Simulating shot peening based on a dislocation density-based model with a novel time integration algorithm

被引:0
|
作者
Ren, Feihu [1 ]
Zhao, Minghao [1 ,2 ,4 ]
Lu, Chunsheng [3 ]
Zhang, Jianwei [2 ,4 ]
Wang, Bingbing [2 ,4 ]
机构
[1] Zhengzhou Univ, Sch Mech Engn, Zhengzhou 450001, Henan, Peoples R China
[2] Zhengzhou Univ, Sch Mech & Safety Engn, Zhengzhou 450001, Henan, Peoples R China
[3] Curtin Univ, Sch Civil & Mech Engn, Perth, WA 6845, Australia
[4] Henan Prov Ind Sci &Technol Inst Antifatigue Mfg, Zhengzhou 450016, Henan, Peoples R China
基金
中国国家自然科学基金;
关键词
Shot peening; Dislocation density; Time integration algorithm; Grain refinement; Finite element simulation; RANGE INTERNAL-STRESSES; GRAIN-REFINEMENT; SURFACE NANOCRYSTALLIZATION; DEFORMATION-BEHAVIOR; FATIGUE BEHAVIOR; RESIDUAL-STRESS; STAINLESS-STEEL; ALUMINUM; FLOW; PREDICTION;
D O I
10.1016/j.ijsolstr.2024.112823
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
Shot peening has been widely used in processing various components since it can bring in residual compressive stress and effectively refine the grain size of impacted area. To simulate grain refinement induced by shot peening, the dislocation density-based model has recently been introduced, however, the existing time integration algorithm is not stable and usually leads to divergent solutions in iterations. In this paper, a novel time integration algorithm is proposed for the dislocation density-based model. Based upon the algorithm, numerical studies on multi-shot AISI4340 steel are carried out with different coverages, velocities, shot diameters, and peening angles. It is shown that the method converges faster than the two-level iteration method, and the predicted dislocation cell structure sizes after shooting are consistent with experimental results. Besides that, increasing coverage can refine the size of a dislocation cell, which is closely dependent on the shot diameter, impact velocity, and angle. Thus, to achieve the desired grain size or the depth of refinement, it is necessary to take the shot diameter and velocity into account simultaneously.
引用
收藏
页数:12
相关论文
共 50 条
  • [21] A novel density-based clustering algorithm using nearest neighbor graph
    Li, Hao
    Liu, Xiaojie
    Li, Tao
    Gan, Rundong
    PATTERN RECOGNITION, 2020, 102
  • [22] A novel density-based neural mass model for simulating neuronal network dynamics with conductance-based synapses and membrane current adaptation
    Huang, Chih-Hsu
    Lin, Chou-Ching K.
    NEURAL NETWORKS, 2021, 143 : 183 - 197
  • [23] A novel unified dislocation density-based model for hot deformation behavior of a nickel-based superalloy under dynamic recrystallization conditions
    Lin, Y. C.
    Wen, Dong-Xu
    Chen, Ming-Song
    Chen, Xiao-Min
    APPLIED PHYSICS A-MATERIALS SCIENCE & PROCESSING, 2016, 122 (09):
  • [24] A novel unified dislocation density-based model for hot deformation behavior of a nickel-based superalloy under dynamic recrystallization conditions
    Y. C. Lin
    Dong-Xu Wen
    Ming-Song Chen
    Xiao-Min Chen
    Applied Physics A, 2016, 122
  • [25] Explicit incorporation of cross-slip in a dislocation density-based crystal plasticity model
    Alankar, Alankar
    Field, David P.
    Zbib, Hussein M.
    PHILOSOPHICAL MAGAZINE, 2012, 92 (24) : 3084 - 3100
  • [26] A dislocation density-based model for the work hardening and softening behaviors upon stress reversal
    Lisiecka-Graca, Paulina
    Bzowski, Krzysztof
    Majta, Janusz
    Muszka, Krzysztof
    ARCHIVES OF CIVIL AND MECHANICAL ENGINEERING, 2021, 21 (02)
  • [27] Cell structure formation in a two-dimensional density-based dislocation dynamics model
    Ronghai Wu
    Michael Zaiser
    Materials Theory, 5 (1):
  • [28] Application of a Dislocation Density-Based Constitutive Model to Al-Alloyed TWIP Steel
    Jinkyung Kim
    Yuri Estrin
    Bruno Charles De Cooman
    Metallurgical and Materials Transactions A, 2013, 44 : 4168 - 4182
  • [29] An Efficient Density-Based Algorithm for Data Clustering
    Theljani, Foued
    Laabidi, Kaouther
    Zidi, Salah
    Ksouri, Moufida
    INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS, 2017, 26 (04)
  • [30] DENGRAPH: A density-based community detection algorithm
    Falkowski, Tanja
    Barth, Anja
    Spiliopoulou, Myra
    PROCEEDINGS OF THE IEEE/WIC/ACM INTERNATIONAL CONFERENCE ON WEB INTELLIGENCE: WI 2007, 2007, : 112 - 115