High-cycle fatigue model calibration with a deterministic optimization approach

Arturo Rubio Ruiz; Timo Saksala; Djebar Baroudi; Mikko Hokka; Reijo Kouhia

doi:10.1016/j.ijfatigue.2023.107747

High-cycle fatigue model calibration with a deterministic optimization approach

Arturo Rubio Ruiz^*
, Timo Saksala
, Djebar Baroudi
, Mikko Hokka
, Reijo Kouhia

^*Corresponding author for this work

Tampere University

Research output: Contribution to journal › Article › Scientific › peer-review

8 Citations (Scopus)

136 Downloads (Pure)

Abstract

A parameter identification approach is proposed to calibrate the Ottosen high cycle fatigue model using numerical optimization with regularization. The damage evolution was predicted by a continuum approach based on a moving endurance surface in the stress space, so the stress states outside the endurance surface may lead to damage evolution. The calibration of the model relied on uniaxial and multiaxial experimental data. The predictions of the calibrated models were in fair agreement with the experimental data for the 7075-T7451 and 7050-T6 aluminum alloys subjected to cyclic uniaxial and multiaxial loadings.

Original language	English
Article number	107747
Number of pages	10
Journal	International Journal of Fatigue
Volume	175
Early online date	4 Aug 2023
DOIs	https://doi.org/10.1016/j.ijfatigue.2023.107747
Publication status	Published - Oct 2023
MoE publication type	A1 Journal article-refereed

Funding

Co-funded by the European Union (Grant Agreement No. 101058179; ENGINE). Views and opinions expressed are however those of the authors only and do not necessarily reflect those of the European Union or the European Health and Digital Executive Agency. Neither the European Union nor the granting authority can be held responsible for them. All authors have read and agreed to the final version of the manuscript, except D. Baroudi who untimely passed away before the review of the first manuscript was received.

Keywords

Endurance function
High-cycle fatigue
Morozov discrepancy principle
Optimization
Stable parameter identification

Access to Document

10.1016/j.ijfatigue.2023.107747Licence: CC BY

1-s2.0-S0142112323002487-mainFinal published version, 2.6 MBLicence: CC BY

Cite this

@article{b33112dd295e4ad38dee5fb90579a4fa,

title = "High-cycle fatigue model calibration with a deterministic optimization approach",

abstract = "A parameter identification approach is proposed to calibrate the Ottosen high cycle fatigue model using numerical optimization with regularization. The damage evolution was predicted by a continuum approach based on a moving endurance surface in the stress space, so the stress states outside the endurance surface may lead to damage evolution. The calibration of the model relied on uniaxial and multiaxial experimental data. The predictions of the calibrated models were in fair agreement with the experimental data for the 7075-T7451 and 7050-T6 aluminum alloys subjected to cyclic uniaxial and multiaxial loadings.",

keywords = "Endurance function, High-cycle fatigue, Morozov discrepancy principle, Optimization, Stable parameter identification",

author = "\{Rubio Ruiz\}, Arturo and Timo Saksala and Djebar Baroudi and Mikko Hokka and Reijo Kouhia",

note = "Publisher Copyright: {\textcopyright} 2023 The Author(s)",

year = "2023",

month = oct,

doi = "10.1016/j.ijfatigue.2023.107747",

language = "English",

volume = "175",

journal = "International Journal of Fatigue",

issn = "0142-1123",

publisher = "Elsevier",

}

TY - JOUR

T1 - High-cycle fatigue model calibration with a deterministic optimization approach

AU - Rubio Ruiz, Arturo

AU - Saksala, Timo

AU - Baroudi, Djebar

AU - Hokka, Mikko

AU - Kouhia, Reijo

PY - 2023/10

Y1 - 2023/10

N2 - A parameter identification approach is proposed to calibrate the Ottosen high cycle fatigue model using numerical optimization with regularization. The damage evolution was predicted by a continuum approach based on a moving endurance surface in the stress space, so the stress states outside the endurance surface may lead to damage evolution. The calibration of the model relied on uniaxial and multiaxial experimental data. The predictions of the calibrated models were in fair agreement with the experimental data for the 7075-T7451 and 7050-T6 aluminum alloys subjected to cyclic uniaxial and multiaxial loadings.

AB - A parameter identification approach is proposed to calibrate the Ottosen high cycle fatigue model using numerical optimization with regularization. The damage evolution was predicted by a continuum approach based on a moving endurance surface in the stress space, so the stress states outside the endurance surface may lead to damage evolution. The calibration of the model relied on uniaxial and multiaxial experimental data. The predictions of the calibrated models were in fair agreement with the experimental data for the 7075-T7451 and 7050-T6 aluminum alloys subjected to cyclic uniaxial and multiaxial loadings.

KW - Endurance function

KW - High-cycle fatigue

KW - Morozov discrepancy principle

KW - Optimization

KW - Stable parameter identification

UR - https://www.scopus.com/pages/publications/85161625616

UR - https://doi.org/10.1016/j.ijfatigue.2023.107862

U2 - 10.1016/j.ijfatigue.2023.107747

DO - 10.1016/j.ijfatigue.2023.107747

M3 - Article

AN - SCOPUS:85161625616

SN - 0142-1123

VL - 175

JO - International Journal of Fatigue

JF - International Journal of Fatigue

M1 - 107747

ER -

High-cycle fatigue model calibration with a deterministic optimization approach

Abstract

Funding

Keywords

Access to Document

Other files and links

Fingerprint

High-cycle fatigue model calibration with a deterministic optimization approach

Cite this