The potency of defects on fatigue of additively manufactured metals

A physics-informed machine learning model for porosity analysis in laser powder bed fusion additive manufacturing

(2021) Rui Liu et al.   The International Journal of Advanced Manufacturing Technology

Fatigue life evaluation of Ti–6Al–4V welded joints manufactured by electron beam melting

(2021) Yanan Hu et al.   FATIGUE & FRACTURE OF ENGINEERING MATERIALS & STRUCTURES

The effect of defect population on anisotropic fatigue resistance of selective laser melted AlSi10Mg alloy

(2021) Z.K. Wu et al.   INTERNATIONAL JOURNAL OF FATIGUE

Essential structure of S-N curve: Prediction of fatigue life and fatigue limit of defective materials and nature of scatter

(2021) Yukitaka Murakami et al.   INTERNATIONAL JOURNAL OF FATIGUE

Image-based multiscale modeling with spatially varying microstructures from experiments: Demonstration with additively manufactured metal in fatigue and fracture

(2021) Orion L. Kafka et al.   JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS

Machine learning for design, phase transformation and mechanical properties of alloys

(2021) J.F. Durodola   PROGRESS IN MATERIALS SCIENCE

A machine learning guided investigation of quality repeatability in metal laser powder bed fusion additive manufacturing

(2021) De Jun Huang et al.   MATERIALS & DESIGN

Deep learning model to predict fracture mechanisms of graphene

(2021) Andrew J. Lew et al.   npj 2D Materials and Applications

In-situ synchrotron X-ray tomography investigation of damage mechanism of an extruded magnesium alloy in uniaxial low-cycle fatigue with ratchetting

(2021) Ziyi Wang et al.   ACTA MATERIALIA

Ensemble learning for remaining fatigue life prediction of structures with stochastic parameters: A data-driven approach

(2021) S.Z. Feng et al.   APPLIED MATHEMATICAL MODELLING

A deep learning based life prediction method for components under creep, fatigue and creep-fatigue conditions

(2021) Xiao-Cheng Zhang et al.   INTERNATIONAL JOURNAL OF FATIGUE

A rolling bearing fault diagnosis method using novel lightweight neural network

(2021) Deqiang He et al.   MEASUREMENT SCIENCE and TECHNOLOGY

Fatigue life prediction of glass fiber reinforced epoxy composites using artificial neural networks

(2021) Hemanth Kumar C et al.   COMPOSITES COMMUNICATIONS

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

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

Strength through defects: A novel Bayesian approach for the optimization of architected materials

(2021) Zacharias Vangelatos et al.   Science Advances

Application of the Gaussian process for fatigue life prediction under multiaxial loading

(2021) Aleksander Karolczuk et al.   MECHANICAL SYSTEMS AND SIGNAL PROCESSING

An Introduction to Machine Learning

(2020) Solveig Badillo et al.   CLINICAL PHARMACOLOGY & THERAPEUTICS

Novel probabilistic model for searching most probable point in structural reliability analysis

(2020) Shun-Peng Zhu et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

A new approach to correlate the defect population with the fatigue life of selective laser melted Ti-6Al-4V alloy

(2020) Y.N. Hu et al.   INTERNATIONAL JOURNAL OF FATIGUE

Tensile properties prediction by multiple linear regression analysis for selective laser melted and post heat-treated Ti-6Al-4V with microstructural quantification

(2020) Masahiro Kusano et al.   MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING

Defects as a root cause of fatigue weakening of additively manufactured AlSi10Mg components

(2020) Paolo Ferro et al.   THEORETICAL AND APPLIED FRACTURE MECHANICS

The effect of manufacturing defects on the fatigue life of selective laser melted Ti-6Al-4V structures

(2020) Y.N. Hu et al.   MATERIALS & DESIGN

Determination of the fatigue P-S-N curves – A critical review and improved backward statistical inference method

(2020) Cunhai Li et al.   INTERNATIONAL JOURNAL OF FATIGUE

Defects in additive manufactured metals and their effect on fatigue performance: A state-of-the-art review

(2020) Niloofar Sanaei et al.   PROGRESS IN MATERIALS SCIENCE

Machine-learning assisted laser powder bed fusion process optimization for AlSi10Mg: New microstructure description indices and fracture mechanisms

(2020) Qian Liu et al.   ACTA MATERIALIA

Influence on microstructure, strength and ductility of build platform temperature during laser powder bed fusion of AlSi10Mg

(2020) Juan Guillermo Santos Macías et al.   ACTA MATERIALIA

A machine learning framework to predict local strain distribution and the evolution of plastic anisotropy & fracture in additively manufactured alloys

