Cumincad : CUMINCAD Papers : Search Results

CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

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Reformat results as: short short into frame detailed detailed into frame

_id	ecaade2021_203
id	ecaade2021_203
authors	Arora, Hardik, Bielski, Jessica, Eisenstadt, Viktor, Langenhan, Christoph, Ziegler, Christoph, Althoff, Klaus-Dieter and Dengel, Andreas
year	2021
title	Consistency Checker - An automatic constraint-based evaluator for housing spatial configurations
source	Stojakovic, V and Tepavcevic, B (eds.), Towards a new, configurable architecture - Proceedings of the 39th eCAADe Conference - Volume 2, University of Novi Sad, Novi Sad, Serbia, 8-10 September 2021, pp. 351-358
doi	https://doi.org/10.52842/conf.ecaade.2021.2.351
summary	The gradual rise of artificial intelligence (AI) and its increasing visibility among many research disciplines affected Computer-Aided Architectural Design (CAAD). Architectural deep learning (DL) approaches are being developed and published on a regular basis, such as retrieval (Sharma et al. 2017) or design style manipulation (Newton 2019; Silvestre et al. 2016). However, there seems to be no method to evaluate highly constrained spatial configurations for specific architectural domains (such as housing or office buildings) based on basic architectural principles and everyday practices. This paper introduces an automatic constraint-based consistency checker to evaluate the coherency of semantic spatial configurations of housing construction using a small set of design principles to evaluate our DL approaches. The consistency checker informs about the overall performance of a spatial configuration followed by whether it is open/closed and the constraints it didn't satisfy. This paper deals with the relation of spaces processed as mathematically formalized graphs contrary to existing model checking software like Solibri.
keywords	model checking, building information modeling, deep learning, data quality
series	eCAADe
email
last changed	2022/06/07 07:54

_id	ecaadesigradi2019_171
id	ecaadesigradi2019_171
authors	Uzun, Can and Çolako?lu, Meryem Birgül
year	2019
title	Architectural Drawing Recognition - A case study for training the learning algorithm with architectural plan and section drawing images
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 2, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 29-34
doi	https://doi.org/10.52842/conf.ecaade.2019.2.029
summary	This paper aims to develop a case study for training an algorithm to recognize architectural drawings. In order to succeed that, the algorithm is trained with labeled pixel-based, architectural drawing (plan and section) dataset. During the training process, transfer learning (pre-training model) is applied. The supervised learning and convolutional neural network are utilized. After certain iterations, the algorithm builds awareness and can classify pixel-based plan and section drawings. When the algorithm is shown a section that is not produced with conventional drawing technic but through hybrid technics, it could predict the drawing class correctly with %80 of accuracy. On the other hand, some of the algorithm prediction is misoriented. We examined this prediction problem in the discussion section. The results illustrate that neural networks are successful in training algorithms to recognize and classify pixel-based architectural drawings. But for a highly accurate algorithm prediction, the dataset of the drawing images must be ordered, according to sample resolution, sample size and sample coherence for the dataset.
keywords	Classification Algorithm; Pixel-Based Architectural Drawing Recognition; Plan; Section
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:57

_id	acadia19_338
id	acadia19_338
authors	Aviv, Dorit; Houchois, Nicholas; Meggers, Forrest
year	2019
title	Thermal Reality Capture
source	ACADIA 19:UBIQUITY AND AUTONOMY [Proceedings of the 39th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-59179-7] (The University of Texas at Austin School of Architecture, Austin, Texas 21-26 October, 2019) pp. 338-345
doi	https://doi.org/10.52842/conf.acadia.2019.338
summary	Architectural surfaces constantly emit radiant heat fluxes to their surroundings, a phenomenon that is wholly dependent on their geometry and material properties. Therefore, the capacity of 3D scanning techniques to capture the geometry of building surfaces should be extended to sense and capture the surfaces’ thermal behavior in real time. We present an innovative sensor, SMART (Spherical-Motion Average Radiant Temperature Sensor), which captures the thermal characteristics of the built environment by coupling laser geometry scanning with infrared surface temperature detection. Its novelty lies in the combination of the two sensor technologies into an analytical device for radiant temperature mapping. With a sensor-based dynamic thermal-surface model, it is possible to achieve representation and control over one of the major factors affecting human comfort. The results for a case-study of a 3D thermal scan conducted in the recently completed Lewis Center for the Arts at Princeton University are compared with simulation results based on a detailed BIM model of the same space.
series	ACADIA
type	normal paper
email
last changed	2022/06/07 07:54

