Statistically understanding the roles of nanostructure features in interfacial ice nucleation for enhancing icing delay performance

2019 ◽  
Vol 21 (36) ◽  
pp. 19785-19794 ◽  
Author(s):  
Yizhou Shen ◽  
Xinyu Xie ◽  
Yuehan Xie ◽  
Jie Tao ◽  
Jiawei Jiang ◽  
...  
Keyword(s):  
Ice Nucleation ◽  
Open Cone ◽  
Delay Performance ◽  
Geometrical Features

We designed and constructed two kinds of superhydrophobic nanostructures with sealed layered porous and open cone features for the discussion of the roles of nanostructure geometrical features in interfacial ice nucleation.

Routing Optimization with Efficient Second Order Distributed Approach Using Congestion Control Rules

2017 ◽  
Vol 7 (7) ◽  
pp. 363
Author(s):  
Jaya Pratha Sebastiyar ◽  
Martin Sahayaraj Joseph
Keyword(s):  
Congestion Control ◽  
Second Order ◽  
Back Pressure ◽  
Order Method ◽  
Delay Performance ◽  
Routing Optimization ◽  
Distributed Approach ◽  
Control Rules ◽  
Primal Dual ◽  
Queue Stability

Distributed joint congestion control and routing optimization has received a significant amount of attention recently. To date, however, most of the existing schemes follow a key idea called the back-pressure algorithm. Despite having many salient features, the first-order sub gradient nature of the back-pressure based schemes results in slow convergence and poor delay performance. To overcome these limitations, the present study was made as first attempt at developing a second-order joint congestion control and routing optimization framework that offers utility-optimality, queue-stability, fast convergence, and low delay.  Contributions in this project are three-fold. The present study propose a new second-order joint congestion control and routing framework based on a primal-dual interior-point approach and established utility-optimality and queue-stability of the proposed second-order method. The results of present study showed that how to implement the proposed second-order method in a distributed fashion.

Optimization of a New Reactive Force Field for Silver - Based Materials

2020 ◽  
Author(s):  
Clément Dulong ◽  
Bruno Madebène ◽  
Susanna Monti ◽  
Johannes Richardi
Keyword(s):  
Force Field ◽  
Self Assembled Monolayers ◽  
The Novel ◽  
Reactive Force ◽  
Reactive Force Field ◽  
Energetic Properties ◽  
Extended Training ◽  
Geometrical Features ◽  
Assembled Monolayers ◽  
Gold Thiolate

<div><div><div><p>A new reactive force field based on the ReaxFF formalism is effectively parametrized against an extended training set of quantum chemistry data (containing more than 120 different structures) to describe accurately silver- and silver-thiolate systems. The results obtained with this novel representation demonstrate that the novel ReaxFF paradigm is a powerful methodology to reproduce more appropriately average geometric and energetic properties of metal clusters and slabs when compared to the earlier ReaxFF parametrizations dealing with silver and gold. ReaxFF cannot describe adequately specific geometrical features such as the observed shorter distances between the under-coordinated atoms at the cluster edges. Geometric and energetic properties of thiolates adsorbed on a silver Ag20 pyramid are correctly represented by the new ReaxFF and compared with results for gold. The simulation of self-assembled monolayers of thiolates on a silver (111) surface does not indicate the formation of staples in contrast to the results for gold-thiolate systems.</p></div></div></div>

Delay performance in wireless multi-hop networks

2010 ◽  
Vol 30 (1) ◽  
pp. 134-136
Author(s):  
Ying LIN ◽  
Li XU
Keyword(s):  
Delay Performance

scholarly journals Waterfall Algorithm as a tool of investigation the geometrical features of granular porous media

2021 ◽  
Author(s):  
Wojciech Sobieski
Keyword(s):  
Particle Size ◽  
Porous Media ◽  
Lattice Boltzmann ◽  
Granular Media ◽  
Density Ratio ◽  
Geometrical Features ◽  
Granular Porous Media ◽  
Collision Density ◽  
Boltzmann Method ◽  
The Impact

AbstractThe paper describes the so-called Waterfall Algorithm, which may be used to calculate a set of parameters characterising the spatial structure of granular porous media, such as shift ratio, collision density ratio, consolidation ratio, path length and minimum tortuosity. The study is performed for 1800 different two-dimensional random pore structures. In each geometry, 100 individual paths are calculated. The impact of porosity and the particle size on the above-mentioned parameters is investigated. It was stated in the paper, that the minimum tortuosity calculated by the Waterfall Algorithm cannot be used directly as a representative tortuosity of pore channels in the Kozeny or the Carman meaning. However, it may be used indirect by making the assumption that a unambiguous relationship between the representative tortuosity and the minimum tortuosity exists. It was also stated, that the new parameters defined in the present study are sensitive on the porosity and the particle size and may be therefore applied as indicators of the geometry structure of granular media. The Waterfall Algorithm is compared with other methods of determining the tortuosity: A-Star Algorithm, Path Searching Algorithm, Random Walk technique, Path Tracking Method and the methodology of calculating the hydraulic tortuosity based on the Lattice Boltzmann Method. A very short calculation time is the main advantage of the Waterfall Algorithm, what meant, that it may be applied in a very large granular porous media.

scholarly journals Foveal Pit Morphology Characterization: A Quantitative Analysis of the Key Methodological Steps

Entropy ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. 699
Author(s):  
David Romero-Bascones ◽  
Maitane Barrenechea ◽  
Ane Murueta-Goyena ◽  
Marta Galdós ◽  
Juan Carlos Gómez-Esteban ◽  
...  
Keyword(s):  
State Of The Art ◽  
Parameter Estimates ◽  
Human Visual Perception ◽  
The Gaze ◽  
Center Location ◽  
Geometrical Features ◽  
Foveal Center ◽  
Location Methods ◽  
Morphology Characterization ◽  
Fitting Error

Disentangling the cellular anatomy that gives rise to human visual perception is one of the main challenges of ophthalmology. Of particular interest is the foveal pit, a concave depression located at the center of the retina that captures light from the gaze center. In recent years, there has been a growing interest in studying the morphology of the foveal pit by extracting geometrical features from optical coherence tomography (OCT) images. Despite this, research has devoted little attention to comparing existing approaches for two key methodological steps: the location of the foveal center and the mathematical modelling of the foveal pit. Building upon a dataset of 185 healthy subjects imaged twice, in the present paper the image alignment accuracy of four different foveal center location methods is studied in the first place. Secondly, state-of-the-art foveal pit mathematical models are compared in terms of fitting error, repeatability, and bias. The results indicate the importance of using a robust foveal center location method to align images. Moreover, we show that foveal pit models can improve the agreement between different acquisition protocols. Nevertheless, they can also introduce important biases in the parameter estimates that should be considered.

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