species at inguinal regions across time. Shifts in multiple Corynebacterium species were also observed with varying magnitudes depending on the body site. Overall, we provide preliminary evidence of convergence of host microbial communities in military-associated environments that were distinguishable using shotgun metagenomic sequencing approaches. The data presented here on microbiome convergence, dynamics, and stability may inform risk-based mitigation in congregate military settings facilitating development of targeted microbial, dietary, or other interventions to optimize health and performance of military populations.

Biological and medical sciences↗

Multi-Sensor Testing for Automated Rendezvous and Docking Sensor Testing at the Flight Robotics Laboratory

The Exploration Systems Architecture defines missions that require rendezvous, proximity operations, and docking (RPOD) of two spacecraft both in Low Earth Orbit (LEO) and in Low Lunar Orbit (LLO). Uncrewed spacecraft must perform automated and/or autonomous rendezvous, proximity operations and docking operations (commonly known as AR&D). The crewed missions may also perform rendezvous and docking operations and may require different levels of automation and/or autonomy, and must provide the crew with relative navigation information for manual piloting. The capabilities of the RPOD sensors are critical to the success of the Exploration Program. NASA has the responsibility to determine whether the Crew Exploration Vehicle (CEV) contractor proposed relative navigation sensor suite will meet the requirements. The relatively low technology readiness level of AR&D relative navigation sensors has been carried as one of the CEV Project's top risks. The AR&D Sensor Technology Project seeks to reduce the risk by the testing and analysis of selected relative navigation sensor technologies through hardware-in-the-loop testing and simulation. These activities will provide the CEV Project information to assess the relative navigation sensors maturity as well as demonstrate test methods and capabilities. The first year of this project focused on a series of"pathfinder" testing tasks to develop the test plans, test facility requirements, trajectories, math model architecture, simulation platform, and processes that will be used to evaluate the Contractor-proposed sensors. Four candidate sensors were used in the first phase of the testing. The second phase of testing used four sensors simultaneously: two Marshall Space Flight Center (MSFC) Advanced Video Guidance Sensors (AVGS), a laser-based video sensor that uses retroreflectors attached to the target vehicle, and two commercial laser range finders. The multi-sensor testing was conducted at MSFC's Flight Robotics Laboratory (FRL) using the FRL's 6-DOF gantry system, called the Dynamic Overhead Target System (DOTS). The target vehicle for "docking" in the laboratory was a mockup that was representative of the proposed CEV docking system, with added retroreflectors for the AVGS. The multi-sensor test configuration used 35 open-loop test trajectories covering three major objectives: (1) sensor characterization trajectories designed to test a wide range of performance parameters; (2) CEV-specific trajectories designed to test performance during CEV-like approach and departure profiles; and (3) sensor characterization tests designed for evaluating sensor performance under more extreme conditions as might be induced during a spacecraft failure or during contingency situations. This paper describes the test development, test facility, test preparations, test execution, and test results of the multi-sensor series of trajectories.

Brewster, L.↗

Multi-Sensor Testing for Automated Rendezvous and Docking Sensor Testing at the Flight Robotics Lab

