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Journal Articles

A Review of the Applications of Machine Learning for Prediction and Analysis of Mechanical Properties and Microstructures in Additive Manufacturing

Atharv P. Deshmankar, Jagat Sesh Challa, Amit R. Singh, Srinivasa Prakash Regalla

Publisher: ASME

J. Comput. Inf. Sci. Eng. December 2024, 24(12): 120801.

Paper No: JCISE-24-1227

https://doi.org/10.1115/1.4066575

Published Online: October 14, 2024

View Article titled, A Review of the Applications of Machine Learning for Prediction and Analysis of Mechanical Properties and Microstructures in Additive Manufacturing

Topics: Additive manufacturing, Machine learning, Mechanical properties

Journal Articles

Prediction of Mechanical Properties of Three-Dimensional Printed Lattice Structures Through Machine Learning

Shuai Ma, Qian Tang, Ying Liu, Qixiang Feng

Publisher: ASME

J. Comput. Inf. Sci. Eng. June 2022, 22(3): 031008.

Paper No: JCISE-21-1252

https://doi.org/10.1115/1.4053077

Published Online: December 16, 2021

View Article titled, Prediction of Mechanical Properties of Three-Dimensional Printed Lattice Structures Through Machine Learning

Topics: Elastic moduli, Errors, Machine learning, Mechanical properties, Three-dimensional models, Entropy, Yield strength, Design, Porosity

Journal Articles

Data-Driven Predictive Modeling of Tensile Behavior of Parts Fabricated by Cooperative 3D Printing

Ziyang Zhang, Laxmi Poudel, Zhenghui Sha, Wenchao Zhou, Dazhong Wu

Publisher: ASME

J. Comput. Inf. Sci. Eng. April 2020, 20(2): 021002.

Paper No: JCISE-19-1204

https://doi.org/10.1115/1.4045290

Published Online: December 11, 2019

View Article titled, Data-Driven Predictive Modeling of Tensile Behavior of Parts Fabricated by Cooperative 3D Printing

Topics: Additive manufacturing, Tensile strength, Modeling, Shells, Mechanical properties

Journal Articles

Powder Mixed Electric Discharge Machining: An Innovative Surface Modification Technique to Enhance Fatigue Performance and Bioactivity of β -Ti Implant for Orthopedics Application

Chander Prakash, H. K. Kansal, B. S. Pabla, Sanjeev Puri

Publisher: ASME

J. Comput. Inf. Sci. Eng. December 2016, 16(4): 041006.

Paper No: JCISE-16-1046

https://doi.org/10.1115/1.4033901

Published Online: November 7, 2016

View Article titled, Powder Mixed Electric Discharge Machining: An Innovative Surface Modification Technique to Enhance Fatigue Performance and Bioactivity of β -Ti Implant for Orthopedics Application

Topics: Alloys, Electrical discharge machining, Fatigue, High cycle fatigue, Orthopedics, Polishing, Surface roughness, Surface cracks, Biocompatibility, Machining

Journal citation

NARROW

A Review of the Applications of Machine Learning for Prediction and Analysis of Mechanical Properties and Microstructures in Additive Manufacturing

Prediction of Mechanical Properties of Three-Dimensional Printed Lattice Structures Through Machine Learning

Data-Driven Predictive Modeling of Tensile Behavior of Parts Fabricated by Cooperative 3D Printing

Powder Mixed Electric Discharge Machining: An Innovative Surface Modification Technique to Enhance Fatigue Performance and Bioactivity of β -Ti Implant for Orthopedics Application

ASME Journals

ASME Conference Proceedings

ASME eBooks

Resources

Opportunities

A Review of the Applications of Machine Learning for Prediction and Analysis of Mechanical Properties and Microstructures in Additive Manufacturing

Prediction of Mechanical Properties of Three-Dimensional Printed Lattice Structures Through Machine Learning

Data-Driven Predictive Modeling of Tensile Behavior of Parts Fabricated by Cooperative 3D Printing

Powder Mixed Electric Discharge Machining: An Innovative Surface Modification Technique to Enhance Fatigue Performance and Bioactivity of β -Ti Implant for Orthopedics Application

ASME Journals

ASME Conference Proceedings

ASME eBooks

Resources

Opportunities

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