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Report discusses mathematical modeling to predict performance and lifetime of spacecraft power source that is integrated combination of nuclear-fission reactor and thermionic converters. Details of nuclear reaction, thermal conditions in core, and thermionic performance combined with model of swelling of fuel.
A method is described for obtaining optimal attitude estimation algorithms for spacecraft lacking attitude rate measurement devices (rate gyros), and then demonstrated using actual flight data from the Solar, Anomalous, and Magnetospheric Particle Explorer (SAMPEX) spacecraft. SAMPEX does not have on-board rate sensing, and relies on sun sensors and a three-axis magnetometer for attitude determination. Problems arise since typical attitude estimation is accomplished by filtering measurements of both attitude and attitude rates. Rates are nearly always sampled much more densely than are attitudes. Thus, the absence/loss of rate data normally reduces both the total amount of data available and the sampling density (in time) by a substantial fraction. As a result, the sensitivity of the estimates to model uncertainty and to measurement noise increases. In order to maintain accuracy in the attitude estimates, there is increased need for accurate models of the rotational dynamics. The proposed approach is based on the minimum model error (MME) optimal estimation strategy, which has been successfully applied to estimation of poorly modeled dynamic systems which are relatively sparsely and/or noisily measured. The MME estimates may be used to construct accurate models of the system dynamics (i.e. perform system model identification). Thus, an MME-based approach directly addresses the problems created by absence of attitude rate measurements.
The initial assembly of Space Station Freedom involves the Space Shuttle, its Remote Manipulation System (RMS) and the evolving Space Station Freedom. The dynamics of this coupled system involves both the structural and the control system dynamics of each of these components. The modeling and analysis of such an assembly is made even more formidable by kinematic and joint nonlinearities. The current practice of modeling such flexible structures is to use finite element modeling in which the mass and interior dynamics is ignored between thousands of nodes, for each major component. The model characteristics of only tens of modes are kept out of thousands which are calculated. The components are then connected by approximating the boundary conditions and inserting the control system dynamics. In this paper continuum models are used instead of finite element models because of the improved accuracy, reduced number of model parameters, the avoidance of model order reduction, and the ability to represent the structural and control system dynamics in the same system of equations. Dynamic analysis of linear versions of the model is performed and compared with finite element model results. Additionally, the transfer matrix to continuum modeling is presented.
Model calculations have been made to simulate the effect of atmospheric ozone and geographical as well as meteorological parameters on solar UV radiation reaching the ground. Total ozone values as measured by Dobson spectrophotometer and Brewer spectrometer as well as turbidity were used as input to the model calculation. The performance of the model was tested by spectroradiometric measurements of solar global UV radiation at Potsdam. There are small differences that can be explained by the uncertainty of the measurements, by the uncertainty of input data to the model and by the uncertainty of the radiative transfer algorithms of the model itself. Some effects of solar radiation to the biosphere and to air chemistry are discussed. Model calculations and spectroradiometric measurements can be used to study variations of the effective radiation in space in space time. The comparability of action spectra and their uncertainties are also addressed.
