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	acadia17_474
id	acadia17_474
authors	Peng, Wenzhe; Zhang, Fan; Nagakura, Takehiko
year	2017
title	Machines’ Perception of Space: Employing 3D Isovist Methods and a Convolutional Neural Network in Architectural Space Classification
doi	https://doi.org/10.52842/conf.acadia.2017.474
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 474- 481
summary	Simple and common architectural elements can be combined to create complex spaces. Different spatial compositions of elements define different spatial boundaries, and each produces a unique local spatial experience to observers inside the space. Therefore an architectural style brings about a distinct spatial experience. While multiple representation methods are practiced in the field of architecture, there lacks a compelling way to capture and identify spatial experiences. Describing an observer’s spatial experiences quantitatively and efficiently is a challenge. In this paper, we propose a method that employs 3D isovist methods and a convolutional neural network (CNN) to achieve recognition of local spatial compositions. The case studies conducted validate that this methodology works well in capturing and identifying local spatial conditions, illustrates the pattern and frequency of their appearance in designs, and indicates peculiar spatial experiences embedded in an architectural style. The case study used small designs by Mies van der Rohe and Aldo van Eyck. The contribution of this paper is threefold. First, it introduces a sampling method based on 3D Isovist that generates a 2D image that can be used to represent a 3D space from a specific observation point. Second, it employs a CNN model to extract features from the sampled images, then classifies their corresponding space. Third, it demonstrates a few case studies where this space classification method is applied to different architectural styles.
keywords	design methods; information processing; AI; machine learning; computer vision; representation
series	ACADIA
email
last changed	2022/06/07 08:00

_id	acadia17_482
id	acadia17_482
authors	Penman, Scott
year	2017
title	Toward Computational Play
doi	https://doi.org/10.52842/conf.acadia.2017.482
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 482- 491
summary	The day is not far off when autonomous, artificially intelligent agents will be employed in creative industries such as architecture and design. Artificial intelligence is rapidly becoming ubiquitous, and it has absorbed many capabilities once thought beyond its reach. As such, it is critical that we reflect on the relationship between AI and design. Design is often tasked with pushing the envelope in the quest for novel meaning and experience. Designers can’t always rely upon existing models to judge their work. Operating like this requires a curious and open mind, a willingness to eschew reward and occasionally break the rules, and a desire to explore for the sake of exploring. These behaviors fly in the face of traditional implementations of computation and raise difficult questions about the autonomy and subjectivity of artificially intelligent machines. This paper proposes computational play as a field of research that covers how and why designers roam as freely as they do, what the creative potential of such exploration might be, and how such techniques might responsibly be implemented in computational machines. The work argues that autotelism, defined as internal motivation, is an essential aspect of play and outlines how it can be incorporated in a computational framework. The work also demonstrates a proof-of-concept in the form of an autonomous drawing machine that is able to plot a drawing, view the drawing, and make decisions based on what it sees, bringing computational vision and computational drawing together into a cyclical process that permits the use of autotelic play behavior.
keywords	design methods; information processing; art and technology; computational / artistic cultures
series	ACADIA
email
last changed	2022/06/07 08:00

_id	acadia17_552
id	acadia17_552
authors	Sjoberg, Christian; Beorkrem, Christopher; Ellinger, Jefferson
year	2017
title	Emergent Syntax: Machine Learning for the Curation of Design Solution Space
doi	https://doi.org/10.52842/conf.acadia.2017.552
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 552- 561
summary	The expanding role of computational models in the process of design is producing exponential growth in parameter spaces. As designers, we must create and implement new methods for searching these parameter spaces, considering not only quantitative optimization metrics but also qualitative features. This paper proposes a methodology that leverages the pattern modeling properties of artificial neural networks to capture designers' inexplicit selection criteria and create user-selection-based fitness functions for a genetic solver. Through emulation of learned selection patterns, fitness functions based on trained networks provide a method for qualitative evaluation of designs in the context of a given population. The application of genetic solvers for the generation of new populations based on the trained network selections creates emergent high-density clusters in the parameter space, allowing for the identification of solutions that satisfy the designer’s inexplicit criteria. The results of an initial user study show that even with small numbers of training objects, a search tool with this configuration can begin to emulate the design criteria of the user who trained it.
keywords	design methods; information processing; AI; machine learning; generative system
series	ACADIA
email
last changed	2022/06/07 07:56

