Reduced-order microstructure-sensitive protocols to rank-order the transition fatigue resistance of polycrystalline microstructures

被引:33
作者
Paulson, Noah H. [1 ]
Priddy, Matthew W. [2 ]
McDowell, David L. [3 ,4 ]
Kalidindi, Surya R. [3 ,5 ]
机构
[1] Argonne Natl Lab, 9700 S Cass Ave, Argonne, IL 60439 USA
[2] Mississippi State Univ, Dept Mech Engn, Mississippi State, MS 39762 USA
[3] Georgia Inst Technol, George W Woodruff Sch Mech Engn, Atlanta, GA 30332 USA
[4] Georgia Inst Technol, Sch Mat Sci & Engn, Atlanta, GA 30332 USA
[5] Georgia Inst Technol, Sch Computat Sci & Engn, Atlanta, GA 30332 USA
基金
美国国家科学基金会;
关键词
2-point correlations; Extreme value statistics; Structure-property relationship; Crystal plasticity; Fatigue; STRUCTURE-PROPERTY LINKAGES; SCIENCE APPROACH APPLICATION; ELASTIC LOCALIZATION; PLASTICITY SIMULATIONS; TEXTURE; SLIP; DEFORMATION; CALIBRATION; STRATEGIES; FRAMEWORK;
D O I
10.1016/j.ijfatigue.2018.09.011
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
The transition fatigue regime between low cycle fatigue (LCF) and high cycle fatigue (HCF) is often addressed in the design and performance evaluation of load-bearing components used in many structural applications. Transition fatigue is characterized by elevated levels of local inelastic deformation in significant regions of the microstructure as compared to HCF. Typically, crystal plasticity finite element method (CPFEM) simulations are performed to model this phenomenon and to rank-order microstructures by their resistance to crack formation and early growth in the regime of transition fatigue. Unfortunately, these approaches require significant computational resources, inhibiting their use to explore novel materials for transition fatigue resistance. Reduced-order, microstructure-sensitive models are needed to accelerate the search for next-generation, fatigue-resistant materials. In a recent study, Paulson et al. (2018) extended the materials knowledge system (MKS) framework for rank-ordering the HCF resistance of polycrystalline microstructures. The efficacy of this approach lies in the reduced-dimensional representation of microstructures through 2-point spatial correlations and principal component analysis (PCA), in addition to the characterization of the HCF response with a small set of performance measures. In this work, these same protocols are critically evaluated for their applicability to rank-order the transition fatigue resistance of the same class of polycrystalline microstructures subjected to increased strain amplitudes. Success in this endeavor requires the formation of homogenization linkages that account for the significantly higher levels of local inelastic deformation and stress redistribution in transition fatigue as compared to HCF. A set of 12 alpha-titanium microstructures generated using the open access DREAM.3D software (Groeber and Jackson, 2014) are employed for this evaluation.
引用
收藏
页码:1 / 10
页数:10
相关论文
共 61 条
[1]  
Adams B.L., 2012, Microstructure sensitive design for performance optimization
[2]  
[Anonymous], 1986, MONOGR STAT APPL PRO
[3]  
[Anonymous], THESIS
[4]  
[Anonymous], 1982, Texture Analysis in Materials Science: Mathematical Methods
[5]  
Beran MarkJ., 1968, American Journal of Physics, V36, P923, DOI [10.1119/1.1974326, DOI 10.1119/1.1974326]
[6]  
Bergstra J, 2012, J MACH LEARN RES, V13, P281
[7]   Slip and fatigue crack formation processes in an α/β titanium alloy in relation to crystallographic texture on different scales [J].
Bridier, F. ;
Villechaise, P. ;
Mendez, J. .
ACTA MATERIALIA, 2008, 56 (15) :3951-3962
[8]   Microstructure-based knowledge systems for capturing process-structure evolution linkages [J].
Brough, David B. ;
Wheeler, Daniel ;
Warren, James A. ;
Kalidindi, Surya R. .
CURRENT OPINION IN SOLID STATE & MATERIALS SCIENCE, 2017, 21 (03) :129-140
[9]  
Broughton D, 2017, INTEGRATING MAT MANU, P1
[10]   SOLID MIXTURE PERMITTIVITIES [J].
BROWN, WF .
JOURNAL OF CHEMICAL PHYSICS, 1955, 23 (08) :1514-1517