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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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At least 199 records · Page 11

Implementation of the University of Miami Wave Model (UMWM) into the NASA/GMAO Goddard Earth Observing System Model (GEOS)

Wind generated waves are integral element in air-sea interactions and affect exchange of momentum, heat, water, gases and production of marine aerosol. Motivated by the need to resolve the air-sea interface we have implemented the University of Miami Wave model (UMWM) into the NASA/GMAO Goddard Earth Observing System Model (GEOS). The implementation of the wave model in GEOS aimed to facilitate coupling with the atmosphere and ocean model components with minimal changes to the existing system, while at the same time ensure correctness of the predicted wave energy spectrum and wave diagnostics. Here we describe the implementation of the GEOS/UMWM system and show results from model experiments and verifications. This work is a step toward development of a coupled atmosphere-wave-ocean GEOS system.

Darmenov, Anton↗

Measurements of L-shell X-ray Emission lines of Neonlike Europium on an Electron Beam Ion Trap

We report a measurement of the two X-ray transitions that proceed from the (1s22s22p51∕23d3∕2)J=1 and (1s22s1/22p63p1/2)J =1 upper levels to the (1s22s22p6)J =0 ground level in neonlike Eu53+ (Z = 63), that is, near the previously documented avoided crossing of the two upper levels at Z = 68. The measurement was carried out using the calorimeter spectrometer on the Livermore EBIT-I electron beam ion trap. It affirms the trends set by the neighboring neonlike ions both in terms of the relative intensity of the two lines and in terms of the magnitude of disagreement with theoretical energy level predictions.

Peter Beiersdorfer↗

SPACE: Three Decades of Spacecraft Power Systems Analysis with Fortran

The SPACE (System Power Analysis for Capability Evaluation) Fortran program developed at NASA Glenn Research Center has enabled power generation predictions and energy balance analyses for spacecraft electrical power systems (EPS) since 1988. SPACE was originally designed to analyze the EPS of the Space Station Freedom and continues to support certifications for visiting vehicles and extravehicular activities on the International Space Station today. Another version of SPACE currently supports design and mission planning operations for the Orion and Gateway vehicles as part of NASA’s Artemis program. In total, over 50 engineers have contributed to the development and use of SPACE on various platforms throughout its history. Ongoing code modernization efforts aim to generalize the program for use with different vehicles and configurations. While SPACE team analysts currently interact with the program via the command line, future development work also includes the creation of a graphical user interface for use by flight operations personnel. The SPACE code thus has a long legacy in spacecraft EPS analysis and will continue to play a critical role in future human spaceflight missions by leveraging the computational power of Fortran.

Fortran↗

Constraining Arctic Climate Projections of Wintertime Warming With Surface Turbulent Flux Observations and Representation of Surface-Atmosphere Coupling

The drivers of rapid Arctic climate change—record sea ice loss, warming SSTs, and a lengthening of the sea ice melt season—compel us to understand how this complex system operates and use this knowledge to enhance Arctic predictability. Changing energy flows sparked by sea ice decline, spotlight atmosphere-surface coupling processes as central to Arctic system function and its climate change response. Despite this, the representation of surface turbulent flux parameterizations in models has not kept pace with our understanding. The large uncertainty in Arctic climate change projections, the central role of atmosphere-surface coupling, and the large discrepancy in model representation of surface turbulent fluxes indicates that these processes may serve as useful observational constraints on projected Arctic climate change. This possibility requires an evaluation of surface turbulent fluxes and their sensitivity to controlling factors (surface-air temperature and moisture differences, sea ice, and winds) within contemporary climate models (here Coupled Model Intercomparison Project 6). The influence of individual controlling factors and their interactions is diagnosed using a multi-linear regression approach. This evaluation is done for four sea ice loss regimes, determined from observational sea ice loss trends, to control for the confounding effects of natural variability between models and observations. The comparisons between satellite- and model-derived surface turbulent fluxes illustrate that while models capture the general sensitivity of surface turbulent fluxes to declining sea ice and to surface-air gradients of temperature and moisture, substantial mean state biases exist. Specifically, the central Arctic is too weak of a heat sink to the winter atmosphere compared to observations, with implications to the simulated atmospheric circulation variability and thermodynamic profiles. Models were found to be about 50% more efficient at turning an air-sea temperature gradient anomaly into a sensible heat flux anomaly relative to observations. Further, the influence of sea ice concentration on the sensible heat flux is underestimated in models compared to observations. The opposite is found for the latent heat flux variability in models; where the latent heat flux is too sensitive to a sea ice concentration anomaly. Lastly, the results suggest that present-day trends in sea ice retreat regions may serve as suitable observational constraints of projected Arctic warming.

