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	caadria2020_088
id	caadria2020_088
authors	Kado, Keita, Furusho, Genki, Nakamura, Yusuke and Hirasawa, Gakuhito
year	2020
title	rocess Path Derivation Method for Multi-Tool Processing Machines Using Deep-Learning-Based Three Dimensional Shape Recognition
doi	https://doi.org/10.52842/conf.caadria.2020.2.609
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. 609-618
summary	When multi-axis processing machines are employed for high-mix, low-volume production, they are operated using a dedicated computer-aided design/ computer-aided manufacturing (CAD/CAM) process that derives an operating path concurrently with detailed modeling. This type of work requires dedicated software that occasionally results in complicated front-loading and data management issues. We proposed a three-dimensional (3D) shape recognition method based on deep learning that creates an operational path from 3D part geometry entered by a CAM application to derive a path for processing machinery such as a circular saw, drill, or end mill. The methodology was tested using 11 joint types and five processing patterns. The results show that the proposed method has several practical applications, as it addresses wooden object creation and may also have other applications.
keywords	Three-dimensional Shape Recognition; Deep Learning; Digital Fabrication; Multi-axis Processing Machine
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	acadia20_220p
id	acadia20_220p
authors	Rieger, Uwe; Liu, Yinan
year	2020
title	LightWing II
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. 220-225
summary	LightWing II is an immersive XR installation that explores hybrid design strategies equally addressing physical and digital design parameters. The interactive project links a kinetic structure with dynamic digital information in the form of 3D projected imagery and spatial sound. A key component of the project was the development of a new rendering principle that allows the accurate projection of stereoscopic images on a moving target screen. Using simple red/cyan cardboard glasses, the system expands the applications of contemporary AR headsets beyond an isolated viewing towards a communal multi-viewer event. LightWing`s construction consists of thin flexible carbon fibre rods used to tension an almost invisible mesh screen. The structure is asymmetrically balanced on a single pin joint and monitored by an IMU. A light touch sets the delicate wing-like object into a rotational oscillation. As a ‘hands-on’ experience, LightWing II creates a mysterious sensation of tactile data and enables the user to navigate through holographic narratives assembled in four scenes, including the interaction with swarms of three winged creatures, being immersed in a silky bubble, and a journey through a velvet wormhole. The user interface is dissolved through the direct linkage between the physical construction and the dynamic digital content. The project was developed at the arc/sec Lab at the University of Auckland. The Lab explores user responsive constructions where dynamic properties of the virtual world influence the material world and vice versa. The Lab’s vision is to re-connect the intangible computer world to the multisensory qualities of architecture and urban spaces. With a focus on intuitive forms of user interaction, the arc/sec Lab uses large-scale prototypes and installations as the driving method for both the development and the demonstration of new cyber-physical design principles.
series	ACADIA
type	project
email
last changed	2021/10/26 08:08

_id	ecaade2020_032
id	ecaade2020_032
authors	Tuzun Canadinc, Seda, Wang, Bihan, Pi, Yalong and Yan, Wei
year	2020
title	Multi-User and Web-based Parametric Modeling with Multiple Visual Programming Tools
doi	https://doi.org/10.52842/conf.ecaade.2020.1.019
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. 19-28
summary	This paper presents a new framework for Web-based parametric modeling for design collaboration, allowing multiple users to work on the shared Web-based model in the process of building design and modeling, performance simulation, and optimization. The Web-based model viewer displays a shared model. Two visual programming tools: Grasshopper and Dynamo, are used on users' local computers connected to the Web. Two working prototypes of modeling methods were developed to control and modify building models on the Web. Two case studies with three tests each were conducted on a simplified residential building model. In Case Study 1, two simulated users tested the parametric capabilities on transformations including scaling, translation, and rotation of the shared Web-based model using Grasshopper and Dynamo. In Case Study 2, two simulated users collaborated on the shared Web-based model through Grasshopper in the process of optimization for different building performance objectives, in terms of daylight, energy use, and roof coverage. Web-based parametric modeling is expected to provide opportunities for collaboration in parametric design and optimization. Findings and technical limitations of the framework are discussed in the paper.
keywords	Web-based Modeling; Parametric Modeling; Optimization; Visual Programming; Collaborative Design; Building Performance Simulation
series	eCAADe
email
last changed	2022/06/07 07:58

