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These slides presents an overview of SMART NAS Test Bed. The test bed is envisioned to be connected to operational systems and to allow a new concept and technology to be evaluated in its realistic environment. Its role as an accelerator of concepts and technologies development, its use cases and use-case-driven development approach, and its state are presented.
There is growing recognition that Demand Flexibility (DF) can play a major role in enhancing grid reliability, with building control applications emerging as key enablers for DF. However, the traditional approach to deploying new control applications in buildings, including those for DF, remains largely manual and tailored to individual buildings, making it difficult to scale. While research efforts have explored semantics-driven portability, DF controls specification, and assessment approaches, these initiatives are fragmented and limited in scope. This paper proposes a novel methodology, grounded in design science research, to integrate these elements and create a comprehensive DF controls library for both industry and academia. This approach is applied to develop the Demand FLEXibility controls LIBrary using Semantics (DFLEXLIBS), an extensible open-source library that provides DF controls for HVAC systems in Python. DFLEXLIBS enables portable, easy-to-deploy controls that abstract building-specific data points, facilitating assessment across diverse buildings. DFLEXLIBS features nine different control applications, and it is successfully implemented and tested across four virtual and two real buildings, bridging the gap between semantics-driven portability, DF controls specification, and rigorous performance assessment. Its benefits are measured by a reusability ratio greater than 90% and a functional overlap ratio of around 70% for the most common functions used in the library, significantly reducing time for deploying new controls.
Systems for very long-duration human missions to Mars will be designed to operate reliably for many years and many of these systems will never be returned to Earth. The need for high reliability is driven by the requirement for safe functioning of remote, long-duration crewed systems and also by unsympathetic abort scenarios. Abort from a Mars mission could be as long as 450 days to return to Earth. The key to developing a human-in-the-loop architecture is a development process that allows for a logical sequence of validating successful development in a stepwise manner, with assessment of key performance parameters (KPPs) at each step; especially important are KPPs for technologies evaluated in a full systems context with human crews on Earth and on space platforms such as the ISS. This presentation will explore the implications of such an approach to technology development and validation including the roles of ground and space-based testing necessary to develop a highly reliable system for long duration human exploration missions. Historical development and systems testing from Mercury to the International Space Station (ISS) to ground testing will be reviewed. Current work as well as recommendations for future work will be described.
Abstract Ultra‐relativistic electrons with energies greater than or equal to two megaelectron‐volt (MeV) pose a major radiation threat to spaceborne electronics, and thus specifying those highly energetic electrons has a significant meaning to space weather communities. Here we report the latest progress in developing our predictive model for MeV electrons in the outer radiation belt. The new version, primarily driven by electron measurements made along medium‐Earth‐orbits (MEO), is called PREdictive MEV Electron (PreMevE)‐MEO model that nowcasts ultra‐relativistic electron flux distributions across the whole outer belt. Model inputs include >2 MeV electron fluxes observed in MEOs by a fleet of GPS satellites as well as electrons measured by one Los Alamos satellite in the geosynchronous orbit. We developed an innovative Sparse Multi‐Inputs Latent Ensemble NETwork (SmileNet) which combines convolutional neural networks with transformers, and we used long‐term in situ electron data from NASA's Van Allen Probes mission to train, validate, optimize, and test the model. It is shown that PreMevE‐MEO can provide hourly nowcasts with high model performance efficiency and high correlation with observations. This prototype PreMevE‐MEO model demonstrates the feasibility of making high‐fidelity predictions driven by observations from longstanding space infrastructure in MEO, thus has great potential of growing into an invaluable space weather operational warning tool.
Thermomagnetic generators offer a promising approach for sustainable power generation in remote marine environments. Here, this study presents the design, thermal modeling, and experimental validation of a passively driven underwater thermomagnetic generator developed for powering ocean observation and monitoring sensors. The generator was evaluated under varying working fluids, thermal boundary conditions, and extended operation to assess real-world applicability. Two fluids, deionized water and silicone-based Thermal C5, were tested under simulated shallow- and deep-ocean conditions. Deionized water outperformed Thermal C5, especially in colder environments (~5°C), achieving a peak output of 2.7 mW due to larger temperature gradients and enhanced convective-evaporative heat transfer. Long-duration tests revealed a transient evaporation-condensation cycle that temporarily reduced rotor immersion and performance before stabilizing. The generator powered commercial marine sensors for over 6 h without external batteries, demonstrating the viability of compact, passively cooled thermomagnetic systems for autonomous, off-grid marine sensing.
