This dissertation investigates enhancement in accuracy of heat rate predictions in compact 痭-tube heat exchangers. The sources of error from a conventional approach based on correlating heat transfer coe眂ients, sometimes of 25{30%, are studied 痳st. These include the idealized assumptions in the procedure by which

correlations are found, the data compression that occurs through the correlation process, and the multiplicity of solutions for a proposed correlating function obtained using local regression.

To remove the non-uniqueness of regression results, a methodology based on global optimization techniques that include genetic algorithms, simulated annealing and interval analysis is introduced. Applic