Tülin Kaman Data-verified
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Associate Professor
faculty
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Biography and Research Information
OverviewAI-generated summary
Tülin Kaman's research focuses on numerical simulations of fluid dynamics, particularly instabilities in fluid interfaces. She has investigated the Richtmyer-Meshkov Instability, exploring its statistical learning for nonlinear dynamical systems and its application to aircraft-UAV collisions. Her work includes the validation and verification of turbulence mixing associated with this instability, specifically for an air/SF$_6$ interface.
Kaman has also contributed to computational science education, developing an undergraduate course to train future computational scientists. Her research on parallel computing for turbulent mixing simulations highlights her interest in the performance analysis of computational fluid dynamics (CFD) codes. She has received federal funding from the National Science Foundation (NSF) for high-performance computing systems and for a spring lecture series in computational and applied mathematics. Kaman collaborates with researchers at the University of Arkansas at Fayetteville, including Ryan Holley, John McGarigal, Alaina Edwards, and Shannon Dingman.
Metrics
- h-index: 6
- Publications: 24
- Citations: 145
Selected Publications
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A front-tracking/ghost-fluid method for the numerical simulations of Richtmyer–Meshkov Instability (2025)
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Statistical Learning for Nonlinear Dynamical Systems with Applications to Aircraft-UAV Collisions (2023)
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Performance Analysis of the Parallel CFD Code for Turbulent Mixing Simulations (2021)
Federal Grants 2 $524,482 total
Spring Lecture Series in Computational and Applied Mathematics
Collaboration Network
Top Collaborators
- Validation and Verification of Turbulence Mixing due to Richtmyer-Meshkov Instability of an air/SF$_6$ interface
- A front-tracking/ghost-fluid method for the numerical simulations of Richtmyer–Meshkov Instability
- A Front-Tracking/Ghost-Fluid Method for the Numerical Simulations of Richtmyer-Meshkov Instability
- Performance Analysis of the Parallel CFD Code for Turbulent Mixing Simulations
- Performance Analysis of the Parallel CFD Code for Turbulent Mixing Simulations
- Training the next generation of computational scientists through a new undergraduate course
- Training the next generation of computational scientists through a new undergraduate course
- Statistical Learning for Nonlinear Dynamical Systems with Applications to Aircraft-UAV Collisions
- Statistical Learning for Nonlinear Dynamical Systems with Applications to Aircraft-UAV Collisions
- Statistical Learning for Nonlinear Dynamical Systems with Applications to Aircraft-UAV Collisions
- Statistical Learning for Nonlinear Dynamical Systems with Applications to Aircraft-UAV Collisions
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