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	caadria2020_259
id	caadria2020_259
authors	Rhee, Jinmo, Veloso, Pedro and Krishnamurti, Ramesh
year	2020
title	Integrating building footprint prediction and building massing - an experiment in Pittsburgh
doi	https://doi.org/10.52842/conf.caadria.2020.2.669
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 2, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 669-678
summary	We present a novel method for generating building geometry using deep learning techniques based on contextual geometry in urban context and explore its potential to support building massing. For contextual geometry, we opted to investigate the building footprint, a main interface between urban and architectural forms. For training, we collected GIS data of building footprints and geometries of parcels from Pittsburgh and created a large dataset of Diagrammatic Image Dataset (DID). We employed a modified version of a VGG neural network to model the relationship between (c) a diagrammatic image of a building parcel and context without the footprint, and (q) a quadrilateral representing the original footprint. The option for simple geometrical output enables direct integration with custom design workflows because it obviates image processing and increases training speed. After training the neural network with a curated dataset, we explore a generative workflow for building massing that integrates contextual and programmatic data. As trained model can suggest a contextual boundary for a new site, we used Massigner (Rhee and Chung 2019) to recommend massing alternatives based on the subtraction of voids inside the contextual boundary that satisfy design constraints and programmatic requirements. This new method suggests the potential that learning-based method can be an alternative of rule-based design methods to grasp the complex relationships between design elements.
keywords	Deep Learning; Prediction; Building Footprint; Massing; Generative Design
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	acadia20_228
id	acadia20_228
authors	Alawadhi, Mohammad; Yan, Wei
year	2020
title	BIM Hyperreality
doi	https://doi.org/10.52842/conf.acadia.2020.1.228
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. 228-236.
summary	Deep learning is expected to offer new opportunities and a new paradigm for the field of architecture. One such opportunity is teaching neural networks to visually understand architectural elements from the built environment. However, the availability of large training datasets is one of the biggest limitations of neural networks. Also, the vast majority of training data for visual recognition tasks is annotated by humans. In order to resolve this bottleneck, we present a concept of a hybrid system—using both building information modeling (BIM) and hyperrealistic (photorealistic) rendering—to synthesize datasets for training a neural network for building object recognition in photos. For generating our training dataset, BIMrAI, we used an existing BIM model and a corresponding photorealistically rendered model of the same building. We created methods for using renderings to train a deep learning model, trained a generative adversarial network (GAN) model using these methods, and tested the output model on real-world photos. For the specific case study presented in this paper, our results show that a neural network trained with synthetic data (i.e., photorealistic renderings and BIM-based semantic labels) can be used to identify building objects from photos without using photos in the training data. Future work can enhance the presented methods using available BIM models and renderings for more generalized mapping and description of photographed built environments.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	caadria2020_009
id	caadria2020_009
authors	Wang, Likai, Chen, Kian Wee, Janssen, Patrick and Ji, Guohua
year	2020
title	Algorithmic generation of architectural Massing Models for building design optimisation - Parametric Modelling Using Subtractive and Additive Form Generation Principles
doi	https://doi.org/10.52842/conf.caadria.2020.1.385
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 385-394
summary	Using performance-based optimisation to explore unknown design solutions space has become widely acknowledged and considered an efficient approach to designing high-performing buildings. However, the lack of design diversity in the design space defined by the parametric model often confines the search of the optimisation process to a family of similar design variants. In order to overcome this weakness, this paper presents two parametric massing generation algorithms based on the additive and subtractive form generation principles. By abstracting the rule of these two principles, the algorithms can generate diverse building massing design alternatives. This allows the algorithms to be used in performance-based optimisation for exploring a wide range of design alternatives guided by various performance objectives. Two case studies of passive solar energy optimisation are presented to demonstrate the efficacy of the algorithm in helping architects achieve an explorative performance-based optimisation process.
keywords	parametric massing algorithms; performance-based optimisation; design exploration; solar irradiation
series	CAADRIA
email
last changed	2022/06/07 07:58

