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Results for “ensemble methods”

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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NASA NTRS1975

Computer measurement and representation of the heart in two and three dimensions

Methods for accurate measurement and meaningful display of cardiac dimensions as obtained from fluoroscopy were surveyed. Recorded images were scaled back to actual dimensions and cardiac motion was displayed to assess functional changes. This was accomplished by use of a low-cost but flexible ensemble of computer and video equipment which assisted in (1) digitizing image outlines or points, (2) filing digitized images for later recall in any sequence, (3) correcting recorded images for distortion, (4) modeling heart geometry, (5) analyzing dimensional changes, and (6) displaying both heart geometry and results of analysis in a useful form.

Rasmussen, D.↗

NASA NTRS1985

User's manual for airfoil flow field computer code SRAIR

A two dimensional unsteady Navier-Stokes calculation procedure with specific application to the isolated airfoil problem is presented. The procedure solves the full, ensemble averaged Navier-Stokes equations with turbulence represented by a mixing length model. The equations are solved in a general nonorthogonal coordinate system which is obtained via an external source. Specific Cartesian locations of grid points are required as input for this code. The method of solution is based upon the Briley-McDonald LBI procedure. The manual discusses the analysis, flow of the program, control steam, input and output.

Shamroth, S. J.↗

NASA NTRS2023

Heat Stress to Jeopardize Crop Production in the US Corn Belt Based on Downscaled CMIP5 Projections

CONTEXT Global food security faces increasing challenges from the changing climate. Changes of agricultural output from some of the most productive regions such as the US Corn Belt can largely affect the world's food market. Developing predictive understanding of the agricultural risk of climate change and potential mitigation strategies is critical for the global food security. OBJECTIVE The objective of this study is to assess the responses of maize and soybean yield to projected climate changes in the Corn Belt, identify the shifting environment stressors on crop yield, and tackle potential climate adaptation strategies. METHODS We drive a process-based model, the Decision Support System for Agrotechnology Transfer, with high-resolution statistically downscaled and bias-corrected historical and future climates from ten CMIP5 models in the MACA-2 database. RESULTS AND CONCLUSIONS The multi-model ensemble mean suggests a 12% decrease of maize yield by mid-century and 40% by late century, with a high degree of model consensus in the direction of changes; for individual models, the projected decrease of maize yield by late century ranges from <5% to over 80%, with the worst crop outcome corresponding to the most sensitive climate models. Soybean yield is projected to increase by midcentury with a high degree of model consensus, but such consensus is lost by late century as some projections shift to significant decreases. Crop yield in the Corn Belt is currently limited by water stress, but is projected to be increasingly limited by heat stress as well after the midcentury. The mounting heat stress will drive the most productive zone for maize to shift from central to northern part of the Corn Belt, but the projected increase in the northern states cannot fully compensate for the decrease in the south, causing the total production to decrease if agricultural practice stays the same. Earlier planting can alleviate only a small fraction of the heat-induced crop loss in a warmer climate. Climate change will (at least partially) offset the yield boost caused by agricultural technology and intensification. SIGNIFICANCE This study advances our predictive understanding of crop yield responses to climate change, and suggests that a multitude of strategies will be needed to address the climate change challenges for the U.S. agriculture.

Crop yield↗

NASA NTRS1989

Determination of longitudinal aerodynamic derivatives using flight data from an icing research aircraft