The Exploration Systems Architecture defines missions that require rendezvous, proximity operations, and docking (RPOD) of two spacecraft both in Low Earth Orbit (LEO) and in Low Lunar Orbit (LLO). Uncrewed spacecraft must perform automated and/or autonomous rendezvous, proximity operations and docking operations (commonly known as AR&D). The crewed missions may also perform rendezvous and docking operations and may require different levels of automation and/or autonomy, and must provide the crew with relative navigation information for manual piloting. The capabilities of the RPOD sensors are critical to the success ofthe Exploration Program. NASA has the responsibility to determine whether the Crew Exploration Vehicle (CEV) contractor-proposed relative navigation sensor suite will meet the requirements. The relatively low technology readiness level of AR&D relative navigation sensors has been carried as one of the CEV Project's top risks. The AR&D Sensor Technology Project seeks to reduce the risk by the testing and analysis of selected relative navigation sensor technologies through hardware-in-the-Ioop testing and simulation. These activities will provide the CEV Project information to assess the relative navigation sensors maturity as well as demonstrate test methods and capabilities. The first year of this project focused on a series of "pathfinder" testing tasks to develop the test plans, test facility requirements, trajectories, math model architecture, simulation platform, and processes that will be used to evaluate the Contractor-proposed sensors. Four candidate sensors were used in the first phase of the testing. The second phase of testing used four sensors simultaneously: two Marshall Space Flight Center (MSFC) Advanced Video Guidance Sensors (AVGS), a laser-based video sensor that uses retroreflectors attached to the target vehicle, and two commercial laser range finders. The multi-sensor testing was conducted at MSFC's Flight Robotics Laboratory (FRL) using the FRL's 6-DOF gantry system, called the Dynamic Overhead Target System (DOTS). The target vehicle for "docking" in the laboratory was a mockup that was representative of the proposed CEV docking system, with added retroreflectors for the AVGS.' The multi-sensor test configuration used 35 open-loop test trajectories covering three major objectives: (l) sensor characterization trajectories designed to test a wide range of performance parameters; (2) CEV-specific trajectories designed to test performance during CEV-like approach and departure profiles; and (3) sensor characterization tests designed for evaluating sensor performance under more extreme conditions as might be induced during a spacecraft failure or during contingency situations. This paper describes the test development, test facility, test preparations, test execution, and test results of the multisensor series oftrajectories

Brewster, Linda L.↗

Natural Variability Has Concealed Increases in Western US Flood Hazard Since the 1970s

Flood hazard across the western United States (US) has generally shown decreasing trends in recent decades. This region's extreme streamflow is highly influenced by natural variability, which could either mask or amplify anthropogenic streamflow trends. Here, in this study, we utilize a technique known as dynamical adjustment to assess historical (1970–2020) annual maximum 1-day streamflow (Qx1d) from unregulated basins across the western US with and without the impact of natural variability. After removing natural variability, the fraction of basins with a positive (>5%) trend in Qx1d shifts from 25% to 53%. Basins with increasing (decreasing) Qx1d trends after dynamical adjustment exhibit weak (strong) drying, and furthermore are associated with intensifying precipitation extremes and/or large decreases in snowpack. Increasing flood hazard will likely emerge for such basins as the current phase of natural decadal variability shifts, and anthropogenic signals continue to intensify.

54 ENVIRONMENTAL SCIENCES↗

Electrical Fault Detection, Power Quality, Distributed Energy Resource Use Cases, and Cyber Event Applications with the Cyber Grid Guard System Using Distributed Ledger Technology

Electrical utilities continue to deploy more intelligent electronic devices (IEDs) inside and outside electrical substation and are associated with distributed energy resources (DERs). The integrity and confidentiality of data from IEDs is crucial, and distributed ledger technology (DLT) could improve the resilience of microgrids by helping to make these data more secure. The most popular applications using blockchain technology for electrical utilities is in the field is based on energy trading. However, the dynamism of the penetration of customer owned DERs and the deployment of sensors with IEDs have led to the identification of new applications using DLT that are focused on other areas, such as monitoring, operation and management of the grid and its assets. In addition, the majority of studies on electrical grid applications with blockchain were validated with software simulations. Although general monitoring of power systems for using DLT could be evaluated in operational electric grids, other DLT research applications such as defense against cyber-attacks and/or electrical fault detection are not likely to be performed in a real infrastructure because of possible risks to the network/equipment security. This report summarizes the application of power system applications using distributed ledger technology (DLT), providing a secure DLT framework for collecting data from IEDs like power meters and protective relays inside and outside of an electrical substation and/or between two different electrical utilities. In this study, the use case scenarios were created and assessed for different power system application by using DLT. The electrical fault detection for faulted phases (1), power quality monitoring of phase voltage magnitudes, frequency levels and load power factor (2), DERs use case monitoring (3), and cyber-event applications (4) were performed in a test bed with a Cyber-Grid Guard (CGG) system using DLT. It had a real-time simulator with power meters and protective relays in-the-loop. The first section of this report presents a literature review of power system applications using blockchain at research level. The second section shows the theory and equations used on this report. The third section shows the description of the test bed, equipment, architecture, and electrical grid diagrams. The fourth section shows the experimental models and use case scenarios that were performed for the electrical fault detection, power quality, DERs use case, and cyber event applications with the CGG system using DLT. The fifth section shows the results collected from the tests based on comparing the time stamped events of the analog signals from the IEDs, DLT computer and real time simulator. The sixth section performed the discussion of the results for the use case scenarios. Finally, section seven presents the conclusions for this report were presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Ablation and Heating During Atmospheric Entry and Its Effect on Airburst Risk

