Cyclic Nonlinear Modeling Parameters for Unconfined Beam-Column Joints

2022 ◽  
Vol 119 (1) ◽  
Author(s):  
Wael M. Hassan ◽  
Medhat Elmorsy
Keyword(s):  
Nonlinear Modeling

Nonlinear modeling and simulation of flywheel energy storage rotor system with looseness and rub-impact coupling hitch

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Zhu Youfeng ◽  
Liu Xinhua ◽  
Wang Qiang ◽  
Wang Zibo ◽  
Zang Hongyu
Keyword(s):  
Energy Storage ◽  
Differential Equations ◽  
Nonlinear Modeling ◽  
Storage System ◽  
Energy Storage System ◽  
Rotor System ◽  
Flywheel Energy Storage ◽  
Flywheel Energy Storage System ◽  
New Energy ◽  
Single Disk

Abstract Flywheel energy storage system as a new energy source is widely studied. This paper establishes a dynamic model of a single disk looseness and rub-impact coupling hitch flywheel energy storage rotor system firstly. Then dynamic differential equations of the system under the condition of nonlinear oil film force of the sliding bearing are given. Runge–Kutta method is used to solve the simplified dimensionless differential equations. The effect of variable parameters such as disk eccentricity, stator stiffness and bearing support mass on the system are analyzed. With the increase of eccentricity, the range of period-three motion is significantly reduced and the range of chaotic motion begins to appear in the bifurcation diagram. Meanwhile, stiffness of the stator and mass of the bearing support have a significant influence on the flywheel energy storage rotor system.

Accurate Modeling of Complex Antitoxin Effect of Quercetin Based on Neural Networks

2019 ◽  
Vol 29 (01) ◽  
pp. 1950013 ◽  
Author(s):  
Changju Yang ◽  
Entaz Bahar ◽  
Hyonok Yoon ◽  
Hyongsuk Kim
Keyword(s):  
Experimental Data ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Secondary Metabolites ◽  
Hela Cell ◽  
Protective Effect ◽  
Nonlinear Modeling ◽  
Inflammatory Activity ◽  
High Complexity ◽  
Anti Oxidant

A nonlinear modeling of the protective effect of Quercetin (QCT) against various Mycotoxins (MTXs) has a high complexity and is conducted using artificial neural networks (ANNs). QCT is known to possess strong anti-oxidant, anti-inflammatory activity that can prevent many diseases. MTXs are highly toxic secondary metabolites that are capable of causing disease and death in humans and animals. The protective model of QCT against various MTXs (Citrinin, Patulin and Zearalenol) on HeLa cell is built accurately via learning of sparsely measured experimental data by the ANNs. It has shown that the neuro-model can predict the nonlinear protective effect of QCT against MTX-induced cytotoxicity for the measurement of percentage of inhibition of MTXs.

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