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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_id	ascaad2021_022
id	ascaad2021_022
authors	Baºarir, Lale; Kutluhan Erol
year	2021
title	Briefing AI: From Architectural Design Brief Texts to Architectural Design Sketches
source	Abdelmohsen, S, El-Khouly, T, Mallasi, Z and Bennadji, A (eds.), Architecture in the Age of Disruptive Technologies: Transformations and Challenges [9th ASCAAD Conference Proceedings ISBN 978-1-907349-20-1] Cairo (Egypt) [Virtual Conference] 2-4 March 2021, pp. 23-31
summary	The main focus of this research is to uncover the underlying intuitive knowledge of architecture with the help of machine learning models. To achieve this, a generic architectural design process is considered and divided into iterative portions based on their output for each phase. This study looks into the initial portion of the architectural design process called “Briefing”. The authors search for the intuition that exists within the design process and how it can be learned by artificial intelligence (AI) that is currently gained through master-apprentice relationship and experience that builds up this knowledge. In this study, a way to enable users to attain an architectural design sketch while defining an architectural design problem with text is explored. This on-going research decomposes the components of the briefing and preliminary design sketching processes. Therefore the domain knowledge at each phase is considered for translating to constraints via natural language processing (NLP) and machine learning (ML) models such as Generative Adversarial Networks (GANs).
series	ASCAAD
type	normal paper
email
last changed	2021/08/09 13:11

_id	acadia21_572
id	acadia21_572
authors	Rodrigues, Ricardo Cesar; Alzate-Martinez, Fábio A.; Escobar, Daniel; Mistry, Mayur
year	2021
title	Rendering Conceptual Design Ideas with Artificial Intelligence
doi	https://doi.org/10.52842/conf.acadia.2021.572
source	ACADIA 2021: Realignments: Toward Critical Computation [Proceedings of the 41st Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-986-08056-7]. Online and Global. 3-6 November 2021. edited by S. Parascho, J. Scott, and K. Dörfler. 572-575.
summary	This paper documents a data-driven approach to a conceptual rendering workflow with Artificial Intelligence (AI) models. This work originates from the workshop ‘Intro to AI for Architectural Design Explorations’ lectured by the authors Mayur Mistry and Daniel Escobar, during the event ‘Inclusive FUTURES 2021’ at the Digital Futures platform. The observations reflect about the applicability of machine-augmented conceptual design. As a common practice in the fi eld, architects start designing their buildings by sketching their ideas, this is a process that attempts to translate a concept into a spatial and aesthetic solution. Nevertheless, the design process is an iterative and time-consuming task. For this reason, we must experiment new methods that can potentially enhance architectural practice.
series	ACADIA
type	field note
email
last changed	2023/10/22 12:06

_id	ascaad2021_000
id	ascaad2021_000
authors	Abdelmohsen, S, El-Khouly, T, Mallasi, Z and Bennadji, A (eds.)
year	2021
title	ASCAAD 2021: Architecture in the Age of Disruptive Technologies - Transformation and Challenges
source	Architecture in the Age of Disruptive Technologies: Transformations and Challenges [9th ASCAAD Conference Proceedings ISBN 978-1-907349-20-1] Cairo (Egypt) [Virtual Conference] 2-4 March 2021.
summary	The ASCAAD 2021 conference theme addresses the gradual shift in computational design from prototypical morphogenetic-centered associations in the architectural discourse. This imminent shift of focus is increasingly stirring a debate in the architectural community and is provoking a much needed critical questioning of the role of computation in architecture as a sole embodiment and enactment of technical dimensions, into one that rather deliberately pursues and embraces the humanities as an ultimate aspiration. We have encouraged researchers and scholars in the CAAD community to identify relevant visions and challenging aspects such as: from the tangible to the intangible, from the physical to the phenomenological, from mass production to mass customization, from the artifact-centered to the human-centered, and from formalistic top-down approaches to informed bottom-up approaches. A parallel evolving impact in the field of computational design and innovation is the introduction of disruptive technologies which are concurrently transforming practices and businesses. These technologies tend to provoke multiple transformations in terms of processes and workflows, methodologies and strategies, roles and responsibilities, laws and regulations, and consequently formulating diverse emergent modes of design thinking, collaboration, and innovation. Technologies such as mixed reality, cloud computing, robotics, big data, and Internet of Things, are incessantly changing the nature of the profession, inciting novel modes of thinking and rethinking architecture, developing new norms and impacting the future of architectural education. With this booming pace into highly disruptive modes of production, automation, intelligence, and responsiveness comes the need for a revisit of the inseparable relation between technology and the humanities, where it is possible to explore the urgency of a pressing dialogue between the transformative nature of the disruptive on the one hand and the cognitive, the socio-cultural, the authentic, and the behavioral on the other.
series	ASCAAD
last changed	2022/05/19 11:45

