Regularised non-uniform segments and efficient no-slip elastohydrodynamics
نویسندگان
چکیده
Abstract
منابع مشابه
Non-darcy Porous Media Flow in No-slip and Slip Regimes
In this paper lattice-Boltzmann equation method is used to simulate non-Darcy flow in porous media. 2-D in-line and staggered arrangements of uniform cylinders have been considered. The results of a comprehensive computational evaluation are reported: the range of validity of Darcy-Forchheimer equation is investigated and correlations for macroscopic transport properties are presented (i. e., f...
متن کاملEFFICIENT NON−UNIFORM FILTER−BANK EQUALIZER (WedAmPO2)
An efficient realization of a low delay filter−bank will be proposed, which can be regarded as a filter−bank used as equalizer with either fixed or time−varying spectral gain factors. The proposed filter−bank equalizer (FBE) results in a time−domain filter whose coefficients are adapted in the (short−term) spectral−domain. Perfect signal reconstruction is obtained for a broad class of spectral ...
متن کاملNo Uniform
It is interesting to see that in some wards of Littlemore Hospital, in order to promote good relations between patients and staff, some nurses are now wearing plain clothes. Your readers might be interested to learn that from 1929, when the late Dr. Elizabeth Casson started her Nursing Homes, the nursing staff have not worn uniform for the same reason, and that the plan is successful and now pa...
متن کاملNo non-uniform lower bounds implies PIT is hard and no derandomization
We consider arithmetic circuits. In this model, inputs are variables or constants from a field and the computation is performed using + and ×. Formally: Definition 1. An arithmetic circuit C over the field F and the set of variables X = x1, . . . , xn is a directed acyclic graph as follows. The vertices of C are called gates. Every gate in C of in-degree 0 is labeled by either a variable from X...
متن کاملAcoustic model building based on non-uniform segments and bidirectional recurrent neural networks
In this paper a new framework for acoustic model building is presented. It is based on non-uniform segment models, which are learned and scored with a time bidirectional recurrent neural network. While usually neural networks in speech recognition systems are used to estimate posterior "frame to phoneme" probabilities, they are used here to estimate directly "segment to phoneme" probabilities, ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Fluid Mechanics
سال: 2021
ISSN: ['0022-1120', '1469-7645']
DOI: https://doi.org/10.1017/jfm.2021.139