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	sigradi2021_12
id	sigradi2021_12
authors	Guillen Salas, Juan Carlos, Furtado Silva, Neander and Miranda Esper Kallas, Luana
year	2021
title	BIO-FADEN 2.0 Pavilion: Experimental Study of Algorithmic-Generative Design and Digital Fabrication with 3D Printing of a Bionic Pavilion Prototype in the Midwest Region of Brazil
source	Gomez, P and Braida, F (eds.), Designing Possibilities - Proceedings of the XXV International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2021), Online, 8 - 12 November 2021, pp. 1211–1222
summary	This research has as main objective to determine the possibilities and limitations of digital design and digital fabrication by 3D printing of a prototype of bionic pavilion with non-Euclidean geometric shapes in reduced size inspired by fruits present in the MidWest Region of Brazil. The work was structured in 3 stages: Rationale, Materials and Logistic, and Experimentation. The Rationale consisted of a literature review on the concepts of: bionics, generative-algorithmic design, digital fabrication, 3D printing and prototyping. The Materials and Logistics stage consisted of the presentation and classification into categories of materials and the logistics that were usedTthe experiment consisted of 4 phases: Graphic code and 3D digital modeling of the bionic pavilion; operationalization of digital fabrication; selection of 3D printing digital fabrication technology and; digital fabrication by 3D printing. The main result of the research is that digital technologies - rhinoceros 5.0 software, grasshopper software - allow to design a prototype of a pavilion of complex shape or of small size inspired by natural structures.
keywords	Biônica, Desenho Generativo, Impressao 3D, Fabricaçao Digital, Envoltória Arquitetônica
series	SIGraDi
email
last changed	2022/05/23 12:11

_id	ecaade2021_009
id	ecaade2021_009
authors	Majzoub, Omar and Haeusler, M. Hank
year	2021
title	Investigating Computational Methods and Strategies to Reduce Construction and Demolition Waste in Preliminary Design
doi	https://doi.org/10.52842/conf.ecaade.2021.1.325
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. 325-334
summary	The waste produced in construction and demolition presents social, economic, and environmental challenges on a global scale. Research suggests that effective decision-making mechanisms are needed during preliminary design stages to minimise the production of waste. In early research, we presented a beta version of a waste reduction tool which is now in need of a User Experience (UX) and Interaction Experience (IX) strategy to meet our research aims of (a) supporting architects in making informed decisions and (b) offer general as well a specific design optimisation to reduce waste. Thus in our research, we arrived at a point that required an investigation into computational methods and strategies to meet these aims. While optimisation and decision-making in architecture are often achieved through generative design strategies, we aim to investigate and discuss alternatives. Thus we propose the hypothesis of employing augmented intelligence. The paper presents work in augmented intelligence undertaken outside the architecture discipline and presents our literature review with a discussion and conclusion.
keywords	Waste reduction; computational methods and strategies; sustainable development goals; augmented intelligence; position paper
series	eCAADe
email
last changed	2022/06/07 07:59

_id	ascaad2021_132
id	ascaad2021_132
authors	Mansour, Hussein; Sherif Sheta, Medhat Samra
year	2021
title	Towards New Design Patterns for Museum Exhibition Halls using Integrated Algorithmic Generative Techniques
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. 686-698
summary	This paper aims to define the concepts, methods and techniques needed to establish a multifaceted, yet comprehensive description of complex problems facing conventional architectural design, and how to decode the problems knots through integration between techniques and technologies in generative algorithmic and its impact of the quality of design solution. To attain these aims, the study explores the ability of integrated algorithmic techniques in developing dealing with complicated problems in the design of museums exhibition halls. It discusses, analyzes, and evaluates several conventional architectural design methods and reviews the challenges that limit their ability to produce creative solutions. This will help close the gap between the design quality and duration of design process; conforming that engineering programs help designers, not marginalize them. And hence developing architectural considerations in the design process to parametric paradigms that are suitable for scientific curriculum. So, the research problem is how such methodology can implement the integration between generative design techniques.
series	ASCAAD
email
last changed	2021/08/09 13:13

