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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Comparison of a 2D Photochemical Model to Data Using Statistical Trend Analysis

We have analyzed our 23-year merged ozone data set for variability and trends with a statistical time-series model. To assist in that analysis, we have analyzed the Goddard 2D photochemical model for the same time period with the same time-series model. Multiple runs of the photochemical model allow us to separate the effects of various terms on ozone, such as solar cycle and volcanic eruptions. We use this to help us separate those signals from each other in the data. We also used a smoothed version of the photochemical model's prediction of global ozone change in place of a simple linear trend. We find a number of interesting results. This particular photochemical model is more sensitive to chlorine perturbations than the atmosphere appears to be. It is less sensitive to solar cycle. It predicts an effect from the Pinatubo eruption that is nearly symmetric in the two hemispheres, but the data appears to have not responded to Pinatubo in the southern mid-latitudes. These results and their uncertainties will be discussed.

Bhartia, P. K.↗
DOE OSTI2022

Statistics of internal stress fluctuations in dislocated crystals and relevance to density-based dislocation dynamics models

A statistical analysis of internal stress fluctuations, defined as the difference between the local mean stress and stress on dislocations, is presented for deforming crystals with 3D discrete dislocation systems. Dislocation realizations are generated using dislocation dynamics simulations and the associated stress field is computed as a superposition of a regularized stress field of dislocation lines within the domain of the solution and a complementary stress field computed via a finite-element boundary value problem. The internal stress fluctuations of interest are defined by an ensemble of the difference between the stress on dislocation lines and the local mean field stress in the crystal. The latter is established in a piecewise fashion over small voxels in the crystal thus allowing the difference between the local average stress and stress on segments to be easily estimated. The results show that the Schmid stress (resolved shear stress) and Escaig stress fluctuations on various slip systems sampled over a random set of points follow a Cauchy (Lorentz) distribution at all strain levels, with the amplitude and width of the distribution being dependent on the strain. Finally, the implications of the Schmid and Escaig internal stress fluctuations are discussed from the points of view of dislocation cross-slip and the dislocation motion in continuum dislocation dynamics.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Modeling regional precipitation over the Indus River basin of Pakistan using statistical downscaling

Complex processes govern spatiotemporal distribution of precipitation within the high-mountainous headwater regions (commonly known as the upper Indus basin (UIB)), of the Indus River basin of Pakistan. Reliable precipitation simulations particularly over the UIB present a major scientific challenge due to regional complexity and inadequate observational coverage. Here, we present a statistical downscaling approach to model observed precipitation of the entire Indus basin, with a focus on UIB within available data constraints. Taking advantage of recent high altitude (HA) observatories, we perform precipitation regionalization using K-means cluster analysis to demonstrate effectiveness of low-altitude stations to provide useful precipitation inferences over more uncertain and hydrologically important HA of the UIB. We further employ generalized linear models (GLM) with gamma and Tweedie distributions to identify major dynamic and thermodynamic drivers from a reanalysis dataset within a robust cross-validation framework that explain observed spatiotemporal precipitation patterns across the Indus basin. Final statistical models demonstrate higher predictability to resolve precipitation variability over wetter southern Himalayans and different lower Indus regions, by mainly using different dynamic predictors. The modeling framework also shows an adequate performance over more complex and uncertain trans-Himalayans and the northwestern regions of the UIB, particularly during the seasons dominated by the westerly circulations. However, the cryosphere-dominated trans-Himalayan regions, which largely govern the basin hydrology, require relatively complex models that contain dynamic and thermodynamic circulations. Furthermore, we also analyzed relevant atmospheric circulations during precipitation anomalies over the UIB, to evaluate physical consistency of the statistical models, as an additional measure of reliability. Overall, our results suggest that such circulation-based statistical downscaling has the potential to improve our understanding towards distinct features of the regional-scale precipitation across the upper and lower Indus basin. Additionally, such understanding should help to assess the response of this complex, data-scarce, and climate-sensitive river basin amid future climatic changes, to serve communal and scientific interests.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1972

Structural model optimization using statistical evaluation

The results of research in applying statistical methods to the problem of structural dynamic system identification are presented. The study is in three parts: a review of previous approaches by other researchers, a development of various linear estimators which might find application, and the design and development of a computer program which uses a Bayesian estimator. The method is tried on two models and is successful where the predicted stiffness matrix is a proper model, e.g., a bending beam is represented by a bending model. Difficulties are encountered when the model concept varies. There is also evidence that nonlinearity must be handled properly to speed the convergence.

