UTCI thermal comfort map for Pollination.
Project description
UTCI Comfort Map
UTCI thermal comfort map recipe for Pollination.
Compute spatially-resolved Universal Thermal Climate Index (UTCI) and heat/cold stress
conditions an EPW and Honeybee model. Raw results are written into a results/
folder and
include CSV matrices of hourly UTCI temperatures, thermal conditions and heat stress
classifications. Processed metrics of Thermal Comfort Percent (TCP) can be found
in the metrics/
folder.
Methods
This recipe uses EnergyPlus to obtain longwave radiant temperatures and indoor air temperatures. The outdoor air temperature and air speed are taken directly from the EPW. A Radiance-based enhanced 2-phase method is used for all shortwave MRT calculations, which includes an accurate direct sun calculation using precise solar positions. The energy properties of the model geometry are what determine the outcome of the simulation and the model's SensorGrids are what determine where the comfort mapping occurs.
To determine Thermal Comfort Percent (TCP), all hours of the outdoors are considered occupied. For any indoor sensor, the occupancy schedules of the energy model are used. Any hour of the occupancy schedule that is 0.1 or greater will be considered occupied.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for pollination-utci-comfort-map-0.2.4.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3d1b403cbedd4583f3e12ec3d9b5edf1599004340c8a52c4434018fbcc02766d |
|
MD5 | 05fa61f68b0a14b889e9165ec6f26259 |
|
BLAKE2b-256 | 9d46c3d66cdfc4c41fdcf22ea556cdfdc320e592440b593916af7612ba34f527 |
Hashes for pollination_utci_comfort_map-0.2.4-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | a58998054575536de52fc8e8ef88238bd8f0056c805985bfa4a345bbda77766d |
|
MD5 | 7b09748fe38ed2942632f939470ffa48 |
|
BLAKE2b-256 | 1a3327d4c61160ba58e8cd9d366d63f885a3b72b9f1412cd114c71843739424d |