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	acadia18_156
id	acadia18_156
authors	Huang, Weixin; Zheng, Hao
year	2018
title	Architectural Drawings Recognition and Generation through Machine Learning
source	ACADIA // 2018: Recalibration. On imprecisionand infidelity. [Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-17729-7] Mexico City, Mexico 18-20 October, 2018, pp. 156-165
doi	https://doi.org/10.52842/conf.acadia.2018.156
summary	With the development of information technology, the ideas of programming and mass calculation were introduced into the design field, resulting in the growth of computer- aided design. With the idea of designing by data, we began to manipulate data directly, and interpret data through design works. Machine Learning as a decision making tool has been widely used in many fields. It can be used to analyze large amounts of data and predict future changes. Generative Adversarial Network (GAN) is a model framework in machine learning. It’s specially designed to learn and generate output data with similar or identical characteristics. Pix2pixHD is a modified version of GAN that learns image data in pairs and generates new images based on the input. The author applied pix2pixHD in recognizing and generating architectural drawings, marking rooms with different colors and then generating apartment plans through two convolutional neural networks. Next, in order to understand how these networks work, the author analyzed their framework, and provided an explanation of the three working principles of the networks, convolution layer, residual network layer and deconvolution layer. Lastly, in order to visualize the networks in architectural drawings, the author derived data from different layer and different training epochs, and visualized the findings as gray scale images. It was found that the features of the architectural plan drawings have been gradually learned and stored as parameters in the networks. As the networks get deeper and the training epoch increases, the features in the graph become more concise and clearer. This phenomenon may be inspiring in understanding the designing behavior of humans.
keywords	full paper, design study, generative design, ai + machine learning, ai & machine learning
series	ACADIA
type	paper
email
last changed	2022/06/07 07:49

_id	ecaade2018_370
id	ecaade2018_370
authors	Abdelmohsen, Sherif, Massoud, Passaint, El-Dabaa, Rana, Ibrahim, Aly and Mokbel, Tasbeh
year	2018
title	A Computational Method for Tracking the Hygroscopic Motion of Wood to develop Adaptive Architectural Skins
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 2, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 253-262
doi	https://doi.org/10.52842/conf.ecaade.2018.2.253
summary	Low-cost programmable materials such as wood have been utilized to replace mechanical actuators of adaptive architectural skins. Although research investigated ways to understand the hygroscopic response of wood to variations in humidity levels, there are still no clear methods developed to track and analyze such response. This paper introduces a computational method to analyze, track and store the hygroscopic response of wood through image analysis and continuous tracking of angular measurements in relation to time. This is done through a computational closed loop that links the smart material interface (SMI) representing hygroscopic response with a digital and tangible interface comprising a Flex sensor, Arduino kit, and FireFly plugin. Results show no significant difference between the proposed sensing mechanism and conventional image analysis tracking systems. Using the described method, acquiring real-time data can be utilized to develop learning mechanisms and predict the controlled motion of programmable material for adaptive architectural skins.
keywords	Hygroscopic properties of wood; Adaptive architecture; Programmable materials; Real-time tracking
series	eCAADe
email
last changed	2022/06/07 07:54

