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SMALL-SCALE RADIAL INFLOW TURBINE FOR WHR ORC

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SMALL-SCALE RADIAL INFLOW TURBINE FOR WHR ORC ( small-scale-radial-inflow-turbine-for-whr-orc )

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ABSTRACT Expander is the critical component of the organic Rankine cycle (ORC) and its performance has significant effect on the overall cycle efficiency. This thesis is an investigation of different strategies for efficient development and optimization of radial-inflow turbines (RIT) for small-scale ORC systems with power capacity of less than 5kWE. A novel methodology for modelling, optimization and experimental study of the small-scale RITs was proposed that encompassed the one-dimensional mean-line modelling and optimization, three- dimensional CFD analysis and optimization and experimental testing. Such methodology proved to be effective as it allows systematic investigation of the key input parameters on the turbine performance and multi-level optimization to reliably find the optimum turbine geometry that led to maximum performance. Initially, the proposed methodology was employed to develop a small-scale compressed air RIT for validation purposes. The results showed that it is possible to effectively improve the turbine performance while employing both mean-line and CFD approaches. The experimental study of the compressed air RIT revealed that the CFD model can with good accuracy predict the turbine performance and such model can be used as benchmarking model for analysing small-scale RITs. Extending the proposed approach to RITs for ORC systems that operate with organic fluids revealed that they had strong real-gas behaviour and necessitated the real-gas formulation to accurately predict their behaviour. Deficiencies of the constant turbine efficiency assumption that was commonly used in majority of the literature studies were highlighted by showing the errors that such assumption caused during the cycle analysis and fluid selection. In addition, a novel approach for integrated modelling of organic RIT with the ORC coupled with the genetic algorithm optimization technique was developed that not only alleviated the errors during fluid selection and cycle analysis but also optimized the ORC performance based on a wide range of cycle and turbine IV

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