(2020) Waqas Muhammad et al.   INTERNATIONAL JOURNAL OF PLASTICITY

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

Analytical solution for circular inhomogeneous inclusion problems with non-uniform axisymmetric eigenstrain distribution

(2020) Lifeng Ma et al.   INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES

Probabilistic physics-guided machine learning for fatigue data analysis

(2020) Jie Chen et al.   EXPERT SYSTEMS WITH APPLICATIONS

Machine learning-based image processing for on-line defect recognition in additive manufacturing

(2019) Alessandra Caggiano et al.   CIRP ANNALS-MANUFACTURING TECHNOLOGY

An approach using random forest intelligent algorithm to construct a monitoring model for dam safety

(2019) Xing Li et al.   ENGINEERING WITH COMPUTERS

A Methodology for Predicting Surface Crack Nucleation in Additively Manufactured Metallic Components

(2019) Kwai S. Chan et al.   METALLURGICAL AND MATERIALS TRANSACTIONS A-PHYSICAL METALLURGY AND MATERIALS SCIENCE

Process Design of Laser Powder Bed Fusion of Stainless Steel Using a Gaussian Process-Based Machine Learning Model

(2019) Lingbin Meng et al.   JOM

High cycle fatigue life prediction of laser additive manufactured stainless steel: A machine learning approach

(2019) Meng Zhang et al.   INTERNATIONAL JOURNAL OF FATIGUE

Effects of build direction on tensile and fatigue performance of selective laser melting Ti6Al4V titanium alloy

(2019) Wenbo Sun et al.   INTERNATIONAL JOURNAL OF FATIGUE

Fatigue life and mechanistic modeling of interior micro-defect induced cracking in high cycle and very high cycle regimes

(2018) Ming-Liang Zhu et al.   ACTA MATERIALIA

Fatigue life prediction of additively manufactured material: Effects of surface roughness, defect size, and shape

(2018) A. Yadollahi et al.   FATIGUE & FRACTURE OF ENGINEERING MATERIALS & STRUCTURES

Few-Example Object Detection with Model Communication

(2018) Xuanyi Dong et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Online quality inspection using Bayesian classification in powder-bed additive manufacturing from high-resolution visual camera images

(2018) Masoumeh Aminzadeh et al.   JOURNAL OF INTELLIGENT MANUFACTURING

Predicting the 3D fatigue crack growth rate of small cracks using multimodal data via Bayesian networks: In-situ experiments and crystal plasticity simulations

(2018) Andrea Rovinelli et al.   JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS

A Unified Approach for Conventional Zero-Shot, Generalized Zero-Shot, and Few-Shot Learning

(2018) Shafin Rahman et al.   IEEE TRANSACTIONS ON IMAGE PROCESSING

Fatigue properties and material characteristics of additively manufactured AlSi10Mg – Effect of the contour parameter on the microstructure, density, residual stress, roughness and mechanical properties

(2018) Emilie Beevers et al.   INTERNATIONAL JOURNAL OF FATIGUE

Linking microstructure and processing defects to mechanical properties of selectively laser melted AlSi10Mg alloy

(2018) N.O. Larrosa et al.   THEORETICAL AND APPLIED FRACTURE MECHANICS

An analysis of defects influence on axial fatigue strength of maraging steel specimens produced by additive manufacturing

(2018) G. Meneghetti et al.   INTERNATIONAL JOURNAL OF FATIGUE

Fatigue properties of a titanium alloy (Ti–6Al–4V) fabricated via electron beam melting (EBM): Effects of internal defects and residual stress

(2017) Nikolas Hrabe et al.   INTERNATIONAL JOURNAL OF FATIGUE

The Influence of Porosity on Fatigue Crack Initiation in Additively Manufactured Titanium Components

(2017) S. Tammas-Williams et al.   Scientific Reports

Porosity regrowth during heat treatment of hot isostatically pressed additively manufactured titanium components

(2016) S. Tammas-Williams et al.   SCRIPTA MATERIALIA

XCT analysis of the influence of melt strategies on defect population in Ti–6Al–4V components manufactured by Selective Electron Beam Melting

(2015) S. Tammas-Williams et al.   MATERIALS CHARACTERIZATION

Accelerating materials property predictions using machine learning

(2013) Ghanshyam Pilania et al.   Scientific Reports

Material defects as the basis of fatigue design

(2012) Yukitaka Murakami   INTERNATIONAL JOURNAL OF FATIGUE

Variable selection using random forests

(2010) Robin Genuer et al.   PATTERN RECOGNITION LETTERS

Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index

(2009) Andrea Saltelli et al.   COMPUTER PHYSICS COMMUNICATIONS