Collins, J. D.↗
DOE OSTI2022

Graph link prediction in computer networks using Poisson matrix factorisation

Graph link prediction is an important task in cybersecurity: relationships between entities within a computer network, such as users interacting with computers or system libraries and the corresponding processes that use them, can provide key insights into adversary behaviour. Poisson matrix factorisation (PMF) is a popular model for link prediction in large networks, particularly useful for its scalability. In this article PMF is extended to include scenarios that are commonly encountered in cybersecurity applications. Specifically, an extension is proposed to explicitly handle binary adjacency matrices and include known categorical covariates associated with the graph nodes. A seasonal PMF model is also presented to handle seasonal networks. To allow the methods to scale to large graphs, variational methods are discussed for performing fast inference. The results show an improved performance over the standard PMF model and other statistical network models.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2004

Statistical and Prediction modeling of the Ka Band Using Experimental Results from ACTS Propagation Terminals at 20.185 and 27.505 GHZ

With the increase in demand for wireless communication services, most of the operating frequency bands have become very congested. The increase of wireless costumers is only fractional contribution to this phenomenon. The demand for more services such as video streams and internet explorer which require a lot of band width has been a more significant contributor to the congestion in a communication system. One way to increase the amount of information or data per unit of time transmitted with in a wireless communication system is to use a higher radio frequency. However in spite the advantage available in the using higher frequency bands such as, the Ka-band, higher frequencies also implies short wavelengths. And shorter wavelengths are more susceptible to rain attenuation. Until the Advanced Communication Technology Satellite (ACTS) was launched, the Ka- band frequency was virtually unused - the majority of communication satellites operated in lower frequency bands called the C- and Ku- bands. Ka-band is desirable because its higher frequency allows wide bandwidth applications, smaller spacecraft and ground terminal components, and stronger signal strength. Since the Ka-band is a high frequency band, the millimeter wavelengths of the signals are easily degraded by rain. This problem known as rain fade or rain attenuation The Advanced Communication Technology Satellite (ACTS) propagation experiment has collected 5 years of Radio Frequency (RF) attenuation data from December 1993 to November 1997. The objective of my summer work is to help develop the statistics and prediction techniques that will help to better characterize the Ka Frequency band. The statistical analysis consists of seasonal and cumulative five-year attenuation statistics for the 20.2 and 27.5 GHz. The cumulative five-year results give the link outage that occurs for a given link margin. The experiment has seven ground station terminals that can be attributed to a unique rain zone climate. The locations are White Sands, NM, Tampa, Fly Clarksburg, MD, Norman, OK, Ft. Collins, COY Vancouver, BC, and Fairbanks, AK. The analysis will help us to develop and define specific parameters that will help system engineers develop the appropriated instrumentation and structure for a Ka-band wireless communication systems and networks.

Ogunwuyi, Oluwatosin O.↗
NASA NTRS1986

A statistical rain attenuation prediction model with application to the advanced communication technology satellite project. 1: Theoretical development and application to yearly predictions for selected cities in the United States

A rain attenuation prediction model is described for use in calculating satellite communication link availability for any specific location in the world that is characterized by an extended record of rainfall. Such a formalism is necessary for the accurate assessment of such availability predictions in the case of the small user-terminal concept of the Advanced Communication Technology Satellite (ACTS) Project. The model employs the theory of extreme value statistics to generate the necessary statistical rainrate parameters from rain data in the form compiled by the National Weather Service. These location dependent rain statistics are then applied to a rain attenuation model to obtain a yearly prediction of the occurrence of attenuation on any satellite link at that location. The predictions of this model are compared to those of the Crane Two-Component Rain Model and some empirical data and found to be very good. The model is then used to calculate rain attenuation statistics at 59 locations in the United States (including Alaska and Hawaii) for the 20 GHz downlinks and 30 GHz uplinks of the proposed ACTS system. The flexibility of this modeling formalism is such that it allows a complete and unified treatment of the temporal aspects of rain attenuation that leads to the design of an optimum stochastic power control algorithm, the purpose of which is to efficiently counter such rain fades on a satellite link.

