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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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A general-purpose, featurization-agnostic toolkit, MatFold, is provided to automate reproducible generation of cross-validation splits to assess out-of-distribution generalization and encourage further community use in materials model benchmarking.
The primary objective was to present methods for validating predictions of Rocketdyne's most current version of the Space Shuttle Main Engine (SSME) Power Balance Model (PBM) with respect to physical relations governing flow systems. This required the development and implementation of postprocessors to check results of PBM computations for satisfaction of conservation relations. A cursory uncertainty analysis of PBM predictions with respect to mass and energy balances was performed. In addition, an effort to identify the empirical relations and physical assumptions within PBM which impact the ability of the model to attain rigorous balance was begun.
Exponential increases in scientific experimental data are outpacing silicon technology progress, necessitating heterogeneous computing systems—particularly those utilizing machine learning (ML)—to meet future scientific computing demands. The growing importance and complexity of heterogeneous computing systems require systematic modeling to understand and predict the effective roles for ML. We present a model that addresses this need by framing the key aspects of data collection pipelines and constraints and combining them with the important vectors of technology that shape alternatives, computing metrics that allow complex alternatives to be compared. For instance, a data collection pipeline may be characterized by parameters such as sensor sampling rates and the overall relevancy of retrieved samples. Alternatives to this pipeline are enabled by development vectors including ML, parallelization, advancing CMOS, and neuromorphic computing. By calculating metrics for each alternative such as overall F1 score, power, hardware cost, and energy expended per relevant sample, our model allows alternative data collection systems to be rigorously compared. We apply this model to the Compact Muon Solenoid experiment and its planned high luminosity-large hadron collider upgrade, evaluating novel technologies for the data acquisition system (DAQ), including ML-based filtering and parallelized software. The results demonstrate that improvements to early DAQ stages significantly reduce resources required later, with a power reduction of 60% and increased relevant data retrieval per unit power (from 0.065 to 0.31 samples/kJ). However, we predict that further advances will be required in order to meet overall power and cost constraints for the DAQ.
Previous research has shown that a clothes dryer heated by thermoelectric (Peltier) heat pumps can be up to 85% more efficient than a conventional electric-resistance dryer. A previous thermoelectric prototype used a conventional dryer’s air flow of 120 ft3/min (0.06 m3/s) and provided about 1,300 W of thermoelectric heating capacity at a heating coefficient of performance (COP) of approximately 1.2. In this work, the performance of a clothes dryer with a very high air flow rate, up to 300 ft3/min (1.14 m3/s), and only 400 W of thermoelectric heating capacity was investigated using a thermohydraulic model. Key aspects of the model were validated experimentally. Results for dry time and efficiency are presented for various air flow and heating rates.
A full scale engine test of the NASA/General Electric Company (GE) Energy Efficient Engine (E3) was conducted to demonstrate the E3 engine concept and evaluate its performance. The test program, performed at the GE outdoor engine test facilities in Peebles, OH, included a detailed evaluation of the total pressure and temperature profiles at the exit of the mixed flow exhaust system to determine its mixing effectiveness. Subscale model tests of the same mixed flow exhaust system had been previously conducted at FluiDyne Engineering Corporation in Minneapolis, Minnesota as part of the GE E3 mixer aerodynamic technology development program. The scale model and full scale engine nozzle exit survey data and the calculated mixing effectiveness are compared and discussed. Results indicate the full scale engine mixing effectiveness to be five percent higher than the scale model as a result of a geometric difference and higher turbulence levels in the engne exhaust flowfield.
The accurate prediction of jet noise is possible only if the jet flow field can be predicted accurately. Predictions for the mean velocity and turbulence quantities in the jet flowfield are typically the product of a Reynolds-averaged Navier-Stokes solver coupled with a turbulence model. To evaluate the effectiveness of solvers and turbulence models in predicting those quantities most important to jet noise prediction, two CFD codes and several turbulence models were applied to a jet configuration over a range of jet temperatures for which experimental data is available.
A novel shallow bore (< 6 m deep) ground heat exchanger is proposed to substitute the conventional vertical bore ground heat exchanger (> 60 m deep) for ground source heat pump systems. A series of simulations were carried out to evaluate the impacts of the vertical soil temperature profile on the performance of the shallow bore ground heat exchanger in response to thermal loads of a ground source heat pump system, with various lengths of the shallow bore ground heat exchanger and ground thermal properties. The results indicate that the vertical soil temperature profile has a noticeable influence on the thermal response of the shallow bore ground heat exchanger. Moreover, for shallow bore ground heat exchangers with the same volume and buried depth, the one with greater length and narrower diameter has lower tank water temperature fluctuations over the year due to relatively more stable soil temperature, and the larger surface to volume ratio.
