Structural Optimization of a Magnetic Actuator With Simultaneous Consideration of Thermal and Magnetic Performances

Kim, Hansol; Kim, Cheolwoong; Seong, Hong Kyoung; Yoo, Jeonghoon

doi:10.1109/tmag.2015.2453422

Cited by 13 publications

(6 citation statements)

References 15 publications

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“…Moreover, the penalization parameter of relative reluctivity, denoted by q, was set to 1, to take into account the specific characteristics of magnetic reluctivity (Choi and Yoo 2009). The penalization parameter of thermal conductivity p is set to 3 (Kim et al 2015). The convection condition is applied to the design domain using the convection coefficient as ( ) ( ) ( )…”

Section: Process Of Changing Design Variablesmentioning

confidence: 99%

“…Magnetic devices often generate heat during operation, which can affect performance. Therefore, it is essential to consider not only magnetic field-related performance but also the effective dissipation of heat generated from heat sources, especially current sources (Kim et al 2015). As a result, multi-objective optimization problem (MOP), which considers two optimizing objective functions with two or more constraints, needs to be handled.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, in regions with relatively short distances between adjacent solution points, it is difficult to find potential solution points that can be found in the following iteration. The adaptive weighted sum method based on scaled objective values can be used due to its simplicity although it may not accurately reflect preferences (Kim et al 2015). Other studies have proposed creating a hyperplane where previous solutions are located and utilizing the coefficients of the hyperplane as subsequent weights (Sato et al 2017;Ryu et al 2021).…”

Section: Introductionmentioning

confidence: 99%

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Topological optimal design of composite magnetic actuators to improve driving force and thermal conductivity

Oh,

Yoo

2024

Preprint

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The aim of this study is to introduce a topology optimization approach to improve the driving force of magnetic actuators along with their thermal conductivity considering the nonlinearity of composite materials. The anisotropic magnetic composite is composed of two parts, taking into account differences in magnetic saturation effect and thermal conductivity. The first part has low magnetic reluctivity and high conductivity, while the other part has high reluctivity and low conductivity. The representative volume element (RVE) method and deep neural network (DNN) were used to obtain a dataset of effective composite material properties and generate a machine learning (ML) module for material property determination used in the optimization process. To optimize and verify both performances, a multi-objective function was established. By employing gradually changing preferences with an initial and utopia points-based adaptive weighting method, design processes were performed to obtain Pareto-optimal solution sets evenly distributed in the objective space. Numerical examples are presented for both symmetric and asymmetric magnetic actuator models, aiming to validate the effectiveness of the proposed design process. To investigate the effects of nonlinearity in magnetic material properties, design results are compared when subjected to high and low currents.

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Section: Process Of Changing Design Variablesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Topological optimal design of composite magnetic actuators to improve driving force and thermal conductivity

Oh,

Yoo

2024

Preprint

Self Cite

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“…where p f upp and T low TEG are the upper and lower limit values for the allowed pressure drop and TEG temperature, respectively. In equation (29c), R is the total number of finite elements in the design domain and V r is the allowed volume ratio, which is the ratio between the allowed number of steel elements and R. The objective function ðΦÞ is defined using the weighting factor method, 45 as well as the scaling scheme 46,47 as follows…”

Section: Objective Function and Constraintsmentioning

confidence: 99%

“…In equation (29c), R is the total number of finite elements in the design domain and Vr is the allowed volume ratio, which is the ratio between the allowed number of steel elements and R . The objective function (normalΦ) is defined using the weighting factor method, 45 as well as the scaling scheme 46,47 as followswhere the superscript “old” implies the value at the former iteration during the optimization process.…”

Section: To Problem Formulationmentioning

confidence: 99%

Partition layout inside a muffler integrated with a thermoelectric generator: Multi-physics analysis and optimal design

Lee

2022

Journal of Low Frequency Noise, Vibration and Active Control

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A multi-physics-analysis-based topology optimization (TO) method is proposed to optimally design the internal partition layout of a muffler integrated with a thermoelectric generator (TEG). The basic equations governing the acoustical behavior, heat transfer, and fluid flow in the muffler are introduced, and their interaction is designated for exact numerical analysis in terms of acoustics, heat transfer, and fluid mechanics. To implement density-based TO, one design variable is assigned to each finite element in the design domain, and interpolation functions suitable for each physics phenomenon are employed. In the TO problem formulation, the sum of the squared acoustic pressures at the outlet of the muffler for multi-target frequencies is selected as an objective function to achieve broadband noise attenuation. The temperature of the TEG and the pressure drop are constrained for high energy recovery efficiency and fluid passage, respectively. The optimization problem formulated for the muffler design is solved for various design conditions. Optimal partition layouts are obtained depending on the location and length of the TEG, the upper limit value of the pressure drop, and the number of target frequencies in the same frequency band. The noise attenuation performances of each partition layout are compared, and their expected recovery energies are calculated. One optimal partition layout is discussed in terms of acoustics, heat transfer, and fluid mechanics. The numerical results strongly support the validity of our proposed method for the optimal design of a muffler integrated with a TEG.

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Topological optimal design of composite magnetic actuators to improve driving force and thermal conductivity

Oh,

Yoo

2024

Struct Multidisc Optim

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Structural Optimization of a Magnetic Actuator With Simultaneous Consideration of Thermal and Magnetic Performances

Cited by 13 publications

References 15 publications

Topological optimal design of composite magnetic actuators to improve driving force and thermal conductivity

Topological optimal design of composite magnetic actuators to improve driving force and thermal conductivity

Partition layout inside a muffler integrated with a thermoelectric generator: Multi-physics analysis and optimal design

Topological optimal design of composite magnetic actuators to improve driving force and thermal conductivity

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