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	ijac201816406
id	ijac201816406
authors	As, Imdat; Siddharth Pal and Prithwish Basu
year	2018
title	Artificial intelligence in architecture: Generating conceptual design via deep learning
source	International Journal of Architectural Computing vol. 16 - no. 4, 306-327
summary	Artificial intelligence, and in particular machine learning, is a fast-emerging field. Research on artificial intelligence focuses mainly on image-, text- and voice-based applications, leading to breakthrough developments in self-driving cars, voice recognition algorithms and recommendation systems. In this article, we present the research of an alternative graph- based machine learning system that deals with three-dimensional space, which is more structured and combinatorial than images, text or voice. Specifically, we present a function-driven deep learning approach to generate conceptual design. We trained and used deep neural networks to evaluate existing designs encoded as graphs, extract significant building blocks as subgraphs and merge them into new compositions. Finally, we explored the application of generative adversarial networks to generate entirely new and unique designs.
keywords	Architectural design, conceptual design, deep learning, artificial intelligence, generative design
series	journal
email
last changed	2019/08/07 14:04

_id	caadria2018_126
id	caadria2018_126
authors	Khean, Nariddh, Kim, Lucas, Martinez, Jorge, Doherty, Ben, Fabbri, Alessandra, Gardner, Nicole and Haeusler, M. Hank
year	2018
title	The Introspection of Deep Neural Networks - Towards Illuminating the Black Box - Training Architects Machine Learning via Grasshopper Definitions
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 2, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 237-246
doi	https://doi.org/10.52842/conf.caadria.2018.2.237
summary	Machine learning is yet to make a significant impact in the field of architecture and design. However, with the combination of artificial neural networks, a biologically inspired machine learning paradigm, and deep learning, a hierarchical subsystem of machine learning, the predictive capabilities of machine learning processes could prove a valuable tool for designers. Yet, the inherent knowledge gap between the fields of architecture and computer science has meant the complexity of machine learning, and thus its potential value and applications in the design of the built environment remain little understood. To bridge this knowledge gap, this paper describes the development of a learning tool directed at architects and designers to better understand the inner workings of machine learning. Within the parametric modelling environment of Grasshopper, this research develops a framework to express the mathematic and programmatic operations of neural networks in a visual scripting language. This offers a way to segment and parametrise each neural network operation into a basic expression. Unpacking the complexities of machine learning in an intermediary software environment such as Grasshopper intends to foster the broader adoption of artificial intelligence in architecture.
keywords	machine learning; neural network; action research; supervised learning; education
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	ijac201816407
id	ijac201816407
authors	Mahankali, Ranjeeth; Brian R. Johnson and Alex T. Anderson
year	2018
title	Deep learning in design workflows: The elusive design pixel
source	International Journal of Architectural Computing vol. 16 - no. 4, 328-340
summary	The recent wave of developments and research in the field of deep learning and artificial intelligence is causing the border between the intuitive and deterministic domains to be redrawn, especially in computer vision and natural language processing. As designers frequently invoke vision and language in the context of design, this article takes a step back to ask if deep learning’s capabilities might be applied to design workflows, especially in architecture. In addition to addressing this general question, the article discusses one of several prototypes, BIMToVec, developed to examine the use of deep learning in design. It employs techniques like those used in natural language processing to interpret building information models. The article also proposes a homogeneous data format, provisionally called a design pixel, which can store design information as spatial-semantic maps. This would make designers’ intuitive thoughts more accessible to deep learning algorithms while also allowing designers to communicate abstractly with design software.
keywords	Associative logic, creative processes, deep learning, embedding vectors, BIMToVec, homogeneous design data format, design pixel, idea persistence
series	journal
email
last changed	2019/08/07 14:04

_id	ecaade2018_w12
id	ecaade2018_w12
authors	Rahbar, Morteza
year	2018
title	Application of Artificial Intelligence in Architectural Generative Design
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 71-72
doi	https://doi.org/10.52842/conf.ecaade.2018.1.071
summary	In this workshop, data-driven models will be discussed and how they could change the way architects think, design and analyse. Both supervised and unsupervised learning models will be discussed and different projects will be referred as examples. Deep learning models are the third part of the workshop and more specifically, Generative Adversarial Networks will be mentioned in more detail. The GAN's open a new field of generative models in design which is based on data-driven process and we will go into detail with GANs, their branches and how we could test a sample architecture generative problem with GANs.
keywords	Artificial Intelligence; Machine Learning; Generative Design; Knowledge based Design; GAN
series	eCAADe
email
last changed	2022/06/07 08:00