_id	ecaade2017_001
id	ecaade2017_001
authors	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.)
year	2017
title	ShoCK! – Sharing of Computable Knowledge!, Volume 2
doi	https://doi.org/10.52842/conf.ecaade.2017.2
source	ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 2, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, 760 p.
summary	Internet of Things, pervasive nets, Knowledge ‘on tap’, Big Data, Wearable devices and the ‘Third wave’ of AI are disruptive technologies that are upsetting our globalised world as far as it can be foreseen from now. So academicians, professionals, researchers, innovation factories... are warmly invited to further shake up and boost our innovative and beloved CAAD world with new ideas, paradigms and points of view. Will our fine buildings and design traditions survive? Or, will they ‘simply’ be hybridized and enhanced by methods, techniques and CAAD tools? Obviously computation is needed to match the evergrowing performance requirements, but this is not enough to answer all these questions we have to deal with the essence of problems: improve design solutions for a better life. As life is not a matter of single individuals, we need to increase collaboration and to improve knowledge sharing. This means taking care of human beings, and involves a humanistic approach, and the long history of humankind ... from humans to thinking to technology ... and vice versa. A circle of human beings as eternal as our city.
series	eCAADe
last changed	2022/06/07 07:49

_id	ecaade2017_000
id	ecaade2017_000
authors	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.)
year	2017
title	ShoCK! – Sharing of Computable Knowledge!, Volume 1
doi	https://doi.org/10.52842/conf.ecaade.2017.1
source	ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 1, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, 770 p.
summary	Internet of Things, pervasive nets, Knowledge ‘on tap’, Big Data, Wearable devices and the ‘Third wave’ of AI are disruptive technologies that are upsetting our globalised world as far as it can be foreseen from now. So academicians, professionals, researchers, innovation factories... are warmly invited to further shake up and boost our innovative and beloved CAAD world with new ideas, paradigms and points of view. Will our fine buildings and design traditions survive? Or, will they ‘simply’ be hybridized and enhanced by methods, techniques and CAAD tools? Obviously computation is needed to match the evergrowing performance requirements, but this is not enough to answer all these questions we have to deal with the essence of problems: improve design solutions for a better life. As life is not a matter of single individuals, we need to increase collaboration and to improve knowledge sharing. This means taking care of human beings, and involves a humanistic approach, and the long history of humankind ... from humans to thinking to technology ... and vice versa. A circle of human beings as eternal as our city.
series	eCAADe
last changed	2022/06/07 07:49

_id	acadia17_284
id	acadia17_284
authors	Hu, Zhengrong; Park, Ju Hong
year	2017
title	HalO [Indoor Positioning Mobile Platform]: A Data-Driven, Indoor-Positioning System With Bluetooth Low Energy Technology To Datafy Indoor Circulation And Classify Social Gathering Patterns For Assisting Post Occupancy Evaluation
doi	https://doi.org/10.52842/conf.acadia.2017.284
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 284-291
summary	Post-Occupancy Evaluation (POE) as an integrated field between architecture and sociology has created practical guidelines for evaluating indoor human behavior within a built environment. This research builds on recent attempts to integrate datafication and machine learning into POE practices that may one day assist Building Information Modeling (BIM) and multi-agent modeling. This research is based on two premises: 1) that the proliferation of Bluetooth Low Energy (BLE) technology allows us to collect a building user’s data cost-effectively and 2) that the growing application of machine learning algorithms allows us to process, analyze and synthesize data efficiently. This study illustrates that the mobile platform HalO can serve as a generic tool for datafication and automation of data analysis of the movement of a building user. In this research, the iOS mobile application HalO, combined with BLE beacons enable building providers (architects, developers, engineers and facility managers etc.) to collect the user’s indoor location data. Triangulation was used to pinpoint the user’s indoor positions, and k-means clustering was applied to classify users into different gathering groups. Through four research procedures—Design Intention Analysis, Data Collection, Data Storage and Data Analysis—the visualized and classified data helps building providers to better evaluate building performance, optimize building operations and improve the accuracy of simulations.
keywords	design methods; information processing; data mining; IoT; AI; machine learning
series	ACADIA
email
last changed	2022/06/07 07:49

