Step 2 - Open the downloaded .csv file.
Each column represents an unique input parameter. It's important that the name of each column remains unchanged. For your reference each template contains some example data, please replace them with your data. If you do not have data for a certain parameter, simply fill all the rows with a representative constant value. For example, if you conducted the study in a office and did not log the metabolic rate, you may enter a constant value of 1.2 in the "Metabolic rate [met]" column. Every row must contain a value for each parameter.
Please enter the average air speed and the clothing insulation as inputs. The tool automatically calculates the relative air velocity and the dynamic clothing insulation for moving occupants for you. These values will be appended as new columns in the result file.
Step 3 - Select the file to upload by clicking on the "Choose File" button below. Then press the "Upload File" button. The algorithm will automatically calculated the following indexes:
Step 4 - A file named "results.csv" will be automatically downloaded by your browser which contains all the results. The results are calculated using the pythermalcomfort Python package.
Some users may experience issues when uploading very large files. We are sorry for the inconvenience caused and we have created a Google Codelab notebook that you can use to calculate the thermal comfort indices.