A flight test was performed with the NASA Lewis Research Center's DH-6 icing research aircraft. The purpose was to employ a flight test procedure and data analysis method, to determine the accuracy with which the effects of ice on aircraft stability and control could be measured. For simplicity, flight testing was restricted to the short period longitudinal mode. Two flights were flown in a clean (baseline) configuration, and two flights were flown with simulated horizontal tail ice. Forty-five repeat doublet maneuvers were performed in each of four test configurations, at a given trim speed, to determine the ensemble variation of the estimated stability and control derivatives. Additional maneuvers were also performed in each configuration, to determine the variation in the longitudinal derivative estimates over a wide range of trim speeds. Stability and control derivatives were estimated by a Modified Stepwise Regression (MSR) technique. A measure of the confidence in the derivative estimates was obtained by comparing the standard error for the ensemble of repeat maneuvers, to the average of the estimated standard errors predicted by the MSR program. A multiplicative relationship was determined between the ensemble standard error, and the averaged program standard errors. In addition, a 95 percent confidence interval analysis was performed for the elevator effectiveness estimates, C sub m sub delta e. This analysis identified the speed range where changes in C sub m sub delta e could be attributed to icing effects. The magnitude of icing effects on the derivative estimates were strongly dependent on flight speed and aircraft wing flap configuration. With wing flaps up, the estimated derivatives were degraded most at lower speeds corresponding to that configuration. With wing flaps extended to 10 degrees, the estimated derivatives were degraded most at the higher corresponding speeds. The effects of icing on the changes in longitudinal stability and control derivatives were adequately determined by the flight test procedure and the MSR analysis method discussed herein.

Ranaudo, R. J.↗

NASA NTRS1981

Application of Monte Carlo techniques to transient thermal modeling of cavity radiometers having diffuse-specular surfaces

A viable alternative to the net exchange method of radiative analysis which is equally applicable to diffuse and diffuse-specular enclosures is presented. It is particularly more advantageous to use than the net exchange method in the case of a transient thermal analysis involving conduction and storage of energy as well as radiative exchange. A new quantity, called the distribution factor is defined which replaces the angle factor and the configuration factor. Once obtained, the array of distribution factors for an ensemble of surface elements which define an enclosure permits the instantaneous net radiative heat fluxes to all of the surfaces to be computed directly in terms of the known surface temperatures at that instant. The formulation of the thermal model is described, as is the determination of distribution factors by application of a Monte Carlo analysis. The results show that when fewer than 10,000 packets are emitted, an unsatisfactory approximation for the distribution factors is obtained, but that 10,000 packets is sufficient.

Mahan, J. R.↗

NASA NTRS2012

A Reconciled Estimate of Ice-Sheet Mass Balance

We combined an ensemble of satellite altimetry, interferometry, and gravimetry data sets using common geographical regions, time intervals, and models of surface mass balance and glacial isostatic adjustment to estimate the mass balance of Earth's polar ice sheets. We find that there is good agreement between different satellite methods-especially in Greenland and West Antarctica-and that combining satellite data sets leads to greater certainty. Between 1992 and 2011, the ice sheets of Greenland, East Antarctica, West Antarctica, and the Antarctic Peninsula changed in mass by -142 plus or minus 49, +14 plus or minus 43, -65 plus or minus 26, and -20 plus or minus 14 gigatonnes year(sup −1), respectively. Since 1992, the polar ice sheets have contributed, on average, 0.59 plus or minus 0.20 millimeter year(sup −1) to the rate of global sea-level rise.

mass balance↗

NASA NTRS1992

Direct simulation of particle dispersion in a decaying isotropic turbulence

Results of a numerical investigation of the dispersion of solid particles in decaying isotropic turbulence are presented. The 3D time-dependent velocity field of a homogeneous nonstationary turbulence is computed using the method of direct numerical simulation (DNS). The dispersion characteristics of three different solid particles (corn, copper, and glass) injected in the flow are obtained by integrating the complete equation of particle motion along the instantaneous trajectories of 22-cubed particles for each particle type, and then by performing ensemble averaging. Good agreement was achieved between the present DNS results and the measured time development of the mean-square displacement of the particles. Questions of how and why the dispersion statistics of a solid particle differ from those of its corresponding fluid point and surrounding fluid and what influences inertia and gravity have on these statistics are also discussed.

