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At least 1,747 records · Page 97

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DOE OSTI2019

Large covariance matrices: accurate models without mocks

Abstract Covariance matrix estimation is a persistent challenge for cosmology. We focus on a class of model covariance matrices that can be generated with high accuracy and precision, using a tiny fraction of the computational resources that would be required to achieve comparably precise covariance matrices using mock catalogues. In previous work, the free parameters in these models were determined using sample covariance matrices computed using a large number of mocks, but we demonstrate that those parameters can be estimated consistently and with good precision by applying jackknife methods to a single survey volume. This enables model covariance matrices that are calibrated from data alone, with no reference to mocks.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Optimization-Based Model Reduction Scheme for Renewable Energy Power Plants Using Standardized Testing Scenarios

This paper presents an optimization-based model reduction scheme for renewable energy (RE) power plants consisting of inverter-based resources (IBRs) operating in grid-following (GFL) or grid-forming (GFM) modes. More importantly, the datasets feeding the optimization-based model reduction scheme are generated and re-used through the standardized grid-interactive testing scenarios. Particularly, the proposed scheme makes use of the power plant point of common coupling (PCC) measurements of various quantities specified by standardized tests (e.g., voltage and frequency ride through) as per IEEE 2800, to estimate the parameters of the reduced-order model such that its dynamic performance aligns with the original detailed power plant model. The proposed model reduction approach does not require the parameters of individual IBRs and using standardized test data as input to the formulated optimization problem simplifies the reduced-order modelling scheme. Extensive case studies following standardized test scenarios verified the remarkable accuracy of the proposed approach.

Yallamilli, Ram S. [Purdue University]↗

DOE OSTI2015

Bayesian network ensemble as a multivariate strategy to predict radiation pneumonitis risk

Purpose: Prediction of radiation pneumonitis (RP) has been shown to be challenging due to the involvement of a variety of factors including dose–volume metrics and radiosensitivity biomarkers. Some of these factors are highly correlated and might affect prediction results when combined. Bayesian network (BN) provides a probabilistic framework to represent variable dependencies in a directed acyclic graph. The aim of this study is to integrate the BN framework and a systems’ biology approach to detect possible interactions among RP risk factors and exploit these relationships to enhance both the understanding and prediction of RP. Methods: The authors studied 54 nonsmall-cell lung cancer patients who received curative 3D-conformal radiotherapy. Nineteen RP events were observed (common toxicity criteria for adverse events grade 2 or higher). Serum concentration of the following four candidate biomarkers were measured at baseline and midtreatment: alpha-2-macroglobulin, angiotensin converting enzyme (ACE), transforming growth factor, interleukin-6. Dose-volumetric and clinical parameters were also included as covariates. Feature selection was performed using a Markov blanket approach based on the Koller–Sahami filter. The Markov chain Monte Carlo technique estimated the posterior distribution of BN graphs built from the observed data of the selected variables and causality constraints. RP probability was estimated using a limited number of high posterior graphs (ensemble) and was averaged for the final RP estimate using Bayes’ rule. A resampling method based on bootstrapping was applied to model training and validation in order to control under- and overfit pitfalls. Results: RP prediction power of the BN ensemble approach reached its optimum at a size of 200. The optimized performance of the BN model recorded an area under the receiver operating characteristic curve (AUC) of 0.83, which was significantly higher than multivariate logistic regression (0.77), mean heart dose (0.69), and a pre-to-midtreatment change in ACE (0.66). When RP prediction was made only with pretreatment information, the AUC ranged from 0.76 to 0.81 depending on the ensemble size. Bootstrap validation of graph features in the ensemble quantified confidence of association between variables in the graphs where ten interactions were statistically significant. Conclusions: The presented BN methodology provides the flexibility to model hierarchical interactions between RP covariates, which is applied to probabilistic inference on RP. The authors’ preliminary results demonstrate that such framework combined with an ensemble method can possibly improve prediction of RP under real-life clinical circumstances such as missing data or treatment plan adaptation.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Virgo Redux: The Masses and Stellar Content of Nuclei in Early-type Galaxies from Multiband Photometry and Spectroscopy