_id	caadria2021_053
id	caadria2021_053
authors	Rhee, Jinmo and Veloso, Pedro
year	2021
title	Generative Design of Urban Fabrics Using Deep Learning
doi	https://doi.org/10.52842/conf.caadria.2021.1.031
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. 31-40
summary	This paper describes the Urban Structure Synthesizer (USS), a research prototype based on deep learning that generates diagrams of morphologically consistent urban fabrics from context-rich urban datasets. This work is part of a larger research on computational analysis of the relationship between urban context and morphology. USS relies on a data collection method that extracts GIS data and converts it to diagrams with context information (Rhee et al., 2019). The resulting dataset with context-rich diagrams is used to train a Wasserstein GAN (WGAN) model, which learns how to synthesize novel urban fabric diagrams with the morphological and contextual qualities present in the dataset. The model is also trained with a random vector in the input, which is later used to enable parametric control and variation for the urban fabric diagram. Finally, the resulting diagrams are translated to 3D geometric entities using computer vision techniques and geometric modeling. The diagrams generated by USS suggest that a learning-based method can be an alternative to methods that rely on experts to build rule sets or parametric models to grasp the morphological qualities of the urban fabric.
keywords	Deep Learning; Urban Fabric; Generative Design; Artificial Intelligence; Urban Morphology
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	ijac202119302
id	ijac202119302
authors	BuHamdan, Samer; Alwisy, Aladdin; Bouferguene, Ahmed
year	2021
title	Generative systems in the architecture, engineering and construction industry: A systematic review and analysis
source	International Journal of Architectural Computing 2021, Vol. 19 - no. 3, 226–249
summary	Researchers have been extensively exploring the employment of generative systems to support design practices in the architecture, engineering and construction industry since the 1970s. More than half a century passed since the first architecture, engineering and construction industry’s generative systems were developed; researchers have achieved remarkable leaps backed by advances in computing power and algorithms’ capacity. In this article, we present a systematic analysis of the literature published between 2009 and 2019 on the utilization of generative systems in the design practices of the architecture, engineering and construction industry. The present research studies present trends, collaborations and applications of generative systems in the architecture, engineering and construction industry in order to identify existing shortcomings and potential advancements that balance the need for theory development and practical application. It provides insightful observations that are translated into meaningful recommendations for future research necessary to progress the incorporation of generative systems into the design practices of the architecture, engineering and construction industry.
keywords	Generative systems, architecture, engineering and construction industry, performative design, generative design, systematic literature review, future directions
series	journal
email
last changed	2024/04/17 14:29

_id	ascaad2021_069
id	ascaad2021_069
authors	Cheddadi, Aqil; Kensuke Hotta, Yasushi Ikeda
year	2021
title	Exploring the Self-Organizing Structure of the Moroccan Medina: A Simulation Model for Generating Urban Form
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. 672-685
summary	This research explores the use of generative design and computational simulations in the exploration of urban compositions based on traditional urban forms from North Africa. Upon the examination of these urban settlements, we discuss the relationship between traditional urban form and generative urbanism theory. We investigate several factors that allow these self-generated urban tissues to be highly adaptive to social, spatial, and environmental change. Following this, we formulate guidelines to reinterpret some of the characteristics of these urban forms. Built on these features, the simulation seeks to explore the generation of abstract urban forms and their optimization. In this regard, this experiment utilizes 3D and parametric design tools (Rhinoceros 3D and Grasshopper) to define a generative urban simulation and optimization model. It explores the use of algorithmic design methodology in the definition and optimization of the generated urban form. For this purpose, grid-based operations with base modules are used in conjunction with introverted urban blocks. We employ evolutionary algorithms and Pareto front methodology to visualize and rank a multitude of optimized results that are evaluated using three different and conflicting design objectives: sun exposure, physical accessibility, and urban density. The results are ranked and analyzed by comparing the outcomes of these different objective functions. The result of this study shows that it is possible to allow a degree of diversification of a myriad of urban configurations with a generative form-finding algorithm while still maintaining a rather commendable adaptability to various design constraints in the case of high-density settings. In this research, it is anticipated that an algorithmic design model is a fitting contemporary solution that can simulate the philosophy of a design made without a designer and offer a wide range of objective-based spatial solutions. It sets the stage for a discussion about the relevance of reinterpreting traditional urban forms from north Africa by designing a generative model that allows for self-organization.
series	ASCAAD
email
last changed	2021/08/09 13:13

