DigiWo

DigiWo

by | Dec 30, 2020 | Analysis, Design, Synthesis

The further explained grasshopper scripts on the building volumes generation are the output of the DigiWo reserach cooperation between the Bauhaus University Weimar, Decoding Spaces GbR and DIPLAN (today: REHUB digitale Planer). This research was supported by the ZukunftBau Program by the Federal Ministry of the Interior, Building, and Community.

In the following tutorial, you will get introduced to a set of User Objects & Components for the semi-automatic generation of residential multi-family buildings, enabling a user to generate either an urban block or a slab typology, as well as provide the scripts with a predefined sequence, that can generate variations with minimal guidance. The video below presents the concept of how the generation process is organized.

Project Team:
Iuliia Osintseva (Author), Reinhard König (Supervisor), Sven Schneider (Supervisor), Martin Bielik (Supervisor), Andreas Berst (Contributor), Egor Gavrilov (Student Assistant), Martin Oravec (Student Assistant)

If you prefer reading over watching – here is the paper on the block generation.

Download Components & User Objects

Topics covered in tutorial:

Block Generation Components

1a. Basic Block

1b. Actions:

  • Delete Edges
  • Setbacks
  • Cornerbreaks
  • Random Breaks
  • Reduce Height
  • Towers (& Envelopes)
  • Yard Buildings
  • Rooftops

Slab Generation Components

2a. Single Plot Generation

2b. Subdivision of Complex Concave Sites

2c. Multiple Plot Generation

 

 

 

Part 1:

Block Generation Components

1a. Basic setup.

In order to start the generation, the minimal requirement is a closed planar polyline in Rhino, representing the construction site. Additionally, you can add a layer with lines, representing the street axis, as well as the neighbor buildings context on a separate layer. Both those layers will then be considered during the generation.

It is as well required to select the location of the building area in order to derive the correct spacing (see the video above to learn about the spacing concept). Further, you can select multiple values for the building depth to try out, as well as set up a range of the floors count for the basic block. The output of this step is a closed block (or a range of those) around the construction plot perimeter, considering the required spacing based on the block height.

It is possible though, that the spacing should be neglected, in case that your construction plot is placed within existing blocks and thus you should continue the street profile, placing the buildings right along the plot edge. In this case, you can just draw the lines in Rhino to indicate where the spacing should not appear, and insert them into „Baulinie“ input.

The resulting generations are gathered at the „House Instance“ data type, which is a combination of six different parameters: plot after spacing; surfaces; outlines (façade lines towards the street); inlines (façade lines towards towards the inner yard); depth of a building (as a number), floor count (as a number). Using Surface and Floor Count you can display the geometry preview as well as calculate the basic performance indicators, such as FAR, Site Occupancy, or Total Built Area.

 

Download Setup Files

1b. Actions over the Block.

 

1b.1| DELETE EDGES

This action can delete one or multiple edges to reduce the density or to solve a too narrow concave block intersection. You can select the edge to start with and decide on the number of edges to delete.

 

1b.3| SETBACKS CORNERS

This action creates a setback at the corner if the length of the adjusting edges is sufficient and the setback does not cause an intersection. You can select the edge for generation, dimensions range for the setback parameters and a seed for the randomness.

 

1b.5| CORNERBREAKS

This action creates passageways in the block‘s corners, thus avoiding the creation of corners that are rather difficult for the later apartments placement. You can change the width of the passageways as well as the directions of the cuts.

 

1b.7| ENVELOPES

This action creates a spacing envelope, as well as both summer and winter solar envelopes (with the help of LadyBug tools). Informed by those envelopes, you can place buildings that act according to the local requirements, or that are placed to minimize the influence on the lighting conditions for the neighbor buildings around the given site.

Download Grasshopper file

1b.| YARD BUILDINGS

This action creates buildings within the block yard after the user-drawn axis. You can select the depth of the yard buildings as well as their floor count.

 

1b.2| SETBACKS EDGES

This action creates a setback along an edge if the edge length is sufficient. You can selecte the edge for generation, dimensions range for the setback parameters and a seed for the randomness.

 

1b.4 | RANDOM BREAKS

This action creates passageways through the block perimeter at either random, or user-driven spots. You can select the total amount of area to delete or the total width of the passageways, as well as the number of random options to try out per input block.

