Computational Design | Genesis Lab

Configurbanist; Urban Configuration Analysis for Walking and Cycling via Easiest Paths

Mon, 01 Jan 0001 00:00:00 +0000

Authors: Pirouz Nourian, Samaneh Rezvani, Sevil Sariyildiz, Frank van der Hoeven

Abstract:

In a quest for promoting sustainable modes of mobility, we have revisited how feasible and suitable is it for people to walk or cycle to their destinations in a neighbourhood. We propose a few accessibility measures based on an ‘Easiest Path’ algorithm that provides also actual temporal distance between locations. This algorithm finds paths that are as short, flat and straightforward as possible. Considering several ‘points of interest’, the methods can answer such questions as “do I have a 5 minutes ‘easy’ walking/cycling access to all/any of these points?” or, “which is the preferred point of interest with ‘easy’ walking cycling access?” We redefine catchment zones using Fuzzy logics and allow for mapping ‘closeness’ considering preferences such as ‘how far’ people are willing to go on foot/bike for reaching a particular destination. The accessibility measures are implemented in the toolkit CONFIGURBANIST to provide real-time analysis of urban networks for design and planning.

Hospital layout design renovation as a Quadratic Assignment Problem with geodesic distances

Mon, 01 Jan 0001 00:00:00 +0000

Authors: Cemre Cubukcuoglu, Pirouz Nourian, M. Fatih Tasgetiren, I. Sevil Sariyildiz, Shervin Azadi

Abstract:

Hospital facilities are known as functionally complex buildings. There are usually configurational problems that lead to inefficient transportation processes for patients, medical staff, and/or logistics of materials. The Quadratic Assignment Problem (QAP) is a well-known problem in the field of Operations Research from the category of the facility’s location/allocation problems. However, it has rarely been utilized in architectural design practice. This paper presents a formulation of such logistics issues as a QAP for space planning processes aimed at renovation of existing hospitals, a heuristic QAP solver developed in a CAD environment, and its implementation as a computational design tool designed to be used by architects. The tool is implemented in C# for Grasshopper (GH), a plugin of Rhinoceros CAD software. This tool minimizes the internal transportation processes between interrelated facilities where each facility is assigned to a location in an existing building. In our model, the problem of assignment is relaxed in that a single facility may be allowed to be allocated within multiple voxel locations, thus alleviating the complexity of the unequal area assignment problem. The QAP formulation takes into account both the flows between facilities and distances between locations. The distance matrix is obtained from the spatial network of the building by using graph traversal techniques. The developed tool also calculates spatial geodesic distances (walkable, easiest, and/or shortest paths for pedestrians) inside the building. The QAP is solved by a heuristic optimization algorithm, called Iterated Local Search. Using one exemplary real test case, we demonstrate the potential of this method in the context of hospital layout design/re-design tasks in 3D. Finally, we discuss the results and possible further developments concerning a generic computational space planning framework.

Interactive computational methodology for urban mixed-use allocation according to density distribution, network analysis and geographic attractions

Mon, 01 Jan 0001 00:00:00 +0000

Authors: Pirouz Nourian, Samaneh Rezvani

Abstract:

Urban density distribution and mixed-use allocation patterns are considered to be affected primarily by the inherent spatial structure of urban neighborhoods and the geographic attractions of the district that affect people’s choices in movement and settlement. The space syntax theory (Hillier, Space is the Machine, 2007) clearly relates the configuration of urban grid to urban functioning in terms of its effect on the distribution of densities, allocation of land uses such as retail and residence: “Land uses and building density follow movement in the grid, both adapting to and multiplying its effects.” (Hillier, Space is the Machine, 2007, p. 127). It states that a spatially successful city is characterized by the “dense patterns of mixed use”, which are mainly settled as a consequence of movement, which is itself brought about by the grid configuration (Hillier, Space is the Machine, 2007, p. 4). Yet, space syntax theory is merely analytic per se and does not provide any means for ‘designing’ “spatially successful cities”; besides, it does not consider the geographic idiosyncrasies of places and their gravity-like ‘attraction’ effects in its models of movement patterns; and thus their effect on mixed-use allocation patterns. It is explicable that in vernacular settlements and in old harmonically grown cities we find a close correspondence between spatial configuration, geographic idiosyncrasies, density distribution, and mixed-use allocation patterns. However, it is important to know how to develop or change new settlements in such a balanced way. The inherent mathematical complicatedness of the abovementioned patterns, their interrelations, and their fundamental importance in the functioning of a city fully justifies the use of computation for supporting design and decision-making processes. This paper introduces a computational design methodology that relates the urban built-space density distribution and mixed-use land allocation patterns to network configuration and geographic attraction effects, guaranteeing that mixed-use allocation both complies with regional plan and local features. The proposed methodology embraces an inter-subjective understanding of place into the computational design process and combines it with the objective spatial measures such as centrality, integration, and walkability. The computational design approach presented in this paper is an effort for merging the split fields of urban planning, spatial analysis, and urban design. The computational methodology introduced in this paper is implemented within a tool-suite of computational methods for network analysis, built space density distributions, functional allocation techniques, weight/charge handlers, and equalization methods that guarantee the consistency of design alternatives with analysis results.