_id	caadria2020_118
id	caadria2020_118
authors	Chow, Ka Lok and van Ameijde, Jeroen
year	2020
title	Generative Housing Communities - Design of Participatory Spaces in Public Housing Using Network Configurational Theories
doi	https://doi.org/10.52842/conf.caadria.2020.2.283
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 2, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 283-292
summary	This research-by-design project explores how public housing estates can accommodate social diversity and the appropriation of shared spaces, using qualitative and quantitative analysis of circulation networks. A case study housing estate in Hong Kong was analysed through field observations of movements and activities and as a site for the speculative re-design of shared spaces. Generative design processes were developed based on several parameters, including shortest paths, visibility integration and connectivity integration (Hillier & Hanson, 1984). Additional tools were developed to combine these techniques with optimisation of sunlight access, maximisation of views for residential towers and the provision of permeability of ground level building volumes. The project demonstrates how flexibility of use and social engagement can constitute a platform for self-organisation, similar to Jane Jacobs' notion of vibrant streets leading to active and progressive communities. It shows how computational design and configurational theories can promote a bottom-up approach for generating new types of residential environments that support participatory and diverse communities, rather than a conventional top-down approach that is perceived to embody mechanisms of social regimentation.
keywords	Urban Planning and Design; Network Configuration; Community Space and Social Interaction; Hong Kong Public Housing
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	ecaade2020_190
id	ecaade2020_190
authors	Dounas, Theodoros, Jabi, Wassim and Lombardi, Davide
year	2020
title	Smart Contracts for Decentralised Building Information Modelling
doi	https://doi.org/10.52842/conf.ecaade.2020.2.565
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 565-574
summary	The paper presents a model for decentralizing building information modelling, through implementing its infrastructure using the decentralized web. We discuss the shortcomings of BIM in terms of its infrastructure, with a focus on tracing identities of design authorship in this collective design tool. In parallel we examine the issues with BIM in the cloud and propose a decentralized infrastructure based on the Ethereum blockchain and the Interplanetary filesystem (IPFS). A series of computing nodes, that act as nodes on the Ethereum Blockchain, host disk storage with which they participate in a larger storage pool on the Interplanetary Filesystem. This storage is made available through an API is used by architects and designers creating and editing a building information model that resides on the IPFS decentralised storage. Through this infrastructure central servers are eliminated, and BIM libraries and models can be shared with others in an immutable and transparent manner. As such Architecture practices are able to exploit their intellectual property in novel ways, by making it public on the internet. The infrastructure also allows the decentralised creation of a resilient global pool of data that allows the participation of computation agents in the creation and simulation of BIM models.
keywords	Blockchain; decentralisation; immutability; resilience; Building Information Modelling
series	eCAADe
email
last changed	2022/06/07 07:55

_id	ecaade2020_411
id	ecaade2020_411
authors	Muehlbauer, Manuel, Song, Andy and Burry, Jane
year	2020
title	Smart Structures - A Generative Design Framework for Aesthetic Guidance in Structural Node Design - Application of Typogenetic Design for Custom-Optimisation of Structural Nodes
doi	https://doi.org/10.52842/conf.ecaade.2020.1.623
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 1, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 623-632
summary	Virtual prototypes enable performance simulation for building components. The presented research extended the application of generative design using virtual prototypes for interactive optimisation of structural nodes. User-interactivity contributed to the geometric definition of design spaces rather than the final geometric outcome, enabling another stage of generative design for the micro-structure of the structural node. In this stage, the micro-structure inside the design space was generated using fixed topology. In contrast to common optimisation strategies, which converge towards a single optimal outcome, the presented design exploration process allowed the regular review of design solutions. User-based selection guided the evolutionary process of design space exploration applying Online Classification. Another guidance mechanism called Shape Comparison introduced an intelligent control system using an inital image input as design reference. In this way, aesthetic guidance enabled the combined evaluation of quantitative and qualitative criteria in the custom-optimisation of structural nodes. Interactive node design extended the potential for shape variation of custom-optimized structural nodes by addressing the geometric definition of design spaces for multi-scalar structural optimisation.
keywords	generative design; evolutionary computation; interactive machine learning; typogenetic design
series	eCAADe
email
last changed	2022/06/07 07:58