Unsteady flowfields of a two-dimensional oscillating wing are calculated using an implicit, finite-difference, Navier-Stokes numerical scheme using five widely used turbulence models. The objective of this study is to identify an appropriate turbulence model for accurate simulation of three-dimensional dynamic stall. Three unsteady flow conditions corresponding to attached flow, light-stall, and deep-stall of an oscillating wing experiment were chosen as test cases for computations. Results of unsteady airload hysteresis curves, harmonics of unsteady pressures, and instantaneous flow pictures are presented. Comparison of unsteady airloads with experiment show that all models are deficient in some sense and not a single model predicts all airloads consistently and in agreement with experiment for all flow conditions. For the attached flow condition, the Renormalization Group Theory (RNG), the Johnoson-King (J-K), and the Spalart-Allmaras (S-A) models have better performance. The Baldwin-Lomax (B-L) and the Baldwin-Barth (B-B) models fair poorly. At the light-stall condition, the results for the RNG, the J-K, and S-A models are in agreement with experiment for the upstroke but they all over predict the separation shown by the experiment and therefore have bigger hysteresis loops than experimental results. The B-B model results are also in good agreement for upstroke but have poor lift hysteresis for downstroke. It has superior drag and pitching-moment predictions. For deep-stall conditions, the airloads for the RNG, the B -B, and the S-A models have fair agreement with experiment, but the B-B model performed better at the extreme deep-stall condition. Overall, the RNG model provides significant improvement over the B-L model in all flow regimes with no additional computational cost. The Baldwin-Barth model is the most expensive of the models considered here, costing about 2.5 times that of the Baldwin-Lomax model. Finally, a brief discussion of the effects of grid density, time-step size, and numerical dissipation on the unsteady solutions are also presented.
We describe recent work on automation and support of science experiments on the Space Shuttle. PI-in-a-Box, the first interactive expert system for scientific support, was flown onboard STS-58 in October 1993. It was designed to help astronauts perform better science in space by providing expert-level advice in real-time. The system provides help with 'technician' tasks such as data acquisition, data quality monitoring, and diagnostic, troubleshooting and repair. The system also performs 'expert' reasoning on the scientific model and experiment steps scheduling. It can make scheduling recommendations based on hardware status, time available, and agreement between predictions and flight data. The system was successfully deployed and used throughout the mission. Most of the 'technician' skills of the system were used with success. The scientific model study performed correctly, but we believe the results were not exploited by the astronauts because of Spacelab operational pressures. Also, portions of the system were designed around rigid schedule constraints that were essentially relaxed during the mission. This version was tailored to a specific vestibular experiment known as the 'rotating dome'. We are currently expanding our effort in various scientific (other life and microgravity sciences experiments) and technological directions (integrated telescience, astronaut science advisor, and autonomous control).
We describe recent work on automation and support of science experiments on the Space Shuttle. PI-in-a-Box, the first interactive expert system for scientific support, was flown onboard STS-58 in October 1993. It was designed to help astronauts perform better science in space by providing expert-level advice in real-time. The system provides help with "technician" tasks such as data acquisition, data quality monitoring, and diagnostic, troubleshooting and repair. The system also performs "expert" reasoning on the scientific model and experiment steps scheduling. It can make scheduling recommendations based on hardware status, time available, and agreement between predictions and flight data. The system was successfully deployed and used throughout the mission. Most of the "technician" skills of the system were used with success. The scientific model study performed correctly, but we believe the results were not exploited by the astronauts because of Spacelab operational pressures. Also, portions of the system were designed around rigid schedule constraints that were essentially relaxed during the mission. This version was tailored to a specific vestibular experiment known as the "rotating dome". We are currently expanding our effort in various scientific (other life and microgravity sciences experiments) and technological directions (integrated telescience, astronaut science advisor, and autonomous control).
The importance of sea ice leads in the ice-ocean-atmosphere system lies in the fact that each of the boxes in the 'surface processes' interface in this diagram is closely linked to lead conditions. For example, heat, moisture and salt exchange between the Ocean and atmosphere within the ice pack occur nearly entirely through leads. The shear, divergence and convergence associated with lead formation and closure alter surface and basal roughness and topography, which in turn affects momentum transfer in the atmosphere and ocean boundary layers, and modifies the accumulation of snow on the ice surface, which then affects heat conduction and summertime albedo. In addition to providing openings for loss of heat and moisture fluxes to the atmosphere, leads absorb solar energy, which is used to melt ice and is transmitting to the underlying ocean. Given that leads dominate the ice-ocean interface in this manner, then it stands to reason that focusing on lead treatments within models can identify performance limitations of models and yield routes for significant improvements.