_id	ecaade2020_093
id	ecaade2020_093
authors	Veloso, Pedro and Krishnamurti, Ramesh
year	2020
title	An Academy of Spatial Agents - Generating spatial configurations with deep reinforcement learning
doi	https://doi.org/10.52842/conf.ecaade.2020.2.191
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. 191-200
summary	Agent-based models rely on decentralized decision making instantiated in the interactions between agents and the environment. In the context of generative design, agent-based models can enable decentralized geometric modelling, provide partial information about the generative process, and enable fine-grained interaction. However, the existing agent-based models originate from non-architectural problems and it is not straight-forward to adapt them for spatial design. To address this, we introduce a method to create custom spatial agents that can satisfy architectural requirements and support fine-grained interaction using multi-agent deep reinforcement learning (MADRL). We focus on a proof of concept where agents control spatial partitions and interact in an environment (represented as a grid) to satisfy custom goals (shape, area, adjacency, etc.). This approach uses double deep Q-network (DDQN) combined with a dynamic convolutional neural-network (DCNN). We report an experiment where trained agents generalize their knowledge to different settings, consistently explore good spatial configurations, and quickly recover from perturbations in the action selection.
keywords	space planning; agent-based model; interactive generative systems; artificial intelligence; multi-agent deep reinforcement learning
series	eCAADe
email
last changed	2022/06/07 07:58

_id	acadia20_228
id	acadia20_228
authors	Alawadhi, Mohammad; Yan, Wei
year	2020
title	BIM Hyperreality
doi	https://doi.org/10.52842/conf.acadia.2020.1.228
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. 228-236.
summary	Deep learning is expected to offer new opportunities and a new paradigm for the field of architecture. One such opportunity is teaching neural networks to visually understand architectural elements from the built environment. However, the availability of large training datasets is one of the biggest limitations of neural networks. Also, the vast majority of training data for visual recognition tasks is annotated by humans. In order to resolve this bottleneck, we present a concept of a hybrid system—using both building information modeling (BIM) and hyperrealistic (photorealistic) rendering—to synthesize datasets for training a neural network for building object recognition in photos. For generating our training dataset, BIMrAI, we used an existing BIM model and a corresponding photorealistically rendered model of the same building. We created methods for using renderings to train a deep learning model, trained a generative adversarial network (GAN) model using these methods, and tested the output model on real-world photos. For the specific case study presented in this paper, our results show that a neural network trained with synthetic data (i.e., photorealistic renderings and BIM-based semantic labels) can be used to identify building objects from photos without using photos in the training data. Future work can enhance the presented methods using available BIM models and renderings for more generalized mapping and description of photographed built environments.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	caadria2020_254
id	caadria2020_254
authors	Pei, Wanyu, LO, TianTian and Guo, Xiangmin
year	2020
title	A Biofeedback Process: Detecting Architectural Space with the Integration of Emotion Recognition and Eye-tracking Technology
doi	https://doi.org/10.52842/conf.caadria.2020.2.263
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. 263-272
summary	This paper coincides with the conference theme that people have gradually become a vital force influencing the environmental system. In the future, it is necessary to study the influence of not only the built environment on people but also people's feedback on environmental design. This study explores the â€Žprocesses of interactive design using both emotion recognition and eye-tracking of users. By putting on wearable devices to roam and perceive in a virtual reality space, the physiological data of the users are collected in real-time and used to analyze their emotional responses and visual attention to the spaces. This method will provide an auxiliary way for non-architectural professional users to participate in architectural space design. At present, there is a lack of research on the comprehensive application of eye movement knowledge and emotional feedback in architectural space design. This integration will help professional designers to optimize the design of architectural space. For this paper, we review existing research and proposing an interactive design workflow that integrates eye tracking and emotion recognition. This workflow will help with the next stage of research to understand the design of a new International School of Design building.
keywords	Perception detection; Architectural space environment; Interactive design; Virtual reality
series	CAADRIA
email
last changed	2022/06/07 07:59

