A BEHAVIOURAL APPROACH TO THERMAL COMFORT ASSESSMENT

The paper¹ describes the use of field study data to identify and quantify the individual contribution's of adaptive actions by subjects in order to achieve thermal comfort. These actions include operating building controls, responding to spatial variation of room conditions, modifying posture and clothing, and metabolic rate. In order for these actions to occur, the adaptive opportunity must exist, which to some extent is a property of the building. Suggestions for the integration of adaptive effects into comfort-predicting models are made including a way of avoiding temperature as an input, which is shown to have poor correlation with reported thermal satisfaction.     

CLUSTER ANALYSIS AFTER A PARTIAL GENETIC ALGORITHM SEARCH

After a few generations of a genetic algorithm minimization, the resulting population of design vectors will typically cluster around a small number of prospective global or relative minima. If these clusters can be identified, sequential search methods can often be used to more efficiently locate the isolated minima as part of a broad-based design process. Two such “cluster analysis” algorithms are proposed here: a frequency distribution technique and a community technique. The first sorts the genetic algorithm population into intervals for each design variable, while the second identifies those individuals with many close neigbors which are also distant from other such population centers. Numerical results from two small test problems are presented to demonstrate the use of these techniques.