_id	sigradi2020_104
id	sigradi2020_104
authors	Pita, Juliano Veraldo da Costa; Tramontano, Marcelo
year	2020
title	Deciding together: a BIM-based platform for participative design processes
source	SIGraDi 2020 [Proceedings of the 24th Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Online Conference 18 - 20 November 2020, pp. 104-111
summary	This article discusses aspects of building a digital platform that allows non-technical actors to participate in the development of the design of public facilities using BIM. The concept of the design of such a platform refers to characteristics specific to BIM, aiming at an equivalence between the contributions of non-technical and technical actors to the process. We have developed a platform prototype and studied its adaptation to different applications. The article discusses the construction and testing of the different versions and the preliminary results of performance tests.
keywords	BIM, Participatory processes, Public facilities
series	SIGraDi
email
last changed	2021/07/16 11:48

_id	sigradi2020_490
id	sigradi2020_490
authors	Santos, Ítalo Guedes dos; Andrade, Max Lira Veras Xavier de
year	2020
title	Standardization of Airport Architectural Design Projects BIM-based for Code Checking
source	SIGraDi 2020 [Proceedings of the 24th Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Online Conference 18 - 20 November 2020, pp. 490-498
summary	This paper addresses the use of BIM for code verification and automatic validation of the Architectural Design of Airports (ADA). In Brazil, the evaluation and approval of ADA are carried out by INFRAERO. Currently, designs are evaluated manually, resulting in errors and long evaluation time. To deal with this problem, a conceptual framework for automated ADA assessment with Code Checking is proposed. The method used was Design Science Research, with the proposal of an artifact. The partial results show the importance of establishing protocols for BIM modeling, based on IFC as an important tool for automated assessment with code checking.
keywords	Airports, Architectural Design of Airport, Building Information Modeling, Code Checking, IFC
series	SIGraDi
email
last changed	2021/07/16 11:49

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

_id	acadia20_290
id	acadia20_290
authors	Stuart-Smith, Robert; Danahy, Patrick; Revelo La Rotta, Natalia
year	2020
title	Topological and Material Formation
doi	https://doi.org/10.52842/conf.acadia.2020.1.290
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. 290-299.
summary	Extrusion-based additive manufacturing (AM) is gaining traction in the construction industry, offering lower environmental and economic costs through reductions in material and production time. AM designs achieve these reductions by increasing topological and geometric complexity, and through variable material distribution via custom-programmed robot tool paths. Limited approaches are available to develop AM building designs within a topologically free design search or to leverage material affects relative to structural performance. Established methods such as topological structural optimization (TSO) operate primarily within design rationalization, demonstrating less formal or aesthetic diversity than agent-based methods that exhibit behavioral character. While material-extrusion gravitational affects have been explored in AM research using viscous materials such as concrete and ceramics, established methods are not sufficiently integrated into simulation and structural analysis workflows. A novel three-part method is proposed for the design and simulation of extrusion-based AM that includes topoForm, an evolutionary multi-agent software capable of generating diverse topological designs; matForm, an agent-based AM robot tool-path generator that is geometrically agnostic and adapts material effects to local structural and geometric data; and matSim, a material-physics simulation environment that enables high-resolution AM material effects to be simulated and structurally and aesthetically analyzed. The research enables designers to incorporate and simulate material behavior prior to fabrication and produce instructions suitable for industrial robot AM. The approach is demonstrated in the generative design of four AM column-like elements.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	ascaad2022_102
id	ascaad2022_102
authors	Turki, Laila; Ben Saci, Abdelkader
year	2022
title	Generative Design for a Sustainable Urban Morphology
source	Hybrid Spaces of the Metaverse - Architecture in the Age of the Metaverse: Opportunities and Potentials [10th ASCAAD Conference Proceedings] Debbieh (Lebanon) [Virtual Conference] 12-13 October 2022, pp. 434-449
summary	The present work concerns the applications of generative design for sustainable urban fabric. This represents an iterative process that involves an algorithm for the generation of solar envelopes to satisfy solar and density constraints. We propose in this paper to explore a meta-universe of human-machine interaction. It aims to design urban forms that offer solar access. This being to minimize heating energy expenditure and provide solar well-being. We propose to study the impact of the solar strategy of building morphosis on energy exposure. It consists of determining the layout and shape of the constructions based on the shading cut-off time. This is a period of desirable solar access. We propose to define it as a balance between the solar irradiation received in winter and that received in summer. We rely on the concept of the solar envelope defined since the 1970s by Knowles and its many derivatives (Koubaa Turki & al., 2020). We propose a parametric model to generate solar envelopes at the scale of an urban block. The generative design makes it possible to create a digital model of the different density solutions by varying the solar access duration. The virtual environment created allows exploring urban morphologies resilient both to urban densification and better use of the context’s resources. The seasonal energy balance, between overexposure in summer and access to the sun in winter, allows reaching high energy and environmental efficiency of the buildings. We have developed an algorithm on Dynamo for the generation of the solar envelope by shading exchange. The program makes it possible to detect the boundaries of the parcels imported from Revit, establish the layout of the building, and generate the solar envelopes for each variation of the shading cut-off time. It also calculates the FAR1 and the FSI2 from the variation of the shading cut-off time for each parcel of the island. We compare the solutions generated according to the urban density coefficients and the solar access duration. Once the optimal solution has been determined, we export the results back into Revit environment to complete the BIM modelling for solar study. This article proposes a method for designing buildings and neighbourhoods in a virtual environment. The latter acts upstream of the design process and can be extended to the different phases of the building life cycle: detailed design, construction, and use.
series	ASCAAD
email
last changed	2024/02/16 13:38

