This work studies the Voce–Chaboche (V–C) material model parameter optimization for high-strength steel welded joints subjected to cyclic loading. The model parameters of each material zone in a S690 steel butt-welded joint were determined using an optimization algorithm based on the Newton trust region (NTR) method and an accumulated true strain parameter. The model parameters were fitted to stress–strain histories from uniaxial strain-controlled cyclic tests. To validate the model, fully-reversed variable amplitude fatigue experiments were performed under load control. The experimental results were then compared to numerical results from a finite element analysis. When the elastic modulus is optimized as a V–C parameter, the results indicate that the V–C model slightly underestimates the strain range, leading to conservative fatigue life estimates. However, the results can be improved by using an elastic modulus obtained experimentally. In this case, the resulting material model slightly overestimates the strain range, leading to a non-conservative, but more accurate, fatigue life estimation. It can be concluded that the NTR-based accumulated true strain approach successfully determined the V–C model parameters for different material zones in the welded joint, and closely estimated the strain range and the fatigue life for a variable amplitude load history.

Optimizing the Voce – Chaboche Model Parameters for Fatigue Life Estimation of Welded Joints in High-Strength Marine Structures / Petry, Alice; Gallo, Pasquale; Remes, Heikki; Niemelä, Ari. - In: JOURNAL OF MARINE SCIENCE AND ENGINEERING. - ISSN 2077-1312. - 10:6(2022), p. 818. [10.3390/jmse10060818]

Optimizing the Voce – Chaboche Model Parameters for Fatigue Life Estimation of Welded Joints in High-Strength Marine Structures

Gallo, Pasquale
Secondo
;
2022-01-01

Abstract

This work studies the Voce–Chaboche (V–C) material model parameter optimization for high-strength steel welded joints subjected to cyclic loading. The model parameters of each material zone in a S690 steel butt-welded joint were determined using an optimization algorithm based on the Newton trust region (NTR) method and an accumulated true strain parameter. The model parameters were fitted to stress–strain histories from uniaxial strain-controlled cyclic tests. To validate the model, fully-reversed variable amplitude fatigue experiments were performed under load control. The experimental results were then compared to numerical results from a finite element analysis. When the elastic modulus is optimized as a V–C parameter, the results indicate that the V–C model slightly underestimates the strain range, leading to conservative fatigue life estimates. However, the results can be improved by using an elastic modulus obtained experimentally. In this case, the resulting material model slightly overestimates the strain range, leading to a non-conservative, but more accurate, fatigue life estimation. It can be concluded that the NTR-based accumulated true strain approach successfully determined the V–C model parameters for different material zones in the welded joint, and closely estimated the strain range and the fatigue life for a variable amplitude load history.
2022
6
Petry, Alice; Gallo, Pasquale; Remes, Heikki; Niemelä, Ari
Optimizing the Voce – Chaboche Model Parameters for Fatigue Life Estimation of Welded Joints in High-Strength Marine Structures / Petry, Alice; Gallo, Pasquale; Remes, Heikki; Niemelä, Ari. - In: JOURNAL OF MARINE SCIENCE AND ENGINEERING. - ISSN 2077-1312. - 10:6(2022), p. 818. [10.3390/jmse10060818]
File in questo prodotto:
File Dimensione Formato  
2022_Alice_Petry_VC_jmse-10-00818 (ottimizzato).pdf

accesso aperto

Tipologia: Versione editoriale (Publisher’s layout)
Licenza: Creative commons
Dimensione 2.03 MB
Formato Adobe PDF
2.03 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/403654
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 10
  • ???jsp.display-item.citation.isi??? 9
social impact