Large meteoroids and asteroids entering the atmosphere endure tremendous heating from the shock heated air, and thereby lose a significant fraction of their mass during atmospheric entry a process known as ablation. The predicted evolution of the asteroids mass as it passes through the atmosphere can affect both the predicted energy deposition profile relevant to an airburst event, or the residual mass that strikes the ground in the case of an impact event. This presentation is divided roughly into two parts. In the first part, an overview of traditional models for heat transfer and ablation that are historically used in the meteor physics community is presented, and the validity in the asteroid entry regime discussed. Sensitivity analyses performed using the recently developed Fragment-Cloud Model (FCM) will be presented which show illustrate the range of sizes and entry parameters for which the predicted asteroid threat is most sensitive to the models for ablation and heat transfer. The second part of the presentation shall focus on recent work done under NASAs Asteroid Threat Assessment Project (ATAP) to develop new models for heat transfer and ablation using high-fidelity numerical simulation in concert with state-of-the-art experiments. Coupled computational fluid dynamics (CFD)radiation transport simulations preformed using the state-of-the-art entry modeling tools at NASA show that, for large meteoroids and asteroids, there can significant attenuation of the heat transfer to the surface (95 in some cases) by the products of ablation. In addition to the heat transfer, new models for the material response and ablation of asteroidal material have been developed [cite]. In the current work, we present finding from recent novel experiments performed in the arc jet facility at NASA Ames, which allows us to, in part, simulate the extreme environment experienced by the asteroid during entry. Briefly, the experimental set-up was comprised of a 1.5 conical article of machined H5 chondrite, which was exposed to a high-enthalpy flow resulting in approximately 4 kWcm2 of heating to the surface. A still frame capture from high-speed video taken during this experiment can be seen in Figure 1. In this figure, we can observe some of the major mechanisms for meteoroid ablation, such as melt flow, spallation (mechanical removal of material), and vaporization. Major findings from this, and other experiments will be discussed, as well progress on utilizing the data from the experiments to inform and develop improved models for ablation.

Asteroids↗

Guidance Enhancements and Performance Assessments for the Mars Ascent Vehicle Spin-Stabilized Upper Stage Configuration

he objective of the Mars Sample Return (MSR) campaign is to return samples from the surface of Mars to Earth for research. As one element of the MSR campaign, the Mars Ascent Vehicle (MAV) is responsible for transporting the samples from the surface of Mars to a Low-Martian Orbit (LMO) for retrieval. Complete autonomy is required throughout ascent, and orbital insertion is constrained by tight dispersion boundaries. An unguided, spin-stabilized second stage for MAV has been selected over a guided upper-stage to drive mass savings and reduce overall MSR campaign mass risk, at the cost of reduced GNC capability. To address this design change, the MAV GNC team has derived a robust prediction algorithm, building on previous energy management schemes, that solves for a single inertial pointing direction solution for the spin-stabilized 2nd stage burn. Algorithm stability is explored that compared to previous versions of the algorithm. Also, a set of analytical partials was developed to study MAV’s dispersed orbital insertion performance with respect to MAV system uncertainties. These partials were verified through simulation analysis and prove useful for analytical insight into the dynamics of MAV during the 2nd stage maneuver.

Jason M Everett↗

Guidance Enhancements and Performance Assessments for the Mars Ascent Vehicle Spin-Stabilized Upper Stage Configuration

The objective of the Mars Sample Return (MSR) campaign is to return samples from the surface of Mars to Earth for research. As one element of the MSR campaign, the Mars Ascent Vehicle (MAV) is responsible for transporting the samples from the surface of Mars to a Low-Martian Orbit (LMO) for retrieval. Complete autonomy is required throughout ascent, and orbital insertion is constrained by tight dispersion boundaries. An unguided, spin-stabilized second stage for MAV has been selected over a guided upper-stage to drive mass savings and reduce overall MSR campaign mass risk, at the cost of reduced GNC capability. To address this design change, the MAV GNC team has derived a robust prediction algorithm, building on previous energy management schemes, that solves for a single inertial pointing direction solution for the spin-stabilized 2nd stage burn. Algorithm stability is explored that compared to previous versions of the algorithm. Also, a set of analytical partials was developed to study MAV’s dispersed orbital insertion performance with respect to MAV system uncertainties. These partials were verified through simulation analysis and prove useful for analytical insight into the dynamics of MAV during the 2nd stage maneuver.

