On going Research

"Time is a dimension of dimensions in the scale of time itself". - Sudip Dey

Research Domain

1. Mechanics of composite and functionally graded materials

2. Uncertainty Quantification

3. Tribology of Bearings

4. Computational Mechanics and Modelling

5. Meta-materials and Multi-scale Analysis

6. Molecular Dynamics Simulation

7. Design Optimization

8. Impact Engineering

9. Vibration and Modal Analysis

10. Finite Element Analysis

11. Reliability Analysis

The following domains are explored for further research and development in the broad area of my interest. If you are interested for collaborative research work, please contact me through email (sudip@mech.nits.ac.in). I am open to explore for research collaboration in other areas which are not explicitly mentioned below:

(A) Molecular Dynamics :: Computational Mechanics and Material Modelling

1. 2D Materials

2. Stochastic modes in fracture mechanics, damage mechanics, impact mechanics and structural analysis

3. Behaviour at interfaces, Thermal behaviour of nanomaterials

4. Energy harvesting

(B) Tribology of Bearings

1. Stochastic finite difference analysis for dynamic analysis of hydrodynamic journal bearings

2. Matlab code for two and three axial groove bearings with effect of elasto-hydrodynamics

3. Stochastic thermo-hydrodynamic effect on performance of journal bearings

1. Finite element analysis for laminated and delaminated composite shells: It can obtain the elastic stiffness matrix, geometric stiffness matrix and mass matrix of delaminated composite shells with different geometries such as cylindrical, conical, spherical, hyper shells. The generalized code can take the size, location and number of delaminations in laminated composite structures. From this code it is possible to carry out different analyses such as: dynamic analysis, multiple delaminated structural analyses.

2. Low Velocity Impact analysis of laminated and delaminated Composite Structures: Transient low velocity impact analysis of both laminated and delaminated composite Structures.

3. Failure analysis of Composite Structures: To determine the failure loads based on the five different failure criteria such as maximum stain, maximum stress, Tsai-Hill, Tsai-Wu-Hahn and Tsai-Hill-Hoffman

(D) Stochastic Analysis of Fibre Reinforced Composites, Sandwich and Functionally Graded Materials (FGM) Structures

1. Stochastic static and dynamic analysis of fiber reinforced composite and FGM beams, plates and shells: Both deterministic and stochastic analysis can be carried out by these codes. The developed codes can also take spatially varying material properties and ply orientation angle as input parameters

2. Stochastic finite element analysis for analyzing effect of cutout in composite / sandwich / FGM plates and shells

3. Stochastic finite element analysis for analyzing effect of rotation of composite / sandwich / FGM plates and shells

4. Stochastic finite element analysis for low velocity impact in composite / sandwich/ FGM plates and shells

5. Stochastic finite element analysis for analyzing the hygrothermal effect in composite plates and shells

6. Stochastic finite element analysis for first ply failure analysis of composite plates and shells

7. Stochastic finite element analysis for dynamic stability analysis of composite / FGM plates

8. Stochastic finite element analysis for effect of delamination in composite plates and shells

(E) Surrogate Models / Metamodels

1. Matlab code developed for different surrogate models: Polynomial regression, kriging, high dimensional model representation, polynomial chaos expansion, artificial neural network, moving least square, support vector regression, multivariate adaptive regression splines, radial basis function, deep learning algorithm and polynomial neural network

2. Matlab code developed for the kriging model variants: ordinary kriging, universal kriging based on pseudo-likelihood estimator, blind kriging, co-kriging and universal kriging

(F) Uncertainty Quantification, Optimization and Reliability Analysis

1. Uncertainty quantification, reliability analysis, noise, optimization and sensitivity analysis

2. Matlab code for Karhunen-Loève expansion to consider spatially correlated system properties

(G) Budding Misc Areas

1. Machine Learning Problems: Research work dealing with image processing, support vector machines, neural network models, digital twins.

2. Meta-materials: Research works consider the dynamic stiffness of metamaterial model idealized from origami (such as miura-ori, waterbomb etc.) as a bar and hinge model

3. Multi-scale Analysis: Research on different scale levels such as macro-meso-micro-nano-pico to atomic levels with stochastic approach in material modelling.