Dynamic Anthropogenic activitieS impacting Heat emissions (DASH v1.0): Development and evaluation
| Main Authors: | Capel-Timms, Isabellla, Smith, Stefan Thor, Sun, Ting, Grimmond, Sue |
|---|---|
| Format: | info software Journal |
| Terbitan: |
, 2020
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| Subjects: | |
| Online Access: |
https://zenodo.org/record/3745524 |
Daftar Isi:
- Dynamic Anthropogenic activitieS impacting Heat emissions (DASH v1.0): Development and evaluation DASH - is undergoing significantly development (e.g. being made more generic, more efficient, more capabilities). Currently, results are benchmarked to this version. Please contact c.s.grimmond@reading.ac.uk to find out about the most appropriate source of code Funding Acknowledgement: UK-China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund EPSRC (Reading) NERC APEx:10.13039/501100000690::NE/T001887/1 ERC-2019-SyG: 855005 urbisphere Overview Source code and input data for v1.0 of the Dynamic Anthropogenic activitieS impacting Heat emissions model. DASH considers both urban form and function in simulating QF by use of an agent-based structure that includes behavioural characteristics of city populations. This allows social practices to drive the calculation of QF as occupants move, varying by day type, demographic, location, activity, socio-economic factors and in response to environmental conditions. DASH has simple transport and building energy models to allow simulation of dynamic vehicle use, occupancy and heating/cooling demand, with subsequent release of energy to the outdoor environment through the building fabric. The entire model comprises two parts: 1. Agent interaction (under 2.movementtravel) 2. Agent reaction (under.energyQfcalcs README files can be found in each folder with quick start guides for each. 1.dataprocessing Currently in python 3.7 ## what does this code do? Various scripts transform elements of raw data to input data readable by DASH ## what does this folder include? Input Data Processed Data ─ source-code # scripts for creating input data from raw data ## how to run this code? 1. Different elements are currently run separately. # 2.movementtravel ## what does this code do? 1. Determines the travel and movement behaviours. 2. Distributes people across the city. 3. Provides occupancy and transport levels across the study area. ## What does this folder include? run `tree . -d -L 1` to show the following (may vary over time) Data # input data ├── Runs # runs with cfg and output ├── py2-backup.tgz # backup of py2 files before 2to3 conversion ├── gen-traveltime-py2 # script to generate travel functions in py2 └── source-code # source code ## How to run this module Before run this code, 2to3 was executed to convert all code into py3. the py2 version is secured into `py2-backup.tgz` archive QUICK START Run the code: 1. entry point: `source_code/Main.py`: `python3 Main.py`# 3.energyQfcalcs## what does this code do? 1. To determine the occupancy levels in buildings 2. To determine distribution of traffic on transport network 2. To calculate energy use - giving Qf (B, T, and M)## what does this folder include? run tree . -d -L 1 to show the following (may vary over time) ├── Data # input data ├── Runs # runs with cfg and output ├── py2-backup.tar # backup of py2 files before 2to3 conversion └── source-code # source code## how to run this code? 1. create and install the C code extension in directory `STEBBS`, run: to install the C extension. 2. main file: `Main.py` switch the same folder of this `README.md` file, run the following: python3 source_code/Main.py # 4.visualisation ## what does this code do? 1. Produces graphs of results from 2.movementtravel and 3.energyQfcalcs ## what does this folder include? run `tree . -d -L 1` to show the following (may vary over time) └── source-code # scripts for creating plots from results ## how to run this code?. Different elements are currently run separately.