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

被引：33

作者：

Huang, Hong ^{[1
,2
]}

Kato, Shinsuke ^{[3
]}

Hu, Rui ^{[4
]}

机构：

[1] Tsinghua Univ, Inst Publ Safety Res, Beijing 100084, Peoples R China

[2] Tsinghua Univ, Dept Engn Phys, Beijing 100084, Peoples R China

[3] Univ Tokyo, Inst Ind Sci, Meguro Ku, Tokyo 153, Japan

[4] Nikken Sekkei Ltd, Chiyoda Ku, Tokyo 102, Japan

来源：

ENERGY AND BUILDINGS | 2012年 / 47卷

基金：

中国国家自然科学基金;

关键词：

Indoor humidity environment; Moisture-buffering material; Optimization design method; CRI(H)&CRI(C) analysis; MOGA; VENTILATION SYSTEM; OFFICE ENVIRONMENT; OPTIMIZATION; AIR; CFD;

D O I：

10.1016/j.enbuild.2011.11.040

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

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. (C) 2011 Elsevier B.V. All rights reserved.

引用

页码：208 / 216

页数：9

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