Squeeze-film gas bearing technology

Squeeze-film bearing is studied to develop a low-friction suspension for the output-axis gimbal of a single-degree-of-freedom gyroscope. Included are a review of pertinent literature, the theory of squeeze-film lubrication, and design elements

On asymptotic analysis of gaseous squeeze-film bearings

Asymptotic analysis for obtaining steady state solution of time dependent gas lubrication equation, of diffusion type, for gaseous squeeze film bearing

Tuning electronic structure of graphene via tailoring structure: theoretical study

Electronic structures of graphene sheet with different defective patterns are investigated, based on the first principles calculations. We find that defective patterns can tune the electronic structures of the graphene significantly. Triangle patterns give rise to strongly localized states near the Fermi level, and hexagonal patterns open up band gaps in the systems. In addition, rectangular patterns, which feature networks of graphene nanoribbons with either zigzag or armchair edges, exhibit semiconducting behaviors, where the band gap has an evident dependence on the width of the nanoribbons. For the networks of the graphene nanoribbons, some special channels for electronic transport are predicted.Comment: 5 figures, 6 page

Investigation of an axial-excursion transducer for squeeze-film bearings

Resonant frequencies and characteristic bearing cone motion of axial-excursion transducer for squeeze-film gas bearing - drive voltage, preload, bearing mass, and mounting ring effect

The solution of special squeeze film gas bearing problems by an improved numerical technique

Computer program for solving squeeze film gas bearing problem

On the slowly time dependent problem of squeeze film bearings

Time dependency of spherical squeeze-film bearing for use in suspension of precision gyroscope outpu

Quantum interference in dirty d-wave superconductors

The local differential tunneling conductance on a Zn impurity in a disordered d-wave superconductors is studied. Quantum interference between many impurities leads to definitive quasiparticle spectra. We suggest that an elaborate analysis on impurity-induced spectra with quantum interference effect included may be able to pin down the sign and strength of the scattering potential of a Zn impurity in low density limit. Numerical simulations calculated with appropriately determined impurity parameters are in satisfactory agreement with the observations from scanning tunneling microscopy (STM) experiments even in subtle details

On Error Torques of Squeeze-film Cylindrical Journal Bearings

Error torques of squeeze film cylindrical journal bearing

Prototypical Contrastive Learning of Unsupervised Representations

This paper presents Prototypical Contrastive Learning (PCL), an unsupervised representation learning method that addresses the fundamental limitations of instance-wise contrastive learning. PCL not only learns low-level features for the task of instance discrimination, but more importantly, it implicitly encodes semantic structures of the data into the learned embedding space. Specifically, we introduce prototypes as latent variables to help find the maximum-likelihood estimation of the network parameters in an Expectation-Maximization framework. We iteratively perform E-step as finding the distribution of prototypes via clustering and M-step as optimizing the network via contrastive learning. We propose ProtoNCE loss, a generalized version of the InfoNCE loss for contrastive learning, which encourages representations to be closer to their assigned prototypes. PCL outperforms state-of-the-art instance-wise contrastive learning methods on multiple benchmarks with substantial improvement in low-resource transfer learning. Code and pretrained models are available at https://github.com/salesforce/PCL