Optimization of Ventilation Systems in Office Environment, Part Ii: Results and Discussions

Whether one considers the issues related to office workers’ well-being and productivity, or the issues from an energy and environmental perspective, there are clear evidences in favor of improving the quality of office built environment. This paper is concerned with the development and implementation of a practical and robust optimization scheme, with the goal of aiding the office building designers and operators to enhance the thermal comfort and indoor air quality (IAQ) without sacrificing energy costs of ventilation. The path taken is a simulation-based optimization approach by using computational fluid dynamics (CFD) techniques in conjunction with genetic algorithm (GA), with the integration of an artificial neural network (ANN) for response surface approximation (RSA) and for speeding up fitness evaluations inside GA loop. In this part of the work, the results from data preparation for ANN model construction, ANN training and testing, and sensitivity analysis (regarding the impact of weighting factors in the objective function on the optimization results) are presented.