Meanline method for design and off-design turbine performance predictions

Abstract: Early designs are often based on rough estimations and assumptions. Such is also the case when designing space turbines that power rocket engine fuel pumps which generally have obscure performance and size requirements. Often times, this leads to unique, single-use designs. This complicates and restricts the amount of possible testing. To aid in this early design process and to help predict turbine performance in various scenario, a one-dimensional meanline method program is developed in Python. It is able to perform calculations for various geometries and operating conditions by varying inlet conditions such as temperature, pressure, rotational speed and pressure ratios. The program itself makes use of general turbine knowledge with relevant literature in aerodynamic loss modeling, outlet angle calculations and pressure convergence. The accuracy of the program's output has been continuously validated against different types of turbines and shown adequate correlations to real-world performance data, down to half a percentage in relative error for certain cases. Case-specific tailoring to fit certain operating conditions and fast run times of approximately 5 seconds will provide the user with the possibility of performing turbine performance characteristics with ease.