_id	ecaade2018_301
id	ecaade2018_301
authors	Cocho-Bermejo, Ana, Birgonul, Zeynep and Navarro-Mateu, Diego
year	2018
title	Adaptive & Morphogenetic City Research Laboratory
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 2, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 659-668
doi	https://doi.org/10.52842/conf.ecaade.2018.2.659
summary	"Smart City" business model is guiding the development of future metropolises. Software industry sales to town halls for city management services efficiency improvement are, these days, a very pro?table business. Being the model decided by the industry, it can develop into a dangerous situation in which the basis of the new city design methodologies is decided by agents outside academia expertise. Drawing on complex science, social physics, urban economics, transportation theory, regional science and urban geography, the Lab is dedicated to the systematic analysis of, and theoretical speculation on, the recently coined "Science of Cities" discipline. On the research agenda there are questions arising from the synthesis of architecture, urban design, computer science and sociology. Collaboration with citizens through inclusion and empowerment, and, relationships "City-Data-Planner-Citizen" and "Citizen-Design-Science", configure Lab's methodology provoking a dynamic responsive process of design that is yet missing on the path towards the real responsive city.
keywords	Smart City; Morphogenetic Urban Design; Internet of Things; Building Information Modelling; Evolutionary Algorithms; Machine Learning & Artificial Intelligence
series	eCAADe
email
last changed	2022/06/07 07:56

_id	ecaade2018_111
id	ecaade2018_111
authors	Khean, Nariddh, Fabbri, Alessandra and Haeusler, M. Hank
year	2018
title	Learning Machine Learning as an Architect, How to? - Presenting and evaluating a Grasshopper based platform to teach architecture students machine learning
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 95-102
doi	https://doi.org/10.52842/conf.ecaade.2018.1.095
summary	Machine learning algorithms have become widely embedded in many aspects of modern society. They have come to enhance systems, such as individualised marketing, social media services, and search engines. However, contrasting its growing ubiquity, the architectural industry has been comparatively resistant in its adoption; objectively one of the slowest industries to integrate with machine learning. Machine learning expertise can be separate from professionals in other fields; however, this separation can be a major hinderance in architecture, where interaction between the designer and the design facilitates the production of favourable outcomes. To bridge this knowledge gap, this research suggests that the solution lies with architectural education. Through the development of a novel educative framework, the research aims to teach architecture students how to implement machine learning. Exploration of student-centred pedagogical strategies was used to inform the conceptualisation of the educative module, which was subsequently implemented into an undergraduate computational design studio, and finally evaluated on its ability to effectively teach designers machine learning. The developed educative module represents a step towards greater technological adoption in the architecture industry.
keywords	Artificial Intelligence; Machine Learning; Neural Networks; Student-Centred Learning; Educative Framework
series	eCAADe
email
last changed	2022/06/07 07:52

_id	acadia18_166
id	acadia18_166
authors	Kvochick, Tyler
year	2018
title	Sneaky Spatial Segmentation. Reading Architectural Drawings with Deep Neural Networks and Without Labeling Data
source	ACADIA // 2018: Recalibration. On imprecisionand infidelity. [Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-17729-7] Mexico City, Mexico 18-20 October, 2018, pp. 166-175
doi	https://doi.org/10.52842/conf.acadia.2018.166
summary	Currently, it is nearly impossible for an artificial neural network to generalize a task from very few examples. Humans, however, excel at this. For instance, it is not necessary for a designer to see thousands or millions of unique examples of how to place a given drawing symbol in a way that meets the economic, aesthetic, and performative goals of the project. In fact, the goals can be (and usually are) communicated abstractly in natural language. Machine learning (ML) models, however, do need numerous examples. The methods that we explore here are an attempt to circumvent this in order to make ML models more immediately useful. In this work, we present progress on the application of contemporary ML techniques to the design process in the architecture, engineering, and construction (AEC) industry. We introduce a technique to partially circumvent the data hungriness of neural networks, which is a significant impediment to their application outside of the ML research community. We also show results on the applicability of this technique to real-world drawings and present research that addresses how some fundamental attributes of drawings as images affect the way they are interpreted in deep neural networks. Our primary contribution is a technique to train a neural network to segment real-world architectural drawings after using only generated pseudodrawings.
keywords	full paper, representation + perception, computation, ai & machine learning
series	ACADIA
type	paper
email
last changed	2022/06/07 07:51

