@devang and @mostapha and @chris I am doing an indoor comfort study. I measured temperatures in a room over a full year using a data logger. The room is made of concrete block double walls, concrete floor and tile roof with ceiling underneath. The room neither has extra insulation nor any air-tighten measures. I visualised the measured temperatures using the LB adaptive comfort tool. It reveals that the room is comfortable 55% of the time.
I have applied psychrometric analysis to same room using epw data inputs. The same room is now comfortable only 5% of the time. After applying passive design measures this increases to 69%. The largest contributor to extra comfort is “conserve internal heat gains”. This leads me to ask, what are the baseline assumptions for the LB psychrometric chart tool (i.e. what sort of envelope materials and building would yield comfort 5% of the time?). Apologies for long-winding question.
Thanks so much.
The comfort polygon in the psychrometric chart is generated using the PMV model (using the 4 inputs on the component that are beneath the temperature, humidity and pressure). The PMV model is only designed to estimate comfort inside buildings that do not have operable windows.
The adaptive chart uses a completely different model, which is only designed to estimate comfort in buildings where occupants can open the windows.
The polygons on the psych chart are a very rough/hacky way to estimate the hours that can be made comfortable with certain strategies.
I recommend watching this series:
Thanks Chris for the response, explanation and video link. I’ll watch the videos.
Many thanks!