_id	ascaad2021_074
id	ascaad2021_074
authors	Belkaid, Alia; Abdelkader Ben Saci, Ines Hassoumi
year	2021
title	Human-Computer Interaction for Urban Rules Optimization
source	Abdelmohsen, S, El-Khouly, T, Mallasi, Z and Bennadji, A (eds.), Architecture in the Age of Disruptive Technologies: Transformations and Challenges [9th ASCAAD Conference Proceedings ISBN 978-1-907349-20-1] Cairo (Egypt) [Virtual Conference] 2-4 March 2021, pp. 603-613
summary	Faced with the complexity of manual and intuitive management of urban rules in architectural and urban design, this paper offers a collaborative and digital human-computer approach. It aims to have an Authorized Bounding Volume (ABV) which uses the best target values of urban rules. It is a distributed constraint optimization problem. The ABV Generative Model uses multi-agent systems. It offers an intelligent system of urban morphology able to transform the urban rules, on a given plot, into a morphological delimitation permitted by the planning regulations of a city. The overall functioning of this system is based on two approaches: construction and supervision. The first is conducted entirely by the machine and the second requires the intervention of the designer to collaborate with the machine. The morphological translation of urban rules is sometimes contradictory and may require additional external relevance to urban rules. Designer arbitration assists the artificial intelligence in accomplishing this task and solving the problem. The Human-Computer collaboration is achieved at the appropriate time and relies on the degree of constraint satisfaction with fitness function. The resolution of the distributed constraint optimization problem is not limited to an automatic generation of urban rules, but involves also the production of multiple optimal-ABV conditioned both by urban constraints as well as relevance, chosen by the designer.
series	ASCAAD
email
last changed	2021/08/09 13:13

_id	caadria2021_389
id	caadria2021_389
authors	del Campo, Matias
year	2021
title	Architecture,Language and AI - Language,Attentional Generative Adversarial Networks (AttnGAN) and Architecture Design
doi	https://doi.org/10.52842/conf.caadria.2021.1.211
source	A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 1, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 211-220
summary	The motivation to explore Attentional Generative Adversarial Networks (AttnGAN) as a design technique in architecture can be found in the desire to interrogate an alternative design methodology that does not rely on images as starting point for architecture design, but language. Traditionally architecture design relies on visual language to initiate a design process, wither this be a napkin sketch or a quick doodle in a 3D modeling environment. AttnGAN explores the information space present in programmatic needs, expressed in written form, and transforms them into a visual output. The key results of this research are shown in this paper with a proof-of-concept project: the competition entry for the 24 Highschool in Shenzhen, China. This award-winning project demonstrated the ability of GraphCNN to serve as a successful design methodology for a complex architecture program. In the area of Neural Architecture, this technique allows to interrogate shape through language. An alternative design method that creates its own unique sensibility.
keywords	Artificial Intelligence; Machine Learning; Artificial Neural Networks; Semiotics; Design Methodology
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	ascaad2021_112
id	ascaad2021_112
authors	Hassab, Ahmed; Sherif Abdelmohsen, Mohamed Abdallah
year	2021
title	Generative Design Methodology for Double Curved Surfaces using AI
source	Abdelmohsen, S, El-Khouly, T, Mallasi, Z and Bennadji, A (eds.), Architecture in the Age of Disruptive Technologies: Transformations and Challenges [9th ASCAAD Conference Proceedings ISBN 978-1-907349-20-1] Cairo (Egypt) [Virtual Conference] 2-4 March 2021, pp. 622-635
summary	Despite recent approaches to generate unique surfaces using generative design algorithms, there are still challenges including teaching machines how to learn and manipulate surfaces, thus generating novel and unique versions, and exploring possible alternatives in producing unique surfaces using artificial intelligence. This paper proposes a generative design approach using Al. We propose a generative design methodology for producing novel and unique surfaces by faking input surfaces using artificial intelligence networks. This workflow is applied to two different artificial networks: (1) CycleGAN, (2) Pix2Pix and Augmentor. This experimentation is introduced to apply two real surfaces generating two fake surfaces as a unique version through the networks. Upon running the CycleGANs, Pix2Pix, and a Grasshopper script, the experiment results demonstrated how the proposed generative design methodology using AI produced a unique surface version with a higher level of manipulation and result control.
series	ASCAAD
email
last changed	2021/08/09 13:13

