应变梯度塑性的分数阶方法:超越离散位错的芯半径
A fractional approach to strain-gradient plasticity: beyond core-radius of discrete dislocations
AI总结:
该研究借助2023年提出的有限视界分数阶梯度构建半离散位错非局部模型,推导出无需芯半径的塑性应变梯度理论,证明重标度能量随α趋于0会Γ-收敛到2010年的宏观应变梯度模型。
摘要:
我们推导出一种塑性应变梯度理论,它是离散位错分数阶能量的$Γ$-极限,无需引入芯半径。借助Bellido、Cueto与Mora-Corral在2023年提出的有限视界分数阶梯度,我们构建了半离散位错的非局部模型,其中存储弹性能通过阶数为$1-α$的分数阶梯度计算。我们证明,当$α$趋于0时,经适当重标度的能量会$Γ$-收敛到Garroni、Leoni与Ponsiglione在2010年提出的宏观应变梯度模型。
英文摘要:
We derive a strain-gradient theory for plasticity as the $Γ$-limit of discrete dislocation fractional energies, without the introduction of a core-radius. By using the finite horizon fractional gradient introduced by Bellido, Cueto, and Mora-Corral of 2023, we consider a nonlocal model of semi-discrete dislocations, in which the stored elastic energy is computed via the fractional gradient of order $1-α$. As $α$ goes to $0$, we show that suitably rescaled energies $Γ$-converge to the macroscopic strain-gradient model of Garroni, Leoni, and Ponsiglione of 2010.
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