_id	sigradi2021_312
id	sigradi2021_312
authors	Dickinson, Susannah and Ida, Aletheia
year	2021
title	Dynamic Interscalar Methods for Adaptive Design Futures
source	Gomez, P and Braida, F (eds.), Designing Possibilities - Proceedings of the XXV International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2021), Online, 8 - 12 November 2021, pp. 41–53
summary	This paper addresses our current environmental and political climate directly, disseminating work from a research-based, upper-level architecture studio located at the border of Mexico and the United States. Dynamic digital tools and methods were developed to connect multiple scales of spatialized data. Additional field tools, including electromagnetic field (EMF) meters, environmental sensors, and micro-photography, enabled real-time dynamics to be combined with photogrammetry, satellite and GIS data. The selected outcomes utilize the methodological framework in different ways. Three presiding significant outcomes demonstrated from this work include: 1) micro-macro scale inquiry through spatio-temporal data collection and fieldwork; 2) parametric digital tools for emergent design optimization linking natural and artificial systems; and 3) human-machine-nature interactions for cultural awareness, participation, and activism. Collectively, these three functions of the methodology shift practice towards an alter-disciplinary logic to enable adaptive design outcomes that are responsive to a range of issues presented through site-specific climate change dynamics.
keywords	Parametric Generative Design, Sustainable Design, Simulation, Bio-Inspired Design, Digital Pedagogy
series	SIGraDi
email
last changed	2022/05/23 12:10

_id	ijac202119308
id	ijac202119308
authors	Dinçer, Sevde Gülizar; Yazar, Tugrul
year	2021
title	A comparative analysis of the digital re-constructions of muqarnas systems: The case study of Sultanhani muqarnas in Central Anatolia
source	International Journal of Architectural Computing 2021, Vol. 19 - no. 3, 360–385
summary	This paper presents a comparative case study on the digital modeling workflows of a particular muqarnas system. After the literature review and the definition of the context, several digital modeling workflows were described as element-based, tessellation-based and block-based workflows by using computer-aided design and parametric modeling software. As the case study of this research, these workflows were tested on a muqarnas design located at the Sultanhani Caravanserai in Central Anatolia. Then, workflows were compared according to three qualities: analytical, generative, and performative. The outcomes of element-based workflow has more analytical solutions for the study, where tessellation-based workflow has more generative potential and block-based workflow is more performative.
keywords	Anatolian Seljuk muqarnas, digital modeling, parametric modeling, architectural geometry, Sultanhani Caravanserai
series	journal
email
last changed	2024/04/17 14:29

_id	sigradi2021_381
id	sigradi2021_381
authors	El-Khouly, Tamer, Abdelmohsen, Sherif, Riad, Aya, Abdelkhalek, Joumana and Abdelgawad, Norhan
year	2021
title	Heritage-inspired Interactivity: Traditional Geometric Patterns as an Inspiration for Interactive Architectural Prototypes
source	Gomez, P and Braida, F (eds.), Designing Possibilities - Proceedings of the XXV International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2021), Online, 8 - 12 November 2021, pp. 617–628
summary	Coding and visual programming are becoming an important component of design education, with focus on algorithmic thinking, form finding, and generative design. Programming languages like Processing are increasingly explored within shape studies in architecture, thus opening unique possibilities for creative design exploration. Most pedagogical approaches that integrate coding in exploring heritage-inspired geometric patterns focus on shape grammars and rule-based design. This exploratory paper further examines the potential of traditional geometric patterns as inspiration sources for interactivity in architectural design. We discuss the process and outcomes of an undergraduate architectural computing course at the American University in Cairo, Egypt, where students implement visual programming using Processing to develop interactive architecture prototypes based on cultural heritage. Results demonstrated a variety of abstraction and translation strategies for both tangible and intangible heritage inspirations, and generation of emergent concepts for diverse architectural prototypes including urban grids, movable structures, and responsive façades.
keywords	Generative design, programming, pattern generation, heritage, interactivity
series	SIGraDi
email
last changed	2022/05/23 12:11