_id	ecaade2021_237
id	ecaade2021_237
authors	Sönmez, Ayça and Gönenç Sorguç, Arzu
year	2021
title	Computer-Aided Fabrication Technologies as Computational Design Mediators
doi	https://doi.org/10.52842/conf.ecaade.2021.1.465
source	Stojakovic, V and Tepavcevic, B (eds.), Towards a new, configurable architecture - Proceedings of the 39th eCAADe Conference - Volume 1, University of Novi Sad, Novi Sad, Serbia, 8-10 September 2021, pp. 465-474
summary	The developments in recent technologies through Industry 4.0 lead to the integration of digital design and manufacturing processes. Albeit manufacturing continues to increase its importance as design input, it is generally considered at the last stages of the design process. This misconception results in a gap between digital design and fabrication, leading to differences between the initial design and the fabricated outcome in the context of architectural tectonics. Here, we present an artificial intelligence (AI)-based approach that aims to provide a basis to bridge the gap between computation and fabrication. We considered a case study of a 3D model in two stages. In the first stage, an intuitive and top-down design process is adopted, and in the second stage, an AI-based exploration is conducted with three cases derived from the same 3D model. The outcomes of the two stages provided a dataset including different design parameters to be used in a decision tree classifier algorithm which selects the manufacturing method for a given 3D model. Our results show that generative design simulations based on manufacturing constraints can provide a significant variety of manufacturable design alternatives, and minimizes the difference between design alternatives. Using our proposed approach, the time spent in form-finding and fabrication can be reduced significantly. Additionally, the implementation of decision tree classifier learning algorithm shows that AI can serve designers to make accurate predictions for manufacturing method.
keywords	Generative Design; Computer-Aided Fabrication; Arcihtecture 4.0; Artificial Intelligence; Digital Tectonics
series	eCAADe
email
last changed	2022/06/07 07:56

_id	caadria2021_446
id	caadria2021_446
authors	Zhou, Yifan and Park, Hyoung-June
year	2021
title	Sketch with Artificial Intelligence (AI) - A Multimodal AI Approach for Conceptual Design
doi	https://doi.org/10.52842/conf.caadria.2021.1.201
source	A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 1, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 201-210
summary	The goal of the research is to investigate an AI approach to assist architects with multimodal inputs (sketches and textual information) for conceptual design. With different textual inputs, the AI approach generates the architectural stylistic variations of a users initial sketch input as a design inspiration. A novel machine learning approach for the multimodal input system is introduced and compared to other approaches. The machine learning approach is performed through procedural training with the content curation of training data in order to control the fidelity of generated designs from the input and to manage their diversity. In this paper, the framework of the proposed AI approach is explained. Furthermore, the implementation of its prototype is demonstrated with various examples.
keywords	Artificial Intelligence; Stylistic Variations; Multimodal Input; Content Curation; Procedural Training
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	cdrf2021_92
id	cdrf2021_92
authors	Ana Zimbarg
year	2021
title	Bio-Design Intelligence
doi	https://doi.org/https://doi.org/10.1007/978-981-16-5983-6_9
source	Proceedings of the 2021 DigitalFUTURES The 3rd International Conference on Computational Design and Robotic Fabrication (CDRF 2021)
summary	Architecture has a substantial influence worldwide as it shapes our cities, and it is made to last. Urban areas are also responsible for 70% of the world’s carbon emissions. Consequently, architects are responsible for minimising the destructive effects of construction on the environment. How can biological intelligence be inserted in architecture as a possibility to increase environmental performance? Bio-design goes further than biology-inspired approaches. Biodesign refers to incorporating living organisms as an essential component of a system, changing the natural and built environment boundaries. It contains living and machine intelligence, whether embedded in the design process or in the building itself. This paper seeks to give an overview of bio-design and how it can be seen as a strategy of thinking of new research pathways.
series	cdrf
email
last changed	2022/09/29 07:53

