Work and power optimization of a finite-time Brayton cycle
Chih Wu, Robert L. Kiang
Abstract
Chih Wu, Robert L. Kiang
Abstract
SYNOPSIS This paper extends the author's previous work on the formulation of criteria for comparing the performance of real and ideal processes through the use of finite-time processes. The efficiency for the finite-time Carnot cycle at maximum power is derived. This is followed by an expression for the power output of the finite-time Brayton cycle. However, this is considered to be too complex to yield simple analytical solutions and a numerical solution is given. Finally the efficiency of a Carnot cycle, a finite-time Carnot cycle and a finite-time Brayton cycle are compared, showing that the latter cycle can provide a more suitable basis for real engine design.
OpenAlex reports 50 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
SYNOPSIS This paper extends the author's previous work on the formulation of criteria for comparing the performance of real and ideal processes through the use of finite-time processes. The efficiency for the finite-time Carnot cycle at maximum power is derived. This is followed by an expression for the power output of the finite-time Brayton cycle. However, this is considered to be too complex to yield simple analytical solutions and a numerical solution is given. Finally the efficiency of a Carnot cycle, a finite-time Carnot cycle and a finite-time Brayton cycle are compared, showing that the latter cycle can provide a more suitable basis for real engine design.
Key concepts: Carnot cycle, Brayton cycle, Power (physics), Control theory (sociology), Work (physics), Mathematics, Engineering, Computer science