SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
This technical paper presents a brief decription of the major activities for this grant during the last three years. Technologyical areas discussed include: model development, ExB convection heating study, study of energetic electron precipitation, polar cap data-model comparison, study of wave heating of O(+), study of photoelectron effects, and study of molecular ion outflow.
The purpose of the chemistry component of the model comparison is to assess to what extent differences in the formulation of chemical processes explain the variance between model results. Observed concentrations of chemical compounds are used to estimate to what degree the various models represent realistic situations. For readability, the materials for the chemistry experiment are reported in three separate sections. This section discussed the data used to evaluate the models in their simulation of the source gases and the Nitrogen compounds (NO(y)) and Chlorine compounds (Cl(y)) species.
Traction tests were performed on RP-1, a common kerosene based rocket propellant. Traction data on this fluid are required for purposes of turbopump bearing design, using codes such as SHABERTH. To obtain the traction data, an existing twin disc machine was used, operating under the side slip mode and using elliptical contacts. The range of test variables were: contact peak Hertz stress from 1.0 to 2.0 GPa, disc surface speed from 10 to 50 m/s, fluid inlet temperature from 30 to 70 C, and with a contact aspect ratio of 1.7. The resulting traction curves were reduced to fundamental fluid property parameters using the Johnson and Tevaarwerk traction model. Theoretical traction predictions were performed by back substitution of the fundamental properties into the traction model. Comparison of the predicted with the measured curves gives a high degree of confidence in the correctness of the traction model. For purposes of input to the NASA SHABERTH program, the traction model was next used to predict the expected traction of RP-1 under line contact conditions.
Traction tests were performed on RPI, a common kerosene-based rocket propellant. Traction data on this fluid are required for purposes of turbopump bearing design, using such codes as SHABERTH. To obtain the traction data, an existing twin disk machine was used, operating under the side slip mode and using elliptical contacts. The resulting traction curves were reduced to fundamental fluid property parameters using the Johnson and Tevaarwerk traction model. Theoretical traction predictions were performed by back substitution of the fundamental properties into the traction model. Comparison of the predicted with the measured curves gives a high degree of confidence in the correctness of the traction model.
We present a simplified treatment for calculating the cosmic microwave background anisotropy power spectrum in adiabatic models. It consists of solving for the evolution of a two-fluid model until the epoch of recombination and then integrating over the sources to obtain the cosmic microwave background (CMB) anisotropy power spectrum. The approximation is useful both for a physical understanding of CMB anisotropies as well as for a quantitative analysis of cosmological models. Comparison with exact calculations shows that the accuracy is typically 10%-20% over a large range of angles and cosmological models, including those with curvature and cosmological constant. Using this approximation we investigate the dependence of the CMB anisotropy on the cosmological parameters. We identify six dimensionless parameters that uniquely determine the anisotropy power spectrum within our approximation. CMB experiments on different angular scales could in principle provide information on all these parameters. In particular, mapping of the Doppler peaks would allow an independent determination of baryon mass density, matter mass density, and the Hubble constant.
A detailed comparison of the near-earth neutral sheet position according to several approximations has been made. In particular, two empirical formulas for the neutral sheet location, recently derived from AMPTE/CCE data, have been compared with the corresponding positions derived from Tsyganenko's magnetic field models. Cylindrical coordinates referenced to the geodipole have been used, and the position of the neutral sheet has been identified by the reversal of the radial component of the magnetic field. The analysis reveals that, in the region X(GSM) = -9 to -5 earth radii, abs. value of Y(GSM) not greater than 5 earth radii, close agreement exists between the empirical formulas and the Tsyganenko models. Furthermore, the Tsyganenko models provide a representation for the neutral sheet position in the transition region between near-earth and distant tail models.
