Fatigue life prediction of aluminum alloy via knowledge-based machine learning

Machine learning‐based genetic feature identification and fatigue life prediction

(2021) Kun Zhou et al.   FATIGUE & FRACTURE OF ENGINEERING MATERIALS & STRUCTURES

Residual stress effects on fatigue life prediction using hardness measurements for butt-welded joints made of high strength steels

(2021) Haohui Xin et al.   INTERNATIONAL JOURNAL OF FATIGUE

A novel method of multiaxial fatigue life prediction based on deep learning

(2021) Jingye Yang et al.   INTERNATIONAL JOURNAL OF FATIGUE

Machine learning-based predictions of fatigue life and fatigue limit for steels

(2021) Lei He et al.   JOURNAL OF MATERIALS SCIENCE & TECHNOLOGY

Using machine learning and feature engineering to characterize limited material datasets of high-entropy alloys

(2020) Dongbo Dai et al.   COMPUTATIONAL MATERIALS SCIENCE

Pore-affected fatigue life scattering and prediction of additively manufactured Inconel 718: An investigation based on miniature specimen testing and machine learning approach

(2020) Y.W. Luo et al.   MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING

A machine-learning fatigue life prediction approach of additively manufactured metals

(2020) Hongyixi Bao et al.   ENGINEERING FRACTURE MECHANICS

Determination of fatigue life for low probability of failure for different stress levels using 3-parameter Weibull distribution

(2020) Przemysław Strzelecki   INTERNATIONAL JOURNAL OF FATIGUE

Deep materials informatics: Applications of deep learning in materials science

(2019) Ankit Agrawal et al.   MRS Communications

Effect of Zr on the high cycle fatigue and mechanical properties of Al–Si–Cu–Mg alloys at elevated temperatures

(2019) Guangyu Liu et al.   JOURNAL OF ALLOYS AND COMPOUNDS

Fatigue behavior of 2618-T851 aluminum alloy under uniaxial and multiaxial loadings

(2019) Benaïssa Malek et al.   INTERNATIONAL JOURNAL OF FATIGUE

An online tool for predicting fatigue strength of steel alloys based on ensemble data mining

(2018) Ankit Agrawal et al.   INTERNATIONAL JOURNAL OF FATIGUE

Design of high-entropy alloys with a single solid-solution phase: Average properties vs. their variances

(2018) Yiming Tan et al.   JOURNAL OF ALLOYS AND COMPOUNDS

A strategy to apply machine learning to small datasets in materials science

(2018) Ying Zhang et al.   npj Computational Materials

A probabilistic Stüssi function for modelling the S-N curves and its application on specimens made of steel S355J2+N

(2018) Paul Dario Toasa Caiza et al.   INTERNATIONAL JOURNAL OF FATIGUE

Fatigue damage evolution and lifetime prediction of welded joints with the consideration of residual stresses and porosity

(2017) Fei Shen et al.   INTERNATIONAL JOURNAL OF FATIGUE

Fatigue behavior of high-entropy alloys: A review

(2017) PeiYong Chen et al.   Science China-Technological Sciences

Microstructural characterization and high cycle fatigue behavior of investment cast A357 aluminum alloy

(2015) S. Dezecot et al.   INTERNATIONAL JOURNAL OF FATIGUE

Effect of humidity on porosity, microstructure, and fatigue strength of A7N01S-T5 aluminum alloy welded joints in high-speed trains

(2015) G. Gou et al.   MATERIALS & DESIGN

Fatigue of 2024-T351 aluminium alloy at different load ratios up to 1010 cycles

(2012) H. Mayer et al.   INTERNATIONAL JOURNAL OF FATIGUE

High cycle fatigue strength of permanent mold and rheocast aluminum 357 alloy

(2010) Myriam Brochu et al.   INTERNATIONAL JOURNAL OF FATIGUE

A Survey on Transfer Learning

(2009) Sinno Jialin Pan et al.   IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING

Fatigue life scatter in 7xxx series aluminum alloys

(2009) D.L. DuQuesnay et al.   INTERNATIONAL JOURNAL OF FATIGUE

Comparison of genetic programming with conventional methods for fatigue life modeling of FRP composite materials

(2007) A VASSILOPOULOS et al.   INTERNATIONAL JOURNAL OF FATIGUE