We present an analysis of 39 nuclei and their early-type hosts in the Virgo Cluster using 10 broadband filters: F300W, F475W, F850LP, F160W, u{sup ∗}griz, and K {sub s}. We describe the Virgo Redux program, which provides high-resolution UV and NIR imaging. Combining this data with optical and NIR imaging from the ACS Virgo Cluster Survey and the Next Generation Virgo Cluster Survey, we estimate masses, metallicities, and ages using simple stellar population (SSP) models. For 19 nuclei, we compare to SSP parameters derived from Keck and Gemini spectra and find reasonable agreement between the photometric and spectroscopic metallicity: the rms scatter is 0.3 dex. We reproduce the nucleus–galaxy mass fraction of 0.33{sub −0.07}{sup +0.09}% for galaxy stellar masses 10{sup 8.4}--10{sup 10.3} M{sub ⊙} with a typical precision of ∼35% for the nuclei masses. Based on available model predictions, there is no single preferred formation scenario for nuclei, suggesting that nuclei are formed stochastically through a mix of processes. Nuclei metallicities are statistically identical to those of their hosts, appearing 0.07 ± 0.3 dex more metal-rich on average; however, omitting galaxies with unusual origins, nuclei are 0.20 ± 0.28 dex more metal-rich. Nuclei appear to be 0.56 ± 0.12 dex more metal-rich than ultracompact dwarf galaxies (UCDs) at fixed mass. We find no clear age difference between nuclei and their galaxies, with nuclei displaying a broad range of ages. Interestingly, we find that the most massive nuclei may be flatter and more closely aligned with the semimajor axes of their hosts, suggesting that they formed through predominantly dissipative processes.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1974

A review of averaging techniques and their application to orbit determination systems

The theory of numerical averaging and analytical averaging will be reviewed and the application of these techniques to orbit and parameter estimation problems will be presented. Comparisons will be made between utilizing mean elements versus tracking data as the observation types. Results will be presented comparing the accuracy and efficiency of the combined orbit estimation and orbit prediction problem using averaged equations of motion, the Cowell equations of motion and the Brouwer general perturbation theory. The problem of converting the averaged element space back to osculating element space for orbit operations will also be discussed.

Velez, C. E.↗

NASA NTRS1974

Estimation of nonlinear aerodynamic derivatives of a variable geometry fighter aircraft from flight data

This paper is concerned with the estimation of stability and control parameters of a high performance fighter aircraft from data obtained from high angle of attack flight. The estimation process utilizes a maximum likelihood algorithm derived for the case of a nonlinear aerodynamic force and moment model. The aircraft used was a high speed variable sweep heavy weight fighter with twin vertical tails. Comparisons of results from the nonlinear analysis are made with linear theory and wind tunnel results when available.

Ramachandran, S.↗

NASA NTRS1978

M2 ocean tide parameters and the deceleration of the moon's mean longitude from satellite orbit data

An estimation was made of the principal long period spherical harmonic parameters in the representation for the M sub 2 ocean tide from the orbital histories of three satellites - 1967-92A (TRANSIT), Starlette, and GEOS-3. The data used were primarily the evolution of the orbital inclinations of the satellites, with the addition of the longitude of the ascending node from GEOS-3. The results are: (1) C sub 22 superscript + = 3.42 plus or minus 0.24 cm; (2) sub 42 superscript + = 0.97 plus or minus 0.12 cm; (3) epsilon subscript 22 superscript + = 325 D.5 plus or minus 3.D9; (4) epsilon subscript 42 superscript + = 42 = 124D.0 plus or minus 6 D.9. These values agree quite well with recent numerical models and another recent determination from satellite data. The M sub 2 parameters obtained here infer an N of -25 plus or minus 3 arc seconds/century squared, in good agreement with other investigators. The range of current determinations of N is from -24.6 to 27.2 arc second/century squared.

Felsentreger, T. L.↗

NASA NTRS1982

Determination of airplane aerodynamic parameters from flight data at high angles of attack

The problem of determining airplane aerodynamic model equations and estimating the associated parameters from flight data taken at high angles of attack is addressed. Two representations of the aerodynamic function based on the polynomial and spline representations are given. Then the technique of building an adequate model using a stepwise regression is presented with examples demonstrating the construction of the model and various approaches to model verification.

Klein, V.↗

NASA NTRS1982

Cross-validation for densities and regressions

Virtually all nonparametric (infinite dimensional) problems require the choice of a smoothing parameter. It is natural to attempt to use the data to guide the choice of this parameter. The most widely applicable data driven technique is cross validation. The method of cross validation is introduced and results are presented which establish consistency for certain cross validated density estimators and consistency as well as asymptotic normality for rigid regression.