Numerical cloud resolving models (CRMs), which are based the non-hydrostatic equations of motion, have been extensively applied to cloud-scale and mesoscale processes during the past four decades. Recent GEWEX Cloud System Study (GCSS) model comparison projects have indicated that CRMs agree with observations in simulating various types of clouds and cloud systems from different geographic locations. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that Numerical Weather Prediction (NWP) and regional scale model can be run in grid size similar to cloud resolving model through nesting technique. Current and future NASA satellite programs can provide cloud, precipitation, aerosol and other data at very fine spatial and temporal scales. It requires a coupled global circulation model (GCM) and cloud-scale model (termed a szrper-parameterization or multi-scale modeling -framework, MMF) to use these satellite data to improve the understanding of the physical processes that are responsible for the variation in global and regional climate and hydrological systems. The use of a GCM will enable global coverage, and the use of a CRM will allow for better and more sophisticated physical parameterization. NASA satellite and field campaign can provide initial conditions as well as validation through utilizing the Earth Satellite simulators. At Goddard, we have developed a multi-scale modeling system with unified physics. The modeling system consists a coupled GCM-CRM (or MMF); a state-of-the-art weather research forecast model (WRF) and a cloud-resolving model (Goddard Cumulus Ensemble model). In these models, the same microphysical schemes (2ICE, several 3ICE), radiation (including explicitly calculated cloud optical properties), and surface models are applied. In addition, a comprehensive unified Earth Satellite simulator has been developed at GSFC, which is designed to fully utilize the multi-scale modeling system. A brief review of the multi-scale modeling system with unified physics/simulator and examples is presented in this article.
The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) consists of a series of time slice experiments targeting the long-term changes in atmospheric composition between 1850 and 2100, with the goal of documenting composition changes and the associated radiative forcing. In this overview paper, we introduce the ACCMIP activity, the various simulations performed (with a requested set of 14) and the associated model output. The 16 ACCMIP models have a wide range of horizontal and vertical resolutions, vertical extent, chemistry schemes and interaction with radiation and clouds. While anthropogenic and biomass burning emissions were specified for all time slices in the ACCMIP protocol, it is found that the natural emissions are responsible for a significant range across models, mostly in the case of ozone precursors. The analysis of selected present-day climate diagnostics (precipitation, temperature, specific humidity and zonal wind) reveals biases consistent with state-of-the-art climate models. The model-to- model comparison of changes in temperature, specific humidity and zonal wind between 1850 and 2000 and between 2000 and 2100 indicates mostly consistent results. However, models that are clear outliers are different enough from the other models to significantly affect their simulation of atmospheric chemistry.
A calculational program utilizing data from radiation dosimetry measurements aboard the Long Duration Exposure Facility (LDEF) satellite to reduce the uncertainties in current models defining the ionizing radiation environment is in progress. Most of the effort to date has been on using LDEF radiation dose measurements to evaluate models defining the geomagnetically trapped radiation, which has provided results applicable to radiation design assessments being performed for Space Station Freedom. Plans for future data comparisons, model evaluations, and assessments using additional LDEF data sets (LET spectra, induced radioactivity, and particle spectra) are discussed.
Comparison of Lyman-alpha, 740- to 1050-A, and Balmer-alpha airglow measurements made at 134 deg solar-zenith angle on Oct. 13, 1969, with resonance-scattering models of solar radiation. Model comparison with Lyman-alpha data fixes the hydrogen column abundance over 215 km to 2 x 10 to the 13th per cu cm within a factor of 2. Differences between the Lyman-alpha model and data indicate a polar-equatorial departure from spherical symmetry in the hydrogen distribution. A Lyman-beta model based on the hydrogen distribution found to fit the Lyman-alpha data fits the spatial variation of the 740- to 1050-A data well from 100 to 130 km, but it does not fit the data well at higher altitudes; thus the presence of more rapidly absorbed shorter-wavelength radiation is indicated. This same resonance-scattering model yields Balmer-alpha intensities that result in good spatial agreement with the Balmer-alpha measurements, but a fivefold increase in the measured solar line center Lyman-beta flux is required (as required for the Lyman-beta measurement). The intensity ratio of Lyman-beta and Balmer-alpha at night is found to be a simple measure of the hydrogen optical depth if measurements with good accuracy can be made in the visible and ultraviolet spectrum.
