Energy-absorbing analysis and reliability-based multiobjective optimization design of graded thickness B pillar with grey relational analysis

Optimization design of the structures and thicknesses of the sound packages is performed for automotive interior acoustic performance and lightweight characteristics. A SEA model of the car was created, and its interior noise of the automobile was predicted and validated at speed of 120 km/h. The contributions of some major subsystems to interior noise were calculated at 120 km/h. Both of major characteristic indices including interior SPL and total weight of sound packages are selected to evaluate automotive interior acoustic performance and lightweight characteristics, and four selected optimization parameters are structures and thicknesses of the sound package of firewall and front floor. The problem of multiple performance indices is simplified into single performance index by using grey relational grade. The optimal combination of sound package parameters is determined by employing grey relational analysis method. Furthermore, the validation tests show that the values of interior SPL and overall weight of sound packages decrease by 1.31% and 60.36%, respectively. Also, the comparison of the overall SPL for automotive interior noise experiments between original and optimized structures and thicknesses of the sound packages shows that automotive interior acoustic performance is obviously improved from 200 Hz to 10,000 Hz. Therefore, it is demonstrated that it is an effective way to deal with optimization problems by using the presented approach in this research.

Download Full-text

AUTOMOTIVE EXTERIOR NOISE OPTIMIZATION USING GREY RELATIONAL ANALYSIS COUPLED WITH PRINCIPAL COMPONENT ANALYSIS

Fluctuation and Noise Letters ◽

10.1142/s021947751350017x ◽

2013 ◽

Vol 12 (03) ◽

pp. 1350017 ◽

Cited By ~ 2

Author(s):

SHUMING CHEN ◽

DENGFENG WANG ◽

BO LIU

Keyword(s):

Principal Component Analysis ◽

Grey Relational Analysis ◽

Optimization Design ◽

Principal Component ◽

Aluminum Foil ◽

Component Analysis ◽

Optimal Combination ◽

Relational Analysis ◽

Noise Optimization ◽

Grey Relational

This paper investigates optimization design of the thickness of the sound package performed on a passenger automobile. The major characteristics indexes for performance selected to evaluate the processes are the SPL of the exterior noise and the weight of the sound package, and the corresponding parameters of the sound package are the thickness of the glass wool with aluminum foil for the first layer, the thickness of the glass fiber for the second layer, and the thickness of the PE foam for the third layer. In this paper, the process is fundamentally with multiple performances, thus, the grey relational analysis that utilizes grey relational grade as performance index is especially employed to determine the optimal combination of the thickness of the different layers for the designed sound package. Additionally, in order to evaluate the weighting values corresponding to various performance characteristics, the principal component analysis is used to show their relative importance properly and objectively. The results of the confirmation experiments uncover that grey relational analysis coupled with principal analysis methods can successfully be applied to find the optimal combination of the thickness for each layer of the sound package material. Therefore, the presented method can be an effective tool to improve the vehicle exterior noise and lower the weight of the sound package. In addition, it will also be helpful for other applications in the automotive industry, such as the First Automobile Works in China, Changan Automobile in China, etc.

Download Full-text

Multiobjective Optimization of ELID Grinding Process Using Grey Relational Analysis Coupled with Principal Component Analysis

Advances in Mechanical Engineering ◽

10.1155/2014/878510 ◽

2014 ◽

Vol 6 ◽

pp. 878510 ◽

Cited By ~ 2

Author(s):

S. Prabhu ◽

B. K. Vinayagam

Keyword(s):

