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	ecaadesigradi2019_514
id	ecaadesigradi2019_514
authors	de Miguel, Jaime, Villafa?e, Maria Eugenia, Piškorec, Luka and Sancho-Caparrini, Fernando
year	2019
title	Deep Form Finding - Using Variational Autoencoders for deep form finding of structural typologies
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 1, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 71-80
doi	https://doi.org/10.52842/conf.ecaade.2019.1.071
summary	In this paper, we are aiming to present a methodology for generation, manipulation and form finding of structural typologies using variational autoencoders, a machine learning model based on neural networks. We are giving a detailed description of the neural network architecture used as well as the data representation based on the concept of a 3D-canvas with voxelized wireframes. In this 3D-canvas, the input geometry of the building typologies is represented through their connectivity map and subsequently augmented to increase the size of the training set. Our variational autoencoder model then learns a continuous latent distribution of the input data from which we can sample to generate new geometry instances, essentially hybrids of the initial input geometries. Finally, we present the results of these computational experiments and lay out the conclusions as well as outlook for future research in this field.
keywords	artificial intelligence; deep neural networks; variational autoencoders; generative design; form finding; structural design
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:55

_id	ecaade2023_259
id	ecaade2023_259
authors	Sonne-Frederiksen, Povl Filip, Larsen, Niels Martin and Buthke, Jan
year	2023
title	Point Cloud Segmentation for Building Reuse - Construction of digital twins in early phase building reuse projects
source	Dokonal, W, Hirschberg, U and Wurzer, G (eds.), Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) - Volume 2, Graz, 20-22 September 2023, pp. 327–336
doi	https://doi.org/10.52842/conf.ecaade.2023.2.327
summary	Point cloud processing has come a long way in the past years. Advances in computer vision (CV) and machine learning (ML) have enabled its automated recognition and processing. However, few of those developments have made it through to the Architecture, Engineering and Construction (AEC) industry. Here, optimizing those workflows can reduce time spent on early-phase projects, which otherwise could be spent on developing innovative design solutions. Simplifying the processing of building point cloud scans makes it more accessible and therefore, usable for design, planning and decision-making. Furthermore, automated processing can also ensure that point clouds are processed consistently and accurately, reducing the potential for human error. This work is part of a larger effort to optimize early-phase design processes to promote the reuse of vacant buildings. It focuses on technical solutions to automate the reconstruction of point clouds into a digital twin as a simplified solid 3D element model. In this paper, various ML approaches, among others KPConv Thomas et al. (2019), ShapeConv Cao et al. (2021) and Mask-RCNN He et al. (2017), are compared in their ability to apply semantic as well as instance segmentation to point clouds. Further it relies on the S3DIS Armeni et al. (2017), NYU v2 Silberman et al. (2012) and Matterport Ramakrishnan et al. (2021) data sets for training. Here, the authors aim to establish a workflow that reduces the effort for users to process their point clouds and obtain object-based models. The findings of this research show that although pure point cloud-based ML models enable a greater degree of flexibility, they incur a high computational cost. We found, that using RGB-D images for classifications and segmentation simplifies the complexity of the ML model but leads to additional requirements for the data set. These can be mitigated in the initial process of capturing the building or by extracting the depth data from the point cloud.
keywords	Point Clouds, Machine Learning, Segmentation, Reuse, Digital Twins
series	eCAADe
email
last changed	2023/12/10 10:49

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

_id	ecaadesigradi2019_135
id	ecaadesigradi2019_135
authors	Newton, David
year	2019
title	Deep Generative Learning for the Generation and Analysis of Architectural Plans with Small Datasets
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 2, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 21-28
doi	https://doi.org/10.52842/conf.ecaade.2019.2.021
summary	The field of generative architectural design has explored a wide range of approaches in the automation of design production, but these approaches have demonstrated limited artificial intelligence. Generative Adversarial Networks (GANs) are a leading deep generative model that use deep neural networks (DNNs) to learn from a set of training examples in order to create new design instances with a degree of flexibility and fidelity that outperform competing generative approaches. Their application to generative tasks in architecture, however, has been limited. This research contributes new knowledge on the use of GANs for architectural plan generation and analysis in relation to the work of specific architects. Specifically, GANs are trained to synthesize architectural plans from the work of the architect Le Corbusier and are used to provide analytic insight. Experiments demonstrate the efficacy of different augmentation techniques that architects can use when working with small datasets.
keywords	generative design; deep learning; artificial intelligence; generative adversarial networks
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:58