_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
doi	https://doi.org/10.52842/conf.ecaade.2021.2.351
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
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	ijac202119106
id	ijac202119106
authors	Del Campo, Matias; Alexandra Carlson, and Sandra Manninger
year	2021
title	Towards Hallucinating Machines - Designing with Computational Vision
source	International Journal of Architectural Computing 2021, Vol. 19 - no. 1, 88–103
summary	There are particular similarities in how machines learn about the nature of their environment, and how humans learn to process visual stimuli. Machine Learning (ML), more specifically Deep Neural network algorithms rely on expansive image databases and various training methods (supervised, unsupervised) to “make sense” out of the content of an image. Take for example how students of architecture learn to differentiate various architectural styles. Whether this be to differentiate between Gothic, Baroque or Modern Architecture, students are exposed to hundreds, or even thousands of images of the respective styles, while being trained by faculty to be able to differentiate between those styles. A reversal of the process, striving to produce imagery, instead of reading it and understanding its content, allows machine vision techniques to be utilized as a design methodology that profoundly interrogates aspects of agency and authorship in the presence of Artificial Intelligence in architecture design. This notion forms part of a larger conversation on the nature of human ingenuity operating within a posthuman design ecology. The inherent ability of Neural Networks to process large databases opens up the opportunity to sift through the enormous repositories of imagery generated by the architecture discipline through the ages in order to find novel and bespoke solutions to architectural problems. This article strives to demystify the romantic idea of individual artistic design choices in architecture by providing a glimpse under the hood of the inner workings of Neural Network processes, and thus the extent of their ability to inform architectural design.The approach takes cues from the language and methods employed by experts in Deep Learning such as Hallucinations, Dreaming, Style Transfer and Vision. The presented approach is the base for an in-depth exploration of its meaning as a cultural technique within the discipline. Culture in the extent of this article pertains to ideas such as the differentiation between symbolic and material cultures, in which symbols are defined as the common denominator of a specific group of people.1 The understanding and exchange of symbolic values is inherently connected to language and code, which ultimately form the ingrained texture of any form of coded environment, including the coded structure of Neural Networks.A first proof of concept project was devised by the authors in the form of the Robot Garden. What makes the Robot Garden a distinctively novel project is the motion from a purely two dimensional approach to designing with the aid of Neural Networks, to the exploration of 2D to 3D Neural Style Transfer methods in the design process.
keywords	Artificial intelligence, design agency, neural networks, machine learning, machine vision
series	journal
email
last changed	2021/06/03 23:29

_id	ascaad2021_062
id	ascaad2021_062
authors	Elgobashi, Aya; Yasmeen El Semary
year	2021
title	Redefinition of Heritage Public Spaces Using PPGIS: The Case of Religious Complex in Old Cairo
source	Abdelmohsen, S, El-Khouly, T, Mallasi, Z and Bennadji, A (eds.), Architecture in the Age of Disruptive Technologies: Transformations and Challenges [9th ASCAAD Conference Proceedings ISBN 978-1-907349-20-1] Cairo (Egypt) [Virtual Conference] 2-4 March 2021, pp. 355-370
summary	Plenty of challenges all over the world are affecting the urban development of spaces in the cities, especially those of heritage sites; these urban spaces provide various ambiances that appeal to the senses. Although surrounded open spaces in heritage sites are full of rich, deep knowledge that plays an active role in the community perceptions, it has been recently neglected. A contribution is paid to the combination of digital technologies to help in preserving those spaces. Its integrated use could exponentially increase the effectiveness of conservation strategies of ancient buildings. GIS technology became a usual documentation tool for heritage managers, conservators, restorers, architects, archaeologists, painters, and all other categories of experts involved in cultural heritage activities. Consequently, the GIS has faced strong criticism as it is a tool for documentation without engaging in the public environment and the users’ needs; as a result, GIS cannot help in any enhancing process as it does not have any idea about the needs of the users. This paper analyses public uses efficiency in heritage public spaces in Cairene context using public participation geographic information system (PPGIS) methodology, as it gives attention to the term “user” to include the “public” incorporating the concept of “public participation” commonly used in planning. An online survey was set up, based on Google Maps, where respondents were asked to place and rate twenty-five items on an interactive map done by (ARCGIS 10.4). These items were based on the criteria of placemaking to make those spaces full of creative ambiance to be more attractive and useful to the communities. Finally, 200 valid surveys have been collected and mapped 1500 opinions have been mapped. The Results of this research show that PPGIS is an effective tool in measuring the efficiency of those heritage public spaces, which may be valuable for future planning.
series	ASCAAD
email
last changed	2021/08/09 13:13