_id	ecaade2018_315
id	ecaade2018_315
authors	Koehler, Daniel, Abo Saleh, Sheghaf, Li, Hua, Ye, Chuwei, Zhou, Yaonaijia and Navasaityte, Rasa
year	2018
title	Mereologies - Combinatorial Design and the Description of Urban Form.
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 2, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 85-94
doi	https://doi.org/10.52842/conf.ecaade.2018.2.085
summary	This paper discusses the ability to apply machine learning to the combinatorial design-assembly at the scale of a building to urban form. Connecting the historical lines of discrete automata in computer science and formal studies in architecture this research contributes to the field of additive material assemblies, aggregative architecture and their possible upscaling to urban design. The following case studies are a preparation to apply deep-learning on the computational descriptions of urban form. Departing from the game Go as a testbed for the development of deep-learning applications, an equivalent platform can be designed for architectural assembly. By this, the form of a building is defined via the overlap between separate building parts. Building on part-relations, this research uses mereology as a term for a set of recursive assembly strategies, integrated into the design aspects of the building parts. The models developed by research by design are formally described and tested under a digital simulation environment. The shown case study shows the process of how to transform geometrical elements to architectural parts based merely on their compositional aspects either in horizontal or three-dimensional arrangements.
keywords	Urban Form; Discrete Automata ; Combinatorics; Part-Relations; Mereology; Aggregative Architecture
series	eCAADe
email
last changed	2022/06/07 07:51

_id	acadia18_000
id	acadia18_000
authors	Anzalone, Phillip; Del Signore,Marcella; Wit, Andrew John (eds.)
year	2018
title	ACADIA 2018: Re/Calibration: On Imprecision and Infidelity
source	Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-17729-7, Mexico City, Mexico 18-20 October, 2018, 482 p.
doi	https://doi.org/10.52842/conf.acadia.2018
summary	Contained in this years paper proceedings are an unbiased mixed of the precise/imprecise and the computationally faithful/unfaithful. The juxtaposition of this seeming contradictory research and/or projects paints a picture of a broadening computational discourse at the intersection of art, science and technology. The presented research mediates physical, digital, virtual and mixed realities, bridges scales from the singular material compounds to the complex conglomerations associated with the urban environment, and all the while pushing against the limits of design both on Earth and beyond. This year’s conference calls into question how we within the disciplines of architecture and design as well as those outside view the role of computation, production and advanced technologies such as robotics and artificial intelligence within architecture, design and the built environment.
series	ACADIA
last changed	2022/06/07 07:49

_id	acadia18_226
id	acadia18_226
authors	Glynn, Ruairi; Abramovic, Vasilija; Overvelde, Johannes T. B.
year	2018
title	Edge of Chaos. Towards intelligent architecture through distributed control systems based on Cellular Automata.
source	ACADIA // 2018: Recalibration. On imprecisionand infidelity. [Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-17729-7] Mexico City, Mexico 18-20 October, 2018, pp. 226-231
doi	https://doi.org/10.52842/conf.acadia.2018.226
summary	From the “Edge of Chaos”, a mathematical space discovered by computer scientist Christopher Langton (1997), compelling behaviors originate that exhibit both degrees of organization and instability creating a continuous dance between order and chaos. This paper presents a project intended to make this complex theory tangible through an interactive installation based on metamaterial research which demonstrates emergent behavior using Cellular Automata (CA) techniques, illustrated through sound, light and motion. We present a multi-sensory narrative approach that encourages playful exploration and contemplation on perhaps the biggest questions of how life could emerge from the disorder of the universe. We argue a way of creating intelligent architecture, not through classical Artificial Intelligence (AI), but rather through Artificial Life (ALife), embracing the aesthetic emergent possibilities that can spontaneously arise from this approach. In order to make these ideas of emergent life more tangible we present this paper in four integrated parts, namely: narrative, material, hardware and computation. The Edge of Chaos installation is an explicit realization of creating emergent systems and translating them into an architectural design. Our results demonstrate the effectiveness of a custom CA for maximizing aesthetic impact while minimizing the live time of architectural kinetic elements.
keywords	work in progress, complexity, responsive architecture, distributed computing, emergence, installation, interactive architecture, cellular automata
series	ACADIA
type	paper
email
last changed	2022/06/07 07:51