The NASA Next Space Technologies for Exploration Partnerships (NextSTEP) program is a public-private partnership model that seeks commercial development of deep space exploration capabilities to support extensive human spaceflight missions around and beyond cislunar space. NASA first issued the Phase 1 NextSTEP Broad Agency Announcement to U.S. industries in 2014, which called for innovative cislunar habitation concepts that leveraged commercialization plans for low Earth orbit. These habitats will be part of the Deep Space Gateway (DSG), the cislunar space station planned by NASA for construction in the 2020s. In 2016, Phase 2 of the NextSTEP program selected five commercial partners to develop ground prototypes. A team of NASA research engineers and subject matter experts have been tasked with developing the ground test protocol that will serve as the primary means by which these Phase 2 prototype habitats will be evaluated. Since 2008, this core test team has successfully conducted multiple spaceflight analog mission evaluations utilizing a consistent set of operational products, tools, methods, and metrics to enable the iterative development, testing, analysis, and validation of evolving exploration architectures, operations concepts, and vehicle designs. The purpose of implementing a similar evaluation process for the NextSTEP Phase 2 Habitation Concepts is to consistently evaluate the different commercial partner ground prototypes to provide data-driven, actionable recommendations for Phase 3.
This report describes a generic method for addressing any new technology to its associated set of regulations and certification criteria. The result is a framework under which a detailed assessment can be conducted. Using just such a framework, the report maps the detailed updated regulations and evolving ASTM standards to the particular technology planning and tests. As a result, a roadmap of NASA technology is documented that shows clear transfer of technology data to industry (standards developers, as well as technology developers) and the FAA regulatory policy and certification staff upon whom certification and policy will be data-driven. A clear description of benefits and gaps are identified, as well.
The Green Propellant Infusion Mission (GPIM) is a project in the NASA Technology Demonstration Missions (TDM) that will perform a spaceflight demonstration of an AF-M315E propulsion system. The mission is led by Ball Aerospace & Technologies Corporation, with participation across industry and government. The spacecraft is based on the Ball BCP-100 bus, with an Aerojet propulsion system. NASA GSFC provides system testing and analysis of the flow within the AF-M315E propulsion system. A facility was developed at the NASA GSFC propulsion test site to safely use and test the AF-M315E propellant. Testing was performed on multiple 1 N and 22 N non-flight thruster valves provided by Aerojet. A mock-up of the flight system was driven at multiple pressures and temperatures to approximate different flight conditions. Testing was conducted to observe how AF-M315E behaves in fight-like conditions due to the propellant's mass properties heavy dependence on changes in temperature. The testing consisted of driving the different thruster valves at a set on-time and off-time for all and varying the driving pressure from 125 psig to 410 psig. Individual pulses were measured and analyzed for each valve to compare the various rise times and fall times of each thruster valve. The rise times and fall times were then analyzed for thruster valves by measuring the differential pressure from directly upstream and downstream of the valve. The rise times and fall times were also analyzed by measuring the amperage trace of the thruster valve measured with an oscilloscope. The pressure and amperage rise and fall times were compared collectively and individually for the various thruster valves. These results were compared to the fall time data provided by Aerojet.
Abstract Neural networks (NNs) are increasingly used for data‐driven subgrid‐scale parameterizations in weather and climate models. While NNs are powerful tools for learning complex non‐linear relationships from data, there are several challenges in using them for parameterizations. Three of these challenges are (a) data imbalance related to learning rare, often large‐amplitude, samples; (b) uncertainty quantification (UQ) of the predictions to provide an accuracy indicator; and (c) generalization to other climates, for example, those with different radiative forcings. Here, we examine the performance of methods for addressing these challenges using NN‐based emulators of the Whole Atmosphere Community Climate Model (WACCM) physics‐based gravity wave (GW) parameterizations as a test case. WACCM has complex, state‐of‐the‐art parameterizations for orography‐, convection‐, and front‐driven GWs. Convection‐ and orography‐driven GWs have significant data imbalance due to the absence of convection or orography in most grid points. We address data imbalance using resampling and/or weighted loss functions, enabling the successful emulation of parameterizations for all three sources. We demonstrate that three UQ methods (Bayesian NNs, variational auto‐encoders, and dropouts) provide ensemble spreads that correspond to accuracy during testing, offering criteria for identifying when an NN gives inaccurate predictions. Finally, we show that the accuracy of these NNs decreases for a warmer climate (4 × CO 2 ). However, their performance is significantly improved by applying transfer learning, for example, re‐training only one layer using ∼1% new data from the warmer climate. The findings of this study offer insights for developing reliable and generalizable data‐driven parameterizations for various processes, including (but not limited to) GWs.
