The planning of single-storey layouts

Whitehead, B.; Eldars, M.Z.

doi:10.1016/0007-3628(65)90014-9

Cited by 57 publications

(10 citation statements)

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“…Researchers viewed designing as a process amenable to depiction into decomposable components, represented numerically, and interpreted and administered by a computing machine and software. The computational frame of reference stemmed from research and theoretical foundations which include cognitive science, expert systems and artificial intelligence (Whitehead and Eldars, 1965; Eastman, 1969; Maver, 1971; Newell and Simon, 1972; Mitchell, 1979). The works of Mitchell (1979, 1990), Gero (1983) and Gero and Maher (1993) demonstrate well-recognised achievements on the utilisation of systems thinking and machine learning in design that drifted into two directions.…”

Section: Perspectives and Frames Of Referencementioning

confidence: 99%

Methodological research in architecture and allied disciplines

Salama

2019

ARCH

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Purpose The purpose of this paper is to contribute an inclusive insight into methodological research in architecture and allied disciplines and unravel aspects that include philosophical positions, frames of reference and spheres of inquiry. Design/methodology/approach Following ontological and epistemological interpretations, the adopted methodology involves conceptual and critical analysis which is based on reviewing and categorising classical literature and more than hundred contributions in architectural and design research developed over the past five decades which were classified under the perspectives of inquiry and frames of reference. Findings Postulated through three philosophical positions – positivism, anti-positivism and emancipationist – six frames of reference were identified: systematic, computational, managerial, psychological, person–environment type-A and person–environment type-B. Technically oriented research and conceptually driven research were categorised as the perspectives of inquiry and were scrutinised together with their developmental aspects. By mapping the philosophical positions to the frames of reference, various characteristics and spheres of inquiry within each frame of reference were revealed. Research limitations/implications Further detailed examples can be developed to offer discerning elucidations relevant to each frame of reference. Practical implications The study is viewed as an enabling mechanism for researchers to identify the unique particularities of their research and the way in which it is pursued. Originality/value The study is a response to a glaring dearth of cognisance and a reaction to a growing but confusing body of knowledge that does not offer a clear picture of what research in architecture is. By identifying key characteristics, philosophical positions and frames of reference that pertain to the research in architecture and associated disciplines, the findings represent a scholastic endeavour in its field.

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Section: Perspectives and Frames Of Referencementioning

confidence: 99%

Methodological research in architecture and allied disciplines

Salama

2019

ARCH

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“…The model of grid or the model of volume could be employed as a generative system for architecture. A lot of approaches to spatial synthesis have employed either of them as the main model, for example Whitehead (1965) and Roseman(1996) chose the grid model; Chouchoulas (2003) and Lehnerer(2010) preferred the volume model. Nevertheless, few approaches have tried to use both models for design in the field of CAAD or computational design.…”

Section: Decoupling Grid and Volumementioning

confidence: 99%

“…This paper presents a generative design method employing multiple models. In the field of CAAD, early computational approaches to spatial planning were based on single model of architecture -especially the grid (Armour 1963;Whitehead 1965;Seehof 1966) . It was widely believed that a minimal representation of the architecture is sufficient to carry out design processes based on CAAD methodologies.…”

Section: Introductionmentioning

confidence: 99%

Decoupling Grid and Volume: A generative approach to architectural design

Hua¹,

Hayek²,

Grêt‐Regamey³

et al. 2012

eCAADe Proceedings

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“…Since the rise of computer-aided design (CAD) in the 1960s, academics have attempted to address the generative design of architectural plans to cope with SAP [8,9]. Pattern languages [10][11][12] and formal grammar [13,14] became the theoretical anchors and sources of ideas [15] during the first low-tide era of development following the introduction of AI [16].…”

Section: Introductionmentioning

confidence: 99%

A Deep Learning Approach toward Energy-Effective Residential Building Floor Plan Generation

Wan

Zhao

et al. 2022

Sustainability

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The ability of deep learning has been tested to learn graphical features for building-plan generation. However, whether the deeper space allocation strategies can be obtained and thus reduce energy consumption has still not been investigated. In the present study, we aimed to train a neural network by employing a characterized sample set to generate a residential building floor plan (RBFP) for achieving energy reduction effects. The network is based on Pix2Pix, including two sub-models: functional segmentation layout (FSL) generation and building floor plan (BFP) generation. To better characterize the energy efficiency, 98 screened floor plans of Solar Decathlon (SD) entries were labeled as the sample set. The data augmentation method was adopted to improve the performance of the FSL sub-model after the preliminary testing. Three existing residential buildings were used as cases to observe whether the network-generated RBFP gained the effect of decreasing energy consumption with decent space allocation. The results showed that, under the same simulation settings and building exterior profile (BEP) conditions, the function arrangement of the generated scheme was more reasonable compared to the original scheme in each case. The annual total energy consumption was reduced by 13.38%, 12.74%, and 7.47%, respectively. In conclusion, trained by the sample set that characterizes energy efficiency, the RBFP generation network has a positive effect in both optimizing the space allocation and reducing energy consumption. The implemented data augmentation method can significantly improve the network’s training results with a small sample size.

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The planning of single-storey layouts

Cited by 57 publications

References 0 publications

Methodological research in architecture and allied disciplines

Methodological research in architecture and allied disciplines

Decoupling Grid and Volume: A generative approach to architectural design

A Deep Learning Approach toward Energy-Effective Residential Building Floor Plan Generation

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