Development of a multi-objective artificial tree (MOAT) algorithm and its application in acoustic metamaterials

He, Zhichen; Li, Eric; Chen, Tao; Wang, Qiuyu; Cheng, Aiguo

doi:10.1007/s12293-020-00302-9

Cited by 10 publications

(4 citation statements)

References 28 publications

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“…The goals of these multi-objective problems are to maximize the MCF and minimize the SM. MOAT algorithm [40][41][42] is applied to perform the optimization design. The mathematical models of these optimization problems are expressed in Eq.…”

Section: Optimize These Three Front Railsmentioning

confidence: 99%

Improve the frontal crashworthiness of vehicle through the design of front rail

Chen

et al. 2021

Thin-Walled Structures

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Section: Optimize These Three Front Railsmentioning

confidence: 99%

Improve the frontal crashworthiness of vehicle through the design of front rail

Chen

et al. 2021

Thin-Walled Structures

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“…First, two optimization objectives are considered in the B-pillar and the rocker, that maximizing MCF and minimizing SM. We use the MOAT algorithm [51][52][53][54] to optimize the two-objective issues. The theory of MOAT algorithm is shown in supplementary file.…”

Section: Optimize the B-pillar And The Rockermentioning

confidence: 99%

Multi-objective optimization design of B-pillar and rocker sub-systems of battery electric vehicle

Chen

et al. 2021

Struct Multidisc Optim

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B-pillar and rocker are the key force transmission sub-systems of the side impact of Battery Electric Vehicle (BEV), and scholars have studied the side crashworthiness of these sub-systems and vehicle body a lot. However, these works are insufficient on the analysis of benchmarking vehicle models, the simulation and experiment of the B-pillar and rocker sub-systems, and the optimization of these sub-systems. To make up these shortcomings, this work aims to design the B-pillar and the rocker, and improve the side crashworthiness of BEV. It presents a systematic method on the side crashworthiness of BEV. The dynamic bending performance of the B-pillar and the rocker are studied in simulation analyses and experiments. The materials, structures and crashworthiness of these two sub-systems of eleven benchmark models are studied. Minimizing structural mass (SM) and Cost as well as maximizing mean crushing force (MCF) are performed based on multi-objective artificial tree (MOAT) algorithm to optimize the B-pillar and the rocker. The optimized sub-systems are applied to the body of a BEV. As a result, the performance of the B-pillar and the rocker is significantly improved, and their optimal solution templates are provided. The performance of the BEV is also improved under the Advanced European Mobile Deformable Barrier (AEMDB) side impact and the oblique pole side impact. Some interesting conclusions for BEV are presented. In summary, this work has obvious reference value for automotive engineers and scholars to further study the crashworthiness and lightweight of BEV.

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“…Besides the application of new materials, structural optimization [46][47][48][49][50][51][52][53] can further enhance the performance of thin-walled beams. Li et al [54] takes the thickness of steel hat-shaped beams as variables, and their crashworthiness was significantly improved by constructing surrogate models and applying a multi-objective algorithm.…”

Section: Introductionmentioning

confidence: 99%