Research

CMEO Research Group currently focus on i) real-time shape sensing and structural health monitoring of composite structures using optic sensors, (ii) topology optimization for additive manufacturing, (iii) numerical and experimental structural mechanics of 2D/3D composites including fracture, damage, fatigue analyses, (iv) optimizing design for mitigating stress intensification and increasing stiffness-to-weight performance, (v) piezoelectric sensor design for energy harvesting and parameter identification processes, and (vi) complex fluid-structure interaction analysis of large-scale engineering structures.

Shape sensing and structural health monitoring

Structural health monitoring (SHM) is a very important discipline in the areas of civil, aerospace, marine, automotive engineering, etc. The utilization of SHM allows us to increase both human and environmental safety in conjunction with reduction in maintenance costs. Known as “shape sensing”, real-time reconstruction of a structure’s three-dimensional displacements using a network of in situ strain sensors and measured strains is a vital technology for SHM process. The inverse finite element method (iFEM) is a mechanics-based shape-sensing algorithm shown to be fast, accurate, and robust for usage as a part of SHM systems.

 

One of our main research areas involves development of mathematically robust and efficient iFEM methodologies to perform real-time monitoring of full-field and three-dimensional structural deformations and stress states of a structure via a network of in situ strain sensors. As depicted the graphical abstract in above, an application of iFEM methodology have been demonstrated by using both fiber optic sensor and strain gauges/rosettes for shape sensing of fiber-reinforced composite materials and sandwich structures.

 

Particle-based topology optimization of structures

Peridynamics is a new nonlocal continuum mechanics formulation. Its equations are always applicable whether there is any discontinuity in the structure or not due to the non-derivative (i.e., purely integral) nature of the theory. On the other hand, topology optimization can be considered as finding an optimal distribution of material deposition (i.e., where should the material be?) whilst improving an objective function (e.g., stiffness) and satisfying design constraints.

 

In this research effort, we developed a novel topology optimization algorithm based on Peridynamics to perform structural optimization of engineering components involving damages/cracks/failures. As clearly depicted in the figure above, this new concept, abbreviated as PD-TO, allow engineers to model existence of damage as a constraint during geometrical optimization process. In addition, the PD-TO approach simply eliminate the limitations encountered when performing the topology optimization analysis using traditional finite element methods especially for problems involving moving boundaries, large deformations, and cracks/defects.

 

Topology Optimization for Additive Manufacturing

In this research effort, various three-dimensional topology optimization algorithms have been developed for additive manufacturing of structures. During topology optimization stages, the mechanical/manufacturing constraints including minimum feature size, overhang supports angle, selective print directions are considered for rapid prototyping of an optimized geometry.

 

The fundamental solution methods contain comprehensive combination of different modelling techniques such Peridynamics, finite element methods, other continuum formulations. Hence, vital mechanical parameters including residual stress, stress-induced cracks, thermomechanical damages can be viably to be taken into account during topology optimization. Various geometry smoothing methods are implemented on the geometry being optimized, thereby producing ready-to-print structures (i.e., with/without consideration of cracks) as depicted in the figure above.