turbulent fluxes↗

Sharply curved turn around duct flow predictions using spectral partitioning of the turbulent kinetic energy and a pressure modified wall law

Computational predictions of turbulent flow in sharply curved 180 degree turn around ducts are presented. The CNS2D computer code is used to solve the equations of motion for two-dimensional incompressible flows transformed to a nonorthogonal body-fitted coordinate system. This procedure incorporates the pressure velocity correction algorithm SIMPLE-C to iteratively solve a discretized form of the transformed equations. A multiple scale turbulence model based on simplified spectral partitioning is employed to obtain closure. Flow field predictions utilizing the multiple scale model are compared to features predicted by the traditional single scale k-epsilon model. Tuning parameter sensitivities of the multiple scale model applied to turn around duct flows are also determined. In addition, a wall function approach based on a wall law suitable for incompressible turbulent boundary layers under strong adverse pressure gradients is tested. Turn around duct flow characteristics utilizing this modified wall law are presented and compared to results based on a standard wall treatment.

Santi, L. Michael↗

Prediction of shuttle vehicle damping from component test results

A dissipative energy approach for predicting the damping of four-component space shuttle model by means of modal parameters obtained from tests of the individual components is presented. A relationship between modal damping energy per cycle and peak strain (or kinetic) energy is first determined empirically from test data for each component. Undamped analytical models of each component are also developed, and combined into a system model from which are obtained modal kinetic (or strain) energies for its respective modes. These data are then used with the empirical damping curves to apportion the proper amount of damping energy to each component in a combined system mode, and thereby allow a prediction of damping ratio. Some discrepancies in results are noted to occur because of incomplete modeling of connecting link mechanisms and anomalies in modal responses.

Kana, D. D.↗

Prediction of the far field noise from wind energy farms

The basic physical factors involved in making predictions of wind turbine noise and an approach which allows for differences in the machines, the wind energy farm configurations and propagation conditions are reviewed. Example calculations to illustrate the sensitivity of the radiated noise to such variables as machine size, spacing and numbers, and such atmosphere variables as absorption and wind direction are presented. It is found that calculated far field distances to particular sound level contours are greater for lower values of atmospheric absorption, for a larger total number of machines, for additional rows of machines and for more powerful machines. At short and intermediate distances, higher sound pressure levels are calculated for closer machine spacings, for more powerful machines, for longer row lengths and for closer row spacings.

Shepherd, K. P.↗

Mathematical modeling of moving boundary problems in thermal energy storage

The capability for predicting the performance of thermal energy storage (RES) subsystems and components using PCM's based on mathematical and physical models is developed. Mathematical models of the dynamic thermal behavior of (TES) subsystems using PCM's based on solutions of the moving boundary thermal conduction problem and on heat and mass transfer engineering correlations are also discussed.

