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_200
id	sigradi2021_200
authors	Karabagli, Kaan, Koc, Mustafa, Basu, Prithwish and As, Imdat
year	2021
title	A Machine Learning Approach to Translate Graph Representations into Conceptual Massing Models
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. 191–202
summary	Machine learning (ML) has popular applications in domains involving image, video, text and voice. However, in architecture, image-based ML systems face challenges capturing the complexity of three-dimensional space. In this paper, we leverage a graph-based ML system that can capture the inherent topology of architectural conceptual designs and identify high-performing latent patterns within such designs. In particular, our goal is to translate architectural graph data into three-dimensional massing models. We are building on our prior ML work, where we, a. discovered latent topological features, b. composed building blocks into new designs, c. evaluated their feasibility, and d. explored Generative Adversarial (Neural) Networks (GAN)-generated design variations. We trained the ML system with architectural design data that we gathered from an online architectural design competition platform, translated them into machine-readable graph representations, and identified their essential subgraphs to develop novel compositions. In this paper, we explore how these novel designs (outputted in graph form), can be translated into three-dimensional architectural form. We present an ML approach to turn graph representations into functional volumetric massing models. The ultimate goal of the study is to develop an end-to-end pipeline to generate architectural design - from a graph representation to a fully developed conceptual proxy of a designed product. The research question is promising in automating conceptual design, and we believe the outcome can be relevant to other design disciplines as well.
keywords	Architectural design, machine learning, conceptual design, deep learning, artificial intelligence
series	SIGraDi
email
last changed	2022/05/23 12:10

_id	ijac202119311
id	ijac202119311
authors	Kovacs, Adam Tamas; Micsik, Andras
year	2021
title	BIM quality control based on requirement linked data
source	International Journal of Architectural Computing 2021, Vol. 19 - no. 3, 431–448
summary	This article discusses a BIM Quality Control Ecosystem that is based on Requirement Linked Data in order to create a framework where automated BIM compliance checking methods can be widely used. The meaning of requirements is analyzed in a building project context as a basis for data flow analysis: what are the main types of requirements, how they are handled, and what sources they originate from. A literature review has been conducted to find the present development directions in quality checking, besides a market research on present, already widely used solutions. With the conclusions of these research and modern data management theory, the principles of a holistic approach have been defined for quality checking in the Architecture, Engineering and Construction (AEC) industry. A comparative analysis has been made on current BIM compliance checking solutions according to our review principles. Based on current practice and ongoing research, a state-of-the-art BIM quality control ecosystem is proposed that is open, enables automation, promotes interoperability, and leaves the data governing responsibility at the sources of the requirements. In order to facilitate the flow of requirement and quality data, we propose a model for requirements as Linked Data and provide example for quality checking using Shapes Constraint Language (SHACL). As a result, an opportunity is given for better quality and cheaper BIM design methods to be implemented in the industry.
keywords	Compliance check, quality assurance, quality control, linked data, requirement, BIM
series	journal
email
last changed	2024/04/17 14:29