_id	ecaadesigradi2019_619
id	ecaadesigradi2019_619
authors	Beyer, Bastian, Suárez, Daniel and Palz, Norbert
year	2019
title	Microbiologically Activated Knitted Composites - Reimagining a column for the 21st century
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 2, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 541-552
doi	https://doi.org/10.52842/conf.ecaade.2019.2.541
summary	A column is an archetypal constituent of architecture which historically underwent constant reiteration in accordance with the prevalent architectural style, material culture or technical and structural possibilities. The project reimagined this architectural element through harnessing the synergies of digital design, textile logic, and contemporary biotechnology. Textile materiality and aesthetic are deeply rooted in architectural history as a soft and ephemeral antipode to rigid building materials. An investigation in historic mechanical hand-knitting techniques allowed to extract their underlying structural and geometric logic to develop a structural optimisation pipeline with a graded yarn as a base material and a geometric optimization based on local distribution of knitting patterns. Bacterially driven biocalcification was applied to transform the soft textile structure into a rigid material. Hereby an active textile microbiome was established through colonizing of the yarn with the bacterium S. pasteurii which successively precipitated calcite on microscale within the textile substrate hence ultimately influencing the global structural behaviour of the column.
keywords	textile microbiome; material customization; knitting; yarn augmentation
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:52

_id	ecaade2024_222
id	ecaade2024_222
authors	Bindreiter, Stefan; Sisman, Yosun; Forster, Julia
year	2024
title	Visualise Energy Saving Potentials in Settlement Development: By linking transport and energy simulation models for municipal planning
source	Kontovourkis, O, Phocas, MC and Wurzer, G (eds.), Data-Driven Intelligence - Proceedings of the 42nd Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2024), Nicosia, 11-13 September 2024, Volume 2, pp. 79–88
doi	https://doi.org/10.52842/conf.ecaade.2024.2.079
summary	To achieve Sustainable Development Goals, in addition to the switch to sustainable energy sources and energy-efficient buildings, transport offers a major lever for reducing energy consumption and greenhouse gases. The increasing demand for emission-free mobility (e.g. through electromobility) but also heat pumps has a direct impact on the electricity consumption of buildings and settlements. It is still difficult to simulate the effects and interactions of different measures as sector coupling concepts require comprehensible tools for ex ante evaluation of planning measures at the community level and the linking of domain-specific models (energy, transport). Using the municipality of Bruck an der Leitha (Austria) as an example, a digital twin based on an open data model (Bednar et al., 2020) is created for the development of methods, which can be used to simulate measures to improve the settlement structure within the municipality. Forecast models for mobility (Schmaus, 2019; Ritz, 2019) and the building stock are developed or applied and linked via the open data model to be able to run through development scenarios and variants. The forecasting and visualisation options created in the project form the basis for the ex-ante evaluation of measures and policies on the way to a Positive-Energy-District. By identifying and collecting missing data, data gaps are filled for the simulation of precise models in the specific study area. A digital, interactive 3D model is created to examine the forecast results and the different scenarios.
keywords	visualisation, decision support, sector coupling, holistic spatial energy models for municipal planning, (energy) saving potentials in settlement development
series	eCAADe
email
last changed	2024/11/17 22:05

