Research
My research focuses on mathematical model development and analysis of magnetoelastic slender structures and its real-world applications in soft robotics, magentically actuated systems.
Current focus
Lumped parameter modeling of CT gantry (GE HealthCare). As part of my research work at GE HealthCare, I am working on development of lumped parameter mathematical model of CT gantry and investigate lateral-torsional-translation coupling.
Curvature-mediated magnetoelasticity in ferromagnetic shells
Longitudinal bandgaps in phononic magneto-mechanical metamaterials (Independent research)
Research directions and interests
- Development of theoretical models for magnetoelastic slender structures.
- Investigating mechanical instabilities of such structures.
- Exploring real-world applications of magnetically actuated robotics.
- Exploring magneto-mechanical metamaterials for energy harvesting and structural health monitoring.
Ideas and emerging directions
Lightweight sandwich structures that block low frequencies. Embedding resonators in the core of aerospace sandwich panels can stop low-frequency vibration without heavy damping layers. The open challenge is to keep attenuation broadband while the panel still carries load and can be manufactured at scale.
Civil-scale vibration barriers. Recent reviews describe meta-concrete, periodic foundations and buried resonators for seismic and traffic vibration [1, 2]. Closed-form design rules for bandgap position and width could make such barriers easier to size for real soil and structures.
Disorder as a design tool. Manufacturing variability is usually treated as a defect, yet disorder can localise waves, as shown for flexural waves in disordered beams [3]. Combining local resonance with controlled disorder, and quantifying it statistically, is a route to broadband attenuation.
Mechanical computing. Bistable metamaterial elements can store information and perform logic [4, 5]. Nonlinear wave propagation and bandgaps that switch on and off offer a way to carry and process signals mechanically.
Physics-informed, data-driven design. Machine learning is now widely used to predict band structures and to inverse-design phononic metamaterials [6]. Analytical solutions for band boundaries can serve as fast, interpretable constraints inside such design loops.
Energy harvesting and structural health monitoring. Resonators that trap vibrational energy can also convert it to electricity, and shifts in a bandgap can reveal damage, so the same structure could isolate, harvest and sense.
Foundations from my published Ph.D. work
Unified model for deformable ferromagnetic ribbons
Closed-form expressions for attenuation peaks and band boundaries, and the mechanism behind double attenuation peaks.
- Closed-form solutions for general monocoupled systems, Journal of Sound and Vibration (2022)
- Double attenuation peaks with simultaneous negative mass and stiffness, Physics Letters A (2022)
Hamiltonian formulation for deformable ferromagnetic rods
Combining rigid and elastic segments to shape flexural waves and isolate vibration.
- Flexural wave propagation in rigid elastic combined metabeam, Journal of Vibration and Acoustics (2023)
- Vibration isolation by relative resonance, Journal of Sound and Vibration (2024)
Spatial localized deformation of hard and soft ferromagnetic rods
The effect of nonlinear stiffness and damping on dispersion, using multiple-scales analysis.
- Damped beam on cubic nonlinear springs, Physical Review E (2024)
Independent research
Methods
- Analytical: Variational calculus, Nonlinear dynamics, Stability analysis, Numerical continuation, Parallel computing, Optimization methods, Bloch–Floquet analysis, Uncertainty quantification
- Numerical: C, C++, MATLAB, Python, ABAQUS, COMSOL Multiphysics, FeNICSx Mathematica
- Experimental: magneto-elastic deformation, sample preparation, imaging