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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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DOE OSTI2019

A note on the Bayesian analysis of experiments with correlated multiple responses using a matrix-logarithmic covariance model

In the literature, analysis of multiple responses from experiments with replicates has modeled the covariance matrix directly as linear models of the transformed variances and correlations, i.e., covariance modeling. This article considers models based on the matrix- logarithm of the covariance matrix. This so-called log-covariance modeling is illustrated with data from actual experiments and compared with the traditional covariance modeling.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Combinatorial impedance spectroscopy with Bayesian analysis for triple ionic-electronic conducting perovskites

We construct an empirical map of oxide electrode materials performance relevant to intermediate-temperature electrochemical devices.

14 SOLAR ENERGY↗

DOE OSTI2011

A Bayesian analysis of QCD sum rules

A new technique has recently been developed, in which the Maximum Entropy Method is used to analyze QCD sum rules. This approach has the virtue of being able to directly generate the spectral function of a given operator, without the need of making an assumption about its specific functional form. To investigate whether useful results can be extracted within this method, we have first studied the vector meson channel, where QCD sum rules are traditionally known to provide a valid description of the spectral function. Our results show a significant peak in the region of the experimentally observed {rho}-meson mass, which is in agreement with earlier QCD sum rules studies and suggests that the Maximum Entropy Method is a strong tool for analyzing QCD sum rules.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

A Bayesian analysis of nuclear deformation properties with Skyrme energy functionals

In spite of numerous scientific and practical applications, there is still no comprehensive theoretical description of the nuclear fission process based solely on protons, neutrons and their interactions. Furthermore, the most advanced simulations of fission are currently carried out within nuclear density functional theory (DFT). In spite of being fully quantum-mechanical and rooted in the theory of nuclear forces, DFT still depends on a dozen or so parameters characterizing the energy functional. Calibrating these parameters on experimental data results in uncertainties that must be quantified for applications. This task is very challenging because of the high computational cost of DFT calculations for fission. In this paper, we use Gaussian processes to build emulators of DFT models in order to quantify and propagate statistical uncertainties of theoretical predictions for a range of nuclear deformations relevant to describing the fission process.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021