_id	caadria2019_491
id	caadria2019_491
authors	Cai, Chenyi, Tang, Peng and Li, Biao
year	2019
title	Intelligent Generation of Architectural layout inheriting spatial features of Chinese Garden Based on Prototype and Multi-agent System - A Case Study on Lotus Teahouse in Yixing
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 1, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 291-300
doi	https://doi.org/10.52842/conf.caadria.2019.1.291
summary	This study presents an approach for the intelligent generation of architectural layout, in which partial space inherits Chinese garden spatial features. The approach combines spatial prototype analysis and evolutionary optimization process. On one hand, from the perspective of shape grammar, this paper both analyzes and abstracts the spatial prototype that describes the spatial characteristics of Chinese gardens, including the organization system of architecture and landscape, with the spatial sequences along the tourism orientation. On the other hand, taking the design task of Lotus teahouse as an example, a typical spatial prototype is selected to develop the generative intelligent experiment to achieve the architectural layout, in which the spatial prototype is inherited. Through rule-making and parameter adjustment, the spatial prototype will eventually be transformed into a computational model based on the multi-agent system. Hence, the experiment of intelligent generation of architectural layout is carried out under the influence of the function, form and environmental factors; and a three-dimensional conceptual model that inherits the Chinese garden spatial prototype is obtained ultimately.
keywords	Chinese garden; Architectural layout; Spatial prototype; Multi-agent system; Intelligent generation
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	ijac201917102
id	ijac201917102
authors	Cutellic, Pierre
year	2019
title	Towards encoding shape features with visual event-related potential based brain–computer interface for generative design
source	International Journal of Architectural Computing vol. 17 - no. 1, 88-102
summary	This article will focus on abstracting and generalising a well-studied paradigm in visual, event-related potential based brain–computer interfaces, for the spelling of characters forming words, into the visually encoded discrimination of shape features forming design aggregates. After identifying typical technologies in neuroscience and neuropsychology of high interest for integrating fast cognitive responses into generative design and proposing the machine learning model of an ensemble of linear classifiers in order to tackle the challenging features that electroencephalography data carry, it will present experiments in encoding shape features for generative models by a mechanism of visual context updating and the computational implementation of vision as inverse graphics, to suggest that discriminative neural phenomena of event-related potentials such as P300 may be used in a visual articulation strategy for modelling in generative design.
keywords	Generative design, machine learning, brain–computer interface, design computing and cognition, integrated cognition, neurodesign, shape, form and geometry, design concepts and strategies
series	journal
email
last changed	2019/08/07 14:04

_id	caadria2019_117
id	caadria2019_117
authors	Deniz Kiraz, Leyla and Kocaturk, Tuba
year	2019
title	Integrating User-Behaviour as Performance Criteria in Conceptual Parametric Design
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 1, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 215-224
doi	https://doi.org/10.52842/conf.caadria.2019.1.215
summary	Prediction of user behaviour has always been problematic in architectural design. Several methods have already been developed and explored to model human behaviour in architecture. However, the majority of these methods are implemented during post-design evaluation where the insights obtained can only be implemented in a limited capacity. There is an apparent gap and opportunity, in current research and practice, to embed behaviour simulations directly into the conceptual design process. The proposed paper (research) aims to fill this gap. This paper will report on the results of a recently completed research exploring the integration process of Agent Based Modelling into the conceptual design process, using a parametric design approach. The research resulted in the development of a methodological framework for the integration of behavioural parameters into the explorative stages of the early design process. This paper also offers a categorisation and critical evaluation of existing Agent Based Modelling applications in current research and practice, which leads to the formulation of possible pathways for future implementation.
keywords	Performance Based Design; Generative Design; Behaviour Modelling; Agent Based Modelling; Parametric Design
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	ecaadesigradi2019_191
id	ecaadesigradi2019_191
authors	Engel, Pedro
year	2019
title	CONTROLING DESIGN VARIATIONS - DESIGNING A SEMANTIC CONTROLER FOR A GENERATIVE SYSTEM
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 2, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 369-376
doi	https://doi.org/10.52842/conf.ecaade.2019.2.369
summary	This article will describe the recent steps in the development of a computational generative system based on the selection and combination of ordinary architectural elements. Built as a Grasshopper definition, the system was conceived to generate designs of architectural façades and to produce models, physical and digital, for didactic use. More specifically, The paper will address the conception of controlling devices, that is, the parts of the computational system that govern design variations. This process involved two complementary actions: first, the definition of a clear organizational logic, where elements can be represented as a data structure that encompasses classes, sub-classes, sets, libraries and attributes; secondly, the establishment of means to operate the variations through the use of filters and heuristics based on visual patterns, allowing varying degrees of automation and user control. It will be argued that such organizational model paves the way to increase the number of design possibilities in the future and to and provide means to integrate of architectural criteria into the generation process. This research has received the support of CNPq.
keywords	Algorithm; Parametric Design; Architectural Design; Teaching ; Physical Model
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:55