_id	acadia20_94
id	acadia20_94
authors	Yoo, Wonjae; Kim, Hyoungsub; Shin, Minjae; J.Clayton, Mark
year	2020
title	BIM-Based Automatic Contact Tracing System Using Wi-Fi
doi	https://doi.org/10.52842/conf.acadia.2020.1.094
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. 94-101.
summary	This study presents a BIM-based automatic contact tracing method using a stations-oriented indoor localization (SOIL) system. The SOIL system integrates BIM models and existing network infrastructure (i.e., Wi-Fi), using a clustering method to generate roomlevel occupancy schedules. In this study, we improve the accuracy of the SOIL system by including more detailed Wi-Fi signal travel sources, such as reflection, refraction, and diffraction. The results of field measurements in an educational building show that the SOIL system was able to produce room-level occupant location information with a 95.6% level of accuracy. This outcome is 2.6% more accurate than what was found in a previous study. We also describe an implementation of the SOIL system for conducting contact tracing in large buildings. When an individual is confirmed to have COVID-19, public health professionals can use this system to quickly generate information regarding possible contacts. The greatest strength of this SOIL implementation is that it has wide applicability in largescale buildings, without the need for additional sensing devices. Additional tests using buildings with multiple floors are required to further explore the robustness of the system.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	cdrf2019_134
id	cdrf2019_134
authors	Zhen Han, Wei Yan, and Gang Liu
year	2020
title	A Performance-Based Urban Block Generative Design Using Deep Reinforcement Learning and Computer Vision
doi	https://doi.org/https://doi.org/10.1007/978-981-33-4400-6_13
source	Proceedings of the 2020 DigitalFUTURES The 2nd International Conference on Computational Design and Robotic Fabrication (CDRF 2020)
summary	In recent years, generative design methods are widely used to guide urban or architectural design. Some performance-based generative design methods also combine simulation and optimization algorithms to obtain optimal solutions. In this paper, a performance-based automatic generative design method was proposed to incorporate deep reinforcement learning (DRL) and computer vision for urban planning through a case study to generate an urban block based on its direct sunlight hours, solar heat gains as well as the aesthetics of the layout. The method was tested on the redesign of an old industrial district located in Shenyang, Liaoning Province, China. A DRL agent - deep deterministic policy gradient (DDPG) agent - was trained to guide the generation of the schemes. The agent arranges one building in the site at one time in a training episode according to the observation. Rhino/Grasshopper and a computer vision algorithm, Hough Transform, were used to evaluate the performance and aesthetics, respectively. After about 150 h of training, the proposed method generated 2179 satisfactory design solutions. Episode 1936 which had the highest reward has been chosen as the final solution after manual adjustment. The test results have proven that the method is a potentially effective way for assisting urban design.
series	cdrf
email
last changed	2022/09/29 07:51

