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Markus Hundshagen and Romuald Skoda
Predicting pump performance and ensuring operational reliability under two-phase conditions is a major goal of three-dimensional (3D) computational fluid dynamics (CFD) analysis of liquid/gas radial centrifugal pump flows. Hence, 3D CFD methods are incre...
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Markus Hundshagen, Kevin Rave, Michael Mansour, Dominique Thévenin and Romuald Skoda
A hybrid two-phase flow solver is proposed, based on an Euler?Euler two-fluid model with continuous blending of a Volume-of-Fluid method when phase interfaces of coherent gas pockets are to be resolved. In a preceding study on a two-dimensional bladed re...
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Pavel N. Kazanskii
The complex unsteady flow in cavities leads to the formation of large-scale disturbances in the shear layer. Natural closed-loop mechanisms provoke a dramatic increase in pressure pulsations and aerodynamic noise. This paper presents the experimental stu...
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Matteo Dellacasagrande, Edward Canepa, Andrea Cattanei and Mehrdad Moradi
The present work reports an experimental study of the leakage flow in a low-speed fan ring. Existing 2D Particle Image Velocimetry (PIV) measurements taken in a meridional plane in front of the rotor gap have been further processed and analyzed by means ...
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Francesco Cosimi, Antonio Arena, Paolo Gai and Sergio Saponara
In this manuscript, we propose a configurable hardware device in order to build a coherent data log unit. We address the need for analyzing mixed-criticality systems, thus guaranteeing the best performances without introducing additional sources of inter...
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Jörg P. Kotthaus
An acoustoelectric approach to neuron function is proposed that combines aspects of the widely accepted electrical-circuit-based Hodgkin?Huxley model for the generation and propagation of action potentials via electric polarization with mechanical models...
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Jong Woo Kim, Marc Messerschmidt and William S. Graves
We present a supervised deep neural network model for phase retrieval of coherent X-ray imaging and evaluate the performance. A supervised deep-learning-based approach requires a large amount of pre-training datasets. In most proposed models, the various...
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Jong Woo Kim, Marc Messerschmidt and William S. Graves
We present a deep learning-based generative model for the enhancement of partially coherent diffractive images. In lensless coherent diffractive imaging, a highly coherent X-ray illumination is required to image an object at high resolution. Non-ideal ex...
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Qichen Xie, Cheng Chi, Shenglong Jin, Guanqun Wang, Yu Li and Haining Huang
The detection of tonal signals with unknown frequencies is an important area of study in underwater signal processing. A common approach to address this issue is to use the Discrete Fourier Transform (DFT) for observations. When a tone does not lie preci...
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Guigui Wang, Shihan Tan, Ge Song and Sheng Wang
The CBATS (carrier-based aircraft take-off and landing training system) is an important application of virtual reality technology in the simulation field. Large-scale, real-time ocean simulations are the biggest challenge to the authenticity of the visua...
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