 

1b.6 | REDUCE HEIGHT

This action cuts the block through the corners and reduces the floor count of some of the building fragments. Here, you can indicate the total amount of area to delete. This actions creates several different height profiles per input block.

 

1b.8 | TOWERS

This action places one or two towers along the existing block perimeter in order to gain extra area. You can select the desired area per tower, restrict the extra floors, or assign a point where the tower should be located if you dont want random generations to appear. The limit of tower height is resulting from the envelopes script.

 

1b.10 | ROOFTOPS

This action creates offsetted rooftop floors over the block perimeter. You can decide on the orientation of the buildings (toward street/yard), depth, and their overall amount.

 

1c. Examplatory Generation Sequence

In the following video you‘ll find an examplatory combination of actions for generating a bunch of various building volumes for one construction site, including the parameters setting for each of the actions. Keep in mind that the suggested sequence is not the only possible one, and you can try to arrange actions in another way, and thus receive different results.


Download Example Generation Files

*please remember to unblock the .gha components before inserting them into your Libraries folder

Part 2:

Slabs Generation Components

2a. Single Plot Generation.

Here, the generation logic is slightly different than it was the case for the block typology. Whereas block was about offsetting and further modifying the site outline, slabs is about the pattern of the placement of several simple forms on the given site. Therefore, it is possible to order several slabs at one site. First, the site edges are translated into 4 characteristic edges based on the angles between them.

Further, slabs can appear along each of the edges – as long as the space is sufficient.

 

 

Depending on the selected order of the edges, the pattern of the slabs allocation can differ greatly.

 

Accordingly, each further parameter to influence the slabs pattern is repeated four times in order to allow different variations along each of the edges. In all further parameters, the order of the values will be applied accordingly to your selected order of the site edges. You can re-adjust the edges order at any later moment of the generation. Below, you can find a short video with the overview of the parameters that you can influence for the slabs typology.

2b. Subdivision of Complex Concave Sites and Multiple Plots Generation

In case of large area plots, such generation might cause monotonous strict patterns, non usable for modern urban plannings. In order to escape this, we developed a method on the subdivision of the big concave plots into smaller and simpler sub-fragments. Those sub-plots can then be filled with slabs in a single direction.

In the previous part, there were nine parameters for each slab raw at a single edge. In the case of generating slabs for multiple plots at the same time, the number of parameters gets multiplied accordingly. As follows, taking control over generation becomes exhausting. That is why for the multiple plots generation it was decided to leave only single-direction slabs. However, the user can decide between different orientation patterns as well as subdivision patterns himself, thus still exploring the design space to a several extent. In the following video you can see the brief overview of parameters to guide the generation for the slabs typology at multiple sites.

Download Examplatory Files for the Slabs Generation

SSS12 Workshop | Parametric urban planning with Space Syntax and DeCodingSpaces-toolbox for Grasshopper

SSS12 Workshop | Parametric urban planning with Space Syntax and DeCodingSpaces-toolbox for Grasshopper

by | Jul 3, 2019 | Analysis, Synthesis

The workshop on parametric urban planning  with Space Syntax and DeCodingSpaces-toolbox for Grasshopper is hosted by:

The 12th International Space Syntax Symposium (12SSS) will be held in Beijing from 8th to 13th July 2019, at Beijing Jiaotong University

 

Lecturers:

Reinhard König                   Bauhaus University, Weimar
Martin Bielik                       Bauhaus University, Weimar
Yufan Miao                          ETH Zurich, FCL Singapore

Short summary:

During this one-day-workshop you will be introduced to methods for the analysis, generation and optimizations of urban layouts with DeCodingSpaces-Toolbox for Grasshopper. We will use existing urban context to analyze the impact of the street network configuration on different types of human behavior such as movement, walkability or land use distribution. Than we will learn how to use the analysis results to generate new street network layouts, parcels and buildings parametrically. Finally, we will demonstrate how to you evolutionary optimization to improve the performance of the parametric design toward pre-defined planning goals.

For this purpose we use Grasshopper for Rhino3D with the plugin DecodingSpaces-Toolbox. The methods are demonstrated by realistic case studies in an existing urban environments.

This workshop is intended for both practitioners and researchers interested in rapid context aware generation of urban layouts. The presented workflow let you computationally explore the design options of new urban development area with the potential to assess the site potential and inform the early planning stages.

