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	ecaade2022_367
id	ecaade2022_367
authors	Doumpioti, Christina and Huang, Jeffrey
year	2022
title	Field Condition - Environmental sensibility of spatial configurations with the use of machine intelligence
doi	https://doi.org/10.52842/conf.ecaade.2022.2.067
source	Pak, B, Wurzer, G and Stouffs, R (eds.), Co-creating the Future: Inclusion in and through Design - Proceedings of the 40th Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2022) - Volume 2, Ghent, 13-16 September 2022, pp. 67–74
summary	Within computational environmental design (CED), different Machine Learning (ML) models are gaining ground. They aim for time efficiency by automating simulation and speeding up environmental performance feedback. This study suggests an approach that enhances not the optimization but the generative aspect of environmentally driven ML processes in architectural design. We follow Stan Allen's (2009) idea of 'field conditions' as a bottom-up phenomenon according to which form and space emerge from local invisible and dynamic connections. By employing parametric modeling, environmental analysis data, and conditional Generative Adversarial Networks [cGAN] we introduce a generative approach in design that reverses the typical design process of going from formal interpretation to analysis and encourages the emergence of spatial configurations with embedded environmental intelligence. We call it Intensive-driven Environmental Design Computation [IEDC], and we employ it in a case study on a residential building typology encountered in the Mediterranean. The paper describes the process, emphasizing dataset preparation as the stage where the logic of field conditions is established. The proposed research differentiates from cGAN models that offer automatic environmental performance predictions to one that spatial predictions stem from dynamic fields.
keywords	Field Architecture, Environmental Design, Generative Design, Machine Learning, Residential Typologies
series	eCAADe
email
last changed	2024/04/22 07:10

_id	ascaad2022_087
id	ascaad2022_087
authors	Mallasi, Zaki
year	2022
title	A Pixels-Based Design Approach for Parametric Thinking in Patterning Dynamic Facades
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. 654-673
summary	In today’s Architectural design process, there has been considerable advancements in design computation tools that empowers designer to explore and configure the building façades schemes. However, one could formally argue that some processes are prescribed, lacks automation and are only for the purpose of visualizing the aesthetic design concepts. As a result, these design concept explorations are driven manually to exhibit variations between schemes. To overcome such limitations, the development presented here describes a proactive approach to incorporate parametric design thinking process and Building Information Modeling (BIM). This paper reports on an ongoing development in computational design and its potential application in exploring an interactive façade pattern. The objective is to present the developed approach for exploring façade patterns that responds parametrically to design-performance attractors. Examples of these attractors are solar exposure, interior privacy importance, and aesthetics. It introduces a paradigm-shift in the development of design tools and theory of parameterization in architecture. This work utilizes programming script to manipulate the logic behind placement of faced panels. The placement and sizes for the building facade 3D parametric panels react to variety of Analytical Image Data (AID) as a source for the design-performance data (e.g.: solar exposure, interior privacy importance, and aesthetics). Accordingly, this research developed the PatternGen(c) add-on in Autodesk ® Revit that utilizes a merge (or an overlay) of AID images as a source to dynamically pattern the building façade and generate the facade panels arrangement rules panels on the building exterior. This work concludes by a project case study assessment, that the methodology of applying AID would be an effective dynamic approach to patterning façades. A case-study design project is presented to show the use of the AID pixel-gradient range from Red, Green and Blue as information source value. In light of the general objectives in this study, this work highlights how future designers may shift to a hybrid design process.
series	ASCAAD
email
last changed	2024/02/16 13:29

