Modeling and analysis of a novel approach for particle separation using time-varying amplitude dielectrophoresis

2016 ◽  
Author(s):  
Paresa Modarres ◽  
Maryam Tabrizian
Keyword(s):  
Particle Separation ◽  
Time Varying ◽  
Modeling And Analysis ◽  
Novel Approach

A Novel Approach to Accumulate Superparamagnetic Particles in Aqueous Environment Using Time-Varying Magnetic Field

2020 ◽  
Vol 67 (6) ◽  
pp. 1558-1564 ◽  
Author(s):  
Ya-Li Liu ◽  
Jing-Jie Chen ◽  
Fiaz Ahmad ◽  
Tuo-Di Zhang ◽  
Wei-Hong Guo ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Aqueous Environment ◽  
Time Varying ◽  
Superparamagnetic Particles ◽  
Novel Approach

scholarly journals A novel approach of testability modeling and analysis for PHM systems based on failure evolution mechanism

2013 ◽  
Vol 26 (3) ◽  
pp. 766-776 ◽  
Author(s):  
Xiaodong Tan ◽  
Jing Qiu ◽  
Guanjun Liu ◽  
Kehong Lv ◽  
Shuming Yang ◽  
...  
Keyword(s):  
Evolution Mechanism ◽  
Modeling And Analysis ◽  
Novel Approach ◽  
Failure Evolution

scholarly journals Discrete element method approach to modelling VPP dampers

2018 ◽  
Vol 157 ◽  
pp. 02014
Author(s):  
Pawel Chodkiewicz ◽  
Jakub Lengiewicz ◽  
Robert Zalewski
Keyword(s):  
Discrete Element Method ◽  
Granular Medium ◽  
Discrete Element ◽  
Modeling And Analysis ◽  
Novel Approach ◽  
Particle Dampers ◽  
Pressure Boundary Conditions ◽  
Dem Model ◽  
Method Approach ◽  
Element Method

In this paper, we present a novel approach to modeling and analysis of Vacuum Packed Particle dampers (VPP dampers) with the use of Discrete Element Method (DEM). VPP dampers are composed of loose granular medium encapsulated in a hermetic envelope, with controlled pressure inside the envelope. By changing the level of underpressure inside the envelope, one can control mechanical properties of the system. The main novelty of the DEM model proposed in this paper is the method to treat special (pressure) boundary conditions at the envelope. The model has been implemented within the open-source Yade DEM software. Preliminary results are presented and discussed in the paper. The qualitative agreement with experimental results has been achieved.

scholarly journals Stability of nonlinear Volterra equations

2017 ◽  
Vol 65 (3) ◽  
pp. 333-340
Author(s):  
P. H. A. Ngoc ◽  
L. T. Hieu
Keyword(s):  
Global Exponential Stability ◽  
Zero Solution ◽  
Volterra Equations ◽  
Time Varying ◽  
Bidirectional Associative Memory ◽  
Stability Bound ◽  
Novel Approach ◽  
Nonlinear Volterra Equations ◽  
Volterra Difference Equations ◽  
Explicit Criteria

AbstractUsing a novel approach, we present some new explicit criteria for global exponential stability of the zero solution of general nonlinear time-varying Volterra difference equations. Furthermore, an explicit stability bound for equations subject to nonlinear time-varying perturbations is given. Finally, the obtained results are used to study uniform attraction of equilibrium of discrete-time bidirectional associative memory (BAM) neural networks. Some illustrative examples are given.

Intensive Care Unit Operational Modeling and Analysis

2011 ◽  
pp. 132-147
Author(s):  
Yue Dong ◽  
Huitian Lu ◽  
Ognjen Gajic ◽  
Brian Pickering
Keyword(s):  
Health Care ◽  
Critical Care ◽  
Health Care Providers ◽  
Systems Engineering ◽  
Care Delivery ◽  
Healthcare Delivery ◽  
Organizational Factors ◽  
Modeling And Analysis ◽  
Novel Approach ◽  
Life Threatening

The outcome of critical illness depends not only on life threatening pathophysiologic disturbances, but also on several complex “system” dimensions: health care providers’ performance, organizational factors, environmental factors, family preferences and the interactions between each component. Systems engineering tools offer a novel approach which can facilitate a “systems understanding” of patient-environment interactions enabling advances in the science of healthcare delivery. Due to the complexity of operations in critical care medicine, certain assumptions are needed in order to understand system behavior. Patient variation and uncertainties underlying these assumptions present a challenge to investigators wishing to model and improve health care delivery processes. In this chapter we present a systems engineering approach to modeling critical care delivery using sepsis resuscitation as an example condition.

Meaningful Modeling of Section Bus Running Times by Time Varying Mixture Distributions of Fixed Components

2020 ◽  
Vol 2674 (8) ◽  
pp. 626-637
Author(s):  
Beda Büchel ◽  
Francesco Corman
Keyword(s):  
Travel Time ◽  
Explanatory Power ◽  
Time Varying ◽  
Time Data ◽  
Running Time ◽  
Novel Approach ◽  
Travel Time Data ◽  
Conventional Models ◽  
Bus Travel Time ◽  
Transit Reliability

Understanding the variability of bus travel time is a key issue in the optimization of schedules, transit reliability, route choice analysis, and transit simulation. The statistical modeling of bus travel time data is of increasing importance given the increasing availability of data. In this paper, we introduce a novel approach to modeling the day-to-day variability of urban bus running times on a section level. First, the explanatory power of conventionally used distributions is examined, based on likelihood and effect size. We show that a mixture model is a powerful tool to increase fitting performance, but the applied components need to be justified. To overcome this issue, we propose a novel model consisting of two individual characteristic distributions representing either off-peak or peak hour dynamics. The observed running time distribution at every hour of the day can be described as a combination (mixture) of the two dynamics. The proposed time varying model uses a small set of parameters, which are physically interpretable and capable of accurately describing running time distributions. With our modeling approach, we reduce the complexity of mixture models and increase the explanatory power and fit compared with conventional models.

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