Configurative Design | Genesis Lab

A Participatory Design Game for Social Housing Configuration

Wed, 27 Apr 2016 00:00:00 +0000

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Developing a Computational Method for Including a Client’s Input In a Mass Customizable 3D Module Building Industry

Wed, 27 Apr 2016 00:00:00 +0000

GEN:ARCH

Wed, 27 Apr 2016 00:00:00 +0000

Generating Building Envelopes Using Multi-Objective Optimization Techniques

Wed, 27 Apr 2016 00:00:00 +0000

Participatory Design Game for Urban Slum

Wed, 27 Apr 2016 00:00:00 +0000

Reconfigurable architecture for compression-only structures

Wed, 27 Apr 2016 00:00:00 +0000

ShellTerra

Wed, 27 Apr 2016 00:00:00 +0000

Generative Solar-Climatic Configuration

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

The complete thesis is under a temporary embargo until we publish the results of the research in a peer-reviewed journal article that is in preparation. Team: Ir. A. Kassiani Florou, Dr.ir. P. Nourian, Ir. S.Azadi

The typical solar energy potential simulation workflows used in the AEC industry require an abundance of information regarding the detailed geometry and materialization of the design. These requisites render them incompatible with early-stage design decision-making pertaining to form-finding. By performing solar energy potential simulations at the pre-conceptual design phase, the necessary time for later-stage environmental assessments and design improvements is reduced considerably, while building designs with high performance but low environmental footprint are attained. This research proposes a computational framework to navigate voxel-based morphologies of building envelopes in a performative design space. It investigates a generative workflow through an embedded multi-criteria optimization of solar-related indicators, which are mapped in a solar energy potential field. The formulation of this field consists of an a priori assessment of the solar energy potential in every discrete volumetric unit (voxel) and a vectorized description of the interdependency of them. The astronomical size of this solution space renders the use of metaheuristic methods more appropriate. More specifically, a subtractive strategy that incorporates an MCDA approach is being applied in order to reach user-defined optimization targets. The novelty and potential of the proposed methodology lies in streamlining the early decision making process for designers and architects and expanding the morphological possibilities. Through this framework, the performative design space is effectively navigated and nearly optimal solutions are generated, to act as suggestive mechanisms for informed architectural decisions.

A Computational Method to Generate One-story Floor Plans

Wed, 27 Apr 2016 00:00:00 +0000

Cochleas

Wed, 27 Apr 2016 00:00:00 +0000

David & The Vegetable Factory

Wed, 27 Apr 2016 00:00:00 +0000

Encoding Building Products

Wed, 27 Apr 2016 00:00:00 +0000

SYNTACTIC ARCHITECTURAL DESIGN METHODOLOGY; Integrating real-time Space Syntax analysis in a configurative architectural design process

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

Authors: Pirouz Nourian, Samaneh Rezvani, Sevil Sariyildiz

Abstract:

This paper presents a computational toolkit developed for configurative architectural design, i.e. a computational design process, equipped with real-time space syntax analyses in a parametric CAD environment, which begins with defining the desired spatial configuration in form of a bubble diagram. The syntactic design methodology put forward by this toolkit is aimed at bridging the gap between space syntax as an analytic theory of architecture and architectural design practice. The toolkit has been made in an attempt to investigate the possibility of deriving at plan layout patterns through sketching spatial configuration using an ‘interactive bubble diagram’ that represents a spatial connectivity graph. In other words, we have worked on a way of reaching at concrete plan layouts from an abstract connectivity pattern as a graph. Beginning the design process with a graph allows for real-time feedback of Space Syntax measures such as integration, choice and difference factor. Besides, by choosing every space as a ‘root’, designers can immediately view their configurative ideas, literally from different points of views in automatically drawn justified graphs. In this paper, we give an overview of a syntactic design process as a graph theoretical approach to architectural design and report our preliminary results.

AI Configurators

Sat, 06 Feb 2021 16:49:47 +0000

Background and aim:

Spatial qualities heavily depend on the configuration of spaces. In this research project, we develop computational agents that configures the space within a voxelated envelope while ensuring spatial qualities such as daylight, accessibility to other spaces, etc., via Multi-Criteria Decision Analysis. Each computational agent utilizes Reinforcement Learning to understand the inter-relation of global spatial quality criteria with local spatial decisions.

Research question:

How to train an ensemble of artificial agents to make local spatial decisions to attain high global spatial qualities?

Design objective:

To design and implement a computational 3D layout methodology using DRL.

Methods:

Deep Reinforcement Learning (DRL, Artificial Intelligence)

Multi-Criteria Decision Analysis (MCDA)

Topology Optimization

Computer Programming (Python/C#)

Generative Configuration Design

Sat, 06 Feb 2021 16:49:47 +0000

Background and aim:

The spatial configuration of a building can be abstracted as a network of functional spaces that influences the functionality of a building in terms of movements of the occupants, logistic efficiency, feasibility of social distancing, safety of routing, and security. The aim of the research is to propose a systematic way of configuring buildings in 3D to optimally meet functional requirements pertaining to such factors etc.

Research question:

How to computationallyHow to configure a building procedurally given a program of requirements, accessibility, and daylight requirements and complex site constraints?

Design objective:

To design and implement a computational 3D layout methodology.

Methods:

Architectural Engineering
Discrete Optimization
Computational Topology and Graph Theory
Computer Programming (Python)

Space Optimization

Sat, 06 Feb 2021 16:49:47 +0000

Background and aim:

Research question:

How to optimize the allocation of spaces in a building based on a program of requirements, and a set of criteria concerning accessibility and visibility?

Design objective:

To design and implement a computational 3D layout methodology.

Methods:

Operations Research (Mathematical Optimization)

Quadratic Assignment Problem

Computational Topology and Graph Theory

Computer Programming (Python/C#)