_id	sigradi2018_1693
id	sigradi2018_1693
authors	Granero, Adriana Edith
year	2018
title	The Inclusion of decentralized and self-organized system in the process of construction of design thinking
source	SIGraDi 2018 [Proceedings of the 22nd Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Brazil, São Carlos 7 - 9 November 2018, pp. 115-122
summary	This work exposes the possible composition of a system composed of "crowd-working" of static, inert, flexible architecture elements, similar or identical entities, the "tesserae" and the integration with the link generated with Artificial Intelligence artifacts, a complex adaptive system, as a first experimental step to developments of Nanomaterials and systems that respond to the construction of the projective thought of the architectural envelope. The research responds to a general strategy of theoretical revision, with inductive and mixed methods. The exploration work examines the relative space within the idea of reason and the social function of architecture.
keywords	Self-organized; Decentralized; Nanorrobotic; Parametrism; Architectural Envelope
series	SIGRADI
email
last changed	2021/03/28 19:58

_id	sigradi2018_1616
id	sigradi2018_1616
authors	Rodrigues Alves, Manoel; Martins Abdalla, Alvaro; Tapia, Carlos
year	2018
title	Exploring Urban Interventions through Computational tools: genetic algorithm and urban connection patterns
source	SIGraDi 2018 [Proceedings of the 22nd Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Brazil, São Carlos 7 - 9 November 2018, pp. 109-114
summary	This paper presents a particular approach to design processes in urban design, in a transdisciplinary environment. Exploring geotechnologies, information and communication technologies, artificial intelligence techniques and experimental softwares (fuzzy logic and generic algorithm), the workshop “Generation of Urban Connection Patterns”, developed by IAU-USP (Brazil) and ETSA-US (Spain), aimed: to investigate urban space connection patterns in areas of environmental and social vulnerability; to explore formal arrangements in urban design; to foster academic exchange and possibilities of collaborative workshops. The article also discusses the role of computational tools and the implementation of in-person and non-presential methods in the teaching/learning process.
keywords	Transdisciplinarity; Teaching and Learning; Genetic Algorithm; Urban Connection Patterns; Urban Design
series	SIGRADI
email
last changed	2021/03/28 19:59

_id	acadia18_146
id	acadia18_146
authors	Rossi, Gabriella; Nicholas, Paul
year	2018
title	Re/Learning the Wheel. Methods to Utilize Neural Networks as Design Tools for Doubly Curved Metal Surfaces
source	ACADIA // 2018: Recalibration. On imprecisionand infidelity. [Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-17729-7] Mexico City, Mexico 18-20 October, 2018, pp. 146-155
doi	https://doi.org/10.52842/conf.acadia.2018.146
summary	This paper introduces concepts and computational methodologies for utilizing neural networks as design tools for architecture and demonstrates their application in the making of doubly curved metal surfaces using a contemporary version of the English Wheel. The research adopts an interdisciplinary approach to develop a novel method to model complex geometric features using computational models that originate from the field of computer vision. The paper contextualizes the approach with respect to the current state of the art of the usage of artificial neural networks both in architecture and beyond. It illustrates the cyber physical system that is at the core of this research, with a focus on the employed neural network–based computational method. Finally, the paper discusses the repercussions of these design tools on the contemporary design paradigm.
keywords	full paper, ai & machine learning, digital craft, robotic production, computation
series	ACADIA
type	paper
email
last changed	2022/06/07 07:56

_id	acadia18_108
id	acadia18_108
authors	Sanchez, Jose
year	2018
title	Platforms for Architecture: Imperatives and Opportunities of Designing Online Networks for Design
source	ACADIA // 2018: Recalibration. On imprecisionand infidelity. [Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-17729-7] Mexico City, Mexico 18-20 October, 2018, pp. 108-117
doi	https://doi.org/10.52842/conf.acadia.2018.108
summary	The rise of platforms such as Facebook, YouTube, and Uber, initially celebrated as part of a disruptive new era of the internet, has slowly been reassessed as a problematic and unregulated form of twenty-first-century info-capitalism that contributes to inequality, mistrust, and user polarization. The internet has become a place for content creation, not only consumption, and the content freely created by the network of users has defined a self-organizing system of ad-hoc audiences following echo chambers organized through artificial intelligence, which amplifies previously identified trends. While a large portion of the content created by users seems to be aimed at personal forms of entertainment, a few remarkable projects, such as Wikipedia, have allowed hundreds of users to contribute to a collective goal. While we can observe that the platform model has appeared in diverse disciplines, allowing the creation of content from news articles to music, we have not seen the emergence of a robust design platform intended to proliferate and advance the discipline of architecture. This paper makes the case that video game technology and its audiences have reached a state of technical capability that could allow for architectural platforms to emerge, one in which players could learn, create, and share architectural designs. Such a platform comes with a series of ethical imperatives, questions of value proposition, and liabilities, as well as a high potential to communicate and proliferate architectural knowledge and know-how. Common’hood, currently under development, will be used as a case study to engage the development of an ethical architectural platform that develops a proposition towards authorship, ownership, and collective engagement.
keywords	full paper, platforms, capitalism, network, video game, combinatorics, information theory, entropy, co-ops, platform cooperativism, privacy, encryption
series	ACADIA
type	paper
email
last changed	2022/06/07 07:56

