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	cdrf2022_209
id	cdrf2022_209
authors	Yecheng Zhang, Qimin Zhang, Yuxuan Zhao, Yunjie Deng, Feiyang Liu, Hao Zheng
year	2022
title	Artificial Intelligence Prediction of Urban Spatial Risk Factors from an Epidemic Perspective
doi	https://doi.org/https://doi.org/10.1007/978-981-19-8637-6_18
source	Proceedings of the 2022 DigitalFUTURES The 4st International Conference on Computational Design and Robotic Fabrication (CDRF 2022)
summary	From the epidemiological perspective, previous research methods of COVID-19 are generally based on classical statistical analysis. As a result, spatial information is often not used effectively. This paper uses image-based neural networks to explore the relationship between urban spatial risk and the distribution of infected populations, and the design of urban facilities. We take the Spatio-temporal data of people infected with new coronary pneumonia before February 28 in Wuhan in 2020 as the research object. We use kriging spatial interpolation technology and core density estimation technology to establish the epidemic heat distribution on fine grid units. We further examine the distribution of nine main spatial risk factors, including agencies, hospitals, park squares, sports fields, banks, hotels, Etc., which are tested for the significant positive correlation with the heat distribution of the epidemic. The weights of the spatial risk factors are used for training Generative Adversarial Network models, which predict the heat distribution of the outbreak in a given area. According to the trained model, optimizing the relevant environment design in urban areas to control risk factors effectively prevents and manages the epidemic from dispersing. The input image of the machine learning model is a city plan converted by public infrastructures, and the output image is a map of urban spatial risk factors in the given area.
series	cdrf
email
last changed	2024/05/29 14:02

_id	ecaade2020_143
id	ecaade2020_143
authors	Ilyas, Sobia, Wang, Xinyue, Li, Wenting, Zhang, Zhuoqun, Wang, Tsung-Hsien and Peng, Chengzhi
year	2020
title	Towards an Interactionist Model of Cognizant Architecture - A sentient maze built with swarm intelligence
doi	https://doi.org/10.52842/conf.ecaade.2020.2.201
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. 201-208
summary	Cognizant Architecture is a term used to define sentient and smart structures broadly. In this paper, an 'Interactionist' model of cognizant architecture is proposed as a method of investigating the development process by inverting the conventional concept of maze design. The proposed 'Cognizant Maze' aims to achieve user-architecture micro-interactions through delighting the users, presenting a physical activity equally attractive to kids and adults alike, and activating mind-enticing visual effects. Like many previous innovations, nature is what inspires us in the maze-making process. In modelling the cognizant maze, we develop the concept and workflow of prototyping a form of swarm intelligence. We are particularly interested in exploring how simulated behaviours of swarm intelligence can be manifested in a maze environment for micro-interactions to take place. Combining parametric modelling and Arduino-based physical computing, our current interactive prototyping shows how the maze and its users can 'think, act and play' with each other, hence achieving an interactionist model of cognizant architecture. We reflect that the lessons learned from the Cognizant Maze experiment may lead to further development of cognizant architecture as a propagation of swarm intelligence through multi-layered micro-interactions.
keywords	swarm intelligence; maze design; Micro-interactions; interactive prototyping; cognizant architecture
series	eCAADe
email
last changed	2022/06/07 07:50

_id	caadria2020_178
id	caadria2020_178
authors	Luo, Yue, Liang, Manchen, Gao, Letong, Zhang, Yuchun, Wang, Chenxi, Su, Xia and Huang, Weixin
year	2020
title	Investigating Site Survey Process with Protocol Analysis and an Extended FBS Framework
doi	https://doi.org/10.52842/conf.caadria.2020.2.547
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. 547-556
summary	In this paper, we try to investigate architectural site survey process by conducting experiment and quantitative analysis. 17 student volunteers were asked to practice site survey for a fixed design objective. With site survey process recorded along with sketching and utterance, we adopt protocol analysis and FBS ontology, which are widely used and discussed in design process research, as the basis of our analysis. Since site survey is a preliminary stage of architectural design, it differs from actual design process in many aspects. In this case, we extended the original FBS framework by adding two extra activities- Objective Processor and Subjective Processor- to better describe site survey process.
keywords	Site Survey; Protocol Analysis; FBS Ontology; Architecture Education
series	CAADRIA
email
last changed	2022/06/07 07:51