Workshop schedule

8:30 – 9:00 Registration
9:00 – 12:25 Analysis | Street network analysis with DeCodingSpaces Toolbox

Shortest paths – Metric, Angular, Custom
Multi modal travel
Centrality measures
Weighting origins and destinations of movement
12:25 – 13:30 Lunch break
13:30 – 15:00 Generation | Parametric urban form synthesis

Street network synthesis
Street block recognition
Parametric parcelation
Parametric building generation
15:00 – 15:30 break
15:30 – 17:00

Optimization | Evolutionary optimization of street network configuration

Evolutionary optimization basics
Street network as custom chromosome
Application examples

Requirements

Install instructions

Unblocking plugins

After downloading the RequiredGHPlugins_SimAUD19.zip file, check if its unblocked before extracting the zip archive. Right click on the file > Properties > select unblock > select ok

Install components

After unlocking and extracting the RequiredGHPlugins_SimAUD19.zip archive, copy the “SimAUD19 components” folder into the grasshopper component folder. The grasshopper component folder can be found at:

 C:\Users\YourUserName\AppData\Roaming\Grasshopper\Libraries

or via grasshopper file menu:

Install user objects

After unlocking and extracting the RequiredGHPlugins_SimAUD19.zip archive, copy the “SimAUD19 user objects” folder into the grasshopper UserObjects folder. The grasshopper component folder can be found at:

 C:\Users\YourUserName\AppData\Roaming\Grasshopper\UserObjects

or via grasshopper file menu:

Enable GPU acceleration

The requirement to run the GPU accelerated street network analysis is the CUDA platform enabled NVIDIA GPU.
If this requirement is fulfilled, you have to copy the folders “Alea.CUDA.CT.LibDevice” and “Alea.CUDA.CT.Native.X86.B64.Windows” from the GPU acceleration folder to your Rhino install folder (i.e. “Program Files\Rhinoceros 6 (64-bit)\System\”).

Part 1 – Street Network Analysis

Presentation

Documentation

Interactive documentation of the Street Network Analysis toolbox.

Hands on example files:

Street Network Editing Utilities

01| CITY GRAPH STARTING EXAMPLE

Basic setup for different options how to use the street network analysis tools to calculate shortest paths and centrality measures.

Download Grasshopper file

04| CITY GRAPH ONE WAY ROADS

The underlying spatial graph is directed one, which means that to every street we can assign different distance weight in each direction. In the example we demonstrate how this can be used to model traffic regulation such as one way streets.

Download Grasshopper file

02| PARK EDGE WEIGHTING

Calculating shortest paths by assigning custom distance weights (graph edges) to the spatial network. The edge weights can be metric, angular, custom or any combination of these. Thus we can represent different concepts of distance (e.g. time, safety, cognitive distance)

Download Grasshopper file

05| CITY GRAPH CENTRALITY VERTEX WEIGHTING

When calculation street network centrality, we can assign custom weight to each graph vertex (origin and destination of shortest path). This can be used to model network in which some nodes (e.g. train station) produce more movement than others.

Download Grasshopper file

03| CITY GRAPH BUS EDGE WEIGHTING

The application of custom distance weights (edge weights) is demonstrated on the example of multi-modal transportation network. Street segment which serve as bus routes are given shorter distance representing travel time compared to pedestrian street segments.

Download Grasshopper file
Download Rhino file

06| CITY GRAPH CENTRALITY DISTANCE DECAY

In several centrality measures (e.g. gravity), the attractiveness of destination is  inversely proportional to function of distance. As distance grows, the attractiveness is getting lower. In the street network analysis toolbox, this distance decay function can be defined by user representing different types of behavior and aversion to travel.

Download Grasshopper file

Street Network Editing Utilities

01| NETWORK EDITING TOOLS

To gain correct and speedy analysis results of any street network, this has to be usually simplified and corrected for drawing errors. DeCodingSpaces toolbox offers range of tools to split lines, remove duplicates, simplify intersections and remove dead ends.

Download Grasshopper file

02| CUSTOM OFFSET

Transforms the street network into closed polylines – street blocks which can be offseted by custom value for each block edge. We demonstrate this functionality by offseting the block edges by their respective street network centrality values.

Download Grasshopper file

Part 2 – Generation of Street network, Plots and Buildings

Street Network Optimization

01| STREET NETWORK GENERATION

Generate Street Networks in a given area with initial street segments by controlling parameters for street segment length, angle between streets and connectivity.