Geman, S.↗

NASA NTRS1989

High-precision radiometric tracking for planetary approach and encounter in the inner solar system

The benefits of improved radiometric tracking data have been studied for planetary approach within the inner Solar System using the Mars Rover Sample Return trajectory as a model. It was found that the benefit of improved data to approach and encounter navigation was highly dependent on the a priori uncertainties assumed for several non-estimated parameters, including those for frame-tie, Earth orientation, troposphere delay, and station locations. With these errors at their current levels, navigational performance was found to be insensitive to enhancements in data accuracy. However, when expected improvements in these errors are modeled, performance with current-accuracy data significantly improves, with substantial further improvements possible with enhancements in data accuracy.

Christensen, C. S.↗

NASA NTRS1991

A numerical procedure for recovering true scattering coefficients from measurements with wide-beam antennas

A numerical procedure for estimating the true scattering coefficient, sigma(sup 0), from measurements made using wide-beam antennas. The use of wide-beam antennas results in an inaccurate estimate of sigma(sup 0) if the narrow-beam approximation is used in the retrieval process for sigma(sup 0). To reduce this error, a correction procedure was proposed that estimates the error resulting from the narrow-beam approximation and uses the error to obtain a more accurate estimate of sigma(sup 0). An exponential model was assumed to take into account the variation of sigma(sup 0) with incidence angles, and the model parameters are estimated from measured data. Based on the model and knowledge of the antenna pattern, the procedure calculates the error due to the narrow-beam approximation. The procedure is shown to provide a significant improvement in estimation of sigma(sup 0) obtained with wide-beam antennas. The proposed procedure is also shown insensitive to the assumed sigma(sup 0) model.

Wang, Qinglin↗

NASA NTRS1992

A rotorcraft flight database for validation of vision-based ranging algorithms

A helicopter flight test experiment was conducted at the NASA Ames Research Center to obtain a database consisting of video imagery and accurate measurements of camera motion, camera calibration parameters, and true range information. The database was developed to allow verification of monocular passive range estimation algorithms for use in the autonomous navigation of rotorcraft during low altitude flight. The helicopter flight experiment is briefly described. Four data sets representative of the different helicopter maneuvers and the visual scenery encountered during the flight test are presented. These data sets will be made available to researchers in the computer vision community.

Smith, Phillip N.↗

NASA NTRS1994

Investigation of spreading center ecolution by joint inversion of seafloor magnetic anomaly and tectonic fabric data

Spreading center segments that have experienced a complex tectonic history including rift propagation may have a complicated signature in bathymetric and magnetic anomaly data. To gain insight into the history of such regions, we have developed techniques in which both the magnetic anomaly patterns and seafloor fabric trends are predicted theoretically, and the combined predictions are compared numerically with the data to estimate best fitting parameters for the propagation history. Fitting functions are constructed to help determine which model best matches the digitized fabric and magnetic anomaly data. Such functions offer statistical criteria for choosing the best fit model. We use this approach to resolve the propagation history of the Cobb Offset along the Juan de Fuca ridge. In this example, the magnetic anomaly data prove more useful in defining the geometry of the propagation events, while the fabric, with its greater temporal resolution, is more useful for constraining the rate of propagation. It thus appears that joint inversion of magnetic and seafloor fabric data can be valuable in tectonic analyses.

Shoberg, Tom↗

NASA NTRS1994

Budget analysis of FIFE 1987 sonde data

Mean thermodynamic profiles are presented for the daytime convective boundary layer evolution for three groups of sunny days in late June and early July, August, and October using data from the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) 1987 Kansas experiment. Budget models for the mixed layer evolution and the boundary layer rise are used to estimate the boundary layer top entrainment parameter. A value of A(sub R) = 0.44 +/- 0.21 is found for the mean ratio of the inversion level virtual heat flux to the surface virtual heat flux.