_id	ecaade2024_92
id	ecaade2024_92
authors	Mayor Luque, Ricardo; Beguin, Nestor; Rizvi Riaz, Sheikh; Dias, Jessica; Pandey, Sneham
year	2024
title	Multi-material Gradient Additive Manufacturing: A data-driven performative design approach to multi-materiality through robotic fabrication
source	Kontovourkis, O, Phocas, MC and Wurzer, G (eds.), Data-Driven Intelligence - Proceedings of the 42nd Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2024), Nicosia, 11-13 September 2024, Volume 1, pp. 381–390
doi	https://doi.org/10.52842/conf.ecaade.2024.1.381
summary	Buildings are responsible for 39% of global energy-related carbon emissions, with operational activities contributing 28% and materials and construction accounting for 11%(World Green Building Council, 2019) It is therefore vital to reconsider our reliance on fossil fuels for building materials and to develop new advanced manufacturing techniques that enable an integrated approach to material-controlled conception and production. The emergence of Multi-material Additive Manufacturing (MM-AM) technology represents a paradigm shift in producing elements with hybrid properties derived from novel and optimized solutions. Through robotic fabrication, MM-AM offers streamlined operations, reduced material usage, and innovative fabrication methods. It encompasses a plethora of methods to address diverse construction needs and integrates material gradients through data-driven analyses, challenging traditional prefabrication practices and emphasizing the current growth of machine learning algorithms in design processes. The research outlined in this paper presents an innovative approach to MM-AM gradient 3D printing through robotic fabrication, employing data-driven performative analyses enabling control over print paths for sustainable applications in both the AM industry and our built environment. The article highlights several designed prototypes from two distinct phases, demonstrating the framework's viability, implications, and constraints: a workshop dedicated to data-driven analyses in facade systems for MM-AM 3D-printed brick components, and a 3D-printed brick facade system utilizing two renewable and bio-materials—Cork sourced from recycled stoppers and Charcoal, with the potential for carbon sequestration.
keywords	Data-driven Performative design, Multi-material 3d Printing, Material Research, Fabrication-informed Material Design, Robotic Fabrication
series	eCAADe
email
last changed	2024/11/17 22:05

_id	ecaadesigradi2019_327
id	ecaadesigradi2019_327
authors	Silva, Daniela, Paio, Alexandra and Sousa, José Pedro
year	2019
title	Reprogramming Practice - Revising design thinking through digital fabrication
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 1, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 379-386
doi	https://doi.org/10.52842/conf.ecaade.2019.1.379
summary	Questioning the importance and impact of design thinking methodologies in the architectural design studios is a backbone of architectural education in twenty first century. 3D printing and digital manufacturing are disruptive technologies that are changing architects and designers daily lives. These trends require new skills, based on a deep understanding of digital continuum from design to production, from generation to fabrication. This continuity transcends the merely instrumental contributions of a person-machine relationship to praxis, has begun to evolve as a medium that supports a continuous logic of design thinking and making. Design thinking methodologies associated with digital fabrication emerged as a leading technological and design issue of digital research and design. As designers, we are witnessing a no frontier between computational design and digital fabrication. For this paper is taken into consideration the work of two architecture studios that share a unique background on new methodologies by embracing the digital technology in their own practice. Their work reflects on new design methodologies facing the expansion of digital technology in architectural practice. This paper discusses the possibility of new design thinking methods driven by digital fabrication.
keywords	Design thinking; Digital Fabrication; AEC; Collaborative Design; Architectural Practice
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:56