_id	acadia21_512
id	acadia21_512
authors	Liu, Zidong
year	2021
title	Topological Networks Using a Sequential Method
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. 512-519.
doi	https://doi.org/10.52842/conf.acadia.2021.512
summary	The paper shares preliminary results of a novel sequential method to expand existing topology-based generative design. The approach is applied to building an interactive community design system based on a mobile interface. In the process of building an interactive design system, one of the core problems is to harness the complex topological network formed by user demands. After decades of graph theory research in architecture, a consensus on self-organized complex networks has emerged. However, how to convert input complex topological data into spatial layouts in generative designs is still a difficult problem worth exploring. The paper proposes a way to simplify the problem: in some cases, the spatial network of buildings can be approximated as a collection of sequences based on circulation analysis. In the process of network serialization, the personalized user demands are transformed into activity patterns and further into serial spaces. This network operation gives architects more room to play with their work. Rather than just designing an algorithm that directly translates users’ demands into shape, architects can be more actively involved in organizing spatial networks by setting up a catalogue of activity patterns of the residents, thus contributing to a certain balance of top-down order and bottom-up richness in the project. The research on data serialization lays a solid foundation for the future exploration of Recurrent Neural Network (RNN) applied to generative design.
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
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
doi	https://doi.org/10.52842/conf.caadria.2021.2.111
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_007
id	ascaad2021_007
authors	Alabbasi, Mohammad; Han-Mei Chen, Asterios Agkathidis
year	2021
title	Developing a Design Framework for the 3D Printing Production of Concrete Building Components: A Case Study on Column Optimization for Efficient Housing Solutions in Saudi Arabia
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. 713-726
summary	This paper is examining the development of a design and fabrication framework aiming to increase the efficiency of the construction of concrete building components by introducing 3D concrete printing in the context of Saudi Arabia. In particular, we will present an algorithmic process focusing on the design and fabrication of a typical, mass customised, single-family house, which incorporates parametric modelling, topology optimisation, finite element (FE) analysis and robotic 3D printing techniques. We will test and verify our framework by designing and fabricating a loadbearing concrete column with structural and material properties defined by the Saudi Building Code of Construction. Our findings are highlighting the advantages and challenges of the proposed file-to-factory framework in comparison to the conventional construction methods currently applied in Saudi Arabia, or other similar sociopolitical contexts. By comparing the material usage in both conventional and optimised columns, the results have shown that material consumption has been reduced by 25%, the required labour in the construction site has been mitigated by 28 and the duration time has been reduced by 80% without the need for formwork.
series	ASCAAD
email
last changed	2021/08/09 13:11

_id	ascaad2021_021
id	ascaad2021_021
authors	Albassel, Mohamed; Mustafa Waly
year	2021
title	Applying Machine Learning to Enhance the Implementation of Egyptian Fire and Life Safety Code in Mega Projects
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. 7-22
summary	Machine Learning has become a significant research area in architecture; it can be used to retrieve valuable information for available data used to predict future instances. the purpose of this research was to develop an automated workflow to enhance the implementation of The Egyptian fire & life safety (FLS) code in mega projects and reduce the time wasted on the traditional process of rooms’ uses, occupant load, and egress capacity calculations to increase productivity by applying Supervised Machine Learning based on classification techniques through data mining and building datasets from previous projects, and explore the methods of preparation and analyzing data (text cleanup- tokenization- filtering- stemming-labeling). Then, provide an algorithm for classification rules using C# and python in integration with BIM tools such as Revit-Dynamo to calculate cumulative occupant load based on factors which are mentioned in the Egyptian FLS code, determine classification and uses of rooms to validate all data related to FLS. Moreover, calculating the egress capacity of means of egress for not only exit doors but also exit stairs. In addition, the research is to identify a clear understanding about ML and BIM through project case studies and how to build a model with the needed accuracy.
series	ASCAAD
email
last changed	2021/08/09 13:11

_id	sigradi2021_283
id	sigradi2021_283
authors	Alexandrino, Joao Victor Mota, Amorim, Leonardo Edson, Muniz, Vinícius Fernandes and Leite, Raquel Magalhaes
year	2021
title	Architecture and Context: A Data-based Approach to Optimize Climate Performance of Built Facades
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. 1139–1150
summary	The present research stems from a critical reflection about the environmental adaptability of existing building envelopes. The main goal is to explore how to balance environmental optimization with contextual constraints, using modularity, flexibility and mass customization as guiding principles. An application study was carried out with the development of a second skin proposal aligned with the use and context of the building under study. For this purpose, simulations that assess environmental conditions were developed within a visual programming tool, not only feeding the design process with essential information, but also providing a flexible creative process. Results show that such simulations allow the designer to interpret these studies more accurately, reducing the iterative guesswork, since in this workflow it is possible to transform these outputs into proposition parameters for new designs or interventions.
keywords	Data-Driven Analysis, Optimization, Parametric Facade Design, Thermal performance, High-low architecture, Mass Customization, Second Skin
series	SIGraDi
email
last changed	2022/05/23 12:11

