Flow Stress Modeling of Tube and Slab Route Sheets of Zircaloy-4 Using Machine Learning Techniques and Arrhenius Type Constitutive Equations

Kanthi, Limbadri; Wankhede, Pankaj; Suresh, Kurra; Singh, Swadesh Kumar; Rajashekharan, Sabareesh Geetha

doi:10.1007/s11665-022-07102-x

J. of Materi Eng and Perform

2022

DOI: 10.1007/s11665-022-07102-x

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Flow Stress Modeling of Tube and Slab Route Sheets of Zircaloy-4 Using Machine Learning Techniques and Arrhenius Type Constitutive Equations

Limbadri Kanthi¹,

Pankaj Wankhede

Kurra Suresh

et al.

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Cited by 4 publications

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Predicting Stress–Strain Characteristics of Hot Deformed Cu-Zr Metallic Glass Alloy Composite Nanowires Using Supervised Machine Learning Algorithms

Katakareddi,

Ali,

Jungalwala

et al. 2024

J. of Materi Eng and Perform

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Flow Stress Modeling of Tube and Slab Route Sheets of Zircaloy-4 Using Machine Learning Techniques and Arrhenius Type Constitutive Equations

Cited by 4 publications

References 44 publications

Predicting Stress–Strain Characteristics of Hot Deformed Cu-Zr Metallic Glass Alloy Composite Nanowires Using Supervised Machine Learning Algorithms

Predicting Stress–Strain Characteristics of Hot Deformed Cu-Zr Metallic Glass Alloy Composite Nanowires Using Supervised Machine Learning Algorithms

Hot Deformation and Microstructure Evolution of a Cu-Ni-Co-Si-Cr-Mg Alloy

Research on hot deformation behavior of Cu-Ti alloy based on machine learning algorithms and microalloying

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