Abstract
Inverse engineering problems have many applications in various industries. While most of the research is focused on the steady state problems, transient heat transfer also has potential with regard to application and research. A detailed study of the forward transient wall plume is developed and the analytical results are used to build an inverse solution methodology. The goal of the inverse solution is to find the heat source location and energy input or strength using a few, limited, data points downstream. The methodology involves developing interpolating functions that relates transient features to plume strength and location at each location downstream of the plume and then using these functions to set up a system of equations. This system of equations is then solved to find the unknown variables. A search based optimization method, particle swarm optimization (PSO), is used to find the optimal sensor locations downstream of the plume in order to minimize the number of downstream data points needed for an accurate prediction.