_id	ecaade2022_47
id	ecaade2022_47
authors	Marsillo, Laura, Suntorachai, Nawapan, Karthikeyan, Keshava Narayan, Voinova, Nataliya, Khairallah, Lea and Chronis, Angelos
year	2022
title	Context Decoder - Measuring urban quality through artificial intelligence
doi	https://doi.org/10.52842/conf.ecaade.2022.2.237
source	Pak, B, Wurzer, G and Stouffs, R (eds.), Co-creating the Future: Inclusion in and through Design - Proceedings of the 40th Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2022) - Volume 2, Ghent, 13-16 September 2022, pp. 237–246
summary	Understanding the quality of places during the early design process can improve design decision making and increase not only the chance of effective site development for the place and surroundings but also provide foresight to the mental, physical and environmental well-being of the future occupants. A context can be described differently depending on the designer's studies. However, in order to view the place holistically, various layers should be considered for a cross-disciplinary correlation. This paper proposes a prototypical tool to evaluate the quality of places using machine learning to help cluster and visualise design metrics according to the features provided. By selecting a location in a city, it offers other site contexts with similar characteristics and a similar level of complexity in relation to the surroundings. The tool was initially developed for Naples (Italy) as a case study city and incorporates key indicators related to connectivity of amenities, walkability, urban density, population density, outdoor thermal comfort, popular rate review and sentiment analysis from social media. With current open-source data, these indicators such as OpenStreetMap or social media sentiment can be collected with embedded geotags. These site-specific multilayers were evaluated under the metrics of 3 ranges i.e 400, 800 and 1,200-metre walking distance. This paper demonstrates the potential of using machine learning integrated with computational design tools to visualise the otherwise invisible data for users to interpret any context comprehensively in a holistic approach. Even though this tool is made for Naples, this tool can be extended to other cities across the world. As a result, the tool assists users in understanding not only site-specific location but also draws lines to other neighbourhoods within the city with a similar phenomenon of correlation between key performance indicators.
keywords	Computational Design, Urban Analysis, Machine Learning, Computer Vision, Sentiment Analysis
series	eCAADe
email
last changed	2024/04/22 07:10

_id	sigradi2022_99
id	sigradi2022_99
authors	Schmidlin, Flavio; Tavares da Silva, Felipe
year	2022
title	Investigation of indoor daylight performance of the two-sided roof monitor system solution space
source	Herrera, PC, Dreifuss-Serrano, C, Gómez, P, Arris-Calderon, LF, Critical Appropriations - Proceedings of the XXVI Conference of the Iberoamerican Society of Digital Graphics (SIGraDi 2022), Universidad Peruana de Ciencias Aplicadas, Lima, 7-11 November 2022 , pp. 237–248
summary	The present study evaluated levels of zenith daylight and the incidence of solar radiation in an indoor environment with two-sided roof monitor system opening using a parametric geometric model, numerical simulations and machine learning techniques. It was used a climatic database from a locality with a hot and humid tropical climate, at low latitude in Brazil. The daylight performance was analyzed using the Useful Daylight Illuminances and the incident solar radiation with annual and daily maximum results. The study included analyzes with the zenith openings oriented to North-South and East-West, considering the photosensitive sensor meshes on the walls and floor. The results presented that the modeling process used can help the architectural design process in its dimension of natural illuminance and incidence of solar radiation in internal environments, showing optimized configurations for the room size and for the zenithal opening geometry.
keywords	Predictive Modeling, Parametric Modeling, Radiation, Zenithal Daylight, Indoor Environment
series	SIGraDi
email
last changed	2023/05/16 16:55

_id	ijac202220104
id	ijac202220104
authors	Wang, Likai
year	2022
title	Workflow for applying optimization-based design exploration to early-stage architectural design – Case study based on EvoMass
source	International Journal of Architectural Computing 2022, Vol. 20 - no. 1, pp. 41–60
summary	The role of optimization-based design exploration in early-stage architectural design has been increasingly recognized and valued. It has been widely considered an effective approach to achieving performance- informed and performance-driven design. Nevertheless, there is little research into how such design ex- ploration can be adapted to various early-stage architectural design tasks. With this motivation, this paper revolves around a computer-aided design workflow for early-stage building massing design optimization and exploration while presenting three workshop case studies to demonstrate how the workflow can be in- tertwined with the design process. The design workflow is based on EvoMass, an integrated building massing design generation and optimization tool in Rhino-Grasshopper. The case study illustrates task-specific applications of the design workflow for synthesizing building design, finding design precedents, and un- derstanding the interrelationship between formal attributes and building performance. The paper concludes by discussing the relevant efficacy of the design workflow for architectural design.
keywords	Performance-based design, design workflow, design exploration, early design stage, parametric design, optimization
series	journal
last changed	2024/04/17 14:29

