Prediction of Strain Hardening and Durability Based on the Calculated Non-Proportional Cyclic Hardening Coefficient
The effectiveness of the previously proposed improved approach for determining the non-proportional cyclic hardening coefficient in predicting the maximum level of strain hardening and durability of metallic materials was tested. The approach is based on the correlation between static and cyclic str...
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Veröffentlicht in: | Strength of materials 2024-03, Vol.56 (2), p.271-280 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | The effectiveness of the previously proposed improved approach for determining the non-proportional cyclic hardening coefficient in predicting the maximum level of strain hardening and durability of metallic materials was tested. The approach is based on the correlation between static and cyclic strain hardening of metallic materials, takes into account the amplitude of cyclic deformation, and does not require fatigue experiments under non-proportional loading. The calculated and experimental values of this coefficient were compared for structural materials with different cyclic and physical properties. For the 27 analyzed materials, the maximum level of strain hardening was predicted using the obtained calculated coefficient, and a good agreement with experimental data was demonstrated. Using the strain criterion for assessing durability, which includes the calculated non-proportional cyclic hardening coefficient, the durability for circular cyclic trajectories of non-proportional deformation was predicted on the basis of the basic uniaxial fatigue diagram. Satisfactory results of durability prediction (in comparison with the experiment) were obtained for materials with FCC metal lattice structure. For materials with BCC structure, the agreement between the calculated and experimental data was somewhat worse. It is shown that for this type of materials, the use of an alternative method for determining the non-proportional cyclic hardening coefficient can improve the results of durability prediction. |
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ISSN: | 0039-2316 1573-9325 |
DOI: | 10.1007/s11223-024-00646-4 |