Research PaperPrediction of fouling tendency in PHE by data of on-site monitoring. Case study at sugar factory

- The data of PHE fouling monitoring in sugar factory are presented.
- Mathematical model for fouling deposition development in time is proposed.
- The model parameters are determined according to industrial tests data.
- The discrepancies between test data and model results are within 8%.
- The model can be used for design and service scheduling of PHEs.

The fouling deposition on heat transfer surfaces can have significant detrimental effect on heat recuperation and jeopardise the efficiency of energy usage, increasing fossil fuels consumption and harmful environmental effects. The data of plate heat exchanger (PHE) thermal performance monitoring in fouling conditions are presented. PHE is installed at sugar factory for preheating purified thin juice before evaporation. The character of deposits on plate heat transfer surface is examined by opening PHE after the tests. It reviled the scaling and particulate fouling mechanism. Mathematical model for prediction of fouling deposition development in time is proposed, which accounts for shear stress at the channel walls and surface temperature. The model parameters are determined according to industrial tests data. The ways of fouling mitigation in PHE are discussed using the model predictions. It is shown that fouling mitigation in PHE is possible by increasing wall shear stress at the same pressure drop in heat exchanger. It requires to eliminate additional pressure loss in connections and to optimize the number of plates and their arrangement adding some plates with higher corrugation angle. These recommendations are discussed and some are implemented at the factory conditions. That allowed increase the operation time between stops for PHE cleaning maintenance. The proposed model can be directly used for design and maintenance scheduling at the specific factory. It can also be used as a preliminary guidance for energy saving reconstructions in other sugar factories. But the direct model application requires data of fouling formation monitoring to identify its parameters for work with specific media streams prone to fouling.