_id	ecaade2021_203
id	ecaade2021_203
authors	Arora, Hardik, Bielski, Jessica, Eisenstadt, Viktor, Langenhan, Christoph, Ziegler, Christoph, Althoff, Klaus-Dieter and Dengel, Andreas
year	2021
title	Consistency Checker - An automatic constraint-based evaluator for housing spatial configurations
source	Stojakovic, V and Tepavcevic, B (eds.), Towards a new, configurable architecture - Proceedings of the 39th eCAADe Conference - Volume 2, University of Novi Sad, Novi Sad, Serbia, 8-10 September 2021, pp. 351-358
doi	https://doi.org/10.52842/conf.ecaade.2021.2.351
summary	The gradual rise of artificial intelligence (AI) and its increasing visibility among many research disciplines affected Computer-Aided Architectural Design (CAAD). Architectural deep learning (DL) approaches are being developed and published on a regular basis, such as retrieval (Sharma et al. 2017) or design style manipulation (Newton 2019; Silvestre et al. 2016). However, there seems to be no method to evaluate highly constrained spatial configurations for specific architectural domains (such as housing or office buildings) based on basic architectural principles and everyday practices. This paper introduces an automatic constraint-based consistency checker to evaluate the coherency of semantic spatial configurations of housing construction using a small set of design principles to evaluate our DL approaches. The consistency checker informs about the overall performance of a spatial configuration followed by whether it is open/closed and the constraints it didn't satisfy. This paper deals with the relation of spaces processed as mathematically formalized graphs contrary to existing model checking software like Solibri.
keywords	model checking, building information modeling, deep learning, data quality
series	eCAADe
email
last changed	2022/06/07 07:54

_id	caadria2021_088
id	caadria2021_088
authors	Batalle Garcia, Anna, Cebeci, Irem Yagmur, Vargas Calvo, Roberto and Gordon, Matthew
year	2021
title	Material (data) Intelligence - Towards a Circular Building Environment
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. 361-370
doi	https://doi.org/10.52842/conf.caadria.2021.1.361
summary	The integration of repurposed material in new construction products generates resiliency strategies that diminish the dependency on raw resources and reduce the CO2 emissions produced by their extraction, transportation, and manufacturing. This research emphasizes the need to expand preliminary data collation from pre-demolition sites to inform early design decisions. Material (data) Intelligence investigates how the merging of artificial intelligence and data analysis could have a crucial impact on achieving widespread material reuse. The first step consists of automating the process of detecting materials and construction elements from pre-demolition sites through drone photography and computer vision. The second part of the research links the resulting database with a computational design tool that can be integrated into construction software. This paper strengthens the potential of circular material flows in a digital paradigm and exposes the capability for constructing big data sets of reusable materials, digitally available, for sharing and organizing material harvesting.
keywords	computer vision; material database; automation; reclaimed material; digitalization
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	ecaade2021_279
id	ecaade2021_279
authors	Coraglia, Ugo Maria, Zhu, Zhelun, Fioravanti, Antonio, Simeone, Davide and Cursi, Stefano
year	2021
title	A new Relation Matrix as a Fruitful Meta-Design Tool - How to overcome typological limits
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. 295-302
doi	https://doi.org/10.52842/conf.ecaade.2021.1.295
summary	The use of meta-design tools to support the early stages of the design process is widely proven in literature. Among these tools, the adjacency matrix and the bubble diagram provided the various professionals involved - not only in the AEC sector - with some useful information mainly regarding the connection types between spaces and the sizing of their dimensions. With the evolution of design and the change of architectural aims (e.g. sustainability, refurbishment), it is not fruitful, especially related to complex buildings (e.g. hospital, airport), to manage spaces and their connections through the traditional Adjacency Matrix and its dual (Bubble Diagram). These tools, used as they were originally designed, do not consider other characteristics but basic topological ones and are still linked to 2D geometry. For this reason, this research aims to increase the unexplored design potential of these tools considering huge advances in building object representation and links with knowledge. The first research steps led to a 3D analysis capable of providing knowledge on the connections and adjacencies between spaces and its environments located on different floors. Therefore, we decided to define further goals, breaking limits of the "adjacency" concept for a more extendable and general concept of "relation" between spaces and environments.
keywords	Relation Matrix; Meta-design; Architectural design theory; Tool
series	eCAADe
email
last changed	2022/06/07 07:56

