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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Estimation of the Ocean Skin Temperature using the NASA GEOS Atmospheric Data Assimilation System

This report documents the status of the development of a sea surface temperature (SST) analysis for the Goddard Earth Observing System (GEOS) Version-5 atmospheric data assimilation system (ADAS). Its implementation is part of the steps being taken toward the development of an integrated earth system analysis. Currently, GEOS-ADAS SST is a bulk ocean temperature (from ocean boundary conditions), and is almost identical to the skin sea surface temperature. Here we describe changes to the atmosphere-ocean interface layer of the GEOS-atmospheric general circulation model (AGCM) to include near surface diurnal warming and cool-skin effects. We also added SST relevant Advanced Very High Resolution Radiometer (AVHRR) observations to the GEOS-ADAS observing system. We provide a detailed description of our analysis of these observations, along with the modifications to the interface between the GEOS atmospheric general circulation model, gridpoint statistical interpolation-based atmospheric analysis and the community radiative transfer model. Our experiments (with and without these changes) show improved assimilation of satellite radiance observations. We obtained a closer fit to withheld, in-situ buoys measuring near-surface SST. Evaluation of forecast skill scores corroborate improvements seen in the observation fits. Along with a discussion of our results, we also include directions for future work.

AGCM↗
NASA NTRS1997

Fade Dynamics and Its Evolution: The Other Part of the Acts Rain Prediction Model

The inception of the Advanced Communication Technology Satellite (ACTS) Project has required as similarly advanced statistical mathematical modeling formalism to describe the behavior of the 30/20 GHz links emanating to and from the earth terminals through the deleterious effects of the earth's atmosphere. The resulting ACTS Rain Attenuation Prediction Model has been thoroughly described in [Manning, 1990]. In the present paper, the basic rudiments of this model will be reviewed; Section 1 covers the static or time-independent portion of the model and Section 2 covers the dynamic of time-dependent portion. The results of Section 2 are then applied to a new approximate solution of the famous problem of the time duration tau of a fade of random process below some threshold. This is known as the fade duration. The new approximate solution was published in Russian [Denisenko] and, unfortunately, was never published into English. Hence, this work is restated following [Denisenko] in Section 3 which is immediately applied to the random rain fade process. The results for all five ACTS propagation sites as well as Tampa, FL are then given.

Manning, Robert M.↗
NASA NTRS1997

Fade Dynamics and its Evolution: The Other Part of the ACTS Rain Prediction Model

The inception of the Advanced Communication Technology Satellite (ACTS) Project has required a similarly advanced statistical mathematical modeling formalism to describe the behavior of the 30/20 GHz links emanating to and from the earth terminals through the deleterious effects of the earth's atmosphere. The resulting ACTS Rain Attenuation Prediction Model has been thoroughly described in (Manning). In the present paper, the basic rudiments of this model will be reviewed; Section 1 covers the static or time-independent portion of the model and Section 2 covers the dynamic or time-dependent portion. The results of Section 2 are then applied to a new approximate solution of the famous problem of the time duration tau of a fade of a random process below some threshold. This is known as the fade duration. The new approximate solution was published in Russian (Denisenko) and, unfortunately, was never published into English. Hence, this work is restated following (Denisenko) in Section 3 which is immediately applied to the random rain fade process. The results for all five ACTS propagation sites as well as Tampa, FL are then given.

Manning, Robert M.↗
NASA NTRS2004

Multivariate Error Covariance Estimates by Monte-Carlo Simulation for Assimilation Studies in the Pacific Ocean

