Capel-Timms, Isabellla
Smith, Stefan Thor
Sun, Ting
Grimmond, Sue
2020-07-06
<ul>
<li><strong>Dynamic Anthropogenic activitieS impacting Heat emissions (DASH v1.0): Development and evaluation</strong></li>
<li><strong>DASH</strong> - 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</li>
</ul>
<p><strong>Funding Acknowledgement:</strong></p>
<ul>
<li>UK-China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund</li>
<li>EPSRC (Reading)</li>
<li>NERC APEx:10.13039/501100000690::NE/T001887/1</li>
<li>ERC-2019-SyG: 855005 urbisphere</li>
</ul>
<p><strong>Overview</strong></p>
<ul>
<li>Source code and input data for v1.0 of the Dynamic Anthropogenic activitieS impacting Heat emissions model.</li>
<li>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.</li>
<li>The entire model comprises two parts:</li>
<li>1. Agent interaction (under 2.movementtravel)</li>
<li>2. Agent reaction (under.energyQfcalcs</li>
<li>README files can be found in each folder with quick start guides for each.</li>
</ul>
<p><strong>1.dataprocessing </strong></p>
<ul>
<li>Currently in python 3.7</li>
<li>## what does this code do?</li>
<li>Various scripts transform elements of raw data to input data readable by DASH</li>
<li>## what does this folder include?</li>
<li>Input Data</li>
<li>Processed Data</li>
<li>─ source-code # scripts for creating input data from raw data</li>
<li>## how to run this code?</li>
<li>1. Different elements are currently run separately.</li>
<li># 2.movementtravel</li>
<li>## what does this code do?</li>
<li>1. Determines the travel and movement behaviours.</li>
</ul>
<ul>
<li>2. Distributes people across the city.</li>
</ul>
<ul>
<li>3. Provides occupancy and transport levels across the study area.</li>
</ul>
<ul>
<li>## What does this folder include?</li>
</ul>
<ul>
<li>run `tree . -d -L 1` to show the following (may vary over time)</li>
</ul>
<ul>
<li>Data # input data</li>
</ul>
<ul>
<li>├── Runs # runs with cfg and output</li>
</ul>
<ul>
<li>├── py2-backup.tgz # backup of py2 files before 2to3 conversion</li>
</ul>
<ul>
<li>├── gen-traveltime-py2 # script to generate travel functions in py2</li>
</ul>
<ul>
<li>└── source-code # source code</li>
<li>## How to run this module</li>
<li>Before run this code, 2to3 was executed to convert all code into py3. the py2 version is secured into `py2-backup.tgz` archive
<ul>
<li><strong>QUICK START</strong></li>
<li><strong>Run the code:</strong></li>
</ul>
<ul>
<li><strong>1. entry point: `source_code/Main.py`: `python3 Main.py`<strong># 3.energyQfcalcs</strong><strong>## what does this code do? </strong></strong></li>
</ul>
<ul>
<li><strong>1. To determine the occupancy levels in buildings</strong></li>
</ul>
<ul>
<li><strong>2. To determine distribution of traffic on transport network</strong></li>
<li><strong>2. To calculate energy use - giving Qf (B, T, and M)<strong>## what does this folder include?</strong></strong></li>
</ul>
<ul>
<li><strong>run tree . -d -L 1 to show the following (may vary over time)</strong></li>
<li><strong>├── Data # input data</strong></li>
</ul>
<ul>
<li><strong>├── Runs # runs with cfg and output</strong></li>
</ul>
<ul>
<li><strong>├── py2-backup.tar # backup of py2 files before 2to3 conversion</strong></li>
</ul>
<ul>
<li><strong>└── source-code # source code<strong>## how to run this code?</strong></strong></li>
</ul>
<ul>
<li><strong>1. create and install the C code extension</strong></li>
</ul>
<ul>
<li><strong>in directory `STEBBS`, run:</strong></li>
</ul>
<ul>
<li><strong>to install the C extension.</strong></li>
</ul>
<ul>
<li><strong>2. main file: `Main.py`</strong></li>
</ul>
<ul>
<li><strong>switch the same folder of this `README.md` file, run the following:</strong></li>
</ul>
<ul>
<li><strong>python3 source_code/Main.py</strong></li>
</ul>
<strong><strong># 4.visualisation</strong></strong></li>
</ul>
<ul>
<li><strong><strong>## what does this code do?</strong></strong></li>
</ul>
<ul>
<li><strong>1. Produces graphs of results from 2.movementtravel and 3.energyQfcalcs</strong></li>
</ul>
<ul>
<li><strong><strong>## what does this folder include? </strong></strong></li>
</ul>
<ul>
<li><strong><strong>run `tree . -d -L 1` to show the following (may vary over time)</strong></strong></li>
<li><strong><strong>└── source-code # scripts for creating plots from results</strong></strong></li>
</ul>
<ul>
<li><strong><strong><strong>## how to run this code?.</strong></strong></strong></li>
</ul>
<ul>
<li><strong><strong>Different elements are currently run separately.</strong></strong></li>
</ul>
<p>New ZipFile (7/7/2020) - <strong>BESTEST evaluation of STEBBS using EnergyPlus</strong></p>
https://doi.org/10.5281/zenodo.3933327
oai:zenodo.org:3933327
Zenodo
https://zenodo.org/deposit/2649165
https://zenodo.org/communities/luma
https://doi.org/10.5281/zenodo.3745523
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Urban
London, UK
Anthropogenic Heat Flux
DASH
Agent based model
Dynamic Anthropogenic activitieS impacting Heat emissions (DASH v1.0): Development and evaluation
info:eu-repo/semantics/other