Applying Reliability Assessment Methods to Superconducting Magnetic Energy Storage System (SMES) Designs

Sung, Young Hwa; Kim, Dong-Wook; Kim, Dong-Hun

doi:10.1109/tmag.2011.2157516

Cited by 11 publications

(12 citation statements)

References 15 publications

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“…2. For solving (6), the Hasofer Lind and Rackwitz Fiessler (HL-RF) method [5] is employed here because of its simplicity and efficiency. The flowchart of the HL-RF method is illustrated in Fig.…”

Section: ) Transformation Of a Design Spacementioning

confidence: 99%

“…[1][2][3][4][5][6]. The methodology for treating optimization problems in the presence of uncertainties of design parameters/variables can be categorized into two approaches.…”

Section: Introductionmentioning

confidence: 99%

“…Until now, most of the reported attempts for EM designs fall into RDO. Although the reliability analysis has been applied to a superconducting magnetic energy storage system (SMES) design [6], it is to merely assess the robustness of performance functions considered at different design points and not to execute design optimization of SMES.…”

Section: Introductionmentioning

confidence: 99%

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Reliability-Based Design Optimization of a Superconducting Magnetic Energy Storage System (SMES) Utilizing Reliability Index Approach

Jeung¹,

Kim²,

Sung³

et al. 2012

Journal of Magnetics

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A reliability-based optimization method for electromagnetic design is presented to take uncertainties of design parameters into account. The method can provide an optimal design satisfying a specified confidence level in the presence of uncertain parameters. To achieve the goal, the reliability index approach based on the firstorder reliability method is adopted to deal with probabilistic constraint functions and a double-loop optimization algorithm is implemented to obtain an optimum. The proposed method is applied to the TEAM Workshop Problem 22 and its accuracy and efficiency is verified with reference of Monte Carlo simulation results.

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Section: ) Transformation Of a Design Spacementioning

confidence: 99%

“…[1][2][3][4][5][6]. The methodology for treating optimization problems in the presence of uncertainties of design parameters/variables can be categorized into two approaches.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Reliability-Based Design Optimization of a Superconducting Magnetic Energy Storage System (SMES) Utilizing Reliability Index Approach

Jeung¹,

Kim²,

Sung³

et al. 2012

Journal of Magnetics

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“…R ECENTLY, robust design optimization (RDO) has been developed and applied in electromagnetic (EM) designs [1]- [5]. Unlike conventional deterministic design optimization (DDO), the outstanding merit of robust design is to incorporate design uncertainty into an early design stage.…”

Section: Introductionmentioning

confidence: 99%

“…Consequently, they do not address the quantitative assessment of the first two statistical moments, mean and variance, of system output. In other words, they cannot give any probabilistic information on how much the impact of the uncertainty concerned with system input is on system output at a nominal design [5]- [8]. On the other hand, MCS could be accurate for the moment estimation, but it requires a large number of function evaluations.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Statistical Moments of a Performance Function for Robust Design of Electromagnetic Devices

et al. 2015

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This paper proposes a statistical probability approach to evaluate the quality loss function of electromagnetic design problems, which is expressed in terms of the first two statistical moments, mean and variance. A univariate dimension reduction method is employed to calculate the statistical moments of a performance function and their sensitivities accurately, and efficiently. Finally, the method is integrated into the robust design optimization algorithm. The proposed method explores an optimum design with statistical information so that it can provide a more accurate solution than other robust design methods. The proposed method is tested with a mathematical model and a blushless DC motor, and its numerical accuracy and efficiency are examined by comparison with existing methods.

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Efficient strategies for reliability‐based design optimisation of a superconducting magnetic energy storage system‐based on reliability index approach

Kim¹,

Jeung²,

Choi

et al. 2013

IET Science, Measurement & Technology

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This study presents an enriched reliability index approach for reliability-based design optimisation of electromagnetic devices in the presence of variability in design variables. To substantially improve computational efficiency, two new optimisation strategies consisting of a constraint indicator condition and a successive optimum search technique are incorporated into the existing method based on the reliability index approach. The constraint indicator decides whether reliability analysis is needed for each intermediate design during the reliability-based optimisation process. Employing the successive optimum search technique, a deterministic optimum is first sought from an initial design and then a probabilistic optimum is obtained by launching at the deterministic optimum. The proposed method is tested with a coil design problem for a superconducting magnetic energy storage system, and is thoroughly investigated by comparing the results with the conventional method based on the reliability index approach and the Monte Carlo simulation in terms of computational efficiency and accuracy. Finally, the results show that the method leads to a significantly decreasing computational cost.

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Applying Reliability Assessment Methods to Superconducting Magnetic Energy Storage System (SMES) Designs

Cited by 11 publications

References 15 publications

Reliability-Based Design Optimization of a Superconducting Magnetic Energy Storage System (SMES) Utilizing Reliability Index Approach

Reliability-Based Design Optimization of a Superconducting Magnetic Energy Storage System (SMES) Utilizing Reliability Index Approach

Assessment of Statistical Moments of a Performance Function for Robust Design of Electromagnetic Devices

Efficient strategies for reliability‐based design optimisation of a superconducting magnetic energy storage system‐based on reliability index approach

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