GNC↗

Modeling Flight: The Role of Dynamically Scaled Free-Flight Models in Support of NASA's Aerospace Programs

The state of the art in aeronautical engineering has been continually accelerated by the development of advanced analysis and design tools. Used in the early design stages for aircraft and spacecraft, these methods have provided a fundamental understanding of physical phenomena and enabled designers to predict and analyze critical characteristics of new vehicles, including the capability to control or modify unsatisfactory behavior. For example, the relatively recent emergence and routine use of extremely powerful digital computer hardware and software has had a major impact on design capabilities and procedures. Sophisticated new airflow measurement and visualization systems permit the analyst to conduct micro- and macro-studies of properties within flow fields on and off the surfaces of models in advanced wind tunnels. Trade studies of the most efficient geometrical shapes for aircraft can be conducted with blazing speed within a broad scope of integrated technical disciplines, and the use of sophisticated piloted simulators in the vehicle development process permits the most important segment of operations the human pilot to make early assessments of the acceptability of the vehicle for its intended mission. Knowledgeable applications of these tools of the trade dramatically reduce risk and redesign, and increase the marketability and safety of new aerospace vehicles. Arguably, one of the more viable and valuable design tools since the advent of flight has been testing of subscale models. As used herein, the term "model" refers to a physical article used in experimental analyses of a larger full-scale vehicle. The reader is probably aware that many other forms of mathematical and computer-based models are also used in aerospace design; however, such topics are beyond the intended scope of this document. Model aircraft have always been a source of fascination, inspiration, and recreation for humans since the earliest days of flight. Within the scientific community, Leonardo da Vinci, George Cayley, and the Wright brothers are examples of early aviation pioneers who frequently used models during their scientific efforts to understand and develop flying machines. Progress in the technology associated with model testing in worldwide applications has firmly established model aircraft as a key element in new aerospace research and development programs. Models are now routinely used in many applications and roles, including aerodynamic data gathering in wind tunnel investigations for the analysis of full-scale aircraft designs, proof-of-concept demonstrators for radical aeronautical concepts, and problem-solving exercises for vehicles already in production. The most critical contributions of aerospace models are to provide confidence and risk reduction for new designs and to enhance the safety and efficiency of existing configurations.

Chambers, Joseph↗

Dynamic Modeling and Soil Mechanics for Path Planning of the Mars Exploration Rovers

To help minimize risk of high sinkage and slippage during drives and to better understand soil properties and rover terramechanics from drive data, a multidisciplinary team was formed under the Mars Exploration Rover (MER) project to develop and utilize dynamic computer-based models for rover drives over realistic terrains. The resulting tool, named ARTEMIS (Adams-based Rover Terramechanics and Mobility Interaction Simulator), consists of the dynamic model, a library of terramechanics subroutines, and the high-resolution digital elevation maps of the Mars surface. A 200-element model of the rovers was developed and validated for drop tests before launch, using MSC-Adams dynamic modeling software. Newly modeled terrain-rover interactions include the rut-formation effect of deformable soils, using the classical Bekker-Wong implementation of compaction resistances and bull-dozing effects. The paper presents the details and implementation of the model with two case studies based on actual MER telemetry data. In its final form, ARTEMIS will be used in a predictive manner to assess terrain navigability and will become part of the overall effort in path planning and navigation for both Martian and lunar rovers.

terramechanics↗

Pre-Launch GOES-R Risk Reduction Activities for the Geostationary Lightning Mapper

