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Results for “substructures”

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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Receptance coupling substructure analysis and chatter frequency-informed machine learning for milling stability

This paper describes a milling stability identification approach that simultaneously considers: physics-based models for the tool tip frequency response functions and stability predictions; the binary result from a milling test (automatically labeled as stable or unstable based on frequency content); chatter frequency when an unstable result is obtained; and user risk tolerance. The algorithm applies probabilistic Bayesian machine learning with adaptive, parallelized Markov Chain Monte Carlo sampling to update the probability of stability with each milling test. Furthermore, the result is a robust solution for rapid convergence to optimized milling parameters for maximum metal removal rate using all available information.

42 ENGINEERING↗
DOE OSTI2022

Inferring dark matter substructure with astrometric lensing beyond the power spectrum

Abstract Astrometry—the precise measurement of positions and motions of celestial objects—has emerged as a promising avenue for characterizing the dark matter population in our Galaxy. By leveraging recent advances in simulation-based inference and neural network architectures, we introduce a novel method to search for global dark matter-induced gravitational lensing signatures in astrometric datasets. Our method based on neural likelihood-ratio estimation shows significantly enhanced sensitivity to a cold dark matter population and more favorable scaling with measurement noise compared to existing approaches based on two-point correlation statistics. We demonstrate the real-world viability of our method by showing it to be robust to non-trivial modeled as well as unmodeled noise features expected in astrometric measurements. This establishes machine learning as a powerful tool for characterizing dark matter using astrometric data.

convolutional neural networks (1938)↗
DOE OSTI2022

Substructure detection reanalysed: dark perturber shown to be a line-of-sight halo

ABSTRACT Observations of structure at subgalactic scales are crucial for probing the properties of dark matter, which is the dominant source of gravity in the universe. It will become increasingly important for future surveys to distinguish between line-of-sight haloes and subhalos to avoid wrong inferences on the nature of dark matter. We reanalyse a subgalactic structure (in lens JVAS B1938 + 666) that has been previously found using the gravitational imaging technique in galaxy-galaxy lensing systems. This structure has been assumed to be a satellite in the halo of the main lens galaxy. We fit the redshift of the perturber of the system as a free parameter, using the multiplane thin-lens approximation, and find that the redshift of the perturber is $z_\mathrm{int} = 1.42^{+0.10}_{-0.15}$ (with a main lens redshift of z = 0.881). Our analysis indicates that this structure is more massive than the previous result by an order of magnitude. This constitutes the first dark perturber shown to be a line-of-sight halo with a gravitational lensing method.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

O 16 O 16 collisions at energies available at the BNL Relativistic Heavy Ion Collider and at the CERN Large Hadron Collider comparing α clustering versus substructure

Collisions of . light and heavy nuclei in relativistic heavy-ion collisions have been shown to be sensitive to nuclear structure. With a proposed 16 O 16 O run at the CERN Large Hadron Collider (LHC) and at the BNL Relativistic Heavy Ion Collider (RHIC) we study the potential for finding α clustering in 16 O. Here we use the state-of-the-art iEBE-VISHNU package with 16 O nucleonic configurations from ab initio nuclear lattice simulations. This setup was tuned using a Bayesian analysis on p Pb and PbPb systems. We find that the 16 O 16 O system always begins far from equilibrium and that at LHC and RHIC it approaches the regime of hydrodynamic applicability only at very late times. Finally, by taking ratios of flow harmonics we are able to find measurable differences between α-clustering, nucleonic, and subnucleonic degrees of freedom in the initial state.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