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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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Mariner IV models of three Mars atmospheric layers analogous to terrestrial E, F-1 and F-2 layers, considering relative mass densities, temperatures, carbon dioxide photodissociation and ionization profile
The comparative modeling of p(+)n and n(+)p indium phosphide solar cell structures is studied using a numerical program PC-1D. The optimal design study has predicted that the p(+)n structure offers improved cell efficiencies as compared to n(+)p structure, due to higher open-circuit voltage. The various cell material and process parameters to achieve the maximum cell efficiencies are reported. The effect of some of the cell parameters on InP cell I-V characteristics was studied. The available radiation resistance data on n(+)p and p(+)p InP solar cells are also critically discussed.
Simulation modeling can play a number of important roles in large-scale ecosystem studies, including synthesis of patterns and changes in carbon and nutrient cycling dynamics, scaling up to regional estimates, and formulation of testable hypotheses for process studies. Recent comparative studies have shown that ecosystem models of soil trace gas exchange with the atmosphere are evolving into several distinct simulation approaches. Different levels of detail exist among process models in the treatment of physical controls on ecosystem nutrient fluxes and organic substrate transformations leading to gas emissions. These differences are is in part from distinct objectives of scaling and extrapolation. Parameter requirements for initialization scalings, boundary conditions, and time-series driven therefore vary among ecosystem simulation models, such that the design of field experiments for integration with modeling should consider a consolidated series of measurements that will satisfy most of the various model requirements. For example, variables that provide information on soil moisture holding capacity, moisture retention characteristics, potential evapotranspiration and drainage rates, and rooting depth appear to be of the first order in model evaluation trials for tropical moist forest ecosystems. The amount and nutrient content of labile organic matter in the soil, based on accurate plant production estimates, are also key parameters that determine emission model response. Based on comparative model results, it is possible to construct a preliminary evaluation matrix along categories of key diagnostic parameters and temporal domains. Nevertheless, as large-scale studied are planned, it is notable that few existing models age designed to simulate transient states of ecosystem change, a feature which will be essential for assessment of anthropogenic disturbance on regional gas budgets, and effects of long-term climate variability on biosphere-atmosphere exchange.
Solar protons are the primary source of ionizing radiation for certain missions. Several models of these solar energetic proton events exist, giving different results. We compare three models with satellite data to assess these differences.
Using a computer program to model the earth's horizon and to duplicate the signal processing procedure employed by the ESA (Earth Sensor Assembly), errors due to radiance variation have been computed for a particular time of the year. Errors actually occurring in flight at the same time of year are inferred from integrated rate gyro data for a satellite of the TIROS series of NASA weather satellites (NOAA-A). The predicted performance is compared with actual flight history.
Our ability to extract information from the spectra of stars depends on reliable models of stellar atmospheres and appropriate techniques for spectral synthesis. Various model codes and strategies for the analysis of stellar spectra are available today. Aims. We aim to compare the results of deriving stellar parameters using different atmosphere models and different analysis strategies. The focus is set on high-resolution spectroscopy of cool giant stars. Methods. Spectra representing four cool giant stars were made available to various groups and individuals working in the area of spectral synthesis, asking them to derive stellar parameters from the data provided. The results were discussed at a workshop in Vienna in 2010. Most of the major codes currently used in the astronomical community for analyses of stellar spectra were included in this experiment. Results. We present the results from the different groups, as well as an additional experiment comparing the synthetic spectra produced by various codes for a given set of stellar parameters. Similarities and differences of the results are discussed. Conclusions. Several valid approaches to analyze a given spectrum of a star result in quite a wide range of solutions. The main causes for the differences in parameters derived by different groups seem to lie in the physical input data and in the details of the analysis method. This clearly shows how far from a definitive abundance analysis we still are.
The coordination of the modeling and field efforts for an Intensive Field Campaign (IFC) may resemble the chicken and egg dilemma. This session's theme advocates that early and proactive involvement by modeling teams can produce a scientific and operational benefit for the IFC and Experiment. This talk will provide some examples and suggestions originating from the NASA funded IFC's of the FIFE First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment, Oregon Transect Ecosystem Research (OTTER) and predominately Boreal Ecosystem-Atmosphere Study (BOREAS) Experiments. In February 1994 and prior to the final selection of the BOREAS study sites, a group of funded BOREAS investigators agreed to run their models with data for five community types representing the proposed tower flux sites. All participating models were given identical initial values and boundary conditions and driven with identical climate data. The objectives of the intercomparison exercise were: 1) compare simulation results of participating terrestrial, hydrological, and atmospheric models over selected time frames; 2) learn about model behavior and sensitivity to estimated boreal site and vegetation definitions; 3) prioritize BOREAS field data collection efforts supporting modeling studies; 4) identify individual model deficiencies as early as possible. Out of these objectives evolved some important coordination and science issues for the BOREAS Experiment that can be generalized to IFCs and long term archiving of the data. Some problems are acceptable because they are endemic to maintaining fair and open competition prior to the peer review process. Others are logistical and addressable through application of planning, management, and information sciences. This investigator has identified one source of measurement and model incompatibility that is manifest in the IFC scaling approach. Although intuitively obvious, scaling problems are already more formally defined in the Geography literature. An example of the scaling problem will be demonstrated with Vegetation/Ecosystem Mapping and Analysis Project (VEMAP) and OTTER data.
Latitude-height cross sections of the Eliassen-Palm (ep) flux, its divergence, the residual mean meridional circulation as well as conventional eddy and mean flow fields are computed using both observational and general circulation model data.