_id	caadria2022_169
id	caadria2022_169
authors	Xu, Hang and Wang, Tsung-Hsien
year	2022
title	An Integrated Parametric Generation and Computational Workflow to Support Sustainable City Planning
doi	https://doi.org/10.52842/conf.caadria.2022.1.535
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 535-544
summary	To examine how efforts in the built environment can contribute to global climate change mitigation at the urban scale, urban building energy modelling (UBEM) is one of the research areas gaining increasing interest in recent years. However, limited studies systematically illustrate a comprehensive UBEM workflow for most architects and urban planners considering available public datasets, particularly at the early conceptual design phase. In current UBEM studies, major challenges arise from the lack of fine-grained measured urban data and incompatibility between software. To address these challenges and support future sustainable cities and communities, this paper proposed a streamlined computational workflow of UBEM to facilitate sustainable urban design development. Through a case study of Sheffield in the UK, this paper demonstrated an automated and standardised computational workflow that can test the decarbonisation potential in built environments by evaluating energy demand and supply scenarios at an urban scale. This workflow is envisaged to be applicable at various scales of an urban region given an appropriate geographic information system (GIS) dataset.
keywords	Parametric Design Generation, Urban Sustainability, Urban Building Energy Modelling, Building Performance Simulation, Renewable Energy, Decarbonisation, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_264
id	caadria2022_264
authors	Zhang, Garry Hangge, Meng, Leo Lin, Gardner, Nicole, Yu, Daniel and Haeusler, Matthias Hank
year	2022
title	Transit Oriented Development Assistive Interface (TODAI): A Machine Learning Powered Computational Urban Design Tool for TOD
doi	https://doi.org/10.52842/conf.caadria.2022.1.253
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 253-262
summary	Transit-oriented Development(TOD) is widely regarded as a sustainable development paradigm for its sensible space planning and promotion of public transit access. Research in providing decision support tools of TOD may contribute to the Sustainable Development Goals, especially towards sustainable cities and communities (SDG goal 11).While the existing Geographic Information System(GIS) approach may well inform TOD planning, computational design, simulation, and visualisation techniques can further enhance this process. The research aims to provide a data-driven, computational-aided planning support system (PSS) to enhance the TOD decision-making process. The research adopts an action research methodology, which iteratively designs experiments and inquires through situating the research question in real-world practice. A work-in-progress prototype is provided - Transit-Oriented Development Assistive Interface (TODAI), along with an experiment in a newly proposed metro station in Sydney, Australia. TODAI provides real-time visualisation of urban forms and analytical data indicators reflecting key considerations relevant to TOD performance. A regressive machine learning model (XGBoost) is used to make predictions of analytical indicators, promptly producing outcomes that may otherwise require a costly computational operation.
keywords	TransUrban Planning, Transit-Oriented Development, Planning Support System, Machine Learning, SDG 11it-Oriented Development, Urban Planning, Machine Learning, Computational Design, SDG11, Sustainable Cities and Communities
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_54
id	caadria2022_54
authors	Zhuang, Dian and Shi, Xing
year	2022
title	Building Information Modelling based Transparent Envelope Optimization Considering Environmental Quality, Energy and Cost
doi	https://doi.org/10.52842/conf.caadria.2022.2.537
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 537-546
summary	The balance of energy consumption, indoor environmental satisfaction and cost is a continuing challenge in the field of building energy efficiency research. Building transparent envelope play a key role in building energy-saving design. While in existing BIM system, the separation of component family and local supply chain hinders the integrated performance evaluation and design. This paper proposes a general sustainable performance optimization model for transparent envelope design from the product perspective. A performance data integrated BIM technique framework, linking BIM with multi-dimension performance data stored in external database, is introduced as the foundation of local supply chain based optimization process. A multi-objective optimization model for window components is constructed for the early design stage. Three comprehensive design targets in the engineering practice, energy consumption, life cycle cost and IEQ are evaluated and optimized, representing the concern from government, developer and occupant, respectively. Autodesk Revit as the technique platform, its internal material library and adaptive component system are directly integrated for model control and feedback. An optimization tool is developed as an individual plug-in for user interaction and performance visualization. As a case study, the multi-objective optimization process is applied to design a school building in China.
keywords	BIM, multi-objective optimization, transparent envelope, sustainable performance, SDG 3, SDG 7, SDG 11, SDG 12
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	sigradi2022_42
id	sigradi2022_42
authors	ªahin, Murat; Agirbas, Asli; Kaynar, Hilal
year	2022
title	The Use of Parametric Mapping as an Analysis Method in Contextual Design Studio
source	Herrera, PC, Dreifuss-Serrano, C, Gómez, P, Arris-Calderon, LF, Critical Appropriations - Proceedings of the XXVI Conference of the Iberoamerican Society of Digital Graphics (SIGraDi 2022), Universidad Peruana de Ciencias Aplicadas, Lima, 7-11 November 2022 , pp. 1007–1016
summary	This paper is discussed an experimental study carried out in the undergraduate Contextual Design Studio (CDS). The studio comprises four stages: Site Analysis Phase, Conceptual Design Studies, Design Development Phase, and Final Presentation. The site analysis stage lasts for about four weeks,10 hours a week in the studio. Particular importance is given to this part of the project so that students have a chance to gain different perspectives on multiple meanings of context and, more specifically, the historical, social and physical context of the the neighborhood. Besides conventional mapping and representation techniques and tools, some new design tools have been introduced in the studio, one of which was this experimental study in question. The study aims at the integration of the Parametric Mapping techniques, at a basic level, into the site analysis process in the contextual design studio to provide an entry point to thinking through the tool used for the students. In this term, the method of abstracting site features through Parametric Mapping was used in the site analysis process and the effect of this form-oriented data on the concepts of the projects was interpreted. NudiBranch, an add-on to the Grasshopper program, was used in the Parametric Mapping workshop. Students' works were discussed briefly with the help of some representative instances.
keywords	Hybrid Education, Parametric mapping, Contextual design studio, Architectural design studio, Architectural education
series	SIGraDi
email
last changed	2023/05/16 16:57

