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	cdrf2019_159
id	cdrf2019_159
authors	Hang Zhang and Ye Huang
year	2020
title	Machine Learning Aided 2D-3D Architectural Form Finding at High Resolution
doi	https://doi.org/https://doi.org/10.1007/978-981-33-4400-6_15
source	Proceedings of the 2020 DigitalFUTURES The 2nd International Conference on Computational Design and Robotic Fabrication (CDRF 2020)
summary	In the past few years, more architects and engineers start thinking about the application of machine learning algorithms in the architectural design field such as building facades generation or floor plans generation, etc. However, due to the relatively slow development of 3D machine learning algorithms, 3D architecture form exploration through machine learning is still a difficult issue for architects. As a result, most of these applications are confined to the level of 2D. Based on the state-of-the-art 2D image generation algorithm, also the method of spatial sequence rules, this article proposes a brand-new strategy of encoding, decoding, and form generation between 2D drawings and 3D models, which we name 2D-3D Form Encoding WorkFlow. This method could provide some innovative design possibilities that generate the latent 3D forms between several different architectural styles. Benefited from the 2D network advantages and the image amplification network nested outside the benchmark network, we have significantly expanded the resolution of training results when compared with the existing form-finding algorithm and related achievements in recent years
series	cdrf
email
last changed	2022/09/29 07:51

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

_id	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_435
id	caadria2020_435
authors	Yeow, Michael, Tracy, Kenneth and Yogiaman, Christine
year	2020
title	Immersive Simulations of Acoustics for Building Analysis - An Alternative Application of Unreal Engine as a Design Tool for Acoustic Environments
doi	https://doi.org/10.52842/conf.caadria.2020.1.619
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. 619-628
summary	This paper presents the exploration and analysis of alternative workflows in studying acoustics in architectural models, utilized in the development of the author's thesis project. Acoustic simulation software allows professionals to better understand the effects of different acoustic strategies on the overall aural experience of the space. These results are often presented as quantitative data, and auralisation programs cut back on visual representation for acoustic accuracy. The objective of this investigation is to explore the possibility of utilizing Unreal Engine as an acoustic simulation software that provides both quantitative data and an immersive understanding of the audio-visual experience of a space designed.
keywords	Architectural Acoustics; Immersive Simulation; Unreal Engine
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	caadria2020_012
id	caadria2020_012
authors	Chatzi, Anna-Maria and Wesseler, Lisa-Marie
year	2020
title	OGOS+ - A Tool to Visualize Densification potential
doi	https://doi.org/10.52842/conf.caadria.2020.1.773
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. 773-782
summary	OGOS+ is a GIS data-based tool, which would offer urban planners, architects, and researchers visualisations of potential building mass in the form of 3D models. It compares the height of existing buildings to the maximum permitted height by German zoning law and calculates the potential building mass. To ensure minimum building footprints it only calculates the densification potential on top of existing buildings. It summarises information of the building potential for future utilisation. The goal is an increase of urban density achieved with micro interventions.
keywords	Urban densification; City Information Modeling and GIS; Big Data and Analytics in Architecture
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	ecaade2023_99
id	ecaade2023_99
authors	Dervishaj, Arlind, Fonsati, Arianna, Hernández Vargas, José and Gudmundsson, Kjartan
year	2023
title	Modelling Precast Concrete for a Circular Economy in the Built Environment
doi	https://doi.org/10.52842/conf.ecaade.2023.2.177
source	Dokonal, W, Hirschberg, U and Wurzer, G (eds.), Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) - Volume 2, Graz, 20-22 September 2023, pp. 177–186
summary	In recent years, there has been a growing interest in adopting circular approaches in the built environment, specifically reusing existing buildings or their components in new projects. To achieve this, drawings, laser scanning, photogrammetry and other techniques are used to capture data on buildings and their materials. Although previous studies have explored scan-to-BIM workflows, automation of 2D drawings to 3D models, and machine learning for identifying building components and materials, a significant gap remains in refining this data into the right level of information required for digital twins, to share information and for digital collaboration in designing for reuse. To address this gap, this paper proposes digital guidelines for reusing precast concrete based on the level of information need (LOIN) standard EN 17412-1:2020 and examines several CAD and BIM modelling strategies. These guidelines can be used to prepare digital templates that become digital twins of existing elements, develop information requirements for use cases, and facilitate data integration and sharing for a circular built environment.
keywords	building information modelling (BIM), circular construction, reuse, concrete
series	eCAADe
email
last changed	2023/12/10 10:49