_id	acadia23_v1_242
id	acadia23_v1_242
authors	Noel, Vernelle A.
year	2023
title	Carnival + AI: Heritage, Immersive virtual spaces, and Machine Learning
source	ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 1: Projects Catalog of the 43rd Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9860805-8-1]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 242-245.
summary	Built on a Situated Computations framework, this project explores preservation, reconfiguration, and presentation of heritage through immersive virtual experiences, and machine learning for new understandings and possibilities (Noel 2020; 2017; Leach and Campo 2022; Leach 2021). Using the Trinidad and Tobago Carnival - hereinafter referred to as Carnival - as a case study, Carnival + AI is a series of immersive experiences in design, culture, and artificial intelligence (AI). These virtual spaces create new digital modes of engaging with cultural heritage and reimagined designs of traditional sculptures in the Carnival (Noel 2021). The project includes three virtual events that draw on real events in the Carnival: (1) the Virtual Gallery, which builds on dancing sculptures in the Carnival and showcases AI-generated designs; (2) Virtual J’ouvert built on J’ouvert in Carnival with AI-generated J’ouvert characters specific; and (3) Virtual Mas which builds on the masquerade.
series	ACADIA
type	project
email
last changed	2024/04/17 13:58

_id	caadria2017_163
id	caadria2017_163
authors	Kalantari, Saleh and Saleh Tabari, Mohammad Hassan
year	2017
title	GrowMorph: Bacteria Growth Algorithm and Design
doi	https://doi.org/10.52842/conf.caadria.2017.479
source	P. Janssen, P. Loh, A. Raonic, M. A. Schnabel (eds.), Protocols, Flows, and Glitches - Proceedings of the 22nd CAADRIA Conference, Xi'an Jiaotong-Liverpool University, Suzhou, China, 5-8 April 2017, pp. 479-487
summary	GrowMorph is an ongoing research project that addresses the logic of bacterial cellular growth and its potential uses in architecture and design. While natural forms have always been an inspiration for human creativity, contemporary technology and scientific knowledge can allow us to advance the principle of biomimesis in striking new directions. By examining various patterns of bacterial growth, including their parametric logic, their use of responsive membranes and scaffolding structures, and their environmental fitness, this research creates new algorithmic design and construction models that can be applied through digital fabrication. Based on data from confocal microscopy, simulations were created using programming language Processing to model the environmental responses and morphology of the bacteria's growth. To demonstrate the utility of the results, the simulations created in this research were used to design an organically shaped pavilion and to suggest a new digital knitting process for material construction. The results from the study can inspire designers to make use of bacterial growth logic in their work, and provide them with practical tools for this purpose. Potential applications include novel designs for responsive surfaces, new fabrication processes, and unique spatial structures in future architectural work.
keywords	Synthetic Biology; Architecture; Bio-fabrication; Bio-constructs; Design Computation
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	acadia17_92
id	acadia17_92
authors	Anzalone, Phillip; Bayard, Stephanie; Steenblik, Ralph S.
year	2017
title	Rapidly Deployed and Assembled Tensegrity System: An Augmented Design Approach
doi	https://doi.org/10.52842/conf.acadia.2017.092
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 92-101
summary	The Rapidly Deployable and Assembled Tensegrity (RDAT) project enables the efficient automated design and deployment of differential-geometry tensegrity structures through computation-driven design-to-installation workflow. RDAT employs the integration of parametric and solid-modeling methods with production by streamlining computer numerically controlled manufacturing through novel detailing and production techniques to develop an efficient manufacturing and assembly system. The RDAT project emerges from the Authors' research in academia and professional practice focusing on computationally produced full-scale performative building systems and their innovative uses in the building and construction industry.
keywords	design methods; information processing; AI; machine learning; form finding; VR; AR; mixed reality
series	ACADIA
email
last changed	2022/06/07 07:54

_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	acadia17_164
id	acadia17_164
authors	Brugnaro, Giulio; Hanna, Sean
year	2017
title	Adaptive Robotic Training Methods for Subtractive Manufacturing
doi	https://doi.org/10.52842/conf.acadia.2017.164
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 164-169
summary	This paper presents the initial developments of a method to train an adaptive robotic system for subtractive manufacturing with timber, based on sensor feedback, machine-learning procedures and material explorations. The methods were evaluated in a series of tests where the trained networks were successfully used to predict fabrication parameters for simple cutting operations with chisels and gouges. The results suggest potential benefits for non-standard fabrication methods and a more effective use of material affordances.
keywords	design methods; information processing; construction; robotics; ai & machine learning; digital craft; manual craft
series	ACADIA
email
last changed	2022/06/07 07:52

