scholarly journals Dual optimization method of radiofrequency and quasistatic field simulations for reduction of eddy currents generated on 7T radiofrequency coil shielding

2014 ◽  
Vol 74 (5) ◽  
pp. 1461-1469 ◽  
Author(s):  
Yujuan Zhao ◽  
Tiejun Zhao ◽  
Shailesh B. Raval ◽  
Narayanan Krishnamurthy ◽  
Hai Zheng ◽  
...  
Keyword(s):  
Eddy Currents ◽  
Optimization Method ◽  
Radiofrequency Coil ◽  
Quasistatic Field

An optimization method fitted for model inversion in non destructive control by eddy currents

2000 ◽  
Vol 12 (3) ◽  
pp. 231-238 ◽  
Author(s):  
R. Chelouah ◽  
P. Siarry ◽  
G. Berthiau ◽  
B. De Barmon
Keyword(s):  
Eddy Currents ◽  
Optimization Method ◽  
Model Inversion ◽  
Non Destructive

scholarly journals A Study on the Optimal Machining Parameters of the Induction Assisted Milling with Inconel 718

Materials ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 233 ◽  
Author(s):  
Eun Kim ◽  
Choon Lee
Keyword(s):  
Surface Roughness ◽  
Tool Wear ◽  
Cutting Force ◽  
Inconel 718 ◽  
Eddy Currents ◽  
Optimization Method ◽  
Machining Parameters ◽  
Element Analysis ◽  
Coated Carbide ◽  
Machining Parameter

This paper focuses on an analysis of tool wear and optimum machining parameter in the induction assisted milling of Inconel 718 using high heat coated carbide and uncoated carbide tools. Thermally assisted machining is an effective machining method for difficult-to-cut materials such as nickel-based superalloy, titanium alloy, etc. Thermally assisted machining is a method of softening the workpiece by preheating using a heat source, such as a laser, plasma or induction heating. Induction assisted milling is a type of thermally assisted machining; induction preheating uses eddy-currents and magnetic force. Induction assisted milling has the advantages of being eco-friendly and economical. Additionally, the preheating temperature can be easily controlled. In this study, the Taguchi method is used to obtain the major parameters for the analysis of cutting force, surface roughness and tool wear of coated and uncoated tools under various machining conditions. Before machining experiments, a finite element analysis is performed to select the effective depth of the cut. The S/N ratio and ANOVA of the cutting force, surface roughness and tool wear are analyzed, and the response optimization method is used to suggest the optimal machining parameters.

Optimization Method of Superelevation Transition for Oval Racing Tracks

CICTP 2019 ◽  
2019 ◽  
Author(s):  
Yuchen Wang ◽  
Tao Lu ◽  
Hongxing Zhao ◽  
Zhiying Bao
Keyword(s):  
Optimization Method

Determination of eddy current losses and hysteresis losses in magnetic circuits of electrical machines

2020 ◽  
pp. 54-58
Author(s):  
S. M. Plotnikov
Keyword(s):  
Eddy Current ◽  
Magnetization Reversal ◽  
Eddy Currents ◽  
Technical Problem ◽  
Electrical Machines ◽  
Eddy Current Losses ◽  
Hysteresis Losses ◽  
Magnetic Circuits ◽  
Core Losses ◽  
Reversal Frequency

The division of the total core losses in the electrical steel of the magnetic circuit into two components – losses dueto hysteresis and eddy currents – is a serious technical problem, the solution of which will effectively design and construct electrical machines with magnetic circuits having low magnetic losses. In this regard, an important parameter is the exponent α, with which the frequency of magnetization reversal is included in the total losses in steel. Theoretically, this indicator can take values from 1 to 2. Most authors take α equal to 1.3, which corresponds to the special case when the eddy current losses are three times higher than the hysteresis losses. In fact, for modern electrical steels, the opposite is true. To refine the index α, an attempt was made to separate the total core losses on the basis that the hysteresis component is proportional to the first degree of the magnetization reversal frequency, and the eddy current component is proportional to the second degree. In the article, the calculation formulas of these components are obtained, containing the values of the total losses measured in idling experiments at two different frequencies, and the ratio of these frequencies. It is shown that the rational frequency ratio is within 1.2. Presented the graphs and expressions to determine the exponent α depending on the measured no-load losses and the frequency of magnetization reversal.

Sistem Kontrol Optimal Fuzzy-Particle Swarm Optimization

2018 ◽  
Vol 9 (1) ◽  
pp. 1-5
Author(s):  
Fachrudin Hunaini ◽  
Imam Robandi ◽  
Nyoman Sutantra
Keyword(s):  
Fuzzy Logic ◽  
Particle Swarm Optimization ◽  
Control System ◽  
Membership Function ◽  
Fuzzy Logic Control ◽  
Particle Swarm ◽  
Optimization Method ◽  
Swarm Optimization ◽  
Motion Error ◽  
Logic Control

Fuzzy Logic Control (FLC) is a reliable control system for controlling nonlinear systems, but to obtain optimal fuzzy logic control results, optimal Membership Function parameters are needed. Therefore in this paper Particle Swarm Optimization (PSO) is used as a fast and accurate optimization method to determine Membership Function parameters. The optimal control system simulation is carried out on the automatic steering system of the vehicle model and the results obtained are the vehicle's lateral motion error can be minimized so that the movement of the vehicle can always be maintained on the expected trajectory

Dimensioning a recovery boiler furnace using mathematical optimization

TAPPI Journal ◽  
2015 ◽  
Vol 14 (2) ◽  
pp. 119-129 ◽  
Author(s):  
VILJAMI MAAKALA ◽  
PASI MIIKKULAINEN
Keyword(s):  
Radial Basis Function Network ◽  
High Capacity ◽  
Mathematical Optimization ◽  
Optimization Procedure ◽  
Optimization Method ◽  
Performance Criteria ◽  
Boiler Furnace ◽  
Starting Point ◽  
Recovery Boiler ◽  
Base Design

Capacities of the largest new recovery boilers are steadily rising, and there is every reason to expect this trend to continue. However, the furnace designs for these large boilers have not been optimized and, in general, are based on semiheuristic rules and experience with smaller boilers. We present a multiobjective optimization code suitable for diverse optimization tasks and use it to dimension a high-capacity recovery boiler furnace. The objective was to find the furnace dimensions (width, depth, and height) that optimize eight performance criteria while satisfying additional inequality constraints. The optimization procedure was carried out in a fully automatic manner by means of the code, which is based on a genetic algorithm optimization method and a radial basis function network surrogate model. The code was coupled with a recovery boiler furnace computational fluid dynamics model that was used to obtain performance information on the individual furnace designs considered. The optimization code found numerous furnace geometries that deliver better performance than the base design, which was taken as a starting point. We propose one of these as a better design for the high-capacity recovery boiler. In particular, the proposed design reduces the number of liquor particles landing on the walls by 37%, the average carbon monoxide (CO) content at nose level by 81%, and the regions of high CO content at nose level by 78% from the values obtained with the base design. We show that optimizing the furnace design can significantly improve recovery boiler performance.

A Power Optimization Method in Large-Scale Wireless Sensor Networks Using a Two-Stage Meta-Heuristic Algorithm

2014 ◽  
Vol 2 ◽  
pp. 302-305
Author(s):  
Ryohei Sato ◽  
Hidehiro Nakano ◽  
Arata Miyauchi
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Heuristic Algorithm ◽  
Large Scale ◽  
Power Optimization ◽  
Optimization Method ◽  
Wireless Sensor ◽  
Two Stage
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