Research and Projects

Current Projects 

Understanding the Effects of Stochastic Morphology on Compressive Behavior in Freeze-Casted Alumina Ceramic

This project focuses on the development of a macroscale homogenized progressive failure analysis (PFA) model to investigate how morphological variability in freeze-casted ceramics influences their compressive mechanical behavior. The study incorporates stochastic material features, including lamellar wall misalignment and local defects, into a finite element failure model to better predict material performance.

Impact of Element Layout on the Mechanical and Fracture Behavior of 3D Printed Glass Fiber-Reinforced Composites and Composite Sandwich Structures

This research explores how fused filament fabrication (FFF) processing parameters and element layouts influence the mechanical and fracture behavior of glass fiber-reinforced composites (GFRC) and composite sandwich structures (CSS). The study investigates the effects of fiber orientation, infill density, and geometric configurations on the tensile, flexural, and fracture properties of 3D-printed composite components.

 Mechanical Behavior of 3D printed carbon fiber reinforced Nylon composite 

A finite element (FE) model was developed to simulate tensile testing of 3D-printed glass fiber-reinforced nylon composites using the Abaqus implicit computational tool. The model utilized Abaqus Implicit as the simulation platform. The model accounted for the material with the printed layers of short glass fiber reinforcement and long glass fiber reinforcement fused filament composite. The structure of the model includes printing layers with specified thicknesses and transversely isotropic behavior. A field output was defined to capture the orientation of elements. Finite element domains were assigned coordinate systems for every printing layer with a specified printing orientation to represent the printing material's orientation. Cohesive interfaces were implemented to model interlayer interactions and define the bonding behavior between layers. A continuum damage mechanism was incorporated to predict material failure under tensile loading.

Finite Element Modeling of Infill-Dependent Mechanical Behavior in 3D-Printed PLA Components 

This study develops a finite element (FE) model to predict the compressive behavior of FDM-printed PLA components, incorporating damage and interface mechanisms. Various infill patterns (lattice-grid with circular reinforcements, honeycomb, hexagonal, and rectangular) were analyzed at 25%, 50%, and 60% densities. The model integrates ductile damage and cohesive interface behavior to capture anisotropic material response. Experimental compression testing validated the model, demonstrating its effectiveness in predicting the influence of infill density, geometry, and printing orientation on 3D-printed polymer structures. 

Recent Projects 

The Role of Annealing and Isostatic Compaction on the Mechanical Properties of 3D-Printed Short Glass Fiber Nylon Composites

This study examined the effects of constant compaction pressure at elevated temperatures on the mechanical performance of 3D-printed glass-nylon fiber composites. By evaluating the mechanical and thermal behaviors of the composites, the results showed that the proper selection of temperature and compaction significantly enhanced tensile properties without changing geometric characteristics. Key parameters such as the degree of compaction, crystalline structure, fiber orientation, and void content were assessed using microscopy, differential scanning calorimetry (DSC), and Raman spectroscopy. The findings also revealed a healing effect linked to material softening and the applied pressure during processing.

Analysis of the Structure-Property Relationship of Glass Fiber Nylon Organosheets Processed with In-Situ Polymerization

This research focused on developing novel glass fiber-reinforced nylon composites and creating a computational model to predict the effects of micro- and mesostructure on mechanical and failure behavior. The study included three key investigations: 1. Progressive Failure Analysis (PFA) was utilized to analyze the structure-property relationships and predict failure behavior. 2. The effects of notch sensitivity were examined through computational and analytical modeling, simulating and predicting open-hole tensile properties. 3. The influence of flow-induced crystallization and morphology on mechanical behavior was explored, highlighting the interplay between recrystallization and fiber reorientation and its impact on composite performance.

Mechanical and Thermal Properties of Carbon Fiber Epoxy Composites with Interlaminar Graphene at Elevated Temperatures

This study investigated the effects of renewable graphene nanoparticles (pGNP) as an alternative filler for polymer composites. The results demonstrated that pGNP fillers improved composite performance, revealing that polymer crosslinking within the graphene surface groups restricted side chain movement, thereby enhancing mechanical properties and thermal conductivity. The analysis centered on the mechanical strength, crack propagation resistance, and thermal performance of spray-deposited pGNP composite laminates, employing Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), microscopy, and dynamic mechanical analysis (DMA). These findings support the effective use of pGNP as a filler alternative, contributing to the design of high-performance materials for advanced engineering applications.

Computational Modeling of Freeze-Casted Porous Alumina Ceramics

This research focused on developing a computational model to analyze freeze-casted ceramics. By utilizing a Representative Volume Element (RVE) model, the study investigated the microstructural morphology of alumina ceramics and its impact on mechanical properties. The model offered valuable insights into material behavior, allowing for accurate predictions of mechanical responses and optimization of freeze-casting manufacturing processes. These findings are instrumental in enhancing material properties and lowering production costs for ceramic-based applications.

Performance Analysis of Prepreg Platelet Molded Composites (PPMCs)

This study examined the structure-property relationships and variability in the mechanical properties of PPMCs. A progressive failure finite element analysis (FEA) model was developed to simulate failure behavior and assess the influence of mesostructural morphology and fiber orientation. The findings offered predictions and simulations of material properties and failure behavior, enabling the optimization of composite properties based on material morphology. Additionally, to address fiber orientation distribution (FOD), a microstructure reconstruction model using artificial intelligence (MR-AI) was proposed. By leveraging thermal strain as an input, the MR-AI model effectively predicted the average FOD through the thickness of PPMCs, using microscopy analysis and image processing for validation.