_id	ecaade2020_290
id	ecaade2020_290
authors	Elesawy, Amr Alaaeldin, Signer, Mario, Seshadri, Bharath and Schlueter, Arno
year	2020
title	Aerial Photogrammetry in Remote Locations - A workflow for using 3D point cloud data in building energy modeling
doi	https://doi.org/10.52842/conf.ecaade.2020.1.723
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. 723-732
summary	Building energy modelling (BEM) results are highly affected by the surrounding environment, due to the impact of solar radiation on the site. Hence, modelling the context is a crucial step in the design process. This is challenging when access to the geometrical data of the built and natural environment is unavailable as in remote villages. The acquisition of accurate data through conventional surveying proves to be costly and time consuming, especially in areas with a steep and complex terrain. Photogrammetry using drone-captured aerial images has emerged as an innovative solution to facilitate surveying and modeling. Nevertheless, the workflow of translating the photogrammetry output from data points to surfaces readable by BEM tools proves to be tedious and unclear. This paper presents a streamlined and reproducible approach for constructing accurate building models from photogrammetric data points to use for architectural design and energy analysis in early design stage projects.
keywords	Building Energy Modeling; Photogrammetry; 3D Point Clouds; Low-energy architecture; Multidisciplinary design; Education
series	eCAADe
email
last changed	2022/06/07 07:55

_id	ecaade2020_222
id	ecaade2020_222
authors	Ikeno, Kazunosuke, Fukuda, Tomohiro and Yabuki, Nobuyoshi
year	2020
title	Automatic Generation of Horizontal Building Mask Images by Using a 3D Model with Aerial Photographs for Deep Learning
doi	https://doi.org/10.52842/conf.ecaade.2020.2.271
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. 271-278
summary	Information extracted from aerial photographs is widely used in urban planning and design. An effective method for detecting buildings in aerial photographs is to use deep learning for understanding the current state of a target region. However, the building mask images used to train the deep learning model are manually generated in many cases. To solve this challenge, a method has been proposed for automatically generating mask images by using virtual reality 3D models for deep learning. Because normal virtual models do not have the realism of a photograph, it is difficult to obtain highly accurate detection results in the real world even if the images are used for deep learning training. Therefore, the objective of this research is to propose a method for automatically generating building mask images by using 3D models with textured aerial photographs for deep learning. The model trained on datasets generated by the proposed method could detect buildings in aerial photographs with an accuracy of IoU = 0.622. Work left for the future includes changing the size and type of mask images, training the model, and evaluating the accuracy of the trained model.
keywords	Urban planning and design; Deep learning; Semantic segmentation; Mask image; Training data; Automatic design
series	eCAADe
email
last changed	2022/06/07 07:50

_id	caadria2020_107
id	caadria2020_107
authors	Meng, Leo Lin, Graham, Jeremy and Haeusler, M. Hank
year	2020
title	t-SNE: A Dimensionality Reduction Tool for Design Data Visualisation
doi	https://doi.org/10.52842/conf.caadria.2020.2.629
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. 629-638
summary	One can argue that data is the 'new oil'. Yet more important than the sheer quantity of data is the question, in the context of architecture and design, how data is represented in design, as this is becoming a more relevant question to the architecture profession. We argue that data, in particular n-dimensional, is often hidden even in BIM models. Hence we propose a new way of understanding the space by (1) generate and integrate space analytics data using space syntax method as well as space usage data and (2) visualise the data using t-Distributed Stochastic Neighbour Embedding (t-SNE), an unsupervised learning and dimensionality reduction tool to help intuitively display high dimensions of data. This approach may help to discover the 'hidden layers' of the building information that may be otherwise omitted. This investigation, its proposed hypothesis, methodology, implications, significance and evaluation are presented in the paper.
keywords	Data-Driven Design; t-SNE; Machine Learning; Space Syntax
series	CAADRIA
email
last changed	2022/06/07 07:58

