The Definition of Atomic Scale Strain and Its Application in Identifying the Evolution of Microdefects

  • Ying SHENG ,
  • Bin JIA ,
  • Ruheng WANG ,
  • Guoping CHEN
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  • 1 Shock and Vibration of Engineering Materials and Structures Key Laboratory of Sichuan Province, Southwest University of Science and Technology, Mianyang 621010, China
    2 School of Civil Engineering and Architecture, Southwest University of Science and Technology, Mianyang 621010, China

Received date: 2019-10-15

  Revised date: 2020-03-03

  Online published: 2020-04-30

Supported by

Doctor Foundation in Southwest University of Science and Technology(17zx7149);Open Foundation of Shock and Vibration of Engineering Materials and Structures Key Laboratory of Sichuan Province(18kfgk12)

Abstract

The strain tensors are commonly defined by the local deformation of continuum. Unlike displacement, strain is not a physical quantity that can be measured directly, and it is calculated from a definition that relies on the gradient of the continuous displacement field. At the microscale, it is difficult to define the local deformation according to the position of each atom which is obtained from the adjacent discrete time interval, so there is no universally accepted definition of strain tensors of atomic scale so far, and none of the molecular dynamics software can be used to calculate the atomic strain until now. In order to define the atomic scale strain, a method for calculating the "deformation" both in the atomic scale and the continuum scale is proposed. In the definition, the discrete deformation gradient is proposed to describe the "deformation" in the atomic scale and the influence weight function of neighborhood atom is introduced. Then the weighted least squares error optimization model is established to seek the optimal coefficients of the weight function and the optimal local deformation gradient of each atom. After that, the advanced multilayer complex genetic algorithm can be used to calculate the atomic strain. Finally, take NiTi alloy as an example, the molecular dynamics evolution model of deformation and failure of NiTi alloy was established. Then the atomic scale strain nephogram at each time was calculated, and the microdefects such as twins were observed by strain nephogram. Compared with the micro-observation experiment of crack tip of NiTi alloy for three-point bending, the rationality of the atomic scale strain definition method established in this study and its application significance in identifying the evolution of microdefects are verified.

Cite this article

Ying SHENG , Bin JIA , Ruheng WANG , Guoping CHEN . The Definition of Atomic Scale Strain and Its Application in Identifying the Evolution of Microdefects[J]. Acta Metall Sin, 2020 , 56(8) : 1144 -1154 . DOI: 10.11900/0412.1961.2019.00343

