Theoretically study of fuel vapor turbine for hypersonic vehicles: Wide operating range performance enhancement via a novel corrected loss model

AbstractThe fuel vapor turbine is widely recognized as an ideal power generation technology to address the electrical energy supply challenges of hypersonic vehicles. However, current research of fuel vapor turbines predominantly mainly focuses on the design operation. Therefore, a mean-line-based low-fidelity performance prediction model incorporating loss mechanisms is established and calibrated using three-dimensional simulation results. Subsequently, an optimization study on turbine performance under off-design conditions was conducted based on the Non-dominated Sorting Genetic Algorithm II and the calibrated low-fidelity performance prediction model. Results indicated that the variable composition case exhibits a more significant efficiency drop under low-pressure and low-temperature conditions. Within the given operating conditions, the fuel vapor turbine efficiency decreased from the design value of 80.52% to a minimum of 53.87%. The corrected low-fidelity performance prediction model exhibits exceptional predictive capability, with efficiency discrepancies relative to numerical simulations consistently below the 2% threshold across the entire operational envelope. The optimized fuel vapor turbine demonstrates a significant improvement in average efficiency across variable operating conditions compared to the baseline design. Under an inlet total pressure of 3.6 MPa, the absolute efficiency enhancement reaches 21.4%. This study provides a theoretical foundation for enhancing the performance of fuel vapor turbine power generation systems across a wide range of operating conditions, thereby facilitating their engineering applications.