_id	ecaade2020_445
id	ecaade2020_445
authors	Spiegelhalter, Thomas, Andia, Alfredo, Levente, Juhasz and Namuduri, Srikanth
year	2020
title	Part 1: The Integrated Decision Support System - Generative and synthetic biological design imaginations for the Miami bay area
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 11-20
doi	https://doi.org/10.52842/conf.ecaade.2020.2.011
summary	In less than 150 years our carbon society transformed the planet. Today more than 50% of ecologies in the world are determined by unsustainable industrialization processes. The latest IPCC reports show that we are quickly arriving at points of no return in the warming of our planet. We cannot afford to continue in the same direction, we need a new imagination. As part of an E.U.-US funded $1.9 million research project we have been working on multiple projects for the future of the Miami islands since 2018:1. We developed a generative GIS-BIM based Python API for mapping and optimization of carbon-neutral design workflows. It includes genetic design combinatorics with intuitive graphical Dynamo-Python-Grasshopper programming with experimental design results. 2. We worked on a series of design research for the Miami Bay that envisions islands, living shorelines, programmable soils, and infrastructures that grow by themselves using synthetic biology.
keywords	Automated Workflows, Synthetic Biology, Artificial Intelligence, Architecture, Sea-level Rise
series	eCAADe
email
last changed	2022/06/07 07:56

_id	acadia18_216
id	acadia18_216
authors	Ahrens, Chandler; Chamberlain, Roger; Mitchell, Scott; Barnstorff, Adam
year	2018
title	Catoptric Surface
source	ACADIA // 2018: Recalibration. On imprecisionand infidelity. [Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-17729-7] Mexico City, Mexico 18-20 October, 2018, pp. 216-225
doi	https://doi.org/10.52842/conf.acadia.2018.216
summary	The Catoptric Surface research project explores methods of reflecting daylight through a building envelope to form an image-based pattern of light on the interior environment. This research investigates the generation of atmospheric effects from daylighting projected onto architectural surfaces within a built environment in an attempt to amplify or reduce spatial perception. The mapping of variable organizations of light onto existing or new surfaces creates a condition where the perception of space does not rely on form alone. This condition creates a visual effect of a formless atmosphere and affects the way people use the space. Often the desired quantity and quality of daylight varies due to factors such as physiological differences due to age or the types of tasks people perform (Lechner 2009). Yet the dominant mode of thought toward the use of daylighting tends to promote a homogeneous environment, in that the resulting lighting level is the same throughout a space. This research project questions the desire for uniform lighting levels in favor of variegated and heterogeneous conditions. The main objective of this research is the production of a unique facade system that is capable of dynamically redirecting daylight to key locations deep within a building. Mirrors in a vertical array are individually adjusted via stepper motors in order to reflect more or less intense daylight into the interior space according to sun position and an image-based map. The image-based approach provides a way to specifically target lighting conditions, atmospheric effects, and the perception of space.
keywords	full paper, non-production robotics, representation + perception, performance + simulation, building technologies
series	ACADIA
type	paper
email
last changed	2022/06/07 07:54