Sequential Monte Carlo (SMC) samplers are powerful tools for Bayesian inference but suffer from high computational costs due to their reliance on large particle ensembles for accurate estimates. We introduce persistent sampling (PS), an extension of SMC that systematically retains and reuses particles from all prior iterations to construct a growing, weighted ensemble. By leveraging multiple importance sampling and resampling from a mixture of historical distributions, PS mitigates the need for excessively large particle counts, directly addressing key limitations of SMC such as particle impoverishment and mode collapse. Crucially, PS achieves this without additional likelihood evaluations-weights for persistent particles are computed using cached likelihood values. This framework not only yields more accurate posterior approximations but also produces marginal likelihood estimates with significantly lower variance, enhancing reliability in model comparison. Furthermore, the persistent ensemble enables efficient adaptation of transition kernels by leveraging a larger, decorrelated particle pool. Experiments on high-dimensional Gaussian mixtures, hierarchical models, and non-convex targets demonstrate that PS consistently outperforms standard SMC and related variants, including recycled and waste-free SMC, achieving substantial reductions in mean squared error for posterior expectations and evidence estimates, all at reduced computational cost. PS thus establishes itself as a robust, scalable, and efficient alternative for complex Bayesian inference tasks.
The research goals are to create a simulation framework that can accept any combination of models written at the gate or behavioral level. The framework provides the ability to fault simulate and create scenarios of experiments using concurrent simulation. In order to meet these goals we have had to fulfill the following requirements. The ability to accept models written in VHDL, Verilog or the C languages. The ability to propagate faults through any model type. The ability to create experiment scenarios efficiently without generating every possible combination of variables. The ability to accept adversity of fault models beyond the single stuck-at model. Major development has been done to develop a parser that can accept models written in various languages. This work has generated considerable attention from other universities and industry for its flexibility and usefulness. The parser uses LEXX and YACC to parse Verilog and C. We have also utilized our industrial partnership with Alternative System's Inc. to import vhdl into our simulator. For multilevel simulation, we needed to modify the simulator architecture to accept models that contained multiple outputs. This enabled us to accept behavioral components. The next major accomplishment was the addition of "functional fault models". Functional fault models change the behavior of a gate or model. For example, a bridging fault can make an OR gate behave like an AND gate. This has applications beyond fault simulation. This modeling flexibility will make the simulator more useful for doing verification and model comparison. For instance, two or more versions of an ALU can be comparatively simulated in a single execution. The results will show where and how the models differed so that the performance and correctness of the models may be evaluated. A considerable amount of time has been dedicated to validating the simulator performance on larger models provided by industry and other universities.
Windblown dust emissions are controlled by near-surface wind speed and sediment erodibility, the latter modulated by hydroclimate and land-use conditions. Accurate representations of these drivers are critical for reproducing historical dust variability and projecting future dust changes in Earth system models (ESMs). This study examines the discrepancies among 21 ESMs in the relative importance of wind speed versus five hydroclimate drivers in explaining the historical (1980–2014) variability of dust emissions from global drylands. In hyperarid areas, models show poor agreement in the simulated dust variability, with only 9 % out of 210 inter-model comparisons exhibiting significant positive correlations. In contrast, arid and semiarid areas exhibit a dual pattern driven by a “double-edged sword” effect of land surface memory: models with coherent hydroclimate variability show better agreement, whereas those with divergent hydroclimate representations show larger disagreement. While the ESMs capture the dominant role of wind speed in hyperarid areas, they diverge markedly in the relative contributions of wind and hydroclimate drivers in arid and semiarid areas. Replacing the Zender et al. (2003) dust scheme with the Kok et al. (2014) scheme in CESM and E3SM generally strengthens hydroclimate influences while reducing wind speed contributions to simulated dust variability. MERRA-2 reanalysis produces stronger wind influences than most ESMs across all dryland regions. These results underscore the need for improved near-surface wind simulations in hyperarid areas and more realistic land surface and hydroclimate representations in arid and semiarid areas to reduce uncertainties in global dust emission simulations.
The effect of acoustic coupling on random and harmonic plate vibrations is studied using two numerical models. In the coupled model, the plate response is obtained by integration of the nonlinear plate equation coupled with the nonlinear Euler equations for the surrounding acoustic fluid. In the uncoupled model, the nonlinear plate equation with an equivalent linear viscous damping term is integrated to obtain the response of the plate subject to the same excitation field. For a low-level, narrow-band excitation, the two models predict the same plate response spectra. As the excitation level is increased, the response power spectrum predicted by the uncoupled model becomes broader and more shifted towards the high frequencies than that obtained by the coupled model. In addition, the difference in response between the coupled and uncoupled models at high frequencies becomes larger. When a high intensity harmonic excitation is used, causing a nonlinear plate response, both models predict the same frequency content of the response. However, the level of the harmonics and subharmonics are higher for the uncoupled model. Comparisons to earlier experimental and numerical results show that acoustic coupling has a significant effect on the plate response at high excitation levels. Its absence in previous models may explain the discrepancy between predicted and measured responses.