Space diversity performance is examined on the basis of radar modeling techniques. Radar-derived joint probability distributions are calculated for determining path attenuation and statistical formulation. The computational aspects of the model are discussed in terms of the data base, determining path length and converting statistics to other path angles. The results are presented in terms of prediction accuracy, predicted joint probability distributions, diversity gain, and the autocorrection function. When compared to other models, this model's rain-derived relative diversity gain shows good agreement.
CAD/CAE packages change on a continuous basis as the power of the tools increase to meet demands. End -users must adapt to new products as they come to market and replace legacy packages. CAE modeling has continued to evolve and is constantly becoming more detailed and complex. Though this comes at the cost of increased computing requirements Parallel processing coupled with appropriate hardware can minimize computation time. Users of Maya Thermal Model Generator (TMG) are faced with transitioning from NX I -deas to NX Space Systems Thermal (SST). It is important to understand what differences there are when changing software packages We are looking for consistency in results.
Projected performance requirements for cryogenic spacecraft sensor cooling systems which demand higher reliability and longer lifetimes are outlined. The gas/solid sorption refrigerator is viewed as a potential solution to cryogenic cooling needs. A software model of an entire gas sorption refrigerator system was developed. The numerical model, evaluates almost any combination and order of refrigerator components and any sorbent-sorbate pair or which the sorption isotherm data are available. Parametric curves for predicting system performance were generated for two types of refrigerators, a LaNi5-H2 absorption cooler and a Charcoal-N2 adsorption cooler. It is found that precooling temperature and heat exchanger effectiveness affect the refrigerator performance. It is indicated that gas sorption refrigerators are feasible for a number of space applications.
Airframe noise is a growing concern in the vicinity of airports because of population growth and gains in engine noise reduction that have rendered the airframe an equal contributor during the approach and landing phases of flight for many transport aircraft. The leading-edge-slat device of a typical high-lift system for transport aircraft is a prominent source of airframe noise. Two technologies have significant potential for slat noise reduction; the slat-cove filler (SCF) and the slat-gap filler (SGF). Previous work was done on a 2D section of a transport-aircraft wing to demonstrate the implementation feasibility of these concepts. Benchtop hardware was developed in that work for qualitative parametric study. The benchtop models were mechanized for quantitative measurements of performance. Computational models of the mechanized benchtop apparatus for the SCF were developed and the performance of the system for five different SCF assemblies is demonstrated.
The 45th Weather Squadron (45 WS) Launch Weather Officers use the 12-km resolution North American Mesoscale (NAM) model (MesoNAM) text and graphical product forecasts extensively to support launch weather operations. However, the actual performance of the model at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) has not been measured objectively. In order to have tangible evidence of model performance, the 45 WS tasked the Applied Meteorology Unit to conduct a detailed statistical analysis of model output compared to observed values. The model products are provided to the 45 WS by ACTA, Inc. and include hourly forecasts from 0 to 84 hours based on model initialization times of 00, 06, 12 and 18 UTC. The objective analysis compared the MesoNAM forecast winds, temperature and dew point, as well as the changes in these parameters over time, to the observed values from the sensors in the KSC/CCAFS wind tower network. Objective statistics will give the forecasters knowledge of the model's strength and weaknesses, which will result in improved forecasts for operations.