_id	caadria2018_086
id	caadria2018_086
authors	Castelo Branco, Renata and Leit?o, António
year	2018
title	Algorithmic Architectural Visualization
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 2, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 557-566
doi	https://doi.org/10.52842/conf.caadria.2018.2.557
summary	Digitally-generated visualizations, such as renders or movies, are, nowadays, commonly used as representation methods for architectural creations. This occurs not only in final stages of the process, with the goal of selling the product's image, but also in midst creation process to express concepts and ideas. Presently, the spread of parametric and algorithmic approaches to design creates a problem for visualization, as it enables the almost effortless change of 3D models, thus requiring repeated visualization efforts to keep up with the changes applied to the design. To solve this, we propose extending the algorithmic design approach to also include the high-level description of architectural image creation. The methodology, Algorithmic Architectural Visualization (AAV), also contemplates the required preparation settings for the visualization process, and includes possible visualization productions inspired by film techniques.
keywords	Algorithmic Design; Architectural Visualization; Render; Film Grammar
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	ecaade2018_329
id	ecaade2018_329
authors	De Luca, Francesco, Nejur, Andrei and Dogan, Timur
year	2018
title	Facade-Floor-Cluster - Methodology for Determining Optimal Building Clusters for Solar Access and Floor Plan Layout in Urban Environments
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 2, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 585-594
doi	https://doi.org/10.52842/conf.ecaade.2018.2.585
summary	Daylight standards are one of the main factors for the shape and image of cities. With urbanization and ongoing densification of cities, new planning regulations are emerging in order to manage access to sun light. In Estonia a daylight standard defines the rights of light for existing buildings and the direct solar access requirement for new premises. The solar envelope method and environmental simulations to compute direct sun light hours on building façades can be used to design buildings that respect both daylight requirements. However, no existing tool integrates both methods in an easy to use manner. Further, the assessment of façade performance needs to be related to the design of interior layouts and of building clusters to be meaningful to architects. Hence, the present work presents a computational design workflow for the evaluation and optimisation of high density building clusters in urban environments in relation to direct solar access requirements and selected types of floor plans.
keywords	Performance-driven Design; Urban Design; Direct Solar Access; Environmental Simulations and Evaluations; Parametric Modelling
series	eCAADe
email
last changed	2022/06/07 07:55

_id	ecaade2018_295
id	ecaade2018_295
authors	Dezen-Kempter, Eloisa, Cogima, Camila Kimi, Vieira de Paiva, Pedro Victor and Garcia de Carvalho, Marco Antonio
year	2018
title	BIM for Heritage Documentation - An ontology-based approach
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 213-222
doi	https://doi.org/10.52842/conf.ecaade.2018.1.213
summary	In the recent decades, the high-resolution remote sensing, through 3D laser scanning and photogrammetry benefited historic buildings maintenance, conservation, and restoration works. However, the dense surface models (DSM) generated from the data capture have nonstructured features as lack of topology and semantic discretization. The process to create a semantically oriented 3D model from the DSM, using the of Building Information Model technology, is a possibility to integrate historical information about the life cycle of the building to maintain and improving architectural valued building stock to its functional level and safeguarding its outstanding historical value. Our approach relies on an ontology-based system to represent the knowledge related to the building. Our work outlines a model-driven approach based on the hybrid data acquisition, its post-processing, the identification of the building' main features for the parametric modeling, and the development of an ontological map integrated with the BIM model. The methodology proposed was applied to a large-scale industrial historical building, located in Brazil. The DSM were compared, providing a qualitative assessment of the proposed method.
keywords	Reality-based Surveying; Ontology-based System; BIM; Built heritage management
series	eCAADe
email
last changed	2022/06/07 07:55

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

_id	caadria2018_044
id	caadria2018_044
authors	Inoue, Kazuya, Fukuda, Tomohiro, Cao, Rui and Yabuki, Nobuyoshi
year	2018
title	Tracking Robustness and Green View Index Estimation of Augmented and Diminished Reality for Environmental Design - PhotoAR+DR2017 project
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 1, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 339-348
doi	https://doi.org/10.52842/conf.caadria.2018.1.339
summary	To assess an environmental design, augmented and diminished reality (AR/DR) have a potential to build a consensus more smoothly through the landscape simulation of new design visualization of the items to be assessed, such as the green view index. However, the current system is still considered to be impractical because it does not provide complete user experience. Thus, we aim to improve the robustness of the AR/DR system and to integrate the estimation of the green view index into the AR/DR system on a game engine. Further, we achieve an improved stable tracking by eliminating the outliers of the tracking reference points using the random sample consensus (RANSAC) method and by defining the tracking reference points over an extensive area of the AR/DR display. Additionally, two modules were implemented, among which one module is used to solve the occlusion problem while the other is used to estimate the green view index. The novel integrated AR/DR system with all modules was developed on the game engine. A mock design project was developed in an outdoor environment for simulation purposes, thereby verifying the applicability of the developed system.
keywords	Environmental Design; Augmented Reality (AR); Diminished Reality (DR); Green View Index; Segmentation
series	CAADRIA
email
last changed	2022/06/07 07:50