_id	sigradi2020_418
id	sigradi2020_418
authors	Neto, Olavo Avalone; Avalone, Marianne Costa
year	2020
title	CAPTURING THE ENVIRONMENT: using photogrammetry to register the built environment for simulation
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. 418-424
summary	This study tested two forms of data gathering, three different methods of data registration, and two of modeling for the creation of 3D models of heritage landmarks. The applications on elements of three different scales were tested, a Cathedral, a Monument, and an Art Panel. The open-source Meshroom resulted in the best model in measures of mesh detail, reconstruction capability, and mesh refinement, regardless of the data acquisition method. Results may aid researchers and designers in choosing a workflow that suits their needs developing the best model possible, according to the tools they have at their disposal.
keywords	Photogrammetry, Mesh modeling, Reality capture, Cultural heritage, 3D models
series	SIGraDi
email
last changed	2021/07/16 11:49

_id	cdrf2019_103
id	cdrf2019_103
authors	Runjia Tian
year	2020
title	Suggestive Site Planning with Conditional GAN and Urban GIS Data
doi	https://doi.org/https://doi.org/10.1007/978-981-33-4400-6_10
source	Proceedings of the 2020 DigitalFUTURES The 2nd International Conference on Computational Design and Robotic Fabrication (CDRF 2020)
summary	In architecture, landscape architecture, and urban design, site planning refers to the organizational process of site layout. A fundamental step for site planning is the design of building layout across the site. This process is hard to automate due to its multi-modal nature: it takes multiple constraints such as street block shape, orientation, program, density, and plantation. The paper proposes a prototypical and extensive framework to generate building footprints as masterplan references for architects, landscape architects, and urban designers by learning from the existing built environment with Artificial Neural Networks. Pix2PixHD Conditional Generative Adversarial Neural Network is used to learn the mapping from a site boundary geometry represented with a pixelized image to that of an image containing building footprint color-coded to various programs. A dataset containing necessary information is collected from open source GIS (Geographic Information System) portals from the city of Boston, wrangled with geospatial analysis libraries in python, trained with the TensorFlow framework. The result is visualized in Rhinoceros and Grasshopper, for generating site plans interactively.
series	cdrf
email
last changed	2022/09/29 07:51

_id	caadria2020_054
id	caadria2020_054
authors	Shen, Jiaqi, Liu, Chuan, Ren, Yue and Zheng, Hao
year	2020
title	Machine Learning Assisted Urban Filling
doi	https://doi.org/10.52842/conf.caadria.2020.2.679
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. 679-688
summary	When drawing urban scale plans, designers should always define the position and the shape of each building. This process usually costs much time in the early design stage when the condition of a city has not been finally determined. Thus the designers spend a lot of time working forward and backward drawing sketches for different characteristics of cities. Meanwhile, machine learning, as a decision-making tool, has been widely used in many fields. Generative Adversarial Network (GAN) is a model frame in machine learning, specially designed to learn and generate image data. Therefore, this research aims to apply GAN in creating urban design plans, helping designers automatically generate the predicted details of buildings configuration with a given condition of cities. Through the machine learning of image pairs, the result shows the relationship between the site conditions (roads, green lands, and rivers) and the configuration of buildings. This automatic design tool can help release the heavy load of urban designers in the early design stage, quickly providing a preview of design solutions for urban design tasks. The analysis of different machine learning models trained by the data from different cities inspires urban designers with design strategies and features in distinct conditions.
keywords	Artificial Intelligence; Urban Design; Generative Adversarial Networks; Machine Learning
series	CAADRIA
email
last changed	2022/06/07 07:56