One of the most difficult aspects of ocean state estimation is the prescription of the model forecast error covariances. The paucity of ocean observations limits our ability to estimate the covariance structures from model-observation differences. In most practical applications, simple covariances are usually prescribed. Rarely are cross-covariances between different model variables used. Here a comparison is made between a univariate Optimal Interpolation (UOI) scheme and a multivariate OI algorithm (MvOI) in the assimilation of ocean temperature. In the UOI case only temperature is updated using a Gaussian covariance function and in the MvOI salinity, zonal and meridional velocities as well as temperature, are updated using an empirically estimated multivariate covariance matrix. Earlier studies have shown that a univariate OI has a detrimental effect on the salinity and velocity fields of the model. Apparently, in a sequential framework it is important to analyze temperature and salinity together. For the MvOI an estimation of the model error statistics is made by Monte-Carlo techniques from an ensemble of model integrations. An important advantage of using an ensemble of ocean states is that it provides a natural way to estimate cross-covariances between the fields of different physical variables constituting the model state vector, at the same time incorporating the model's dynamical and thermodynamical constraints as well as the effects of physical boundaries. Only temperature observations from the Tropical Atmosphere-Ocean array have been assimilated in this study. In order to investigate the efficacy of the multivariate scheme two data assimilation experiments are validated with a large independent set of recently published subsurface observations of salinity, zonal velocity and temperature. For reference, a third control run with no data assimilation is used to check how the data assimilation affects systematic model errors. While the performance of the UOI and MvOI is similar with respect to the temperature field, the salinity and velocity fields are greatly improved when multivariate correction is used, as evident from the analyses of the rms differences of these fields and independent observations. The MvOI assimilation is found to improve upon the control run in generating the water masses with properties close to the observed, while the UOI failed to maintain the temperature and salinity structure.

Borovikov, Anna↗
NASA NTRS2003

Ising model of cardiac thin filament activation with nearest-neighbor cooperative interactions

We have developed a model of cardiac thin filament activation using an Ising model approach from equilibrium statistical physics. This model explicitly represents nearest-neighbor interactions between 26 troponin/tropomyosin units along a one-dimensional array that represents the cardiac thin filament. With transition rates chosen to match experimental data, the results show that the resulting force-pCa (F-pCa) relations are similar to Hill functions with asymmetries, as seen in experimental data. Specifically, Hill plots showing (log(F/(1-F)) vs. log [Ca]) reveal a steeper slope below the half activation point (Ca(50)) compared with above. Parameter variation studies show interplay of parameters that affect the apparent cooperativity and asymmetry in the F-pCa relations. The model also predicts that Ca binding is uncooperative for low [Ca], becomes steeper near Ca(50), and becomes uncooperative again at higher [Ca]. The steepness near Ca(50) mirrors the steep F-pCa as a result of thermodynamic considerations. The model also predicts that the correlation between troponin/tropomyosin units along the one-dimensional array quickly decays at high and low [Ca], but near Ca(50), high correlation occurs across the whole array. This work provides a simple model that can account for the steepness and shape of F-pCa relations that other models fail to reproduce.

Evaluation Studies↗
NASA NTRS1999

Mathematical model to estimate risk of calcium-containing renal stones

BACKGROUND/AIMS: Astronauts exposed to microgravity during the course of spaceflight undergo physiologic changes that alter the urinary environment so as to increase the risk of renal stone formation. This study was undertaken to identify a simple method with which to evaluate the potential risk of renal stone development during spaceflight. METHOD: We used a large database of urinary risk factors obtained from 323 astronauts before and after spaceflight to generate a mathematical model with which to predict the urinary supersaturation of calcium stone forming salts. RESULT: This model, which involves the fewest possible analytical variables (urinary calcium, citrate, oxalate, phosphorus, and total volume), reliably and accurately predicted the urinary supersaturation of the calcium stone forming salts when compared to results obtained from a group of 6 astronauts who collected urine during flight. CONCLUSIONS: The use of this model will simplify both routine medical monitoring during spaceflight as well as the evaluation of countermeasures designed to minimize renal stone development. This model also can be used for Earth-based applications in which access to analytical resources is limited.

NASA Center JSC↗
NASA NTRS2017

The Substorm Cycle as Reproduced by Global MHD Models

Recently, Gordeev et al. (2015) suggested a method to test global MHD models against statistical empirical data. They showed that four community-available global MHD models supported by the Community Coordinated Modeling Center (CCMC) produce a reasonable agreement with reality for those key parameters (the magnetospheric size, magnetic field, and pressure) that are directly related to the large-scale equilibria in the outer magnetosphere. Based on the same set of simulation runs, here we investigate how the models reproduce the global loading-unloading cycle. We found that in terms of global magnetic flux transport, three examined CCMC models display systematically different response to idealized2 h north then 2 h south interplanetary magnetic field (IMF) Bz variation. The LFM model shows a depressed return convection and high loading rate during the growth phase as well as enhanced return convection and high unloading rate during the expansion phase, with the amount of loaded unloaded magnetotail flux and the growth phase duration being the closest to their observed empirical values during isolated substorms. Two other models exhibit drastically different behavior. In the BATS-R-US model the plasma sheet convection shows a smooth transition to the steady convection regime after the IMF southward turning. In the Open GGCM a weak plasma sheet convection has comparable intensities during both the growth phase and the following slow unloading phase. We also demonstrate potential technical problem in the publicly available simulations which is related to post processing interpolation and could affect the accuracy of magnetic field tracing and of other related procedures.