Elghobashi, S.↗

NASA NTRSDate not supplied

Using Federated Learning to Overcome Data Gravity in Space

Humans intend to take longer missions to outer space. Understanding the impact that space has on human health is paramount to the success of these missions. Controlled experiments with model organisms are run to infer the impact of space conditions on human health, but the data these experiments generate are too large to transfer to Earth for building models. The same is true for space-relevant data generated on Earth. Ideally, these datasets should be combined to improve statistical power and model accuracy without having to transfer data. Federated learning is such a method which trains an algorithm across decentralized computing systems, each of which has their own local copy of training and testing data. In this research, made possible by NASA@Work, the AI for Life in Space group at NASA demonstrates the use of federated learning to train an ensemble of causality inference models on a combination of data residing on the International Space Station (ISS) and in the cloud. Our work leverages CRISP, a causal inference platform developed during the 2020 Frontier Development Lab’s “Astronaut Health Challenge.” We also leverage the OpenFL federated learning library which was collaboratively developed at Intel and UPenn. We used publicly available data from the NASA Ames Life Sciences Data Archive to identify features in ionizing radiation experiments as causal of changes in cardiac blood velocity. This research demonstrates, for the first time, the possibility of running machine learning algorithms on datasets separated by astronomical distances. In this experiment, all the data were generated in terra, half of which were transferred to the ISS and analyzed on the Spaceborne Computer. In the future, our research will leverage federated learning on data generated in situ on the ISS with data generated terrestrially to predict the impact of spaceflight on mammalian female reproductive capacity.

James Casaletto↗

NASA NTRS2016

Developing Atmospheric Retrieval Methods for Direct Imaging Spectroscopy of Gas Giants in Reflected Light I: Methane Abundances and Basic Cloud Properties

Reflected light spectroscopy and photometry of cool, directly imaged extrasolar giant planets are expected to be performed in the next decade by space-based telescopes equipped with optical wavelength coronagraphs and integral field spectrographs, such as the Wide-Field Infrared Survey Telescope (WFIRST). We are developing a new atmospheric retrieval methodology to help assess the science return and inform the instrument design for such future missions, and ultimately interpret the resulting observations. Our retrieval technique employs an albedo model coupled with both a Markov chain Monte Carlo Ensemble Sampler (emcee) and a multimodal nested sampling algorithm (MultiNest) to map the posterior distribution. This combination makes the global evidence calculation more robust for any given model, and highlights possible discrepancies in the likelihood maps. Here we apply this methodology to simulated spectra of cool giant planets. As a proof-of-concept, our current atmospheric model contains 1 or 2 cloud layers, methane as a major absorber, and a H2-He background gas. This 6-to-9 parameter model is appropriate for Jupiter-like planets and can be easily expanded in the future. In addition to deriving the marginal likelihood distribution and confidence intervals for the model parameters, we perform model selection to determine the significance of methane and cloud detection as a function of expected signal-to-noise, in the presence of spectral noise correlations. After internal validation, the method is applied to realistic reflected-light spectra of Jupiter, Saturn, and HD 99492 c, a likely observing target. We find that the presence or absence of clouds and methane can be determined with high accuracy, while parameters uncertainties are model-dependent.

spectroscopy↗

NASA NTRSDate not supplied

Continuous Habitable Zones: Pairing a GCM and Bayesian Framework to Predict Habitable Zone Evolution

In the near-future, new space telescopes like JWST, LUVOIR, and HabEx will begin attempting to explore the properties of atmospheres of potentially habitable planets. This will require a significant amount of time and resources for even a single planet, which makes it essential to prioritize observations by those most-likely to have detectable life. Here we present a statistical method to estimate the probabilities that specific exoplanets have been continuously in the habitable zone of their host stars for more than 2 billion years, the approximate time it took life on Earth to significantly increase the oxygen content of the atmosphere. We introduce the use of statistics of an ensemble of 3D planetary general circulation models to estimate these probabilities, replacing prior 1D model estimates.

