Jie Chen
Jie Chen
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Equivalent surface defect model for fatigue life prediction of steel reinforcing bars with pitting corrosion
J Chen, B Diao, J He, S Pang, X Guan
International Journal of Fatigue 110, 153-161, 2018
Probabilistic physics-guided machine learning for fatigue data analysis
J Chen, Y Liu
Expert Systems with Applications 168, 114316, 2021
Uncertainty quantification of fatigue SN curves with sparse data using hierarchical Bayesian data augmentation
J Chen, S Liu, W Zhang, Y Liu
International Journal of Fatigue 134, 105511, 2020
Multiaxial high-cycle fatigue life prediction under random spectrum loadings
H Wei, P Carrion, J Chen, A Imanian, N Shamsaei, N Iyyer, Y Liu
International Journal of Fatigue 134, 105462, 2020
Lifetime distribution selection for complete and censored multi-level testing data and its influence on probability of failure estimates
J He, J Chen, X Guan
Structural and Multidisciplinary Optimization 62 (1), 1-17, 2020
Fatigue modeling using neural networks: A comprehensive review
J Chen, Y Liu
Fatigue & Fracture of Engineering Materials & Structures 45 (4), 945-979, 2022
Fatigue property prediction of additively manufactured Ti-6Al-4V using probabilistic physics-guided learning
J Chen, Y Liu
Additive Manufacturing 39, 101876, 2021
Piecewise stochastic rainflow counting for probabilistic linear and nonlinear damage accumulation considering loading and material uncertainties
J Chen, A Imanian, H Wei, N Iyyer, Y Liu
International Journal of Fatigue 140, 105842, 2020
Uncertainty quantification of fatigue properties with sparse data using hierarchical Bayesian model
J Chen, Y Liu
AIAA Scitech 2020 Forum, 0680, 2020
Thermal conductivity of metal coated polymer foam: Integrated experimental and modeling study
R Dai, G Chandrasekaran, J Chen, C Jackson, Y Liu, Q Nian, B Kwon
International Journal of Thermal Sciences 169, 107045, 2021
Data-driven sensitivity analysis for static mechanical properties of additively manufactured Ti–6Al–4V
A Sharma, J Chen, E Diewald, A Imanian, J Beuth, Y Liu
ASCE-ASME J Risk and Uncert in Engrg Sys Part B Mech Engrg 8 (1), 2022
Probabilistic bulk property estimation using multimodality surface non-destructive measurements for vintage pipes
J Chen, D Ersoy, Y Liu
Structural Safety 87, 101995, 2020
Physics-guided machine learning for multi-factor fatigue analysis and uncertainty quantification
J Chen, Y Liu
AIAA Scitech 2021 Forum, 1242, 2021
Multimodality data fusion for probabilistic strength estimation of aging materials using Bayesian networks
J Chen, Y Liu
AIAA Scitech 2020 Forum, 1653, 2020
Multi-fidelity Data Aggregation using Convolutional Neural Networks
J Chen, Y Gao, Y Liu
Computer Methods in Applied Mechanics and Engineering 391, 114490, 2022
Bayesian Information Fusion of Multmodality Nondestructive Measurements for Probabilistic Mechanical Property Estimation
J Chen, Y Liu
ASME International Mechanical Engineering Congress and Exposition 84669 …, 2020
Multimodality information fusion for aging pipe strength and toughness estimation using Bayesian networks
J Chen, Y Liu
11th Annual Conference of the Prognostics and Health Management Society, PHM …, 2019
Probabilistic Aging Pipe Strength Estimation Using Multimodality Information Fusion
J Chen, Y Liu
Annual Conference of the PHM Society 11 (1), 2019
Neural Optimization Machine: A Neural Network Approach for Optimization
J Chen, Y Liu
arXiv preprint arXiv:2208.03897, 2022
Subcycle fatigue crack growth and equivalent initial flaw size model for fatigue life assessment under arbitrary loadings for Al-7075
S Shivankar, J Chen, Y Liu
International Journal of Fatigue 156, 106685, 2022
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