The University of Southampton
University of Southampton Institutional Repository

Optimal calibration of Q235B steel Johnson-Cook model parameters based on global response surface algorithm

Optimal calibration of Q235B steel Johnson-Cook model parameters based on global response surface algorithm
Optimal calibration of Q235B steel Johnson-Cook model parameters based on global response surface algorithm
This study investigates the mechanical properties of Q235B steel through quasi-static tests at both room temperature and elevated temperature. The initial values of the Johnson-Cook model parameters are determined using a fitting method. The global response surface algorithm is employed to optimize and calibrate the Johnson-Cook model parameters for Q235B steel under both room temperature and elevated temperature conditions. A simulation model is established at room temperature, and the simulated mechanical performance curves for displacement and stress are monitored. Multiple optimization algorithms are applied to optimize and calibrate the model parameters at room temperature. The global response surface algorithm is identified as the most suitable algorithm for this optimization problem. Sensitivity analysis is conducted to explore the impact of model parameters on the objective function. The analysis indicates that the optimized material model better fits the experimental values, aligning more closely with the actual test results of material strain mechanisms over a wide temperature range.
Q235B Mechanical property test Numerical simulation Johnson cook model Global response surface algorithm, Johnson cook model, Q235B, Numerical simulation, Mechanical property test, Global response surface algorithm
1671-9433
470-478
Su, Shaojuan
8d90b64e-8e08-49de-beae-f9d76ccdd4c3
Wu, Yujie
ac6a0074-46ac-4e39-98d0-092909d0c1c0
Wang, Guohui
ee5c47ec-3a98-46ef-8ee5-2aabc69270e5
Miao, Zhe
64dfd268-69ce-4dfa-a48d-9c197ca97c04
Xiong, Yeping
51be8714-186e-4d2f-8e03-f44c428a4a49
Guo, Fangxin
a9718148-f2e9-4c6a-ac70-38bac0a91687
Liu, Haibo
713d0ae3-557f-4214-aa76-c2f314a27509
Su, Shaojuan
8d90b64e-8e08-49de-beae-f9d76ccdd4c3
Wu, Yujie
ac6a0074-46ac-4e39-98d0-092909d0c1c0
Wang, Guohui
ee5c47ec-3a98-46ef-8ee5-2aabc69270e5
Miao, Zhe
64dfd268-69ce-4dfa-a48d-9c197ca97c04
Xiong, Yeping
51be8714-186e-4d2f-8e03-f44c428a4a49
Guo, Fangxin
a9718148-f2e9-4c6a-ac70-38bac0a91687
Liu, Haibo
713d0ae3-557f-4214-aa76-c2f314a27509

Su, Shaojuan, Wu, Yujie, Wang, Guohui, Miao, Zhe, Xiong, Yeping, Guo, Fangxin and Liu, Haibo (2024) Optimal calibration of Q235B steel Johnson-Cook model parameters based on global response surface algorithm. Journal of Marine Science and Application, 23 (2), 470-478. (doi:10.1007/s11804-024-00414-5).

Record type: Article

Abstract

This study investigates the mechanical properties of Q235B steel through quasi-static tests at both room temperature and elevated temperature. The initial values of the Johnson-Cook model parameters are determined using a fitting method. The global response surface algorithm is employed to optimize and calibrate the Johnson-Cook model parameters for Q235B steel under both room temperature and elevated temperature conditions. A simulation model is established at room temperature, and the simulated mechanical performance curves for displacement and stress are monitored. Multiple optimization algorithms are applied to optimize and calibrate the model parameters at room temperature. The global response surface algorithm is identified as the most suitable algorithm for this optimization problem. Sensitivity analysis is conducted to explore the impact of model parameters on the objective function. The analysis indicates that the optimized material model better fits the experimental values, aligning more closely with the actual test results of material strain mechanisms over a wide temperature range.

Text
2024 paper_Su&Xiong - Version of Record
Restricted to Repository staff only
Request a copy

More information

Accepted/In Press date: 4 August 2023
e-pub ahead of print date: 24 May 2024
Published date: 13 June 2024
Keywords: Q235B Mechanical property test Numerical simulation Johnson cook model Global response surface algorithm, Johnson cook model, Q235B, Numerical simulation, Mechanical property test, Global response surface algorithm

Identifiers

Local EPrints ID: 494602
URI: http://eprints.soton.ac.uk/id/eprint/494602
ISSN: 1671-9433
PURE UUID: 3bad7f3b-ab95-4fd3-b569-a0b86408891e
ORCID for Yeping Xiong: ORCID iD orcid.org/0000-0002-0135-8464

Catalogue record

Date deposited: 10 Oct 2024 17:04
Last modified: 11 Oct 2024 01:37

Export record

Altmetrics

Contributors

Author: Shaojuan Su
Author: Yujie Wu
Author: Guohui Wang
Author: Zhe Miao
Author: Yeping Xiong ORCID iD
Author: Fangxin Guo
Author: Haibo Liu

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×