The purpose of this Cooperative Research and Development Agreement (CRADA) between UT-Battelle, LLC (the “Contractor) and Procter & Gamble Company (the “Participant”) is the development of a research partnership to create new tools, tests and analytical methods to improve the performance, safety and/or environmental quality of chemicals, advanced materials, food products and manufacturing processes. The Participant operates in three global business units: Beauty, Health and Well-Being and Household Care. Some of its worldwide products include Head and Shoulders®, Pantene®, Gillette® razors and personal care products, Crest®, Dawn®, Tide®, Bounty®, Duracell® batteries; and Iams® pet food among others. At its core, however, the Participant is a science driven company. It supports one of the most robust industrial research and development (R&D) programs in the world. The Participant uses this rich foundation of science to drive innovation across all of its product lines. But the innovation process is not confined in-house The Participant pursues an “open innovation” policy, seeking partnerships with scientists and researchers in universities and national laboratories where it can contribute its extensive knowledge assets and collaborate to advance scientific understanding. The research under this multi-task CRADA was directed under the following general task areas and, throughout the duration of this CRADA the work statement was modified to match the needs of the Parties and the direction of the research. (1) Software modeling, simulation and development; (2) Manufacturing Technologies; (3) Supply Chain Optimization, (4) Advanced Materials.
The development and evaluation of a low cost blade concept based on the NASA-Lewis specifications is discussed. A blade structure was designed and construction methods and materials were selected. Complete blade tooling concepts, various technical and economic analysis, and evaluations of the blade design were performed. A comprehensive fatigue test program was conducted to provide data and to verify the design. A test specimen of the spar assembly, including the root end attachment, was fabricated. This is a full-scale specimen of the root end configuration, 20 ft long. A blade design for the Mod '0' system was completed.
Refrigerator technology has advanced significantly over the last couple of decades. Today’s refrigerators use only about 25% of the energy that was required to power models built in 1975. Even as they continually improve efficiency to meet standards, refrigerators have increased in size by almost 20%, added energy-consuming features such as through-the-door ice, and provide more benefits than ever before. However, a few challenges and technology gaps are preventing further improvement of the demand responsiveness and efficiency of the refrigerators. One of the major technology gaps in existing refrigerators is their outdated de-icing process. When the evaporator generates frost, an old-fashioned resistive heating element melts the ice. Most refrigerators have a timed defrost cycle, rather than an active system that could monitor the state of the frost. In these systems, not only is the precious electricity used at its least efficient form of conversion (direct conversion of electricity to heat), but also all the latent heat associated with the ice is wasted during the melting process. On top of that, the refrigerator needs to work harder to pull the temperature down after defrosting, and, last but not least, the food quality is severely impacted by the temperature swings during the defrost cycle. According to a study, the EU alone wastes 89 million tons of food in the supply chain every year. Any temperature swing during defrosting (about 6F according to Emerson for low-temperature cases) can negatively impact the shelf life of meat and other products for multiple days. All these issues can happen during the peak demand time of the electric grid. Unlike the conventional systems, the proposed novel advanced micro-vibrational deicing process uses no heat for defrosting. Instead, it uses the micro vibrations generated by a piezoelectric or vibration-generating module to mechanically break ice from the heat exchanger almost instantaneously. The project titled “Higher Efficiency, Demand Flexible Refrigerator with On-Demand Micro-Vibrational De-icing Technology, performed by Ultrasonic Technology Solutions, LLC (UTS) of Knoxville, TN, in collaboration with Emerson (now Copeland), represents the final phase of a multi-year effort funded under the U.S. Department of Energy’s Building Technologies Office (BTO) BENEFIT FOA 2020. Initiated on October 1, 2021, and completed after a nine-month no-cost extension ending September 30, 2025, this project aimed to develop and validate a novel micro-vibrational mechanical defrosting system, achieving more than 25% improvement in defrosting energy efficiency over conventional baseline defrosting technologies. Over sixteen quarters, the project advanced from fundamental ice-mechanical characterization and prototype development to full-scale system integration and validation. Initial efforts established project management infrastructure and characterized ice adhesion properties, followed by the design and fabrication of early aluminum-based prototypes for resonance frequency testing. Subsequent quarters saw rapid technical progression, including the identification of optimal piezoelectric and motor-based vibration mechanisms, the demonstration of effective de-icing over 6x6-inch aluminum surfaces. The