Kai-Shang Li

East China University of Science and Technology

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Shan‐Tung Tu

East China University of Science and Technology

Run‐Zi Wang

Tohoku University

Xiancheng Zhang

East China University of Science and Technology

Xian‐Cheng Zhang

Shaanxi University of Science and Technology

Jian Peng

Changzhou University

Lv‐Yi Cheng

East China University of Science and Technology

Shulei Yao

Second Hospital of Shanxi Medical University

Tiwen Lu

East China University of Science and Technology

Hang-Hang Gu

East China University of Science and Technology

Li Sun

University of Shanghai for Science and Technology

Cooperative Institutions

East China University of Science and Technology

Chinese Academy of Sciences

Tohoku University

Shanghai Jiao Tong University

Nanjing Tech University

Central South University

Changzhou University

Hunan University

Tsinghua University

Harbin Institute of Technology

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Collaborative improvement of macro-deformation and fatigue property for thin-walled parts in TA19 titanium alloy via a double-sided simultaneous ultrasonic surface rolling process

Journal of Materials Processing Technology (2024)

Lin Zhu Huayi Cheng Kaiming Zhang Chengcheng Zhang Changli Liu

Macro

Titanium alloy

10.1016/j.jmatprotec.2024.118616

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Citations (1)

Cavitation abrasive integrated waterjet peening process and the effect of process parameters on the surface integrity of TA19 titanium alloy

Surface and Coatings Technology (2022)

Shulei Yao Gongyu Wang Kai-Shang Li Ning Wang Chengcheng Zhang

Surface Integrity

Titanium alloy

Severe Plastic Deformation

Work hardening

10.1016/j.surfcoat.2022.128477

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Citations (21)

Fretting fatigue life improvement of nickel-based superalloy GH4169 dovetail slots by deflecting abrasive waterjet peening process

International Journal of Fatigue (2023)

Shulei Yao Xi-Ting Zeng Kai-Shang Li Ji Wang Run‐Zi Wang

Surface Integrity

10.1016/j.ijfatigue.2023.107832

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Citations (11)

Mechanical Behavior of 316L Stainless Steel after Strain Hardening

MATEC Web of Conferences (2017)

Kai-Shang Li Jian Peng Jian Peng

The effects of strain hardening on the mechanical behavior of 316L stainless steel were studied in the paper. The original and different strain hardening materials were compared to investigate the mechanical behavior. The results demonstrate that the yield strengths increase with the magnitude of strain hardening significantly, but the ultimate strengths of the original and different strain hardening materials are closed. In addition, the plastic parameters of 316L stainless steel including fracture elongation and fracture surface shrinkage decrease with the magnitude of strain hardening. Finally, the Ramberg-Osgood equation is used to predict the stress-strain curves after strain hardening, and the results indicate that the predicted values agree with the experimental values.

Strain hardening exponent

Hardening (computing)

Elongation

Shrinkage

10.1051/matecconf/201711402003

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Citations (12)

Life prediction and damage analysis of creep-fatigue combined with high-low cycle loading by using a crystal plasticity-based approach

International Journal of Fatigue (2022)

Kai-Shang Li Run‐Zi Wang Xu Le Chengcheng Zhang Xian‐Xi Xia

Crystal Plasticity

Low-cycle fatigue

Lüders band

Deformation mechanism

10.1016/j.ijfatigue.2022.107154

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Citations (16)

Lamellar aspect-ratio and thickness-dependent strength-ductility synergy in pure nickel during in-situ micro-tensile loading

Journal of Material Science and Technology (2023)

Zi-Meng Wang Yun-Fei Jia Kai-Shang Li Yong Zhang Jia-Dong Cai

Ductility (Earth science)

Stacking-fault energy

Deformation mechanism

Grain boundary strengthening

10.1016/j.jmst.2023.01.037

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Citations (6)

Dislocation-based crystal plasticity modelling of a nickel-based superalloy under dwell-fatigue: From life prediction to residual life assessment

International Journal of Fatigue (2021)

Kai-Shang Li Run‐Zi Wang Lv‐Yi Cheng Tiwen Lu Xiancheng Zhang

Dwell time

Crystal Plasticity

Robustness

Low-cycle fatigue

10.1016/j.ijfatigue.2021.106569

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Citations (14)

A life prediction method and damage assessment for creep-fatigue combined with high-low cyclic loading

International Journal of Fatigue (2022)

Kai-Shang Li Ji Wang Zhichao Fan Lv‐Yi Cheng Shulei Yao

Failure assessment

Inconel

Low-cycle fatigue

10.1016/j.ijfatigue.2022.106923

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Citations (25)

The Application of Modified Artificial Neural Network on Tensile Behaviour of 316L Austenitic Stainless Steel

MATEC Web of Conferences (2017)

Jian Peng Jian Peng Kai-Shang Li

In this paper, genetic algorithm (GA) was used to enhance the accuracy of back propagation artificial neural network (ANN) for the tensile behaviour of 316L. With GA optimization, the random weight and threshold between different layers in original ANN model can be updated constantly to describe the characteristics of 316L austenitic stainless steel accurately, just considering the nodes of hidden layer. According to the sample distribution, the data were divided into training and test. When the model was set to predict test data, the results showed coincident with the experimental ones, and errors of the data between prediction and experiment displayed the small values at room and intermediate temperatures.

Austenitic stainless steel

Backpropagation

10.1051/matecconf/201711402004

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Citations (0)

Data-driven fatigue life prediction of small-deep holes in a nickel-based superalloy after a cold expansion process

International Journal of Fatigue (2024)

Chao-Zong Tang Hongwei Li Kai-Shang Li Xuelin Lei Lv‐Yi Cheng

10.1016/j.ijfatigue.2024.108159

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Citations (11)