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At least 163 records · Page 9

Statistical Analysis of CMC Constituent and Processing Data

Ceramic Matrix Composites (CMCs) are the next "big thing" in high-temperature structural materials. In the case of jet engines, it is widely believed that the metallic superalloys currently being utilized for hot structures (combustors, shrouds, turbine vanes and blades) are nearing their potential limits of improvement. In order to allow for increased turbine temperatures to increase engine efficiency, material scientists have begun looking toward advanced CMCs and SiC/SiC composites in particular. Ceramic composites provide greater strength-to-weight ratios at higher temperatures than metallic alloys, but at the same time require greater challenges in micro-structural optimization that in turn increases the cost of the material as well as increases the risk of variability in the material s thermo-structural behavior. to model various potential CMC engine materials and examines the current variability in these properties due to variability in component processing conditions and constituent materials; then, to see how processing and constituent variations effect key strength, stiffness, and thermal properties of the finished components. Basically, this means trying to model variations in the component s behavior by knowing what went into creating it. inter-phase and manufactured by chemical vapor infiltration (CVI) and melt infiltration (MI) were considered. Examinations of: (1) the percent constituents by volume, (2) the inter-phase thickness, (3) variations in the total porosity, and (4) variations in the chemical composition of the Sic fiber are carried out and modeled using various codes used here at NASA-Glenn (PCGina, NASALife, CEMCAN, etc...). The effects of these variations and the ranking of their respective influences on the various thermo-mechanical material properties are studied and compared to available test data. The properties of the materials as well as minor changes to geometry are then made to the computer model and the detrimental effects observed using statistical analysis software. The ultimate purpose of this study is to determine what variations in material processing can lead to the most critical changes in the materials property. The work I have taken part in this summer explores, in general, the key properties needed In this study SiC/SiC composites of varying architectures, utilizing a boron-nitride (BN)

Fornuff, Jonathan↗

HASA: Hypersonic Aerospace Sizing Analysis for the Preliminary Design of Aerospace Vehicles

A review of the hypersonic literature indicated that a general weight and sizing analysis was not available for hypersonic orbital, transport, and fighter vehicles. The objective here is to develop such a method for the preliminary design of aerospace vehicles. This report describes the developed methodology and provides examples to illustrate the model, entitled the Hypersonic Aerospace Sizing Analysis (HASA). It can be used to predict the size and weight of hypersonic single-stage and two-stage-to-orbit vehicles and transports, and is also relevant for supersonic transports. HASA is a sizing analysis that determines vehicle length and volume, consistent with body, fuel, structural, and payload weights. The vehicle component weights are obtained from statistical equations for the body, wing, tail, thermal protection system, landing gear, thrust structure, engine, fuel tank, hydraulic system, avionics, electral system, equipment payload, and propellant. Sample size and weight predictions are given for the Space Shuttle orbiter and other proposed vehicles, including four hypersonic transports, a Mach 6 fighter, a supersonic transport (SST), a single-stage-to-orbit (SSTO) vehicle, a two-stage Space Shuttle with a booster and an orbiter, and two methane-fueled vehicles.

Harloff, Gary J.↗

Hypersonic aerospace sizing analysis for the preliminary design of aerospace vehicles

A review of the hypersonic literature indicated that a general weight and sizing analysis was not available for hypersonic orbital, transport, and fighter vehicles. The objective here is to develop such a method for the preliminary design of aerospace vehicles. This report describes the developed methodology and provides examples to illustrate the model, entitled the Hypersonic Aerospace Sizing Analysis (HASA). It can be used to predict the size and weight of hypersonic single-stage and two-stage-to-orbit vehicles and transports, and is also relevant for supersonic transports. HASA is a sizing analysis that determines vehicle length and volume, consistent with body, fuel, structural, and payload weights. The vehicle component weights are obtained from statistical equations for the body, wing, tail, thermal protection system, landing gear, thrust structure, engine, fuel tank, hydraulic system, avionics, electrical system, equipment payload, and propellant. Sample size and weight predictions are given for the Space Shuttle orbiter and other proposed vehicles, including four hypersonic transports, a Mach 6 fighter, a supersonic transport (SST), a single-stage-to-orbit (SSTO) vehicle, a two-stage Space Shuttle with a booster and an orbiter, and two methane-fueled vehicles.