We present D-SHIELD, a challenging climate science application to plan coordinated measurements (observations) for a constellation of satellites, each containing two different sensors, each with 61 pointing angle options. The L-band and P-band radar sensors collect data fed into a soil moisture model which tracks and predicts soil moisture across 1.67 million Ground Positions (GP). Soil moisture is an important predictor of wildfires, and then a predictor of floods, landslides and debris flow after a fire. Each measurement covers multiple GP due to the sensor footprint. Each GP has a "model error" which represents the uncertainty of the the soil moisture state prediction. Model error changes at different rates for each GP as the time since last observation increases and after significant events like rain. The planner's goal is to select measurements which maximize soil moisture model improvement (reduce model uncertainty). This problem is combinatorically explosive, involving many degrees of freedom for planner choices. Good domain heuristics can find solutions within a reasonable time for our application needs but cannot be proven optimal. In this paper we compare two different planning approaches to this problem: Dynamic Constraint Processing (DCP) and Mixed Integer Linear Programming (MILP). We match inputs and metrics for both DCP and MILP algorithms to enable a direct apples-to-apples comparison. We demonstrate and discuss the trades between DCP flexibility and performance vs. MILP's promise of provable optimality.
Observational evidence suggests that of the tritium produced during nuclear bomb tests that has already reached the ocean, more than twice as much arrived through vapor impact as through precipitation. In the present study, the Goddard Institute for Space Studies 8 x 10 deg atmospheric general circulation model is used to simulate tritium transport from the upper atmosphere to the ocean. The simulation indicates that tritium delivery to the ocean via vapor impact is about equal to that via precipitation. The model result is relatively insensitive to several imposed changes in tritium source location, in model parameterizations, and in model resolution. Possible reasons for the discrepancy are explored.
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The light curve of Supernova 1993J is calculated using two computational radiation transport approaches. The two approaches are represented by the computer codes STELLA and EDDINGTON. The emphasis is on the shock breakout and the photometry in the U, B and V bands during the first 120 days of the supernova. The STELLA model includes implicit hydrodynamics and is able to model early supernova evolution before the expansion is homologous. The STELLA model employs multi-group photonics and is able to follow the radiation as it decouples from the matter. The EDDINGTON code uses an algorithm for integrating the transport equation which assumes homologous expansion and uses a finer frequency resolution. The agreement between the two codes is considered to be satisfactory only in the case where compatible physical assumptions are made concerning the opacity. The assumptions are justified. The continuum spectrum for SN 1993J is predicted near the shock breakout to be superior to that predicted by standard single energy group hydrocodes. The uncertainties involved in current time dependent models of supernova light curves are discussed.
Model simulations have been used to analyze the factors influencing ozone loss during the 1999-2000 and 2002-2003 js. For both winters, the evolution of the Arctic vortex from November to April has been simulated using a trajectory-based microphysical and photochemical model. Extensive PSC formation and strong ozone depletion are evident in both winters. However, the ozone loss begins earlier in the 2002-2003 winter, with significant ozone depletion by early January. Analysis of the model results shows that during December 2002 not only cold temperatures but also the vortex structure was critical, allowing PSC-processed air parcels to experience significant solar exposure. The resultant ozone loss can be differentiated from ozone loss that occurs in the springtime, in particular because of the continued exposure to PSCs. For example, chlorine reactivation by the PSCs causes ozone loss to be insensitive to denitrification. Therefore, diagnosing the extent of ozone loss early in the winter is critical In understanding the overall winter-long ozone depletion.
Probabilistic methods are presented for characterizing and quantifying uncertainties in models and model predictions. Techniques are given for constructing specific uncertainty distributions based on available information. Alternative techniques are given for propagating uncertainties in model inputs to obtain the uncertainty in the model result or prediction. Bayesian techniques are also described for utilizing data and information to update and revise model results and predictions. The focus is on applications with numerous specific examples given. The use of data to revise Micrometeoroid and Orbital Debris (MMOD) risk prediction models are among the examples given.
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This viewgraph presentation provides a brief review of two-equation eddy-viscosity models (TEM's) from the perspective of applied CFD. It provides objective assessment of both well-known and newer models, compares model predictions from various TEM's with experiments, identifies sources of modeling error and gives historical perspective of their effects on model performance and assessment, and recommends directions for future research on TEM's.
Comparative evaluation of interference factor corrections in wind tunnel tests on vertical takeoff aircraft models
Five years of meteorological and hydrological data from a typical New England watershed where winter snow cover is significant were used to drive and validate two off-line land surface schemes suitable for use in the Goddard Institute for Space Studies (GISS) general circulation model (GCM): a baseline scheme that does not model the physics of a snowpack and therefore, neglects the insulating properties of snow cover; and a modified scheme in which a three-layer snowpack is modeled. Comparing baseline model results with validation data reveals several model deficiencies. Surface radiation temperatures could not adequately be modeled and the ground froze to unreasonable depths. Furthermore, because of ground cooling resulting from large surface heat fluxes to the atmosphere from the uninsulated surface, deeper model layers did not unfreeze until midsummer. As such, the normal hydrologic processes of runoff, ground water infiltration, and movement, etc., are compromised for a good part of the year. With the inclusion of a simple three-layer snow model into the baseline model, not only are the ground and surface radiation temperatures adequately modeled but all the features of snowpack ripening that characterize pack growth/ablation are simulated.