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The baseline Space Station Freedom electric power system (EPS) employs photovoltaic (PV) arrays and nickel hydrogen (NiH2) batteries to supply power to housekeeping and user electrical loads via a direct current (dc) distribution system. The EPS was originally designed for an operating life of 30 years through orbital replacement of components. As the design and development of the EPS continues, accurate EPS performance predictions are needed to assess design options, operating scenarios, and resource allocations. To meet these needs, NASA Lewis Research Center (LeRC) has, over a 10 year period, developed SPACE (Station Power Analysis for Capability Evaluation), a computer code designed to predict EPS performance. This paper describes SPACE, its functionality, and its capabilities.
We describe results from a comprehensive computer model developed to guide optimization of an ultraviolet Raman lidar system for measuring daytime profiles of atmospheric water vapor. Daytime measurements present added challenges because of the difficulties inherent in detecting Raman signals against solar backgrounds. We are pursuing two concepts for optimizing the daytime performance of a Raman lidar system. The first involves operating the system in the solar blind region of the ultraviolet spectrum. The second concept involves operation of the system in a narrowband, narrow field-of-view mode. Calculations for lidar systems based on both concepts are presented.
A demonstration version of an aircraft interior materials computer data library was developed and contains information on selected materials applicable to aircraft seats and wall panels, including materials for the following: panel face sheets, bond plies, honeycomb, foam, decorative film systems, seat cushions, adhesives, cushion reinforcements, fire blocking layers, slipcovers, decorative fabrics and thermoplastic parts. The information obtained for each material pertains to the material's performance in a fire scenario, selected material properties and several measures of processability.
The author has identified the following significant results. The probability of correct classification of various populations in data was defined as the primary performance index. The multispectral data being of multiclass nature as well, required a Bayes error estimation procedure that was dependent on a set of class statistics alone. The classification error was expressed in terms of an N dimensional integral, where N was the dimensionality of the feature space. The multispectral scanner spatial model was represented by a linear shift, invariant multiple, port system where the N spectral bands comprised the input processes. The scanner characteristic function, the relationship governing the transformation of the input spatial, and hence, spectral correlation matrices through the systems, was developed.
Abstract Historically, fire has been essential in Southwestern US forests. However, a century of fire-exclusion and changing climate created forests which are more susceptible to uncharacteristically severe wildfires. Forest managers use a combination of thinning and prescribed burning to reduce forest density to help mitigate the risk of high-severity fires. These treatments are laborious and expensive, therefore optimizing their impact is crucial. Landscape simulation models can be useful in identifying high risk areas and assessing treatment effects, but uncertainties in these models can limit their utility in decision making. In this study we examined underlying uncertainties in the initial vegetation layer by leveraging a previous study from the Santa Fe fireshed and using new inventory plots from 111 stands to interpolate the initial forest conditions. We found that more inventory plots resulted in a different geographic distribution and wider range of the modelled biomass. This changed the location of areas with high probability of high-severity fires, shifting the optimal location for management. The increased range of biomass variability from using a larger number of plots to interpolate the initial vegetation layer also influenced ecosystem carbon dynamics, resulting in simulated forest conditions that had higher rates of carbon uptake. We conclude that the initial forest layer significantly affects fire and carbon dynamics and is dependent on both number of plots, and sufficient representation of the range of forest types and biomass density.
We are investigating a microwave cavity-based transducer for in-core high-temperature fluid flow sensing in molten salt cooled reactors (MSCR) and sodium fast reactors (SFR). This sensor is a hollow metallic cylindrical cavity. The principle of sensing consists of making one wall of the cylindrical cavity flexible enough so that dynamic pressure, which is proportional to fluid velocity, will cause membrane deflection. Membrane deflection causes cavity volume change, which leads to a shift in the resonant frequency. To validate sensor physics, we have performed proof-of-principle test of flow sensing in water. For this test, we have developed a cylindrical resonator for K-band, which was machined from brass. The cavity was excited through WR-42 waveguide through a subwavelength hole on the side of the wall of the cylinder. To increase the spectral signal visibility, we developed a signal processing method for baseline subtraction. A flow loop for proof-of-principle test of transducer performance in water was assembled. A commercial flow meter was installed in the loop for reference measurements. Cylindrical cavity was excited in the TEM 011 mode with resonant frequency f ≈ 17.8GHz. Frequency shift of cavity spectral response was obtained by gradually increasing water flow rate from 0 to 60gpm. Corresponding monotonic increase of resonant frequency shift by several MHz was observed.
