Estimation of thermal and flow fields due to natural convection using support vector machines (SVM) in a porous cavity with discrete heat sources

Support vector machines (SVM), a soft programming technique, has been used to estimate the temperature distribution and flow fields in a square porous enclosure heated discretely by three isothermal heaters from the left vertical wall. Right vertical wall of the cavity was isothermal but it has colder temperature than the heaters while remaining walls were adiabatic. A database was prepared by solving the governing equations which were written using Darcy flow model. Using finite difference method to discretize the equation, a computational fluid dynamics (CFD) code was written. A correlation was developed between Nusselt and Rayleigh numbers. Using obtained database, further values of temperature and velocities were estimated by SVM technique at different Rayleigh numbers and locations of heater. It was observed that SVM was a useful technique on estimation of streamlines and isotherms. Thus, SVM reduces the computational time and helps to solve some cases when CFD fails to solve due to numerical instability.