_id	ecaadesigradi2019_046
id	ecaadesigradi2019_046
authors	Ferreira Borges, Marina
year	2019
title	Conversations between architects and engineers
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 1, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 99-108
doi	https://doi.org/10.52842/conf.ecaade.2019.1.099
summary	The structural education in architectural schools emphasize that the dialogue between professionals is what should be raised as the point of connection between the conception of the structural morphology to be carried out by the architect and its validation and construction by the structural engineer. However, is this dialogue occurring? The proposal of this work is to study the conversational model proposed by Paul Pangaro (2009), based on Gordon Pask's Conversation Theory (1976a), and investigate if in fact a dialogic process between architectural design and structures education in architectural schools occurs, or if there exist the possibility of proposing a new conversational model, promoting transdisciplinary participation and collaboration procedures.Please write your abstract here by clicking this paragraph.
keywords	Architectural Design Teaching; Structural Education; Conversation Theory
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:56

_id	caadria2019_637
id	caadria2019_637
authors	Han, Dongchen, Zhang, Hong, Cui, Weiwen and Huang, Jie
year	2019
title	Towards to a Hybrid Model-Making Method based on Translations between Physical and Digital Models - A case study of the freeform architectural design
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 2, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 561-570
doi	https://doi.org/10.52842/conf.caadria.2019.2.561
summary	The extensive applications of digital models might decrease the capacity of physical model-making for perceptual thinking and enlarge the gap between architects and physical space with limited visual experience. This study aims to propose a reverse process for realizing translations between physical and digital model-making methods from which architects could maximize their initial ideas in conceptual design while allowing for rational digitalization in the detailed design. A review of Reverse Engineering architectural applications is presented and the hybrid method is proposed and examined in a freeform design case. The research shows that in the first translation phase, from handmade physical models to parametric digital models, freeform geometry could be better parameterized in a low degree of deformation based on photogrammetry. Meanwhile, in the second translation phase, from detailed digital models to large-scale physical models, the digitally-driven fabrication could be applied more precisely and automatically based on error handling by 3D laser scanning. Moreover, the process and algorithms developed for the hybrid model-making method indicate the possibility of being applied to further freeform architectural design cases.
keywords	Physical models; Digital models; RE technologies; Freeform design; Accuracy
series	CAADRIA
email
last changed	2022/06/07 07:50

