NLP Deterministic Optimization of Shell and Tube Heat Exchangers with Twisted Tape Turbulence Promoters

This study presents a deterministic optimization methodology for the design of shell-and-tube heat exchangers with twisted tape turbulence promoters, focusing on minimizing the total annualized cost (TAC) while balancing thermal performance and energy consumption. A sensitivity analysis was carried out as Case I (Methanol-Water), it reveals that increasing the twist ratio (TR) reduces flow turbulence, resulting in lower fluid velocity, pressure drop (?Pi), and overall heat transfer coefficient (U). Among the turbulence promoters evaluated, twisted tapes with V-cuts achieved a 21.1% increase in U with a 52.27% increase in pressure drop, demonstrating an optimal balance between thermal enhancement and energy cost. In contrast, promoters with circular rings and multiple perforations showed the highest U improvements (26.7% and 25.8%, respectively) but incurred significant pressure drops (93.5% and 97.9%). The optimization problem has been stated as a nonlinear programming (NLP) problem and solved with the CONOPT solver. Results from two case studies emphasize the importance of operating with similar mass flows, directing the smaller flow through the tubes to maximize promoter effectiveness and achieve balanced heat transfer and pressure drop. For Case II (Residue-Water), the TAC was estimated at 11,467 USD/year, with the equipment cost as the major contributor. Case III (Water-Water) demonstrated improved balance in convective coefficients due to lower thermal effectiveness and similar mass flow rates, highlighting the positive impact of turbulence promoters on performance. This work demonstrates the potential of turbulence promoters for enhancing heat exchangers while emphasizing the importance of careful design to optimize performance and cost.