UQ Lab

In Uncertainty Quantification (UQ) laboratory, we work not only on uncertainty quantification of engineering systems but also on versatile areas such as, tribology, molecular dynamics, metamaterials, bio-inspired structures for the development of a new class of shape-changing programmable mechanical properties. We are actively involved in stochastic multi-scale analysis and uncertainty quantification of composite (including functionally graded materials, sandwich and smart structures) materials and structures considering the effect of irregularities, different forms of progressive damages and operational and environmental conditions.

Research Keywords: Tribology of Bearings, Uncertainty Quantification, Molecular Dynamics (2D materials and heterostructures), Metamaterials, Machine learning, Artificial intelligence, Additive Manufacturing, Advanced multi-functional composites and Graded structures, Bio-inspired deployable structures, Multi-scale mechanics, Digital Twin, Stochastic structural mechanics, Reliability analysis, Surrogate modelling,, Micromachining

Our other active fields of research are machine learning and surrogate modelling to efficiently deal with different computationally intensive problems related to structural analysis (with application in the fields of reliability analysis, uncertainty quantification and optimization). Our students worked in the area of surrogate based stochastic structural analysis.

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Our research group is passionately interested in almost each and every aspect of mechanics at multiple length-scales. We enjoy the development of fundamental analytical and computational algorithms in relevant fields as well as application oriented research in the interdisciplinary realm of Aerospace, Mechanical and Civil Engineering. We are always keen to explore novel ideas and strengthen the footing of our earlier research activities. Please refer to our published works for more specific information and feel free to get in touch with me for further discussions.

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(A) 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

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

1. 2D Materials and heterostructures

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

3. Behaviour at interfaces, Thermal behaviour of nanomaterials

4. Energy harvesting

(C) Composite Structures

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. It is carried out to 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) Other Areas

1. Machine Learning Problems: Research work dealing with high-dimensional model representation, support vector machines, neural network models.

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.

4. Computational Additive Manufacturing: Research work dealing with image processing, digital twins and 3D-printing of deployable weight-sensitive structures.

Open Positions: Our research group is constantly looking for bright and motivated students for carrying out funded research in the broad fields mentioned below. Students from the background of Mechanical, Aerospace, Civil and Materials Science can find suitable opportunities in our research group. Please contact me directly for prospective opportunities in PhD (including direct PhD after having a Bachelor's degree), MTech, B.Tech and research internships.

Please contact @email: sudip@mech.nits.ac.in