_id	ecaade2022_234
id	ecaade2022_234
authors	Afsar, Secil, Estévez, Alberto T., Abdallah, Yomna K., Turhan, Gozde Damla, Ozel, Berfin and Doyuran, Aslihan
year	2022
title	Activating Co-Creation Methodologies of 3D Printing with Biocomposites Developed from Local Organic Wastes
doi	https://doi.org/10.52842/conf.ecaade.2022.1.215
source	Pak, B, Wurzer, G and Stouffs, R (eds.), Co-creating the Future: Inclusion in and through Design - Proceedings of the 40th Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2022) - Volume 1, Ghent, 13-16 September 2022, pp. 215–224
summary	Compared to the take-make-waste-oriented linear economy model, the circular model has been studied since the 1980s. Due to consumption-oriented lifestyles along with having a tendency of considering waste materials as trash, studies on sustainable materials management (SMM) have remained at a theoretical level or created temporary and limited impacts. To ensure SMM supports The European Green Deal, there is a necessity of developing top-down and bottom-up strategies simultaneously, which can be metaphorized as digging a tunnel from two different directions to meet in the middle of a mountain. In parallel with the New European Bauhaus concept, this research aims to create a case study for boosting bottom-up and data-driven methodologies to produce short-loop products made of bio-based biocomposite materials from local food & organic wastes. The Architecture departments of two universities from different countries collaborated to practice these design democratization methodologies using data transfer paths. The 3D printable models, firmware code, and detailed explanation of working with a customized 3D printer paste extruder were shared using online tools. Accordingly, the bio-based biocomposite recipe from eggshell, xanthan gum, and citric acid, which can be provided from local shops, food & organic wastes, was investigated concurrently to enhance its printability feature for generating interior design elements such as a vase or vertical gardening unit. While sharing each step from open-source platforms with adding snapshots and videos allows further development between two universities, it also makes room for other researchers/makers/designers to replicate the process/product. By combining modern manufacturing and traditional crafting methods with materials produced with DIY techniques from local resources, and using global data transfer platforms to transfer data instead of products themselves, this research seeks to unlock the value of co-creative design practices for SMM.
keywords	Sustainable Materials Management, Co-Creation, Food Waste, 3D Printing, New European Bauhaus
series	eCAADe
email
last changed	2024/04/22 07:10

_id	sigradi2022_243
id	sigradi2022_243
authors	Banda, Pablo; Carrasco-Pérez, Patricio; García-Alvarado, Rodrigo; Munoz-Sanguinetti, Claudia
year	2022
title	Planning & Design Platform of Buildings By Robotic Additive Manufacturing for Construction.
source	Herrera, PC, Dreifuss-Serrano, C, Gómez, P, Arris-Calderon, LF, Critical Appropriations - Proceedings of the XXVI Conference of the Iberoamerican Society of Digital Graphics (SIGraDi 2022), Universidad Peruana de Ciencias Aplicadas, Lima, 7-11 November 2022 , pp. 421–430
summary	The following paper describes and comments a construction planning platform for the Additive Manufacturing of wall modules, as a set of design and planning actions that interwove robotic, material capacities and spatial characteristics. Goal here is to take semi-conventional strategy and augment the algorithmic process for design and knowledge acquisition regarding design oriented to 3D Printing Construction.
keywords	Additive Manufacturing for Construction, 3D Printing, Digital Fabrication, Parametric Design
series	SIGraDi
email
last changed	2023/05/16 16:56