Harloff, Gary J.↗

Thermochemical Ablation Analysis of the Orion Heatshield

The Orion Multi-Purpose Crew Vehicle will one day carry astronauts to the Moon and beyond, and Orion's heatshield is a critical component in ensuring their safe return to Earth. The Orion heatshield is the structural component responsible for absorbing the intense heating environment caused by re-entry to Earth's atmosphere. The heatshield is primarily composed of Avcoat, an ablative material that is consumed during the re-entry process. Ablation is primarily characterized by two processes: pyrolysis and recession. The decomposition of in-depth virgin material is known as pyrolysis. Recession occurs when the exposed surface of the heatshield reacts with the surrounding flow. The Orion heatshield design was changed from an individually filled Avcoat honeycomb to a molded block Avcoat design. The molded block Avcoat heatshield relies on an adhesive bond to keep it attached to the capsule. In some locations on the heatshield, the integrity of the adhesive bond cannot be verified. For these locations, a mechanical retention device was proposed. Avcoat ablation was modelled in CHAR and the in-depth virgin material temperatures were used in a Thermal Desktop model of the mechanical retention device. The retention device was analyzed and shown to cause a large increase in the maximum bondline temperature. In order to study the impact of individual ablation modelling parameters on the heatshield sizing process, a Monte Carlo simulation of the sizing process was proposed. The simulation will give the sensitivity of the ablation model to each of its input parameters. As part of the Monte Carlo simulation, statistical uncertainties on material properties were required for Avcoat. Several properties were difficult to acquire uncertainties for: the pyrolysis gas enthalpy, non-dimensional mass loss rate (B´c), and Arrhenius equation parameters. Variability in the elemental composition of Avcoat was used as the basis for determining the statistical uncertainty in pyrolysis gas enthalpy and B´c. A MATLAB program was developed to allow for faster, more accurate and automated computation of Arrhenius reaction parameters. These parameters are required for a material model to be used in the CHAR ablation analysis program. This MATLAB program, along with thermogravimetric analysis (TGA) data, was used to generate uncertainties on the Arrhenius parameters for Avcoat. In addition, the TGA fitting program was developed to provide Arrhenius parameters for the ablation model of the gap filler material, RTV silicone.

Sixel, William↗

Statistical Methods for Rapid Aerothermal Analysis and Design Technology

The cost and safety goals for NASA's next generation of reusable launch vehicle (RLV) will require that rapid high-fidelity aerothermodynamic design tools be used early in the design cycle. To meet these requirements, it is desirable to establish statistical models that quantify and improve the accuracy, extend the applicability, and enable combined analyses using existing prediction tools. The research work was focused on establishing the suitable mathematical/statistical models for these purposes. It is anticipated that the resulting models can be incorporated into a software tool to provide rapid, variable-fidelity, aerothermal environments to predict heating along an arbitrary trajectory. This work will support development of an integrated design tool to perform automated thermal protection system (TPS) sizing and material selection.

Morgan, Carolyn↗

Physics Based Modeling and Rendering of Vegetation in the Thermal Infrared

We outline a procedure for rendering physically-based thermal infrared images of simple vegetation scenes. Our approach incorporates the biophysical processes that affect the temperature distribution of the elements within a scene. Computer graphics plays a key role in two respects. First, in computing the distribution of scene shaded and sunlit facets and, second, in the final image rendering once the temperatures of all the elements in the scene have been computed. We illustrate our approach for a simple corn scene where the three-dimensional geometry is constructed based on measured morphological attributes of the row crop. Statistical methods are used to construct a representation of the scene in agreement with the measured characteristics. Our results are quite good. The rendered images exhibit realistic behavior in directional properties as a function of view and sun angle. The root-mean-square error in measured versus predicted brightness temperatures for the scene was 2.1 deg C.