_id	ascaad2021_150
id	ascaad2021_150
authors	Fathima, Linas; Chithra K
year	2021
title	Shapegrammar: A Tool for Research in Traditional Architecture
source	Abdelmohsen, S, El-Khouly, T, Mallasi, Z and Bennadji, A (eds.), Architecture in the Age of Disruptive Technologies: Transformations and Challenges [9th ASCAAD Conference Proceedings ISBN 978-1-907349-20-1] Cairo (Egypt) [Virtual Conference] 2-4 March 2021, pp. 465-478
summary	Every Architectural style consists of an Architectural language with vocabulary, syntax, and semantics. The compositional principles of a particular style can be defined over as a set of rules. These rules can be reformed and converted using mathematical computational techniques using Shape Grammar (A systematic method used for interpreting spatial design and activities). Researchers across the world used shape grammar to analyse design patterns of traditional architectural styles, master architects' works, etc. These rule-based methods can be adopted into computer languages to produce new designs. Traditional Architecture of a region portrays culture integrated with all aspects of human life. The proposed paper is to study the potentials of shape grammar to use as a tool in the research of traditional architectural styles by analysing case studies. The research methodology reviews the previous shape grammar studies conducted in various conventional styles and comparative analysis of the approaches of authors in shape grammar generation. The research by Lambe and Dongre on the formulation of shape grammar of Pol houses of Ahmadabad and Cagdas's work on traditional Turkish houses is an example of this. T Knight had formulated shape grammar of Japanese tea houses, and Yousefniapasha and Teeling developed a grammar of vernacular houses facing rice fields of Mazandaran, Iran. Similarly, many researchers used shape grammars as a tool to analyse traditional architecture. So the study will compare the different traditional shape grammar generations and formulate a sample shape grammar of a traditional prototype to conclude the scope of further research in the domain.
series	ASCAAD
email
last changed	2021/08/09 13:13

_id	ijac202119404
id	ijac202119404
authors	Ghandi, Mona; Blaisdell, Marcus; Ismail, Mohamed
year	2021
title	Embodied empathy: Using affective computing to incarnate human emotion and cognition in architecture
source	International Journal of Architectural Computing 2021, Vol. 19 - no. 4, 532–552
summary	This research aims to develop a cyber-physical adaptive architectural space capable of real-time responses topeople’s emotions, based on biological and neurological data. To achieve this goal, we integrated artificialintelligence (AI), wearable technology, sensory environments, and adaptive architecture to create anemotional bond between a space and its occupants and encourage affective emotional interactions betweenthe two. The project’s objectives were to (1) measure and analyze biological and neurological data to detectemotions, (2) map and illustrate that emotional data, and (3) link occupants’emotions and cognition to a builtenvironment through a real-time emotive feedback loop. Using an interactive installation as a case study, thiswork examines the cognition-emotion-space interaction through changes in volume, color, and light as ameans of emotional expression. It contributes to the current theory and practice of cyber-physical design andthe role AI plays, as well as the interaction of technology and empathy.
keywords	Places and awareness, artificial intelligence and machine learning in design, intelligent responsive spaces,affective computing in architecture, cognition-emotion-space interaction, embodied empathy, neuromorphicdesign, cyber-physical neurospaces
series	journal
email
last changed	2024/04/17 14:29

