Patrick Janssen

A generative evolutionary design method

Abstract This paper describes a generative evolutionary design method, called the ‘schema method’, which requires the design team to participate in the programming of generative and evolutionary rules and representations. The method consists of two phases: in the first phase, the design team develops and encodes the essential and identifiable character of the designs to be generated and evolved; in the second phase, the design team uses an evolutionary system to generate and evolve designs that incorporate this character. This method is based on a previous generative evolutionary design method, developed by John Frazer from the late 1960s onwards, called the ‘concept seeding method’.

Custom Digital Workflows: A New Framework for Design Analysis Integration

Flexible information exchange is critical to successful design-analysis integration, but current top-down, standards-based and model-oriented strategies impose restrictions that contradict this flexibility. In this article we present a bottom-up, user-controlled and process-oriented approach to linking design and analysis applications that is more responsive to the varied needs of designers and design teams. Drawing on research into scientific workflows, we present a framework for integration that capitalises on advances in cloud computing to connect discrete tools via flexible and distributed process networks. We then discuss how a shared mapping process that is flexible and user friendly supports non-programmers in creating these custom connections. Adopting a services-oriented system architecture, we propose a web-based platform that enables data, semantics and models to be shared on the fly. We then discuss potential challenges and opportunities for its development as a flexible, visual, collaborative, scalable and open system.

A Framework for Generating and Evolving Building Designs

This paper describes a comprehensive framework for generative evolutionary design. The key problem that is identified is generating alternative designs with an appropriate level of variability. Within the proposed framework, the design process is split into two phases: in the first phase, the design team develops and encodes the essential and identifiable character of the designs to be generated and evolved; in the second phase, the design team uses an evolutionary system to generate and evolve designs that embody this character. This approach allows design variability to be carefully controlled. In order to verify the feasibility of the proposed framework, a generative process capable of generating controlled variability is implemented and demonstrated.

Decision chain encoding: evolutionary design optimization with complex constraints

A novel encoding technique is presented that allows constraints to be easily handled in an intuitive way. The proposed encoding technique structures the genotype-phenotype mapping process as a sequential chain of decision points, where each decision point consists of a choice between alternative options. In order to demonstrate the feasibility of the decision chain encoding technique, a case-study is presented for the evolutionary optimization of the architectural design for a large residential building.

Dexen: A scalable and extensible platform for experimenting with population-based design exploration algorithms

Abstract A platform for experimenting with population-based design exploration algorithms is presented, called Dexen. The platform has been developed in order to address the needs of two distinct groups of users loosely labeled as researchers and designers. Whereas the researchers group focuses on creating and testing customized toolkits, the designers group focuses on applying these toolkits in the design process. A platform is required that is scalable and extensible: scalable to allow computationally demanding population-based exploration algorithms to be executed on distributed hardware within reasonable time frames, and extensible to allow researchers to easily implement their own customized toolkits consisting of specialized algorithms and user interfaces. In order to address these requirements, a three-tier client–server system architecture has been used that separates data storage, domain logic, and presentation. This separation allows customized toolkits to be created for Dexen without requiring any changes to the data or logic tiers. In the logic tier, Dexen uses a programming model in which tasks only communicate through data objects stored in a key-value database. The paper ends with a case study experiment that uses a multicriteria evolutionary algorithm toolkit to explore alternative configurations for the massing and façade design of a large residential development. The parametric models for developing and evaluating design variants are described in detail. A population of design variants are evolved, a number of which are selected for further analysis. The case study demonstrates how evolutionary exploration methods can be applied to a complex design scenario without requiring any scripting.

A Rule-Based Generative Analysis Approach for Urban Planning

Urban plans are difficult to comprehensively analyze quantitatively because they lack sufficiently detailed information. They tend to emphasize land-use, possibly suggesting general building typologies. Nevertheless, they are generally conceived with respect to objective criteria, such as population targets, plot ratios, gross floor areas, etc. This research suggests a rule-based approach to generate relevant building data that can serve to analyze and assess such urban plans with respect to these and other relevant criteria, requirements and targets. Such generation must necessarily take into account local conditions, building typologies, codes and regulations.