_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_375
id	caadria2020_375
authors	Kalo, Ammar, Tracy, Kenneth and Tam, Mark
year	2020
title	Robotic Sand Carving - Machining Techniques Derived from a Traditional Balinese Craft
doi	https://doi.org/10.52842/conf.caadria.2020.2.443
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. 443-452
summary	This paper presents research aimed at translating Ukiran Pasir Melela, traditional Balinese sand carving, into a new robotic-enabled framework for rapidly carving stiff but uncured cement sand blocks to create free-form and architecturally scalable unique volumetric elements. The research aims to reconsider vernacular materials and craft through their integration robotic manufacturing processes and how this activity can provide localized, low energy manufacturing solutions for building in the Anthropocene.Balinese sand carving shows potential advantages over current, and rather environmentally damaging, machining process primarily using soft materials state to make deep, smooth cuts into material with little torque. Transferring this manual and low-impact craft to robotic-enabled fabrication leverages heuristic knowledge developed over decades and opens possibilities for expanding and transforming these capabilities to increase the variability of potential future applications.
keywords	Robotic Fabrication; Computational Design; Traditional Craft
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	acadia20_170
id	acadia20_170
authors	Li, Peiwen; Zhu, Wenbo
year	2020
title	Clustering and Morphological Analysis of Campus Context
doi	https://doi.org/10.52842/conf.acadia.2020.2.170
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. 170-177.
summary	“Figure-ground” is an indispensable and significant part of urban design and urban morphological research, especially for the study of the university, which exists as a unique product of the city development and also develops with the city. In the past few decades, methods adapted by scholars of analyzing the figure-ground relationship of university campuses have gradually turned from qualitative to quantitative. And with the widespread application of AI technology in various disciplines, emerging research tools such as machine learning/deep learning have also been used in the study of urban morphology. On this basis, this paper reports on a potential application of deep clustering and big-data methods for campus morphological analysis. It documents a new framework for compressing the customized diagrammatic images containing a campus and its surrounding city context into integrated feature vectors via a convolutional autoencoder model, and using the compressed feature vectors for clustering and quantitative analysis of campus morphology.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	acadia20_426
id	acadia20_426
authors	Zohier, Islam; EL Antably, Ahmed; S. Madani, Ahmed
year	2020
title	An AI Lens on Historic Cairo
doi	https://doi.org/10.52842/conf.acadia.2020.1.426
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. 426-434.
summary	Reports show that numerous heritage sites are in danger due to conflicts and heritage mismanagement in many parts of the world. Experts have resorted to digital tools to attempt to conserve and preserve endangered and damaged sites. To that end, in this applied research, we aim to develop a deep learning framework applied to the decaying tangible heritage of Historic Cairo, known as “The City of a Thousand Minarets.” The proposed framework targets Cairo’s historic minaret styles as a test case study for the broader applications of deep learning in digital heritage. It comprises recognition and segmentation tasks, which use a deep learning semantic segmentation model trained on two data sets representing the two most dominant minaret styles in the city, Mamluk (1250–1517 CE) and Ottoman (1517–1952 CE). The proposed framework aims to classify these two types using images. It can help create a multidimensional model from just a photograph of a historic building, which can quickly catalog and document a historic building or element. The study also sheds light on the obstacles preventing the exploration and implementation of deep learning techniques in digital heritage. The research presented in this paper is a work-in-progress of a larger applied research concerned with implementing deep learning techniques in the digital heritage domain.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	acadia20_236p
id	acadia20_236p
authors	Anton, Ana; Jipa, Andrei; Reiter, Lex; Dillenburger, Benjamin
year	2020
title	Fast Complexity
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. 236-241
summary	The concrete industry is responsible for 8% of the global CO2 emissions. Therefore, using concrete in more complex and optimized shapes can have a significant benefit to the environment. Digital fabrication with concrete aims to overcome the geometric limitations of standardized formworks and thereby reduce the ecological footprint of the building industry. One of the most significant material economy potentials is in structural slabs because they represent 85% of the weight of multi-story concrete structures. To address this opportunity, Fast Complexity proposes an automated fabrication process for highly optimized slabs with ornamented soffits. The method combines reusable 3D-printed formwork (3DPF) and 3D concrete printing (3DCP). 3DPF uses binder-jetting, a process with submillimetre resolution. A polyester coating is applied to ensure reusability and smooth concrete surfaces otherwise not achievable with 3DCP alone. 3DPF is selectively used only where high-quality finishing is necessary, while all other surfaces are fabricated formwork-free with 3DCP. The 3DCP process was developed interdisciplinary at ETH Zürich and employs a two-component material system consisting of Portland cement mortar and calcium aluminate cement accelerator paste. This fabrication process provides a seamless transition from digital casting to 3DCP in a continuous automated process. Fast Complexity selectively uses two complementary additive manufacturing methods, optimizing the fabrication speed. In this regard, the prototype exhibits two different surface qualities, reflecting the specific resolutions of the two digital processes. 3DCP inherits the fine resolution of the 3DPF strictly for the smooth, visible surfaces of the soffit, for which aesthetics are essential. In contrast, the hidden parts of the slab use the coarse resolution specific to the 3DCP process, not requiring any formwork and implicitly achieving faster fabrication. In the context of an increased interest in construction additive manufacturing, Fast Complexity explicitly addresses the low resolution, lack of geometric freedom, and limited reinforcement options typical to layered extrusion 3DCP, as well as the limited customizability in concrete technology.
series	ACADIA
type	project
email
last changed	2021/10/26 08:08

