group
What campus are you from?
Daytona Beach
Authors' Class Standing
Kalkamanali Satvaldy, Senior Anuranan Bharadwaj, Senior Vincent Shi, Senior
Lead Presenter's Name
Kalkamanali Satvaldy
Faculty Mentor Name
Luis E. Ferrer-Vidal España-Heredia
Abstract
This research presents an integrated study combining computational modeling and experimental validation to enhance the design and performance characterization of small-scale turbine systems. The theoretical component focuses on developing an object-oriented Python code for the preliminary design and performance prediction of radial turbines, capable of generating velocity triangles, thermodynamic properties, and geometric parameters from user-defined inputs. The tool employs Whitfield-based correlations and fundamental gas-dynamic relations to estimate exit flow parameters, work ratio, and efficiency, offering flexibility for expansion into geometry export and CAD integration. Complementing the computational model, the experimental component aims to improve the aerodynamic testing capabilities of the axial turbine cascade rig through instrumentation and analysis upgrades. A Python-Excel integrated tool was created to determine turbine blade throat openings and deviation angles using Aungier’s correlations and Mach-dependent flow effects. Concurrently, a custom horizontal Kiel probe rake is being designed and fabricated to enable multi-point total pressure measurements, replacing single-point probes and improving data resolution. Together, these efforts establish a cohesive framework for turbomachinery design, analysis, and experimental validation. The combined methodology demonstrates how computational and experimental approaches can jointly advance the understanding of turbine aerodynamics and streamline future research and educational workflows in jet propulsion and power systems.
Did this research project receive funding support from the Office of Undergraduate Research.
No
Integrated Computational and Experimental Analysis of Turbine Aerodynamics
This research presents an integrated study combining computational modeling and experimental validation to enhance the design and performance characterization of small-scale turbine systems. The theoretical component focuses on developing an object-oriented Python code for the preliminary design and performance prediction of radial turbines, capable of generating velocity triangles, thermodynamic properties, and geometric parameters from user-defined inputs. The tool employs Whitfield-based correlations and fundamental gas-dynamic relations to estimate exit flow parameters, work ratio, and efficiency, offering flexibility for expansion into geometry export and CAD integration. Complementing the computational model, the experimental component aims to improve the aerodynamic testing capabilities of the axial turbine cascade rig through instrumentation and analysis upgrades. A Python-Excel integrated tool was created to determine turbine blade throat openings and deviation angles using Aungier’s correlations and Mach-dependent flow effects. Concurrently, a custom horizontal Kiel probe rake is being designed and fabricated to enable multi-point total pressure measurements, replacing single-point probes and improving data resolution. Together, these efforts establish a cohesive framework for turbomachinery design, analysis, and experimental validation. The combined methodology demonstrates how computational and experimental approaches can jointly advance the understanding of turbine aerodynamics and streamline future research and educational workflows in jet propulsion and power systems.