The GOES-R Geostationary Lightning Mapper (GLM) is a new instrument planned for GOES-R that will greatly improve storm hazard nowcasting and increase warning lead time day and night. Daytime detection of lightning is a particularly significant technological advance given the fact that the solar illuminated cloud-top signal can exceed the intensity of the lightning signal by a factor of one hundred. Our approach is detailed across three broad themes which include: Data Processing Algorithm Readiness, Forecast Applications, and Radiance Data Mining. These themes address how the data will be processed and distributed, and the algorithms and models for developing, producing, and using the data products. These pre-launch risk reduction activities will accelerate the operational and research use of the GLM data once GOES-R begins on-orbit operations. The GLM will provide unprecedented capabilities for tracking thunderstorms and earlier warning of impending severe and hazardous weather threats. By providing direct information on lightning initiation, propagation, extent, and rate, the GLM will also capture the updraft dynamics and life cycle of convective storms, as well as internal ice precipitation processes. The GLM provides information directly from the heart of the thunderstorm as opposed to cloud-top only. Nowcasting applications enabled by the GLM data will expedite the warning and response time of emergency management systems, improve the dispatch of electric power utility repair crews, and improve airline routing around thunderstorms thereby improving safety and efficiency, saving fuel and reducing delays. The use of GLM data will assist the Bureau of Land Management (BLM) and the Forest Service in quickly detecting lightning ground strikes that have a high probability of causing fires. Finally, GLM data will help assess the role of thunderstorms and deep convection in global climate, and will improve regional air quality and global chemistry/climate modeling. The GLM has a robust design that benefits and improves upon its strong heritage of NASA-developed LEO predecessors, the Optical Transient Detector (OTD) and the Lightning Imaging Sensor (LIS). GLM will have a substantially larger number of pixels within the focal plane, two lens systems, and multiple Real-Time Event Processors REPS for on-board event detection and data compression to provide continuous observations of the Americas and adjacent oceans.

Goodman, S. J.↗

NPP Clouds and the Earth's Radiant Energy System (CERES) Predicted Sensor Performance Calibration and Preliminary Data Product Performance

Continuation of the Earth Radiation Budget (ERB) Climate Data Record (CDR) has been identified as critical in the 2007 NRC Decadal Survey, the Global Climate Observing System WCRP report, and in an assessment titled Impacts of NPOESS Nunn-McCurdy Certification on Joint NASA-NOAA Climate Goals. In response, NASA, NOAA and NPOESS agreed in early 2008 to fly the final existing CERES Flight Model (FM-5) on the NPP spacecraft for launch in 2010. Future opportunities for ERB CDR continuity consist of procuring an additional CERES Sensor with modest performance upgrades for flight on the NPOESS C1 spacecraft in 2013, followed by a new CERES follow-on sensor for flight in 2018 on the NPOESS C3 spacecraft. While science goals remain unchanged for the long-term ERB Climate Data Record, it is now understood that the task of achieving these goals is more difficult for two reasons. The first is an increased understanding of the dynamics of the Earth/atmosphere system which demonstrates that rigorous separation of natural variability from anthropogenic change on decadal time scales requires higher accuracy and stability than originally envisioned. Secondly, future implementation scenarios involve less redundancy in flight hardware (1 vs. 2 orbits and operational sensors) resulting in higher risk of loss of continuity and reduced number of independent observations to characterize performance of individual sensors. Although EOS CERES CDR's realize a factor of 2 to 4 improvement in accuracy and stability over previous ERBE CDR's, future sensors will require an additional factor of 2 improvement to answer rigorously the science questions moving forward. Modest investments, defined through the CERES Science Team s 30-year operational history of the EOS CERES sensors, in onboard calibration hardware and pre-flight calibration and test program will ensure meeting these goals while reducing costs in re-processing scientific datasets. The CERES FM-5 pre-flight radiometric characterization program benefited from the 30-year operational experience of the CERES EOS sensors, as well as a stronger emphasis of radiometric characterization in the Statement of Work with the sensor provider. Improvements to the pre-flight program included increased spectral, spatial, and temporal sampling under vacuum conditions as well as additional tests to characterize the primary and transfer standards in the calibration facility. Future work will include collaboration with NIST to further enhance the understanding of the radiometric performance of this equipment prior to flight. The current effort summarizes these improvements to the CERES FM-5 pre-flight sensor characterization program, as well as modifications to inflight calibration procedures and operational tasking. In addition, an estimate of the impacts to the system level accuracy and traceability is presented.