Gordeev, E.↗
NASA NTRSDate not supplied

Uncertainty in the response of sudden stratospheric warmings and stratosphere- troposphere coupling to quadrupled CO2 concentrations in CMIP6 models

Major sudden stratospheric warmings (SSWs), vortex formation and final breakdown dates are key highlight points of the stratospheric polar vortex. These phenomena are relevant for stratosphere-troposphere coupling, which explains the interest in understanding their future changes. However, up to now, there is not a clear consensus on which projected changes to the polar vortex are robust, particularly in the Northern Hemisphere, possibly due to short data record or relatively moderate CO2 forcing. The new simulations performed under the Coupled Model Intercomparison Project, Phase 6, together with the long daily data requirements of the DynVarMIP project in preindustrial and quadrupled CO2 (4xCO2 ) forcing simulations provide a new opportunity to revisit this topic by overcoming the limitations mentioned above. In this study, we analyze this new model output to document the change, if any, in the frequency of SSWs under 4xCO2 forcing. Our analysis reveals a large disagreement across the models as to the sign of this change, even though most models show a statistically significant change. The models, however, are in good agreement as to the impact of SSWs over the North Atlantic: there is no indication of a change under 4xCO2 forcing. Over the Pacific, however, the change is more uncertain. Finally, the models show robust changes to the seasonal cycle in the stratosphere. Specifically, we find a longer duration of the stratospheric polar vortex, and thus a longer season of stratosphere-troposphere coupling.

sudden stratospheric warmings (SSWs)↗
DOE OSTI2024

Random insights into the complexity of two-dimensional tensor network calculations

Projected entangled pair states (PEPS) offer memory-efficient representations of some quantum many-body states that obey an entanglement area law and are the basis for classical simulations of ground states in two-dimensional (2d) condensed matter systems. However, rigorous results show that exactly computing observables from a 2d PEPS state is generically a computationally hard problem. Yet approximation schemes for computing properties of 2d PEPS are regularly used, and empirically seen to succeed, for a large subclass of (“not too entangled”) condensed matter ground states. Adopting the philosophy of random matrix theory, in this work, we analyze the complexity of approximately contracting a 2d random PEPS by exploiting an analytic mapping to an effective replicated statistical mechanics model that permits a controlled analysis at a large bond dimension. Through this statistical-mechanics lens, we argue that (i) although approximately sampling wave-function amplitudes of random PEPS faces a computational-complexity phase transition above a critical bond dimension, and (ii) one can generically efficiently estimate the norm and correlation functions for any finite bond dimension. Furthermore, these results are supported numerically for various bond-dimension regimes. It is an important open question whether the above results for random PEPS apply more generally also to PEPS representing physically relevant ground states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1995

Analysis of the progressive failure of brittle matrix composites

This report investigates two of the most common modes of localized failures, namely, periodic fiber-bridged matrix cracks and transverse matrix cracks. A modification of Daniels' bundle theory is combined with Weibull's weakest link theory to model the statistical distribution of the periodic matrix cracking strength for an individual layer. Results of the model predictions are compared with experimental data from the open literature. Extensions to the model are made to account for possible imperfections within the layer (i.e., nonuniform fiber lengths, irregular crack spacing, and degraded in-situ fiber properties), and the results of these studies are presented. A generalized shear-lag analysis is derived which is capable of modeling the development of transverse matrix cracks in material systems having a general multilayer configuration and under states of full in-plane load. A method for computing the effective elastic properties for the damaged layer at the global level is detailed based upon the solution for the effects of the damage at the local level. This methodology is general in nature and is therefore also applicable to (0(sub m)/90(sub n))(sub s) systems. The characteristic stress-strain response for more general cases is shown to be qualitatively correct (experimental data is not available for a quantitative evaluation), and the damage evolution is recorded in terms of the matrix crack density as a function of the applied strain. Probabilistic effects are introduced to account for the statistical nature of the material strengths, thus allowing cumulative distribution curves for the probability of failure to be generated for each of the example laminates. Additionally, Oh and Finney's classic work on fracture location in brittle materials is extended and combined with the shear-lag analysis. The result is an analytical form for predicting the probability density function for the location of the next transverse crack occurrence within a crack bounded region. The results of this study verified qualitatively the validity of assuming a uniform crack spacing (as was done in the shear-lag model).