_id	ijac201917105
id	ijac201917105
authors	Agkathidis, Asterios; Yorgos Berdos and André Brown
year	2019
title	Active membranes: 3D printing of elastic fibre patterns on pre-stretched textiles
source	International Journal of Architectural Computing vol. 17 - no. 1, 74-87
summary	There has been a steady growth, over several decades, in the deployment of fabrics in architectural applications; both in terms of quantity and variety of application. More recently, three-dimensional printing and additive manufacturing have added to the palette of technologies that designers in architecture and related disciplines can call upon. Here, we report on research that brings those two technologies together – the development of active membrane elements and structures. We show how these active membranes have been achieved by laminating three-dimensional printed elasto-plastic fibres onto pre-stretched textile membranes. We report on a set of experimentations involving one-, two- and multi-directional geometric arrangements that take TPU 95 and polypropylene filaments and apply them to Lycra textile sheets, to form active composite panels. The process involves a parameterised design, actualised through a fabrication process including stress-line simulation, fibre pattern three-dimensional printing and the lamination of embossed patterns onto a pre-stretched membrane; followed by the release of tension afterwards in order to allow controlled, self-generation of the final geometry. Our findings document the investigation into mapping between the initial two-dimensional geometries and their resulting three-dimensional doubly curved forms. We also reflect on the products of the resulting, partly serendipitous, design process.
keywords	Digital fabrication, three-dimensional printing, parametric design, material computation, fabrics
series	journal
email
last changed	2019/08/07 14:04

_id	ecaadesigradi2019_425
id	ecaadesigradi2019_425
authors	Betti, Giovanni, Aziz, Saqib and Ron, Gili
year	2019
title	Pop Up Factory : Collaborative Design in Mixed Rality - Interactive live installation for the makeCity festival, 2018 Berlin
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 3, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 115-124
doi	https://doi.org/10.52842/conf.ecaade.2019.3.115
summary	This paper examines a novel, integrated and collaborative approach to design and fabrication, enabled through Mixed Reality. In a bespoke fabrication process, the design is controlled and altered by users in holographic space, through a custom, multi-modal interface. Users input is live-streamed and channeled to 3D modelling environment,on-demand robotic fabrication and AR-guided assembly. The Holographic Interface is aimed at promoting man-machine collaboration. A bespoke pipeline translates hand gestures and audio into CAD and numeric fabrication. This enables non-professional participants engage with a plethora of novel technology. The feasibility of Mixed Reality for architectural workflow was tested through an interactive installation for the makeCity Berlin 2018 festival. Participants experienced with on-demand design, fabrication an AR-guided assembly. This article will discuss the technical measures taken as well as the potential in using Holographic Interfaces for collaborative design and on-site fabrication.Please write your abstract here by clicking this paragraph.
keywords	Holographic Interface; Augmented Reality; Multimodal Interface; Collaborative Design; Robotic Fabrication; On-Site Fabrication
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:52

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

_id	cf2019_021
id	cf2019_021
authors	Cheng, Chi-Li and June-Hao Hou
year	2019
title	A Method of Mesh Simplification for Drone 3D Modeling with Architectural Feature Extraction
source	Ji-Hyun Lee (Eds.) "Hello, Culture!" [18th International Conference, CAAD Futures 2019, Proceedings / ISBN 978-89-89453-05-5] Daejeon, Korea, p. 169
summary	This paper proposes a method of mesh simplification for 3D terrain or city models generated photogrammetrically from drone captured images, enabled by the ability of extracting the architectural features. Compare to traditional geometric computational method, the proposed method recognizes and processes the features from the architectural perspectives. In addition, the workflow also allows exporting the simplified models and geometric features to open platforms, e.g. OpenStreetMap, for practical usages in site analysis, city generation, and contributing to the open data communities.
keywords	Mesh Reconstruction, photogrammetry, mesh simplification, procedural mode, machine learning
series	CAAD Futures
email
last changed	2019/07/29 14:08