_id	acadia18_166
id	acadia18_166
authors	Kvochick, Tyler
year	2018
title	Sneaky Spatial Segmentation. Reading Architectural Drawings with Deep Neural Networks and Without Labeling Data
source	ACADIA // 2018: Recalibration. On imprecisionand infidelity. [Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-17729-7] Mexico City, Mexico 18-20 October, 2018, pp. 166-175
doi	https://doi.org/10.52842/conf.acadia.2018.166
summary	Currently, it is nearly impossible for an artificial neural network to generalize a task from very few examples. Humans, however, excel at this. For instance, it is not necessary for a designer to see thousands or millions of unique examples of how to place a given drawing symbol in a way that meets the economic, aesthetic, and performative goals of the project. In fact, the goals can be (and usually are) communicated abstractly in natural language. Machine learning (ML) models, however, do need numerous examples. The methods that we explore here are an attempt to circumvent this in order to make ML models more immediately useful. In this work, we present progress on the application of contemporary ML techniques to the design process in the architecture, engineering, and construction (AEC) industry. We introduce a technique to partially circumvent the data hungriness of neural networks, which is a significant impediment to their application outside of the ML research community. We also show results on the applicability of this technique to real-world drawings and present research that addresses how some fundamental attributes of drawings as images affect the way they are interpreted in deep neural networks. Our primary contribution is a technique to train a neural network to segment real-world architectural drawings after using only generated pseudodrawings.
keywords	full paper, representation + perception, computation, ai & machine learning
series	ACADIA
type	paper
email
last changed	2022/06/07 07:51

_id	ecaade2018_108
id	ecaade2018_108
authors	Luo, Dan, Wang, Jingsong and Xu, Weiguo
year	2018
title	Applied Automatic Machine Learning Process for Material Computation
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 109-118
doi	https://doi.org/10.52842/conf.ecaade.2018.1.109
summary	Machine learning enables computers to learn without being explicitly programmed. This paper outlines state-of-the-art implementations of machine learning approaches to the study of physical material properties based on Elastomer we developed, which combines with robotic automation and image recognition to generate a computable material model for non-uniform linear Elastomer material. The development of the neural network includes a few preliminary experiments to confirm the feasibility and the influential parameters used to define the final RNN neural network, the study of the inputs and the quality of the testing samples influencing the accuracy of the output model, and the evaluation of the generated material model as well as the method itself. To conclude, this paper expands such methods to the possible architectural implications on other non-uniform materials, such as the performance of wood sheets with different grains and tensile material made from composite materials.
keywords	neural network; robotic; material computation; automation
series	eCAADe
email
last changed	2022/06/07 07:59

_id	caadria2018_083
id	caadria2018_083
authors	Luo, Dan, Wang, Jinsong and Xu, Weiguo
year	2018
title	Robotic Automatic Generation of Performance Model for Non-Uniform Linear Material via Deep Learning
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 1, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 39-48
doi	https://doi.org/10.52842/conf.caadria.2018.1.039
summary	In the following research, a systematic approach is developed to generate an experiment-based performance model that computes and customizes properties of non-uniform linear materials to accommodate the form of designated curve under bending and natural force. In this case, the test subject is an elastomer strip of non-uniform sections. A novel solution is provided to obtain sufficient training data required for deep learning with an automatic material testing mechanism combining robotic arm automation and image recognition. The collected training data are fed into a deep combination of neural networks to generate a material performance model. Unlike most traditional performance models that are only able to simulate the final form from the properties and initial conditions of the given materials, the trained neural network offers a two-way performance model that is also able to compute appropriate material properties of non-uniform materials from target curves. This network achieves complex forms with minimal and effective programmed materials with complicated nonlinear properties and behaving under natural forces.
keywords	Material performance model; Deep Learning; Robotic automation; Material computation; Neural network
series	CAADRIA
email
last changed	2022/06/07 07:59