_id	ecaade2020_089
id	ecaade2020_089
authors	Ardic, Sabiha Irem, Kirdar, Gulce and Lima, Angela Barros
year	2020
title	An Exploratory Urban Analysis via Big Data Approach: Eindhoven Case - Measuring popularity based on POIs, accessibility and perceptual quality parameters
doi	https://doi.org/10.52842/conf.ecaade.2020.2.309
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. 309-318
summary	The cities are equipped with the data as a result of the individuals' sharings and application usage. This significant amount of data has the potential to reveal relations and support user-centric decision making. The focus of the research is to examine the relational factors of the neighborhoods' popularity by implementing a big data approach to contribute to the problem of urban areas' degradation. This paper presents an exploratory urban analysis for Eindhoven at the neighborhood level by considering variables of popularity: density and diversity of points of interest (POI), accessibility, and perceptual qualities. The multi-sourced data are composed of geotagged photos, the location and types of POIs, travel time data, and survey data. These different datasets are evaluated using BBN (Bayesian Belief Network) to understand the relationships between the parameters. The results showed a positive and relatively high connection between popularity - population change, accessibility by walk - density of POIs, and the feeling of safety - social cohesion. For further studies, this approach can contribute to the decision-making process in urban development, specifically in real estate and tourism development decisions to evaluate the land prices or the hot-spot touristic places.
keywords	big data approach; neighborhood analysis; popularity; point of interest (POI); accessibility; perceptual quality
series	eCAADe
email
last changed	2022/06/07 07:54

_id	sigradi2020_260
id	sigradi2020_260
authors	Bhattacharya, Maharshi; Jung, Francisco
year	2020
title	Multi-Mission Space Exploration Vehicle (MMSEV) Nosecone Design Optimization
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. 260-266
summary	This paper addresses ergonomic drawbacks in NASA’s modular Multi-Mission Space Exploration Vehicle’s (MMSEV) latest prototype, 2B’s nosecone, to propose new iteration based on considerations such as mass minimization, visibility maximization, and structural integrity. With 2B as a benchmark, and using computational tools typically used in the AEC industry to carry out FEA analysis, comparisons are made with potential design changes. The numerical and visual data such as weight, and stress distribution, provided by the benchmark analysis, served as metrics for comparison and redesign. In turn, this design development exercise attempts to bring together the different design approaches to design, held by human- factors designers and structural engineers.
keywords	Form, Optimization, Finite Element Analysis, Space-Exploration Vehicle, Stress-Analysis
series	SIGraDi
email
last changed	2021/07/16 11:49

