Structural sensitivity reanalysis formulations based on the polynomial-type extrapolation methods

Yousef Hosseinzadeh* (Corresponding Author), Shahin Jalili

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This paper presents new structural sensitivity reanalysis formulations based on the polynomial-type extrapolation methods. In these formulations, the displacement vector of the modified structure is expressed in the form of the vector sequences based on the fixed-point iteration method. By using these vector sequences, the minimal polynomial extrapolation (MPE) and the reduced rank extrapolation (RRE) methods calculate the approximate displacement vector of the modified structure by solving reduced linear least-square problems. Based on the definitions of the MPE and RRE methods, two sensitivity reanalysis formulations are derived, in which the first- and second-order sensitivities of the modified structure are obtained by solving a set of the over-determined least-square problems with much smaller size than the complete set of equations of the exact sensitivity analyses. The performance of the proposed sensitivity reanalysis formulations is evaluated by using four structural sensitivity reanalysis problems under multiple modifications in their initial designs. The results obtained from the numerical test problems indicate that the proposed sensitivity reanalysis formulations approximate the first- and second-order sensitivities of the modified structure with a high level of accuracy and they are able to converge to the exact solutions.
Original languageEnglish
Pages (from-to)1027-1050
Number of pages24
JournalStructural and multidisciplinary optimization
Volume61
Early online date16 Oct 2019
DOIs
Publication statusPublished - Mar 2020

Bibliographical note

Funding
This research is supported by a research grant of the University of Tabriz (grant No. 3500).

Keywords

  • Minimal polynomial extrapolation
  • Polynomial-type extrapolation
  • Reanalysis
  • Reduced rank extrapolation
  • Sensitivity
  • ACCELERATION
  • DESIGN
  • APPROXIMATION
  • CONVERGENCE

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