Abstract
A transient method, based on an inverse heat conduction solution, for experimentally determining the distribution of local heat transfer rates on the surface of a body has been numerically evaluated. The particular interest is in situations in which the heat transfer coefficients are relatively low and in which there are relatively large changes in the heat transfer coefficient over the surface of the body being considered. In the method, a solid body of the shape being investigated, constructed from a low conductivity material, is heated to a uniform temperature and then exposed to a test flow. Using a layer of temperature sensitive crystal placed over the surface of this model or by other means, the time taken for the temperature at a relatively small number of selected points on the surface to reach a selected value is determined. The surface heat flux rate distribution is then found from these measured times using a simple inverse heat conduction method. The feasibility of this method has been evaluated by considering relatively low Reynolds number flow over a square cylinder and natural convective flow over a circular cylinder. Known local heat transfer coefficient distributions for these situation have been applied as boundary conditions in the numerical solution of the transient cooling of a the “experimental” models. These solutions are used to generate “measured” data i.e. to generate simulated experimental data. The inverse heat transfer method has then been used to predict the local heat transfer coefficient distribution over the surface and the predicted and input distributions have been compared. The effect of uncertainties in the experimental measurements on this comparison has then been evaluated using various assumed uncertainty values. The results of the study indicate that the proposed method of measuring local heat transfer coefficients is capable of giving results of good accuracy.
Local heat transfer estimation in microchannels during convective boiling under microgravity conditions: 3D inverse heat conduction problem using BEM techniques
