A Modification of the Ostergren Model for Thermomechanical Fatigue Life Prediction of Die-Casting Die Steel.

Pengpeng Zuo, Xijuan He, Jie Ji, Xiaochun Wu

Abstract read

In one paragraph

Article in Materials (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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5 · Who and what money

Authors and funding

4 authors.

Pengpeng ZuoSchool of Materials Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang 212003, China.ORCID 0000-0001-9650-9052

Xijuan HeState Key Laboratory of Advanced Special Steel, Shanghai University, Shanghai 200444, China.

Jie JiState Key Laboratory of Advanced Special Steel, Shanghai University, Shanghai 200444, China.

Xiaochun WuState Key Laboratory of Advanced Special Steel, Shanghai University, Shanghai 200444, China.

Funding

National Key R&D program of China 2016YFB0300400

6 · The paper itself

Abstract

The Ostergren model is simple in form and widely used in engineering practice, also serving as the modeling basis of both the damage differentiation and crack propagation models. However, the shortcomings of the Ostergren model are that the modeling process is affected by thermomechanical fatigue (TMF) test parameters. To establish a TMF life normalized model, a modified Ostergren model based on hysteresis energy damage and TMF data for H13 steel was proposed. The model was successfully applied to TMF life prediction for 4Cr5Mo2V steel. The band of predicted life and test life is basically within the factor of 1.5. In summary, the modified Ostergren model is suitable for the TMF life prediction of Cr-Mo-V-type die-casting die steel.

Indexed as

die-casting die steellife predictionOstergren modelthermomechanical fatigue (TMF)

Identifiers

PMID39685180

DOI10.3390/ma17235744

PMCPMC11642089

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.