Optimization of an auxetic jounce bumper based on Gaussian process metamodel and series hybrid GA-SQP algorithm

Wang, Yuanlong; Zhao, Wanzhong; Guan, Zailin; Gao, Qiang; Wang, Chunyan

doi:10.1007/s00158-017-1869-z

Cited by 32 publications

(16 citation statements)

References 37 publications

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“…The results indicated that the auxetic panels performed better than conventional honeycomb panels in force mitigation and blast-resistance performances. Wang et al 25 researched the auxetic jounce bumper with NPR structure, and the results showed that the maximum vertical acceleration of vehicle when traveling through bump was reduced and the vehicle ride comfort performance was improved. Li et al 26 presented two novel two-dimensional (2D) re-entrant topologies with NPR effect and studied their Poisson’s ratio and energy absorption performance by finite element model.…”

Section: Introductionmentioning

confidence: 99%

Multi-objective crashworthiness optimization of vehicle body with negative Poisson’s ratio structure based on factorial analysis

Zou

Dai

Zhao

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part D:

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To improve vehicle side crashworthiness, this paper first introduces the negative Poisson’s ratio structure to the traditional B-pillar and proposes a negative Poisson’s ratio B-pillar. Then, the performance of the negative Poisson’s ratio B-pillar is studied in detail by comparison with a traditional B-pillar and honeycomb B-pillar. Aiming at the problem that the side crashworthiness is also significantly affected by the side structure parameters of vehicle body, the factorial analysis theory is adopted to screen out the side structure parameters with significant effect. Based on this, by combining the optimal Latin hypercube design and response surface model, a multi-objective optimization design is conducted for those structure parameters based on non-dominated sorting genetic algorithm II. Finally, the normal boundary intersection method is adopted to seek the Pareto optimal solution, and the simulation results show that compared with the traditional B-pillar, the negative Poisson’s ratio B-pillar optimized by non-dominated sorting genetic algorithm II has better comprehensive crashworthiness. The results of this paper can provide some basis for the design and optimization of vehicle side crashworthiness.

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Section: Introductionmentioning

confidence: 99%

Multi-objective crashworthiness optimization of vehicle body with negative Poisson’s ratio structure based on factorial analysis

Zou

Dai

Zhao

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part D:

Self Cite

View full text Add to dashboard Cite

show abstract

“…SQP is executed in numerous optimisation models of numerous complexes as well as non-stiff systems. Presently, it is used to investigate the guidewire deformation in blood vessels [42], in the power system stabiliser design [43], optimal control of rapid cooperative rendezvous [44], 3D deformable prostate model pose estimation in minimally invasive surgery [45], deterministic constrained production optimisation of hydrocarbon reservoirs [46], prediction differential system [47] and in the optimisation of an auxetic jounce bumper [48]. To switch the sluggishness of GA, hybridisation of the GA-SQP process is implemented along with the necessary steps, as provided in Table 1.…”

Section: Optimisation Measures: Mwnns-ga-sqpmentioning

confidence: 99%

Design of Morlet wavelet neural network to solve the non-linear influenza disease system

Sabir

Umar

Raja

et al. 2021

Applied Mathematics and Nonlinear Sciences

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In this study, the solution of the non-linear influenza disease system (NIDS) is presented using the Morlet wavelet neural networks (MWNNs) together with the optimisation procedures of the hybrid process of global/local search approaches. The genetic algorithm (GA) and sequential quadratic programming (SQP), that is, GA-SQP, are executed as the global and local search techniques. The mathematical form of the NIDS depends upon four groups: susceptible S(y), infected I(y), recovered R(y) and cross-immune individuals C(y). To solve the NIDS, an error function is designed using NIDS and its leading initial conditions (ICs). This error function is optimised with a combination of MWNNs and GA-SQP to solve for all the groups of NIDS. The comparison of the obtained solutions and Runge–Kutta results is presented to authenticate the correctness of the designed MWNNs along with the GA-SQP for solving NIDS. Moreover, the statistical operators using different measures are presented to check the reliability and constancy of the MWNNs along with the GA-SQP to solve the NIDS.

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“…e experimental results from a quarter car test rig which were done by Mitra et al [9] show that mass and damping coefficient are the most influential parameters for ride comfort. erefore, many scholars focus their attention on optimizing the mass, damping coefficient, and stiffness coefficient of suspension system and achieve many significant results in enhancing ride comfort by using GA [10][11][12][13][14]. Essentially, the dynamics parameter optimization of suspension system belongs to a multiobjective optimization problem (MOOP) which can be solved by using multiobjective optimization algorithm (MOOA) [15,16].…”

Section: Introductionmentioning

confidence: 99%

Integrated Vibration Control of In‐Wheel Motor‐Suspensions Coupling System via Dynamics Parameter Optimization

Wang

Niu

Song

2019

Shock and Vibration

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In order to integrally control the vibration of in-wheel motor- (IWM-) suspensions coupling system of an electric vehicle, a novel nonlinear dynamics model of the coupling system, which consists of the motor magnetic gap (MMG), is established. Synthesizing subtargets of the vertical vibration acceleration of bodywork, the vertical deformation of tire, the suspension travel, and the vertical fluctuation of MMG, a composite optimization mathematical model is set up. Based on artificial fish swarm algorithm (AFSA), a novel dynamics parameter optimization method is proposed to search the optimal parameter combination existing in the nonlinear dynamics model. Simulation analyses demonstrate that the proposed optimization method is superior to genetic algorithm (GA) under the same optimization conditions, and it can significantly decrease the fluctuation of MMG and improve ride comfort.

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Optimization of an auxetic jounce bumper based on Gaussian process metamodel and series hybrid GA-SQP algorithm

Cited by 32 publications

References 37 publications

Multi-objective crashworthiness optimization of vehicle body with negative Poisson’s ratio structure based on factorial analysis

Multi-objective crashworthiness optimization of vehicle body with negative Poisson’s ratio structure based on factorial analysis

Design of Morlet wavelet neural network to solve the non-linear influenza disease system

Integrated Vibration Control of In‐Wheel Motor‐Suspensions Coupling System via Dynamics Parameter Optimization

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