SMES Optimization Benchmark Extended: Introducing Pareto Optimal Solutions Into TEAM22

Alotto, Piergiorgio; Baumgartner, Ulrike; Freschi, Fabio; Jaindl, Michael; Köstinger, Alice; Magele, Christian; Renhart, Werner; Repetto, Maurizio

doi:10.1109/tmag.2007.916091

Cited by 60 publications

(29 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Table 6 compares reliabilities calculated for optimal designs in Table 3, where the corresponding current densities are taken as uncertain ones with σ=[0.179,0.179] T MA/m 2 . The optimal design [15], however, is definitely better than [16] because the former gives a better objective value and a higher reliability at the same time. Between the optimal designs [17] and [18], neither of them can be said a superior design because of the confliction between the objective value and the reliability level.…”

Section: B Uncertainty Is Considered In Physical Parametersmentioning

confidence: 98%

“…8, should be as small as possible. In order to achieve these targets, the geometric parameters of inside and outside coils, and current densities (J 1 , J 2 ) should be optimized [15]. The objective function to be minimized is defined as follows: where B stray,i is the magnetic flux density on the ith sampling point and the reference stray field is B norm =3 mT.…”

Section: Team Problem 22mentioning

confidence: 99%

“…For design [15], the approximated constraint functions by the first-order sensitivity are compared with their target values. The corresponding relative errors are shown in Fig.…”

Section: A Uncertainty Is Considered In Geometric Variablesmentioning

confidence: 99%

See 2 more Smart Citations

A New Sensitivity-Based Reliability Calculation Algorithm in the Optimal Design of Electromagnetic Devices

Ren¹,

Koh²

2013

Journal of Electrical Engineering and Technology

View full text Add to dashboard Cite

-A new reliability calculation method is proposed based on design sensitivity analysis by the finite element method for nonlinear performance constraints in the optimal design of electromagnetic devices. In the proposed method, the reliability of a given design is calculated by using the Monte Carlo simulation (MCS) method after approximating a constraint function to a linear one in the confidence interval with the help of its sensitivity information. The validity and numerical efficiency of the proposed sensitivity-assisted MCS method are investigated by comparing its numerical results with those obtained by using the conventional MCS method and the first-order reliability method for analytic functions and the TEAM Workshop Problem 22.

show abstract

Section: B Uncertainty Is Considered In Physical Parametersmentioning

confidence: 98%

Section: Team Problem 22mentioning

confidence: 99%

See 1 more Smart Citation

A New Sensitivity-Based Reliability Calculation Algorithm in the Optimal Design of Electromagnetic Devices

Ren¹,

Koh²

2013

Journal of Electrical Engineering and Technology

View full text Add to dashboard Cite

show abstract

“…Fig. 5 shows the configuration of one SMES system, which has been accepted as one benchmark optimization problem for testing of electromagnetic analysis method; it is composed of two concentric coils carrying current with opposite directions [10]. The optimal design of the SMES should couple the totally stored energy of E 0 =180 (MJ) with a minimal stray field.…”

Section: Electromagnetic Application To the Superconductor Magnetic Ementioning

confidence: 99%

“…For the three-parameter (radius, height, and thickness of outer coil) SMES optimization problem [10], the three geometric parameters…”

Section: A Reliability Calculationmentioning

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

View full text Add to dashboard Cite

-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.

show abstract

Introduction

Lei

Zhu

Guo

2016

Multidisciplinary Design Optimization Methods for Electrical Machines and Drive Systems

View full text Add to dashboard Cite

SMES Optimization Benchmark Extended: Introducing Pareto Optimal Solutions Into TEAM22

Cited by 60 publications

References 5 publications

A New Sensitivity-Based Reliability Calculation Algorithm in the Optimal Design of Electromagnetic Devices

A New Sensitivity-Based Reliability Calculation Algorithm in the Optimal Design of Electromagnetic Devices

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

Introduction

Contact Info

Product

Resources

About