_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	acadia20_526
id	acadia20_526
authors	Bruce, Mackenzie; Clune, Gabrielle; Culligan, Ryan; Vansice, Kyle; Attraya, Rahul; McGee, Wes; Yan Ng, Tsz
year	2020
title	FORM{less}
doi	https://doi.org/10.52842/conf.acadia.2020.1.526
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. 526-535
summary	Form{less} focuses on the creation of complex thin-shell concrete forms using robotically thermoformed plastic molds. Typically, similar molds would be created using the vacuum forming process, producing direct replications of the pattern. Creating molds with this process is not only time- and material-intensive but also costly if customization is involved. Thin-shell concrete forms often require a labor-intensive process of manually finishing the open-face surface. The devised process of thermoforming two nested molds allows the concrete to be cast in between, with finished surfaces on both sides. Molds made with polyethylene terephthalate glycol (PETG) allow the formwork to be reused and recycled. The research and fabrication work include the development of heating elements and the creation of the robotic process for forming the PETG. The PETG is manipulated via a robotic arm, with a custom magnetic end effector. The integration of robotics not only enables precision for manufacturing but also allows for replicability with unrestricted threedimensional deformation. The repeatable process allows for rapid prototyping and geometric customization. Design options are then simulated computationally using SuperMatterTools, enabling further design exploration of this process without the need for extensive physical prototyping. This research aims to develop a process that allows for the creation of complex geometries while reducing the amount of material waste used for concrete casting. The novelty of the process created by dynamically forming PETG allows for quick production of formwork that is both customizable and replicable. This method of creating double-sided building components is simulated at various scales of implementation.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	ecaade2020_037
id	ecaade2020_037
authors	Dortheimer, Jonathan, Neuman, Eran and Milo, Tova
year	2020
title	A Novel Crowdsourcing-based Approach for Collaborative Architectural Design
doi	https://doi.org/10.52842/conf.ecaade.2020.2.155
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. 155-164
summary	This paper provides an overview of "Architasker", a large-scale crowdsourcing approach, platform, and method that enables a collaborative professional architectural design process in collaboration with a community of stakeholders. The platform includes communicating complex architectural project requirements; solution space exploration using different micro-tasks like sketching, 2D and 3D CAD; design selection; and design review as an evolutionary process. The architectural crowdsourcing model underlying the platform is contextualized in the state-of-the-art research on creative crowdsourcing methods and is supported by relevant evidence from empirical experiments. Experimental results validate the effectiveness of the method to generate architectural artifacts by harnessing the skills, talents, and experience of architects and the opinions and values of the stakeholders.
keywords	Crowdsourcing; Participatory Design; Human Computation; Creative Crowdsourcing; Co-Design; Collective Intelligence
series	eCAADe
email
last changed	2022/06/07 07:55

_id	caadria2020_423
id	caadria2020_423
authors	Erhan, Halil, Zarei, Maryam, Abuzuraiq, Ahmed M., Haas, Alyssa, Alsalman, Osama and Woodbury, Robert
year	2020
title	FlowUI: Combining Directly-Interactive Design Modeling with Design Analytics
doi	https://doi.org/10.52842/conf.caadria.2020.1.475
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. 475-484
summary	In a systems building experiment, we explored how directly manipulating non-parametric geometries can be used together with a real-time parametric performance analytics for informed design decision-making in the early phases of design. This combination gives rise to a design process where considerations that would traditionally take place in the late phases of design can become part of the early phases. The paper presents FlowUI, a prototype tool for performance-driven design that is developed in a collaboration with our industry partner as part of our design analytics research program. The tool works with and responds to changes in the design modeling environment, processes the design data and presents the results in design (data) analytics interfaces. We discuss the system's design intent and its overall architecture, followed by a set of suggestions on the comparative analysis of design solutions and design reports generation as integral parts of design exploration tasks.
keywords	Non-Parametric Modeling; Performance-Driven Design; Design Analytics; Information Visualization
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	caadria2020_146
id	caadria2020_146
authors	Lertsithichai, Surapong
year	2020
title	Fantastic Facades and How to Build Them
doi	https://doi.org/10.52842/conf.caadria.2020.1.355
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. 355-364
summary	As part of an ongoing investigation in augmented architecture, the exploration of an architectural facade as a crucial element of architecture is a challenging design experiment. We believe that new architectural facades when seamlessly integrated with augmented architecture, enhanced with multiple functionalities, interactivity and performative qualities can extend a building's use beyond its typical function and limited lifespan. Augmented facades or "Fantastic Facades," can be seen as a separate entity from the internal spaces inside the building but at the same time, can also be seen as an integral part of the building as a whole that connects users, spaces, functions and interactivity between inside and outside. An option design studio for 4th year architecture students was offered to conduct this investigation for a duration of one semester. During the process of form generations, students experimented with various 2D and 3D techniques including biomimicry and generative designs, biomechanics or animal movement patterns, leaf stomata patterns, porous bubble patterns, and origami fold patterns. Eventually, five facade designs were carried on towards the final step of incorporating performative interactions and contextual programs to the facade requirements of an existing building or structure in Bangkok.
keywords	Facade Design; Augmented Architecture; Form Generation; Surface System; Performative Interactions
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	ecaade2020_511
id	ecaade2020_511
authors	Maierhofer, Mathias, Ulber, Marie, Mahall, Mona, Serbest, Asli and Menges, Achim
year	2020
title	Designing (for) Change - Towards adaptivity-specific architectural design for situational open Environments
doi	https://doi.org/10.52842/conf.ecaade.2020.2.575
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. 575-584
summary	The introduction of cybernetic principles to the architectural discourse some 50 years ago stimulated a new notion of buildings as dynamic and under-specified systems. Although their traditional conception as static and deterministic objects has remained predominant to this day, concepts for adaptive architecture capable of interacting with their surroundings and occupants have gained renewed attention in recent decades. However, investigations so far have largely concentrated on small-scale applications or individual adaptation strategies. The notion of situational open Environments, as argued in this paper, provides a framework through which adaptivity can be conceived and explored more holistically as well as on an inhabitable scale. Environments reject deterministic design and adaptation solutions and hence call for integrative and interactive design strategies that not only allow for the exploration of particularly adaptable (i.e. underspecified) architectural morphologies, but also for the communication and negotiation during their further development beyond deployment. In respect thereof, this paper discusses the potentials and implications of computational (design) strategies, meaning the agencies of buildings, designers, residents, and surroundings. The presented research originates from the author's involvement in an interdisciplinary research project centered around the development of an adaptive high-rise building that incorporates various adaptation strategies.
keywords	Adaptive Architecture; Architectural Environment; Computational Design; Agent-based Modeling; Architecture Theory; Cybernetics
series	eCAADe
email
last changed	2022/06/07 07:59