Solomon, A. D.↗

The NASA Energy and Water Cycle Extreme (NEWSE) Integration Project

Skillful predictions of water and energy cycle extremes (flood and drought) are elusive. To better understand the mechanisms responsible for water and energy extremes, and to make decisive progress in predicting these extremes, the collaborative NASA Energy and Water cycle Extremes (NEWSE) Integration Project, is studying these extremes in the U.S. Southern Great Plains (SGP) during 2006-2007, including their relationships with continental and global scale processes, and assessment of their predictability on multiple space and time scales. It is our hypothesis that an integrative analysis of observed extremes which reflects the current understanding of the role of SST and soil moisture variability influences on atmospheric heating and forcing of planetary waves, incorporating recently available global and regional hydro- meteorological datasets (i.e., precipitation, water vapor, clouds, etc.) in conjunction with advances in data assimilation, can lead to new insights into the factors that lead to persistent drought and flooding. We will show initial results of this project, whose goals are to provide an improved definition, attribution and prediction on sub-seasonal to interannual time scales, improved understanding of the mechanisms of decadal drought and its predictability, including the impacts of SST variability and deep soil moisture variability, and improved monitoring/attributions, with transition to applications; a bridging of the gap between hydrological forecasts and stakeholders (utilization of probabilistic forecasts, education, forecast interpretation for different sectors, assessment of uncertainties for different sectors, etc.).

House, P. R.↗

What can nuclear energy do for society?

The utilization of nuclear energy and the predicted impact of future uses of nuclear energy are discussed. Areas of application in electric power production and transportation methods are described. It is concluded that the need for many forms of nuclear energy will become critical as the requirements for power to supply an increasing population are met.

Rom, F. E.↗

The Energy Systems Optimization Computer Program /ESOP/ developed for Modular Integrated Utility Systems /MIUS/ analysis

A significant energy and cost savings can be obtained by integrating various utility services (space heating and cooling, electrical power generation, solid waste disposal, potable water, and waste water treatment) into a single unit which provides buildings or groups of buildings with these services. This paper presents a description of a computer program, called the Energy Systems Optimization Program (ESOP). This program predicts the loads, energy requirements, equipment sizes, and life-cycle costs of alternative methods of meeting these utility requirements. The program has been used extensively for performing energy analyses of Modular Integrated Utility Systems (MIUS).

Ferden, S. L.↗

Vibroacoustic Characterization of a New Hybrid Wing-Body Fuselage Concept

A lighter, more robust airframe design is required to withstand the loading inherent to next generation non cylindrical commercial airliners. The Pultruded Rod Stitched Efficient Unitized Structure concept, a highly integrated composite design involving a stitched and co-cured substructure, has been developed to meet such requirements. While this structure has been shown to meet the demanding out-of-plane loading requirements of the flat-sided pressurized cabin design, there are concerns that the stiff co-cured details will result in relatively high acoustic radiation efficiencies at frequencies well below the thin skin acoustic coincidence frequency. To address this concern and establish a set of baseline vibroacoustic characteristics, a representative test panel was fabricated and a suite of tests were conducted that involved measurements of panel vibration and radiated sound power during point force and diffuse acoustic field excitations. Experimental results are shown and compared with Finite Element and Statistical Energy Analysis model predictions through the use of modal and energy correlation techniques among others. The behavior of the structure subject to turbulent boundary layer excitation is also numerically examined.

Allen, Albert R.↗

Washington, D.C. & Maryland Energy: Estimating Solar Potential Using NASA POWER Data to Inform Renewable Energy Policy for Washington, D.C.

In line with the Sustainable D.C. 2.0 plan to combat climate change, Washington D.C. aims to decrease its greenhouse gas emissions by 100% by 2050. As solar energy is a clean, renewable energy form, its integration into the region’s power grids lowers energy costs and incentivizes sustainable development. We partnered with the Washington D.C. Department of Energy & Environment (DOEE) to determine how urban areas surrounding D.C. can better be incorporated into decisions regarding renewable energy policy. The team used NASA’s Prediction of Worldwide Energy Resources (POWER) solar data and a Light Detection and Ranging (LiDAR) derived digital surface model, to estimate and visualize rooftop solar potential for Maryland’s Prince George’s and Montgomery counties. POWER provided solar irradiance data adjusted for tilt angle while the digital surface model contributed aspect and slope data. This methodology factored out areas that were unsuitable for solar panel installation while displaying areas that possess a high potential for energy return. The team found the total rooftop solar potential for the study area to be almost 32 million kW, which is equivalent to roughly 660 kW per building. The methodology used to generate the solar potential maps can be applied to other regions of the country seeking to efficiently utilize solar energy. The end users at the DOEE can use our resulting solar potential map and data table to effectively target buildings that have the highest potential to generate solar energy.