_id	caadria2020_193
id	caadria2020_193
authors	Wang, Sihan, Liu, Chi, Zhang, Guo Li, Luo, Qi Huan, Xu, Weishun and Raspall, Felix
year	2020
title	Digital Planting - Fabrication of Integrated Concrete Green Wall via Additive Manufacturing
doi	https://doi.org/10.52842/conf.caadria.2020.1.145
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. 145-151
summary	Green walls are becoming a symbol of modern architecture representing sustainability and aesthetics. However, the fabrication of wall components that can nurture the growth of plants and other living creatures requires components to locate soil and other substrates, a controlled rugosity for plants and moss to grip, and conduits to distribute water and nutrients. This is normally done by adding extra attachments to the faÃ§ade. In this paper, we introduce a digital approach to design and produce architectural components that can integrate green wall's functional requirements into the wall itself. Such components are fabricated via Additive Manufacturing (AM) extrusion with the assists of robotic arms.
keywords	Green Wall; Additive Manufacturing; Robotic Fabrication; Clay Printing
series	CAADRIA
email
last changed	2022/06/07 07:58

_id	artificial_intellicence2019_295
id	artificial_intellicence2019_295
authors	Xiang Wang, Kam-Ming Mark Tam, Alexandre Beaudouin-Mackay,Benjamin Hoyle, Molly Mason, Zhe Guo, Weizhe Gao, Ce Li, Weiran Zhu,Zain Karsan, Gene Ting-Chun Kao, Liming Zhang, Hua Chai, Philip F. Yuan, and Philippe Block
year	2020
title	3d-Printed Bending-Active Formwork for Shell Structures
doi	https://doi.org/https://doi.org/10.1007/978-981-15-6568-7_18
source	Architectural Intelligence Selected Papers from the 1st International Conference on Computational Design and Robotic Fabrication (CDRF 2026)
summary	This paper presents a novel building technique for the formwork of thin shell structures with 3d-printed bending-active mesh sheets. To enhance the structural stiffness of the flexible plastic materials, bending-active form is applied to utilize the geometry stiffening effect through the large deformation of bending. As it is the main problem to determine the final geometry of the bent surface, design methods with consideration of the numerical simulation is researched and both simulations via dynamic relaxation and finite element method are presented. Several demonstrator pavilions and the building process are shown to test the feasibilities of the presented building techniques in the real shell project. It is expected that this method could be applied into more thin shell projects to realize an efficient building technology with less exhaust of materials.
series	Architectural Intelligence
email
last changed	2022/09/29 07:28