References

[1] Subramaniyan A K, Sun C T. Continuum interpretation of virial stress in molecular simulations [J]. Int. J. Solids Struct., 2008, 45: 4340
[2] Zimmerman J A, Webb E B, Hoyt J J, et al. Calculation of stress in atomistic simulation [J]. Modell. Simul. Mater. Sci. Eng., 2004, 12: 319
[3] Cormier J, Rickman J M, Delph T J. Stress calculation in atomistic simulations of perfect and imperfect solids [J]. J. Appl. Phys., 2001, 89: 99
[4] Zhou M. A new look at the atomic level virial stress: On continuum-molecular system equivalence [J]. Proc. R. Soc., 2003, 459A: 2347
[5] Liu B, Qiu X M. How to compute the atomic stress objectively? [J]. J. Comput. Theor. Nanosci., 2009, 6: 1081
[6] Xu R, Liu B. Investigation on applicability of various stress definitions in atomistic simulation [J]. Acta Mech. Solida Sin., 2009, 22: 644
[7] Wang Y C, Wu C Y, Chu J P, et al. Indentation behavior of Zr-based metallic-glass films via molecular-dynamics simulations [J]. Metall. Mater. Trans., 2010, 41A: 3010
[8] Hirth J P, Lothe J. Theory of dislocations (2nd Ed.,) [J]. J. Appl. Mech., 1983, 50: 476
[9] Seol J B, Kim J G, Na S H, et al. Deformation rate controls atomic-scale dynamic strain aging and phase transformation in high Mn TRIP steels [J]. Acta Mater., 2017, 131: 187
[10] Zimmerman J A, Bammann D J, Gao H J. Deformation gradients for continuum mechanical analysis of atomistic simulations [J]. Int. J. Solids Struct., 2009, 46: 238
[11] Mott P H, Argon A S, Suter U W. The atomic strain tensor [J]. J. Comput. Phys., 1992, 101: 140
[12] Falk M L. Molecular-dynamics study of ductile and brittle fracture in model noncrystalline solids [J]. Phys. Rev., 1999, 60B: 7062
[13] Kim H, Meng Y F, Rouviére J L, et al. Peak separation method for sub-lattice strain analysis at atomic resolution: Application to InAs/GaSb superlattice [J]. Micron, 2017, 92: 6
[14] Gullett P M, Horstemeyer M F, Baskes M I, et al. A deformation gradient tensor and strain tensors for atomistic simulations [J]. Modell. Simul. Mater. Sci. Eng., 2008, 16: 015001
[15] Quyen T N T. Variational method for multiple parameter identification in elliptic PDEs [J]. J. Math. Anal. Appl., 2018, 461: 676
[16] Sheng Y, Zeng X G, Chen H Y, et al. Identification of target parameters and experimental verification for dislocation-mechanics-based constitutive relations of titanium alloy [J]. J. Sichuan Univ. (Eng. Sci. Ed.), 2015, 47(6): 69
[16] (盛 鹰, 曾祥国, 陈华燕等. 基于位错机制钛合金本构关系的目标参数识别及实验验证 [J]. 四川大学学报(工程科学版), 2015, 47(6): 69)
[17] Kramer O. Genetic Algorithm Essentials [M]. Cham: Springer, 2017: 1
[18] Mei Y, Sun Q L, Yu L H, et al. Grain size prediction of aluminum alloy dies castings based on GA-ELM [J]. Acta Metall. Sin., 2017, 53: 1125
[18] (梅 益, 孙全龙, 喻丽华等. 基于GA-ELM的铝合金压铸件晶粒尺寸预测 [J]. 金属学报, 2017, 53: 1125)
[19] Bradford E, Schweidtmann A M, Lapkin A. Correction to: Efficient multiobjective optimization employing Gaussian processes, spectral sampling and a genetic algorithm [J]. J. Global Optim., 2018, 71: 407
[20] Yu B S, Wang S L, Yang T, et al. BP neural netwok constitutive model based on optimization with genetic algorithm for SMA [J]. Acta Metall. Sin., 2017, 53: 248
[20] (余滨杉, 王社良, 杨 涛等. 基于遗传算法优化的SMABP神经网络本构模型 [J]. 金属学报, 2017, 53: 248)
[21] Qian W W, Chai J R. Clustering genetic algorithm based on complex method [J]. Comput. Eng. Appl., 2017, 53(3): 87
[21] (钱武文, 柴军瑞. 基于复合形法的聚类遗传算法 [J]. 计算机工程与应用, 2017, 53(3): 87)
[22] Sheng Y, Zeng X G, Chen G P, et al. Application of multilayer complex genetic algorithm in parameters identification of titanium alloy dynamic constitutive model [J]. J. Chengdu Univ. (Nat. Sci.), 2018, 37: 242
[22] (盛 鹰, 曾祥国, 陈国平等. 自适应多层复形遗传算法在钛合金动态本构模型参数识别中的应用 [J]. 成都大学学报(自然科学版), 2018, 37: 242)
[23] Luo J F, Mao S C, Han X D, et al. High-cycle fatigue mechanisms of a NiTi shape memory alloy under different mean strains [J]. Mater. Sci. Forum, 2009, 610-613: 1120
[24] Wei Z Z, Ma X, Zhang X P. Topological modelling of the B2-B19' martensite transformation crystallography in NiTi alloy [J]. Acta Metall. Sin., 2018, 54: 1461
[24] (韦昭召, 马 骁, 张新平. NiTi合金B2-B19'马氏体相变晶体学的拓扑模拟研究 [J]. 金属学报, 2018, 54: 1461)
[25] Krishnan M, Singh J B. A novel B19' martensite in nickel titanium shape memory alloys [J]. Acta Mater., 2000, 48: 1325
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