A generalized prediction model of waterside fouling for internally enhanced tubes in shell and tube condensers

Fouling is one of the most significant problems for internally enhanced tubes installed in the shell and tube condensers. Due to the lack of long-term test data, current fouling models are developed based on accelerated particulate fouling tests that have the low precision and hence are inapplicable for predicting combined fouling in most practical cooling tower systems. In addition, the constant values of fouling resistance (factor) recommended by the Air-Conditioning, Heating, and Refrigeration Institute (AHRI) are extremely limited under different operating conditions. To overcome these challenges, this research developed and validated two fouling prediction models based on experimental long-term tests. One of the models was in the form of a ratio of asymptotic fouling resistance of the enhanced tube to that of the plain tube (R_f^∗/R_f,p^∗), and the other one was in the form of the asymptotic fouling resistance of the directly enhanced tube (R_f^∗). Both models considered water quality, water velocity, and the tube geometries as the variables with the acceptable accuracy for prediction. 1) For the water quality, the parameter of valid concentration (C_com) of cooling water was defined in this study, which reflected the potential amount of valid components to form the fouling. 2) For the water velocity, its impacts on the two critical parameters of the fouling process: sticking probability (P) and deposit bond strength (ξ) were investigated using experimental studies. Test results showed that in enhanced tubes with the increased water velocity the sticking probability (P) decreased continuously while the deposit bond strength (ξ) initially increased, and then, decreased. 3) For the tube geometries, by taking the parameters of tube geometries as variables the multi-variable correlations of the sticking probability (P) and deposit bond strength (ξ) were developed. From the results the generalized fouling prediction model as a ratio of asymptotic fouling resistance (R_f^∗/R_f,p^∗) was recommended for the application in HVAC&R industry due to its suitability and accuracy in practical project applications.