_id	caadria2020_320
id	caadria2020_320
authors	Cheng, Jiahui, Zhang, Zhuoqun and Peng, Chengzhi
year	2020
title	Parametric Modelling and Simulation of an Indoor Temperature Responsive Rotational Shading System Design
doi	https://doi.org/10.52842/conf.caadria.2020.1.579
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. 579-588
summary	We present a digital design strategy for developing an intelligent rotational shading system responsive to changes in indoor temperatures. The strategy was first modelled with an Arduino-based physical prototype, identifying the concept of "mapping" between building indoor air temperature and rotational movement (angle) of external solar shading. A virtual parametric modelling approach was then followed to test three methods of mapping: linear, quadratic and logarithmic. The aim was to examine the performative differences exhibited by the three mapping methods in terms of the total comfort hours and estimated cooling energy demand during summer months. A typical cellular office in the Arts Tower of University of Sheffield was chosen for the parametric modelling (Rhino-Grasshopper) and environmental simulation (Honeybee-Ladybug) of horizontal and vertical rotational shading system design. The simulation shows that the horizontal shading system rotating according to the linear mapping methods achieve greater total comfort hours with lower cooling energy demand in the case of Arts Tower in Sheffield, UK.
keywords	indoor temperature responsive shading; temperature-angle mapping; parametric design; kinetic shading; overheating
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	acadia20_300
id	acadia20_300
authors	H Arnardottir, Thora; Dade-Robertson, Martyn; Mitrani, Helen; Zhang, Meng; Christgen, Beate
year	2020
title	Turbulent Casting
doi	https://doi.org/10.52842/conf.acadia.2020.1.300
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. 300-309.
summary	There has been a growing interest in living materials and fabrication processes including the use of bacteria, algae, fungi, and yeast to offer sustainable alternatives to industrial materials synthesis. Microbially induced calcium carbonate precipitation (MICP) is a biomineralization process that has been widely researched to solve engineering problems such as concrete cracking and to strengthen soils. MICP can also be used as an alternative to cement in the fabrication of building materials and, because of the unique process of living fabrication, if we see bacteria as our design collaborators, new types of fabrication and processes may be possible. The process of biomineralization is inherently different from traditional fabrication processes that use casting or molding. Its properties are influenced by the active bacterial processes that are connected to the casting environment. Understanding and working with interrelated factors enables a novel casting approach and the exploration of a range of form types and materials of variable consistencies and structure. We report on an experiment with partial control of mineralization through the design of different experimental vessels to direct and influence the cementation process of sand. In order to capture the form of the calcification in these experiments, we have analyzed the results using three-dimensional imaging and a technique that excavates the most friable material from the cast in stages. The resulting scans are used to reconstruct the cementation timeline. This reveals a hidden fabrication/growth process. These experiments offer a different perspective on form finding in material fabrication.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_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	cdrf2021_13
id	cdrf2021_13
authors	Hao Wen, Pengcheng Gu, Yuchao Zhang, Shuai Zou, and Patrik Schumacher
year	2021
title	A Generative Approach to Social Ecologies in Project [Symbios]City
doi	https://doi.org/https://doi.org/10.1007/978-981-16-5983-6_2
source	Proceedings of the 2021 DigitalFUTURES The 3rd International Conference on Computational Design and Robotic Fabrication (CDRF 2021)
summary	The following paper talks about the studio project [Symbios]City, which is developed as a design research project in 2020–2021 Schumacher’ studio on social ecology of the graduate program in Architectural Association’s design research lab. The project aims to create an assemblage of social ecologies through a rich but cohesive multi-authored urban district. The primary ambition is to generate an urban area with a characterful, varied identity, that achieves a balanced order between unity and difference avoiding both the sterile and disorienting monotony of centrally planned modernist cities and the (equally disorienting) visual chaos of an agglomeration of utterly unrelated interventions as we find now frequently. Through a thorough research process, our project evolves mainly out of three principles that are taken into consideration for the development of our project: topological optimization, phenomenology, and ecology. By “ecology”, we understand it as a living network of information exchange. Therefore, every strategy we employ is not merely about reacting to the weather conditions, but instead it is an inquiry into the various ways we can exploit the latter, a translation of the weather conditions into spatial and programmatic properties. [Symbios]City therefore aims at developing a multi-authored urban area with a rich identity that achieves a balance between the various elements. [Symbios]City began formally from topological optimization, developed based on studies on ecology, and concluded the design following our phenomenological explorations, aiming at a complex design project that unifies the perception of all scales of design: from the platform to the skyscrapers.
series	cdrf
email
last changed	2022/09/29 07:53

_id	artificial_intellicence2019_129
id	artificial_intellicence2019_129
authors	Hua Chai, Liming Zhang, and Philip F. Yuan
year	2020
title	Advanced Timber Construction Platform Multi-Robot System for Timber Structure Design and Prefabrication
doi	https://doi.org/https://doi.org/10.1007/978-981-15-6568-7_9
source	Architectural Intelligence Selected Papers from the 1st International Conference on Computational Design and Robotic Fabrication (CDRF 2023)
summary	Robotic Timber Construction has been widely researched in the last decade with remarkable advancements. While existing robotic timber construction technologies were mostly developed for specific tasks, integrated platforms aiming for industrialization has become a new trend. Through the integration of timber machining center and advanced robotics, this research tries to develop an advanced timber construction platform with multi-robot system. The Timber Construction Platform is designed as a combination of three parts: multi-robot system, sensing system, and control system. While equipped with basic functions of machining centers that allows multi-scale multifunctional timber components’ prefabrication, the platform also served as an experimental facility for innovative robotic timber construction techniques, and a service platform that integrates timber structure design and construction through real-time information collection and feedback. Thereby, this platform has the potential to be directly integrated into the timber construction industry, and contributes to a mass-customized mode of timber structures design and construction.
series	Architectural Intelligence
email
last changed	2022/09/29 07:28

