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Design with Comfort: Enhancing the psychrometric chart with radiation and convection dimensions

See Live Demo

http://comfortch.art/

What is this chart?

An expansion to the classic pschrometric chart, including the effects of radiation heat exchange on human comfort.

About the Repo

  • The jupyter_notebook folder contains a .ipynb file in which you can play with the source code, and see how the app works
  • The app folder contains the python source code in its plain format, fully bundled as a responsive flask web app
    • within the app folder, the calculate_chart.py contains the algorithm, while application.py serves the algorithm on the website via templates/graphs.html

Reference

A paper submitted by Eric Teitelbaum, Prageeth Jayathissa, Clayton Miller and Forrest Meggers to the journal Energy and Buildings

This paper presents a makeover of the psychrometric chart using a new color-shading method that allows the whole chart to be considered comfortable based on the variation of non-air temperature comfort parameters such as mean radiant temperature, air movement, and the transitional behavior of occupants. These representations allow for thinking outside the thermal comfort box with the use of innovative system types and comfort feedback for occupants. The new chart representations are then applied on several real-world scenario datasets to illustrate the value in practice. An open-source repository is available for other researchers to reproduce the charts and color-shading for their own projects using Python and the matplotlib visualization library. The chart is also served at comfortch.art.

Run App Locally

  1. Pull the repo git@github.com:buds-lab/psychrometric-chart-makeover.git, and cd psychrometric-chart-makeover

  2. Start the virtual environment source v_env/bin/activate

  3. cd app: Here you can find three files, application.py runs the flask web server, calculate_cart.py is the core calculation script, templates/graphs.html is the html template that renders the website.

  4. Run the app locally

From the route folder, in terminal, run

export FLASK_APP=application.py flask run

You may need to pip3 install flask first

The app shoudld be locally hosted at http://127.0.0.1:5000/

Deploy to AWS

  1. Install the Elastic Beanstalk CLI https://docs.aws.amazon.com/elasticbeanstalk/latest/dg/eb-cli3.html

  2. Run eb deploy

if it doesn't work, check out the wiki, talk to PJ or see the elastic beanstalk-flask documentaiton which is a buit sucky https://docs.aws.amazon.com/elasticbeanstalk/latest/dg/create-deploy-python-flask.html

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Adding more dimension to the psychrometric chart

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