The effect of acoustic coupling on random and harmonic plate vibrations is studied using two numerical models. In the coupled model, the plate response is obtained by integration of the nonlinear plate equation coupled with the nonlinear Euler equations for the surrounding acoustic fluid. In the uncoupled model, the nonlinear plate equation with an equivalent linear viscous damping term is integrated to obtain the response of the plate subject to the same excitation field. For a low-level, narrow-band excitation, the two models predict the same plate response spectra. As the excitation level is increased, the response power spectrum predicted by the uncoupled model becomes broader and more shifted towards the high frequencies than that obtained by the coupled model. In addition, the difference in response between the coupled and uncoupled models at high frequencies becomes larger. When a high intensity harmonic excitation is used, causing a nonlinear plate response, both models predict the same frequency content of the response. However, the level of the harmonics and subharmonics are higher for the uncoupled model. Comparisons to earlier experimental and numerical results show that acoustic coupling has a significant effect on the plate response at high excitation levels. Its absence in previous models may explain the discrepancy between predicted and measured responses.
Climate policy in the United States is currently guided by public-private partnerships and actions at the local and state levels. This mitigation strategy is made up of programs that focus on energy efficiency, renewable energy, agricultural practices and implementation of technologies to reduce greenhouse gases. How will policy makers know if these strategies are working, particularly at the scales at which they are being implemented? The NASA Carbon Monitoring System (CMS) will provide information on carbon dioxide fluxes derived from observations of earth's land, ocean and atmosphere used in state of the art models describing their interactions. This new modeling system could be used to assess the impact of specific policy interventions on CO2 reductions, enabling an iterative, results-oriented policy process. In January of 2012, the CMS team held a meeting with carbon policy and decision makers in Washington DC to describe the developing modeling system to policy makers. The NASA CMS will develop pilot studies to provide information across a range of spatial scales, consider carbon storage in biomass, and improve measures of the atmospheric distribution of carbon dioxide. The pilot involves multiple institutions (four NASA centers as well as several universities) and over 20 scientists in its work. This pilot study will generate CO2 flux maps for two years using observational constraints in NASA's state-of -the-art models. Bottom-up surface flux estimates will be computed using data-constrained land and ocean models; comparison of the different techniques will provide some knowledge of uncertainty in these estimates. Ensembles of atmospheric carbon distributions will be computed using an atmospheric general circulation model (GEOS-5), with perturbations to the surface fluxes and to transport. Top-down flux estimates will be computed from observed atmospheric CO2 distributions (ACOS/GOSAT retrievals) alongside the forward-model fields, in conjunction with an inverse approach based on the CO2 model of GEOS ]Chem. The forward model ensembles will be used to build understanding of relationships among surface flux perturbations, transport uncertainty and atmospheric carbon concentration. This will help construct uncertainty estimates and information on the true spatial resolution of the top-down flux calculations. The relationship between the top-down and bottom-up flux distributions will be documented. Because the goal of NASA CMS is to be policy relevant, the scientists involved in the flux modeling pilot need to understand and be focused on the needs of the climate policy and decision making community. If policy makers are to use CMS products, they must be aware of the modeling effort and begin to design policies that can be evaluated with information. Improving estimates of carbon sequestered in forests, for example, will require information on the spatial variability of forest biomass that is far more explicit than is presently possible using only ground observations. Carbon mitigation policies being implemented by cities around the United States could be designed with the CMS data in mind, enabling sequential evaluation and subsequent improvements in incentives, structures and programs. The success of climate mitigation programs being implemented in the United States today will hang on the depth of the relationship between scientists and their policy and decision making counterparts. Ensuring that there is two-way communication between data providers and users is important for the success both of the policies and the scientific products meant to support them..