_id	acadia17_426
id	acadia17_426
authors	Moorman, Andrew
year	2017
title	Pattern Making and Learning: Non-Routine Practices in Generative Design
doi	https://doi.org/10.52842/conf.acadia.2017.426
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 426- 435
summary	We now witness an upsurge in mainstream generative design tools fortified by simulation that speed up the concealed linear synthesis of optimized design alternatives. In pursuit of optimality, these tools saturate local machines or cloud servers with analysis and design iteration data, only to discard it once the procedure has concluded. Largely absent, however, are tools for an active, adaptive relationship with design exploration and the reuse of corresponding design data and metadata. In Pattern Making and Pattern Learning, we propose that these characteristics are mutually beneficial. This paper presents a series of revisions to the optimization framework for routine design synthesis that examine a potential symbiosis between the production of large datasets (big data) and non-routine practices of making in design. Our engagement with iterative design exercises is twofold: as a supply of computer-generated design information to foster user intuition and explore the design space on non-objective terms, and as a supply of human-generated design information to learn artifacts of user preference in the interest of design software personalization. These concepts are applied to the generation of functionally graded patterning in chair design, combining methods of physical production with programmable sheet material behavior through a custom interactive synthesis framework.
keywords	design methods; information processing; ai & machine learning; simulation & optimization; generative system
series	ACADIA
email
last changed	2022/06/07 07:58

_id	ecaade2017_021
id	ecaade2017_021
authors	Agirbas, Asli
year	2017
title	The Use of Simulation for Creating Folding Structures - A Teaching Model
doi	https://doi.org/10.52842/conf.ecaade.2017.1.325
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 1, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 325-332
summary	In architectural education, the demand for creating forms with a non-Euclidean geometry, which can only be achieved by using the computer-aided design tools, is increasing. The teaching of this subject is a great challenge for both students and instructors, because of the intensive nature of architecture undergraduate programs. Therefore, for the creation of those forms with a non-Euclidean geometry, experimental work was carried out in an elective course based on the learning visual programming language. The creation of folding structures with form-finding by simulation was chosen as the subject of the design production which would be done as part of the content of the course. In this particular course, it was intended that all stages should be experienced, from the modeling in the virtual environment to the digital fabrication. Hence, in their early years of architectural education, the students were able to learn versatile thinking by experiencing, simultaneously, the use of simulation in the environment of visual programming language, the forming space by using folding structures, the material-based thinking and the creation of their designs suitable to the digital fabrication.
keywords	Folding Structures; CAAD; Simulation; Form-finding; Architectural Education
series	eCAADe
email
last changed	2022/06/07 07:54

_id	acadia17_28
id	acadia17_28
authors	Aguiar, Rita; Cardoso, Carmo; Leit?o,António
year	2017
title	Algorithmic Design and Analysis Fusing Disciplines
doi	https://doi.org/10.52842/conf.acadia.2017.028
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 28-37
summary	In the past, there has been a rapid evolution in computational tools to represent and analyze architectural designs. Analysis tools can be used in all stages of the design process, but they are often only used in the final stages, where it might be too late to impact the design. This is due to the considerable time and effort typically needed to produce the analytical models required by the analysis tools. A possible solution would be to convert the digital architectural models into analytical ones, but unfortunately, this often results in errors and frequently the analytical models need to be built almost from scratch. These issues discourage architects from doing a performance-oriented exploration of their designs in the early stages of a project. To overcome these issues, we propose Algorithmic Design and Analysis, a method for analysis that is based on adapting and extending an algorithmic-based design representation so that the modeling operations can generate the elements of the analytical model containing solely the information required by the analysis tool. Using this method, the same algorithm that produces the digital architectural model can also automatically generate analytical models for different types of analysis. Using the proposed method, there is no information loss and architects do not need additional work to perform the analysis. This encourages architects to explore several design alternatives while taking into account the design’s performance. Moreover, when architects know the set of design variations they wish to analyze beforehand, they can easily automate the analysis process.
keywords	design methods; information processing; simulation & optimization; BIM; generative system
series	ACADIA
email
last changed	2022/06/07 07:54

