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At least 1,117 records · Page 62

Spacecraft Internal Acoustic Environment Modeling

Acoustic modeling can be used to identify key noise sources, determine/analyze sub-allocated requirements, keep track of the accumulation of minor noise sources, and to predict vehicle noise levels at various stages in vehicle development, first with estimates of noise sources, later with experimental data. This paper describes the implementation of acoustic modeling for design purposes by incrementally increasing model fidelity and validating the accuracy of the model while predicting the noise of sources under various conditions. During FY 07, a simple-geometry Statistical Energy Analysis (SEA) model was developed and validated using a physical mockup and acoustic measurements. A process for modeling the effects of absorptive wall treatments and the resulting reverberation environment were developed. During FY 08, a model with more complex and representative geometry of the Orion Crew Module (CM) interior was built, and noise predictions based on input noise sources were made. A corresponding physical mockup was also built. Measurements were made inside this mockup, and comparisons were made with the model and showed excellent agreement. During FY 09, the fidelity of the mockup and corresponding model were increased incrementally by including a simple ventilation system. The airborne noise contribution of the fans was measured using a sound intensity technique, since the sound power levels were not known beforehand. This is opposed to earlier studies where Reference Sound Sources (RSS) with known sound power level were used. Comparisons of the modeling result with the measurements in the mockup showed excellent results. During FY 10, the fidelity of the mockup and the model were further increased by including an ECLSS (Environmental Control and Life Support System) wall, associated closeout panels, and the gap between ECLSS wall and mockup wall. The effect of sealing the gap and adding sound absorptive treatment to ECLSS wall were also modeled and validated.

Chu, Shao-Sheng R.↗

Spatial validation reveals poor predictive performance of large-scale ecological mapping models

Mapping aboveground forest biomass is central for assessing the global carbon balance. However, current large-scale maps show strong disparities, despite good validation statistics of their underlying models. Here, we attribute this contradiction to a flaw in the validation methods, which ignore spatial autocorrelation (SAC) in data, leading to overoptimistic assessment of model predictive power. To illustrate this issue, we reproduce the approach of large-scale mapping studies using a massive forest inventory dataset of 11.8 million trees in central Africa to train and validate a random forest model based on multispectral and environmental variables. A standard nonspatial validation method suggests that the model predicts more than half of the forest biomass variation, while spatial validation methods accounting for SAC reveal quasi-null predictive power. This study underscores how a common practice in big data mapping studies shows an apparent high predictive power, even when predictors have poor relationships with the ecological variable of interest, thus possibly leading to erroneous maps and interpretations.

biomass↗

Coherent Eigenmodes in Homogeneous MHD Turbulence

The statistical mechanics of Fourier models of ideal, homogeneous, incompressible magnetohydrodynamic (MHD) turbulence is discussed, along with their relevance for dissipative magnetofluids. Although statistical theory predicts that Fourier coefficients of fluid velocity and magnetic field are zero-mean random variables, numerical simulations clearly show that certain coefficients have a non-zero mean value that can be very large compared to the associated standard deviation, i.e., we have coherent structure. We use eigenanalysis of the modal covariance matrices in the probability density function to explain this phenomena in terms of `broken ergodicity', which is defined to occur when dynamical behavior does not match ensemble predictions on very long time-scales. We provide examples from 2-D and 3-D magnetohydrodynamic simulations of homogeneous turbulence, and show new results from long-time simulations of MHD turbulence with and without a mean magnetic field

Shebalin, John V.↗

Bayes Analysis and Reliability Implications of Stress-Rupture Testing a Kevlar/Epoxy COPV Using Temperature and Pressure Acceleration

Composite Overwrapped Pressure Vessels (COPVs) that have survived a long service time under pressure generally must be recertified before service is extended. Flight certification is dependent on the reliability analysis to quantify the risk of stress rupture failure in existing flight vessels. Full certification of this reliability model would require a statistically significant number of lifetime tests to be performed and is impractical given the cost and limited flight hardware for certification testing purposes. One approach to confirm the reliability model is to perform a stress rupture test on a flight COPV. Currently, testing of such a Kevlar49 (Dupont)/epoxy COPV is nearing completion. The present paper focuses on a Bayesian statistical approach to analyze the possible failure time results of this test and to assess the implications in choosing between possible model parameter values that in the past have had significant uncertainty. The key uncertain parameters in this case are the actual fiber stress ratio at operating pressure, and the Weibull shape parameter for lifetime; the former has been uncertain due to ambiguities in interpreting the original and a duplicate burst test. The latter has been uncertain due to major differences between COPVs in the database and the actual COPVs in service. Any information obtained that clarifies and eliminates uncertainty in these parameters will have a major effect on the predicted reliability of the service COPVs going forward. The key result is that the longer the vessel survives, the more likely the more optimistic stress ratio model is correct. At the time of writing, the resulting effect on predicted future reliability is dramatic, increasing it by about one "nine," that is, reducing the predicted probability of failure by an order of magnitude. However, testing one vessel does not change the uncertainty on the Weibull shape parameter for lifetime since testing several vessels would be necessary.