Thomas, David J.↗
NASA NTRS1983

Statistical Analysis of a Debugging Model

Suppose that a system is undergoing a sequence of trials and design changes in an effort to find and eliminate design flaws in the system. Specifically, suppose that each trial is classified as an assignable cause failure (if the failure is due to one or more design flaws), an inherent failure (if the failure is not due to a design flaw), or a success. After each assignable cause failure, the design flaws that caused the failure are removed. In the case of statistically independent and identical design flaws, a probabilistic model is developed to describe this debugging process. Explicit expressions are obtained for the distributions of the important random variables and for the important measures of reliability. Statistical methods are developed for estimating the parameters of the model from accumulated test data.

Siegrist, K.↗
NASA NTRS1976

Vector wind and vector wind shear models 0 to 27 km altitude for Cape Kennedy, Florida, and Vandenberg AFB, California

The techniques are presented to derive several statistical wind models. The techniques are from the properties of the multivariate normal probability function. Assuming that the winds can be considered as bivariate normally distributed, then (1) the wind components and conditional wind components are univariate normally distributed, (2) the wind speed is Rayleigh distributed, (3) the conditional distribution of wind speed given a wind direction is Rayleigh distributed, and (4) the frequency of wind direction can be derived. All of these distributions are derived from the 5-sample parameter of wind for the bivariate normal distribution. By further assuming that the winds at two altitudes are quadravariate normally distributed, then the vector wind shear is bivariate normally distributed and the modulus of the vector wind shear is Rayleigh distributed. The conditional probability of wind component shears given a wind component is normally distributed. Examples of these and other properties of the multivariate normal probability distribution function as applied to Cape Kennedy, Florida, and Vandenberg AFB, California, wind data samples are given. A technique to develop a synthetic vector wind profile model of interest to aerospace vehicle applications is presented.

Smith, O. E.↗
NASA NTRS1994

Canopy reflectance modelling of semiarid vegetation

Three different types of remote sensing algorithms for estimating vegetation amount and other land surface biophysical parameters were tested for semiarid environments. These included statistical linear models, the Li-Strahler geometric-optical canopy model, and linear spectral mixture analysis. The two study areas were the National Science Foundation's Jornada Long Term Ecological Research site near Las Cruces, NM, in the northern Chihuahuan desert, and the HAPEX-Sahel site near Niamey, Niger, in West Africa, comprising semiarid rangeland and subtropical crop land. The statistical approach (simple and multiple regression) resulted in high correlations between SPOT satellite spectral reflectance and shrub and grass cover, although these correlations varied with the spatial scale of aggregation of the measurements. The Li-Strahler model produced estimated of shrub size and density for both study sites with large standard errors. In the Jornada, the estimates were accurate enough to be useful for characterizing structural differences among three shrub strata. In Niger, the range of shrub cover and size in short-fallow shrublands is so low that the necessity of spatially distributed estimation of shrub size and density is questionable. Spectral mixture analysis of multiscale, multitemporal, multispectral radiometer data and imagery for Niger showed a positive relationship between fractions of spectral endmembers and surface parameters of interest including soil cover, vegetation cover, and leaf area index.

Franklin, Janet↗
DOE OSTI2025

First simultaneous measurement of the γ-ray and neutron emission probabilities in inverse kinematics at a heavy-ion storage ring

The probabilities for γ-ray and particle emission as a function of the excitation energy of a decaying nucleus are valuable observables for constraining the ingredients of the models that describe the deexcitation of nuclei near the particle emission threshold. These models are essential in nuclear astrophysics and applications. In this paper, we have for the first time simultaneously measured the γ-ray and neutron emission probabilities of 208 Pb. The measurement was performed in inverse kinematics at the Experimental Storage Ring (ESR) of the GSI/FAIR facility, where a 208 Pb beam interacted through the 208 Pb (p,p') reaction with a hydrogen gas jet target. Instead of detecting the γ rays and neutrons emitted by 208 Pb, we detected the heavy beamlike residues produced after γ and neutron emission. These heavy residues were fully separated by a dipole magnet of the ESR and were detected with outstanding efficiencies. The comparison of the measured probabilities with model calculations has allowed us to test and select different descriptions of the γ-ray strength function and the nuclear level density available in the literature.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1985