habitable planets↗

NASA NTRSDate not supplied

Pairing a GCM and Bayesian Framework to Predict Habitable Zone Evolution

habitable planets↗

NASA NTRSDate not supplied

Spectral Gap Filling Method Using the Spectral Information from CLARREO-Pathfinder Measured Earth-Reflected Solar Spectra to Support CPF-CERES Intercalibration

The high-accuracy Earth-reflected solar spectral radiances from CLARREO Pathfinder (CPF) will serve as in-orbit benchmark measurements for intercalibrating other satellite imagers. The CPF team is developing a state-of-the-art intercalibration method to calibrate the shortwave channel (300-5000 nm) of the CERES instrument against the CPF reference with an uncertainty of 0.3%. Because the CPF instrument only covers spectral range from 350 nm to 2300 nm, the team has developed a spectral extension method to fill in the gaps between the spectral domains of CPF and the CERES shortwave channel. The method solely relies on using the hyperspectral information from the CPF wavelengths to predict the radiances below 350 nm and above 2300 nm. To quantify the relationship between the CPF spectrum and the non-overlapping portions of the spectrum between CPF and CERES, the team has simulated a large ensemble of spectra that cover the spectral range for both CPF and CERES. A hyperspectral bidirectional reflectance model for land surface based on thousands of measured land surface reflectance has been developed. This land surface model as well as the Cox-Munk model for ocean surface are used in the spectral gap filling. Various water/ice clouds, aerosols, atmosphere profiles and surfaces were used to simulate Earth-reflected radiances from 200 nm to 15 um under different solar and sensor geometries. The targeted uncertainty for the CPF-extended broadband CERES radiances is less than 0.1%. The previously derived training spectra were updated to replace the Kurucz solar irradiance model with the TSIS-1 Hybrid Solar Reference Spectrum. The influence of the scalar assumption in radiative transfer model equations on the uncertainty in estimating the broadband radiances was also investigated.

Hyperspectral↗

NASA NTRSDate not supplied

Establishing Cleaning Methods for Cleanroom and Safety Suits at Remote Sites with Available Resources

"The James Webb Space Telescope (JWST) spent considerable time in multiple clean facilities during its launch campaign at the Centre Spatial Guyanais (CSG) in French Guiana. Throughout this time, it was imperative that personnel wear approved cleanroom or safety suits when working in proximity to the JWST observatory. This proved to be challenging for two reasons: 1) A large quantity of NASA cleanroom suits needed to be shipped to CSG to account for the heavy volume of NASA and ESA personnel requiring access to the clean facilities. It became evident that shipping clean suits from the US to CSG in a timely fashion during the launch campaign would be challenging. Consequently, a backup plan needed to be established to avoid running out. 2) For safety purposes, Self-Contained Atmospheric Protection Ensemble (SCAPE) and Splash suits were required for hazardous operations. Neither type of suit was cleanroom compatible; therefore, a viable cleaning process needed to be developed to ensure both types of suits met JWST’s approved cleanliness standards. The NASA Contamination Control (CC) team partnered with CSG’s S5E cleanroom and suit processing team. The teams were able to make modifications to the S5E facility to create a NASA approved makeshift clean environment where NASA cleanroom suits and CSG Splash suits were inspected, folded, and bagged for cleanroom use once they were washed and dried. Since SCAPE suits could not be cleaned using conventional methods, a procedure was developed to clean and inspect the suits by the CC team in a temporary clean environment prior to fueling. "

James Webb Space Telescope↗

NASA NTRSDate not supplied

Establishing Cleaning Methods For Cleanroom And Safety Suits At Remote Sites With Available Resources