_id	ecaade2018_229
id	ecaade2018_229
authors	Rogers, Jessie and Schnabel, Marc Aurel
year	2018
title	Digital Design Ecology - An Analysis for an Intricate Framework of Architectural Design
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 459-468
doi	https://doi.org/10.52842/conf.ecaade.2018.1.459
summary	This paper evaluates, along with expert assessment, the novel, evolving and creative instruments employed for a digital design process. Applications within this paper derive outputs which are attention-grabbing. These include Agent Simulations, Artistic Image Processing, Realistic Site Geometry, Projected 3D Space Sketching, Immersive 3D Space Sketching, Rhinoceros3D, Grasshopper3D, Fuzor, and Immersive Virtual Reality Presentation. The expert evaluations conclude that all design instruments and methodologies implemented within the digital design ecology work together well for educational purposes. Within the professional practice, however, the various tools could be implemented seamlessly; whereas some of them would not suit the industry from a time-cost perspective. Throughout this paper reason and insight becomes explained and is clear as to why various applications should be selected within various modes of operandi for design processes.
keywords	Methodology Ecology; Agent Simulation; Digital Design; Virtual Reality; Photogrammetry; Image Processing
series	eCAADe
email
last changed	2022/06/07 07:56

_id	caadria2018_197
id	caadria2018_197
authors	Rogers, Jessie, Schnabel, Marc Aurel and Lo, Tian Tian
year	2018
title	Digital Culture - An Interconnective Design Methodology Ecosystem
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 1, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 493-502
doi	https://doi.org/10.52842/conf.caadria.2018.1.493
summary	Transitioning away from traditional design methodology, for example, paper sketching, CAAD works, and 'flat screen' rendering, this paper proposes a new methodological ecosystem of which tests its validity within a studio-based case study. The focus will prove whether dynamic implementation and interconnectivity of evolving design tools can create richness and complexity of a design outcome through arbitrary phases of a generative design methodology ecosystem. Processes tested include combinations of agent simulations, artistic image processing analysis, site photogrammetry, 3D immersive sketching both abstract and to site-scale, parametric design generation, and virtual reality style presentations. Enhancing the process of design with evolving techniques in a generative way which dynamically interconnects will stimulate a digital culture of design generation that includes new aspects of interest and introduces innovative opportunities within all corners of the architectural realm. Methodology components within this ecosystem of interaction prove that the architecture cannot be as rich and complex without the utilisation of all strengths within each unique design tool.
keywords	Methodology Ecosystem; Simulation; Immersive; Virtual Reality; Photogrammetry
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	acadia18_250
id	acadia18_250
authors	Seibold, Zach; Grinham, Jonathan; Geletina, Olga; Ahanotu, Onyemaechi; Sayegh, Allen; Weaver, James; Bechthold, Martin
year	2018
title	Fluid Equilibrium: Material Computation in Ferrofluidic Castings
source	ACADIA // 2018: Recalibration. On imprecisionand infidelity. [Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-17729-7] Mexico City, Mexico 18-20 October, 2018, pp. 250-259
doi	https://doi.org/10.52842/conf.acadia.2018.250
summary	We present a computationally-based manufacturing process that allows for variable pattern casting through the use of ferrofluid – a mixture of suspended magnetic nanoparticles in a carrier liquid. The capacity of ferrofluid to form intricate spike and labyrinthine packing structures from ferrohydrodynamic instabilities is well recognized in industry and popular science. In this paper we employ these instabilities as a mold for the direct casting of rigid materials with complex periodic features. Furthermore, using a bitmap-based computational workflow and an array of high-strength neodymium magnets with linear staging, we demonstrate the ability to program the macro-scale pattern formation by modulating the magnetic field density within a single cast. Using this approach, it is possible to program specific patterns in the resulting cast tiles at both the micro- and macro-scale and thus generate tiled arrays with predictable halftone-like image features. We demonstrate the efficacy of this approach for a variety of materials typically used in the architecture, engineering, and construction industries (AEC) including epoxys, ceramics, and cements.
keywords	full paper, materials & adaptive systems, digital fabrication, digital materials, physics
series	ACADIA
type	paper
email
last changed	2022/06/07 08:00