Download Grasshopper file

02| BUILDING PLOTS GENERATION

Based on the generated Street Network we extract the Street Blocks and generate Plots based on control parameters like the maximal area, minimal width of the street side, etc.

Download Grasshopper file

03| BUILDING GENERATION

For each plot we generate buildings of various typologies controlling the parameters for setbacks, building sizes, orientation and density.

Download Grasshopper file

Part 3 – Street Network Optimization

Hands on example files:

Street Network Optimization

01| Chromosome Demonstration

In this example file, we demonstrate how the generative methods are represented using a specific data structure to be used for evolutionary optimization in the next step.

Download Grasshopper file

02| Evolutionary Multi-Criteria Optimization

Based on the generative components and a particular data structure, we can use a multi-criteria evolutionary optimization algorithm to search for good urban design variants.

Download Grasshopper file

SimAUD 2019 Workshop | Adaptive Urban Layout Optimization with DeCodingSpaces-Toolbox

SimAUD 2019 Workshop | Adaptive Urban Layout Optimization with DeCodingSpaces-Toolbox

by | Apr 4, 2019 | Analysis, Synthesis

During this one-day-workshop you will be introduced to methods for the analysis, synthesis and optimization of urban layouts. We will cover computational generation of the street network, parcellation and the building form, based on the existing urban context and various design goals. You learn how to analyze street networks effectively, and we show you how to compare and optimize the generated designs systematically. For this purpose we use Grasshopper for Rhino3D with the plugin DecodingSpaces-Toolbox, and a new Design-Space-Exploration tool. The methods are demonstrated by realistic case studies in an existing urban environments.

This workshop is intended for both practitioners and researchers interested in rapid context aware generation of urban layouts. The presented workflow let you computationally explore the design options of new urban development area with the possibility to assess the site potential and inform the early planning stages. The presented DeCodingSpaces-Toolbox for Grasshopper is a collection of analytical and generative components for algorithmic architectural and urban planning. The toolbox is free software released by the Computational Planning Group (CPlan).

The workshop on Adaptive Urban Layout Optimization in Grasshopper is hosted by:

SimAUD 2019, Atlanta – USA, School of Architecture, Georgia Tech,  7. April 2019

Requirements

Install instructions

Unblocking plugins

After downloading the RequiredGHPlugins_SimAUD19.zip file, check if its unblocked before extracting the zip archive. Right click on the file > Properties > select unblock > select ok

Install components

After unlocking and extracting the RequiredGHPlugins_SimAUD19.zip archive, copy the “SimAUD19 components” folder into the grasshopper component folder. The grasshopper component folder can be found at:

 C:\Users\YourUserName\AppData\Roaming\Grasshopper\Libraries

or via grasshopper file menu:

Install user objects

After unlocking and extracting the RequiredGHPlugins_SimAUD19.zip archive, copy the “SimAUD19 user objects” folder into the grasshopper UserObjects folder. The grasshopper component folder can be found at:

 C:\Users\YourUserName\AppData\Roaming\Grasshopper\UserObjects

or via grasshopper file menu:

Enable GPU acceleration

The requirement to run the GPU accelerated street network analysis is the CUDA platform enabled NVIDIA GPU.
If this requirement is fulfilled, you have to copy the folders “Alea.CUDA.CT.LibDevice” and “Alea.CUDA.CT.Native.X86.B64.Windows” from the GPU acceleration folder to your Rhino install folder (i.e. “Program Files\Rhinoceros 6 (64-bit)\System\”).

Part 1 – Street Network Analysis

Presentation

Documentation

Interactive documentation of the Street Network Analysis toolbox.

Hands on example files:

Street Network Editing Utilities

01| CITY GRAPH STARTING EXAMPLE

Basic setup for different options how to use the street network analysis tools to calculate shortest paths and centrality measures.

Download Grasshopper file

04| CITY GRAPH ONE WAY ROADS

The underlying spatial graph is directed one, which means that to every street we can assign different distance weight in each direction. In the example we demonstrate how this can be used to model traffic regulation such as one way streets.

Download Grasshopper file

02| PARK EDGE WEIGHTING

Calculating shortest paths by assigning custom distance weights (graph edges) to the spatial network. The edge weights can be metric, angular, custom or any combination of these. Thus we can represent different concepts of distance (e.g. time, safety, cognitive distance)

Download Grasshopper file

05| CITY GRAPH CENTRALITY VERTEX WEIGHTING

When calculation street network centrality, we can assign custom weight to each graph vertex (origin and destination of shortest path). This can be used to model network in which some nodes (e.g. train station) produce more movement than others.