_id	ecaade2018_297
id	ecaade2018_297
authors	Elesawy, Amr, Caranovic, Stefan, Zarb, Justin, Jayathissa, Prageeth and Schlueter, Arno
year	2018
title	HIVE Parametric Tool - A simplified energy simulation tool for educating architecture students
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 657-666
doi	https://doi.org/10.52842/conf.ecaade.2018.1.657
summary	This paper presents HIVE, a new open source design toolbox, which focuses on teaching concepts of Energy and Climate Systems integration in buildings. .The aim is to empower architecture students to integrate aspects of energy efficiency during the architectural design process. The tool employs a simplified input format designed for ease of use and provides almost instantaneous, direct feedback to support students of all experience levels in the early, conceptual building design stages, where numerous iterations need to be conducted efficiently within a short period of time.The project aims to create a robust toolbox that will become an innovative reference in architecture and engineering - lectures, design studios, and project-based learning - through its capacity to quickly, and effectively, translate building energy systems concepts into graphic formats central to building design teaching and practice. The fast feedback that the users receive to their design parameters changes will enable an effective and quick build-up of tacit knowledge about building energy systems, complementary to the explicit, theoretical knowledge that is usually taught in courses, thus creating a more complete learning experience.
keywords	Building Simulation; Low-energy architecture; Integrated curriculum; PV Assessment; Simplified GUI; Architecture Education
series	eCAADe
email
last changed	2022/06/07 07:55

_id	caadria2018_301
id	caadria2018_301
authors	Fereos, Pavlos, Tsiliakos, Marios and Jaschke, Clara
year	2018
title	Spaceship Architecture - A Sci-Fi Pedagogical Approach to Design Computation
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 1, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 81-90
doi	https://doi.org/10.52842/conf.caadria.2018.1.081
summary	The analysis of make-belief drawings and models of Sci-Fi spaceships and architecture, leaves architects usually in absence of interior, material or program information. The spatial depth of sci-fi digital or physical models is virtually non-existent and unresolved. This discrepancy within sci-fi scenarios inspired the development of an integrated teaching methodology within design studios, with the academic objective to utilize computational methods for analysis, reproduction and eventually composition, while assessing its capacity to achieve a successful assimilation of design computation in the curriculum. The Spaceship Architecture Design Studio at University of Innsbruck's Institute for Experimental Architecture.hochbau follows a procedural approach in which the design objective is not predefined. Yet, it aims to be 'outside of this world' as a sci-fi architectural quality-enriched result of our reality, via a design oriented course with immersive computational strategies.
keywords	pedagogy; computation; sci-fi; academia; teaching
series	CAADRIA
email
last changed	2022/06/07 07:50

_id	caadria2018_052
id	caadria2018_052
authors	Fung, Enrica and Crolla, Kristof
year	2018
title	Choreographed Architecture - Body-Spatial Exploration
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 1, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 101-110
doi	https://doi.org/10.52842/conf.caadria.2018.1.101
summary	This paper presents a design-methodological case study that looks into the practical expansion of conventional conceptual architectural design media by incorporating contemporary technology of motion capture. It discusses challenges of integrating dance movement as a real-time input parameter for architectural design that aims at translating body motion into space. The paper consists of four parts, beginning with a historic background overview of scientists, physiologists, artists, choreographers, and architects who have attempted capturing body motion and turning the motion into space. The second part of the paper discusses the iterative development of the 'Dance Machine' as a methodological tool for the integration of motion capture into conceptual architectural design. Thirdly, the paper discusses tested design applications of the 'Dance Machine' by looking at two sited applications. Finally, the overall methodology is critically assessed and discussed in the light of continuous development of creative applications of motion capturing technology. The paper concludes by highlighting the architectural potential found in specific qualities of dance and by advocating for a broader palette of tools, techniques, and input methods for the conceptual design of architecture.
keywords	Choreographed architecture; Motion capture; Conceptual design media; Space design; Human body
series	CAADRIA
email
last changed	2022/06/07 07:50

_id	ijac201816204
id	ijac201816204
authors	Gengnagel, Christoph; Riccardo La Magna, Mette Ramsgaard Thomsen and Martin Tamke
year	2018
title	Shaping hybrids – Form finding of new material systems
source	International Journal of Architectural Computing vol. 16 - no. 2, 91-103
summary	Form-finding processes are an integral part of structural design. Because of their limitations, the classic approaches to finding a form – such as hanging models and the soap-film analogy – play only a minor role. The various possibilities of digital experimentation in the context of structural optimisation create new options for the designer generating forms, while enabling control over a wide variety of parameters. A complete mapping of the mechanical properties of a structure in a continuum mechanics model is possible but so are simplified modelling strategies which take into account only the most important properties of the structure, such as iteratively approximating to a solution via representations of kinematic states. Form finding is thus an extremely complex process, determined both by the freely selected parameters and by design decisions.
keywords	Bending active, form finding, hybrid structures, simulation, textile architecture
series	journal
email
last changed	2019/08/07 14:03

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