The James Webb Space Telescope (JWST) spent considerable time in multiple clean facilities during its launch campaign at the Centre Spatial Guyanais (CSG) in French Guiana. Throughout this time, it was imperative that personnel wear approved cleanroom or safety suits when working in proximity to the JWST observatory. This proved to be challenging for two reasons: 1) A large quantity of NASA cleanroom suits needed to be shipped to CSG to account for the heavy volume of NASA and ESA personnel requiring access to the clean facilities. It became evident that shipping clean suits from the US to CSG in a timely fashion during the launch campaign would be challenging. Consequently, a backup plan needed to be established to avoid running out. 2) For safety purposes, Self-Contained Atmospheric Protection Ensemble (SCAPE) and Splash suits were required for hazardous operations. Neither type of suit was cleanroom compatible; therefore, a viable cleaning process needed to be developed to ensure both types of suits met JWST’s approved cleanliness standards. The NASA Contamination Control (CC) team partnered with CSG’s S5E cleanroom and suit processing team. The teams were able to make modifications to the S5E facility to create a NASA approved makeshift clean environment where NASA cleanroom suits and CSG Splash suits were inspected, folded, and bagged for cleanroom use once they were washed and dried. Since SCAPE suits could not be cleaned using conventional methods, a procedure was developed to clean and inspect the suits by the CC team in a temporary clean environment prior to fueling.

James Webb Space Telescope↗

NASA NTRS2008

Generalized Linear Covariance Analysis

We review and extend in two directions the results of prior work on generalized covariance analysis methods. This prior work allowed for partitioning of the state space into "solve-for" and "consider" parameters, allowed for differences between the formal values and the true values of the measurement noise, process noise, and a priori solve-for and consider covariances, and explicitly partitioned the errors into subspaces containing only the influence of the measurement noise, process noise, and a priori solve-for and consider covariances. In this work, we explicitly add sensitivity analysis to this prior work, and relax an implicit assumption that the batch estimator s anchor time occurs prior to the definitive span. We also apply the method to an integrated orbit and attitude problem, in which gyro and accelerometer errors, though not estimated, influence the orbit determination performance. We illustrate our results using two graphical presentations, which we call the "variance sandpile" and the "sensitivity mosaic," and we compare the linear covariance results to confidence intervals associated with ensemble statistics from a Monte Carlo analysis.

Carpenter, J. Russell↗

NASA NTRS2014

Generalized Linear Covariance Analysis

This talk presents a comprehensive approach to filter modeling for generalized covariance analysis of both batch least-squares and sequential estimators. We review and extend in two directions the results of prior work that allowed for partitioning of the state space into solve-for'' and consider'' parameters, accounted for differences between the formal values and the true values of the measurement noise, process noise, and textita priori solve-for and consider covariances, and explicitly partitioned the errors into subspaces containing only the influence of the measurement noise, process noise, and solve-for and consider covariances. In this work, we explicitly add sensitivity analysis to this prior work, and relax an implicit assumption that the batch estimator's epoch time occurs prior to the definitive span. We also apply the method to an integrated orbit and attitude problem, in which gyro and accelerometer errors, though not estimated, influence the orbit determination performance. We illustrate our results using two graphical presentations, which we call the variance sandpile'' and the sensitivity mosaic,'' and we compare the linear covariance results to confidence intervals associated with ensemble statistics from a Monte Carlo analysis.

Navagation↗

NASA NTRS2014

Generalized Linear Covariance Analysis

n/a↗

NASA NTRS2011

Precipitation Estimates for Hydroelectricity

Hydroelectric plants require precise and timely estimates of rain, snow and other hydrometeors for operations. However, it is far from being a trivial task to measure and predict precipitation. This paper presents the linkages between precipitation science and hydroelectricity, and in doing so it provides insight into current research directions that are relevant for this renewable energy. Methods described include radars, disdrometers, satellites and numerical models. Two recent advances that have the potential of being highly beneficial for hydropower operations are featured: the Global Precipitation Measuring (GPM) mission, which represents an important leap forward in precipitation observations from space, and high performance computing (HPC) and grid technology, that allows building ensembles of numerical weather and climate models.

Tapiador, Francisco J.↗