Advancing the performance of multi-physics heart simulations
Abstract/Contents
- Abstract
- Cardiovascular diseases (CVDs) are the leading cause of death globally, accounting for an estimated 17.9 million deaths in 2019. CVDs are a group of disorders that affect the heart and blood vessels, and include coronary heart disease, stroke, heart failure, and arrhythmias. Computational models of the heart offer a powerful tool to understand the mechanisms of CVDs and develop new diagnostic and therapeu- tic strategies. Finite element method (FEM) is a widely used numerical method for solving complex engineering problems, and has been successfully applied to model the heart. In this thesis, we used FEM to develop computational models of the heart to understand disease mechanisms, study model parameters to understand their ef- fects on the simulation results, and develop a novel constitutive material model to improve accuracy of the simulations. We first studied the effects of viscoelastic model parameters on the simulation results of healthy heart model, in order to understand the trade-off between increased model complexity and increased accuracy of the sim- ulations. We also developed a patient-specific computational model of a diseased pediatric heart. We used this model to study the mechanisms playing role in the progress of this disease and to evaluate possible treatment options. Finally, we devel- oped a novel constitutive material model for the heart muscle. This model is more accurate than existing models, and can better capture the complex behavior of the heart muscle. Our work demonstrates the potential of computational modeling to improve our understanding of CVDs and develop new diagnostic and therapeutic strategies. Given the scale of the CVD epidemic, it is essential to continue to invest in research on computational modeling of the heart.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2023; ©2023 |
| Publication date | 2023; 2023 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Tikenogullari, Oguz Ziya |
|---|---|
| Degree supervisor | Kuhl, Ellen, 1971- |
| Thesis advisor | Kuhl, Ellen, 1971- |
| Thesis advisor | Ennis, Daniel B |
| Thesis advisor | Marsden, Alison (Alison Leslie), 1976- |
| Degree committee member | Ennis, Daniel B |
| Degree committee member | Marsden, Alison (Alison Leslie), 1976- |
| Associated with | Stanford University, School of Engineering |
| Associated with | Stanford University, Department of Mechanical Engineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Oguz Ziya Tikenogullari. |
|---|---|
| Note | Submitted to the Department of Mechanical Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2023. |
| Location | https://purl.stanford.edu/rf452rw7377 |
Access conditions
- Copyright
- © 2023 by Oguz Ziya Tikenogullari
- License
- This work is licensed under a Creative Commons Attribution Non Commercial No Derivatives 3.0 Unported license (CC BY-NC-ND).
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