team achieved its Go/No-Go milestone by exceeding the 25% energy-efficiency improvement target—reaching up to 3,340% under optimized conditions—and later confirmed that motor-driven systems offered superior performance and energy efficiency compared to piezoelectric alternatives. Continued refinement led to the development of amplifier systems on printed circuit boards, improved control and instrumentation hardware, and integration into full-scale heat exchanger (HX) prototypes at both UTS and Copeland facilities. Multiple vibration-mounting studies and frost-growth experiments guided mechanical optimization and noise-mitigation strategies, achieving a 17.5 dB reduction in sound pressure level and verifying robust mechanical performance. Advanced analyses, including modal and harmonic simulations, established a quantitative understanding of vibrational behavior and de-icing efficiency across >1000 cm² systems. The final project phase successfully demonstrated scalable integration within reach-in and chest freezer prototypes, confirmed >25% efficiency improvements in large-area systems, and completed a comprehensive business model and scale-up strategy identifying electric defrost systems as the primary beachhead market. The culmination of this DOE-supported effort establishes micro-vibrational defrosting as a viable, high-efficiency, low-noise, and demand-flexible de-icing technology, paving the way for commercial deployment and broader application in next-generation refrigeration systems.
The capabilities of the National Transonic Facility (NTF) at NASA-Langley and its impact on aerodynamics investigations are surveyed. The fan-driven, closed-circuit transonic wind tunnel has an 8.2 sq ft slotted test section. Trials can be run from Mach 0.2-1.2, pressures of 1-8.9 atm, and temperatures of -320 to 150 F using nitrogen as the working gas. Instrumentation has been developed for monitoring force, pressure, attitude, deformation, temperature, skin friction, flow transition, and flow velocity as well as visualizing flows around the models. Pressures of 15-130 psi are available, as are Re up to 120 million at Mach 1. Correlations are being made with flight data from the Shuttle, 767, X-29A, and TACT aircraft for real-world extrapolations. The NTF, when combined with computational fluid dynamics techniques, will permit testing of aerodynamically sophisticated shapes while narrowing the design goals for each model during basic research in fluid mechanics, transport, and aerodynamic phenomena.
Exercise countermeasures provide benefits that are crucial for successful human spaceflight, to mitigate the spaceflight physiological deconditioning which occurs during exposure to microgravity. The NASA Human Research Program (HRP) within the Human Exploration and Operations Mission Directorate (HEOMD) is managing next generation Advanced Exercise Concepts (AEC) requirements development and candidate technology maturation to Technology Readiness Level (TRL) 7 (ground prototyping and flight demonstration) for all exploration mission profiles from Multi Purpose Crew Vehicle (MPCV) Exploration Missions (up to 21 day duration) to Mars Transit (up to 1000 day duration) missions. These validated and optimized exercise countermeasures systems will be provided to the ISS Program and MPCV Program for subsequent flight development and operations. The International Space Station (ISS) currently has three major pieces of operational exercise countermeasures hardware: the Advanced Resistive Exercise Device (ARED), the second-generation (T2) treadmill, and the cycle ergometer with vibration isolation system (CEVIS). This suite of exercise countermeasures hardware serves as a benchmark and is a vast improvement over previous generations of countermeasures hardware, providing both aerobic and resistive exercise for the crew. However, vehicle and resource constraints for future exploration missions beyond low Earth orbit will require that the exercise countermeasures hardware mass, volume, and power be minimized, while preserving the current ISS capabilities or even enhancing these exercise capabilities directed at mission specific physiological functional performance and medical standards requirements. Further, mission-specific considerations such as preservation of sensorimotor function, autonomous and adaptable operation, integration with medical data systems, rehabilitation, and in-flight monitoring and feedback are being developed for integration with the exercise countermeasures systems. Numerous technologies have been considered and evaluated against HRP-approved functional device requirements for these extreme mission profiles, and include wearable sensors, exoskeletons, flywheel, pneumatic, and closed-loop microprocessor controlled motor driven systems. Each technology has unique advantages and disadvantages. The Advanced Exercise Concepts project oversees development of candidate next generation exercise countermeasures hardware, performs trade studies of current and state of the art exercise technologies, manages and supports candidate systems physiological evaluations with human test subjects on the ground, in flight analogs and flight. The near term goal is evaluation of candidate systems in flight, culminating in an integrated candidate next generation exercise countermeasures suite on the ISS which coalesces research findings from HRP disciplines in the areas of exercise performance for muscle, bone, cardiovascular, sensorimotor, behavioral health, and nutrition for optimal benefit to the crew.