_id	cdrf2019_93
id	cdrf2019_93
authors	Jiaxin Zhang , Tomohiro Fukuda , and Nobuyoshi Yabuki
year	2020
title	A Large-Scale Measurement and Quantitative Analysis Method of Façade Color in the Urban Street Using Deep Learning
doi	https://doi.org/https://doi.org/10.1007/978-981-33-4400-6_9
source	Proceedings of the 2020 DigitalFUTURES The 2nd International Conference on Computational Design and Robotic Fabrication (CDRF 2020)
summary	Color planning has become a significant issue in urban development, and an overall cognition of the urban color identities will help to design a better urban environment. However, the previous measurement and analysis methods for the facade color in the urban street are limited to manual collection, which is challenging to carry out on a city scale. Recent emerging dataset street view image and deep learning have revealed the possibility to overcome the previous limits, thus bringing forward a research paradigm shift. In the experimental part, we disassemble the goal into three steps: firstly, capturing the street view images with coordinate information through the API provided by the street view service; then extracting facade images and cleaning up invalid data by using the deep-learning segmentation method; finally, calculating the dominant color based on the data on the Munsell Color System. Results can show whether the color status satisfies the requirements of its urban plan for façade color in the street. This method can help to realize the refined measurement of façade color using open source data, and has good universality in practice.
series	cdrf
email
last changed	2022/09/29 07:51

_id	caadria2020_047
id	caadria2020_047
authors	Lee, Han Jie, Lin, Zhuoli, Zhang, Ji and Janssen, Patrick
year	2020
title	Irradiance Mappinig for Large Scale City Models
doi	https://doi.org/10.52842/conf.caadria.2020.1.803
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. 803-812
summary	This paper reports on the development of a geocomputational simulation workflow for the irradiance mapping of large scale city models. A fully automated workflow is presented, for importing CityGML city models, generating the simulation input models, executing the simulations, and aggregating the results. In order to speed up the overall processing time, the workflow uses parallel processing across multiple computers and multiple cores. Two case studies are presented, for Singapore and for Rotterdam.
keywords	Integrated irradiance simulation; Solar potential assessment ; Large scale urban 3D model; Houdini; Radiance
series	CAADRIA
email
last changed	2022/06/07 07:51

_id	ecaade2020_113
id	ecaade2020_113
authors	Li, Yunqin, Yabuki, Nobuyoshi, Fukuda, Tomohiro and Zhang, Jiaxin
year	2020
title	A big data evaluation of urban street walkability using deep learning and environmental sensors - a case study around Osaka University Suita campus
doi	https://doi.org/10.52842/conf.ecaade.2020.2.319
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. 319-328
summary	Although it is widely known that the walkability of urban street plays a vital role in promoting street quality and public health, there is still no consensus on how to measure it quantitatively and comprehensively. Recent emerging deep learning and sensor network has revealed the possibility to overcome the previous limit, thus bringing forward a research paradigm shift. Taking this advantage, this study explores a new approach for urban street walkability measurement. In the experimental study, we capture Street View Picture, traffic flow data, and environmental sensor data covering streets within Osaka University and conduct both physical and perceived walkability evaluation. The result indicates that the street walkability of the campus is significantly higher than that of municipal, and the streets close to large service facilities have better walkability, while others receive lower scores. The difference between physical and perceived walkability indicates the feasibility and limitation of the auto-calculation method.
keywords	walkability; WalkScore; deep learning; Street view picture; environmental sensor
series	eCAADe
email
last changed	2022/06/07 07:51

_id	ecaade2020_138
id	ecaade2020_138
authors	Patel, Sayjel Vijay, Tchakerian, Raffi, Lemos Morais, Renata, Zhang, Jie and Cropper, Simon
year	2020
title	The Emoting City - Designing feeling and artificial empathy in mediated environments
doi	https://doi.org/10.52842/conf.ecaade.2020.2.261
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. 261-270
summary	This paper presents a theoretical blueprint for implementing artificial empathy into the built environment. Transdisciplinary design principles have oriented the creation of a new model for autonomous environments integrating psychology, architecture, digital media, affective computing and interactive UX design. 'The Emoting City', an interactive installation presented at the 2019 Shenzhen Bi-City Biennale of Urbanism/Architecture, is presented as a first step to explore how to engage AI-driven sensing by integrating human perception, cognition and behaviour in a real-world scenario. The approach described encompasses two main elements: embedded cyberception and responsive surfaces. Its human-AI interface enables new modes of blended interaction that are conducive to self-empathy and insight. It brings forth a new proposition for the development of sensing systems that go beyond social robotics into the field of artificial empathy. The installation innovates in the design of seamless affective computing that combines 'alloplastic' and 'autoplastic' architectures. We believe that our research signals the emergence of a potential revolution in responsive environments, offering a glimpse into the possibility of designing intelligent spaces with the ability to sense, inform and respond to human emotional states in ways that promote personal, cultural and social evolution.
keywords	Artificial Intelligence; Responsive Architecture; Affective Computation; Human-AI Interfaces; Artificial Empathy
series	eCAADe
email
last changed	2022/06/07 07:59