Smith, J. A.↗

The Impact of the Assimilation of AIRS Radiance Measurements on Short-term Weather Forecasts

Advanced spaceborne instruments have the ability to improve the horizontal and vertical characterization of temperature and water vapor in the atmosphere through the explicit use of hyperspectral thermal infrared radiance measurements. The incorporation of these measurements into a data assimilation system provides a means to continuously characterize a three-dimensional, instantaneous atmospheric state necessary for the time integration of numerical weather forecasts. Measurements from the National Aeronautics and Space Administration (NASA) Atmospheric Infrared Sounder (AIRS) are incorporated into the gridpoint statistical interpolation (GSI) three-dimensional variational (3D-Var) assimilation system to provide improved initial conditions for use in a mesoscale modeling framework mimicking that of the operational North American Mesoscale (NAM) model. The methodologies for the incorporation of the measurements into the system are presented. Though the measurements have been shown to have a positive impact in global modeling systems, the measurements are further constrained in this system as the model top is physically lower than the global systems and there is no ozone characterization in the background state. For a study period, the measurements are shown to have positive impact on both the analysis state as well as subsequently spawned short-term (0-48 hr) forecasts, particularly in forecasted geopotential height and precipitation fields. At 48 hr, height anomaly correlations showed an improvement in forecast skill of 2.3 hours relative to a system without the AIRS measurements. Similarly, the equitable threat and bias scores of precipitation forecasts of 25 mm (6 hr)-1 were shown to be improved by 8% and 7%, respectively.

McCarty, Will↗

Global Core Plasma Model

Over 40 years of ground and spacecraft plasmaspheric measurements have resulted in many statistical descriptions of plasmaspheric properties. In some cases, these properties have been represented as analytical descriptions that are valid for specific regions or conditions. For the most part, what has not been done is to extend regional empirical descriptions or models to the plasmasphere as a whole. In contrast, many related investigations depend on the use of representative plasmaspheric conditions throughout the inner magnetosphere. Wave propagation, involving the transport of energy through the magnetosphere, is strongly affected by thermal plasma density and its composition. Ring current collisional and wave particle losses also strongly depend on these quantities. Plasmaspheric also plays a secondary role in influencing radio signals from the Global Positioning System satellites. The Global Core Plasma Model (GCPM) is an attempt to assimilate previous empirical evidence and regional models for plasmaspheric density into a continuous, smooth model of thermal plasma density in the inner magnetosphere. In that spirit, the International Reference Ionosphere is currently used to complete the low altitude description of density and composition in the model. The models and measurements on which the GCPM is currently based and its relationship to IRI will be discussed.

Gallagher, Dennis L.↗

Empirical Modeling of the Plasmasphere

Over 40 years of ground and spacecraft plasmaspheric measurements have resulted in many statistical descriptions of plasmaspheric properties. In some cases, these properties have been represented as analytical descriptions that are valid for specific regions or conditions. For the most part, what has not been done is to extend regional empirical descriptions or models to the plasmasphere as a whole. In contrast, many related investigations depend on the use of representative plasmaspheric conditions throughout the inner magnetosphere. Wave propagation, involving the transport of energy through the magnetosphere, is strongly affected by thermal plasma density and its composition. Ring current collisional and wave particle losses also strongly depend on these quantities, Plasmaspheric also plays a secondary role in influencing radio signals from the Global Positioning System satellites. The Global Core Plasma Model (GCPM) is an attempt to assimilate previous empirical evidence and regional models for plasmaspheric density into a continuous, smooth model of then-nal plasma density in the inner magnetosphere. In that spirit, the International Reference Ionosphere is currently used to complete the low altitude description of density and composition in the model. The models and measurements on which the GCPM is currently based and its relationship to IRI will be discussed.

