Project which shows the use of the SIMULTAN data model and Python for digital twins
Project description
Reproducible code and data for this publication Digital Twin applications using the SIMULTAN data model and Python
This repository contains the three packages CO2_Prediction, MonitoringFaker and SimultanCO2Prediction to calculate the trend of the CO2-concentration in a zone ventilated by windows with real-time data.
CO2_Prediction:
Classes and methods to calculate the CO2 concentration trend for a zone were implemented. The calculation of the trend is done with a simple analytical model, where the air flow rate is calculated as a function of the opening area and the temperature difference between the inside and outside according to OENORM B 8110-3. With the calculated air volume flow, the CO2-concentration inside and outside and the CO2-emission in the zone, the trend of the CO2-concentration can be calculated for constant boundary conditions. In addition, classes for a database and sensors were implemented using SQLalchemy, which can read and write the latest measured value of a sensor in a database. The measurements are then used as a boundary condition for the calculation of the CO2 concentration.
MonitoringFaker
Generate measurement values for sensors, which initializes the databases for the sensors in the imported project and writes artificially generated measurement values to the databases.
SimultanCO2Prediction
Package, which integrates the SIMULTAN data-model in the CO2_Prediction-package.
Installation
Install via pip:
pip install https://github.com/DerMaxxiKing/DigiTwin_CO2_SampleProject
This installs the packages CO2_Prediction, MonitoringFaker and SimultanCO2Prediction
Usage:
Run fake measurement generation:
Run in cmd:
run_measurement_generator
Run CO2 trend calculation:
Run in cmd:
run_co2_prediction
SIMULTAN model
The SIMULTAN model can be found here:
Resources
├── database_test.simultan
Databases
The database with the measurements can be found here:
Resources
├── measurements.db
The database with the weather data can be found here:
Resources
├── weather_database.db
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