_id	acadia21_100
id	acadia21_100
authors	Ghandi, Mona; Ismail, Mohamed; Blaisdell, Marcus
year	2021
title	Parasympathy
doi	https://doi.org/10.52842/conf.acadia.2021.100
source	ACADIA 2021: Realignments: Toward Critical Computation [Proceedings of the 41st Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-986-08056-7]. Online and Global. 3-6 November 2021. edited by B. Bogosian, K. Dörfler, B. Farahi, J. Garcia del Castillo y López, J. Grant, V. Noel, S. Parascho, and J. Scott. 100-109.
summary	Parasympathy is an interactive spatial experience operating as an extension of visitors’ minds. By integrating Artificial Intelligence (AI), wearable technologies, affective computing (Picard 1995; Picard 2003), and neuroscience, this project blurs the lines between the physical, digital, and biological spheres and empowers users’ brains to solicit positive changes from their spaces based on their real-time biophysical reactions and emotions. The objective is to deploy these technologies in support of the wellbeing of the community especially when related to social matters such as inclusion and social justice in our built environment. Consequently, this project places the users’ emotions at the very center of its space by performing real-time responses to the emotional state of the individuals within the space.
series	ACADIA
type	project
email
last changed	2023/10/22 12:06

_id	caadria2023_446
id	caadria2023_446
authors	Guida, George
year	2023
title	Multimodal Architecture: Applications of Language in a Machine Learning Aided Design Process
doi	https://doi.org/10.52842/conf.caadria.2023.2.561
source	Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 561–570
summary	Recent advances in Natural Language Processing (NLP) and Diffusion Models (DMs) are leading to a significant change in the way architecture is conceived. With capabilities that surpass those of current generative models, it is now possible to produce an unlimited number of high-quality images (Dhariwal and Nichol 2021). This opens up new opportunities for using synthetic images and marks a new phase in the creation of multimodal 3D forms, central to architectural concept design stages. Presented here are three methodologies of generation of meaningful 2D and 3D designs, merging text-to-image diffusion models Stable Diffusion, and DALL-E 2 with computational methods. These allow designers to intuitively navigate through a multimodal feedback loop of information originating from language and aided by artificial intelligence tools. This paper contributes to our understanding of machine-augmented design processes and the importance of intuitive user interfaces (UI) in enabling new dialogues between humans and machines. Through the creation of a prototype of an accessible UI, this exchange of information can empower designers, build trust in these tools, and increase control over the design process.
keywords	Machine Learning, Diffusion Models, Concept Design, Semantics, User Interface, Design Agency
series	CAADRIA
email
last changed	2023/06/15 23:14

_id	ascaad2021_130
id	ascaad2021_130
authors	Hossameldin, Hala; Ramy Bakir, Sherif Elfiki
year	2021
title	Conditions of Tacit Knowledge Transfer in Architectural Computational Design: An Analytical Review
source	Abdelmohsen, S, El-Khouly, T, Mallasi, Z and Bennadji, A (eds.), Architecture in the Age of Disruptive Technologies: Transformations and Challenges [9th ASCAAD Conference Proceedings ISBN 978-1-907349-20-1] Cairo (Egypt) [Virtual Conference] 2-4 March 2021, pp. 43-56
summary	This paper investigates the transfer of tacit knowledge between designers and the computer in architectural design. Most research efforts in computational architectural design recently focus on the tangible and technical domains of the design process. This resulted in a lack of understanding of the role of other qualitative intangible domains, such as tacit design knowledge, in the computational design process. Despite the attempts of a few recent studies to tackle some tacit aspects within design computing, little research extended further to study how tacit knowledge can be transferred between different entities of the computational design process and how it can be represented. Through an analytical review, the paper will first discuss the notions of tacit knowledge in different disciplines, with particular emphases on architecture. Second, the study reviews the conditions and factors that influence the transfer of tacit knowledge between humans, and accordingly between the human and the computer, as addressed by different architects and authors. The study particularly emphasizes the significance of a human-computer symbiotic relationship for the process of tacit knowledge transfer to take place. In conclusion, this paper presents a theoretical basis for understanding and facilitating the transfer and representation of tacit knowledge in a computational design environment.
series	ASCAAD
email
last changed	2021/08/09 13:13