The results are presented from testing one-eighth scale models of the Pratt and Whitney aircraft reference and Boeing nozzles for the JT8D-100 series mixed flow engines. The objective of the test was to obtain the nozzle velocity and flow coefficients for the reference configurations and compare these with the Boeing configurations which incorporated a longer splitter between the fan and primary flows. A further comparison was made between the JT8D-100 series nozzles and the Boeing JT8D-9/727 production nozzle performance. A statistical analysis was used to compare configurations which showed the performance (velocity coefficient) of the reference and the Boeing configuration was the same for the JT8D-109. It also showed no difference between reference and the Boeing configuration for the JT8D-115 and no difference for the JT8D-117 nozzles. Bypass ratio (match) was shown to be equally dependent on splitter position as on nozzle area within the range investigated. The nozzles were very similar in flow coefficient within an engine family. Excellent profile data was recorded. The effects of swirl on the nozzle performance was examined and found to degrade the velocity and flow coefficients.
Rigorous verification, validation, and credibility (VVC) processes are imperative to ensure that models and simulations (MS) are sufficiently reliable to address issues within their intended scope. The NASA standard for MS, NASA-STD-7009 (7009) [1] was a resultant outcome of the Columbia Accident Investigation Board (CAIB) to ensure MS are developed, applied, and interpreted appropriately for making decisions that may impact crew or mission safety. Because the 7009 focus is engineering systems, a NASA-STD-7009 Guidance Document is being developed to augment the 7009 and provide information, tools, and techniques applicable to the probabilistic and deterministic biological MS more prevalent in human health and performance (HHP) and space biomedical research and operations.
We are investigating a microwave cavity-based transducer for in-core high-temperature fluid flow sensing in molten salt cooled reactors (MSCR) and sodium fast reactors (SFR). This sensor is a hollow metallic cylindrical cavity, which can be fabricated from stainless steel, and as such is expected to be resilient to radiation, high temperature and corrosive environment of MSCR and SFR. The principle of sensing consists of making one wall of the cylindrical cavity flexible enough so that dynamic pressure, which is proportional to fluid velocity, will cause membrane deflection. Membrane deflection causes cavity volume change, which leads to a shift in the resonant frequency. Feasibility of the sensor was initially investigated with analytical derivations and with COMSOL RF Module computer simulations of resonant frequency spectral shift due to uniform load. We also investigated the mechanical integrity of the flowmeter’s membrane through analytical modelling and COMSOL Structural Mechanics Module computer simulations. Both the analytic model and COMSOL model showed that maximum stresses on the plate, which are at the radial boundary of the plate, are three orders of magnitude smaller than the material’s yield strength and ultimate tensile strength. This indicates that the sensor is at a low risk of mechanical failure. Using results from models, we have developed an initial design for a microwave K-band sensor. A cylindrical resonator prototype was fabricated from brass for the initial tests. The external dimensions of the cavity are matched to the flange of a standard WR-42 waveguide. Microwave field is coupled into the resonant cavity through a subwavelength-size aperture. A test article was developed consisting of a piping Tee with a bulkhead WR-42 microwave waveguide installed in a leak-proof assembly. A microwave waveguide circulator was installed in the setup to suppress the effect of reflections at the cavity entrance by increasing the isolation between the input and the output port. Preliminary spectral characterization of cavity spectral response was performed with a portable PXIe chassis microwave VNA with a custom GUI. Preliminary dry tests of the transducer response were conducted with a set of calibrated weights. Transducer frequency shift was shown to be monotonically increasing with increasing pressure. The next steps will involve investigation of the transducer performance for water flow sensing.
Aerosol optical depth (AOD), derived from satellite measurements using Moderate Resolution Imaging Spectrometer (MODIS), offers indirect estimates of particle matter. Research shows a significant positive correlation between satellite-based measurements of AOD and ground-based measurements of particulate matter with aerodynamic diameter less than or equal to 2.5 micrometers (PM2.5). In addition, satellite observations have also shown great promise in improving estimates of PM2.5 air quality surface. Research shows that correlations between AOD and ground PM2.5 are affected by a combination of many factors such as inherent characteristics of satellite observations, terrain, cloud cover, height of the mixing layer, and weather conditions, and thus might vary widely in different regions, different seasons, and even different days in a same location. Analysis of correlating AOD with ground measured PM2.5 on a day-to-day basis suggests the temporal scale, a number of immediate latest days for a given run's day, for their correlations needs to be considered to improve air quality surface estimates, especially when satellite observations are used in a real-time pollution system. The second reason is that correlation coefficients between AOD and ground PM2.5 cannot be predetermined and needs to be calculated for each day's run for a real-time system because the coefficients can vary over space and time. Few studies have been conducted to explore the optimal way to apply AOD data to improve model accuracies of PM2.5 surface estimation in a real-time air quality system. This paper discusses the best temporal scale to calculate the correlation of AOD and ground particle matter data to improve the results of pollution models in real-time system.