Optimum design for indoor humidity by coupling Genetic Algorithm with transient simulation based on Contribution Ratio of Indoor Humidity and Climate analysis

• Published in: Energy and buildings Vol. 47; pp. 208 - 216
• Main Authors: HONG HUANG, KATO, Shinsuke, RUI HU
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier 01.04.2012
• Subjects: Applied sciences; Buildings. Public works; Climate; Computation methods. Tables. Charts; Computer simulation; Design engineering; Exact sciences and technology; Genetic algorithms; Humidity; Indoor; Moisture; Optimization; Pollution indoor buildings; Project management. Process of design; Structural analysis. Stresses; Moisture-buffering material; Indoor climate; Multiobjective programming; Indoor humidity environment; Optimization design method; Buffering capacity; analysis; Optimization; Optimal design; Analysis method; Genetic algorithm; Humidity; MOGA; Objective function; Simulation model; CRI
• ISSN: 0378-7788
• DOI: 10.1016/j.enbuild.2011.11.040

In recent years, the capacity to remove moisture is relatively decreased because houses and office buildings are being built with high airtightness and thermal insulation. It is important to maintain indoor humidity at an appropriate level. This study presents a method for the optimum and reliable design of indoor humidity with moisture-buffering materials. An optimum design system was developed using Genetic Algorithm (GA) and the transient simulation for the indoor humidity environment based on Contribution Ratio of Indoor Humidity (CRI(H)) and Contribution Ratios of Indoor Climate (CRI(C)) analysis. To confirm the availability of the proposed system, a living room with a number of heat and moisture sources was analyzed. As design parameters, the amount and arrangement of moisture-buffering materials were analyzed. Two case studies, including single objective and multi-objective optimization problems, were conducted. The purpose of the single objective optimization problem was to prevent high humidity in the indoor environment. In the multi-objective optimization problem, a reliable indoor humidity environment was achieved, and the initial cost of the materials was also used as an objective function. The Pareto-optimal solution sets were analyzed, and the method was proven to be useful for the optimization of indoor humidity.