_id	ecaade2020_432
id	ecaade2020_432
authors	Fragkia, Vasiliki and Worre Foged, Isak
year	2020
title	Methods for the Prediction and Specification of Functionally Graded Multi-Grain Responsive Timber Composites
doi	https://doi.org/10.52842/conf.ecaade.2020.2.585
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. 585-594
summary	The paper presents design-integrated methods for high-resolution specification and prediction of functionally graded wood-based thermal responsive composites, using machine learning. The objective is the development of new circular design workflow, employing robotic fabrication, in order to predict fabrication files linked to material performance and design requirements, focused on application for intrinsic responsive and adaptive architectural surfaces. Through an experimental case study, the paper explores how machine learning can form a predictive design framework where low-resolution data can solve material systems at high resolution. The experimental computational and prototyping studies show that the presented image-based machine learning method can be adopted and adapted across various stages and scales of architectural design and fabrication. This in turn allows for a design-per-requirement approach that optimizes material distribution and promotes material economy.
keywords	material specification; responsive timber composites; machine learning; robotic fabrication; building envelopes
series	eCAADe
email
last changed	2022/06/07 07:50

_id	caadria2020_032
id	caadria2020_032
authors	Gu, Zhuoxing and Yang, Chunxia
year	2020
title	Generation of Public Space Structure Based on Digital Multi-agent System - Taking the interaction between self-consensus "Stigmergy" particles and the old city area as an example
doi	https://doi.org/10.52842/conf.caadria.2020.1.285
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. 285-294
summary	In the study, the ant colony behavior was simulated to establish a parametric multi-agent system with independent consensus "Stigmergy" for interaction with the site. In the experiment, the initial points of the particles correspond to the key historical buildings, and the target points correspond to the important public space nodes. Edit and adjust the motion characteristics, search features, generation and disappearance characteristics of the simulated particles to obtain the main consensus particle swarm distribution and the distributed consensus particle swarm distribution. This form has a compliant or conflicting relationship with the existing urban environment. Using the contours of the self-consensus spatial form, the particle swarm density, and the pointing relationship between the particles and the building can provide a basis for the transformation and renewal of the existing urban environment, thus forming a spatial transformation strategy that more closely matches the user behavior in the space.
keywords	Multi-agent system; Particle property construction; Stigmergy; Self-consensus particles; Public space structure
series	CAADRIA
email
last changed	2022/06/07 07:51

_id	ecaade2020_209
id	ecaade2020_209
authors	Han, Yoojin and Lee, Hyunsoo
year	2020
title	Investigating the Effectiveness of AR-enhanced Signage in Multi-purpose Commercial Complexes - Focusing on response time to directional signage
doi	https://doi.org/10.52842/conf.ecaade.2020.1.145
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. 145-152
summary	The aim of this study was to investigate next level digital signage utilizing augmented reality for multi-purpose commercial complexes. Recently, despite the rapid growth of the urban solution, mixed-use commercial complexes have experienced significant problems in terms of wayfinding. As a potential solution to the problem, this study sought to determine the effectiveness of state-of-the-art augmented reality (AR) on wayfinding. Focusing on the response time to directional signage, this study compared wayfinding through traditional signage with AR-enhanced signage. The response time in milliseconds was measured using a program developed with Python. In all, 30 sign images were presented to 48 participants in random order. A third of them included existing signs as the control condition, and the others were AR signs with half graphic and half text. The results of this study demonstrated that AR-enhanced signage had tremendous potential to improve wayfinding performance in multi-purpose commercial complexes. Results revealed that response time to directional signage was reduced in AR environments. In particular, the AR signage system combining text and graphics was useful in terms of both response time and cognitive appraisal.
keywords	Augmented Reality (AR); Signage; Wayfinding; Multi-purpose Commercial Complexes
series	eCAADe
email
last changed	2022/06/07 07:50