_id	caadria2021_391
id	caadria2021_391
authors	Elshani, Diellza, Koenig, Reinhard, Duering, Serjoscha, Schneider, Sven and Chronis, Angelos
year	2021
title	Measuring Sustainability and Urban Data Operationalization - An integrated computational framework to evaluate and interpret the performance of the urban form.
doi	https://doi.org/10.52842/conf.caadria.2021.2.407
source	A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 2, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 407-416
summary	With rapid urbanization, the necessity for sustainable development has skyrocketed, and sustainable urban development is a must. Recent advances in computing performance of urban layouts in real-time allow for new paradigms of performance-driven design. As beneficial as utilizing multiple layers of urban data may be, it can also create a challenge in interpreting and operationalizing data. This paper presents an integrated computational framework to measure sustainability, operationalize and interpret the urban forms performance data using generative design methods, novel performance simulations, and machine learning predictions. The performance data is clustered into three pillars of sustainability: social, environmental, and economical, and it is followed with the performance space exploration, which assists in extracting knowledge and actionable rules of thumb. A significant advantage of the framework is that it can be used as a discussion table in participatory planning processes since it could be easily adapted to interactive environments.
keywords	generative design; data interpretation ; urban sustainability; performance simulation; machine learning
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	cdrf2021_13
id	cdrf2021_13
authors	Hao Wen, Pengcheng Gu, Yuchao Zhang, Shuai Zou, and Patrik Schumacher
year	2021
title	A Generative Approach to Social Ecologies in Project [Symbios]City
doi	https://doi.org/https://doi.org/10.1007/978-981-16-5983-6_2
source	Proceedings of the 2021 DigitalFUTURES The 3rd International Conference on Computational Design and Robotic Fabrication (CDRF 2021)
summary	The following paper talks about the studio project [Symbios]City, which is developed as a design research project in 2020–2021 Schumacher’ studio on social ecology of the graduate program in Architectural Association’s design research lab. The project aims to create an assemblage of social ecologies through a rich but cohesive multi-authored urban district. The primary ambition is to generate an urban area with a characterful, varied identity, that achieves a balanced order between unity and difference avoiding both the sterile and disorienting monotony of centrally planned modernist cities and the (equally disorienting) visual chaos of an agglomeration of utterly unrelated interventions as we find now frequently. Through a thorough research process, our project evolves mainly out of three principles that are taken into consideration for the development of our project: topological optimization, phenomenology, and ecology. By “ecology”, we understand it as a living network of information exchange. Therefore, every strategy we employ is not merely about reacting to the weather conditions, but instead it is an inquiry into the various ways we can exploit the latter, a translation of the weather conditions into spatial and programmatic properties. [Symbios]City therefore aims at developing a multi-authored urban area with a rich identity that achieves a balance between the various elements. [Symbios]City began formally from topological optimization, developed based on studies on ecology, and concluded the design following our phenomenological explorations, aiming at a complex design project that unifies the perception of all scales of design: from the platform to the skyscrapers.
series	cdrf
email
last changed	2022/09/29 07:53