Download Grasshopper file

03| CITY GRAPH BUS EDGE WEIGHTING

The application of custom distance weights (edge weights) is demonstrated on the example of multi-modal transportation network. Street segment which serve as bus routes are given shorter distance representing travel time compared to pedestrian street segments.

Download Grasshopper file
Download Rhino file

06| CITY GRAPH CENTRALITY DISTANCE DECAY

In several centrality measures (e.g. gravity), the attractiveness of destination is  inversely proportional to function of distance. As distance grows, the attractiveness is getting lower. In the street network analysis toolbox, this distance decay function can be defined by user representing different types of behavior and aversion to travel.

Download Grasshopper file

Street Network Editing Utilities

01| NETWORK EDITING TOOLS

To gain correct and speedy analysis results of any street network, this has to be usually simplified and corrected for drawing errors. DeCodingSpaces toolbox offers range of tools to split lines, remove duplicates, simplify intersections and remove dead ends.

Download Grasshopper file

02| CUSTOM OFFSET

Transforms the street network into closed polylines – street blocks which can be offseted by custom value for each block edge. We demonstrate this functionality by offseting the block edges by their respective street network centrality values.

Download Grasshopper file

Part 2 – Street Network Synthesis

Hands on example files:

Street Network Generation and Optimization

01| STREET NETWORK SYNTHESIS

UTILITIES

Download Grasshopper file

02| Chromosome Demonstration

UTILITIES

Download Grasshopper file

03| Evolutionary Multi-Criteria Optimization

UTILITIES

Download Grasshopper file

In case you have issues with the Selector component of the DeCodingSpaces-Toolbox, it may be caused by the decimal symbol used by your operating system: make sure you use point, no comma. Second, ensure that the path to your PISA folder (part of the DeCodingSpaces-Toolbox in your libraries folder) has no space characters, points, or other special characters. You can copy the PISA folder with its content to C:\PISA and delete it from the libraries folder.

Part 3 – Exploration

Magnetizing Floor Plan Generator

Magnetizing Floor Plan Generator

by | Mar 23, 2019 | Design, Exploration, Synthesis

Presented project can be considered as an exploration of various ways of generating floor plans for public
buildings. Public buildings were chosen because of their complex and non-standardized structure. The aim was to
try different approaches, choose the best methods and incorporate them into my own algorithm.

Project Team:
Egor Gavrilov (Author), Reinhard König (Supervisor), Sven Schneider (Supervisor), Martin Dennemark (Supervisor)

Grasshopper MFG components
Grasshopper MFG script
Rhino MFG example file

Introduction

For architects as well as developers and urban planners working on the floor plans or estimating the shape and dimensions of large buildings is always a challenge. This task requires some knowledge and what is more important – even with understanding of the process it is a very time-consuming task. One should take into consideration the arrangement of all rooms as well as adjacencies and connections of main spaces. Generally, for every different shape or position of the building’s footprint the whole new room structure should be created.

The statement was put on as a starting point: Each of the rooms in a building is somehow accessible from any other room. It means that the whole communication structure is interlinked and thus forms the core. It could be said that the first step of the generation would be developing an evacuation plan, which can later be converted into more intelligible communication network.

Every room is extended by a corridor, which goes along one, two or four of its sides. Rooms are placed one-by-one in such a way, that every placed room should be attached to the main corridor structure with its own corridor. Additionally, every room should be adjacent with all required rooms. This process continues until there is no suitable space left for the next room. After that the new iteration starts and a new variant is generated. Simultaneously previously computed solutions are developed with the help of quasi-evolutionary algorithm. Eventually, the generator produces a huge number of solutions and then the best one is chosen, according to the evaluation function (generally number of the rooms placed or the total area of the rooms placed provide the most comprehensible evaluation results).