_id	acadia19_392
id	acadia19_392
authors	Steinfeld, Kyle
year	2019
title	GAN Loci
source	ACADIA 19:UBIQUITY AND AUTONOMY [Proceedings of the 39th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-59179-7] (The University of Texas at Austin School of Architecture, Austin, Texas 21-26 October, 2019) pp. 392-403
doi	https://doi.org/10.52842/conf.acadia.2019.392
summary	This project applies techniques in machine learning, specifically generative adversarial networks (or GANs), to produce synthetic images intended to capture the predominant visual properties of urban places. We propose that imaging cities in this manner represents the first computational approach to documenting the Genius Loci of a city (Norberg-Schulz, 1980), which is understood to include those forms, textures, colors, and qualities of light that exemplify a particular urban location and that set it apart from similar places. Presented here are methods for the collection of urban image data, for the necessary processing and formatting of this data, and for the training of two known computational statistical models (StyleGAN (Karras et al., 2018) and Pix2Pix (Isola et al., 2016)) that identify visual patterns distinct to a given site and that reproduce these patterns to generate new images. These methods have been applied to image nine distinct urban contexts across six cities in the US and Europe, the results of which are presented here. While the product of this work is not a tool for the design of cities or building forms, but rather a method for the synthetic imaging of existing places, we nevertheless seek to situate the work in terms of computer-assisted design (CAD). In this regard, the project is demonstrative of a new approach to CAD tools. In contrast with existing tools that seek to capture the explicit intention of their user (Aish, Glynn, Sheil 2017), in applying computational statistical methods to the production of images that speak to the implicit qualities that constitute a place, this project demonstrates the unique advantages offered by such methods in capturing and expressing the tacit.
series	ACADIA
type	normal paper
email
last changed	2022/06/07 07:56

_id	ecaade2018_331
id	ecaade2018_331
authors	Trento, Armando and Fioravanti, Antonio
year	2018
title	Contextual Capabilities Meet Human Behaviour - Round the peg and square the hole
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 613-620
doi	https://doi.org/10.52842/conf.ecaade.2018.1.613
summary	To improve environmental wellbeing and productivity, design innovation focuses on human's use-process, evolving individual space to flexible and specialized ones, according to the users' tasks - activity-based. BIM models supports sophisticated behaviours' simulation such as energy, acoustics, although it is not able to manage space use-processes. The present paper rather than a report of a case study or the presentation of a new methodology wants to contribute, together with previous works, in sketching a theroretical framework within which it is possible to compute the interaction between users and spaces (and vice versa). The quest is to reflect on possible paths for engineering knowledge and understanding, providing a BIM system the semantic information required to operate adaptively and achieve robust and innovative goal-directed behavior. Compared to current research on simulation systems, this research approach links Context, intended as spaces capabilities to Actor's Behavioural Knowledge including formalization of personality typologies and profiled behavioural patterns. By means of a classical problem solving metaphor, the "squared peg in a round hole" one, multiple categories for goal achievement are sketched, based on reciprocal Actors and Context behaviour adaptation.
keywords	Use-process Knowledge; Behavioural Knowledge; Use Simulation; Cognitive Computing
series	eCAADe
email
last changed	2022/06/07 07:57

_id	sigradi2018_1619
id	sigradi2018_1619
authors	Agirbas, Asli
year	2018
title	Creating Non-standard Spaces via 3D Modeling and Simulation: A Case Study
source	SIGraDi 2018 [Proceedings of the 22nd Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Brazil, São Carlos 7 - 9 November 2018, pp. 1051-1058
summary	Especially in the film industry, architectural spaces away from Euclidean geometry are brought to foreground. The best environment in which such spaces can be designed, is undoubtedly the 3D modeling environment. In this study, an experimental study was carried out on the creation of alternative spaces with undergraduate architectural students. Via using 3D modeling and various simulation techniques in the Maya software, students created spaces, which were away from the traditional architectural spaces. Thus, in addition to learning the 3D modeling software, architectural students learned to use animation and simulation as a part of design, not just as a presentation tool, and opening up new horizons for non-standard spaces was provided.
keywords	3D Modeling; Simulation; Animation; CAAD; Maya; Non-standard spaces
series	SIGRADI
email
last changed	2021/03/28 19:58