_id	acadia20_382
id	acadia20_382
authors	Hosmer, Tyson; Tigas, Panagiotis; Reeves, David; He, Ziming
year	2020
title	Spatial Assembly with Self-Play Reinforcement Learning
source	ACADIA 2020: Distributed Proximities / Volume I: Technical Papers [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95213-0]. Online and Global. 24-30 October 2020. edited by B. Slocum, V. Ago, S. Doyle, A. Marcus, M. Yablonina, and M. del Campo. 382-393.
doi	https://doi.org/10.52842/conf.acadia.2020.1.382
summary	We present a framework to generate intelligent spatial assemblies from sets of digitally encoded spatial parts designed by the architect with embedded principles of prefabrication, assembly awareness, and reconfigurability. The methodology includes a bespoke constraint-solving algorithm for autonomously assembling 3D geometries into larger spatial compositions for the built environment. A series of graph-based analysis methods are applied to each assembly to extract performance metrics related to architectural space-making goals, including structural stability, material density, spatial segmentation, connectivity, and spatial distribution. Together with the constraint-based assembly algorithm and analysis methods, we have integrated a novel application of deep reinforcement (RL) learning for training the models to improve at matching the multiperformance goals established by the user through self-play. RL is applied to improve the selection and sequencing of parts while considering local and global objectives. The user’s design intent is embedded through the design of partial units of 3D space with embedded fabrication principles and their relational constraints over how they connect to each other and the quantifiable goals to drive the distribution of effective features. The methodology has been developed over three years through three case study projects called ArchiGo (2017–2018), NoMAS (2018–2019), and IRSILA (2019-2020). Each demonstrates the potential for buildings with reconfigurable and adaptive life cycles.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	cf2019_015
id	cf2019_015
authors	Ladron de Guevara, Manuel; Luis Ricardo Borunda and Ramesh Krishnamurti
year	2019
title	A Multi-Resolution Design Methodology Based on Discrete Models
source	Ji-Hyun Lee (Eds.) "Hello, Culture!" [18th International Conference, CAAD Futures 2019, Proceedings / ISBN 978-89-89453-05-5] Daejeon, Korea, p. 129
summary	The use of programming languages in design opens up unexplored and previously unworkable territories, mainly, in conventional architectural practice. In the 1990s, languages of continuity, smoothness and seamlessness dominated the architectural inquiry with the CNC milling machine as its manufacturing tool. Today’s computational design and fabrication technology look at languages of synthesis of fragments or particles, with the 3D printer as its fabrication archetype. Fundamental to this idea is the concept of resolution– the amount of information stored at any localized region. Construction of a shape is then based on multiple regions of resolution. This paper explores a novel design methodology that takes this concept of resolutions on discrete elements as a design driver for architectural practice. This research has been tested primarily through additive manufacturing techniques.
keywords	Multi-Resolution Design Methodology; Discrete-Based Computational Design; Resolutions; Additive Manufacturing
series	CAAD Futures
email
last changed	2019/07/29 14:08

_id	ecaadesigradi2019_455
id	ecaadesigradi2019_455
authors	Moreira, Jo?o, Figueiredo, Bruno and Cruz, Paulo
year	2019
title	Ceramic Additive Manufacturing in Architecture - Computational Methodology for Defining a Column System
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 1, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 471-476
doi	https://doi.org/10.52842/conf.ecaade.2019.1.471
summary	The present paper describes a research that explores the design and production of customised architectural ceramic components defined through parametric relations of biomorphic inspiration and to be built through additive manufacturing. In this sense, is presented a case study that develops a system of both architectural and structural components - a column system. The definition process of the system is mediated by computational design, implementing not only structural analysis and optimization strategies, but also mimetic formal characteristics of nature to an initial grid, creating a model that adapts its formal attributes, depending on its assumptions and the material constraints. This process resulted in the definition of a set of solutions that better answer to a specific design problem.
keywords	Additive Manufacturing; Ceramic 3D; Computational Design; Structural Optimization; Biomorphism
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:58