_id	ecaade2022_285
id	ecaade2022_285
authors	Brasil, Alexander and Martinez, Andressa
year	2022
title	Potential for Social Housing Mass Customization in Brazil through the Integration between BIM and Algorithmic-Parametric Modeling
doi	https://doi.org/10.52842/conf.ecaade.2022.2.347
source	Pak, B, Wurzer, G and Stouffs, R (eds.), Co-creating the Future: Inclusion in and through Design - Proceedings of the 40th Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2022) - Volume 2, Ghent, 13-16 September 2022, pp. 347–356
summary	This paper presents a design system for low-cost production of mass customized housing units, in the context of the city of Teresina, in Piaui State, Brazil. The platform stands for the integration between Building Information Modeling (BIM) and algorithmic parametric modeling systems. The research aims to verify the potential of this integration to enable the mass customization of social housing during the design process through the automation of design solutions and real-time visualization of construction data, such as building schedule and estimation of the final cost. The results demonstrated that real-time manipulation and visualization of data related to construction, using specific algorithmic- parametric routines, is capable of aiding designers in developing a solution that matches specific demands with cost and scheduling estimation control in a short period of time.
keywords	Housing, Mass customization, Algorithmic-Parametric Modeling, BIM
series	eCAADe
email
last changed	2024/04/22 07:10

_id	sigradi2022_32
id	sigradi2022_32
authors	Brasil, Alexander; Martinez, Andressa
year	2022
title	Social Housing Mass Customization: Description of a system for real-time cost and spatial generation
source	Herrera, PC, Dreifuss-Serrano, C, Gómez, P, Arris-Calderon, LF, Critical Appropriations - Proceedings of the XXVI Conference of the Iberoamerican Society of Digital Graphics (SIGraDi 2022), Universidad Peruana de Ciencias Aplicadas, Lima, 7-11 November 2022 , pp. 53–64
summary	This study explores mass customization as an alternative strategy for social housing provision. The paper aims to demonstrate the implementation of an integrated system based on the connection between Building Information Modeling and algorithmic-parametric modeling technologies, seeking to design variability with real-time cost and time data control of single-family housing units. We developed the study according to five phases: (1) context analysis and design language definition; (2) rule-based design system definition; (3) cost and execution time estimation; (4) computer system based on the specified technologies definition; (5) quantitative evaluation and qualitative evaluation of the system. The experiment demonstrates that with the aid of algorithmic-parametric modeling, building information manipulation and visualization can be responsive enough to meet mass demands.
keywords	Data analytics, Mass customization, Social Housing, BIM, Cost control
series	SIGraDi
email
last changed	2023/05/16 16:55

