Deep learning prediction of stress fields in additively manufactured metals with intricate defect networks

Difference-based deep learning framework for stress predictions in heterogeneous media

(2021) Haotian Feng et al.   COMPOSITE STRUCTURES

Uncovering the coupled impact of defect morphology and microstructure on the tensile behavior of Ti-6Al-4V fabricated via laser powder bed fusion

(2021) Timothy Montalbano et al.   JOURNAL OF MATERIALS PROCESSING TECHNOLOGY

Predicting Microstructural Void Nucleation in Discontinuous Fiber Composites through Coupled in-situ X-ray Tomography Experiments and Simulations

(2020) Imad Hanhan et al.   Scientific Reports

Relationship between ductility and the porosity of additively manufactured AlSi10Mg

(2020) Christopher M. Laursen et al.   MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING

Prediction of microstructural defects in additive manufacturing from powder bed quality using digital image correlation

(2020) Jamison L. Bartlett et al.   MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING

Predicting elastic strain fields in defective microstructures using image colorization algorithms

(2020) Pranav Milind Khanolkar et al.   COMPUTATIONAL MATERIALS SCIENCE

Evolution of damage and failure in an additively manufactured 316L SS structure: experimental reinvestigation of the third Sandia fracture challenge

(2019) S. L. B. Kramer et al.   INTERNATIONAL JOURNAL OF FRACTURE

Fatigue of additively manufactured 316L stainless steel: The influence of porosity and surface roughness

(2019) Klas Solberg et al.   FATIGUE & FRACTURE OF ENGINEERING MATERIALS & STRUCTURES

Predicting the reliability of an additively-manufactured metal part for the third Sandia fracture challenge by accounting for random material defects

(2019) Kyle L. Johnson et al.   INTERNATIONAL JOURNAL OF FRACTURE

The third Sandia fracture challenge: predictions of ductile fracture in additively manufactured metal

(2019) Sharlotte L. B. Kramer et al.   INTERNATIONAL JOURNAL OF FRACTURE

Material structure-property linkages using three-dimensional convolutional neural networks

(2018) Ahmet Cecen et al.   ACTA MATERIALIA

Fatigue properties of AlSi10Mg obtained by additive manufacturing: Defect-based modelling and prediction of fatigue strength

(2018) S. Romano et al.   ENGINEERING FRACTURE MECHANICS

A deep learning approach to estimate stress distribution: a fast and accurate surrogate of finite-element analysis

(2018) Liang Liang et al.   Journal of the Royal Society Interface

Analysis of the damage initiation in a SiC/SiC composite tube from a direct comparison between large-scale numerical simulation and synchrotron X-ray micro-computed tomography

(2018) Yang Chen et al.   INTERNATIONAL JOURNAL OF SOLIDS AND STRUCTURES

Establishing structure-property localization linkages for elastic deformation of three-dimensional high contrast composites using deep learning approaches

(2018) Zijiang Yang et al.   ACTA MATERIALIA

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

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

Qualification of AM parts: Extreme value statistics applied to tomographic measurements

(2017) S. Romano et al.   MATERIALS & DESIGN

Metal Additive Manufacturing: A Review of Mechanical Properties

(2016) John J. Lewandowski et al.   Annual Review of Materials Research

Damage evolution and failure mechanisms in additively manufactured stainless steel

(2016) Holly D. Carlton et al.   MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING

X-ray computed tomography for additive manufacturing: a review

(2016) A Thompson et al.   MEASUREMENT SCIENCE and TECHNOLOGY

Deep learning

(2015) Yann LeCun et al.   NATURE

Influence of defects on mechanical properties of Ti–6Al–4V components produced by selective laser melting and electron beam melting

(2015) Haijun Gong et al.   MATERIALS & DESIGN

Computed tomography for characterization of fatigue performance of selective laser melted parts

(2015) Shafaqat Siddique et al.   MATERIALS & DESIGN