_id	ecaade2020_534
id	ecaade2020_534
authors	Verniz, Debora and Duarte, José P
year	2020
title	From Analysis to Design - A framework for developing synthetic shape grammars
doi	https://doi.org/10.52842/conf.ecaade.2020.2.535
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 535-544
summary	This paper focuses on the problem of lack of housing, due to fast urbanization processes and urban population growth, particularly in developing regions of the globe. The goal is to propose an alternative for planning housing settlements, using a computational-based approach, and having as a case study an existing Brazilian favela, Santa Marta. The paper proposes a strategy to bridge between the use of shape grammars from analysis to design, by performing changes on the rule level. The research includes the development of an analytical grammar that captures the physical features of the settlement and its subsequent transformation into a synthetic grammar that can generate urban configurations that keep key features of the original settlement while avoiding its flaws. The paper is focused on the grammatical transformations performed to the analytic grammar to obtain the synthetic grammar and its subsequent validation. Results show that the solutions generated by the synthetic grammar do have higher quality when compared to the case study. This strategy is proposed as a framework for the application of shape grammars in design.
keywords	shape grammars; grammatical transformations; Santa Marta favela; Santa Marta Urban Grammar
series	eCAADe
email
last changed	2022/06/07 07:58

_id	caadria2020_045
id	caadria2020_045
authors	Zheng, Hao and Ren, Yue
year	2020
title	Machine Learning Neural Networks Construction and Analysis in Vectorized Design Drawings
doi	https://doi.org/10.52842/conf.caadria.2020.2.707
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 2, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 707-716
summary	Machine Learning, a recently prevalent research domain in data prediction and analysis, has been widely used in a variety of fields. In the design field, especially for architectural design, a machine learning method to learn and generate design data as pixelized images has been developed in previous researches. However, proceeding pixelized image data will cause the problems of precision loss and calculation waste, since the geometric architectural design data is efficiently stored and presented as vectorized CAD files. Thus, in this article, the author developed a specific machine learning neural network to learn and predict design drawings as vectorized data, speeding up the learning and predicting process, while improving the accuracy. First, two necessary geometric tests have been successfully done, which shows the central concept of neural network construct. Then, a design rule prediction model was built to demonstrate the methods to optimize the neural network and data structure. Lastly, a generation model based on human-made design data was constructed, which can be used to predict and generate the bedroom furniture positions by inputting the boundary data of the room, door, and window.
keywords	Machine Learning; Artificial Intelligence; Generative Design; Geometric Design
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	caadria2020_443
id	caadria2020_443
authors	Abuzuraiq, Ahmed M. and Erhan, Halil
year	2020
title	The Many Faces of Similarity - A Visual Analytics Approach for Design Space Simplification
doi	https://doi.org/10.52842/conf.caadria.2020.1.485
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 485-494
summary	Generative design methods may involve a complex design space with an overwhelming number of alternatives with their form and design performance data. Existing research addresses this complexity by introducing various techniques for simplification through clustering and dimensionality reduction. In this study, we further analyze the relevant literature on design space simplification and exploration to identify their potentials and gaps. We find that the potentials include: alleviating the choice overload problem, opening up new venues for interrelating design forms and data, creating visual overviews of the design space and introducing ways of creating form-driven queries. Building on that, we present the first prototype of a design analytics dashboard that combines coordinated and interactive visualizations of design forms and performance data along with the result of simplifying the design space through hierarchical clustering.
keywords	Visual Analytics; Design Exploration; Dimensionality Reduction; Clustering; Similarity-based Exploration
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	sigradi2020_60
id	sigradi2020_60
authors	Asmar, Karen El; Sareen, Harpreet
year	2020
title	Machinic Interpolations: A GAN Pipeline for Integrating Lateral Thinking in Computational Tools of Architecture
source	SIGraDi 2020 [Proceedings of the 24th Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Online Conference 18 - 20 November 2020, pp. 60-66
summary	In this paper, we discuss a new tool pipeline that aims to re-integrate lateral thinking strategies in computational tools of architecture. We present a 4-step AI-driven pipeline, based on Generative Adversarial Networks (GANs), that draws from the ability to access the latent space of a machine and use this space as a digital design environment. We demonstrate examples of navigating in this space using vector arithmetic and interpolations as a method to generate a series of images that are then translated to 3D voxel structures. Through a gallery of forms, we show how this series of techniques could result in unexpected spaces and outputs beyond what could be produced by human capability alone.
keywords	Latent space, GANs, Lateral thinking, Computational tools, Artificial intelligence
series	SIGraDi
email
last changed	2021/07/16 11:48