Priestly, Kory↗

Simulation-based characterization of the variability of earthquake risk to buildings in the near-field

Recent advancements in high performance computing platforms and computational workflow for regional-scale simulations are enabling unprecedented modeling of fault-to-structure earthquake processes. Regional simulations resolving ground motions at frequencies relevant to engineered systems are becoming computationally viable and provide a new capability to improve understanding of the geographical distribution and intensity of risk to buildings and critical infrastructure. As computational capabilities advance, it is essential to move beyond illustrative single rupture realizations for scenario earthquake events towards the development of a full suite of rupture realizations that appropriately characterize the range of risk to building systems. The work described in this article investigates the application of a suite of fault rupture realizations with the objective of assessing near-fault, site-specific seismic demand variability for building structures. A representative high-performance regional-scale computational model is utilized to execute ground motion and building response simulations based on 18 kinematic rupture realizations of an M7 strike-slip scenario earthquake. The fault rupture models for the scenario earthquake are created by systematically perturbing the hypocenter location and stochastically generating rupture parameters (slip, rise time, rake angle) to represent a breadth of ground motion intensities resulting from the spatial and temporal variabilities of an earthquake rupture process. The resulting seismic demand variability for three-story (short period) and forty-story (long period) steel moment-resisting frame buildings is characterized in terms of the median and distribution of peak inter-story drift ratio for a range of near-fault sites. The full suite of 18 fault rupture realizations and approximately 280,000 nonlinear dynamic building simulations indicate that the three-story building undergoes higher median seismic demand and significantly greater variability of demand at a given site than the forty-story building, which has important implications for the level of certainty in predicting building performance during an earthquake. The simulations performed provide deeper insight into the relationship between fault rupture parameterization and building response, which is essential information for developing a representative suite of rupture realizations for specific earthquake scenarios.

58 GEOSCIENCES↗

Understanding the Effects of Long-duration Space Flight on Astronant Functional Task Performance

Space flight is known to cause alterations in multiple physiological systems including changes in sensorimotor, cardiovascular, and neuromuscular systems. These physiological changes cause balance, gait and visual disturbances, cardiovascular deconditioning, and loss of muscle mass and strength. These changes may affect a crewmember's ability to perform critical mission tasks immediately after landing on a planetary surface. To understand how changes in physiological function affect functional performance, an interdisciplinary pre- and postflight testing regimen, Functional Task Test (FTT), was developed to systematically evaluate both astronaut functional performance and related physiological changes. Ultimately this information will be used to assess performance risks and inform the design of countermeasures for exploration class missions. We are currently conducting the FTT study on International Space Station (ISS) crewmembers before and after 6-month expeditions. Additionally, in a corresponding study we are using the FTT protocol on subjects before and after 70 days of 6deg head-down bed-rest as an analog for space flight. Bed-rest provides the opportunity for us to investigate the role of prolonged axial body unloading in isolation from the other physiological effects produced by exposure to the microgravity environment of space flight. Therefore, the bed rest analog allows us to investigate the impact of body unloading on both functional tasks and on the underlying physiological factors that lead to decrement in performance and then compare them with the results obtained in our space flight study. Functional tests included ladder climbing, hatch opening, jump down, manual manipulation of objects and tool use, seat egress and obstacle avoidance, recovery from a fall and object translation tasks. Physiological measures included assessments of postural and gait control, dynamic visual acuity, fine motor control, plasma volume, heart rate, blood pressure, orthostatic intolerance, upper- and lower-body muscle strength, power, endurance, control, and neuromuscular drive. ISS crewmembers were tested three times before flight, and on 1, 6, and 30 days after landing. Bed-rest subjects were tested three times before bed-rest and immediately after getting up from bed-rest as well as 1, 6, and 12 days after reambulation.