Edward Cronin↗

A candidate concept for display of forward-looking wind shear information

A concept is proposed which integrates forward-look wind shear information with airplane performance capabilities to predict future airplane energy state as a function of range. The information could be displayed to a crew either in terms of energy height or airspeed deviations. The anticipated benefits of the proposed display information concept are: (1) a wind shear hazard product that scales directly to the performance impact on the airplane and that has intuitive meaning to flight crews; (2) a reduction in flight crew workload by automatic processing of relevant hazard parameters; and (3) a continuous display of predicted airplane energy state if the approach is continued. Such a display may be used to improve pilot situational awareness or improve pilot confidence in wind shear alerts generated by other systems. The display is described and the algorithms necessary for implementation in a simulation system are provided.

Hinton, David A.↗

A prediction model for bipolar RAMs in a high energy ion/proton environment

A model has been developed which predicts the relative susceptibility of bipolar RAMs to heavy ion and proton upset. During the course of evaluating this model, physical and electrical variations were also evaluated indicating that the minimum internal signal level is the primary upset susceptibility indicator. Unfortunately, all of the physical and electrical variations expected during a normal product development cycle are in direct opposition to improved high-energy particle upset tolerance. Hence, a trade-off between highly susceptible, low power (medium speed) devices must be made against the less susceptible, higher power (high speed) equivalent device, taking into account the systems trade-off with respect to system power, software, error correction procedures and/or circuit redundancy.

Myers, D. K.↗

Prediction of interior noise due to random acoustic or turbulent boundary layer excitation using statistical energy analysis

The feasibility of predicting interior noise due to random acoustic or turbulent boundary layer excitation was investigated in experiments in which a statistical energy analysis model (VAPEPS) was used to analyze measurements of the acceleration response and sound transmission of flat aluminum, lucite, and graphite/epoxy plates exposed to random acoustic or turbulent boundary layer excitation. The noise reduction of the plate, when backed by a shallow cavity and excited by a turbulent boundary layer, was predicted using a simplified theory based on the assumption of adiabatic compression of the fluid in the cavity. The predicted plate acceleration response was used as input in the noise reduction prediction. Reasonable agreement was found between the predictions and the measured noise reduction in the frequency range 315-1000 Hz.

Grosveld, Ferdinand W.↗

Improved Performance and Safety for High Energy Batteries Through Use of Hazard Anticipation and Capacity Prediction

Prediction of the capacity remaining in used high rate, high energy batteries is important information to the user. Knowledge of the capacity remaining in used batteries results in better utilization. This translates into improved readiness and cost savings due to complete, efficient use. High rate batteries, due to their chemical nature, are highly sensitive to misuse (i.e., over discharge or very high rate discharge). Battery failure due to misuse or manufacturing defects could be disastrous. Since high rate, high energy batteries are expensive and energetic, a reliable method of predicting both failures and remaining energy has been actively sought. Due to concerns over safety, the behavior of lithium/sulphur dioxide cells at different temperatures and current drains was examined. The main thrust of this effort was to determine failure conditions for incorporation in hazard anticipation circuitry. In addition, capacity prediction formulas have been developed from test data. A process that performs continuous, real-time hazard anticipation and capacity prediction was developed. The introduction of this process into microchip technology will enable the production of reliable, safe, and efficient high energy batteries.

Atwater, Terrill↗