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

doi: 10.1002/ese3.1863
AbstractThis 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.
Tesla turbine, Technology, efficiency, T, Science, Q, OpenFOAM, energy losses
Tesla turbine, Technology, efficiency, T, Science, Q, OpenFOAM, energy losses
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
