794 research outputs found
Longtime behavior of nonlocal Cahn-Hilliard equations
Here we consider the nonlocal Cahn-Hilliard equation with constant mobility
in a bounded domain. We prove that the associated dynamical system has an
exponential attractor, provided that the potential is regular. In order to do
that a crucial step is showing the eventual boundedness of the order parameter
uniformly with respect to the initial datum. This is obtained through an
Alikakos-Moser type argument. We establish a similar result for the viscous
nonlocal Cahn-Hilliard equation with singular (e.g., logarithmic) potential. In
this case the validity of the so-called separation property is crucial. We also
discuss the convergence of a solution to a single stationary state. The
separation property in the nonviscous case is known to hold when the mobility
degenerates at the pure phases in a proper way and the potential is of
logarithmic type. Thus, the existence of an exponential attractor can be proven
in this case as well
Application of SAR time-series and deep learning for estimating landslide occurence time
The time series of normalized difference vegetation index (NDVI) and interferometric coherence extracted from optical and Synthetic Aperture Radar (SAR) images, respectively, have strong responses to sudden landslide failures in vegetated regions, which is expressed by a sudden increase or decrease in the values of NDVI and coherence. Compared with optical sensors, SAR sensors are not affected by cloud and daylight conditions and can detect the occurrence time of failure in near real-time. The purpose of this paper is to automatically determine the time of failure occurrence using time series coherence values. We propose, based on some existing anomaly detection algorithms, a deep neural network-based anomaly detection strategy that combines supervised and unsupervised learning without a priori knowledge about failure time. Our experiment using July 21, 2020 Shaziba landslide in China shows that in comparison to widely used unsupervised methodology, the use of our algorithm leads to a more accurate detection of the timing of the landslide failure
Single shot cathode transverse momentum imaging in high brightness photoinjectors
In state of the art photoinjector electron sources, thermal emittance from photoemission dominates the final injector emittance. Therefore, low thermal emittance cathode developments and diagnostics are very important. Conventional thermal emittance measurements for the high gradient gun are time-consuming and thus thermal emittance is not measured as frequently as quantum efficiency during the lifetime of photocathodes, although both are important properties for the photoinjector optimizations. In this paper, a single shot measurement of photoemission transverse momentum, i.e., thermal emittance per rms laser spot size, is proposed for photocathode rf guns. By tuning the gun solenoid focusing, the electrons' transverse momenta at the cathode are imaged to a downstream screen, which enables a single shot measurement of both the rms value and the detailed spectra of the photoelectrons' transverse momenta. Both simulations and proof of principle experiments are reported
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