Cooling towers are utilized in a wide variety of industrial applications for dissipating waste heat into the atmosphere. The design of effective, economical, and environment-friendly cooling towers is paramount for industrial applications. In this thesis, a numerical optimization framework for cooling tower design is presented as an innovative alternative to the time consuming trial-and-error design process. The analysis component of the framework predicts the thermal and hydrodynamic performance of mechanical induced-draft counter-flow wet cooling towers through the solution of a one-dimensional zone-specific thermodynamic model and air draft equation. Furthermore, the analysis component of the framework evaluates the environmental impact of cooling tower operation in cold climatic conditions by predicting the visible plume length through the solution of an integral axisymmetric turbulent plume model. The optimization component of the framework embodies the iterative design procedure by applying numerical optimization. The numerical optimization framework is used to solve three design problems:​ (i) airflow selection;​ (ii) size optimization;​ and (iii) size optimization with visible plume constraint. The method of feasible directions (MFD) is the optimization algorithm to solve the first design problem, while the other two design problems are solved by a multi-objective genetic algorithm (MOGA). The presented investigation related to the size optimization problem is the first attempt in the literature to study quantitatively the best possible trade-offs between the capital and operating costs of the cooling tower. Additionally, visible plume constraint is introduced for the first time in the thermo-economical performance optimization of wet cooling towers.

The results obtained from the airflow selection show that increasing the fill height leads to smaller airflow requirements which decreases fan power consumption. There is a threshold fill height beyond which fan power savings become small. This threshold is determined by the location in the fill where the air becomes saturated with vapor. The results obtained from the size optimization show that the design with the lowest capital cost delivers a desired cooling performance at peak operating conditions with 3.1% more air mass flow rate, 13.0% less fill height, and 37.9% less tower frontal area with respect to the design with the lowest operating cost. The design with the lowest capital cost has 39.2% less cooling tower volume on account of a 141.0% increase in fan power consumption. On the other hand, the design with the lowest operating cost delivers the desired cooling performance at the same operating conditions with 3.0% less air mass flow rate, 14.9% more fill height, and 61.0% more tower frontal area with respect to the design with lowest capital cost. The design with the lowest operating cost consumes 58.5% less fan power on account of a 64.5% increase in cooling tower volume. The results obtained from the size optimization with visible plume constraint show that the visible plume length is reduced by one order of magnitude with 26% more air mass flow rate, 48% less fill height, and 6% more tower frontal area with respect to an optimal cooling tower design with the same volume when the cooling tower operates at an ambient temperature of 12.5C and relative humidity of 40%. Such an optimal design consumes 55% more fan power in order to provide an adequate entrainment of ambient air into the plume core, which helps in accelerating plume dilution. On the other hand, the same results show that, at the same relative humidity, the suggested design becomes insufficient in reducing the visible plume length as the ambient temperature drops below 10.0C. In such ambient conditions, the effect of a high condensation rate overcomes the effect of high plume entrainment.