_id	sigradi2018_1628
id	sigradi2018_1628
authors	Agirbas, Asli
year	2018
title	The Use of Multi-Software in Undergraduate Architectural Design Studio Education: A Case Study
source	SIGraDi 2018 [Proceedings of the 22nd Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Brazil, São Carlos 7 - 9 November 2018, pp. 1059-1064
summary	In the architectural design process, instead of using the computer programs effectively, the ability of choosing the most suitable program for the purpose takes place. However, different programs used in the design process serve different purposes. Therefore, the use of more than one program throughout the project design process arises. Every day the number of programs used increases rapidly. Hence, the designers find difficult to adapt this speed. The same applies to the students of architectural design studio course. Therefore, in this study with undergraduate architecture students, a pilot study focusing on the use of multi-software was conducted within the scope of architectural design studio. The process and outputs were evaluated.
keywords	Use of multi-software; Contextual design; Architectural design education; CAAD
series	SIGRADI
email
last changed	2021/03/28 19:58

_id	acadia22pr_124
id	acadia22pr_124
authors	Ago, Viola; Tursack, Hans
year	2022
title	Understorey - A Pavilion in Parts
source	ACADIA 2022: Hybrids and Haecceities [Projects Catalog of the 42nd Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9860805-7-4]. University of Pennsylvania Stuart Weitzman School of Design. 27-29 October 2022. edited by M. Akbarzadeh, D. Aviv, H. Jamelle, and R. Stuart-Smith. 124-129.
summary	In the summer of 2018, our collaboration was awarded a University Design Fellowship from the Exhibit Columbus organization to design, fabricate, and build a large pavilion in Columbus, Indiana as part of a biannual contemporary architecture exhibition. Our proposal for the competition was a pavilion that would double as an ecological education center. Our inspiration for this program was triggered in part by our reading of Jane Bennett’s materialist philosophy outlined in her book Vibrant Matter (2009). Through Bennett’s lens, our design rendered our site’s context as an animate field, replete with pre-existing material composites that we wanted to celebrate through a series of displays, information boards, and artificial lighting. In this, the installation would feature samples of local plants, minerals, and rocks, indigenous to Southern Indiana.
series	ACADIA
type	project
email
last changed	2024/02/06 14:06

_id	sigradi2018_1508
id	sigradi2018_1508
authors	Akta?, Begüm; Birgül Çolako?lu, M.
year	2018
title	Systematic approach to design builds for freeform façade: AFA Cultural Center
source	SIGraDi 2018 [Proceedings of the 22nd Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Brazil, São Carlos 7 - 9 November 2018, pp. 176-182
summary	The design and construction of the complex, irregularly shaped, and curvilinear building forms are also known as freeform architecture, have gained an interest form architects and engineers. This paper presents how freeform façade designs are defined with its curvilinear geometric characteristics and the systematic approach that is used to design and implement them. The proposed method incorporates product design and integral façade construction approach at AFA Cultural Center freeform façade implementation. Therefore, the paper aims to improve the viability of the proposed method and decreasing the gap between the other disciplines and architects in a systematic way without losing the creativity of the architects.
keywords	Parametric modeling; Systematic approach; Design thinking; System thinking; Freeform façade design
series	SIGRADI
email
last changed	2021/03/28 19:58

_id	ecaade2018_172
id	ecaade2018_172
authors	Al-Douri, Firas
year	2018
title	The Employment of Digital Simulation in the Planning Departments in US Cities - How does it affect design and decision-making processes?
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 2, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 539-548
doi	https://doi.org/10.52842/conf.ecaade.2018.2.539
summary	The increased interactivity of digital simulation tools has offered a wide range of opportunities that may provoke a paradigmatic shift in urban design practice. Yet, research results did not provide any clear evidence that such shift seems to exist. Further studies are required to examine the methods and impact of their usage on decision-making and design outcome. To that goal, this research uses the single-case study design that has been pursued in three phases: literature review, online survey, and semi-structured interviews. The results have shown inadequacies, inconsistency, and ineffectiveness of usage of the tools that are most appropriate to the design activities of each phase and thus a limited impact on critical areas of the decision-making. The impact of the tools' usage is found to be correlated with not only the extent of their usage, but also with a variety of procedural and substantive factors such as the plan methodology, extent of tool's usage, choice of the appropriate tool, and planners' skills and capabilities in using those tools.
keywords	Urban Simulation ; Urban Design Practice
series	eCAADe
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last changed	2022/06/07 07:54

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