P-07 · SEE 352

Brayton Cycle Solver

A Brayton cycle solver for gas turbine analysis. Built off the ideal textbook cycle, with advanced options such as regeneration, n-stage intercooling/reheating and component efficiencies. Built iteratively in Python with OOP architecture. Ported with Pyodide to an interactive web tool.

Code: 07
Course: SEE 352 — Applied Thermodynamics and Energy Conversion
Role: Energy Engineer
Date: Summer 2026

Ideal Brayton cycle on temperature-entropy axes: isentropic compression 1 to 2, constant-pressure heat addition to 3, isentropic expansion to 4, constant-pressure heat rejection back to 1. — The ideal cycle on temperature-entropy axes. The solver works the same four states, with losses and extra stages switched on.

Notes

Given a pressure ratio, a compressor-inlet state and a turbine-inlet temperature, the solver returns every state point around the cycle (temperature, pressure, enthalpy, entropy) together with thermal efficiency, net specific work, heat added and rejected, back-work ratio, the Carnot limit for the same temperature range, and the pressure ratio that maximises work. It plots the result on temperature-entropy axes.
At the defaults it loads with — cold-air-standard, r _p = 15, T₁ = 273 K, P₁ = 70 kPa, T _max = 873 K, advanced options off — it returns a thermal efficiency of 53.9 %, net specific work of 152.2 kJ/kg and a back-work ratio of 0.678, against a Carnot limit of 68.7 %, with the four states at 273.0, 591.8, 873.0 and 402.7 K.
Two fluid models are available: cold-air-standard with constant specific heats, and variable-c _p air read from the Cengel A-2c table. The advanced options add component efficiencies, regeneration, and n-stage intercooling and reheating, which raise the number of state points from four to as many as ten.