دورية أكاديمية

Modification of the Reloading Plastic Modulus in Generalized Plasticity Models for Soil by Introducing a New Equation for the Memory Parameter in Cyclic Loadings.

التفاصيل البيبلوغرافية
العنوان: Modification of the Reloading Plastic Modulus in Generalized Plasticity Models for Soil by Introducing a New Equation for the Memory Parameter in Cyclic Loadings.
المؤلفون: Oliaei, Mohammad, Kamgar, Reza, Heidarzadeh, Heisam, Jankowski, Robert
المصدر: Applied Sciences (2076-3417); Jun2024, Vol. 14 Issue 11, p4418, 15p
مصطلحات موضوعية: CYCLIC loads, COMPUTER equipment, PLASTICS, SOILS, COMPUTATION laboratories, SHAPE memory alloys
مستخلص: Nowadays, with the widespread supply of very powerful laboratory and computer equipment, it is expected that the analyses conducted for geotechnical problems are carried out with very high precision. Precise analyses lead to better knowledge of structures' behavior, which, in turn, reduces the costs related to uncertainty of materials' behavior. A precise analysis necessitates a precise knowledge and definition of the behavior of the constituent materials, which itself requires applying an appropriate constitutive model to show the behavior of materials. Constitutive models used in the generalized plasticity framework are very powerful constitutive models for the simulation of sand behavior. However, the simulation of a cyclic behavior in these models, especially the simulation of the undrained cyclic behavior, is not well-recognized. In this study, in order to eliminate the weakness of generalized constitutive models under cyclic loading, a new equation is presented to substitute the so-called coefficient of the discrete memory factor to consider the loading history in such a way that the plastic modulus is modified during reloading and, as a result, more appropriate predictions of sand behavior are obtained. The performance accuracy of the proposed coefficient was evaluated in accordance with the experimental data. Finally, the results show that after using the modification of the loading history coefficient, predictions of the constitutive model are significantly improved. [ABSTRACT FROM AUTHOR]
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قاعدة البيانات: Complementary Index
الوصف
تدمد:20763417
DOI:10.3390/app14114418