_id	caadria2019_298
id	caadria2019_298
authors	Karoji, Gen, Hotta, Kensuke, Hotta, Akito and Ikeda, Yasushi
year	2019
title	Pedestrian Dynamic Behaviour Modeling - An application to commercial environment using RNN framework
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 1, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 281-290
doi	https://doi.org/10.52842/conf.caadria.2019.1.281
summary	The research of developing and improving pedestrian simulation model is essential in the process of analysing, evaluating and generating the architectural spaces that can not only satisfy circulation design condition but also promote sales by attracting customers. In terms of programming the simulation for commercial environment, current study attempts to use shortest-path algorithm generally and these results suggested that the model can reproduce approximate real trajectory within given environment. However, these studies also mentioned about necessity of considering shopper internal state and visual field. In this paper, in order to further incorporate the dynamic internal state (memory) into simulation model, we propose using iterative algorithm based on recurrent neural network (RNN) framework which allow it to exhibit temporal dynamic behaviour for a time sequence. Finally, we demonstrate the effectiveness of these algorithms we introduce and assess the combination of multiple algorithms and calibration of probability by comparing with trajectories of the experiment.
keywords	Pedestrian simulation; Algorithm; RNN; Commercial environment
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	acadia19_522
id	acadia19_522
authors	Kohler, Daniel; Galika, Anna; Pu, Qiuru; Bai, Junyi
year	2019
title	Blockerties
source	ACADIA 19:UBIQUITY AND AUTONOMY [Proceedings of the 39th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-59179-7] (The University of Texas at Austin School of Architecture, Austin, Texas 21-26 October, 2019) pp. 522-531
doi	https://doi.org/10.52842/conf.acadia.2019.522
summary	The paper aims for new urban forms of property enabled by computation models of distributed ledgers as they are currently being deployed with technologies like Blockchain. Distributed ledgers promise to constitute whole environments by chaining and sharing blocks of data. Upscaling this prospective, the paper describes objects with unique and strong compositional characteristics that act as closed black boxes and are able through distribution to create large scale effects. The final result of the nesting is the Interchain, a chain of chains that initiate with the characteristics of the contributing chains, and due to the distribution, unprecedented patterns arise. The resulting Interchain, observed with spatial and architectural characteristics, can project a new building form and a new urban model based on blockchain theory.
series	ACADIA
type	normal paper
email
last changed	2022/06/07 07:51

_id	caadria2019_449
id	caadria2019_449
authors	Lin, Yuqiong, Yao, Jiawei, Huang, Chenyu and Yuan, Philip F.
year	2019
title	The Future of Environmental Performance Architectural Design Based on Human-Computer Interaction - Prediction Generation Based on Physical Wind Tunnel and Neural Network Algorithms
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 2, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 633-642
doi	https://doi.org/10.52842/conf.caadria.2019.2.633
summary	As the medium of the environment, a building's environment performance-based generative design cannot be separated from intelligent data processing. Sustainable building design should seek an optimized form of environmental performance through a complete set of intelligent induction, autonomous analysis and feedback systems. This paper analyzed the trends in architectural design development in the era of algorithms and data and the status quo of building generative design based on environmental performance, as well as highlighting the importance of physical experiments. Furthermore, a design method for self-generating environmental performance of urban high-rise buildings by applying artificial intelligence neural network algorithms to a customized physical wind tunnel is proposed, which mainly includes a morphology parameter control and environmental data acquisition system, code translation of environmental evaluation rules and architecture of a neural network algorithm model. The design-oriented intelligent prediction can be generated directly from the target environmental requirements to the architectural forms.
keywords	Physical wind tunnel; neural network algorithms; dynamic model; environmental performance; building morphology self-generation
series	CAADRIA
email
last changed	2022/06/07 07:59

_id	caadria2019_345
id	caadria2019_345
authors	Marschall, Max and Burry, Jane
year	2019
title	Can the Use of Stochastic Models of Occupants' Environmental Control Behavior Influence Architectural Design Outcomes? - How field data can influence design outcomes
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 1, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 715-724
doi	https://doi.org/10.52842/conf.caadria.2019.1.715
summary	Thermal comfort research has shown that natural ventilation can reduce energy consumption while increasing comfort. However, giving occupants control over their environment introduces uncertainty into building performance which is challenging to emulate using current simulation techniques. Traditionally, window operation is modelled deterministically, for instance by assuming windows to be opened at a predefined temperature. Studies have shown this to be inaccurate, often causing large discrepancies between simulated and actual performance; instead, probabilistic models have emerged based on field study data. The literature on this topic is currently limited to building science and lacks an analysis of how these insights may affect architecture. In a design study, we used evolutionary computation to determine comfort-optimized housing designs for various climates, each time comparing the results of both window operation models. The resulting designs varied considerably; most notably, using the stochastic approach resulted in more shading elements, especially in warmer climates.
keywords	window operation model; stochastic; natural ventilation; thermal comfort; occupant behavior
series	CAADRIA
email
last changed	2022/06/07 07:59