_id	caadria2022_242
id	caadria2022_242
authors	Cheng, Chung-Chieh, Sheng, Yu-Ting and Wang, Shih-Yuan
year	2022
title	Robotic Fabrication Process of Glued Laminated Bamboo for Material Efficient Construction
doi	https://doi.org/10.52842/conf.caadria.2022.2.213
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 213-222
summary	This paper aims to introduce the development of a new-style glue-laminated bamboo (GLB) board structure and evaluating computational technologies aiming to enhance the performance of fibre materials and a set of digital manufacturing processes. Specifically, this paper develops a method to introduce the concept of topology optimisation into the properties of fibre materials. At the same time, it explains the unique structure optimisation design and manufacturing process (including the design process, digital tools and auxiliary equipment system). To test the design, this paper compares the data obtained via the gravity suspension test of the physical model and the simulation. Through digital manufacturing methods, the project aims to establish structural elements that could improve material efficiency. Furthermore, it may establish a GLB floor structure system in line with the material economy.
keywords	Digital fabrication, Robotic Assembly, Glued Laminate Bamboo, SDG 11, SDG 12, SDG 15
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_522
id	caadria2022_522
authors	Cheng, Sifan, Leung, Carson Ka Shut and van Ameijde, Jeroen
year	2022
title	Evaluating the Accessibility of Amenities toward Walkable Neighourhoods: an Integrated Method for Testing Alternatives in a Generative Urban Design Process
doi	https://doi.org/10.52842/conf.caadria.2022.1.495
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 495-504
summary	Studies have shown that walkable communities reduce traffic-related pollution and the risk of chronic illnesses, promote economic growth and prosperity, and stimulate community participation and the growth of social capital. To assess the walkability of urban areas, various methodologies have been developed around shortest-distance calculations between various points of interest (POIs), yet their outcomes do not guide potential urban design improvements. The absence of appropriate measurements and procedures that may give quantitative and actionable feedback to support design decision-making is one of the primary issues in building walkable neighborhoods. The work presented in this paper revolves around a new workflow, that employed Urbano, a mobility simulation and assessment tool, and integrated it within a generative design process to allowing for the quantitative evaluation on amenity accessibility for several alternative design scenarios for a case study site in Mong Kok, Hong Kong. The results show how this data-driven urban design process benefits from generative techniques to produce solutions with improved contextual connectivity, energy-efficient urban form, and good quality public spaces that contribute to the walkability of neighbourhoods.
keywords	Generative Urban Design, Walkability, Urbano, SDG 3, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_152
id	caadria2022_152
authors	Deshpande, Rutvik, Nisztuk, Maciej, Cheng, Cesar, Subramanian, Ramanathan, Chavan, Tejas, Weijenberg, Camiel and Patel, Sayjel Vijay
year	2022
title	Synthetic Machine Learning for Real-time Architectural Daylighting Prediction
doi	https://doi.org/10.52842/conf.caadria.2022.1.313
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 313-322
summary	"Synthetic Machine Learning‚ offers a revolutionary leap in real-time environmental analysis for conceptual architectural design. By integrating automatic synthetic data generation, artificial neural network (ANN) training and online deployment, Synthetic Machine Learning offers two main advantages over conventional simulation; First, it reduces the analysis time for a reference simulation from minutes to seconds; Second, it is possible to deploy ANN as a web service in an online design environment, which therein increases accessibility, significantly reducing simulation costs and setup time. The application of Synthetic Machine Learning to perform Daylight Autonomy (DA) and Spatial Daylight Autonomy (sDA) studies to maximise building daylighting for a given use, window to wall ratio, and floorplan arrangement is showcased through a preliminary demonstration work. Comparatively the use of algorithmically generated synthetic data versus real-world data is becoming ubiquitous in other disciplines, the advantages of this approach to the building design process are further discussed.
keywords	Daylight Autonomy, machine learning, building energy performance, synthetic data-sets, SDG 7, SDG 11
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	sigradi2022_271
id	sigradi2022_271
authors	Dong, Siyu; Yan, Jingjing; Yang, Shunyi; Cui, Xiangguo
year	2022
title	Light Transmittance Ceramic Design-Computation with Robotics
source	Herrera, PC, Dreifuss-Serrano, C, Gómez, P, Arris-Calderon, LF, Critical Appropriations - Proceedings of the XXVI Conference of the Iberoamerican Society of Digital Graphics (SIGraDi 2022), Universidad Peruana de Ciencias Aplicadas, Lima, 7-11 November 2022 , pp. 515–526
summary	Building envelope design incorporates a range of light-related analyses, often providing an essential feedback loop for shaping an envelope’s performance, geometry, or components. This is true for solar radiation studies of envelopes, calculated irrespective of building material or assembly. Extending our light-related analysis to include diffuse lighting effects on a building interior presents an opportunity to explore the translucency, porosity, and forms of materials. Glazed architectural ceramic components fabricated using adaptive robotic manufacturing provide an opportunity to exploit material dynamics within the design and alleviate fabrication waste from molds, ultimately accelerating the production manufacturing system. In addition to analyzing the solar radiation on the building facade design, lighting effects can be engaged in profoundly different ways depending on the degree of design-production agency. The production process can be extended beyond automatic routines using robotic fabrication with levels of autonomous involvement that allow for alternative form expressions of the dynamic clay material. In addition to negotiating several design criteria, the design research will develop an aesthetic character originating from customized clay materials and robotic manufacturing processes for lighting transmittance architectural ceramics.
keywords	Digital Fabrication, Light Transmittance, Data-Driven Fabrication, Computer Vision
series	SIGraDi
email
last changed	2023/05/16 16:56

