Reliability Assessment on Different Designs of a SMES System Based on the Reliability Index Approach

Kim, Dong-Wook; Sung, Young Hwa; Jeung, Gi-Woo; Jung, Sang Sik; Kim, Hongjoon; Kim, Dong-Hun

doi:10.5370/jeet.2012.7.1.46

Cited by 9 publications

(16 citation statements)

References 9 publications

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“…2 [10,11]. For solving (5), the Hasofer-Lind and Rackwitz-Fiessler (HL-RF) method is employed here because of its simplicity and efficiency [11][12][13].…”

Section: Reliability Analysis Using Riamentioning

confidence: 99%

“…Generally, DDO is performed by two representative methodologies: one is the sampling-based approach, such as evolution strategy, genetic algorithm, particle swarm and so on; the other is the sensitivity-based approach employing design sensitivity values. Unlike DDO, not enough intensive research on the issue of uncertainty in EM designs has been conducted so far [1][2][3][4][5][6][7][8][9][10][11]. Probabilistic design optimisation can be classified into two approaches: robust design optimisation (RDO) and reliability-based design optimisation (RBDO).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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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“…2 [10,11]. For solving (5), the Hasofer-Lind and Rackwitz-Fiessler (HL-RF) method is employed here because of its simplicity and efficiency [11][12][13].…”

Section: Reliability Analysis Using Riamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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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show abstract

“…Very recently, engineers have heightened their interests in improving safety level (reliability) of electromagnetic devices accounting for uncertainties. In this area, the powerful tool, reliability analysis, has been applied to find a reliable optimal design of electromagnetic devices [1], [2]. In the conventional methods for reliability analysis, uncertainties are generally assumed to follow a certain probability density distribution such as Gaussian distribution or uniform distribution.…”

Section: Introductionmentioning

confidence: 99%

A New Reliability Analysis Algorithm With Insufficient Uncertainty Data for Optimal Robust Design of Electromagnetic Devices

et al. 2015

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Due to the existence of randomness and fuzziness in engineering problems, the reliable performance prediction is very complex. In addition, in the early design stage of a new product, the insufficient information on uncertainty further aggravates the difficulty of performance prediction and robustness evaluation. This paper suggests a new reliability analysis method using possibility theory to evaluate constraint feasibility even with insufficient uncertainty data in design variables. In order to save the computing time, two strategies of approximating performance constraints are proposed: 1) design sensitivity-based method and 2) dynamic Kriging-based method. Through applications to analytic example and engineering problem, the proposed methods are investigated and discussed.Index Terms-Finite-element analysis (FEA), fuzzy measures, possibility theory, reliability analysis, uncertainty in design variable.

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“…2, under different uncertainties are calculated by using the RIA [8], the conventional MCS, the FS-MCS, and the SS-MCS methods, respectively. The maximum test designs and CL in the MCSs are set one million and 0.95, respectively.…”

Section: Analytic Test Problemmentioning

confidence: 99%

“…For the reliability analysis, assuming all uncertain variables are independent with each other and follow the Gaussian distribution [8], the uncertainty set is defined as:…”

Section: Reliability Calculation Based On First-and Second-order Sensmentioning

confidence: 99%

A Second-Order Design Sensitivity-Assisted Monte Carlo Simulation Method for Reliability Evaluation of the Electromagnetic Devices

Ren

Koh²

2013

Journal of Electrical Engineering and Technology

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-In the reliability-based design optimization of electromagnetic devices, the accurate and efficient reliability assessment method is very essential. The first-order sensitivity-assisted Monte Carlo Simulation is proposed in the former research. In order to improve its accuracy for wide application, in this paper, the second-order sensitivity analysis is presented by using the hybrid direct differentiation-adjoint variable method incorporated with the finite element method. By combining the second-order sensitivity with the Monte Carlo Simulation method, the second-order sensitivity-assisted Monte Carlo Simulation algorithm is proposed to implement reliability calculation. Through application to one superconductor magnetic energy storage system, its accuracy is validated by comparing calculation results with other methods.

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Reliability Assessment on Different Designs of a SMES System Based on the Reliability Index Approach

Cited by 9 publications

References 9 publications

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

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

A New Reliability Analysis Algorithm With Insufficient Uncertainty Data for Optimal Robust Design of Electromagnetic Devices

A Second-Order Design Sensitivity-Assisted Monte Carlo Simulation Method for Reliability Evaluation of the Electromagnetic Devices

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