_id	ijac202018407
id	ijac202018407
authors	Marcelo Bernal, Victor Okhoya, Tyrone Marshall, Cheney Chen and John Haymaker
year	2020
title	Integrating expertise and parametric analysis for a data-driven decision-making practice
source	International Journal of Architectural Computing vol. 18 - no. 4, 424–440
summary	This study explores the integration of expert design intuition and parametric data analysis. While traditional professional design expertise helps to rapidly frame relevant aspects of the design problem and produce viable solutions, it has limitations in addressing multi-criteria design problems with conflicting objectives. On the other hand, parametric analysis, in combination with data analysis methods, helps to construct and analyze large design spaces of potential design solutions and tradeoffs, within a given frame. We explore a process whereby expert design teams propose a design using their current intuitive and analytical methods. That design is then further optimized using parametric analysis. This study specifically explores the specification of geometric and material properties of building envelopes for two typically conflicting objectives: daylight quality and energy consumption. We compare performance of the design after initial professional design exploration, and after parametric analysis, showing consistently significant performance improvement after the second process. The study explores synergies between intuitive and systematic design approaches, demonstrating how alignment can help expert teams efficiently and significantly improve project performance.
keywords	Performance analysis, parametric analysis, design space, design expertise, data analysis, optimization
series	journal
email
last changed	2021/06/03 23:29

_id	ijac202220109
id	ijac202220109
authors	Ortner, F. Peter; Jing Zhi Tay
year	2022
title	Resilient by design: Informing pandemic-safe building redesign with computational models of resident congestion
source	International Journal of Architectural Computing 2022, Vol. 20 - no. 1, pp. 129–144
summary	This paper describes a computational design-support tool created in response to safe-distancing measures enforced during the COVID-19 pandemic. The tool was developed for a specific use case: understanding congestion in crowded migrant worker dormitories that experienced high rates of COVID-19 transmission in 2020. Building from agent-based and network-based computational simulations, the tool presents a hybrid method for simulating building resident movements based on known or pre-determined schedules and likely itineraries. This hybrid method affords the design tool a novel approach to simultaneous exploration of spatial and temporal design scenarios. The paper demonstrates the use of the tool on an anonymised case study of a high-density migrant worker dormitory, comparing results from a baseline configuration against design variations that modify dormitory physical configuration and schedule. Comparisons between the design scenarios provide evidence for reflections on pandemic-resilient design and operation strategies for dor- mitories. A conclusions section considers the extent to which the model and case study results are applicable to other dense institutional buildings and describes the paper’s contributions to general understanding of configurational and operational aspects of resilience in the built environment.
keywords	Design for resilience, evidence-based design, design support, agent-based model, schedule-based model, network analysis
series	journal
last changed	2024/04/17 14:29

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