_id	ecaadesigradi2019_168
id	ecaadesigradi2019_168
authors	Varinlioglu, Guzden and Halici, Suheyla Muge
year	2019
title	Gamification of Heritage through Augmented Reality
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 1, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 513-518
doi	https://doi.org/10.52842/conf.ecaade.2019.1.513
summary	This paper focuses on a game on architectural heritage, possibilities for using gamification for conveying information through the reanimation of an ancient city. It proposes an immersive AR game involving the portrayal of cultural heritage through mobile devices. The game includes an AR application for Android devices which enabled rendering of 3D content in combination with camera input. This application is an independent game, tracking targets through GPS on a larger scale and using object recognition on a smaller scale. Our research aims to propose implementing game mechanics on an AR system at an archaeological site in order to increase visitors' interest, and promote the dissemination of cultural heritage.
keywords	digital heritage; model-based tracking; augmented reality; gamification; public archaeology
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:58

_id	ecaadesigradi2019_417
id	ecaadesigradi2019_417
authors	Weissenböck, Renate and Symeonidou, Ioanna
year	2019
title	Anatomy of a Building - Introducing interactive RGB lenses for architectural data visualization
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 1, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 739-748
doi	https://doi.org/10.52842/conf.ecaade.2019.1.739
summary	The paper proposes an alternative way to present architectural information, using color filters - specifically RGB lenses - as an interface to emphasize or reveal the internal structure or hidden logic of an architectural artifact. In an interplay of analogue and digital techniques, it employs rules of color blocking in order to highlight certain aspects of complex buildings, urban plans, or interiors, which cannot be discovered using conventional visualization methods. In this research, the authors developed an interactive RGB lens-interface and techniques for superimposed color visualizations that can be used for an enhanced visualization of the internal structure of a building. By applying physical or digital color lenses, viewers can perceive individual layers of project visualizations, in order to understand certain tectonic or construction logics, such as skin, structure or infrastructure. Based on existing bibliography, the paper presents the workflow from drawing, 3D model or photograph to RGB visualization, through a series of test case scenarios applicable to the field of architecture and design.
keywords	architectural visualization; color & light; subtractive color mixing; RGB lenses; post-digital; building anatomy
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:58

_id	ecaadesigradi2019_605
id	ecaadesigradi2019_605
authors	Andrade Zandavali, Bárbara and Jiménez García, Manuel
year	2019
title	Automated Brick Pattern Generator for Robotic Assembly using Machine Learning and Images
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 3, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 217-226
doi	https://doi.org/10.52842/conf.ecaade.2019.3.217
summary	Brickwork is the oldest construction method still in use. Digital technologies, in turn, enabled new methods of representation and automation for bricklaying. While automation explored different approaches, representation was limited to declarative methods, as parametric filling algorithms. Alternatively, this work proposes a framework for automated brickwork using a machine learning model based on image-to-image translation (Conditional Generative Adversarial Networks). The framework consists of creating a dataset, training a model for each bond, and converting the output images into vectorial data for robotic assembly. Criteria such as: reaching wall boundary accuracy, avoidance of unsupported bricks, and brick's position accuracy were individually evaluated for each bond. The results demonstrate that the proposed framework fulfils boundary filling and respects overall bonding structural rules. Size accuracy demonstrated inferior performance for the scale tested. The association of this method with 'self-calibrating' robots could overcome this problem and be easily implemented for on-site.
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:54

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

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

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

_id	caadria2019_546
id	caadria2019_546
authors	Holzer, Dominik
year	2019
title	Teaching Computational Design and BIM in the Age of (Semi)flipped Classrooms
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 2, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 715-724
doi	https://doi.org/10.52842/conf.caadria.2019.2.715
summary	With academic curricula for architectural education increasingly packed with new and expanding fields of inquiry, questions emerge on how to incorporate the ever-growing number of subjects that tackle the use of computational tools for design and delivery. This paper analyses approaches to blended learning under a semi-flipped classroom model where learning content gets divided into complementary in-class and online components. The author describes the epistemological challenges in curating the blended-learning mix and discusses ways to optimise learning outcomes while minimising the effort for custom content-development of training material. Two subjects taught at the author's home institution (one in Computational Design and the other for BIM education) serve as case studies to test the flipped classroom approach and to derive feedback from students about their preferred method of delivery.
keywords	BIM; Flipped-Classroom; Computational Design; Education; Online learning
series	CAADRIA
email
last changed	2022/06/07 07:50

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