Generation Algorithm

// PREPARE INPUT

  •  rotate boundary
  •  sort rooms by their connectivity
  • find first room

// ITERATION 1

  • Place 1st room
  • Find the room that is connected with 1st room -> place it
  • Find the room that is most interconnected with currently placed rooms -> place it
  • If the room can’t be placed -> stop iteration and start over
  • Generate couple of solutions in this way -> choose 5 best of them and remove others

// ITERATION N

New iteration: improve previous solutions and generate new ones:

  • If (iteration % 3 == 0) -> Take all previous solutions, remove last 1-5 rooms and try to place them differently again.
  • If possible to place more rooms than originally, then replace old solution with this one.
  • If (iteration % 3 != 0) -> develop new solution

// END OF ITERATIONS

  • Generate couple of solutions in this way -> choose 5 best of them and remove others
  • Choose the best solution and generate output from it
  • If needed, remove dead ends and convert halls to corridors

User interface

Ease of use was considered as a crucial feature since the beginning of a project. Therefore, a simple solution for managing a room program of a house was created for the grasshopper environment. It enables user to set basic parameters, such as room name, area, room connections, entrance location, type of space (room/hall).

Expreimentation

Example 1

Haus am Horn v.1

Example 2

Haus am Horn v.2

Example 5

House am Horn v.3

Example 6

House am Horn v.4

Example 3

Miller House v.1

Example 4

Miller House v.2

Example 7

Villa Savoye v.1

Example 8

Villa Savoye v.2

eCAADe2018 Workshop | Urban Analysis, Synthesis and Exploration with Grasshopper

eCAADe2018 Workshop | Urban Analysis, Synthesis and Exploration with Grasshopper

by | Sep 12, 2018 | Analysis, Exploration, Networks, Synthesis

DeCodingSpaces workshop on Urban Analysis, Synthesis and Design Exploration in Grasshopper hosted by: eCAADe2018, Poland – Łódź, 18.September 2018

In this workshop, you will learn how to generate urban fabric variants, perform quantitative analysis on it, as well as optimize the generated variants and expore the cooresponding solution space. For this purpose you will be introduced to various components from the DeCodingSpaces Toolbox for Rhino/GH. You will learn how to analyse Street Networks effectively to compute real life phenomena such as the distribution of functions in a city or the movement patterns of citizens. Moreover, you will be introduced to the various methods for the synthesis of urban morphology (street networks, plots, and buildings) and how they connect to the analysis methods. Finally, you will also be introduced to design space exploration tool for beeing able to compare the generated solution systematically. The presented DeCodingSpaces-Toolbox for Grasshopper is a collection of analytical and generative components for algorithmic architectural and urban planning. The toolbox is free software released by the Computational Planning Group (CPlan). It integrates established urban analysis methods, extends them with new features and introduces new methods for the analysis and synthesis of urban morphology. In the first part of the workshop, you will learn to use the street network analysis components and how the computed quantities relate to real life phenomena such as the distribution of functions in a city or the movement patterns of citizens. In the second part, we will implement a dynamic urban simulation in Grasshopper. For this purpose, we will use the results from the network analysis and compute local attractivity values for different urban functions like the population or workplaces, which interact with each other based on the corresponding distances. In the third part, we will demonstrate functions of the DeCodingSpaces-Toolbox for the synthesis of urban morphology (street networks, plots, and buildings), which is directly connected to the analysis and the simulation parts. In the last part, we use a Design-Space-Exploration tool (DSE) that presents the generated solutions in various ways.