Principal Component Analysis ◽

Multiobjective Optimization ◽

Process Parameters ◽

Grey Relational Analysis ◽

Principal Component ◽

Grinding Wheel ◽

Grinding Process ◽

Elid Grinding ◽

Relational Analysis ◽

Grey Relational

Carbon nanotube (CNT) mixed grinding wheel has been used in the electrolytic in-process dressing (ELID) grinding process to analyze the surface characteristics of AISI D2 Tool steel material. CNT grinding wheel is having an excellent thermal conductivity and good mechanical property which is used to improve the surface finish of the work piece. The multiobjective optimization of grey relational analysis coupled with principal component analysis has been used to optimize the process parameters of ELID grinding process. Based on the Taguchi design of experiments, an L9 orthogonal array table was chosen for the experiments. The confirmation experiment verifies the proposed that grey-based Taguchi method has the ability to find out the optimal process parameters with multiple quality characteristics of surface roughness and metal removal rate. Analysis of variance (ANOVA) has been used to verify and validate the model. Empirical model for the prediction of output parameters has been developed using regression analysis and the results were compared for with and without using CNT grinding wheel in ELID grinding process.

Download Full-text

Multi-objective lightweight design of the container S-beam based on MNSGA-II with grey relational analysis

Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science ◽

10.1177/0954406218823802 ◽

2019 ◽

Vol 233 (10) ◽

pp. 3376-3387

Author(s):

Dengfeng Wang ◽

Shuang Wang

Keyword(s):

Weight Reduction ◽

Grey Relational Analysis ◽

Optimization Design ◽

Lightweight Design ◽

Parametric Model ◽

Design Parameters ◽

Combined Method ◽

Multi Objective ◽

Relational Analysis ◽

Grey Relational

A novel bottom corrugated cross-beam (S-beam) structure improved the dynamic and static performance of a container based on the combination of a modified non-dominated sorting genetic algorithm (MNSGA-II) and grey relational analysis. First, a parametric model was established and used to verify the structure’s validity through static physical testing. Eight design variables for the S-beam container structure were also defined according to the parametric model technology. Second, MNSGA-II was used for the multi-objective lightweight optimization design of an S-beam container to obtain the optimal combination of design parameters that are considerably affected by weight reduction under peak bending stress and peak loading deflection as well as first-order natural frequency variations within the allowable range. A set of non-dominated solutions was used to obtain a multi-objective optimization design. Finally, grey relational analysis and grey entropy theory are applied to rank all solutions and determine the best compromise solution. The comparison of the technique for the order of preference by similarity to ideal solution method with grey relational analysis demonstrates the extraordinary reliability and superiority of the latter. In addition, the combined method can achieve a weight reduction of up to 23.54%, which can enhance the utilization of materials and demonstrates the superiority of the combined method relative to the initial model.

Download Full-text

A multiobjective optimization of journal bearing with double parabolic profiles and groove textures under steady operating conditions

Mechanics & Industry ◽

10.1051/meca/2020017 ◽

2020 ◽

Vol 21 (3) ◽

pp. 305

Author(s):

Chongpei Liu ◽

Ning Zhong ◽

Xiqun Lu ◽

Bin Zhao

Keyword(s):

Multiobjective Optimization ◽

Carrying Capacity ◽

Grey Relational Analysis ◽

Journal Bearing ◽

Operating Conditions ◽

Friction Loss ◽

Load Carrying Capacity ◽

Relational Analysis ◽

Load Carrying ◽

Grey Relational

The double parabolic profiles can help journal bearing to reduce bushing edge wear, but it also reduces load carrying capacity and increases friction loss. To overcome these drawbacks, in this study, a multiobjective optimization of journal bearing with double parabolic profiles and groove textures is researched under steady operating conditions using Taguchi and grey relational analysis methods. Firstly, a lubrication model with journal misalignment, elastic deformation, asperity contact, thermal effect is established and formation cause of drawbacks is illustrated. Then, an orthogonal test with considering six factors, i.e., groove number, groove depth, groove length, axial width of double parabolic profiles, radial height of double parabolic profiles and groove location is conducted, meanwhile the effects and significances of each factor on response variables are revealed. Finally, an optimal parameters combination of six factors is determined by grey relational analysis, which gives maximum load carrying capacity and minimum friction loss. Overall, this study may give guidance on journal bearing design to enhance its tribological performance.

Download Full-text