The effect of gravity on the growth and development of plants has been the subject of scientific investigation for over a century. The results obtained in space to test specific hypotheses on gravitropism, gene expression, seed formation, or growth rate are affected by both the primary effect of the microgravity and secondary effects of the spaceflight environment. The secondary effects of the spaceflight environment include physical effects arising from physical changes, such as the absence of buoyancy driven convective mixing, altered behavior of liquids and gases, and the environmental conditions in the spacecraft atmosphere. Thus, the design of biological experiments (e.g. cells, plants, animals, etc.) conducted in microgravity must account for changes in the physical forces, as well as the environmental conditions, imposed by the specific spaceflight vehicle and experimental hardware. In addition, researchers must become familiar with other aspects of spaceflight experiments: payload integration with hardware developers, safety documentation and crew procedures, and the logistics of conducting flight and ground controls. This report reviews the physical and environmental factors that directly and indirectly affect the results of plant science experiments in microgravity and is intended to serve as a guide in the design and implementation plant experiments in space.
An interactive method is proposed for the solution of two-dimensional, laminar flow fields with identifiable regions of recirculation, such as the shear-layer-driven cavity flow. The method treats the flow field as composed of two regions, with an appropriate mathematical model adopted for each region. The shear layer is computed by the compressible boundary layer equations, and the slowly recirculating flow by the incompressible Navier-Stokes equations. The flow field is solved iteratively by matching the local solutions in the two regions. For this purpose a new matching method utilizing an overlap between the two computational regions is developed, and shown to be most satisfactory. Matching of the two velocity components, as well as the change in velocity with respect to depth is amply accomplished using the present approach, and the stagnation points corresponding to separation and reattachment of the dividing streamline are computed as part of the interactive solution. The interactive method is applied to the test problem of a shear layer driven cavity. The computational results are used to show the validity and applicability of the present approach.
In the past several years, domain decomposition was a very popular topic, partly motivated by the potential of parallelization. While a large body of theory and algorithms were developed for model elliptic problems, they are only recently starting to be tested on realistic applications. The application of some of these methods to two model problems in computational fluid dynamics are investigated. Some examples are two dimensional convection-diffusion problems and the incompressible driven cavity flow problem. The construction and analysis of efficient preconditioners for the interface operator to be used in the iterative solution of the interface solution is described. For the convection-diffusion problems, the effect of the convection term and its discretization on the performance of some of the preconditioners is discussed. For the driven cavity problem, the effectiveness of a class of boundary probe preconditioners is discussed.
The need to minimize fan noise radiation from commercial aircraft engine nacelles continues to provide an impetus for developing new acoustic liner concepts. If the full value of such concepts is to be attained, an understanding of grazing flow effects is crucial. Because of this need for improved understanding of grazing flow effects, the NASA Langley Research Center Liner Physics Group has invested a large effort over the past decade into the development of a 2-D finite element method that characterizes wave propagation through a lined duct. The original test section in the Langley Grazing IncidenceTube was used to acquire data needed for implementation of this finite element method. This test section employed a stepper motor-driven axial-traversing bar, embedded in the wall opposite the test liner, to position a flush-mounted microphone at pre-selected locations. Complex acoustic pressure data acquired with this traversing microphone were used to educe the acoustic impedance of test liners using this 2-D finite element method and a local optimization technique. Results acquired in this facility have been extensively reported, and were compared with corresponding results from various U.S. aeroacoustics laboratories in the late 1990 s. Impedance data comparisons acquired from this multi-laboratory study suggested that it would be valuable to incorporate more realistic 3-D aeroacoustic effects into the impedance eduction methodology. This paper provides a description of modifications that have been implemented to facilitate studies of 3-D effects. The two key features of the modified test section are (1) the replacement of the traversing bar and its flush-mounted microphone with an array of 95 fixed-location microphones that are flush-mounted in all four walls of the duct, and (2) the inclusion of a suction device to modify the boundary layer upstream of the lined portion of the duct. The initial results achieved with the modified test section are provided in this report, and a comparison of these results with those achieved using the original test section is used to demonstrate that the data acquisition and analysis with the new test section can be confidently used for impedance eduction.