Home⇛Scientific Augustinian⇛vol. 15 no. 1 (2025)

Development of a Vertical Propeller Turbine Design Based on a Pi-Irrationality Visualization Model for Supplemental Kinetic Energy Harvesting

Tefi P. Moreno | Kevin R. Claveras | Russell N. Gorre

Discipline: Pharmacology

 

Abstract:

Wind turbines are widely utilized as alternative energy systems to reduce dependence on fossil fuels; however, improving the efficiency of Vertical Axis Wind Turbines (VAWTs) remains a significant challenge. This study aimed to optimize a VAWT design by integrating the profile derived from the visualization model of Pi as an irrational number into a Modified Blade Design (MBD) and comparing its performance with a standard Savonius Blade Design (SBD) under identical operating conditions to enhance kinetic energy harvesting. A posttest-only control group design was employed, wherein both turbine designs were tested at wind speeds of 4.52 m/s, 5.33 m/ s, and 6.10 m/s. The parameters evaluated included revolutions per minute (RPM), acceleration time (s), deceleration time (s), kinetic energy (J), specific kinetic energy per mass (J/kg), energy per swept area (J/m²), power coefficient, tip speed ratio, and voltage output (V). Computational parameter optimization was implemented in Python to determine the optimal turbine mass and drag coefficient. Results showed that the MBD exhibited lower RPM (7.17% decrease) and longer acceleration time (59.50% increase) than the SBD, but demonstrated substantially longer deceleration time (219.22% increase), indicating improved resistance to fluctuating wind conditions. Despite reduced rotational speed, the MBD produced higher total kinetic energy (197.83% increase) and energy per swept area (197.84% increase), although it exhibited lower specific kinetic energy per kilogram (14.92% decrease). The MBD also produced a higher power coefficient (84.62% increase), lower tip speed ratio (8.00% decrease), and higher voltage output (13.79% increase), highlighting improved energy capture efficiency. Optimization results further indicated that turbine performance may be enhanced through adjustments in structural parameters such as mass and drag coefficient. Overall, the findings demonstrate that integrating a Pi-irrationality visualization profile into VAWT blade design may improve turbine performance, particularly in sustaining energy output under variable wind conditions. This study highlights the potential application of mathematical visualization models in engineering design for the development of more efficient renewable energy systems.



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