_id	acadia17_52
id	acadia17_52
authors	Ajlouni, Rima
year	2017
title	Simulation of Sound Diffusion Patterns of Fractal-Based Surface Profiles
doi	https://doi.org/10.52842/conf.acadia.2017.052
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 52-61
summary	Acoustical design is one of the most challenging aspects of architecture. A complex system of competing influences (e.g., space geometry, size, proportion, material properties, surface detail, etc.) contribute to shaping the quality of the auditory experience. In particular, architectural surfaces affect the way that sound reflections propagate through space. By diffusing the reflected sound energy, surface designs can promote a more homogeneous auditory atmosphere by mitigating sharp and focused reflections. One of the challenges with designing an effective diffuser is the need to respond to a wide band of sound wavelengths, which requires the surface profile to precisely encode a range of detail sizes, depths and angles. Most of the available sound diffusers are designed to respond to a narrow band of frequencies. In this context, fractal-based surface designs can provide a unique opportunity for mitigating such limitations. A key principle of fractal geometry is its multilevel hierarchical order, which enables the same pattern to occur at different scales. This characteristic makes it a potential candidate for diffusing a wider band of sound wavelengths. However, predicting the reflection patterns of complicated fractal-based surface designs can be challenging using available acoustical software. These tools are often costly, complicated and are not designed for predicting early sound propagation paths. This research argues that writing customized algorithms provides a valuable, free and efficient alternative for addressing targeted acoustical design problems. The paper presents a methodology for designing and testing a customized algorithm for predicting sound diffusion patterns of fractal-based surfaces. Both quantitative and qualitative approaches were used to develop the code and evaluate the results.
keywords	design methods; information processing; simulation & optimization; data visualization
series	ACADIA
email
last changed	2022/06/07 07:54

_id	acadia17_62
id	acadia17_62
authors	Al-Assaf, Nancy S.; Clayton, Mark J.
year	2017
title	Representing the Aesthetics of Richard Meier’s Houses Using Building Information Modeling
doi	https://doi.org/10.52842/conf.acadia.2017.062
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 62-71
summary	Beyond its widespread use for representing technical aspects and matters of building and construction science, Building information modeling (BIM) can be used to represent architectural relationships and rules drawn from aesthetic theory. This research suggests that BIM provides not only vocabulary but also syntactical tools that can be used to capture an architectural language. In a case study using Richard Meier’s language for single-family detached houses, a BIM template has been devised to represent the aesthetic concepts and relations therein. The template employs parameterized conceptual mass objects, syntactical rules, and a library of architectonic elements, such as walls, roofs, columns, windows, doors, and railings. It constrains any design produced using the template to a grammatically consistent expression or style. The template has been used as the starting point for modeling the Smith House, the Douglas House, and others created by the authors, demonstrating that the aesthetic template is general to many variations. Designing with the template to produce a unique but conforming design further illustrates the generality and expressiveness of the language. Having made the formal language explicit, in terms of syntactical rules and vocabulary, it becomes easier to vary the formal grammar and concrete vocabulary to produce variant languages and styles. Accordingly, this approach is not limited to a specific style, such as Richard Meier's. Future research can be conducted to demonstrate how designing with BIM can support stylistic change. Adoption of this approach in practice could improve the consistency of architectural designs and their coherence to defined styles, potentially increasing the general level of aesthetic expression in our built environment.
keywords	design methods; information processing; BIM; education
series	ACADIA
email
last changed	2022/06/07 07:54

_id	ecaade2017_133
id	ecaade2017_133
authors	Ashrafi, Negar and Duarte, José Pinto
year	2017
title	A shape-grammar for double skin facades - A basis for generating context sensitive facades solution
doi	https://doi.org/10.52842/conf.ecaade.2017.2.471
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 2, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 471-476
summary	Double skin façade (DSF) is considered one of the best envelope systems in terms of energy efficiency. However, designing an energy efficient DSF system depends on different factors, such as climate, DSF shape and how the air flows in that system. This study presents a methodology to assist design decisions regarding the DSFs shapes. For this purpose, shape grammars was used as a generative design system to generate alternative DSF shape designs. Results of this study can be integrated with an energy simulation tools to calculate the energy demand of each design and consequently design the most efficient DSF system for each context.
keywords	building envelope design; double skin façade; generative design system; shape grammars
series	eCAADe
email
last changed	2022/06/07 07:54