Phoenix, S. Leigh↗

A New Statistically based Autoconversion rate Parameterization for use in Large-Scale Models

The autoconversion rate is a key process for the formation of precipitation in warm clouds. In climate models, physical processes such as autoconversion rate, which are calculated from grid mean values, are biased, because they do not take subgrid variability into account. Recently, statistical cloud schemes have been introduced in large-scale models to account for partially cloud-covered grid boxes. However, these schemes do not include the in-cloud variability in their parameterizations. In this paper, a new statistically based autoconversion rate considering the in-cloud variability is introduced and tested in three cases using the Canadian Single Column Model (SCM) of the global climate model. The results show that the new autoconversion rate improves the model simulation, especially in terms of liquid water path in all three case studies.

Lin, Bing↗

A cloud and radiation model-based algorithm for rainfall retrieval from SSM/I multispectral microwave measurements

A hybrid statistical-physical retrieval scheme is explored which combines a statistical approach with an approach based on the development of cloud-radiation models designed to simulate precipitating atmospheres. The algorithm employs the detailed microphysical information from a cloud model as input to a radiative transfer model which generates a cloud-radiation model database. Statistical procedures are then invoked to objectively generate an initial guess composite profile data set from the database. The retrieval algorithm has been tested for a tropical typhoon case using Special Sensor Microwave/Imager (SSM/I) data and has shown satisfactory results.

Xiang, Xuwu↗

Design for Vibration Monitoring: A Methodology for Reliable and Cost-Effective Vibration Monitoring

The purpose of health monitoring systems is to detect failures or defects for increased safety and performance and to provide on-condition maintenance with reduced costs. The problems associated with health monitoring systems include high rates of false alarms and missed failures, which make monitoring an unreliable and costly task. The reason for this is that unaccounted variations invalidate signal modeling assumptions. Our approach was to focus on vibration monitoring of rotating components. We analyzed baseline signals to determine statistical variations, identify and model factors that influence vibrations (pre-production vs. post-production variations), determine hit and false alarm rates with baseline flight data, model and predict effects of defects and variations on vibrations, and develop algorithms and metrics for failure and anomaly detection in the presence of variations.

Tumer, Irem Y.↗

The GEOS-5 Data Assimilation System-Documentation of Versions 5.0.1, 5.1.0, and 5.2.0

This report documents the GEOS-5 global atmospheric model and data assimilation system (DAS), including the versions 5.0.1, 5.1.0, and 5.2.0, which have been implemented in products distributed for use by various NASA instrument team algorithms and ultimately for the Modem Era Retrospective analysis for Research and Applications (MERRA). The DAS is the integration of the GEOS-5 atmospheric model with the Gridpoint Statistical Interpolation (GSI) Analysis, a joint analysis system developed by the NOAA/National Centers for Environmental Prediction and the NASA/Global Modeling and Assimilation Office. The primary performance drivers for the GEOS DAS are temperature and moisture fields suitable for the EOS instrument teams, wind fields for the transport studies of the stratospheric and tropospheric chemistry communities, and climate-quality analyses to support studies of the hydrological cycle through MERRA. The GEOS-5 atmospheric model has been approved for open source release and is available from: http://opensource.gsfc.nasa.gov/projects/GEOS-5/GEOS-5.php.

M. M. Rienecker↗

Evidence of Nanoflare Heating in Coronal Loops Observed with Hinolde-XRT and SDO-AIA

We study a series of coronal loop lightcurves from X-ray and EUV observations. In search for signatures of nanoflare heating, we analyze the statistical properties of the observed lightcurves and compare them with synthetic cases obtained with a 2D cellular-automaton model based on nanoflare heating driven by photospheric motions. Our analysis shows that the observed and the model lightcurves have similar statistical properties. The asymmetries observed in the distribution of the intensity fluctuations indicate the possible presence of widespread cooling processes in sub-resolution magnetic strands.