_id	ecaade2020_310
id	ecaade2020_310
authors	Schulz, Daniel, Degkwitz, Till, Luft, Jonas, Zhang, Yuxiang, Stradtmann, Nicola and Noennig, Jörg Rainer
year	2020
title	Cockpit Social Infrastructure - Developing a planning support system in Hamburg
doi	https://doi.org/10.52842/conf.ecaade.2020.2.341
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. 341-350
summary	In a complex urban scenario with a growing number of stakeholders and high dynamic developments, decision makers rely heavily on public data to make informed decisions. Often though, the available data is heterogeneous and stems from incomplete or inconsistent sources. The planning process, especially the definition of planning goals/needs, is often delayed due to time-consuming data procurement and assessment. This paper describes the development of the Cockpit Social Infrastructure (CoSI), a GIS-based planning support system that serves as an easy-access interface between Hamburgs Urban Data Platform GIS data infrastructure and the municipal planners for social infrastructure, bridging the gap between disciplines and facilitating communication and decision-making between stakeholders. CoSI takes full advantage of the UDP infrastructure and aims to introduce a city-wide tool for planners to conduct holistic, evidence-based planning, grounded in the latest and regularly updated statistical data. The paper outlines the project genesis and underlying technical and administrative structures.
keywords	Planning Support System; GIS; Social Infrastructure; Urban Data
series	eCAADe
email
last changed	2022/06/07 07:57

_id	acadia20_124p
id	acadia20_124p
authors	Zhang, Catty Dan
year	2020
title	Vents 2.0
source	ACADIA 2020: Distributed Proximities / Volume II: Projects [Proceedings of the 40th Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 978-0-578-95253-6]. Online and Global. 24-30 October 2020. edited by M. Yablonina, A. Marcus, S. Doyle, M. del Campo, V. Ago, B. Slocum. 124-129
summary	VENTS 2.0 is a responsive environment that relates the moving air at separate locations using real-time data transmission. Functioning as an exhibition installation, a kinetic canopy produces a “rain” of air puffs subtly felt on the skin with a visual pattern of color LED, translating environmental conditions elsewhere into visual, audial, and tactile experiences within the Wurster Gallery at the University of California at Berkeley. The project articulates forms of airflow as part of a dynamic spatial device that stimulates senses beyond sight in a contemporary exhibition setting. It establishes an active system that triggers the emergence of initial states of air and modulates its evolvement. The installation collects real-time and recorded wind velocities via weather API (Application Programmer Interface). The computed data input controls multisensorial effects output by an array of air chambers using a customized script running on a Raspberry Pi. Each chamber generates air vortex rings one can feel when collapsing onto the skin, a typological form of airflow widely used in both art installations and the gaming industry due to its visual and tactile properties. These puffs of air, produced asynchronously, are distributed across the space by a total of twenty-four pairs of chambers assembled onto modified umbrellas on a lightweight aluminum frame. Undulating along the central axis of the 2,200 square feet gallery, the canopy locates right above average human height, illuminating softly a series of projects on display underneath, while at the same time providing visitors unexpected encounters with the constructed “breezes,” the echoing sound, and the fluctuating light.
series	ACADIA
type	project
email
last changed	2021/10/26 08:03

_id	caadria2020_234
id	caadria2020_234
authors	Zhang, Hang and Blasetti, Ezio
year	2020
title	3D Architectural Form Style Transfer through Machine Learning
doi	https://doi.org/10.52842/conf.caadria.2020.2.659
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. 659-668
summary	In recent years, a tremendous amount of progress is being made in the field of machine learning, but it is still very hard to directly apply 3D Machine Learning on the architectural design due to the practical constraints on model resolution and training time. Based on the past several years' development of GAN (Generative Adversarial Network), also the method of spatial sequence rules, the authors mainly introduces 3D architectural form style transfer on 2 levels of scale (overall and detailed) through multiple methods of machine learning algorithms which are trained with 2 types of 2D training data set (serial stack and multi-view) at a relatively decent resolution. By exploring how styles interact and influence the original content in neural networks on the 2D level, it is possible for designers to manually control the expected output of 2D images, result in creating the new style 3D architectural model with a clear designing approach.
keywords	3D; Form Finding; Style Transfer; Machine Learning; Architectural Design
series	CAADRIA
email
last changed	2022/06/07 07:57

