Additive manufacturing (AM) is a rising technology that can be used to fabricate complex metallic components by adding material layer-by-layer. Directional solidification and rapid heating/cooling cycles produce a microstructure with anisotropic mechanical properties, which hinders the widespread adoption of AM technology. Extensive research work has been devoted to predicting the microstructure of AM components using computational models, however, individual models are often not well validated and their integration across length scales is limited. Comprehensive techniques that unify models across size scales will improve robustness of microstructure predictions and provide a basis for subsequent mechanical property modeling and insight into process-structure-property linkages. This research aims to predict the microstructure of AM Ti-6Al-4V, an alloy widely used in the transportation industry for structural applications due to its high specific strength and excellent corrosion resistance. The multi-scale microstructure prediction framework integrates continuum heat transfer, kinetic Monte Carlo (MC) grain structure and crystallographic texture simulation, and phase field (PF) modeling of the solid-state transformation at the subgrain level. The thermal and MC models were implemented using SPPARKS and quantitatively compared to experimental microstructures with a novel two-point spatial correlation and dimension reduction method. The transformation kinetics of martensite formation in the PF model were calibrated and validated through in-situ high-energy X-ray diffraction experiments. To unite these models and enable agile part-scale microstructure simulation, the MC and PF models are integrated using a machine learning surrogate model. This contribution establishes a pathway toward optimization of AM processing, ultimately addressing the need for more economical, energy-efficient, and rapid materials manufacturing.

Creator

• Whitney, Bonnie

Contributors

• Cheng, Lin
• Spangenberger, Anthony
• Brown, Donald W.
• Powell, Adam C., IV
• Rodgers, Theron M.
• Lados, Diana A.

Degree

• PhD

Unit

• Materials Science & Engineering

Publisher

• Worcester Polytechnic Institute

Identifier

• etd-121264

Keyword

• phase field
• microstructure modeling and simulation
• laser powder bed fusion
• titanium alloys
• finite difference-Monte Carlo
• in-situ synchrotron X-ray diffraction

Advisor

• Lados, Diana A.
• Spangenberger, Anthony

Orcid

• https://orcid.org/0000-0001-5286-9494

Committee

• Brown, Donald W.
• Powell, Adam C., IV
• Cheng, Lin
• Rodgers, Theron M.

Defense date

• 2024-04-15

Year

• 2024

UN Sustainable Development Goals

• 9 - Industry, Innovation and Infrastructure

Date created

• 2024-04-22

Resource type

• Dissertation

Source

• etd-121264

Rights statement

• In Copyright

Last modified

• 2024-05-29