As Earth’s largest collection of freshwater, the Laurentian Great Lakes have enormous ecological and socio-economic value. Their basin has become a regional hotspot of climatic and limnological change, potentially threatening its vital natural resources. Consequentially, there is a need to assess the current state of climate models regarding their performance across the Great Lakes region and develop the next generation of high-resolution regional climate models to address complex limnological processes and lake-atmosphere interactions. In response to this need, the current paper focuses on the generation and analysis of a 20-member ensemble of 3-km National Aeronautics and Space Administration (NASA)-Unified Weather Research and Forecasting (NU-WRF) simulations for the 2014-2015 cold season. The study aims to identify the model’s strengths and weaknesses; optimal configuration for the region; and the impacts of different physics parameterizations, coupling to a 1D lake model, time-variant lake-surface temperatures, and spectral nudging. Several key biases are identified in the cold-season simulations for the Great Lakes region, including an atmospheric cold bias that is amplified by coupling to a 1D lake model but diminished by applying the Community Atmosphere Model radiation scheme and Morrison microphysics scheme; an excess precipitation bias; anomalously early initiation of fall lake turnover and subsequent cold lake bias; excessive and overly persistent lake ice cover; and insufficient evaporation over Lakes Superior and Huron. The research team is currently addressing these key limitations by coupling NU-WRF to a 3D lake model in support of the next generation of regional climate models for the critical Great Lakes Basin.
Cycle life requirements are very high for batteries used in aerospace applications in low Earth orbit. The data base required to establish confidence in a particular cell design is thus both extensive and expensive. Reliable accelerated cycle life testing and performance decay modeling represent attractive alternatives to real-time tests of cycle life. In light of certain long-term cycle life test results, this paper examines a very simple performance decay model developed earlier. Application of that model to available data demonstrates a rigid relationship between a battery's expected cycle life and the depth of discharge of cycling. Further, modeling analysis of the data suggests that a significantly improved cycle life can be obtained with advanced components, materials, and designs; and that cycle life can be reliably predicted from the results of accelerated testing.
Cycle life requirements are very high for batteries used in aerospace applications in low earth orbit. The data base required to establish confidence in a particular cell design is thus both extensive and expensive. Reliable accelerated cycle life testing and performance decay modeling represent attractive alternatives to real-time tests of cycle life. In light of certain long-term cycle life test results, this paper examines a very simple performance decay model developed earlier. Application of that model to available data demonstrates a rigid relationship between a battery's expected cycle life and the depth of discharge of cycling. Further, modeling analysis of the data suggests that a significantly improved cycle life can be obtained with advanced components, materials, and designs; and that cycle life can be reliably predicted from the results of accelerated testing.
The 45th Weather Squadron (45 WS) Launch Weather Officers (LWO's) use the 12-km resolution North American Mesoscale (NAM) model (MesoNAM) text and graphical product forecasts extensively to support launch weather operations. However, the actual performance of the model at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS) has not been measured objectively. In order to have tangible evidence of model performance, the 45 WS tasked the Applied Meteorology Unit (AMU; Bauman et ai, 2004) to conduct a detailed statistical analysis of model output compared to observed values. The model products are provided to the 45 WS by ACTA, Inc. and include hourly forecasts from 0 to 84 hours based on model initialization times of 00, 06, 12 and 18 UTC. The objective analysis compared the MesoNAM forecast winds, temperature (T) and dew pOint (T d), as well as the changes in these parameters over time, to the observed values from the sensors in the KSC/CCAFS wind tower network shown in Table 1. These objective statistics give the forecasters knowledge of the model's strengths and weaknesses, which will result in improved forecasts for operations.
Thermal deformations and stresses were studied in a silicon-carbide/aluminum filamentary composite at temperatures up to 370 C (700 F). Longitudinal and transverse thermal strains were measured with strain gages and a dilatometer. An elastoplastic micromechanical analysis based on a one-dimensional rule-of-mixtures model and an axisymmetric two-material composite cylinder model was performed. It was established that beyond a critical temperature thermal strains become nonlinear with decreasing longitudinal and increasing transverse thermal-expansion coefficients. This behavior was attributed to the plastic stresses in the aluminum matrix above the critical temperature. An elastoplastic analysis of both micromechanical models was performed to determine the stress distributions and thermal deformation in the fiber and matrix of the composite. While only axial stresses can be determined by the rule-of-mixtures model, the complete triaxial state of stress is established by the composite cylinder model. Theoretical predictions for the two thermal-expansion coefficients were in satisfactory agreement with experimental results.