_id	sigradi2020_652
id	sigradi2020_652
authors	Baldessin, Guilherme Quinilato; Vaz, Matheus Motta; Medeiros, Givaldo Luiz; Fabricio, Márcio Minto
year	2020
title	Modeling of steel and precast concrete components based on BIM systems and their application for the teaching of Architectural Design
source	SIGraDi 2020 [Proceedings of the 24th Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Online Conference 18 - 20 November 2020, pp. 652-659
summary	This paper addresses the development of parametric components based on BIM (Building Information Modeling) tools and their application for the teaching of architecture and urban designs, in a discipline focused on housing typology. As a didactic and research method, the use of industrialized building technologies in steel and precast concrete for production efficiency and low maintenance is associated with the idea of the studio as a laboratory for verification and experimentation. The system was improved for two years, and provided students with greater constructive control, basic feedback on the budget, and mastery of representation, while they investigated alternative design concepts and new components.
keywords	Architectural Design, Building Technology, BIM, Higher Education, Housing
series	SIGraDi
email
last changed	2021/07/16 11:52

_id	acadia20_120
id	acadia20_120
authors	Barsan-Pipu, Claudiu; Sleiman, Nathalie; Moldovan, Theodor
year	2020
title	Affective Computing for Generating Virtual Procedural Environments Using Game Technologies
doi	https://doi.org/10.52842/conf.acadia.2020.2.120
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. 120-129.
summary	Architects have long sought to create spaces that can relate to or even induce specific emotional conditions in their users, such as states of relaxation or engagement. Dynamic or calming qualities were given to these spaces by controlling form, perspective, lighting, color, and materiality. The actual impact of these complex design decisions has been challenging to assess, from both quantitative and qualitative standpoints, because neural empathic responses, defined in this paper by feature indexes (FIs) and mind indexes (MIs), are highly subjective experiences. Recent advances in the fields of virtual procedural environments (VPEs) and virtual reality (VR), supported by powerful game engine (GE) technologies, provide computational designers with a new set of design instruments that, when combined with brain-computing interfacing (BCI) and eye-tracking (E-T) hardware, can be used to assess complex empathic reactions. As the COVID-19 health crisis showed, virtual social interaction becomes increasingly relevant, and the social catalytic potential of VPEs can open new design possibilities. The research presented in this paper introduces the cyber-physical design of such an affective computing system. It focuses on how relevant empathic data can be acquired in real time by exposing subjects within a dynamic VR-based VPE and assessing their emotional responses while controlling the actual generative parameters via a live feedback loop. A combination of VR, BCI, and E-T solutions integrated within a GE is proposed and discussed. By using a VPE inside a BCI system that can be accurately correlated with E-T, this paper proposes to identify potential morphological and lighting factors that either alone or combined can have an empathic effect expressed by the relevant responses of the MIs.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	caadria2020_258
id	caadria2020_258
authors	Beatricia, Beatricia, Indraprastha, Aswin and Koerniawan, M. Donny
year	2020
title	Revisiting Packing Algorithm - A Strategy for Optimum Net-to Gross Office Design
doi	https://doi.org/10.52842/conf.caadria.2020.1.405
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 405-414
summary	Net-to-gross efficiency is defined as the ratio of net area to a gross area of a building. Net-to-gross efficiency will determine the quantity of leasable building area. On the other side, the effectiveness of the spatial distribution of a floor plan design must follow the value of net-to-gross efficiency. Therefore in the context of office design, there are two challenges need to be improved: 1) to get an optimum value of efficiency, architects need to assign the amount and size of the office units which can be effectively arranged, and 2) to fulfill high net-to-gross efficiency value that usually set out at minimal 85%. This paper aims to apply the packing algorithm as a strategy to achieve optimum net-to-gross efficiency and generating spatial configuration of office units that fit with the result. Our study experimented with series of models and simulations consisting of three stages that start from finding net-to-gross efficiency, defining office unit profiles based on preferable office space units, and applying the packing algorithm to get an optimum office net-to-gross efficiency. Computational processes using physics engine and optimization solvers have been utilized to generate design layouts that have minimal spatial residues, hence increasing the net-to-gross ratio.
keywords	net-to-gross efficiency; packing algorithm; modular office area; area optimization;
series	CAADRIA
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last changed	2022/06/07 07:54

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