_id	caadria2021_117
id	caadria2021_117
authors	Ikeno, Kazunosuke, Fukuda, Tomohiro and Yabuki, Nobuyoshi
year	2021
title	Can a Generative Adversarial Network Remove Thin Clouds in Aerial Photographs? - Toward Improving the Accuracy of Generating Horizontal Building Mask Images for Deep Learning in Urban Planning and Design
doi	https://doi.org/10.52842/conf.caadria.2021.2.377
source	A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 2, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 377-386
summary	Information extracted from aerial photographs is widely used in the fields of urban planning and architecture. An effective method for detecting buildings in aerial photographs is to use deep learning to understand the current state of a target region. However, the building mask images used to train the deep learning model must be manually generated in many cases. To overcome this challenge, a method has been proposed for automatically generating mask images by using textured 3D virtual models with aerial photographs. Some aerial photographs include thin clouds, which degrade image quality. In this research, the thin clouds in these aerial photographs are removed by using a generative adversarial network, which leads to improvements in training accuracy. Therefore, the objective of this research is to propose a method for automatically generating building mask images by using 3D virtual models with textured aerial photographs to enable the removable of thin clouds so that the image can be used for deep learning. A model trained on datasets generated by the proposed method was able to detect buildings in aerial photographs with an accuracy of IoU = 0.651.
keywords	Urban planning and design; Deep learning; Generative Adversarial Network (GAN); Semantic segmentation; Mask image
series	CAADRIA
email
last changed	2022/06/07 07:50

_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	caadria2021_242
id	caadria2021_242
authors	Joe, Joshua and Pelosi, Antony
year	2021
title	PARAMTR v2 - Human-Generative Design tools for prefabricating large-scale residential developments.
doi	https://doi.org/10.52842/conf.caadria.2021.1.041
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. 41-50
summary	Designers are encountering more issues with complexity, scale and performance requirements increase in residential projects. Prefabrication and generative design tools have the potential to significantly reduce construction time, cost, and material waste at scale. Building upon existing research, this paper further investigates how human-generative design tools can improve building performance and feasibility of prefabrication at scale whilst encouraging design variance. In this context, human-generative design tools refer to a partially algorithmic design tool that facilitates an open-box, collaborative approach to design. Following initial research-based design, a new human-generative tool was created (PARAMTR) to address the aforementioned issues using a design-based research methodology. Based on the research performed during the literature review and from initial design results, PARAMTR shows the potential to halve construction time on residential projects in combination with increased manufacturing efficiency. Design outputs share no design commonality, yet use almost 10 times less unique components across four houses when compared to existing residential projects. In combination with the overall benefits discussed and associated with prefabrication, material waste, cost, design time and complexity are expected to be reduced. The paper will discuss further progress towards designing and building smarter homes at scale.
keywords	generative design; generative prefabrication; parametric; residential; prefabrication
series	CAADRIA
email
last changed	2022/06/07 07:52

_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

_id	caadria2021_043
id	caadria2021_043
authors	Ng, Provides
year	2021
title	21E8: Coupling Generative Adversarial Neural Networks (GANS) with Blockchain Applications in Building Information Modelling (BIM) Systems
doi	https://doi.org/10.52842/conf.caadria.2021.2.111
source	A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 2, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 111-120
summary	The ability of GANs to synthesize large sets of data is ideal for coupling with BIM to formulate a multi-access system that enables users to search and browse through a spectrum of articulated options, all personalised to design specificity - an 'Architecture Machine'. Nonetheless, due to challenges in proprietary incompatibility, BIM systems currently lack a secured yet transparent way of freely integrating with crowdsourced efforts. This research proposes to employ blockchain as a means to couple GANs and BIM, with e8 networking topology to facilitate communication and distribution. It consists of a literature review and a design research that proposes a tech stack design and UML (unified modeling language) use cases, and presents preliminary design results obtained using GANs and e8.
keywords	21e8; GANs; Blockchain; BIM; Architecture Machine
series	CAADRIA
email
last changed	2022/06/07 07:58

_id	ascaad2021_063
id	ascaad2021_063
authors	Ronagh, Ehsan; Mohammadjavad Mahdavinejad, Anoosha Kia
year	2021
title	A New Paradigm in Generative Design Linking Parametric Architecture and Music to Form Finding
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. 227-240
summary	In recent years, geometry and innovations have become an important topic in contemporary architecture. In addition, the 21st century is considered as a new era in architectural design. Computer software development has introduced the theory of form-finding. The present study proposes a novel design and construction method in form-finding based on the relationship between parametric architecture and music. To achieve this goal, several algorithms were designed. The simulation was performed in Rhino with Grasshopper and Firefly plugins, and extensive prototyping of the shells was performed at High-performance Architecture Lab (HAL). This study is aimed at presenting a new design and construction method as a generative design that can use two main characteristics of sound namely frequency and intensity over time. The design also forms the numerical outputs of the music to deform the modular two-dimensional geometric patterns and transform them into three-dimensional parametric shells. The resulting research is fully applicable at a large scale such as urban landscape and small scale as interior design.
series	ASCAAD
email
last changed	2021/08/09 13:13

