Numerical response and causality study of the magnetic permeability-frequency function of NiZn ferrites using Genetic Algorithm

Boggi, Silvina; Fano, Walter Gustavo

doi:10.1016/j.jmmm.2019.166305

Cited by 6 publications

(4 citation statements)

References 13 publications

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“…However, spin rotation contribution decreases until reaching similar or even lower values than domain-wall motion contribution when increasing angular frequency. [4][5][6][7]11,[16][17][18]21,24,48 The values of fitting parameters shown in Table 2 are in good agreement with previous ones obtained by the authors for the same Cu-doped Ni-Zn ferrite 11 and with the values reported in literature for similar NiZn ferrites. 4,5,7,18,30 However, fitting values reported in literature are determined for a unique microstructure, and they can be distorted by the effect of relative density and grain size.…”

Section: Ta B L Esupporting

confidence: 90%

“…The frequency dispersion of Cu-doped Ni-Zn ferrites, in the angular frequency range studied, exhibits curves where real part is described as a relaxation curve while the imaginary part describes a curve passing through a maximum. Literature [4][5][6][7][12][13][14][16][17][18][19][20][21][22][23][24] reports several physicomathematical models defining angular frequency functions for 𝜒 ′ 𝑆 (𝜔), 𝜒 ′ 𝐷𝑊 (𝜔), 𝜒 ′′ 𝑆 (𝜔), and 𝜒 ′′ 𝐷 (𝜔) in order to calculate and accurately reproduce the frequency dispersion from Equations ( 5) and (6). One of the most extended model in polycrystalline ferrites was proposed by Nakamura, 13,18 who kept in mind the influence of spin rotation and domain-wall motion mechanisms on magnetic complex susceptibility, considering that the spin rotation component is of relaxation-type and that the domainwall motion component is of resonance type, both depending on the angular frequency, leading to the following equations:…”

Section: Dependence Of Complex Magnetic Permeability On Angular Frequencymentioning

confidence: 99%

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Frequency dispersion model of the complex permeability of soft ferrites in the microwave frequency range

et al. 2021

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The complex permeability of Cu-doped nickel-zinc polycrystalline ferrites is strongly dependent on microstructure, particularly, on relative density (𝜙) and average grain size (𝐺). In this study, a mathematical model, able to fit the measured magnetic permeability spectra from 10 6 to 10 9 Hz, is proposed and validated for a width range of average grain sizes (3.40-23.15 µm) and relative densities (0.83-0.96). To the authors' knowledge, domain-wall motion and spin rotation contributions to magnetic permeability have been integrated jointly with the microstructure for the first time in the proposed model, highlighting the relative influence of each magnetizing mechanism and microstructure on the magnetic permeability at different angular frequencies.

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Section: Ta B L Esupporting

confidence: 90%

Section: Dependence Of Complex Magnetic Permeability On Angular Frequencymentioning

confidence: 99%

Frequency dispersion model of the complex permeability of soft ferrites in the microwave frequency range

et al. 2021

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“…genes is changed. The mutated gene is evaluated to determine whether it meets the environmental requirements; if not, duplication, mating and mutation will continue until the environmental fitness value, or the required number of evolutions, has been reached [35].…”

Section: Multi-objective Genetic Algorithmmentioning

confidence: 99%

The Optimization of Lathe Cutting Parameters Using a Hybrid Taguchi-Genetic Algorithm

Chu

Xie

et al. 2020

IEEE Access

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In this paper, the multi-objective Hybrid Taguchi-genetic Algorithm is used to search for the best processing parameters with specified processing accuracy. The experimental cutting parameters used for the L9 orthogonal table process are cutting depth, cutting velocity and feed rate. The surface roughness of the machined workpiece surface was measured according to the standard of centerline average roughness. The Material Removal Rate (MRR) will be calculated by measuring the diameter of the processed workpiece from the formula to give the MRR. A linear regression model is constructed from the processed quality and the processing parameters of the orthogonal table and the reliability of the model is confirmed by analysis of variance (ANOVA). A Hybrid Taguchi Genetic Algorithm (HTGA) was used to calculate the optimal cutting parameters for multi-objective processing. The results of the experiments indicate that HTGA gave better convergence and robustness than the conventional Genetic Algorithm (GA) using the same number of iterations. This process produces multiple combinations of optimal cutting parameters for material removal rate and surface roughness. As the enhancement of material removal rate improved efficiency on the production line, the optimal cutting parameters were based on the tolerance range of Ra 1.6μm ~ 3.2μm according to the international standard of surface roughness. After actual processing with the selected optimum cutting parameters, the quality of processing is even better than the experimental design of the L9 Orthogonal table.

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“…Los algoritmos genéticos (GA) son procedimientos de búsqueda probabilística que generan soluciones a problemas de optimización utilizando técnicas inspiradas en la evolución natural, como la herencia, la mutación, la selección y el cruce [18].…”

Section: Algoritmos Genéticosunclassified

Implementación de las técnicas de predicción en la generación de energía eléctrica en el sector industrial

Peña

Ávila

Zúñiga

et al. 2020

RITI

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Implementación de las técnicas de predicción en la generación de energía eléctrica en el sector industrialResumen: Las técnicas de predicción actualmente cuentan con un gran potencial, mediante ellas se pueden obtener estimaciones o pronósticos de valores futuros de una manera confiable, las cuales pueden ser utilizadas para la toma de decisiones. Ahora bien, las industrias son unas de las mayores consumidoras de electricidad, por lo que, muchas de ellas utilizan generadores eléctricos propios para poder cumplir con la demanda de energía que requieren sus procesos. Pero también, dentro de este proceso existen problemas o situaciones no beneficiosas, uno de ellos, es que, si no hay monitoreo y control en la generación de energía eléctrica de una manera adecuada, provocará gran pérdida de recursos monetarios. Por tal motivo, se propone implementar las técnicas de predicción dentro del proceso de generación de energía para comparar y seleccionar la técnica que muestre el mejor pronóstico de consumo y así evitar la pérdida de recursos en la industria.Palabras clave: Técnicas de Predicción, Energía, Toma de Decisiones, Industria.Abstract: Prediction techniques currently have great potential, through them you can obtain estimates or forecasts of future values in a reliable way, which can be used for decision making. However, industries are one of the largest consumers of electricity, so many of them use their own electric generators to be able to meet the energy demand that their processes require. But also, within this process there are problems or situations that are not beneficial, one of them, is that, if there is no monitoring and control in the generation of electrical energy in an adequate way, it will cause a great loss of monetary resources. For this reason, it is proposed to implement the prediction techniques within the power generation process to compare and select the technique that shows the best consumption forecast and thus avoid the loss of resources in the industry.

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Numerical response and causality study of the magnetic permeability-frequency function of NiZn ferrites using Genetic Algorithm

Cited by 6 publications

References 13 publications

Frequency dispersion model of the complex permeability of soft ferrites in the microwave frequency range

Frequency dispersion model of the complex permeability of soft ferrites in the microwave frequency range

The Optimization of Lathe Cutting Parameters Using a Hybrid Taguchi-Genetic Algorithm

Implementación de las técnicas de predicción en la generación de energía eléctrica en el sector industrial

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