Bloomberg, Jacob J.↗

EXERGETIC: De-Risking Next-Generation Resilient Geothermal Hybrids via At-Scale Evaluation Using Virtual Emulation Digital Twin Environment for Efficient Operation

The DOE-GTO-funded project, award number 5.1.2.12, entitled "EXERGETIC - De-risking Next Generation Resilient Geothermal Hybrids via at-Scale Evaluation Using a Virtual Emulation Digital Twin Environment for Efficient Operation," advances the solution to these challenges by developing and validating a geothermal co-emulation environment implemented at the National Laboratory of the Rockies (NLR)'s Advanced Research on Integrated Energy Systems (ARIES) platform. This framework enables the de-risking of next-generation geothermal and geothermal hybrid systems through high-fidelity modeling, real-time digital emulation, advanced control strategies, and techno-economic assessment. The project focused on geothermal hybrid configurations that integrate geothermal power plants with concentrated solar power and underground thermal energy storage, enabling enhanced efficiency, flexibility, and grid support capabilities. The main goal of this project was the development of a geothermal digital co-emulation environment to demonstrate the technical and economic value of geothermal hybrid systems and their contribution to grid stability and flexibility. The EXERGETIC framework combined physics-based models, controls, and real assets at ARIES, including digital real-time simulators (DRTS), a 20-MW-scale controllable grid interface (CGI), and a 2-MW conventional generator. Detailed transient models were developed for the key subsystems of a hybrid geothermal plant, including parabolic trough solar collectors, reservoir thermal energy storage (RTES), and a binary Organic Rankine Cycle (ORC) power plant. The ORC model explicitly captured thermal inertia and off-design operation and integrated control strategies to dynamically respond to electric load profiles. The models were validated against published experimental and numerical studies, demonstrating strong agreement and confirming the accuracy and robustness of the modeling approach. The resulting digital twin represents geothermal-solar-storage systems at multiple scales (1 MW to 100 MW) and enables realistic emulation of grid-connected operation. The control architecture allows the geothermal resource to provide stable baseload generation, while solar and stored thermal energy supply flexible, dispatchable support during periods of high demand or variable grid conditions. A key contribution of the EXERGETIC project is the demonstration that geothermal hybrid systems can be designed to be active grid assets rather than passive baseload generators. Using the ARIES platform, the digital twin was evaluated under multiple grid scenarios, including load following, voltage support at the distribution level, and frequency response at the transmission level. Results show that hybrid geothermal systems can respond effectively to dynamic grid conditions, providing inertia-like behavior, primary frequency support, and voltage regulation through coordinated control. In addition to the performance and grid services capability analysis of geothermal and hybrid geothermal systems, the EXERGETIC project also focused on scalability and techno-economic analysis of geothermal hybrid plants. In particular, for the scalability analysis, machine-learning (ML)-based surrogate models were trained using data generated from the geothermal digital twin under different grid-connected scenarios and plant capacities. These ML models demonstrated strong interpolation and extrapolation capabilities across plant sizes, accurately reproducing both steady-state and transient responses with very low errors. Regarding the techno-economic analysis, plant performance results were integrated with cost models for hybrid geothermal systems, and the levelized cost of electricity (LCOE) was used as the main economic metric to evaluate system performance across a range of system capacities, solar shares, solar multiples, and storage durations. Results indicate that economies of scale significantly reduce geothermal LCOE as plant capacity increases, with large-scale systems (25-100 MW) achieving substantially lower costs than small plants. Hybridization with solar thermal energy and storage further improves economic performance by increasing capacity utilization and enabling flexible dispatch. In addition, thermal storage plays a critical role in reducing LCOE by maximizing geothermal, solar, and stored energy resources. In summary, the results from this project demonstrate that geothermal hybrid systems represent a promising alternative for increasing the energy conversion efficiency of geothermal technologies, contributing to the preservation of geothermal resources, and supporting the transition of geothermal plants from traditional baseload resources into flexible, resilient, and cost-competitive energy conversion technologies.

