Anindita Dhar Swarna

1. Modelling of Composite Electrode for Lithium-ion Batteries using PyBaMM. 2. Combination of Recycled material/Virgin material used in the positive electrode. 3. Development of a P2D model. 4. Development of an Equivalent Circuit Model (ECM). 5. Validation of the model using experimental data. 6. Extending the existing model in the case of negative electrode. Teaching Courses: 1. Battery Modelling and Management. 2. Engineering Materials.

Topic: Prediction of Fatigue Damage Evolution and Lifetime for Additively Manufactured AlSi10Mg Alloys Using Two-scale FE Simulations with Application of Machine Learning (ML). 1. Multiscale simulation using FEA software ABAQUS. 2. EBSD image segmentation using ML. 3. Addition of artificially generated SiC particles using GIMP. 4. Generation of 3D mesh using 'Simpleware ScanIP'. 5. Carrying out microstructural fatigue analysis in combination with ML.

1. Created and implemented lesson plans based on different deep learning and machine learning algorithms. 2. Evaluation of students’ assignment.

Conducting both Theoretical and Practical lessons on different Engineering topics (Thermodynamics, Mechanics of Solids, Engineering Materials Sessional etc.)