Artificial intelligence modeling of ultrasonic fatigue test to predict the temperature increase

Machine learning based very-high-cycle fatigue life prediction of Ti-6Al-4V alloy fabricated by selective laser melting

(2022) Jun Li et al.   INTERNATIONAL JOURNAL OF FATIGUE

Prediction and analysis of train arrival delay based on XGBoost and Bayesian optimization

(2021) Rui Shi et al.   APPLIED SOFT COMPUTING

Machine-learning-based investigation into the effect of defect/inclusion on fatigue behavior in steels

(2021) Lei He 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

Failure mode and effects analysis of RC members based on machine-learning-based SHapley Additive exPlanations (SHAP) approach

(2020) Sujith Mangalathu et al.   ENGINEERING STRUCTURES

Prediction of Fatigue Crack Growth Behaviour in Ultrafine Grained Al 2014 Alloy Using Machine Learning

(2020) Allavikutty Raja et al.   Metals

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

Machine-learning-assisted discovery of polymers with high thermal conductivity using a molecular design algorithm

(2019) Stephen Wu et al.   npj Computational Materials

Fault Diagnosis Method for Hydraulic Directional Valves Integrating PCA and XGBoost

(2019) Yafei Lei et al.   Processes

A review about the effects of structural and operational factors on the gigacycle fatigue of steels

(2018) D. Jeddi et al.   FATIGUE & FRACTURE OF ENGINEERING MATERIALS & STRUCTURES

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

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

Accelerating the discovery of materials for clean energy in the era of smart automation

(2018) Daniel P. Tabor et al.   Nature Reviews Materials

Fulfilling the promise of the materials genome initiative with high-throughput experimental methodologies

(2017) M. L. Green et al.   Applied Physics Reviews

Analysis of temperature and fracture surface of AISI4140 steel in very high cycle fatigue regime

(2015) V. Crupi et al.   THEORETICAL AND APPLIED FRACTURE MECHANICS

Explaining prediction models and individual predictions with feature contributions

(2013) Erik Štrumbelj et al.   KNOWLEDGE AND INFORMATION SYSTEMS

The effect of frequency on the giga-cycle fatigue properties of a Ti-6Al-4V alloy

(2008) E. TAKEUCHI et al.   FATIGUE & FRACTURE OF ENGINEERING MATERIALS & STRUCTURES