Betts, Alan K.↗

NASA NTRSDate not supplied

Comparing Two Statistical Models for Low Boom Dose-response Relationships with Correlated Responses

This study compares two statistical modeling approaches to construct summary dose-response curves for low boom community noise surveys. NASA field survey data were used that consist of multiple responses from a survey participant. These data require an approach that accounts for the correlation among repeated annoyance observations from the same participant. A multilevel model accounts for the correlation by allowing estimated parameters to vary with each survey participant. On the other hand, a population average model utilizes generalized estimating equations and accounts for the correlation via a user-specified within-subject correlation structure. A visual comparison of the dose-response curves for these two methods reveals similar results. When comparing specific points along the summary curves, the multilevel model yields more precise confidence bounds than the population average model. The similarity between the summary curves derived from each model lends validity to both approaches for approximating a population representative summary curve.

X-59↗

DOE OSTI2018

How Driving Volatility in Time to Collision Relates to Crash Severity in a Naturalistic Driving Environment

The sequence of instantaneous driving decisions and its variations, known as driving volatility, can be a leading indicator of unsafe driving practices. The research issue is to characterize volatility in instantaneous driving decisions in longitudinal and lateral direction and to seek an understanding of how driving volatility relates to crash severity. By using a unique real-world naturalistic driving database from the SHRP 2, a test set of 671 crash events featuring around 0.2 million temporal samples of real-world driving are analyzed. Based on different driving performance measures, 16 different volatility indices are created. The volatility indices are then linked with individual crash events including information on crash severity, drivers’ pre-crash maneuvers and behaviors, secondary tasks and durations, and other factors. As driving volatility prior to crash involvement can have different components, an in-depth analysis is conducted using the aggregate as well as segmented (based on time to collision) real-world driving data. To account for the issues of observed and unobserved heterogeneity, fixed and random parameter ordered models with heterogeneity in parameter means are estimated. The findings suggest that greater driving volatility (both in longitudinal and lateral direction) prior to crash occurrence increases the likelihood of police reportable or severe crash events. Importantly, compared to the effect of volatility in longitudinal acceleration on crash outcomes, the effect of volatility in longitudinal deceleration is significantly greater in magnitude. Methodologically, the random parameter models with heterogeneity-in-means significantly outperformed both the fixed parameter and random parameter counterparts. The relevance of the findings to the development of proactive behavioral countermeasures for drivers is discussed.

Wali, Behram↗

DOE OSTI2022

Systems and methods for direct estimation of battery parameters using only charge/discharge curves

Electrochemical models for the lithium-ion battery are useful in predicting and controlling its performance. The values of the parameters in these models are vital to their accuracy. However, not all parameters can be measured precisely, especially when destructive methods are prohibited. In some embodiments of the present disclosure, a parameter estimation approach is used to estimate the open circuit potential of the positive electrode (Up) using piecewise linear approximation together with all the other parameters of a single particle model. Up and 10 more parameters may be estimated from a single discharge curve without knowledge of the electrode chemistry using a technique such as a genetic algorithm. Different case studies were presented for estimating Up with different types of parameters of the battery model. The estimated parameters were then validated by comparing simulations at different discharge rates with experimental data.

Qi, Yanbo↗

DOE OSTI2018

In Situ Monitoring of Groundwater Contamination for Sustainable Remediation Using the Kalman Filter - 18423

Groundwater monitoring is critical for nuclear-related facilities as well as radioactively contaminated sites. Recent advances in sensing, data analytics and simulation capabilities provide substantial opportunities to improve and change current monitoring procedures. In particular, we need a paradigm shift from contaminant-only or compliance-only monitoring programs to comprehensive monitoring, i.e., including other ancillary environmental variables for a holistic understanding of the groundwater systems and plume behaviors. Such new approaches are needed for the effective implementation of sustainable remediation (enhanced and natural attenuation), and they have great potential for cost reduction in site monitoring. This paper reviews recent developments for improving long-term monitoring, with focus on the effective use of in situ sensors, data analytics and simulation capabilities. In particular, we highlight a recent application of the Kalman filter algorithm to estimate contaminant concentrations continuously in real time, based on in-situ measured water quality parameters (e.g. electrical conductance and pH) and sparse groundwater sampling. The results show that we can reduce the groundwater sampling frequency significantly, while capturing the dynamics of short- and long-term contaminant concentration changes. Such advanced and integrated monitoring systems will be beneficial for local residents (e.g., to ensure the safety by detecting adverse events early, enabling a swift response) as well as for site operators (e.g., to gain/improve public acceptance, to be better prepared for litigations and false claims, and to reduce overall monitoring cost). (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