Research Output per year
Fingerprint Fingerprint is based on mining the text of the experts' scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.
- 37 Similar Profiles
Computational fluid dynamics
Engineering & Materials Science
Cavitation
Engineering & Materials Science
Multiphase flow
Engineering & Materials Science
Reynolds number
Engineering & Materials Science
Turbomachinery
Engineering & Materials Science
Turbulence models
Engineering & Materials Science
Volume fraction
Engineering & Materials Science
Momentum
Engineering & Materials Science
Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Research Output 1990 2019
An Assessment of Computational Fluid Dynamics Cavitation Models Using Bubble Growth Theory and Bubble Transport Modeling
Kinzel, M. P., Lindau, J. W. V. & Kunz, R. F., Apr 1 2019, In : Journal of Fluids Engineering, Transactions of the ASME. 141, 4, 041301.Research output: Contribution to journal › Article
Bubbles (in fluids)
Cavitation
Computational fluid dynamics
Liquids
Vapors
1
Citation
(Scopus)
A multiphase level-set approach for all-Mach numbers
Kinzel, M. P., Lindau, J. W. V. & Kunz, R. F., May 15 2018, In : Computers and Fluids. 167, p. 1-16 16 p.Research output: Contribution to journal › Article
Mach number
Conservation
Compressible flow
Multiphase flow
Advances and applications in comprehensive Gearbox Aero-thermodynamics and tribology simulation
McIntyre, S. M. & Kunz, R. F., Jan 1 2017, 73rd American Helicopter Society International Annual Forum Special Sessions 2017. American Helicopter Society, Vol. 2017-May. p. 242-261 20 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Tribology
Thermodynamics
Lubrication
Computational fluid dynamics
Multiphase flow
1
Citation
(Scopus)
A unified homogenous multiphase CFD model for cavitation
Kinzel, M. P., Lindau, J. W. V. & Kunz, R. F., 2017, Symposia: Fluid Measurement and Instrumentation; Fluid Dynamics of Wind Energy; Renewable and Sustainable Energy Conversion; Energy and Process Engineering; Microfluidics and Nanofluidics; Development and Applications in Computational Fluid Dynamics; DNS/LES and Hybrid RANS/LES Methods. American Society of Mechanical Engineers (ASME), Vol. 1B-2017.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Cavitation
Computational fluid dynamics
Bubbles (in fluids)
A physics-based tribology model and parametric assessments of loss-of-lubrication using reduced-order system level analysis
Yu, Q., Mclntyre, S., Kunz, R. F., Chang, L. & Bill, R., Jan 1 2016, 72nd American Helicopter Society International Annual Forum 2016: Leveraging Emerging Technologies for Future Capabilities. American Helicopter Society, Vol. 3. p. 2630-2645 16 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Tribology
Lubrication
Physics
Gears
Heat transfer