_id	ecaade2021_186
id	ecaade2021_186
authors	Sebestyen, Adam, Rock, Johanna and Hirschberg, Urs Leonhard
year	2021
title	Towards Abductive Reasoning-Based Computational Design Tools - Using Machine Learning as a way to explore the combined design spaces of multiple parametric models
doi	https://doi.org/10.52842/conf.ecaade.2021.1.141
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. 141-150
summary	Abductive Reasoning - reasoning based on experience - is important for design. This research tries to lay the groundwork for using Variational Autoencoders (VAE) - currently one of the most established deep learning architectures for generative modelling, a subfield of Machine Learning (ML) - as a way to support abductive reasoning in early design stages. While our research is still in its early stages, the first results look promising. In this paper we explain the current state of our research, its premises and methods, and discuss the results achieved thus far. We also explain the motivation behind our work and the potential we see in using VAE in this way and why we believe our approach could represent a paradigmatic shift in the way parametric models can be used in design.
keywords	Machine Learning; Parametric Design; Variational Autoencoders; Generative Modeling; Abductive Reasoning
series	eCAADe
email
last changed	2022/06/07 08:00

_id	ecaade2021_150
id	ecaade2021_150
authors	Song, Yanan and Yuan, Philip F.
year	2021
title	A Research On Building Cluster Morphology Formation Based On Wind Environmental Performance And Deep Reinforcement Learning
doi	https://doi.org/10.52842/conf.ecaade.2021.1.335
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. 335-344
summary	Nowadays, numerous researchers emphasize the significance of the environmen-tal performance-driven generative methodology. However, due to the complex coupling mechanism of environmental regulation factors, the existing optimiza-tion engines and applications are time-consuming and cumbersome. In this re-search, we propose a novel design methodology based on Deep Reinforcement Learning (DRL). This paper is divided into 3 sections, including theoretical framework, design strategy, and practical application. It first introduces an over-view of basic principles, illustrating the potential advantages of DRL in perfor-mance data-driven design. Based on this, the paper proposes a DRL-based gener-ative method. We point out a more specific discussion about the application and workflow of core DRL elements in architectural design. Finally, taking a grid-form urban space composed by multitude high-rise building blocks as an exam-ple, we present a application through a DRL agent to conduct numerous active wind environmental performance-based design tests. It is an interactive and gen-erative design method, owning multiple advantages of timeliness, convenience, and intelligence.
keywords	Deep Reinforcement Learning; Environmental Performance Design; Generative Design; Building Cluster Formation
series	eCAADe
email
last changed	2022/06/07 07:56

_id	ecaade2021_197
id	ecaade2021_197
authors	Szentesi-Nejur, Szende, De Luca, Francesco and Nejur, Andrei
year	2021
title	Integrated Architectural and Environmental Performance-Driven Form-Finding - A teaching case study in Montreal
doi	https://doi.org/10.52842/conf.ecaade.2021.2.105
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. 105-114
summary	The proposed paper presents the methodology and the outcomes of an intensive conception studio taught by the authors at the School of architecture of the University of Montreal having as objective the introduction of 3rd year architecture students to environmental evaluation and optimization techniques linked by the parametric design and the generative creation of architectural object. As opposed to mostly analysis-based approaches, an integration with architectural and urban design concepts was considered to be a more efficient method to initiate architecture students in environmental performance-driven design. The novelty of the course lays in the development of an integrative teaching method having as educational goals the development of environmental analysis skills, the creative use of digital tools, the conception of a coherent optimization process and the ability to represent a performance-driven design process.
keywords	integrative teaching method, environmental design, performance-based design, parametric design, solar architecture, optimization
series	eCAADe
email
last changed	2022/06/07 07:56

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