COMPUTATIONAL STUDY ON MICROSTRUCTURE-SENSITIVE HIGH CYCLE FATIGUE DISPERSIVITY

Abstract

Empirical approaches to characterize the variability of high cycle fatigue have been widely used. However, little is understood about the intrinsic relationship of randomness of microstructure attributes on the overall variability in high cycle fatigue. The ability of quantifying the dispersivity of high cycle fatigue with physics based computational methods has great potential in design of minimum life and can aid in the improvement of fatigue resistance. To investigate the effects between microstructure attributes and high cycle fatigue dispersivity, the microstructure-sensitive extreme value probabilistic framework is introduced. First, the Voronoi algorithm is used to construct random polycrystalline microstructure representative volume elements. Different kinds of periodic boundary conditions are proposed to simulate the interior and surface constraints in polycrystalline microstructure representative volume elements. Then mechanical responses of both interior and surface microstructure representative volume elements under different strain amplitudes are simulated by internal state variable based crystal plasticity. The fatigue indicator parameter is introduced to characterize the driving force for fatigue crack formation dominated by maximum shear plastic strain amplitude. By computing a limited number of random polycrystalline microstructure representative volume elements, the distributions of fatigue indicator parameter under different strain amplitudes are obtained and analyzed with extreme value probability theory. The study with a kind of titanium alloy with material grade TC4 supports that the high cycle fatigue dispersivity increases with the decrease of the strain *国家重点基础研究发展计划资助项目2015CB057400 收到初稿日期: 2015-06-23,收到修改稿日期: 2015-12-01 作者简介:韩世伟,男, 1987年生,博士生 DOI: 10.11900/0412.1961.2015.00322 第289-297页 pp.289-297