Identifying and mitigating energy losses in Tesla turbines: A study on CFD optimization

Abstract This study investigates the flow dynamics and energy losses of Tesla turbines using Computational Fluid Dynamics with OpenFOAM. Our goal is to identify the main sources of energy loss. Four main sources of energy loss were identified. The most significant loss occurred during the conversion of pressure energy to kinetic energy, estimated to range from to of the total energy. Energy losses due to leaks between the rotor and the casing were also quantified, ranging from to of the kinetic energy at peak efficiency points. Design modifications, such as incorporating a nozzle at the entrance of the turbine, can improve efficiency. These findings highlight specific areas for efficiency improvement, offering opportunities for improved turbine design and integration into energy‐generation systems.

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Institutions

Publication Details

Journal
Energy Science & Engineering
Published
2024-09-19
DOI
https://doi.org/10.1002/ese3.1863
Citations
1
Primary Topic
Turbomachinery Performance and Optimization
Type
article
Field-Weighted Citation Impact
1.30

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article

Identifying and mitigating energy losses in Tesla turbines: A study on CFD optimization

Yovany Galindo, Alberto Beltrán, José Núñez
1 citations
Energy Science & Engineering
Turbomachinery Performance and Optimization
1.30
article

Identifying and mitigating energy losses in Tesla turbines: A study on CFD optimization

Yovany Galindo, Alberto Beltrán, José Núñez
article en
1 citations

Abstract

Abstract This study investigates the flow dynamics and energy losses of Tesla turbines using Computational Fluid Dynamics with OpenFOAM. Our goal is to identify the main sources of energy loss. Four main sources of energy loss were identified. The most significant loss occurred during the conversion of pressure energy to kinetic energy, estimated to range from to of the total energy. Energy losses due to leaks between the rotor and the casing were also quantified, ranging from to of the kinetic energy at peak efficiency points. Design modifications, such as incorporating a nozzle at the entrance of the turbine, can improve efficiency. These findings highlight specific areas for efficiency improvement, offering opportunities for improved turbine design and integration into energy‐generation systems.

Energy Science & EngineeringVol. 12(10)
Universidad de Morelia (MX), Universidad Latina de América (MX), Instituto Tecnológico de Morelia (MX), Universidad Nacional Autónoma de México (MX)
Consejo Nacional de Ciencia y Tecnología, Sistema Nacional de Investigadores
Openalex Percentile: Top 13%
Turbomachinery Performance and Optimization
1.30
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Identifying and mitigating energy losses in Tesla turbines: A study on CFD optimization — Yovany Galindo, Alberto Beltrán, et al. · Energy Science & Engineering (2024) | TGRS Research Map | TGRS