| 요약2 |
In a building simulation domain, physical models based on numerical approaches have been widely used to predict dynamic behaviors in building systems. These physical models can be divided into (1) a causal approach and (2) an acausal approach. The acausal approach has been highlighted in the building simulation domain. The acausal approach uses equation based models (e.g. Modelica) and provides remarkable flexible and reusable simulation environment than the causal approach (e.g. FORTRAN). However, a stochastic decision making using Modelica is underdeveloped. This study addresses the stochastic decision making of double glazing systems by coupling Modelica and Monte Carlo Sampling (MCS) method. For this study, three double glazing systems were chosen as follows: (1) 3mm Clear + 12mm Air + 3mm Clear, (2) 3mm Green + 12mm Air + 3mm Clear, (3) 3mm Clear + 12mm Air + 3mm Low-E Clear. Bayesian decision theory was employed to reflect preferences of various decision makers and to identify an optimal alternative. In this paper, it is discussed that Modelica can provide probabilistic results for robust decision making. |