_id	ecaade2021_273
id	ecaade2021_273
authors	Dania, Panagiota, Theodoropoulou, Helena G., Karagianni, Anna, Geropanta, Vasiliki and Parthenios, Panagiotis
year	2021
title	Enhancing User Experience through Interaction Design - Rethinking the municipal agora of Chania through AR narratives
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. 263-272
doi	https://doi.org/10.52842/conf.ecaade.2021.2.263
summary	This paper examines the relationship between designing interactive experiences based on new technologies and the process of architectural narration. It highlights the idea of rethinking a building with historical, architectural and functional value, as an experience and a journey. Referring to the historic building of the Municipal Market of Chania, Greece and using the conceptual idea of designing through narratives, it delineates the process of integrating new technologies into the process of designing a spatial and temporal experience. Exploiting Augmented Reality, we design an application implementing a digital layer with architectural and historical content, that is integrated into reality, improving the on-site visit, providing enhanced understanding of the building and introducing experiential visitor-building interaction. The application is available through mobile devices and the proposed system is evaluated by a group of users showing the positive effects of the use of interactive technologies in redesigning the experience of a space.
keywords	Mobile AR; cultural dissemination; architectural narration; interactive spatial experiences; interactive visualization
series	eCAADe
email
last changed	2022/06/07 07:55

_id	ijac202119102
id	ijac202119102
authors	Doe, Robert Melvin
year	2021
title	An open, integrated modular format: For flexible and intelligible architecture, engineering and construction design and production
source	International Journal of Architectural Computing 2021, Vol. 19 - no. 1, 23–36
summary	The architecture, engineering and construction sector is fragmented, and its computer-aided design systems suffer data loss and errors in workflow between design and realisation. An open source, integrated, modular format is proposed to address the technological nature of these problems. Accordingly, this research updates the notion of the modular format as a more flexible and intelligible computational design method by leveraging knowledge from the computer science and manufacturing sectors where the design and realisation process is intentional and explicit. The research design of this article comprises a theoretical approach combined with an empirical case study. Principles of modularity are extracted from the computer science and manufacturing sectors to assist with a better definition of architecture, engineering and construction computer-aided design processes that use materials and resources more efficiently and sustainably. The methodology of the modular format contributes to the emerging concept of a building lifecycle management system for the architecture, engineering and construction sector.
keywords	Modular format, open source, integrated, computational design, building lifecycle management
series	journal
email
last changed	2021/06/03 23:29

_id	caadria2021_376
id	caadria2021_376
authors	Dounas, Theodoros, Jabi, Wassim and Lombardi, Davide
year	2021
title	Topology Generated Non-Fungible Tokens - Blockchain as infrastructure for a circular economy in architectural design
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. 151-160
doi	https://doi.org/10.52842/conf.caadria.2021.2.151
summary	The paper presents a new digital infrastructure layer for buildings and architectural assets. The infrastructure layer consists of a combination of topology graphs secured on a decentralised ledger. The topology graphs organise non-fungible digital tokens which each represent and correspond to building components, and in the root of the graph to the building itself.The paper presents background research in the relationship of building representation in the form of graphs with topology, of both manifold and non manifold nature. In parallel we present and analyse the relationship between digital representation and physical manifestation of a building, and back again. Within the digital representations the paper analyses the securing and saving of information on decentralised ledger technologies (such as blockchain). We then present a simple sample of generating and registering a non-manifold topology graph on the Ethereum blockchain as an EC721 token, i.e. a digital object that is unique, all through the use of dynamo and python scripting connected with a smart contract on the Ethereum blockchain. Ownership of this token can then be transferred on the blockchain smart contracts. The paper concludes with a discussion of the possibilities that this integration brings in terms of material passports and a circular economy and smart contracts as an infrastructure for whole-lifecycle BIM and digitally encapsulates of value in architectural designPlease write your abstract here by clicking this paragraph.
keywords	Blockchain; Tokenisation; Topology; Circular Economy; decentralisation
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	sigradi2021_20
id	sigradi2021_20
authors	Dounas, Theodoros, Jabi, Wassim and Lombardi, Davide
year	2021
title	Non-Fungible Building Components: Using Smart Contracts for a Circular Economy in the Built Environment
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. 1189–1198
summary	The presented research study tackles the topic of economic and material sustainable development in the built environment and construction industry by introducing and applying the concept and the potential of Non-Fungible Tokens (NFTs) on blockchain within the early stages of the design process via the interface of common design software. We present a digital infrastructure layer for architectural assets and building components that can integrate with AEC supply chains, enabling a more effective and articulated development of circular economies. The infrastructure layer consists of a combination of topology graphs secured with a blockchain. The paper concludes with a discussion about the possibilities of material passports as well as circular economy and smart contracts as an infrastructure for whole lifecycle BIM and digital encapsulation of value in architectural design.
keywords	Non-fungible tokens, Blockchain, Supply Chain, Building Representation, Circular Economy
series	SIGraDi
email
last changed	2022/05/23 12:11

