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Tarek Rakha and Christoph Reinhart

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1 Generative Urban Modeling: A Design Work Flow for walkability-optimized cities
Tarek Rakha and Christoph Reinhart Massachusetts Institute of Technology Department of Architecture Building Technology Program Sustainable Design Lab

2 Outline Introduction Urban Form Generation Methodology
Generative Urban Form Workflow Walkability Assessment Optimization Urban Performance Application - Results Discussion Conclusion

3 Introduction United Nations, World Urbanization Prospects: The 2010 Revision. United Nations, New York. By the year 2050, the world population is projected to reach 10.1 billion!

4 Terrain morphology is often less benign to urban developments
Introduction Terrain morphology is often less benign to urban developments

5 Introduction A comparison between minimally changed street structures in downtown Cairo, Egypt. (Left) Author adapted map of Cairo in 1933 (Nicohosoff, A., 1933). (Right) An online contemporary map of the same area (Bing Maps, 2011). A road network, once in place, tends to be remarkably resistant to change

6 Introduction – Previous Work
Site design and its relationship to terrain in the third dimension has thus far been disregarded. Academic: Beirão, J. N., Nourian, P., Mashhoodi, B., Parametric urban design: an interactive sketching system for shaping neighborhoods. Professional: Growing Cities, SOM

7 Urban Form Generation Methodology
Generative Urban Form Workflow Subdivide terrain following design logic. Manipulate the terrain. Set street widths offsets and building lots. Zone parametrically controlled building forms. Performance Evaluation Walkability, Daylighting Potential, Thermal Comfort Energy Efficiency Carbon Emissions Etc. Optimization Utilization of optimization schemes

8 Urban Form Generation Methodology
Generative Urban Form Workflow Subdivide terrain following design logic. Manipulate the terrain. Set street widths offsets and building lots. Zone parametrically controlled building forms. Performance Evaluation Walkability, Daylighting Potential, Thermal Comfort Energy Efficiency Carbon Emissions Etc. Optimization Utilization of optimization schemes

9 Generative Urban Form Workflow
The coding of an urban massing modeler that allows users to generate and manipulate massing models for multiple buildings is the essence of the tool. When an urban design is generated, it will be ready for identification of urban massing solutions that optimize various neighborhood performance metrics such as potential for pedestrian thermal comfort etc…

10 Load Terrain Subdivide Terra-Form Model Urban Mass

11 Load Terrain Data – Elevation Model

12 Subdivide Terrain

13 Subdivide Lots & Streets

14 Terra-Form

15 Add Buildings

16 Zoning

17 Parametric Tool Layout

18 Urban Form Generation Methodology
Generative Urban Form Workflow Subdivide terrain following design logic. Manipulate the terrain. Set street widths offsets and building lots. Zone parametrically controlled building forms. Performance Evaluation Walkability, Daylighting Potential, Thermal Comfort Energy Efficiency Carbon Emissions Etc. Optimization Utilization of optimization schemes

19 Urban Form Generation Methodology
Generative Urban Form Workflow Subdivide terrain following design logic. Manipulate the terrain. Set street widths offsets and building lots. Zone parametrically controlled building forms. Performance Evaluation Walkability, Daylighting Potential, Thermal Comfort Energy Efficiency Carbon Emissions Etc. Optimization Utilization of optimization schemes

20 Performance Evaluation: Walkability
Walkability was consciously chosen as an initial sustainability performance indicator, since planning of urban density is a necessary step to contain urban growth. It constitutes a key challenge to sustainable urban developments worldwide.

21 Neighborhood Walkability
Walkability is a measure of how friendly an area is to walking. Evaluating walkability is challenging because it requires the consideration of subjective factors. Factors influencing walkability include: The presence or absence and quality of footpaths, sidewalks or other pedestrian right-of-ways Traffic and road conditions Land use patterns Building accessibility and safety.

22 Street Smart Walkscore
Walkability is linked to the density of amenities, number of intersections and block lengths.

23 Street Smart Walkscore
Scaling Factor: less than ¼ mile 100%, more than 1.5 mile 0%

24 Street Smart Walkscore
Walk Score of transit stations in Phoenix, AZ

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26 Urban Form Generation Methodology
Generative Urban Form Workflow Subdivide terrain following design logic. Manipulate the terrain. Set street widths offsets and building lots. Zone parametrically controlled building forms. Performance Evaluation Walkability, Daylighting Potential, Thermal Comfort Energy Efficiency Carbon Emissions Etc. Optimization Utilization of optimization schemes

27 Urban Form Generation Methodology
Generative Urban Form Workflow Subdivide terrain following design logic. Manipulate the terrain. Set street widths offsets and building lots. Zone parametrically controlled building forms. Performance Evaluation Walkability, Daylighting Potential, Thermal Comfort Energy Efficiency Carbon Emissions Etc. Optimization Utilization of optimization schemes

28 Optimization: Genetic Algorithms
Fitness function: Optimize walkscores to be more than 70 (very walkable).

29 Urban Performance Application
Site Area: 1.45 km2 Max. Elevation: 360m Population: 21,600 people

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33 Iterations against fitness function in walkability optimization

34 Population percentages against Walk score
The calculated centroid of the three solutions was almost central to the terrain. Important amenities that give higher scores spread out. If entrances to buildings change, solutions that do not perform will achieve a better score that may be acceptable.

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36 Discussion The scoring system is street dependent, meaning that walking distances from the housing unit to the street are ignored. Disregarding terrain when calculating the walk scores is a weakness. Utilization of automation procedures to generate form. The focus shifts to gaining insight into urban morphology and its effect on performance through iterative explorations and optimization procedures. Cultural adaptation.

37 Conclusion A new Urban Massing tool based on street gradients in hilly situations. A walkability calculation procedure for sustainable infrastructure assessment. Linking to GA’s for performance optimization. Moving forward to validations of walking/biking.

38 ACKNOWLEDGEMENTS The writing of this paper was supported by a grant from the Massachusetts Institute of Technology Energy Initiative (MITEI). The authors are indebted to Panagiotis Michalatos and Jon Sargent for their contributions to the development of the Grasshopper urban massing tool and the walkscore calculator, respectively. Generative Urban Modeling: A Design Work Flow for walkability-optimized cities Tarek Rakha and Christoph Reinhart Massachusetts Institute of Technology Department of Architecture Building Technology Program Sustainable Design Lab


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