_id	ijac202119305
id	ijac202119305
authors	Hosseini, Seyed Vahab; Alim, Usman R.; Oehlberg, Lora; Taron, Joshua M.
year	2021
title	Optically illusive architecture (OIA): Introduction and evaluation using virtual reality
source	International Journal of Architectural Computing 2021, Vol. 19 - no. 3, 291–314
summary	Architects and designers communicate their ideas within a range of representational methods. No single instance of these methods, either in the form of orthographic projections or perspectival representation, can address all questions regarding the design, but as a whole, they demonstrate a comprehensive range of information about the building or object they intend to represent. This explicates an inevitable degree of deficiency in representation, regardless of its type. In addition, perspective-based optical illusions manipulate our spatial perception by deliberately misrepresenting the reality. In this regard, they are not new concepts to architectural representation. As a consequence, Optically Illusive Architecture (OIA) is proposed, not as a solution to fill the gap between the representing and represented spaces, but as a design paradigm whose concept derives from and accounts for this gap. By OIA we aim to cast light to an undeniable role of viewpoints in designing architectural spaces. The idea is to establish a methodology in a way that the deficiency of current representational techniques—manifested as specific thread of optical illusions—flourishes into thoughtful results embodied as actual architectural spaces. Within our design paradigm, we define a framework to be able to effectively analyze its precedents, generate new space, and evaluate their efficiencies. Moreover, the framework raises a hierarchical set of questions to differentiate OIA from a visual gimmick. Furthermore, we study two OIA-driven environments, by conducting empirical studies using Virtual Reality (VR). These studies bear essential information, in terms of design performance, and the public’s ability to engage and interact with an OIA space, prior to the actual fabrication of the structures.
keywords	Architectural representation, optical illusion, design evaluation, virtual reality
series	journal
email
last changed	2024/04/17 14:29

_id	cdrf2021_3
id	cdrf2021_3
authors	Jean Jaminet, Gabriel Esquivel, and Shane Bugni
year	2021
title	Serlio and Artificial Intelligence: Problematizing the Image-to-Object Workflow
doi	https://doi.org/https://doi.org/10.1007/978-981-16-5983-6_1
source	Proceedings of the 2021 DigitalFUTURES The 3rd International Conference on Computational Design and Robotic Fabrication (CDRF 2021)
summary	Virtual design production demands that information be increasingly encoded and decoded with image compression technologies. Since the Renaissance, the discourses of language and drawing and their actuation by the classical disciplinary treatise have been fundamental to the production of knowledge within the building arts. These early forms of data compression provoke reflection on theory and technology as critical counterparts to perception and imagination unique to the discipline of architecture. This research examines the illustrated expositions of Sebastiano Serlio through the lens of artificial intelligence (AI). The mimetic powers of technological data storage and retrieval and Serlio’s coded operations of orthographic projection drawing disclose other aesthetic and formal logics for architecture and its image that exist outside human perception. Examination of aesthetic communication theory provides a conceptual dimension of how architecture and artificial intelligent systems integrate both analog and digital modes of information processing. Tools and methods are reconsidered to propose alternative AI workflows that complicate normative and predictable linear design processes. The operative model presented demonstrates how augmenting and interpreting layered generative adversarial networks drive an integrated parametric process of three-dimensionalization. Concluding remarks contemplate the role of human design agency within these emerging modes of creative digital production.
series	cdrf
email
last changed	2022/09/29 07:53

_id	acadia21_112
id	acadia21_112
authors	Kahraman, Ridvan; Zechmeister, Christoph; Dong, Zhetao; Oguz, Ozgur S.; Drachenberg, Kurt; Menges, Achim; Rinderspacher, Katja
year	2021
title	Augmenting Design
doi	https://doi.org/10.52842/conf.acadia.2021.112
source	ACADIA 2021: Realignments: Toward Critical Computation [Proceedings of the 41st Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-986-08056-7]. Online and Global. 3-6 November 2021. edited by B. Bogosian, K. Dörfler, B. Farahi, J. Garcia del Castillo y López, J. Grant, V. Noel, S. Parascho, and J. Scott. 112-121.
summary	In recent years, generative machine learning methods such as variational autoencoders (VAEs) and generative adversarial networks (GANs) have opened up new avenues of exploration for architects and designers. The presented work explores how these methods can be expanded by incorporating multiple abstract criteria directly into the formulation of the algorithm that negotiates these complex criteria and proposes a fitting design. It draws inspiration from the works of several design theorists who have developed such goal-oriented approaches to design, and sets up multiple-objective VAE and GAN frameworks with this idea in mind. The research demonstrates that by incorporating multiple constraints using auxiliary discriminator networks, the developed algorithms are able to generate innovative solutions to two example problems: the design of 2D digits, and the design of 3D voxel chairs. By speculating and examining the role of the designer in data based generative computational design workflows, the research aims to provide an approach for solving design tasks in the age of big data.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

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