Gallagher, Dennis L.↗

A Chandra Search for Coronal X Rays from the Cool White Dwarf GD 356

We report observations with the Chandra X-ray Observatory of the single, cool, magnetic white dwarf GD 356. For consistent comparison with other X-ray observations of single white dwarfs, we also re-analyzed archival ROSAT data for GD 356 (GJ 1205), G 99-47 (GR 290 = V1201 Ori), GD 90, G 195-19 (EG250 = GJ 339.1), and WD 2316+123 and archival Chandra data for LHS 1038 (GJ 1004) and GD 358 (V777 Her). Our Chandra observation detected no X rays from GD 356, setting the most restrictive upper limit to the X-ray luminosity from any cool white dwarf - Lx less than 6.0 x 10(exp 25) erg s(sup -1), at 99.7% confidence, for a 1- keV thermal-bremsstrahlung spectrum. The corresponding limit to the electron density is no less than 4.4x10(exp 11) per cubic centimeter. Our re-analysis of the archival data confirmed the non-detections reported by the original investigators. We discuss the implications of our and prior observations on models for coronal emission from white dwarfs. For magnetic white dwarfs, we emphasize the more stringent constraints imposed by cyclotron radiation. In addition, we describe (in an appendix) a statistical methodology for detecting a source and for constraining the strength of a source, which applies even when the number of source or background events is small.

Weisskopf, Martin C.↗

Reliability analysis of single crystal NiAl turbine blades

As part of a co-operative agreement with General Electric Aircraft Engines (GEAE), NASA LeRC is modifying and validating the Ceramic Analysis and Reliability Evaluation of Structures algorithm for use in design of components made of high strength NiAl based intermetallic materials. NiAl single crystal alloys are being actively investigated by GEAE as a replacement for Ni-based single crystal superalloys for use in high pressure turbine blades and vanes. The driving force for this research lies in the numerous property advantages offered by NiAl alloys over their superalloy counterparts. These include a reduction of density by as much as a third without significantly sacrificing strength, higher melting point, greater thermal conductivity, better oxidation resistance, and a better response to thermal barrier coatings. The current drawback to high strength NiAl single crystals is their limited ductility. Consequently, significant efforts including the work agreement with GEAE are underway to develop testing and design methodologies for these materials. The approach to validation and component analysis involves the following steps: determination of the statistical nature and source of fracture in a high strength, NiAl single crystal turbine blade material; measurement of the failure strength envelope of the material; coding of statistically based reliability models; verification of the code and model; and modeling of turbine blades and vanes for rig testing.

Salem, Jonathan↗

Geoid height-age relation from Seasat altimeter profiles across the Mendocino Fracture Zone

Twenty-eight Seasat altimeter profiles crossing the Mendocino Fracture Zone are used together with seafloor ages determined from magnetic lineations to estimate the change in oceanic geoid height with age, between ages of 15 and 135 m.y. An unbiased estimate of the overall geoid offset along each profile is determined from a least-squares fit of the along-track derivative of the geoid to the geoid slope predicted from a simple two-layer gravitational edge effect model. Uncertainties based upon the statistical properties of each profile are also determined. A geoid slope-age relation is constructed by normalizing the geoid offsets and uncertainties by the age offsets. The results are in agreement with geoid slope-age relations determined from symmetrically spreading ridges (Sandwell and Schubert, 1980). However, the fracture zone estimates have smaller uncertainties and show less scatter. A comparison of these results with the geoid slope-age prediction of the boundary layer cooling model shows that the thermal structure begins to deviate from this model at an early age (20-40 m.y.). A plate cooling model with a thickness of 125 km is most compatible with the geoid slope-age estimates, although significant deviations occur; these may indicate that the lithospheric thermal structure is not entirely age dependent.