_id	acadia20_238
id	acadia20_238
authors	Zhang, Hang
year	2020
title	Text-to-Form
doi	https://doi.org/10.52842/conf.acadia.2020.1.238
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. 238-247.
summary	Traditionally, architects express their thoughts on the design of 3D architectural forms via perspective renderings and standardized 2D drawings. However, as architectural design is always multidimensional and intricate, it is difficult to make others understand the design intention, concrete form, and even spatial layout through simple language descriptions. Benefiting from the fast development of machine learning, especially natural language processing and convolutional neural networks, this paper proposes a Linguistics-based Architectural Form Generative Model (LAFGM) that could be trained to make 3D architectural form predictions based simply on language input. Several related works exist that focus on learning text-to-image generation, while others have taken a further step by generating simple shapes from the descriptions. However, the text parsing and output of these works still remain either at the 2D stage or confined to a single geometry. On the basis of these works, this paper used both Stanford Scene Graph Parser (Sebastian et al. 2015) and graph convolutional networks (Kipf and Welling 2016) to compile the analytic semantic structure for the input texts, then generated the 3D architectural form expressed by the language descriptions, which is also aided by several optimization algorithms. To a certain extent, the training results approached the 3D form intended in the textual description, not only indicating the tremendous potential of LAFGM from linguistic input to 3D architectural form, but also innovating design expression and communication regarding 3D spatial information.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	acadia20_110
id	acadia20_110
authors	Zhang, Mengni; Dewey, Clara; Kalantari, Saleh
year	2020
title	Dynamic Anthropometric Modeling Interface
doi	https://doi.org/10.52842/conf.acadia.2020.1.110
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. 110-119.
summary	In this paper, we propose a Kinect-based Dynamic Anthropometric Modeling Interface (DAMI), built in Rhinoceros with Grasshopper for patient room layout optimization and nurse posture evaluations. Anthropometry is an important field that studies human body measurements to help designers improve product ergonomics and reduce negative health consequences such as musculoskeletal disorders (MSDs). Unlike existing anthropometric tools, which rely on generic human body datasets and static posture models, DAMI tracks and records user postures in real time, creating custom 3D body movement models that are typically absent in current space-planning practices. A generic hospital patient room, which contains complex and ergonomically demanding activities for nurses, was selected as an initial testing environment. We will explain the project background, the methods used to develop DAMI, and demonstrate its capabilities. There are two main goals DAMI aims to achieve. First, as a generative tool, it will reconstruct dynamic body point cloud models, which will be used as input for optimizing room layout during a project’s schematic design phase. Second, as an evaluation tool, by encoding and visualizing the Rapid Entire Body Assessment (REBA) scores, DAMI will illustrate the spatiotemporal relationship between nurse postures and the built environment during a project’s construction phase or post occupancy evaluation. We envision a distributed system of Kinect sensors to be embedded in various hospital rooms to help architects, planners, and facility managers improve nurse work experiences through better space planning.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	ecaade2020_258
id	ecaade2020_258
authors	Zhang, Ran, Waibel, Christoph and Wortmann, Thomas
year	2020
title	Aerodynamic Shape Optimization for High-Rise Conceptual Design - Integrating and validating parametric design, (fast) fluid dynamics, structural analysis and optimization
doi	https://doi.org/10.52842/conf.ecaade.2020.1.037
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. 37-45
summary	Using an integrated workflow with parametric design, Computational Fluid Dynamic (CFD) and Fast Fluid Dynamic (FFD) simulations, structural analysis and optimization, this paper evaluates the relative suitability of CFD and FFD simulations for Aerodynamic Shape Optimization (ASO). Specifically, it applies RBFOpt, a model-based optimization algorithm, to the ASO of a supertall high-rise. The paper evaluates the accuracy of the CFD and FDD simulations relative to a slower, more exact CFD simulation, and the performance of the model-based optimization algorithm relative to CMA-ES, an evolutionary algorithm. We conclude that FFD is useful for relative comparisons, such as for optimization, but less accurate than CFD in terms of absolute quantities. Although results tend to be similar, CMA-ES performs less well than RBFOpt for both large and small numbers of simulations, and for both CFD and FFD. RBFOpt with FFD emerges as the most suitable method for conceptual design, as it is much faster and only slightly less effective than RBFOpt with CFD.
keywords	Aerodynamic Shape Optimization; Computational Fluid Dynamics (CFD); Fast Fluid Dynamics (FFD); Model-based Optimization; High-rise Conceptual Design
series	eCAADe
email
last changed	2022/06/07 07:57

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