Dynamic Urban Development Model

Dynamic Urban Development Model

With this model we demonstrate the combination of the DeCodingSpaces synthesis and analysis components in order to link them with a basic urban dynamics simulation. The definition creates a synthetic settlement and simulates the distribution of population and workplaces over time. The results from this simulation control the development of the individual blocks including the generation of pacelling patterns and the placing of buildings of various typologies.
The model was first introduced at the seminar “Applied System Dynamics for Urban Modeling and Simulation” of the Professorship for Computational Architecture at the Bauhaus-University Weimar, 2018. It is based on the models described in the article Urban Simulation with Grasshopper for Rhino3D.

Research Team: Reinhard Koenig (contact author), Martin Bielik, and Sven Schneider

Requirements

The Grasshopper files are created for Grasshopper (build 0.9.0076) with Rhino3D v.5. To open and run the models you need to instal the Anemone plugin (we used version 0.4), and the DeCodingSpaces-Toolbox (you need the version from 24.04.2018 or later).

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Grasshopper Definition Dynamic Urban Model

You may find updated versions of the script on the course website Urban Modeling and Simulation.

The animation shows how the simulation results are used as basis for the development of individual blocks.

 

 

The video demonstrates step by step the combination of the DeCodingSpaces synthesis and analysis components with the urban development simulation.
Urban Simulation with Grasshopper for Rhino3D

Urban Simulation with Grasshopper for Rhino3D

Dynamic urban development simulation models are usually separate to urban planning tools making it difficult to test the consequences of urban planning variants directly without switching between expert tools. This paper presents an approach to integrating system dynamics simulation at various scales and abstractions in the visual programming environment Grasshopper for Rhino3D. We demonstrate how Grasshopper may be used with additional customized components as a flexible integrated urban planning and simulation framework. For this purpose, we present three urban planning model examples: The first is a classical system dynamics simulation that abstracts from spatial elements. The second adds spatial relations in terms of distances between locations in a grid. The third shows how to represent a city in more details and adds a network analysis module for more precise distance calculations. As result, we demonstrate a highly flexible approach for integrating simulations for various aspects that predict the behavior of an urban system in order to facilitate more sustainable urban planning processes. The main drawback of this new level of flexibility is the relatively slow execution time for complex simulations.

Research Team: Reinhard Koenig (contact author), Martin Bielik, and Sven Schneider

Requirements

The Grasshopper files are created for Grasshopper (build 0.9.0076) with Rhino3D v.5. To open and run the models you need to instal the Anemone plugin (we used version 0.4), and for the models 3 and 4 the DeCodingSpaces-Toolbox (we used version 2018.01). Download all four Grasshopper models.

Acknowledgement

This page contains accompanying material for the SimAUD 2018 conferece paper System Dynamics for Modeling Metabolism Mechanisms for Urban Planning.

Presentation at SimAUD conference, TU Delft, 7th of June 2018

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1. Wolf-Sheep-Predation Test Model

In the first model, we reproduced the wolf-sheep-predation system dynamics model from the NetLogo model library in Grasshopper.

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2. Abstract urban dynamics model

The second model implemented an abstract urban dynamic system that includes the development of population size, number of jobs and food production (stocks). These stocks depend on various relationships between each other (flows) and on the available areas for the corresponding land uses.

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3. Grid-city model

The third model uses a 12 × 8 = 96 cells grid. Based on the all-pair Manhattan distances between the cells, we compute for each iteration the attractivity of a cell for new population or workplaces.

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4. Net-city model

For the fourth model we use the real geometry of a city and compute the distances between locations by means of shortest paths in the street network. For this demonstration, we used the central part of the city of Weimar in Germany.

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For learning more about the implementation of the Net-City model, please look at the post on our SimAUD Workshop Network analysis based dynamic urban simulation in Grasshopper.

The last model is further extended. Please look at the article Dynamic Urban Development Model.

Related Publications

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Presentation at IWCEE18 – VI International Workshop on Computational Economics and Econometrics, Rome, June 27th 2018

Session: Transitions towards sustainable and resilient cities: analytic and modelling approaches

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