Quantifying alignment deviations for uniaxial material mechanical testing via automated machine learning-Reference-Cited by-同舟云学术

Quantifying alignment deviations for uniaxial material mechanical testing via automated machine learning

Published:2022-10-29 Issue: Volume: Page:1-14
ISSN:1537-6494
Container-title:Mechanics of Advanced Materials and Structures
language:en
Short-container-title:Mechanics of Advanced Materials and Structures

Author:

Chen Junxian¹²^ORCID,Zhang Jianhai¹²³,Zhao Hongwei¹²³

Affiliation:

1. School of Mechanical and Aerospace Engineering, Jilin University, Changchun, China

2. Key Laboratory of CNC Equipment Reliability, Ministry of Education, Jilin University, Changchun, China

3. Chongqing Research Institute, Jilin University, Chongqing, China

Funder

National Key R and D Program of China

National Science and Technology Innovation Leading Academic

the Pre-research of Equipment of the General Armaments Department

Publisher

Informa UK Limited

Subject

Mechanical Engineering,Mechanics of Materials,General Materials Science,General Mathematics,Civil and Structural Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/15376494.2022.2128122

Reference30 articles.

1. In Situ Uniaxial Mechanical Testing of Small Scale Materials—A Review

2. J. Bressers, S. Holdsworth, P. Harris, C. Larsen, M. Sanders, M. Steen, and G. L. A. Tjoa, A code of practice for the measurement of misalignment induced bending in uniaxially loaded tensioncompression test pieces, Report, Joint Research Centre Institute for Energy Petten, The Netherlands, 1995.

3. Uncertainty in the determination of elastic modulus by tensile testing

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