Sandwell, D. T.↗

Use of Satellite Data Assimilation to Infer Land Surface Thermal Inertia

There are two important but observationally uncertain parameters in the grid averaged surface energy budgets of mesoscale models - surface moisture availability and thermal heat capacity. A technique has been successfully developed for assimilating Geostationary Operational Environmental Satellite (GOES) skin temperature tendencies during the mid-morning time frame to improve specification of surface moisture. In a new application of the technique, the use of satellite skin temperature tendencies in early evening is explored to improve specification of the surface thermal heat capacity. Together, these two satellite assimilation constraints have been shown to significantly improve the characterization of the surface energy budget of a mesoscale model on fine spatial scales. The GOES assimilation without the adjusted heat capacity was run operationally during the International H2O Project on a 12-km grid. This paper presents the results obtained when using both the moisture availability and heat capacity retrievals in concert. Preliminary results indicate that retrieved moisture availability alone improved the verification statistics of 2-meter temperature and dew point forecasts. Results from the 1.5 month long study period using the bulk heat capacity will be presented at the meeting.

Lapenta, William↗

Interconnect fatigue design for terrestrial photovoltaic modules

The results of comprehensive investigation of interconnect fatigue that has led to the definition of useful reliability-design and life-prediction algorithms are presented. Experimental data indicate that the classical strain-cycle (fatigue) curve for the interconnect material is a good model of mean interconnect fatigue performance, but it fails to account for the broad statistical scatter, which is critical to reliability prediction. To fill this shortcoming the classical fatigue curve is combined with experimental cumulative interconnect failure rate data to yield statistical fatigue curves (having failure probability as a parameter) which enable (1) the prediction of cumulative interconnect failures during the design life of an array field, and (2) the unambiguous--ie., quantitative--interpretation of data from field-service qualification (accelerated thermal cycling) tests. Optimal interconnect cost-reliability design algorithms are derived based on minimizing the cost of energy over the design life of the array field.

Mon, G. R.↗

Achieving Climate Change Absolute Accuracy in Orbit

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission will provide a calibration laboratory in orbit for the purpose of accurately measuring and attributing climate change. CLARREO measurements establish new climate change benchmarks with high absolute radiometric accuracy and high statistical confidence across a wide range of essential climate variables. CLARREO's inherently high absolute accuracy will be verified and traceable on orbit to Système Internationale (SI) units. The benchmarks established by CLARREO will be critical for assessing changes in the Earth system and climate model predictive capabilities for decades into the future as society works to meet the challenge of optimizing strategies for mitigating and adapting to climate change. The CLARREO benchmarks are derived from measurements of the Earth's thermal infrared spectrum (5-50 micron), the spectrum of solar radiation reflected by the Earth and its atmosphere (320-2300 nm), and radio occultation refractivity from which accurate temperature profiles are derived. The mission has the ability to provide new spectral fingerprints of climate change, as well as to provide the first orbiting radiometer with accuracy sufficient to serve as the reference transfer standard for other space sensors, in essence serving as a "NIST [National Institute of Standards and Technology] in orbit." CLARREO will greatly improve the accuracy and relevance of a wide range of space-borne instruments for decadal climate change. Finally, CLARREO has developed new metrics and methods for determining the accuracy requirements of climate observations for a wide range of climate variables and uncertainty sources. These methods should be useful for improving our understanding of observing requirements for most climate change observations.

Wielicki, Bruce A.↗

Remote Sensing of Evaporation

Evaporation of water from the Earth's surface into the atmosphere is central to the terrestrial energy, water and carbon cycle. Remote sensing approaches to measure evaporation (ET) combine observable inputs to the energy and water balance within statistical or process-based methodologies. These ET products draw on satellite observations from across the electro-magnetic spectrum. The ET retrievals are grouped in two main categories. One category includes approaches that combine meteorological descriptions of potential evaporation with a range of strategies to estimate evaporative stress. A second category includes surface energy balance approaches that retrieve latent heat from the thermal signatures. For each category a practical implementation example is described, including an outlook on progress towards multi-model assessment of global evaporation.