_id	ecaade2021_254
id	ecaade2021_254
authors	Eisenstadt, Viktor, Arora, Hardik, Ziegler, Christoph, Bielski, Jessica, Langenhan, Christoph, Althoff, Klaus-Dieter and Dengel, Andreas
year	2021
title	Comparative Evaluation of Tensor-based Data Representations for Deep Learning Methods in Architecture
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. 45-54
doi	https://doi.org/10.52842/conf.ecaade.2021.1.045
summary	This paper presents an extended evaluation of tensor-based representations of graph-based architectural room configurations. This experiment is a continuation of examination of recognition of semantic architectural features by contemporary standard deep learning methods. The main aim of this evaluation is to investigate how the deep learning models trained using the relation tensors as data representation means perform on data not available in the training dataset. Using a straightforward classification task, stepwise modifications of the original training dataset and manually created spatial configurations were fed into the models to measure their prediction quality. We hypothesized that the modifications that influence the class label will not decrease this quality, however, this was not confirmed and most likely the latent non-class defining features make up the class for the model. Under specific circumstances, the prediction quality still remained high for the winning relation tensor type.
keywords	Deep Learning; Spatial Configuration; Semantic Building Fingerprint
series	eCAADe
email
last changed	2022/06/07 07:55

_id	caadria2021_086
id	caadria2021_086
authors	Eisenstadt, Viktor, Arora, Hardik, Ziegler, Christoph, Bielski, Jessica, Langenhan, Christoph, Althoff, Klaus-Dieter and Dengel, Andreas
year	2021
title	Exploring optimal ways to represent topological and spatial features of building designs in deep learning methods and applications for architecture
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. 191-200
doi	https://doi.org/10.52842/conf.caadria.2021.1.191
summary	The main aim of this research is to harness deep learning techniques to support architectural design problems in early design phases, for example, to enable auto-completion of unfinished designs. For this purpose, we investigate the possibilities offered by established deep learning libraries such as TensorFlow. In this paper, we address a core challenge that arises, namely the transformation of semantic building information into a tensor format that can be processed by the libraries. Specifically, we address the representation of information about room types of a building and type of connection between the respective rooms. We develop and discuss five formats. Results of an initial evaluation based on a classification task show that all formats are suitable for training deep learning networks. However, a clear winner could be determined as well, for which a maximum value of 98% for validation accuracy could be achieved.
keywords	deep learning; spatial configuration; data representation; semantic building fingerprint
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	caadria2021_137
id	caadria2021_137
authors	Fattahi Tabasi, Saba, Alaghmandan, Matin and Rafizadeh, Hamid Reza
year	2021
title	Simultaneous effect of form modifications and topology of the bracing system on the structural performance of timber high rise building - Introducing an innovative approach using parametric design
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. 421-430
doi	https://doi.org/10.52842/conf.caadria.2021.1.421
summary	Topology optimization is a tool that minimizes the material consumption in a structure, while at the same time provides us design alternatives integrating architectural and structural engineering concepts. However, topology optimization is a structural engineering subject and its known methods are required professional knowledge of engineering to be used. In this article, the mutual effect of form modifications and topology of the bracing system in a 9-story timber exoskeleton high-rise building regarding the governing wind load and seismic load is examined. What differentiates this study from former ones and in fact its main purpose is introducing an innovative approach towards structural topology optimization using parametric design. In this innovative approach, the possibility of moving for each central node of bracing systems in defined ranges independently and the possibility of the existence or absence of each bracing member is provided. This parametric model will enable architects to optimize the topology of the structural elements which are part of their architectural design by themselves. The CMA-ES-algorithm-based optimization is done to minimize both total mass of structure per unit area and the horizontal displacement of the top floor. For modeling, optimizing cross-sections and structural analysis, Grasshopper and its plug-in called Karamba are utilized.
keywords	Topology optimization; Form finding; Parametric design; Timber tall buildings; Exoskeleton structures
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	sigradi2021_345
id	sigradi2021_345
authors	Felipe, Bárbara L. and Nome, Carlos
year	2021
title	Digitally Prefabricated Houses: A Comparative Analysis of Executed Projects
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. 967–980
summary	In Brazil, the application of wood in contemporary constructions is concentrated in the south and southeast. However, the entire country has area for cultivation and forest management, which is favorable for expansion in such applications. Wood is capable of absorbing CO2 and consumes little energy in production and manufacturing. During the COVID-19 pandemic, the deficiencies of the building typologies became evident. This research aims to analyze digitally executed prefabricated houses such as Instant House (1), Digitally Fabricated House (2) by Sass, and WikiHouse (3) by Parvin; under the categories of Cardoso (2016): modulation, reversibility, and flexibility. The deductive method was used to investigate assumptions among the three case studies; and grounded in scientific literature to analyze and collect data. In general, the solutions studied enabled customizable systems allied to wood panels, modules, and fittings as generators of architectural form.
keywords	casa pré fabricadas digitalmente, fabricaçao digital, design paramétrico, arquitetura paramétrica
series	SIGraDi
email
last changed	2022/05/23 12:11

