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 environment. Part I of this paper proposed 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, 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. Final optimization results indicate that the present choices of objective function and optimization approach are able to result in great improvement in the design and operation of ventilation systems in an office environment, with the goal of enhancing the thermal comfort and indoor air quality (IAQ) without sacrificing the energy costs of ventilation. (c) 2008 Elsevier Ltd. All rights reserved.