15 GEOTHERMAL ENERGY↗

Numerical modeling of hydrogen mixing in a direct-injection engine fueled with gaseous hydrogen

Hydrogen is considered as one of the most promising options to achieve effective decarbonization of the energy and transportation sectors. As such, it has recently been receiving increasing attention because of its promising potential as an energy carrier for advanced energy and propulsion systems. With a focus on internal combustion engines, direct injection (DI) of gaseous hydrogen during the compression stroke offers great potential for high engine efficiency and specific power while reducing the risk of backfiring and pre-ignition issues. Therefore, many experimental and numerical efforts have recently been dedicated to understanding the physical and chemical behaviors of hydrogen in engine during mixing and combustion. This study focuses on computational fluid dynamics (CFD) modeling of the hydrogen DI process in a hydrogen optical research engine. Under the conditions studied, gaseous hydrogen is injected into the combustion chamber via a centrally located single-hole injector at a pressure of 100 bar. Two configurations, namely low-and high-tumble, are investigated to understand the impact of different in-cylinder flow patterns on the fuel-air mixture preparation. Simulations are carried out using the commercial CFD software CONVERGE. Here, the in-cylinder turbulence is modeled with an unsteady Reynolds-averaged Navier-Stokes (URANS) formulation closed by the renormalization group (RNG) k-ε model. Several numerical methods and model constants, including but not limited to turbulent Schmidt number, are evaluated. The numerical results are systematically compared against experimental measurements of velocity and hydrogen concentration fields on the vertical center plane to assess the performance of the CFD model, unveil the physics of hydrogen mixing, and establish best practices for modeling hydrogen DI under relatively high injection pressure conditions.

33 ADVANCED PROPULSION SYSTEMS↗

Wildfire Risk Evaluation Framework for Grid Operations and Planning

The United States (US) environmental protection agency's (EPA's) climate change indicators for wildfires show a long-term trend of increased annual wildfire activity, larger wildfire size, and more variable dynamics in wildfire behavior. This has caused more frequent preemptive public safety power shutoff (PSPS) events in the regions with recognized high wildfire risk. These preemptive power shutoffs attempt to prevent the ignition of a wildfire but it nonetheless renders the transmission line non-operational, which often sheds load of downstream communities. As wildfires and PSPS events become more frequent, it is crucial to find the communities most at risk of load shedding. To that end, this paper proposes the wildfire risk evaluation of the system (WiRES) framework, which is a performance-based framework that translates extreme weather-related and PSPS event probabilities into a cumulative probability of a non-operational transmission line. This study also provides a geospatial visualization tool that breaks down the entire western electrical coordinating council (WECC) region into 50 km grid cells which can be used to 1) filter out transmission lines with higher than a threshold outage probability, and 2) graphically discover the affected regions and their biophysical and socioeconomic metrics. %such as the social vulnerability index, population density, gross domestic product, etc. Lastly, an impact assessment study is conducted which connects the results of the proposed framework to python and powerworld-based contingency analysis to highlight the applicability of the framework.

Wildfire, Resilience, Extreme Events, Grid Reslien↗

Tunable White Light for Elders (TWLITE): A Protocol Demonstrating Feasibility and Acceptability for Deployment, Remote Data Collection, and Analysis of a Home-Based Lighting Intervention in Older Adults

Sleep disturbances are common in older adults and may contribute to disease progression in certain populations (e.g., Alzheimer’s disease). Light therapy is a simple and cost-effective intervention to improve sleep. Primary barriers to light therapy are: (1) poor acceptability of the use of devices, and (2) inflexibility of current devices to deliver beyond a fixed light spectrum and throughout the entirety of the day. However, dynamic, tunable lighting integrated into the native home lighting system can potentially overcome these limitations. Herein, we describe our protocol to implement a whole-home tunable lighting system installed throughout the homes of healthy older adults already enrolled in an existing study with embedded home assessment platforms (Oregon Center for Aging & Technology—ORCATECH). Within ORCATECH, continuous data on room location, activity, sleep, and general health parameters are collected at a minute-to-minute resolution over years of participation. This single-arm longitudinal protocol collected participants’ light usage in addition to ORCATECH outcome measures over a several month period before and after light installation. The protocol was implemented with four subjects living in three ORCATECH homes. Technical/usability challenges and feasibility/acceptability outcomes were explored. The successful implementation of our protocol supports the feasibility of implementing and integrating tunable whole-home lighting systems into an automated home-based assessment platform for continuous data collection of outcome variables, including long-term sleep measures. Challenges and iterative approaches are discussed. This protocol will inform the implementation of future clinical intervention trials using light therapy in patients at risk for developing Alzheimer’s disease and related conditions.

60 APPLIED LIFE SCIENCES↗