_id	caadria2019_318
id	caadria2019_318
authors	Martinho, Helena, BelÃ©m, Catarina, LeitÃ£o, AntÃ³nio, Loonen, Roel and Gomes, M. GlÃ³ria
year	2019
title	Algorithmic Design and Performance Analysis of Adaptive FaÃ§ades
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 1, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 685-694
doi	https://doi.org/10.52842/conf.caadria.2019.1.685
summary	Building performance simulation tools have the potential for aiding the decision-making process in early design stages of an architectural project. As traditional simulation tools are based on a static design and adaptive faÃ§ades encompass an envisioned movement of construction elements, there is a lack of supporting tools and workflows that can correctly evaluate the performance of such building envelopes at an early stage. The presented ongoing research focuses on developing efficient parametric performance-based approaches for assessing the energy consumption in buildings with adaptive faÃ§ades, combining generative architectural design and performance analysis in a seamless workflow. To this end, we combine a new algorithmic design research tool with the well-established whole-building simulation engine EnergyPlus. The purpose of linking both tools lies in the possibility of generating and simulating models with adaptive faÃ§ade mechanisms through a single script, evaluating and using the simulation results to adjust the model's parameters and develop optimized control strategies.
keywords	Building performance simulation; Adaptive faÃ§ades; Algorithmic design; Energy analysis
series	CAADRIA
email
last changed	2022/06/07 07:59

_id	ijac201917104
id	ijac201917104
authors	Matthews, Linda and Gavin Perin
year	2019
title	Exploiting ambiguity: The diffraction artefact and the architectural surface
source	International Journal of Architectural Computing vol. 17 - no. 1, 103-115
summary	In the contemporary ‘envisioned’ environment, Internet webcams, low- and high-altitude unmanned aerial vehicles and satellites are the new vantage points from which to construct the image of the city. Armed with hi-resolution digital optical technologies, these vantage points effectively constitute a ubiquitous visioning apparatus serving either the politics of promotion or surveillance. Given the political dimensions of this apparatus, it is important to note that this digital imaging of public urban space refers to the human visual system model. In order to mimic human vision, a set of algorithm patterns are used to direct numerous ‘soft’ and ‘hard’ technologies. Mimicry thus has a cost because this insistence on the human visual system model necessitates multiple transformative moments in the production and transmission pipeline. If each transformative moment opens a potential vulnerability within the visioning apparatus, then every glitch testifies to the artificiality of the image. Moreover, every glitch potentially interrupts the political narratives be communicated in contemporary image production and transmission. Paradoxically, the current use of scripting to create glitch-like images has reimagined glitches as a discrete aesthetic category. This article counters this aestheticisation by asserting glitching as a disruption in communication. The argument will rely on scaled tests produced by one of the authors who show how duplicating the digital algorithmic patterns used within the digital imaging pipeline on any exterior building surface glitches the visual data captured within that image. Referencing image-based techniques drawn from the Baroque and contemporary modes of camouflage, it will be argued that the visual aberrations created by these algorithm-based patterned facades can modify strategically the ‘emission signature’ of selected parts of the urban fabric. In this way, the glitch becomes a way to intercede in the digital portrayal of city.
keywords	Surveillance, algorithms, diffraction, pattern, disruptive, optics
series	journal
email
last changed	2019/08/07 14:04

