Vectorial surrogate modeling method for multi-objective reliability design

Fei, Chengwei; Li, Huan; Lu, Cheng; Han, Lei; Keshtegar, Behrooz; Taylan, Osman

doi:10.1016/j.apm.2022.03.033

Cited by 49 publications

(16 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The material of turbine blisk is the nickel-based superalloy GH4133, which elastic modulus, Poisson ratio and density are 1.61 3 10 11 Pa, 0.3224, and 8.56 3 10 3 kg/m 3 , respectively (Lu et al, 2018a, b). The input variables contain density, inlet pressure (2 3 10 6 Pa), outlet pressure (5.88 3 10 5 Pa), inlet velocity and angular speed (Fei et al, 2022). The inlet velocity and angular speed are regarded as changes in the time domain [0, 215 s], which can be seen in Figure 13.…”

Section: Case Studies and Further Research Of The Structural Dynamic ...mentioning

confidence: 99%

See 1 more Smart Citation

Structural dynamic reliability analysis: review and prospects

Teng

Feng

Chen

et al. 2022

IJSI

Self Cite

View full text Add to dashboard Cite

PurposeThe purpose of this paper is to briefly summarize and review the theories and methods of complex structures’ dynamic reliability. Complex structures are usually assembled from multiple components and subjected to time-varying loads of aerodynamic, structural, thermal and other physical fields; its reliability analysis is of great significance to ensure the safe operation of large-scale equipment such as aviation and machinery.Design/methodology/approachIn this paper for the single-objective dynamic reliability analysis of complex structures, the calculation can be categorized into Monte Carlo (MC), outcrossing rate, envelope functions and extreme value methods. The series-parallel and expansion methods, multi-extremum surrogate models and decomposed-coordinated surrogate models are summarized for the multiobjective dynamic reliability analysis of complex structures.FindingsThe numerical complex compound function and turbine blisk are used as examples to illustrate the performance of single-objective and multiobjective dynamic reliability analysis methods. Then the future development direction of dynamic reliability analysis of complex structures is prospected.Originality/valueThe paper provides a useful reference for further theoretical research and engineering application.

show abstract

Section: Case Studies and Further Research Of The Structural Dynamic ...mentioning

confidence: 99%

“…, 2018a, b). The input variables contain density, inlet pressure (2 × 10 6 Pa), outlet pressure (5.88 × 10 5 Pa), inlet velocity and angular speed (Fei et al. , 2022).…”

Section: Case Studies and Further Research Of The Structural Dynamic ...mentioning

confidence: 99%

Structural dynamic reliability analysis: review and prospects

Teng

Feng

Chen

et al. 2022

IJSI

Self Cite

View full text Add to dashboard Cite

show abstract

“…Although the meta-model method greatly reduces the calculation amount, but some traditional meta-model methods have limitations in calculation accuracy and efficiency. Fei et al 11 propose a synchronous modeling concept by introducing matrix thought into the surrogate modeling methods. With respect to the synchronous modeling concept, vectorial surrogate modeling (VSM) method is developed to synchronously establish an overall model of complex structures with multiple objectives.…”

Section: Introductionmentioning

confidence: 99%

A reliability‐based robust optimization design for the drum brake using adaptive Kriging surrogate model

Yang

Pak

Kwon

et al. 2022

Quality & Reliability Eng

View full text Add to dashboard Cite

To decrease random parameters’ influence on the drum brake reliability, the reliability‐based robust optimization design (RBROD) of the electric vehicle brake is proposed. Based on the assumption that the maximum temperature of the brake cannot exceed the allowable temperature, a performance function model of thermal–mechanical coupling reliability of drum brakes is established by the adaptive Kriging method, and the analysis of reliability sensitivity and RBROD are conducted. The accuracy of the proposed model is verified by temperature measurement experiment under emergency braking condition. The robust optimization design improves the drum brake reliability to 0.99998 and reduce the influence of the design parameters on the reliability, with the absolute values of the reliability sensitivity and the weight of the drum brake are significantly smaller. Therefore, the objectives of reliability design, robustness design, and optimization design are simultaneously achieved by the proposed methods. Besides, the relative error of the proposed method is 0.373%, the number of function evaluations is 39, and the comparison with four meta‐model methods show that the proposed method holds high‐accuracy and high‐efficiency. This study provides a high‐precision theoretical explanation for the robust optimization design of drum brake.

show abstract

“…Nowadays, swarm intelligence has been widely used to find globally optimal solutions to optimization problems, such as the genetic algorithm (GA) [22,23], the artificial bee colony algorithm (ABC) [24], and the particle swarm optimization (PSO) [25]. In contrast to various evolutionary techniques, PSO is regarded as one of the best-accepted techniques that are cheap in time consumption and simple for implementation.…”

Section: Introductionmentioning

confidence: 99%

Stress Optimization of Vent Holes with Different Shapes Using Efficient Switching Delayed PSO Algorithm

et al. 2022

View full text Add to dashboard Cite

An effective integrated design optimization method is developed to reduce the maximum von Mises stress around vent holes of a high-pressure turbine sealing disk. It mainly includes four different shape designs (circular, elliptical, race-track, and four-arc) for holes, an updated self-developed modelling and meshing tool, an APDL-based strength analysis, and a self-proposed efficient switching delayed particle swarm optimization (SDPSO) algorithm. The main idea of SDPSO is: (1) by evaluating an evolutionary factor and utilizing a probability transition matrix, a non-homogeneous Markov chain is determined and auto-updated in each generation; (2) the evolutionary factor and the Markov chain are used to adaptively select the inertia weight, acceleration coefficients, and delayed information to adjust the particle’s velocity. The performance of SDPSO is evaluated through two benchmark optimization problems with constraints. The results show that SDPSO is superior to two well-known PSO algorithms in optimization capability, numerical robustness, and convergence speed. Furthermore, SDPSO is used for the stress optimization of vent holes with four different shapes. The results show that: (1) SDPSO is suitable and valuable for practical engineering optimization problems with constraints; (2) the developed integrated design optimization method is effective and advanced for reducing the maximum von Mises stress around the vent holes; and (3) the four-arc hole has more tremendous advantages in reducing the maximum von Mises stress, followed by the elliptical hole, the race-track hole, and the circular hole.

show abstract

Vectorial surrogate modeling method for multi-objective reliability design

Cited by 49 publications

References 45 publications

Structural dynamic reliability analysis: review and prospects

Structural dynamic reliability analysis: review and prospects

A reliability‐based robust optimization design for the drum brake using adaptive Kriging surrogate model

Stress Optimization of Vent Holes with Different Shapes Using Efficient Switching Delayed PSO Algorithm

Contact Info

Product

Resources

About