Cutting models for bio-composites
Authors
Potukuchi, Sri Krishna Sasidhar
ORCID
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Other Contributors
Samuel, Johnson
Picu, Catalin R.
Walczyk, Daniel F.
Ozisik, Rahmi
Picu, Catalin R.
Walczyk, Daniel F.
Ozisik, Rahmi
Issue Date
2021-05
Keywords
Mechanical engineering
Degree
PhD
Terms of Use
This electronic version is a licensed copy owned by Rensselaer Polytechnic Institute, Troy, NY. Copyright of original work retained by author.
Full Citation
Abstract
The research presented in this thesis aims to investigate the cutting behavior of hard and soft bio-composites, specifically, bovine cortical bone and fiber-reinforced hydrogels respectively. For bovine cortical bone, a microstructure-based finite element model to simulate fracture cutting of bovine cortical bone is developed. For soft composites, investigation is done into the experimental and modeling aspects associated with the cutting of fiber-reinforced hydrogels, with a focus on the application of the hydrophone as a process-monitoring sensor.On the bovine cortical bone front, fracture cutting of both the haversian and plexiform components of bovine cortical bone is successfully simulated using a cohesive zone-based approach. This model presents an improvement over existing bone cutting models in this category that have relied only on parametric inputs for the material properties. A key novelty of this work lies in the fact that the cohesive zone parameters associated with each of the failure modes are heuristically extracted using their specific acoustic emission signature. This approach ensures that the Cohesive Zone (CZ) parameters capture the specific failures observed in the cutting experiment. The cohesive tractions were first extracted using the experimental results for the +20° rake tool. They are then successfully used to predict the results for the 0° rake tool.
Description
May 2021
School of Engineering
School of Engineering
Department
Dept. of Mechanical, Aerospace, and Nuclear Engineering
Publisher
Rensselaer Polytechnic Institute, Troy, NY
Relationships
Rensselaer Theses and Dissertations Online Collection
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