Lopez-Fuentes, M. C.↗

Multi-Temperature Emission and Abundances in the Hot Gaseous Halo

We present the results of XMM-Newton observations of NGC 507, a dominant elliptical galaxy in a small group of galaxies. After carefully considering various systematic effects on abundance measurements, we report 'super-solar' metal abundances (both Fe and a-elements) present in the hot ISM: ZFe = 2-3 times solar with an observational limit of as high as 4 times solar inside the D25 ellipse of NGC 507. This is the highest ZFe reported so far, and fully consistent with those expected by the stellar evolution models where heavy elements are enriched by both type II and Ia supernovae ejecta. No unusual constraint either on the SNe rate or IMF is required. Among various factors affecting the accurate abundance measurement, we find that selecting a proper emission model is most important. As opposed to the X-ray spectral data with limited s/n and poor spatial/spectral resolution obtained in the previous missions, the spatially resolved XMM spectra provide enough statistics to untie the model-Z degeneracy and statistically require at least 3 emission components in each concentric shell (2 thermal components representing a finite range of kT in the hot ISM + 1 hard LMXB component). We show that a simpler model (such as a two-component model) produce a much lower best-fit ZFe. The abundances of a-elements (most accurately determined by Si) is also found to be super-solar and its radio to Fe is close to the solar ratio, suggesting a considerably contribution of heavy elements from Type Ia SNe. We estimate approx. 70% of MFe in the hot ISM originate from Type Ia.

Kim, Dong-Woo↗

Real-time Identification and Control of Satellite Signal Impairments Solution and Application of the Stratonovich Equation Part 1. Theoretical Development

As satellite communications systems become both more complex and reliant with respect to their operating environment, it has become imperative to be able to identify, during real-time operation, the onset of one or more impairments to the quality of overall communications system integrity. One of the most important aspects to monitor of a satellite link operating within the Earth's atmosphere is the signal fading due to the occurrence of rain and/or phase scintillations. This, of course, must be done in the presence of the associated measurement uncertainty or potentially faulty measurement equipment such as in the Advanced Communication Technology Satellite (ACTS) experiment. In the present work, an approach originally suggested in 1991, and apparently still considered iconoclastic, will be significantly developed and applied to the satellite communications link on which the deleterious composite signal fade is the result of one or many component fade mechanisms. Through the measurement (with the attendant uncertainty or 'error' in the measurement) of such a composite fading satellite signal, it is desired to extract the level of each of the individual fading mechanisms so they can be appropriately mitigated before they impact the overall performance of the communications network. Rather than employing simple-minded deterministic filtering to the real-time fading, the present approach is built around all the models and/or descriptions used to describe the individual fade components, including their dynamic evolution. The latter is usually given by a first-order Langevin equation. This circumstance allows the description of the associated temporal transition probability densities of each of the component processes. By using this description, along with the real-time measurements of the composite fade (along with the measurement errors), one can obtain statistical estimates of the levels of each of the component fading mechanisms as well as their predicted values into the future. This is all accomplished by the use of the well-known Stratonovich integro-differential equation that results from the model of the measured signal fade that is also tailored to adaptively adjust the values of the parameters used in the statistical models of the individual fade mechanisms. Three examples of increasing complexity are addressed and solved for the iterative determination of fade component levels from the measured composite signal fade in the presence of measurement error and, in the last case, with uncertainty in the model parameters.

Countermeasure↗

Development of a Bayesian Belief Network Runway Incursion and Excursion Model

In a previous work, a statistical analysis of runway incursion (RI) event data was conducted to ascertain the relevance of this data to the top ten Technical Challenges (TC) of the National Aeronautics and Space Administration (NASA) Aviation Safety Program (AvSP). The study revealed connections to several of the AvSP top ten TC and identified numerous primary causes and contributing factors of RI events. The statistical analysis served as the basis for developing a system-level Bayesian Belief Network (BBN) model for RI events, also previously reported. Through literature searches and data analysis, this RI event network has now been extended to also model runway excursion (RE) events. These RI and RE event networks have been further modified and vetted by a Subject Matter Expert (SME) panel. The combined system-level BBN model will allow NASA to generically model the causes of RI and RE events and to assess the effectiveness of technology products being developed under NASA funding. These products are intended to reduce the frequency of runway safety incidents/accidents, and to improve runway safety in general. The development and structure of the BBN for both RI and RE events are documented in this paper.

Green, Lawrence L.↗

Relativistic electron events in interplanetary space

Review of relativistic electron events observed in interplanetary space. The different types of event are identified and illustrated. The relationships between solar X-ray and radio emissions and relativistic electrons are examined, and the relevance of the observations to solar flare acceleration models is discussed. A statistical analysis of electron spectra, the electron/proton ratio and propagation from the flare site to the earth is presented. A model is outlined which can account for the release of electrons from the sun in a manner consistent with observations of energetic solar particles and electromagnetic solar radiation.

Simnett, G. M.↗

Model consistency in large eddy simulation of turbulent channel flows

Combinations of filters and subgrid scale stress models for large eddy simulation of the Navier-Stokes equations are examined by a priori tests and numerical simulations. The structure of the subgrid scales is found to depend strongly on the type of filter used, and consistency between model and filter is essential to ensure accurate results. The implementation of consistent combinations of filter and model gives more accurate turbulence statistics than those obtained in previous investigations in which the models were chosen independently from the filter. Results and limitations of the a priori test are discussed. The effect of grid refinement is also examined.