Strength Modeling Report

Strength modeling is a complex and multi-dimensional issue. There are numerous parameters to the problem of characterizing human strength, most notably: (1) position and orientation of body joints; (2) isometric versus dynamic strength; (3) effector force versus joint torque; (4) instantaneous versus steady force; (5) active force versus reactive force; (6) presence or absence of gravity; (7) body somatotype and composition; (8) body (segment) masses; (9) muscle group envolvement; (10) muscle size; (11) fatigue; and (12) practice (training) or familiarity. In surveying the available literature on strength measurement and modeling an attempt was made to examine as many of these parameters as possible. The conclusions reached at this point toward the feasibility of implementing computationally reasonable human strength models. The assessment of accuracy of any model against a specific individual, however, will probably not be possible on any realistic scale. Taken statistically, strength modeling may be an effective tool for general questions of task feasibility and strength requirements.

Badler, N. I.↗
NASA NTRS2011

Calibrated Noise Measurements with Induced Receiver Gain Fluctuations

The lack of well-developed techniques for modeling changing statistical moments in our observations has stymied the application of stochastic process theory in science and engineering. These limitations were encountered when modeling the performance of radiometer calibration architectures and algorithms in the presence of non stationary receiver fluctuations. Analyses of measured signals have traditionally been limited to a single measurement series. Whereas in a radiometer that samples a set of noise references, the data collection can be treated as an ensemble set of measurements of the receiver state. Noise Assisted Data Analysis is a growing field of study with significant potential for aiding the understanding and modeling of non stationary processes. Typically, NADA entails adding noise to a signal to produce an ensemble set on which statistical analysis is performed. Alternatively as in radiometric measurements, mixing a signal with calibrated noise provides, through the calibration process, the means to detect deviations from the stationary assumption and thereby a measurement tool to characterize the signal's non stationary properties. Data sets comprised of calibrated noise measurements have been limited to those collected with naturally occurring fluctuations in the radiometer receiver. To examine the application of NADA using calibrated noise, a Receiver Gain Modulation Circuit (RGMC) was designed and built to modulate the gain of a radiometer receiver using an external signal. In 2010, an RGMC was installed and operated at the National Institute of Standards and Techniques (NIST) using their Noise Figure Radiometer (NFRad) and national standard noise references. The data collected is the first known set of calibrated noise measurements from a receiver with an externally modulated gain. As an initial step, sinusoidal and step-function signals were used to modulate the receiver gain, to evaluate the circuit characteristics and to study the performance of a variety of calibration algorithms. The receiver noise temperature and time-bandwidth product of the NFRad are calculated from the data. Statistical analysis using temporal-dependent calibration algorithms reveals that the natural occurring fluctuations in the receiver are stationary over long intervals (100s of seconds); however the receiver exhibits local non stationarity over the interval over which one set of reference measurements are collected. A variety of calibration algorithms have been applied to the data to assess algorithms' performance with the gain fluctuation signals. This presentation will describe the RGMC, experiment design and a comparative analysis of calibration algorithms.

Racette, Paul↗
NASA NTRSDate not supplied

Statistical learning framework for safety and failure analysis of a DNN-based autonomous aircraft system

Deep Neural Networks (DNNs) and Machine Learning technology is increasingly used for safety-critical applications in the Aerospace domain. To ensure safe operations, the DNN and the system must undergo rigorous verification and validation, including advanced statistical analyses. Performance and safety of the DNN and system behavior must not only be analyzed for the nominal case, but under numerous off-nominal and failure cases. In this paper we will describe how our statistical learning framework SYSAI can efficiently perform such analyses using the tool’s unique combination of advanced learning modeling and statistical analysis techniques. SYSAI can effectively explore the high-dimensional state and failure space of the system under test; geometrical shape detection of safety regions and boundaries support explainability of the results to the designer. In this paper, we report experiments and results obtained with a vision-based DNN control system (ACT) that is capable of autonomously steering an aircraft down a runway.

Yuning He↗