_id	caadria2019_127
id	caadria2019_127
authors	Nam, Hyunjae
year	2019
title	Programming Intelligent Architecture to be Responsive to Real-Time Data
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 2, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 273-282
doi	https://doi.org/10.52842/conf.caadria.2019.2.273
summary	This study examines the development of intelligent architecture capable of reading real-time data and controlling spatial configurations accordingly. In terms of responsiveness at an architectural scale, it is questionable whether an architectural system can adapt or adjust its spatial configurations to the time-based changes of social activities. The urban open data movement allows individuals to navigate or measure real-time occurrences in cities, and such data can be used to accommodate users' demands for social space. Exploiting urban open data, the design experiment focused on extracting data pertaining to real occurrences of social activities and weather conditions in a city, setting an algorithm mapping the sequence from the data to architectural behaviours, and simulating the architectural model in real time. By means of proposing a design strategy, this research contributes to cross-disciplinary approaches to developing smart buildings and cities.
keywords	real-time data; urban open data; weather API; architectural responsiveness
series	CAADRIA
email
last changed	2022/06/07 07:59

_id	ijac201917302
id	ijac201917302
authors	Nisztuk, Maciej and Pawel B. Myszkowski
year	2019
title	Hybrid Evolutionary Algorithm applied to Automated Floor Plan Generation 260
source	International Journal of Architectural Computing vol. 17 - no. 3, 260-283
summary	The article presents the application of Hybrid Evolutionary and Greedy-based algorithms to the problem of Automated Floor Plan Generation. The described optimization issue is part of a wider domain of Computer-Aided Architectural Design. The article covers the extensive description of the representation domain model (architectural canonical guidelines, user design requirements and constraints) and the explanation of proposed approach: problem representation, genetic algorithm operators, and fitness function definition. The research experimental procedures are based on real-world data: the architectural design guidelines being the design constraints and five real-world functional programs introduced and proposed as benchmarks. The article summarizes the implementation of the proposed approach, compares the Hybrid Evolutionary Algorithm experimental results with the Greedy-based algorithm, and suggests possible extensions and future research directions.
keywords	Computer-Aided Architectural Design, optimization in CAAD, Automated Floor Plan Generation, Hybrid Evolutionary Algorithm, optimization, benchmark
series	journal
email
last changed	2020/11/02 13:34

_id	caadria2020_259
id	caadria2020_259
authors	Rhee, Jinmo, Veloso, Pedro and Krishnamurti, Ramesh
year	2020
title	Integrating building footprint prediction and building massing - an experiment in Pittsburgh
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 2, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 669-678
doi	https://doi.org/10.52842/conf.caadria.2020.2.669
summary	We present a novel method for generating building geometry using deep learning techniques based on contextual geometry in urban context and explore its potential to support building massing. For contextual geometry, we opted to investigate the building footprint, a main interface between urban and architectural forms. For training, we collected GIS data of building footprints and geometries of parcels from Pittsburgh and created a large dataset of Diagrammatic Image Dataset (DID). We employed a modified version of a VGG neural network to model the relationship between (c) a diagrammatic image of a building parcel and context without the footprint, and (q) a quadrilateral representing the original footprint. The option for simple geometrical output enables direct integration with custom design workflows because it obviates image processing and increases training speed. After training the neural network with a curated dataset, we explore a generative workflow for building massing that integrates contextual and programmatic data. As trained model can suggest a contextual boundary for a new site, we used Massigner (Rhee and Chung 2019) to recommend massing alternatives based on the subtraction of voids inside the contextual boundary that satisfy design constraints and programmatic requirements. This new method suggests the potential that learning-based method can be an alternative of rule-based design methods to grasp the complex relationships between design elements.
keywords	Deep Learning; Prediction; Building Footprint; Massing; Generative Design
series	CAADRIA
email
last changed	2022/06/07 07:56

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