Piomelli, Ugo↗

Filtered Mass Density Function for Design Simulation of High Speed Airbreathing Propulsion Systems

The objective of this research is to develop and implement new methodology for large eddy simulation of (LES) of high-speed reacting turbulent flows. We have just completed two (2) years of Phase I of this research. This annual report provides a brief and up-to-date summary of our activities during the period: September 1, 2000 through August 31, 2001. In the work within the past year, a methodology termed "velocity-scalar filtered density function" (VSFDF) is developed and implemented for large eddy simulation (LES) of turbulent flows. In this methodology the effects of the unresolved subgrid scales (SGS) are taken into account by considering the joint probability density function (PDF) of all of the components of the velocity and scalar vectors. An exact transport equation is derived for the VSFDF in which the effects of the unresolved SGS convection, SGS velocity-scalar source, and SGS scalar-scalar source terms appear in closed form. The remaining unclosed terms in this equation are modeled. A system of stochastic differential equations (SDEs) which yields statistically equivalent results to the modeled VSFDF transport equation is constructed. These SDEs are solved numerically by a Lagrangian Monte Carlo procedure. The consistency of the proposed SDEs and the convergence of the Monte Carlo solution are assessed by comparison with results obtained by an Eulerian LES procedure in which the corresponding transport equations for the first two SGS moments are solved. The unclosed SGS convection, SGS velocity-scalar source, and SGS scalar-scalar source in the Eulerian LES are replaced by corresponding terms from VSFDF equation. The consistency of the results is then analyzed for a case of two dimensional mixing layer.

Drozda, T. G.↗

Assimilation of Lidar Planetary Boundary Layer Height Observations

Lidar backscatter and wind retrievals of the planetary boundary layer height (PBLH) are assimilated into 22 hourly forecasts from the NASA Unified - Weather and Research Forecast (NU-WRF) model during the Plains Elevated Convection Convection at Night (PECAN) campaign on July 11, 2015 in Greensburg, Kansas, using error statistics collected from the model profiles to compute the necessary covariance matrices. Two separate forecast runs using different PBL physics schemes were employed, and comparisons with 6 independent radiosonde profiles were made for each run. Both of the forecast runs accurately predicted the PBLH and the state variable profiles within the planetary boundary layer during the early morning, and the assimilation had a small impact during this time. In the late afternoon, the forecast runs showed decreased accuracy as the convective boundary layer developed. However, assimilation of the Doppler lidar PBLH observations were found to improve the temperature and V velocity profiles relative to independent radiosonde profiles. Water vapor was overcorrected, leading to increased differences with independent data. Errors in the U velocity were made slightly larger. The computed forecast error covariances between the PBLH and state variables were found to rise in the late afternoon, leading to the larger improvements in the afternoon. This work represents the first effort to assimilate PBLH into forecast states using ensemble methods.

Andrew Tangborn↗

A computationally efficient statistically downscaled 100 m resolution Greenland product from the regional climate model MAR

The Greenland Ice Sheet (GrIS) has been contributing directly to sea level rise, and this contribution is projected to accelerate over the next decades. A crucial tool for studying the evolution of surface mass loss (e.g., surface mass balance, SMB) consists of regional climate models (RCMs), which can provide current estimates and future projections of sea level rise associated with such losses. However, one of the main limitations of RCMs is the relatively coarse horizontal spatial resolution at which outputs are currently generated. Here, we report results concerning the statistical downscaling of the SMB modeled by the Modèle Atmosphérique Régional (MAR) RCM from the original spatial resolution of 6 km to 100 m building on the relationship between elevation and mass losses in Greenland. To this goal, we developed a geospatial framework that allows the parallelization of the downscaling process, a crucial aspect to increase the computational efficiency of the algorithm. Using the results obtained in the case of the SMB, surface and air temperature are assessed through the comparison of the modeled outputs with in situ and satellite measurement. The downscaled products show a considerable improvement in the case of the downscaled product with respect to the original coarse output, with the coefficient of determination (R 2 ) increasing from 0.868 for the original MAR output to 0.935 for the SMB downscaled product. Moreover, the value of the slope and intercept of the linear regression fitting modeled and measured SMB values shifts from 0.865 for the original MAR to 1.015 for the downscaled product in the case of the slope and from the value −235 mm w.e. yr -1 (original) to −57 mm w.e. yr -1 (downscaled) in the case of the intercept, considerably improving upon results previously published in the literature.

Greenland Ice Sheet↗