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Published July 8, 2020 | Version 1.2
Software Open

Dynamic Anthropogenic activitieS impacting Heat emissions (DASH v1.0): Development and evaluation

  • 1. University of Reading
  • 2. University of Reading, Past: KCL, Indiana University

Description

  • 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.

New ZipFile (7/7/2020) - BESTEST evaluation of STEBBS using EnergyPlus

 

8/7/20 Update data file - DASH-X-GMD-results.zip

8/7/20 code and input data DASH-X-GMD-1.0r.tar.gz

 

 

 

Files

DASH-X-GMD-results.zip

Files (1.3 GB)

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md5:422191b55050a1b2fb9454219a9aff7d
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689.5 MB Preview Download
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Additional details

Related works

Funding

APEx: An Air Pollution Exposure model to integrate protection of vulnerable groups into the UK Clean Air Programme NE/T001887/1
UK Research and Innovation

References

  • Capel-Timms I, ST Smith, T Sun, S Grimmond (in review) Dynamic Anthropogenic activitieS impacting Heat emissions (DASH v1.0): Development and evaluation gmd-2020-52