Abstract

The purpose of this paper is optimizing the performance parameters of a single-shaft micro gas turbine with a power of about 150 kW at the design point by modifying its centrifugal compressor geometry. According to the physics of this problem, a hybrid optimization approach (including modern and numerical optimizers) was employed. The optimization was based on the numerical simulation of each geometry using a three-dimensional Reynolds Averaged Navier-Stokes solver. The geometric parameters of the centrifugal compressor impeller constituted the design variables and the Latin hypercube was employed for sampling. To reduce the cost of the numerical calculation, the neural network was chosen for approximate modeling of the design space. The physics of the optimization problem ahead was identified and a state-of-the-art optimization process was presented accordingly. Furthermore, a detailed discussion was conducted on the design space transparency, convergence criteria, and optimum design selection, the disadvantages of current optimization processes and the advantages of the present one were explained. NASA CC3 compressor was scaled down for the baseline engine, which is a 150 kW single-shaft gas turbine. This engine was optimized using the proposed optimization process and a significant improvement was achieved, where efficiency increased by 13.93% and power by 11.07%, and the specific fuel consumption decreased by 12.15%. Furthermore, despite the constant impeller tip diameter and rotational speed, in the optimum compressor, the mass flow increased by 2.22% and the pressure ratio by 29.62% compared to the baseline compressor, while the isentropic efficiency not only did not decrease but also increased slightly (0.2%). However, the operating range decreased by 12.64%.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call