Event Type:
MSE Grad Presentation
Talk Title:
Self-consistent Modeling and Material Property Analysis of an Additively Manufactured Polycrystalline Material
Via Zoom Videoconferencing
Other Info
Meeting ID: 912 3424 7085 Passcode: 184501

Committee Members: 

  • Prof. Hamid Garmestani, Advisor, MSE 
  • Prof. Steven Liang, ME 
  • Prof. David L. McDowell, ME/MSE 
  • Prof. Preet Singh, MSE 
  • Prof. Saïd Ahzi, MSE 

Self-consistent Modeling and Material Property Analysis of an Additively Manufactured Polycrystalline Material


Material testing is a cornerstone to understanding how a given material will perform when used in an engineering application.  The procedure for investigating properties begins with manufacturing a physical structure, rigorously testing replicates either destructively or non-destructively, and then analyzing material's properties using microscopy. This process is both labor intensive and financially burdensome so recent studies have cut the number of samples and overall scope of study that determines how a material can best be utilized.  Conducting simulations of material microstructures provides a cost-effective method of maximizing data. The simulations can be linked to experimental data to form useful and flexible models.

This research expands on material modeling in the field of Additive Manufacturing (AM) by selecting the manufacturing method (Selective Laser Melting (SLM)), choosing a multi-phase crystalline structure of extreme relevance to the manufacturing industries, and focusing on generating a realistic texture microstructural representation of the material by combining process parameters with statistical continuum mechanics theory. Once the material nature is distilled under the continuum, it can be expanded into a full-size structure with common occurring defects and inelastic strain effects by mimicking experimental data studied on samples produced in a similar manner.  The bulk material structure can then be expanded into an AM part and its microstructure linked with a desired material property.  This study utilizes a self-consistent model to generate a representative texture with the final goal of predicting inelastic properties of the polycrystalline material Titanium-6Al -4V.

This model builds upon extensive research done by Garmestani et al.   His previous work successfully modeled a single-phase body-center-cubic (BCC) structure representing the Ti-beta phase via melt pool thermal evolution using the Rosenthal model.  Since then, I have expanded the model to represent two phases, adding the hexagonal close-packed (HCP) structure representative of the Ti-alpha phase by modeling secondary-phase precipitation tied to the cooling of the microstructure.  This was accomplished via Bunge texture and microstructure analysis methods.  The model controls the texture by generating and then manipulating Euler angles to create unique electron backscatter diffraction (EBSD) and orientation distribution functions (ODF) data.   

The outlook of this research will add one- and two-dimensional defects as well as incorporate process parameter effects with the intension of constructing a final texture that can be expanded into a fully simulated AM SLM part.  The final goal of this project is to formulate a relationship between the generated material texture and the material property of inelastic strain.  In accomplishing this endeavor, the model will be easily tailorable towards other properties as well as different crystalline materials. This study aims to better understand a multitude of properties without the financial impact of manufacturing and testing physical samples. This model could assist in predicting the properties of a given material in advance and offer modifications to manufacturing process parameters to achieve a desirable microstructure that will perform as intended.