_id	acadia20_154p
id	acadia20_154p
authors	Josephson, Alex; Friedman, Jonathan; Salance, Benjamin; Vasyliv, Ivan; Melnichuk, Tim
year	2020
title	Gusto: Rationalizing Computational Masonry Design
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. 154-159
summary	Gusto 501 is a multi-level Infill Building on the footprint of an old car garage. Surrounded by an overpass and former factories, the restaurant and event spaces take the form of a ‘Hyper garage’ as a nod to its urban context. The interior is punctuated with standard terracotta blocks formed to create an intricate play of shadows during the day and embedded with LEDs to provide atmospheric illumination at night. The client's vision, our narrative, and the program demanded an innovative use of the primal material: terracotta. The scale of the project required the use of 3,700 blocks. Within the array wrapped around a 50ft tall interior volume, each block needed to be formed and sequenced uniquely to maintain structural integrity and interface with building systems, and express the sculptural qualities our team had designed. Standard approaches to the masonry could not achieve the effects our team was striving for - we had to develop our ground-up process to manufacture and install mass-customized masonry. The design process involved an algorithmic approach to a series of cuts and geometric manipulations to the blocks that allowed for near-endless combinations/configurations to create a dynamic interior facade system. Partisans, partnering with a terracotta block manufacturer, a local mason, and a masonry engineer, pursued simplifying production using wire cutter systems. Digital and physical mock-ups were then used to create a robust library of parameterized design criteria that optimized corbelling, grout thickness, weight, and fabrication complexity. Working sets of drawings were automated through a fully integrated BIM model, simplifying and speeding up installation. The challenge of marrying these processes with the physical realities of installation required another level of collaboration that included the masons themselves and the electricians who would eventually combine lighting systems into the sculpted block array.
series	ACADIA
type	project
email
last changed	2021/10/26 08:03

_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	ecaade2020_411
id	ecaade2020_411
authors	Muehlbauer, Manuel, Song, Andy and Burry, Jane
year	2020
title	Smart Structures - A Generative Design Framework for Aesthetic Guidance in Structural Node Design - Application of Typogenetic Design for Custom-Optimisation of Structural Nodes
doi	https://doi.org/10.52842/conf.ecaade.2020.1.623
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. 623-632
summary	Virtual prototypes enable performance simulation for building components. The presented research extended the application of generative design using virtual prototypes for interactive optimisation of structural nodes. User-interactivity contributed to the geometric definition of design spaces rather than the final geometric outcome, enabling another stage of generative design for the micro-structure of the structural node. In this stage, the micro-structure inside the design space was generated using fixed topology. In contrast to common optimisation strategies, which converge towards a single optimal outcome, the presented design exploration process allowed the regular review of design solutions. User-based selection guided the evolutionary process of design space exploration applying Online Classification. Another guidance mechanism called Shape Comparison introduced an intelligent control system using an inital image input as design reference. In this way, aesthetic guidance enabled the combined evaluation of quantitative and qualitative criteria in the custom-optimisation of structural nodes. Interactive node design extended the potential for shape variation of custom-optimized structural nodes by addressing the geometric definition of design spaces for multi-scalar structural optimisation.
keywords	generative design; evolutionary computation; interactive machine learning; typogenetic design
series	eCAADe
email
last changed	2022/06/07 07:58

_id	acadia20_170p
id	acadia20_170p
authors	Pawlowska, Gosia
year	2020
title	Viscous Catenary
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. 170-175
summary	Viscous Catenary is a free-form architectural glass structure that embeds material logic in a distributed system. Multi-curved panels are joined in a ‘catenary channel glass’ assembly, expressing the inherent behavior of the material at high temperatures. Float glass will typically achieve a level of viscosity at 1200°F (650°C), formed in a kiln by draping or “slumping. This hybrid fabrication process combines low-tech hardware and modern digital technologies. Glass panels were formed in a traditional kiln over a set of interchangeable waterjet-cut steel profiles or a repositionable tooling system. Parametric design in Grasshopper was essential to establish a discrete number of unique formwork elements and subdivide the overall geometry by panel size. In this case, each panel in the system was draped over four steel profiles. The formwork encourages a specific curvature in the glass, most precisely at the locations of folding. These moments of control allow the panels to align at their folds and join in an assembly by splice-lamination. Between the folds, the material remains free to shape itself, responding to its thickness, span, time, and temperature- into an undetermined “viscous catenary.” Selectively programming the geometry allows for a degree of material agency to remain in the system. This method differs from existing curved architectural glass, which would typically be pressed into a fully deterministic mold, leaving no opportunity for emergent morphologies. A pilot installation joined using transparent silicone adhesive achieved a height of 90cm with overlapping 30cm tall panels. Laser 3-d scanning between fabrication and assembly helped evaluate the fit between adjacent panels, identifying locations that required reinforcement. More research is needed to improve tolerances and overcome limitations in the adhesive before scaling up the fabrication system. Viscous Catenary succeeds in questioning the formal and structural potential of matter-driven curved architectural glass assemblies.
series	ACADIA
type	project
email
last changed	2021/10/26 08:03

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