scholarly journals Assessment of Optimized Electrode Configuration for Electrical Impedance Myography Using Genetic Algorithm via Finite Element Model

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Somen Baidya ◽  
Mohammad A. Ahad
Keyword(s):  
Genetic Algorithm ◽  
Finite Element ◽  
Finite Element Model ◽  
Electrical Impedance ◽  
Muscle Thickness ◽  
Element Model ◽  
Thickness Variation ◽  
Muscle Properties ◽  
Practical Limit ◽  
Muscle Health

Electrical Impedance Myography (EIM) is a noninvasive neurophysiologic technique to diagnose muscle health. Besides muscle properties, the EIM measurements vary significantly with the change of some other anatomic and nonanatomic factors such as skin fat thickness, shape and thickness of muscle, and electrode size and spacing due to its noninvasive nature of measurement. In this study, genetic algorithm was applied along with finite element model of EIM as an optimization tool in order to figure out an optimized EIM electrode setup, which is less affected by these factors, specifically muscle thickness variation, but does not compromise EIM’s ability to detect muscle diseases. The results obtained suggest that a particular arrangement of electrodes and minimization of electrode surface area to its practical limit can overcome the effect of undesired factors on EIM parameters to a larger extent.

scholarly journals Optimization research on arc height of running surface based on reducing partial wear of straddle-type monorail vehicle running wheel tire

2021 ◽  
Vol 13 (10) ◽  
pp. 168781402110534
Author(s):  
XiaoXia Wen ◽  
ZiXue Du ◽  
Liang Chen
Keyword(s):  
Genetic Algorithm ◽  
Finite Element ◽  
Finite Element Model ◽  
Simulation Optimization ◽  
Element Model ◽  
Multidisciplinary Optimization ◽  
Improved Genetic Algorithm ◽  
Running Wheel ◽  
Contact State ◽  
Running Wheels

This article proposes an ideal of reducing the partial wear of the running wheels by optimizing the arc height of the running surface to improve the wheel-rail contact state. To realize this idea, two kinds of concave and convex running surfaces were designed, the “running wheel-rail beam” finite element model of three kinds of rail surfaces of concave, convex, and plane were established. Taking the arc height of the running surface as the design variable, the total friction work and the friction work deviation (FWD) value as the dual optimization goal, an optimization model of arc height of running surface was established based on finite element model and multidisciplinary optimization platform Modefrontier. An improved genetic algorithm was used and an co-simulation optimization mode was put forward in the optimization. The optimization results show that when the concave height of the inner running surface is 22.62 mm, the total friction work and the FWD values are reduced by 11% and 11.8% respectively; When the convex height of the outer running surface is 11.81 mm, the objection values are reduced by 4.9% and 32.1% respectively. An ideal running surface was obtained and the life of the running wheel was extended by the research.

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