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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Entropy-based closure for probabilistic learning on manifolds

In a recent paper, the authors proposed a general methodology for probabilistic learning on manifolds. The method was used to generate numerical samples that are statistically consistent with an existing dataset construed as a realization from a non-Gaussian random vector. The manifold structure is learned using diffusion manifolds and the statistical sample generation is accomplished using a projected Itˆo stochastic differential equation. This probabilistic learning approach has been extended to polynomial chaos representation of databases on manifolds and to probabilistic nonconvex constrained optimization with a fixed budget of function evaluations. The methodology introduces an isotropic-diffusion kernel with hyperparameter ". Currently, " is more or less arbitrarily chosen. In this paper, we propose a selection criterion for identifying an optimal value of ", based on a maximum entropy argument. The result is a comprehensive, closed, probabilistic model for characterizing data sets with hidden constraints. This entropy argument ensures that out of all possible models, this is the one that is the most uncertain beyond any specified constraints, which is selected. Applications are presented for several databases.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

The evidence of N = 16 shell closure and β -delayed neutron emission from 25 F

We measured the β -delayed neutron emission from 25 F for the first time at the Facility for Rare Isotope Beams (FRIB). Using combined neutron and γ -ray detector systems of the FRIB Decay Station Initiator (FDSi), we observed β -decay transitions populating neutron unbound states between 4.2 and 8 MeV in 25 Ne. The experimental results led to the revision of the β -decay half-life and β -delayed neutron-emission probability of 25 F. The β -decay strength distribution of 25 F extracted from the data agrees with the shell-model predictions using the USDB and SDPF-M effective interactions. This result indicates that the spherical neutron shell gap persists in 25 F and 25 Ne.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

A semi-Lagrangian direct-interaction closure of the spectra of isotropic variable-density turbulence

A study of variable-density homogeneous stationary isotropic turbulence based on the sparse direct-interaction perturbation (SDIP) and supporting direct numerical simulations (DNS) is presented. The non-solenoidal flow considered here is an example of turbulent mixing of gases with different densities. The spectral statistics of this type of flow are substantially more difficult to understand theoretically than those of the similar solenoidal flows. In the approach described here, the nonlinearly coupled velocity and scalar (which determine the density of the fluid) equations are expanded in terms of a normalised density ratio parameter. A new set of coupled integro-differential SDIP equations are derived and then solved numerically for the first-order correction to the incompressible equations in the variable-density expansion parameter. By adopting a regular expansion approach, one obtains leading-order corrections that are universal and therefore interesting in their own right. The predictions are then compared with DNS of forced variable-density flow with different density contrasts. It is found that the velocity spectrum owing to variable density is indistinguishable from that of constant-density turbulence, as it is supported by a wealth of indirect experimental evidence, but the scalar spectra show significant deviations, and even loss of monotonicity, as a function of the type and strength of the large-scale source of the mixing. Furthermore, the analysis helps clarify what may be the proper approach to interpret the power spectrum of variable-density turbulence.

Mechanics↗
DOE OSTI2016

Replacing Arginine 33 for Alanine in the Hemophore HasA from Pseudomonas aeruginosa Causes Closure of the H32 Loop in the Apo-Protein

Previous characterization of hemophores from Serratia marcescens (HasAs), Pseudomonas aeruginosa (HasAp), and Yersinia pestis (HasA yp ) showed that hemin binds between two loops, where it is axially coordinated by H32 and Y75. The Y75 loop is structurally conserved in all three hemophores and harbors conserved ligand Y75. The other loop contains H32 in HasAs and HasAp, but a noncoordinating Q32 in HasA yp . The H32 loop in apo-HasAs and apo-HasAp is in an open conformation, which places H32 about 30 Å from the hemin-binding site. Hence, hemin binding onto the Y75 loop of HasAs or HasAp triggers a large relocation of the H32 loop from an open- to a closed-loop conformation and enables coordination of the hemin-iron by H32. In comparison, the Q32 loop in apo-HasA yp is in the closed conformation, and hemin binding occurs with minimal reorganization and without coordinative interactions with the Q32 loop. Studies in crystallo and in solution have established that the open H32 loop in apo-HasAp and apo-HasAs is well structured and minimally affected by conformational dynamics. In this study we address the intriguing issue of the stability of the H32 loop in apo-HasAp and how hemin binding triggers its relocation. Specifically, we address this question with a combination of NMR spectroscopy, X-ray crystallography, and molecular dynamics simulations and find that R33 is critical to the stability of the open H32 loop. Replacing R33 with A causes the H32 loop in R33A apo-HasAp to adopt a conformation similar to that of holo-HasAp. Finally, stopped-flow absorption and resonance Raman analyses of hemin binding to apo-R33A HasAp indicate that the closed H32 loop slows down the insertion of the heme inside the binding pocket, presumably as it obstructs access to the hydrophobic platform on the Y75 loop, but accelerates the completion of the heme iron coordination.

59 BASIC BIOLOGICAL SCIENCES↗