N
Ngoc-Trung Nguyen
Researcher at Pohang University of Science and Technology
Publications - 14
Citations - 226
Ngoc-Trung Nguyen is an academic researcher from Pohang University of Science and Technology. The author has contributed to research in topics: Formability & Hardening (metallurgy). The author has an hindex of 8, co-authored 13 publications receiving 177 citations. Previous affiliations of Ngoc-Trung Nguyen include Indian Institute of Technology Delhi & Purdue University.
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Mechanical Behavior of AZ31B Mg Alloy Sheets under Monotonic and Cyclic Loadings at Room and Moderately Elevated Temperatures
TL;DR: Large-strain monotonic and cyclic loading tests of AZ31B magnesium alloy sheets were performed with a newly developed testing system, at different temperatures, ranging from room temperature to 250 °C, and a critical temperature was identified to account for the transition between the twinning-Dominant and slip-dominant deformation mechanisms.
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A practical constitutive model for AZ31B Mg alloy sheets with unusual stress-strain response
TL;DR: In this paper, a constitutive model is proposed to predict the mechanical behavior of Mg alloy sheets, which can accurately predict the yielding asymmetry behavior and the stress-strain curve featured by the unusual sigmoidal shape.
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Cyclic behavior of AZ31B Mg: Experiments and non-isothermal forming simulations
TL;DR: In this article, the mechanical behavior of AZ31B Mg alloy sheets under in-plane tension-compression (or compression-tension) cyclic loading was experimentally measured for various pre-strains and temperatures.
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Multi-Objective Genetic Algorithm to Optimize Variable Drawbead Geometry for Tailor Welded Blanks Made of Dissimilar Steels
Krishnaswamy Hariharan,Ngoc-Trung Nguyen,Nirupam Chakraborti,Nirupam Chakraborti,Myoung-Gyu Lee,Frédéric Barlat +5 more
TL;DR: In this paper, the design of drawbead is optimized by treating it as a multi-objective problem with maximum dome height and minimum weldline movement as objectives, which were constructed as metamodels through a genetic algorithms based approach.
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Determination of Anisotropic Yield Coefficients by a Data-Driven Multiobjective Evolutionary and Genetic Algorithm
TL;DR: In this article, a robust multiobjective optimization based on evolutionary algorithm is proposed to minimize the error in yield stress and plastic strain ratio simultaneously and thereby overcomes the limitations in the approaches used before.