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Senthilkumar, V.
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Topics
Publications (10/10 displayed)
- 2023Thermal Adsorption and Corrosion Characteristic Study of Copper Hybrid Nanocomposite Synthesized by Powder Metallurgy Routecitations
- 2021EFFECTS OF PARTICLE SIZE AND SINTERING TEMPERATURE ON SUPERELASTICITY BEHAVIOR OF NiTi SHAPE MEMORY ALLOY USING NANOINDENTATIONcitations
- 2021Generative Design and Topology Optimization of Analysis and Repair Work of Industrial Robot Arm Manufactured Using Additive Manufacturing Technologycitations
- 2014Modelling and Analysis of Electrical Discharge Alloying through Taguchi Techniquecitations
- 2014Development of carbide intermetallic layer by electric discharge alloying on AISI-D2 tool steel and its wear resistancecitations
- 2012Mathematical Modeling of Machining Parameters in Electrical Discharge Machining with Cu-B<sub>4</sub>C Composite Electrodecitations
- 2012Prediction of flow stress during hot deformation of MA'ed hybrid aluminium nanocomposite employing artificial neural network and Arrhenius constitutive modelcitations
- 2011Constitutive Modeling for the Prediction of Peak Stress in Hot Deformation Processing of Al Alloy Based Nanocompositecitations
- 2008Influence of titanium carbide particles addition on the forging behaviour of powder metallurgy composite steelscitations
- 2007Some Aspects on Hot Forging Features of P/M Sintered High-Strength Titanium Carbide Composite Steel Preforms Under Different Stress State Conditionscitations
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article
Constitutive Modeling for the Prediction of Peak Stress in Hot Deformation Processing of Al Alloy Based Nanocomposite
Abstract
<jats:p>Hot deformation tests were carried out on Al5083 – 2 %(vol) TiC nanocomposite in a temperature range of 250 – 450°C at varying strain rate of 0.01 – 1.0 sec<jats:sup>-1</jats:sup>. Constitutive models were developed for the prediction of peak flow stress relating strain rate, true stress, temperature and activation energy. The percentage error between measured flow stress and constitutive model values were calculated to analyse the efficacy of the model in the prediction of peak stress. Finally, a window of working of the selected nanocomposite is established for finding out the safer region of working.</jats:p>