_id	acadia17_128
id	acadia17_128
authors	Bacharidou, Maroula
year	2017
title	Touch, See, Make: Employing Active Touch in Computational Making
doi	https://doi.org/10.52842/conf.acadia.2017.128
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 128-137
summary	In architectural education and practice, we don’t come in physical contact with what we make until the later stages of the design process. This vision-oriented approach to design is something deeply rooted in architectural practice: from Alberti’s window to the screens of our computers, design has traditionally been more of a visual and less of a hands-on process. The vision of the presented study is that if we want to understand the way we make in order to improve tools for computational design and making, we need to understand how our ability to make things is enhanced by both our visual and tactile mechanisms. Bringing the notion of active touch from psychology into the design studio, I design and execute a series of experiments investigating how seeing, touching, or seeing and touching exhibit different sensory competencies, and how these competencies are expressed through the process of making. The subjects of the experiment are asked to tactilely, visually, or tactilely and visually observe a three-dimensional object, create descriptions of its composition, and to remake it based on their experience of it using plastic materials. After the execution of the experiment, I analyze twenty-one reproductions of the original object; I point to ways in which touch can detect scale and proportions more accurately than vision, while vision can detect spatial components more efficiently than touch; I then propose ways in which this series of experiments can lead to the creation of new design and making tools.
keywords	education society & culture; computational / artistic culture;s hybrid practices; digital craft; manual craft
series	ACADIA
email
last changed	2022/06/07 07:54

_id	ecaade2017_280
id	ecaade2017_280
authors	Baldissara, Matteo, Perna, Valerio, Saggio, Antonino and Stancato, Gabriele
year	2017
title	Plug-In Design - Reactivating the Cities with responsive Micro-Architectures. The Reciprocal Experience
doi	https://doi.org/10.52842/conf.ecaade.2017.2.571
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 2, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 571-580
summary	Every city has under utilized spaces that create a series of serious negative effects. Waiting for major interventions, those spaces can be reactivated and revitalized with soft temporary projects: micro interventions that light up the attention, give new meaning and add a new reading to abandoned spaces. We can call this kind of operations "plug-in design", inheriting the term from computer architecture: interventions which aim to involve the citizens and activate the environment, engage multiple catalyst processes and civil actions. Plug-in design interventions are by all meanings experimental, they seek for interaction with the users, locally and globally. Information Technology - with its parametric and site-specific capabilities and interactive features - can be instrumental to create such designs and generate a new consciousness of the existing environment. With this paper we will illustrate how two low-budget interventions have re-activated a forgotten public space. Parametric design with a specific script allowing site-specific design, materials and structure optimization and a series of interactive features, will be presented through Reciprocal 1.0 and Reciprocal 2.0 projects which have been built in 2016 in Italy by the nITro group.
keywords	reciprocal frame; parametric design; responsive technology; plug-in design; interactivity; re-activate
series	eCAADe
email
last changed	2022/06/07 07:54

_id	acadia17_138
id	acadia17_138
authors	Berry, Jaclyn; Park, Kat
year	2017
title	A Passive System for Quantifying Indoor Space Utilization
doi	https://doi.org/10.52842/conf.acadia.2017.138
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 138-145
summary	This paper presents the development of a prototype for a new sensing device for anonymously evaluating space utilization, which includes usage factors such as occupancy levels, congregation and circulation patterns. This work builds on existing methods and technology for measuring building performance, human comfort and occupant experience in post-occupancy evaluations as well as pre-design strategic planning. The ability to collect data related to utilization and occupant experience has increased significantly due to the greater accessibility of sensor systems in recent years. As a result, designers are exploring new methods to empirically verify spatial properties that have traditionally been considered more qualitative in nature. With this premise, this study challenges current strategies that rely heavily on manual data collection and survey reports. The proposed sensing device is designed to supplement the traditional manual method with a new layer of automated, unbiased data that is capable of capturing environmental and social qualities of a given space. In a controlled experiment, the authors found that the data collected from the sensing device can be extrapolated to show how layout, spatial interventions or other design factors affect circulation, congregation, productivity, and occupancy in an office setting. In the future, this sensing device could provide designers with real-time feedback about how their designs influence occupants’ experiences, and thus allow the designers to base what are currently intuition-based decisions on reliable data and evidence.
keywords	design methods; information processing; smart buildings; IoT
series	ACADIA
email
last changed	2022/06/07 07:52

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