Active galaxies are shown to account for the observed gamma ray background radiation if a steepening of the spectra above about 100 keV is present. An analytical model is discussed in which protons undergo Fermi acceleration at a shock in a spherical accretion flow onto a massive black hole. Relativistic protons with power law spectra, nuclear interactions producing gamma rays from neutal pion decay and electrons from pion-mu meson-electron decay, with a power law spectrum above several hundred MeV, synchrotron and inverse Compton losses steepening the electron spectrum, a photon spectrum close to the pion gamma spectrum and a high-energy gamma ray spectrum steepened by photon-photon pair production interactions with X rays are covered in the model. Comparisons are made with HEAO 2 data on active galaxies, which have estimated luminosities and radii consistent with the compactness necessary for producing the steepening predicted by the model. The active galaxies spectra would be described by a spherical accretion-shock model.
Current turbulence models tend to give too early and too short a length of flow transition to turbulence, and hence fail to predict flow separation induced by the adverse pressure gradients and streamline flow curvatures. Our discussion will focus on the development and validation of transition models. The baseline data for model comparisons are the T3 series, which include a range of free-stream turbulence intensity and cover zero-pressure gradient to aft-loaded turbine pressure gradient flows. The method will be based on the conditioned N-S equations and a transport equation for the intermittency factor. First, several of the most popular 2-equation models in predicting flow transition are examined: k-e [Launder-Sharina], k-w [Wilcox], Lien-Leschiziner and SST [Menter] models. All models fail to predict the onset and the length of transition, even for the simplest flat plate with zero-pressure gradient(T3A). Although the predicted onset position of transition can be varied by providing different inlet turbulent energy dissipation rates, the appropriate inlet conditions for turbulence quantities should be adjusted to match the decay of the free-stream turbulence. Arguably, one may adjust the low-Reynolds-number part of the model to predict transition. This approach has so far not been very successful. However, we have found that the low-Reynolds-number model of Launder and Sharma [1974], which is an improved version of Jones and Launder [1972] gave the best overall performance. The Launder and Sharma model was designed to capture flow re-laminarization (a reverse of flow transition), but tends to give rise to a too early and too fast transition in comparison with the physical transition. The three test cases were for flows with zero pressure gradient but with different free-stream turbulent intensities. The same can be said about the model when considering flows subject to pressure gradient(T3C1). To capture the effects of transition using existing turbulence models, one approach is to make use of the concept of the intermittency to predict the flow transition. It was originally based on the intermittency distribution of Narasimha [1957], and then gradually evolved into a transport equation for the intermittency factor. Gostelow and associates [1994,1995] have made some improvements to Narasimha's method in an attempt to account for both favorable and adverse pressure gradients. Their approach is based on a linear, explicit combination of laminar and turbulent solutions. This approach fails to predict the overshoot of the skin friction on a flat plate near the end of transition zone, even though the length of transition is well predicted. The major flaw of Gostelow's approach is that it assumes the non-turbulent part being the laminar solution and the turbulent part being the turbulent solution and they do not interact across the transitional region. The technique in condition averaging the flow equations in intermittent flows was first introduced by Libby [1975] and Dopazo [1977] and further refined by Dick and associates [1988, 1996]. This approach employs two sets of transport equations for the non-turbulent part and the other for the turbulent part. The advantage of this approach is that it allows the interaction of non-turbulent and turbulent velocities through the introduction of additional source terms in the continuity and momentum equations for the non-turbulent and turbulent velocities. However, the strong coupling of the two sets of equations has caused some numerical difficulties, which requires special attention. The prediction of the skin friction can be improved by this approach via the implicit coupling of non-turbulent and turbulent velocity flelds. Another improvement of the interrmittency model can be further made by allowing the intermittency to vary in the cross-stream direction. This is one step prior to testing any proposal for the transport equation for the intermittency factor. Instead of solving the transport equation for the intermittency factor, the distribution for the intermittency factor is prescribed by Klebanoff's empirical formula [1955]. The skin friction is very well predicted by this new modification, including the overshoot of the profile near the end of the transition zone. The outcome of this study is very encouraging since it indicates that the proper description of the intermittency distribution is the key to the success of the model prediction. This study will be used to guide us on the modelling of the intermittency transport equation.