Transpiration↗

Improvements to a Response Surface Thermal Model for Orion Mated to the International Space Station

This study is an extension of previous work to evaluate the applicability of Design of Experiments (DOE)/Response Surface Methodology to on-orbit thermal analysis. The goal was to determine if the methodology could produce a Response Surface Equation (RSE) that predicted the thermal model temperature results within +/-10 F. An RSE is a polynomial expression that can then be used to predict temperatures for a defined range of factor combinations. Based on suggestions received from the previous work, this study used a model with simpler geometry, considered polynomials up to fifth order, and evaluated orbital temperature variations to establish a minimum and maximum temperature for each component. A simplified Outer Mold Line (OML) thermal model of the Orion spacecraft was used in this study. The factors chosen were the vehicle's Yaw, Pitch, and Roll (defining the on-orbit attitude), the Beta angle (restricted to positive beta angles from 0 to 75), and the environmental constants (varying from cold to hot). All factors were normalized from their native ranges to a non-dimensional range from -1.0 to 1.0. Twenty-three components from the OML were chosen and the minimum and maximum orbital temperatures were calculated for each to produce forty-six responses for the DOE model. A customized DOE case matrix of 145 analysis cases was developed which used analysis points at the factor corners, mid-points, and center. From this data set, RSE s were developed which consisted of cubic, quartic, and fifth order polynomials. The results presented are for the fifth order RSE. The RSE results were then evaluated for agreement with the analytical model predictions to produce a +/-3(sigma) error band. Forty of the 46 responses had a +/-3(sigma) value of 10 F or less. Encouraged by this initial success, two additional sets of verification cases were selected. One contained 20 cases, the other 50 cases. These cases were evaluated both with the fifth order RSE and with the analytical model. For the maximum temperature predictions, 12 of the 23 components had all predictions within +/-10 F and 17 were within +/-20 F. For the minimum temperature predictions, only 4 of the 23 components (the four radiator temperatures), were within the 10 F goal. The maximum temperature RSEs were then run through 59,049 screening cases. The RSE predictions were then filtered to find 55 cases that produced the hottest temperatures. These 55 cases were then analyzed using the thermal model and the results compared against the RSE predictions. As noted earlier, 12 of the 23 responses were within +/-10 F at 17 within +/-20 F. These results demonstrate that if properly formulated, an RSE can provide a reliable, fast temperature prediction. Despite this progress, additional work is needed to determine why the minimum temperatures responses and 6 of the hot temperature responses did not produce reliable RSEs. Recommend focus areas are the model itself (arithmetic vs. diffusion nodes) and seeking consultations with statistical application experts.

Miller, StephenW.↗

Arctic ice surface temperature retrieval from AVHRR thermal channels

The relationship between AVHRR thermal radiances and the surface (skin) temperature of Arctic snow-covered sea ice is examined through forward calculations of the radiative transfer equation, providing an ice/snow surface temperature retrieval algorithm for the central Arctic Basin. Temperature and humidity profiles with cloud observations collected on an ice island during 1986-1987 are used. Coefficients that correct for atmospheric attenuation are given for three Arctic clear sky 'seasons', as defined through statistical analysis of the daily profiles, for the NOAA 7, 9, and 11 satellites. Modeled directional snow emissivities, different in the two split-window (11 and 12 micron) channels, are used. While the sensor scan angle is included explicitly in the correction equation, its effect in the dry Arctic atmosphere is small, generally less than 0.1 K. Using the split-window channels and scan angle, the rms error in the estimated ice surface temperature is less than 0.1 K in all seasons. Inclusion channel 3(3.7 microns) during the winter decreases the rms error by less than 0.003

Key, J.↗