Manning, Robert M.↗
DOE OSTI2024

Data-driven prediction of scaling and ignition of inertial confinement fusion experiments

Recent advances in inertial confinement fusion (ICF) at the National Ignition Facility (NIF), including ignition and energy gain, are enabled by a close coupling between experiments and high-fidelity simulations. Neither simulations nor experiments can fully constrain the behavior of ICF implosions on their own, meaning pre- and postshot simulation studies must incorporate experimental data to be reliable. Linking past data with simulations to make predictions for upcoming designs and quantifying the uncertainty in those predictions has been an ongoing challenge in ICF research. We have developed a data-driven approach to prediction and uncertainty quantification that combines large ensembles of simulations with Bayesian inference and deep learning. The approach builds a predictive model for the statistical distribution of key performance parameters, which is jointly informed by past experiments and physics simulations. The prediction distribution captures the impact of experimental uncertainty, expert priors, design changes, and shot-to-shot variations. We have used this new capability to predict a 10× increase in ignition probability between Hybrid-E shots driven with 2.05 MJ compared to 1.9 MJ, and validated our predictions against subsequent experiments. We describe our new Bayesian postshot and prediction capabilities, discuss their application to NIF ignition and validate the results, and finally investigate the impact of data sparsity on our prediction results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1971

Properties of hadron matter. II - Dense baryon matter and neutron stars.

In this article we have provided certain details of a nuclear-matter computation, based on the Brueckner-Bethe-Goldstone theory of nuclear reaction, which leads to an equation of state for matter in the density region of 10 to 500 trillion g/cu cm. We also explore the possibilities that at very high baryon densities or for very short baryon separations, the net baryon-baryon interaction may be negligible so that the results of dynamical models, like the statistical bootstrap model and the dual-resonance model, may be applicable to the study of dense baryon matter. Several plausible equations of state are constructed, and their effect on the limiting mass of the neutron star is examined.

Leung, Y. C.↗
NASA NTRS1974

Model optimization using statistical estimation

Program revises initial or prior estimate of stiffness and mass parameters to parameters yielding frequency and mode characteristics in agreement with test data. Variances are also calculated and consequently define uncertainties of final estimates.

Collins, J. D.↗
NASA NTRS1979

A computer program for thermal radiation from gaseous rocket exhuast plumes (GASRAD)

A computer code is presented for predicting incident thermal radiation from defined plume gas properties in either axisymmetric or cylindrical coordinate systems. The radiation model is a statistical band model for exponential line strength distribution with Lorentz/Doppler line shapes for 5 gaseous species (H2O, CO2, CO, HCl and HF) and an appoximate (non-scattering) treatment of carbon particles. The Curtis-Godson approximation is used for inhomogeneous gases, but a subroutine is available for using Young's intuitive derivative method for H2O with Lorentz line shape and exponentially-tailed-inverse line strength distribution. The geometry model provides integration over a hemisphere with up to 6 individually oriented identical axisymmetric plumes, a single 3-D plume, Shading surfaces may be used in any of 7 shapes, and a conical limit may be defined for the plume to set individual line-of-signt limits. Intermediate coordinate systems may specified to simplify input of plumes and shading surfaces.

Reardon, J. E.↗
NASA NTRS1982

Modeling the joint statistics of satellite path XPD and attenuation

A new and simple technique for estimating from attenuation statistics alone the joint distribution of attenuation and cross-polarization impairments on a satellite-to-earth radio path is presented. It compares measurements with predictions for the CTS spacecraft 11.7 GHz right-hand circularly polarized downlink during the first six months of 1979.

Gaines, J. M.↗
NASA NTRS1984

Model development and statistical investigation of turbine blade mistuning

This paper discusses the development of an efficient algorithm which calculates the individual blade response of a bladed turbine disk, the subsequent statistical investigation to establish mistuning dependencies, and procedures which reduce the increase in blade amplitudes caused by mistuning.

Griffin, J. H.↗
NASA NTRS1984

Statistical Time Series Models of Pilot Control with Applications to Instrument Discrimination

A general description of the methodology used in obtaining the transfer function models and verification of model fidelity, frequency domain plots of the modeled transfer functions, numerical results obtained from an analysis of poles and zeroes obtained from z plane to s-plane conversions of the transfer functions, and the results of a study on the sequential introduction of other variables, both exogenous and endogenous into the loop are contained.

Altschul, R. E.↗