Project: Evaluation of Machine Learning Models for Predicting the Hot Deformation Flow Stress of Sintered Al–Zn–Mg Alloy (2023-2024)

The study employs various supervised ML models, including Linear Regression (Lasso and Ridge), Support Vector Regression (SVR), Ensemble Methods (RF, GB, XGB), and Neural Networks (ANN, MLP), to predict flow stress in the hot deformation of an Al-Zn-Mg alloy. 

Project: New Method for Microstructure Segmentation and Automatic Grain Size Determination Using Computer Vision Technology During the Hot Deformation of An Al-Zn-Mg Powder Metallurgy Alloy (2022-2023).

• The proposed algorithm measures the optical images grain size automatically by utilizing image processing functions from libraries like OpenCV, NumPy, and SciPy.

• Addressed issues like fused grains, lens aberrations, and edge-related noise, facilitating automated segmentation and accurate determination of microstructure characteristics such as grain counting, ASTM grain size, and grain size in µm.

Project: Comparative Analysis of Hot Deformation Constitutive Models and Processing Maps for Sintered Al-Zn-Mg Alloy (2022-2023)

• Four constitutive models were constructed; namely the Arrhenius-type, modified Johnson Cook (MJC), modified Zerilli-Armstrong (MZA), and an artificial neural network (ANN) for predicting hot deformation behavior.

• Established processing maps, while considering the effect of strain, facilitated the assessment of the workability of the Al-Zn-Mg alloy. 

Project: Microstructure Characterization of Hot-Deformed Al-Zn-Mg Alloy using EBSD (2022-2023)

The microstructural changes were analysed using EBSD, employing various maps, including IPF, KAM, GOS, and GAM, to assess dislocation density, grain misorientation, and their correlation with recrystallization in relation to both strain rate and temperature.

Project: Role of pre-strain on the corrosion behaviour of Al-Zn-Mg P/M alloy (2021-2022)

Al-5.6Zn-2Mg was subjected to deformation at various temperatures and strain rates then Potentiodynamic polarization and electrochemical impedance spectroscopy were used to assess the electrochemical behavior of deformed preforms.

Project: Effect of interlayers on mechanical properties of AA2014 & AA6061 friction stir welds (2018-2019)

• Attempt has been made to improve the mechanical properties of AA2014 & AA6061 using a Zinc interlayer in friction stir welding.

Project: Design & Analysis of Steering Knuckle (2015-2016)

In this project, an attempt has been made to design a steering knuckle in solidworks for the baja SAE project.