_id	sigradi2022_156
id	sigradi2022_156
authors	Dornelas, Wallace; Martinez, Andressa
year	2022
title	Towards a Parametric Variation of Floor Plans: a Preliminary Approach for Vertical Residential Buildings
source	Herrera, PC, Dreifuss-Serrano, C, Gómez, P, Arris-Calderon, LF, Critical Appropriations - Proceedings of the XXVI Conference of the Iberoamerican Society of Digital Graphics (SIGraDi 2022), Universidad Peruana de Ciencias Aplicadas, Lima, 7-11 November 2022 , pp. 151–162
summary	In the context of the housing demands that respond to several family profiles, allied with the potential of the algorithmic approaches to Architecture, this paper aims to describe an exploratory process of possible solutions toward a generative system of housing distribution in vertical multifamily buildings. As a method, this work presents a parametric design process of a multifamily building, simulating a variety of shape solutions for apartment buildings, in a Grasshopper definition. The work also discusses the data transmission between the parametric modeling using Grasshopper in the Rhinoceros interface and the connection of the final design to Graphisoft’s Archicad BIM-based software. As a result, the parametric model allows several design solutions for several building shapes and contexts. For this study, to fully explore the design possibilities, we applied the method in the context of a Brazilian metropolitan city.
keywords	Generative design, Visual algorithmic design, Parametric architecture, Housing
series	SIGraDi
email
last changed	2023/05/16 16:55

_id	caadria2022_145
id	caadria2022_145
authors	Duering, Serjoscha, Fink, Theresa, Chronis, Angelos and Konig, Reinhard
year	2022
title	Environmental Performance Assessment - The Optimisation of High-Rises in Vienna
doi	https://doi.org/10.52842/conf.caadria.2022.1.545
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 545-554
summary	Our cities are facing different kinds of challenges - in parallel to the urban transformation and densification, climate targets and objectives of decision-makers are on the daily agenda of planning. Therefore, the planning of new neighbourhoods and buildings in high-density areas is complex in many ways. It requires intelligent processes that automate specific aspects of planning and thus enable impact-oriented planning in the early phases. The impacts on environment, economy and society have to be considered for a sustainable planning result in order to make responsible decisions. The objective of this paper is to explore pathways towards a framework for the environmental performance assessment and the optimisation of high-rise buildings with a particular focus on processing large amounts of data in order to derive actionable insights. A development area in the urban centre of Vienna serves as case study to exemplify the potential of automated model generation and applying ML algorithm to accelerate simulation time and extend the design space of possible solutions. As a result, the generated designs are screened on the basis of their performance using a Design Space Exploration approach. The potential for optimisation is evaluated in terms of their environmental impact on the immediate environment.
keywords	simulation, prediction and evaluation, machine learning, computational modelling, digital design, high-rises, SGD 11, SDG 13
series	CAADRIA
email
last changed	2022/07/22 07:34

_id	caadria2022_166
id	caadria2022_166
authors	Eisenstadt, Viktor, Bielski, Jessica, Mete, Burak, Langenhan, Christoph, Althoff, Klaus-Dieter and Dengel, Andreas
year	2022
title	Autocompletion of Floor Plans for the Early Design Phase in Architecture: Foundations, Existing Methods, and Research Outlook
doi	https://doi.org/10.52842/conf.caadria.2022.1.323
source	Jeroen van Ameijde, Nicole Gardner, Kyung Hoon Hyun, Dan Luo, Urvi Sheth (eds.), POST-CARBON - Proceedings of the 27th CAADRIA Conference, Sydney, 9-15 April 2022, pp. 323-332
summary	This paper contributes the current research state and possible future developments of AI-based autocompletion of architectural floor plans and shows demand for its establishment in computer-aided architectural design to facilitate decent work, economic growth through accelerating the design process to meet the future workload. Foundations of data representations together with the autocompletion contexts are defined, existing methods described and evaluated in the integrated literature review, and criteria for qualitative and sustainable autocompletion are proposed. Subsequently, we contribute three unique deep learning-based autocompletion methods currently in development for the research project metis-II. They are described in detail from a technical point of view on the backdrop of how they adhere to the proposed criteria for creating our novel AI.
keywords	Artificial Intelligence, Architectural Design, Floor Plan, Autocompletion, SDG 8, SDG 9
series	CAADRIA
email
last changed	2022/07/22 07:34

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