_id	caadria2021_113
id	caadria2021_113
authors	Fink, Theresa, Vuckovic, Milena and Petkova, Asya
year	2021
title	KPI-Driven Parametric Design of Urban Systems
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. 579-588
doi	https://doi.org/10.52842/conf.caadria.2021.2.579
summary	We present a framework for data-driven algorithmic generation and post-evaluation of alternative urban developments. These urban developments are framed by a strategic placement of diverse urban typologies whose spatial configurations follow design recommendations outlined in existing building and zoning regulations. By using specific rule-based generative algorithms, different spatial arrangements of these urban typologies, forming building blocks, are derived and visualized, given the aforementioned spatial, legal, and functional regulations. Once the envisioned urban configurations are generated, these are evaluated based on a number of aspects pertaining to spatial, economic, and thermal (environmental) dimensions, which are understood as the key performance indicators (KPIs) selected for informed ranking and evaluation. To facilitate the analysis and data-driven ranking of derived numeric KPIs, we deployed a diverse set of analytical techniques (e.g., conditional selection, regression models) enriched with visual interactive mechanisms, otherwise known as the Visual Analytics (VA) approach. The proposed approach has been tested on a case study district in the city of Vienna, Austria, offering real-world design solutions and assessments.
keywords	Urban design evaluation; parametric modelling; urban simulation; environmental performance; visual analytics
series	CAADRIA
email
last changed	2022/06/07 07:50

_id	ijac202119205
id	ijac202119205
authors	Fukuda, Tomohiro; Marcos Novak, Hiroyuki Fujii, Yoann Pencreach
year	2021
title	Virtual reality rendering methods for training deep learning, analysing landscapes, and preventing virtual reality sickness
source	International Journal of Architectural Computing 2021, Vol. 19 - no. 2, 190–207
summary	Virtual reality (VR) has been proposed for various purposes such as design studies, presentation, simulation and communication in the field of computer-aided architectural design. This paper explores new roles for VR; in particular, we propose rendering methods that consist of post-processing rendering, segmentation rendering and shadow-casting rendering for more-versatile approaches in the use of data. We focus on the creation of a dataset of annotated images, composed of paired foreground-background and semantic-relevant images, in addition to traditional immersive rendering for training deep learning neural networks and analysing landscapes. We also develop a camera velocity rendering method using a customised segmentation rendering technique that calculates the linear and angular velocities of the virtual camera within the VR space at each frame and overlays a colour on the screen according to the velocity value. Using this velocity information, developers of VR applications can improve the animation path within the VR space and prevent VR sickness. We successfully applied the developed methods to urban design and a design project for a building complex. In conclusion, the proposed method was evaluated to be both feasible and effective.
keywords	Virtual reality, rendering, shader, deep learning, landscape analytics, virtual reality sickness, Fourth Industrial Revolution, computer-aided architectural design
series	journal
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last changed	2024/04/17 14:29

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