This study focuses on modeling and dynamic identification of a reflux condenser in a batch reactor system. The model uses data from real industrial conditions, along with the Volterra series and Genocchi orthogonal polynomials, to capture the condenser’s nonlinear behavior. Identifying the dynamic behavior of the reflux condenser is essential for the safe and efficient production of phenolic resole resin in batch reactors. The condenser plays a key role in controlling the process temperature during exothermic polymerization by cooling and returning reflux material to the reactor. The model was validated with data from a 3500 kg industrial reactor, achieving a thermal energy prediction error of less than 2.5% during the critical polymerization phase. The results show that the model accurately reflects the condenser’s behavior, supporting its application in advanced control strategies for monitoring and regulating process temperature. Using these strategies can prevent uncontrolled reactions and improve operational safety and the quality of resole phenolic resin production.
Medina et al. (2026) studied this question.