Website Main features The code stems from the minimization of the free energy of the system by using Lagrange multipliers combined with a Newton-Raphson method, upon condition that initial gas properties are defined by two functions of states (e.g., temperature and pressure) When temperature is not externally imposed, the code retrieves a routine also based on Newton-Raphson method to find the equilibrium temperature Solve processes that involve strong changes in the dynamic pressure, such as detonations and shock waves in the steady state Find the equilibrium conditions of the different phenomena undergoing behind the shock: molecular vibrational excitation up to dissociation, and electronic excitation up to ionization, thereby providing the properties of the gas in plasma state within the temperature range given by the NASA’s 9-coefficient polynomial fits. Calculate the chemical equilibrium composition of a mixture by selecting which species can react or remain chemically frozen (inert). The corresponding thermodynamic properties of the species are modelled with NASA’s 9-coefficient polynomial fits, which ranges up to 20000 K, and the ideal gas equation of state Results are in excellent agreement with NASA’s Chemical Equilibrium with Applications (CEA) program, CANTERA, Caltech’s Shock and Detonation Toolbox, and TEA All the routines and computations are encapsulated in a more comprehensive and user-friendly GUI The code is in it’s transition to Python Display predefined plots (e.g., molar fraction vs equilence ratio) Export results in a spreadsheet (requires Excel) Export results as a .mat format Chemical equilibrium problems TP: Equilibrium composition at defined temperature and pressure HP: Adiabatic temperature and composition at constant pressure SP: Isentropic compression/expansion to a specified pressure TV: Equilibrium composition at defined temperature and constant volume EV: Adiabatic temperature and composition at constant volume SV: Isentropic compression/expansion to a specified volume Shock calculations: Pre-shock and post shock states Equilibrium or frozen composition Incident or reflected shocks Chapman-Jouguet detonations and overdriven detonations Reflected detonations Oblique shocks/detonations Shock polar for incident and reflected states Hugoniot curves Ideal jump conditions for a given adiabatic index and pre-shock Mach number Rocket propellant performance assuming: Infinite-Area-Chamber model (IAC) Finite-Area-Chamber model (FAC) All the routines and computations are encapsulated in a more comprehensive and user-friendly GUI The code is in it’s transition to Python Export results in a spreadsheet Export results as a .mat format Display predefined plots (e.g., molar fraction vs equilence ratio) This project is also part of the PhD of Alberto Cuadra-Lara.

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