Custom Digital Workflows with User-Defined Data Transformations Via Property Graphs

Custom digital workflows aim to allow diverse, non-integrated design and analysis applications to be custom linked in digital workflows, created by a variety of users, including those who are not expert programmers. With the intention of introducing this in practice, education and research, this paper focuses on critical aspects of overcoming interoperability hurdles, illustrating the use of property graphs for mapping data between AEC software tools that are not connected by common data formats and/or other interoperability measures. A brief exemplar design scenario is presented to illustrate the concepts and methods proposed, and conclusions are then drawn regarding the feasibility of this approach and directions for further research.

Evolutionary Optimisation of Semi-Transparent Building Integrated Photovoltaic Facades

The optimisation of semi-transparent building integrated photovoltaic facades can be challenging when attempting to find an overall balance performance between conflicting performance criteria. This paper presents a three-phase design optimisation method that maximises overall electricity savings generated by these types of facades by simulating the combined impact of electricity generation, cooling load, and daylight autonomy. Two demonstrations are performed, with the difference being that the second demonstration uses an enhanced model for calculating daylight savings that takes into account the use of blinds to counteract glare. For both demonstrations, the three-phase optimisation method significantly reduces optimisation run times. Comparing the design variants evolved by the two demonstrations, the use of the enhanced daylight savings model results in a total electricity savings that is more accurate but in terms of visual differentiation, the difference between the optimized design variants is relatively small.

Protocols, flows and glitches

This special issue of the International Journal of Architectural computing is a rejoinder to the 2017 CAADRIA conference, with the theme of Protocols, Flows and Glitches. Data structures and network protocols now integrate operations of entire industries, and digital workflows encompass virtually all stages of architectural production. Buildings and the processes they undergo are represented by digital building information models, which are shared across disciplines to generate options and support decisions before they are committed to built form. Yet, there are limits to the reach of digital modelling and predictability. The tools and frameworks, within which building information models are created and used, are themselves subject to constraints and forces similar to those that impede architectural production and maintenance, including technical glitches, noise, error, versioning and compatibility issues, limits to quantifiability, questions of cost effectiveness, incomplete ‘information’ and challenges of interpretation and negotiation. The question arises whether more powerful tools resolve challenges, or whether, in doing so, they encourage us to venture deeper into territories where yet more challenges are encountered? However, our field of computer-aided architectural design engages also that which cannot, or cannot yet, be readily described or modelled. We thus negotiate the reach of formal representation, deepening appreciations of human agency and creativity and laying foundations for industry-transforming technologies. The 22nd International Conference on Computer-Aided Architectural Design Research in Asia (CAADRIA 2017) brought together original contributions presenting current computer-aided architectural design research in a general sense, accommodating a broad spectrum of approaches ranging from speculative, informal investigations to conventional scientific research. The conference was held 5–8 April 2017 at Xi’an Jiaotong-Liverpool University, Suzhou, China. This issue contains a collection of four papers hand-picked from among the best conference papers that have been extended and updated for this special issue. All papers have undergone an additional round of rigorous double-blind review before acceptance to this special issue. The four papers tackle diverse areas of computational design. In the first paper, Blaire Haslop, Marc Aurel Schnabel and Serdar Aydin explore the potential for design emergence based on malfunctions during computational processing of three-dimensional data. The research draws on the broader field of glitch art and describes a series of experiments that transform glitched data into spatial forms with a multitude of possible architectural interpretations. In the second paper, Trevor Patt presents an agent-based planning approach for urban sites, where informal developments make conventional top-down masterplanning ineffectual. The case study is presented for a village in Guangzhou, China. In his proposed method, the redevelopment of a village is guided by a dynamic model consisting of swarms of agents that identify possible urban interventions through localized interactions. These interventions include both modification of selected parcels and modification of the street network. In the third paper, Yufan Miao, Reinhard Koenig, Peter Buš, Mei-Chih Chang, Artem Chirkin and Lukas Treyer present a rapid urban design prototyping method that automatically generates urban layouts including street networks, urban blocks and parcels. In addition, on defining certain parameters, the planners are also able to guide the street network generation by specifying initial street segments. A case study is presented, generating urban layouts for an informal settlement in Cape Town. 798934 JAC0010.1177/1478077118798934International Journal of Architectural ComputingEditorial editorial2018