523
Views
20
CrossRef citations to date
0
Altmetric
Original Articles

Multi-objective robust optimization design of a front-end underframe structure for a high-speed train

, , , &
Pages 753-774 | Received 20 Feb 2018, Accepted 17 Jun 2018, Published online: 06 Aug 2018
 

ABSTRACT

A multi-objective robust design optimization of a front-end underframe structure for application in high-speed trains is proposed and the structural parameter uncertainty is considered. A finite element model of the structure is developed and verified by dynamic impact experiments. The sensitivity analysis demonstrates that the thicknesses of the centre sill have significant influences on structural crushing behaviours. The specific energy absorption and the initial peak crushing force (Fp) are taken as optimization objectives. Compared with the baseline structure, the 6-sigma robust design shows that the Fp and the structural mass are reduced by 54.86% and 13.06%, respectively, and the robust optimum is more reliable. The 6-sigma robust optimal solution has an efficient energy-absorbing capacity while satisfying the design constraint. Thus, 6-sigma robust optimization can be applied for high-speed trains.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The work was supported by the National Natural Science Foundation of China [grant number 51405517, U1334208], the Natural Science Foundation of Hunan Province [grant number 2015JJ3155], the China Postdoctoral Science Foundation [grant number 2015M570691], the National Key Research and Development Program of China [grant number 2016YFB1200505-017] and the Fundamental Research Funds for the Central Universities of Central South University [grant number 2018zzts165].

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 1,161.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.