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Peng Yue
Institutions:
Xihua University,
University of Electronic Science and Technology of China,
Jiangsu University of Science and Technology
Observed institutions:
Xihua University,
Nanjing Tech University,
Xidian University,
University of Electronic Science and Technology of China,
Jiangsu University of Science and Technology,
University of Technology Malaysia
show all 6
ORCID:
0000-0003-0750-4458
Observed ORCID:
0000-0003-0750-4458
OpenAlex ID:
A5019314238
A Combined High and Low Cycle Fatigue Model for Life Prediction of Turbine Blades
2017
·
Shun-Peng Zhu
, Peng Yue
, et al.
·
Materials
·
131
PDF
A fatigue damage accumulation model for reliability analysis of engine components under combined cycle loadings
2020
·
Peng Yue
, Juan Ma
, et al.
·
Fatigue & Fracture of Engineering Materials & Structures
·
84
Threshold damage-based fatigue life prediction of turbine blades under combined high and low cycle fatigue
2021
·
Peng Yue
, Juan Ma
, et al.
·
International Journal of Fatigue
·
66
Dynamic fatigue reliability analysis of turbine blades under combined high and low cycle loadings
2021
·
Peng Yue
, Juan Ma
, et al.
·
International Journal of Damage Mechanics
·
30
Strain energy-based fatigue life prediction under variable amplitude loadings
2018
·
Shun‐Peng Zhu
, Peng Yue
, et al.
·
Consultation of the Doctoral Thesis Database (TESEO) (Ministerio de Educación, Cultura y Deporte)
·
25
Probabilistic framework for reliability analysis of gas turbine blades under combined loading conditions
2023
·
Peng Yue
, Juan Ma
, et al.
·
Structures
·
23
A modified nonlinear cumulative damage model for combined high and low cycle fatigue life prediction
2024
·
Peng Yue
, He Li
, et al.
·
Fatigue & Fracture of Engineering Materials & Structures
·
20
A particle swarm optimization-physical information neural network for combined high and low cycle fatigue life prediction
2025
·
Hui Zhao
, Peng Yue
, et al.
·
Computational Materials Science
·
8
A comparative study on combined high and low cycle fatigue life prediction model considering loading interaction
2024
·
Peng Yue
, Changyu Zhou
, et al.
·
International Journal of Damage Mechanics
·
7
A Nonlinear Combined High and Low Cycle Fatigue Model for Life Prediction Considering Loading Interaction
2025
·
Yuxuan Wang
, Peng Yue
, et al.
·
Fatigue & Fracture of Engineering Materials & Structures
·
6
A novel PHDAL-MCDNN framework for reliability assessment of turbine blades under combined high and low cycle fatigue
2026
·
Peng Yue
, Yuan Wei
, et al.
·
Aerospace Science and Technology
·
5
A Modified Cumulative Damage Model for Fatigue Life Prediction under Variable Amplitude Loadings
2016
·
Peng Yue
, Qiang Lei
, et al.
·
Applied Mechanics and Materials
·
5
Reliability‐Based CCF Damage Analysis for Gas Turbine Blade With Thermal Barrier Coatings
2025
·
Changping Dai
, Peng Yue
, et al.
·
Fatigue & Fracture of Engineering Materials & Structures
·
3
An Efficient Reliability Method with Multiple Shape Parameters Based on Radial Basis Function
2022
·
Wenyi Du
, Juan Ma
, et al.
·
Applied Sciences
·
3
PDF
A New Approach for Fatigue Reliability Analysis of Thin-Walled Structures with DC-ILSSVR
2021
·
Wenyi Du
, Juan Ma
, et al.
·
Materials
·
1
PDF
Dynamic Reliability Analysis of Turbine Blades Under Combined High and Low Cycle Loadings
2021
·
Peng Yue
, Bi-Sen Bai
, et al.
·
Computational Research Progress in Applied Science and Engineering
·
1
PDF
Mean Stress and Ratcheting Corrections in Fatigue Life Prediction of Metals
2016
·
Qiang Lei
, Peng Yue
, et al.
·
Applied Mechanics and Materials
·
1
Dynamic characteristics of ship composite shaft with early-stage damage based on the CUF theory and experiment
2026
·
Junchao Zhu
, Yifan Wang
, et al.
·
Marine Structures
Reliability Analysis of TPMS Structures Considering Uncertainties in Operating Conditions
2026
·
Peng Yue
, Yunlong Zhao
, et al.
·
Fatigue & Fracture of Engineering Materials & Structures
PDF
Combined high and low cycle fatigue life prediction method based on adaptive physical information neural network
2026
·
Peng Yue
, Hui Zhao
, et al.
·
SSRN Electronic Journal
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Works count:
20
Citation count:
419
H-index:
8
I10-index:
7
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