Requirements

Presentation
Workshop files

Part 1 – Analysis

Isovist

01| 2D ISOVIST SINGLE POINT

Analysis 2d, 3d Isovist

Download Grasshopper file

04| 2D ISOVIST OBJECT VISIBILITY

Analysis 2d, 3d Isovist

Download Grasshopper file

02| 2D ISOVIST PATH

Analysis 2d, 3d Isovist

Download Grasshopper file

05| 3D ISOVIST

Analysis 2d, 3d Isovist

Download Grasshopper file

03| 2D ISOVIST FIELD

Analysis 2d, 3d Isovist

Download Grasshopper file

Street Network Analysis

01| CITY GRAPH STARTING EXAMPLE

Street Network Analysis

Download Grasshopper file

04| CITY GRAPH ONE WAY ROADS

Street Network Analysis

Download Grasshopper file

02| PARK EDGE WEIGHTING

Street Network Analysis

Download Grasshopper file

05| CITY GRAPH CENTRALITY VERTEX WEIGHTING

Street Network Analysis

Download Grasshopper file

03| CITY GRAPH BUS EDGE WEIGHTING

Street Network Analysis

Download Grasshopper file
Download Rhino file

Utilities

01| NETWORK EDITING TOOLS

UTILITIES

Download Grasshopper file

02| ANALYSIS GRID

UTILITIES

Download Grasshopper file

03| CUSTOM OFFSET

UTILITIES

Download Grasshopper file

Part 2 – Generation

01| STREET NETWORK FROM GUIDE LINE

UTILITIES

Download Grasshopper file

02| STREET NETWORK FROM GRID

UTILITIES

Download Grasshopper file

03| STREET NETWORK SYNTHESIS

UTILITIES

Download Grasshopper file

Part 3 – Exploration

01| DESIGN SPACE EXPLORATION

Download Grasshopper file

Part 4 – Hands On, Generate Analyze & Explore

Weimar Urban Layout Generator

Download Grasshopper file
Download Rhino file

Impressions of the Workshop Results

http://infar-vm.architektur.uni-weimar.de/dse2/dse
The session ID is: YKIKFUCBTEGlqI6g

Rural Urban Metabolism

Rural Urban Metabolism

by | Aug 4, 2018 | Design, Simulation, Synthesis

The videos on this site document the results of the integrated computational design summer semester course 2018 “Rural-Urban Metabolism – Metabolism-based Planning Strategies for Rural-Urban Transformation in Ethiopia” at the Bauhaus-University Weimar as part of the Advanced Urbanism MSc and European Studies MSc. Both study programs are continued in the future as Integrated Urban Development and Design master program.

The urban design course is related to the research project Integrated Infrastructure (IN³), which is an interdisciplinary international research project at the Bauhaus-Universität Weimar and the Ethiopia Institute for Architecture, Building Construction and City Development (EiABC). The project is funded by the Federal Ministry of Education and Research in Germany (BMBF), German Academic Exchange Service (DAAD) and German Aerospace Center (DLR).

Supervisors team: Sven Schneider, Philippe Schmidt, Reinhard Koenig, Abdulmalik Abdulmawla, Martin Dennemark

Project context

The transformation from a mainly agricultural society to industrialisation that is faced these days in Ethiopia is linked to substantial changes of the country’s rural and urban areas. With these shifts, the processes of urbanisation and expectations towards modernisation is seen as a chance to create new and adaptive urban planning proposals that meet specific needs and conditions of the Ethiopian development context in Sub-Saharan Africa. While the World Bank is promoting rapid economic growth for Ethiopia, still the country is one of the poorest countries in the world, and the question arises in how far urban design and planning can create concepts and flexible urban models that are reactive enough to stimulate different scenarios responding for  balanced development.

One of the main frameworks to create such balance for emerging cities are the United Nations Sustainable Development Goals. Different key factors like food security, energy, water and sanitation are linked to resource questions of material and land and how those can be influential on the development of prospective cities. Thus, for the development of new towns in rapidly urbanizing regions the understanding of material flows and circulation within the urban system is crucial when it comes about any building activity that determines the urban form and what we finally experience as urban, including open and public space and healthy living conditions. 

To better understand how such flows of material resources and energy are linked to building activities in rural  urbanisation processes and their impact on the existing environment, in our study project, we are referring to urban metabolism as a framework for urban design and planning of small cities.

Participants will be analysing urban patterns and flows of small cities, learn about the context between urban metabolism and its spatial implications and apply tools and methods for a spatial analysis and finally implement that knowledge in spatial models and concepts to simulate possible development scenarios. The findings should also make visible the opportunities and limitations of such concepts for disciplines concerned with urban development, taking into account environmental, social and economic factors.

Introduction Lecture

to the project “Rural Urban Metabolism” in Ethiopia by Vertr. Prof. Dr. Sven Schneider

Custom-City

by Constantin Friedrich Kozák, Jonas Wiel, Shunsuke Yoshida & Silke Weise

Bio Communal City

by Harneet Kaur, Truc Anh Nguyen & Yun Shu

SAN City

by Aurelija Matuleviciute, Marina Evstifeeva & Philip Schäffler

Seriti 2.0

by Andrej Sluka, Lina Ayser Jamil Halaseh & Siim Kuusik

Walkable City

by Furui Yang, Maria Dorothea Mönig & Ting-Yu Hsu

Frontiers of Water

by Alejandra Urrutia Pinto, Jakob Moritz Becker & Nils Fabian Voerste

Radius City

by Ayah Al-Sabbagh, Bastiaan Woudenberg & Xuanyu Li

Recreation City

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