Research

Pictorial summary of my research exhibiting its engineering and societal applications

 

My current research is focused on two domains:

Domain 1: Exploiting geometric and material nonlinearities to design shape morphing structures: In this work, I design, fabricate and test a novel airfoil camber morphing mechanism with multiple stable states by harnessing the geometric nonlinearity of structures. This work involved developing computational design and structural optimization framework that leveraged snap-through instabilities to generate a mechanism exhibiting bi-stability. By carefully architecting the geometry using topology optimization with a nonlinear hyperelastic material, we showed that we can tailor the nonlinear response of the baseline structure to generate multi-functional, energy-efficient complaint mechanisms.The non-linear structural equilibrium equations are solved using arc-length and displacement-controlled Newton-Raphson (NR) analysis. Isoparamteric finite element evaluation is used for analyzing kinematic and deformation characteristics of the structure. The optimization problem is solved using a computationally efficient nonlinear optimization algorithm, the Method of Moving Asymptotes (MMA), with a Solid Isotropic Material Penalization (SIMP) scheme. The gradient information required for the optimization has been evaluated using an adjoint sensitivity formulation. The arc-length and the displacement-controlled Newton-Raphson (NR) scheme developed were leveraged to develop functionally-graded structures that showed around 9 % reduction in von-misses stress and approx. 6 % increase in geometric advantage. The developed computational design optimization framework was then leveraged to design another camber morphing airfoil. The design was then extracted and coupled with one-way fluid-structure interaction to gauge its performance computationally. The study shows that with a single airfoil, and without the need for complex actuators, we are able to drastically shift the airfoil’s aerodynamic properties in response to changing flight conditions. As desired, at low angles of attack, the flexible airfoil behaves similar to the rigid high-camber airfoil, and at high angles of attack, the flexible airfoil behaves similar to the rigid no-camber airfoil. The results obtained from the computational design framework was then 3D printed and its shape adaptive characteristics and the resulting performance enhancement was experimentally validated using wind-tunnel experiments. The experimental results agreed well with the computational predictions, demonstrating that the computational framework was ready to be used iteratively to drive the design towards specific aerodynamic control aims. Read the following publications to learn more about the research:


Domain 2: Exploiting stimuli-sensitive materials (smart materials) to design adaptive self-sensing and actuating structures exhibiting complex 3D motions: In this study, I develop a computational design optimization framework, fabricate using 4D printing and experimentally validate the shape adaptive characteristics of structures that can sense external stimulus and actuate automatically into target shapes. Traditional design methods are unable to fully explore the design space and integrate the capabilities of additive manufacturing methods. We present a novel optimization framework for optimal design of structures exhibiting memory characteristics by incorporating shape memory polymers (SMPs). SMPs are a class of memory materials capable of undergoing and recovering applied deformations. A finite-element analysis incorporating the additive decomposition of small strain is implemented to analyze and predict temperature-dependent memory characteristics of SMPs. The finite element method consists of a viscoelastic material modelling combined with a temperature-dependent strain storage mechanism, giving SMPs their characteristic property. The thermo-mechanical characteristics of SMPs are exploited to actuate structural deflection to enable morphing toward a target shape. A time-dependent adjoint sensitivity formulation implemented through a recursive algorithm is used to calculate the gradients required for the topology optimization algorithm. Multimaterial topology optimization combined with the thermo-mechanical programming cycle is used to optimally distribute the active and passive SMP materials within the design domain. This allows us to tailor the response of the structures to design them with specific target displacements, by exploiting the difference in the glass-transition temperatures of the two SMP materials. Forward analysis and sensitivity calculations are combined in a PETSc-based optimization framework to enable efficient multi-functional, multimaterial structural design with controlled deformations. The study revealed that by tailoring the distribution of multiple SMP materials inside a given geometry, we can extract structural performance unseen otherwise. We extend the computational capabilities by developing a hierarchical design framework and experimental method for design and synthesis of material-based morphing mechanisms capable of achieving complex pre-programmed motion. The optimization framework leveraged five different types kinematic structures each capable of generating a single type of motion when exposed to an external stimulus. A genetic algorithm with collision and manufacturing-based constraints was leveraged to optimally distribute the kinematic structures along a geometry to achieve a tailored global motion. By combining active and passive materials, the algorithm can encode the desired movement into the material distribution of the mechanism.  We demonstrate this new capability by de novo design of a 3D printed self-tying knot. Digital Image Correlation (DIC) technique was used to determine the mechanical deformation characteristics of the individual kinematic structures. This method advances a new paradigm in mechanism design that could enable a new generation of material-driven machines that are lightweight, adaptable, robust to damage, and easily manufacturable by 3D printing. The ability of these structures to sense and actuate when exposed to an external stimulus make them an ideal candidate to develop the next generation of energy efficient and multifunctional sensors/actuators. I developed a computational framework for designing resilient truss systems by simultaneously optimizing the shape as well as the placement of sensors and actuators. We provide the adjoint formulation for automated sensor placement and introduce the notion of Sensor Sensitivity Matrix to maximize damage detection using only a limited number of sensors. Our truss optimization scheme leveraged a novel bi-level and multi-material Solid Isotropic Material with Penalization (SIMP) formulation integrating sensor and actuator placement information.  We demonstrated that proposed framework with smart stimuli-sensitive actuators can mitigate the negative effects of structural damage by approx. 7 %.  Read the following publications to learn more about the research: