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	ijac201917102
id	ijac201917102
authors	Cutellic, Pierre
year	2019
title	Towards encoding shape features with visual event-related potential based brain–computer interface for generative design
source	International Journal of Architectural Computing vol. 17 - no. 1, 88-102
summary	This article will focus on abstracting and generalising a well-studied paradigm in visual, event-related potential based brain–computer interfaces, for the spelling of characters forming words, into the visually encoded discrimination of shape features forming design aggregates. After identifying typical technologies in neuroscience and neuropsychology of high interest for integrating fast cognitive responses into generative design and proposing the machine learning model of an ensemble of linear classifiers in order to tackle the challenging features that electroencephalography data carry, it will present experiments in encoding shape features for generative models by a mechanism of visual context updating and the computational implementation of vision as inverse graphics, to suggest that discriminative neural phenomena of event-related potentials such as P300 may be used in a visual articulation strategy for modelling in generative design.
keywords	Generative design, machine learning, brain–computer interface, design computing and cognition, integrated cognition, neurodesign, shape, form and geometry, design concepts and strategies
series	journal
email
last changed	2019/08/07 14:04

_id	caadria2021_053
id	caadria2021_053
authors	Rhee, Jinmo and Veloso, Pedro
year	2021
title	Generative Design of Urban Fabrics Using Deep Learning
source	A. Globa, J. van Ameijde, A. Fingrut, N. Kim, T.T.S. Lo (eds.), PROJECTIONS - Proceedings of the 26th CAADRIA Conference - Volume 1, The Chinese University of Hong Kong and Online, Hong Kong, 29 March - 1 April 2021, pp. 31-40
doi	https://doi.org/10.52842/conf.caadria.2021.1.031
summary	This paper describes the Urban Structure Synthesizer (USS), a research prototype based on deep learning that generates diagrams of morphologically consistent urban fabrics from context-rich urban datasets. This work is part of a larger research on computational analysis of the relationship between urban context and morphology. USS relies on a data collection method that extracts GIS data and converts it to diagrams with context information (Rhee et al., 2019). The resulting dataset with context-rich diagrams is used to train a Wasserstein GAN (WGAN) model, which learns how to synthesize novel urban fabric diagrams with the morphological and contextual qualities present in the dataset. The model is also trained with a random vector in the input, which is later used to enable parametric control and variation for the urban fabric diagram. Finally, the resulting diagrams are translated to 3D geometric entities using computer vision techniques and geometric modeling. The diagrams generated by USS suggest that a learning-based method can be an alternative to methods that rely on experts to build rule sets or parametric models to grasp the morphological qualities of the urban fabric.
keywords	Deep Learning; Urban Fabric; Generative Design; Artificial Intelligence; Urban Morphology
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	ecaade2023_259
id	ecaade2023_259
authors	Sonne-Frederiksen, Povl Filip, Larsen, Niels Martin and Buthke, Jan
year	2023
title	Point Cloud Segmentation for Building Reuse - Construction of digital twins in early phase building reuse projects
source	Dokonal, W, Hirschberg, U and Wurzer, G (eds.), Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) - Volume 2, Graz, 20-22 September 2023, pp. 327–336
doi	https://doi.org/10.52842/conf.ecaade.2023.2.327
summary	Point cloud processing has come a long way in the past years. Advances in computer vision (CV) and machine learning (ML) have enabled its automated recognition and processing. However, few of those developments have made it through to the Architecture, Engineering and Construction (AEC) industry. Here, optimizing those workflows can reduce time spent on early-phase projects, which otherwise could be spent on developing innovative design solutions. Simplifying the processing of building point cloud scans makes it more accessible and therefore, usable for design, planning and decision-making. Furthermore, automated processing can also ensure that point clouds are processed consistently and accurately, reducing the potential for human error. This work is part of a larger effort to optimize early-phase design processes to promote the reuse of vacant buildings. It focuses on technical solutions to automate the reconstruction of point clouds into a digital twin as a simplified solid 3D element model. In this paper, various ML approaches, among others KPConv Thomas et al. (2019), ShapeConv Cao et al. (2021) and Mask-RCNN He et al. (2017), are compared in their ability to apply semantic as well as instance segmentation to point clouds. Further it relies on the S3DIS Armeni et al. (2017), NYU v2 Silberman et al. (2012) and Matterport Ramakrishnan et al. (2021) data sets for training. Here, the authors aim to establish a workflow that reduces the effort for users to process their point clouds and obtain object-based models. The findings of this research show that although pure point cloud-based ML models enable a greater degree of flexibility, they incur a high computational cost. We found, that using RGB-D images for classifications and segmentation simplifies the complexity of the ML model but leads to additional requirements for the data set. These can be mitigated in the initial process of capturing the building or by extracting the depth data from the point cloud.
keywords	Point Clouds, Machine Learning, Segmentation, Reuse, Digital Twins
series	eCAADe
email
last changed	2023/12/10 10:49

_id	caadria2019_345
id	caadria2019_345
authors	Marschall, Max and Burry, Jane
year	2019
title	Can the Use of Stochastic Models of Occupants' Environmental Control Behavior Influence Architectural Design Outcomes? - How field data can influence design outcomes
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 1, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 715-724
doi	https://doi.org/10.52842/conf.caadria.2019.1.715
summary	Thermal comfort research has shown that natural ventilation can reduce energy consumption while increasing comfort. However, giving occupants control over their environment introduces uncertainty into building performance which is challenging to emulate using current simulation techniques. Traditionally, window operation is modelled deterministically, for instance by assuming windows to be opened at a predefined temperature. Studies have shown this to be inaccurate, often causing large discrepancies between simulated and actual performance; instead, probabilistic models have emerged based on field study data. The literature on this topic is currently limited to building science and lacks an analysis of how these insights may affect architecture. In a design study, we used evolutionary computation to determine comfort-optimized housing designs for various climates, each time comparing the results of both window operation models. The resulting designs varied considerably; most notably, using the stochastic approach resulted in more shading elements, especially in warmer climates.
keywords	window operation model; stochastic; natural ventilation; thermal comfort; occupant behavior
series	CAADRIA
email
last changed	2022/06/07 07:59

_id	caadria2019_093
id	caadria2019_093
authors	Shahsavari, Fatemeh, Koosha, Rasool and Yan, Wei
year	2019
title	Uncertainty and Sensitivity Analysis Using Building Information Modeling - (An Energy Analysis Test Case)
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 1, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 615-624
doi	https://doi.org/10.52842/conf.caadria.2019.1.615
summary	Building design decision-making is associated with uncertainties due to variations over time and unpredictable parameters. There is a growing demand for probabilistic methods, i.e., uncertainty and sensitivity analyses to handle the uncertainties in building design. This research intends to encourage the application of Building Information Modeling (BIM) for addressing design uncertainties affecting building energy performance. The mapping between BIM (Revit and Dynamo) and a customized model-based energy analysis tool in Excel is investigated to translate architectural models to energy models and conduct the probabilistic analyses. The application of this method is demonstrated with a test case of a hypothetical residential unit in College Station, Texas, USA. Input variables in this example are the thermal properties of building elements, and the two simulation outputs are annual heating and cooling energy consumption, and deviation from comfort temperature. The results indicate the probability distribution of simulation outputs and the importance factor of each design input. This method deals with uncertainties and provides a more reliable and robust basis for design decision-making.
keywords	building design decision-making ; Building Information Modeling (BIM); Parametric design; Uncertainty and sensitivity analysis; Building performance analysis
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	acadia19_596
id	acadia19_596
authors	Anton, Ana; Yoo, Angela; Bedarf, Patrick; Reiter, Lex; Wangler, Timothy; Dillenburger, Benjamin
year	2019
title	Vertical Modulations
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. 596-605
doi	https://doi.org/10.52842/conf.acadia.2019.596
summary	The context of digital fabrication allows architects to reinvestigate material, process and the design decisions they entail to explore novel expression in architecture. This demands a new approach to design thinking, as well as the relevant tools to couple the form of artefacts with the process in which they are made. This paper presents a customised computational design tool developed for exploring the novel design space of Concrete Extrusion 3D Printing (CE3DP), enabling a reinterpretation of the concrete column building typology. This tool allows the designer to access generative engines such as trigonometric functions and mesh subdivision through an intuitive graphical user interface. Balancing process efficiency as understood by our industry with a strong design focus, we aim to articulate the unique architectural qualities inherent to CE3DP, energising much needed innovation in concrete technology.
series	ACADIA
type	normal paper
email
last changed	2022/06/07 07:54

_id	ecaadesigradi2019_249
id	ecaadesigradi2019_249
authors	Chiarella, Mauro, Gronda, Luciana and Veizaga, Martín
year	2019
title	RILAB - architectural envelopes - From spatial representation (generative algorithm) to geometric physical optimization (scientific modeling)
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 3, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 17-24
doi	https://doi.org/10.52842/conf.ecaade.2019.3.017
summary	Augmented graphical thinking operates by integrating algorithmic, heuristic, and manufacturing processes. The Representation and Ideation Laboratory (RILAB-2018) exercise begins with the application of a parametric definition developed by the team of teachers, allowing for the construction of structural systems by the means of the combination of segmental shells and bending-active. The main objetive is the construction of a scientific model of simulation for bending-active laminar structures has brought into reality trustworthy previews for architectural envelopes through the interaction of parametrized relational variables. This way we put designers in a strategic role for the building of the pre-analysis models, allowing more preciseness at the time of picking and defining materials, shapes, spaces and technologies and thus minimizing the decisions based solely in the definition of structural typological categories, local tradition or direct experience. The results verify that the strategic integration of models of geometric physical optimization and spatial representation greatly expand the capabilities in the construction of the complex system that operates in the act of projecting architecture.
keywords	architectural envelopes; augmented graphic thinking; geometric optimization; bending-active
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:55

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

_id	cdrf2023_526
id	cdrf2023_526
authors	Eric Peterson, Bhavleen Kaur
year	2023
title	Printing Compound-Curved Sandwich Structures with Robotic Multi-Bias Additive Manufacturing
source	Proceedings of the 2023 DigitalFUTURES The 5st International Conference on Computational Design and Robotic Fabrication (CDRF 2023)
doi	https://doi.org/https://doi.org/10.1007/978-981-99-8405-3_44
summary	A research team at Florida International University Robotics and Digital Fabrication Lab has developed a novel method for 3d-printing curved open grid core sandwich structures using a thermoplastic extruder mounted on a robotic arm. This print-on-print additive manufacturing (AM) method relies on the 3d modeling software Rhinoceros and its parametric software plugin Grasshopper with Kuka-Parametric Robotic Control (Kuka-PRC) to convert NURBS surfaces into multi-bias additive manufacturing (MBAM) toolpaths. While several high-profile projects including the University of Stuttgart ICD/ITKE Research Pavilions 2014–15 and 2016–17, ETH-Digital Building Technologies project Levis Ergon Chair 2018, and 3D printed chair using Robotic Hybrid Manufacturing at Institute of Advanced Architecture of Catalonia (IAAC) 2019, have previously demonstrated the feasibility of 3d printing with either MBAM or sandwich structures, this method for printing Compound-Curved Sandwich Structures with Robotic MBAM combines these methods offering the possibility to significantly reduce the weight of spanning or cantilevered surfaces by incorporating the structural logic of open grid-core sandwiches with MBAM toolpath printing. Often built with fiber reinforced plastics (FRP), sandwich structures are a common solution for thin wall construction of compound curved surfaces that require a high strength-to-weight ratio with applications including aerospace, wind energy, marine, automotive, transportation infrastructure, architecture, furniture, and sports equipment manufacturing. Typical practices for producing sandwich structures are labor intensive, involving a multi-stage process including (1) the design and fabrication of a mould, (2) the application of a surface substrate such as FRP, (3) the manual application of a light-weight grid-core material, and (4) application of a second surface substrate to complete the sandwich. There are several shortcomings to this moulded manufacturing method that affect both the formal outcome and the manufacturing process: moulds are often costly and labor intensive to build, formal geometric freedom is limited by the minimum draft angles required for successful removal from the mould, and customization and refinement of product lines can be limited by the need for moulds. While the most common material for this construction method is FRP, our proof-of-concept experiments relied on low-cost thermoplastic using a specially configured pellet extruder. While the method proved feasible for small representative examples there remain significant challenges to the successful deployment of this manufacturing method at larger scales that can only be addressed with additional research. The digital workflow includes the following steps: (1) Create a 3D digital model of the base surface in Rhino, (2) Generate toolpaths for laminar printing in Grasshopper by converting surfaces into lists of oriented points, (3) Generate the structural grid-core using the same process, (4) Orient the robot to align in the direction of the substructure geometric planes, (5) Print the grid core using MBAM toolpaths, (6) Repeat step 1 and 2 for printing the outer surface with appropriate adjustments to the extruder orientation. During the design and printing process, we encountered several challenges including selecting geometry suitable for testing, extruder orientation, calibration of the hot end and extrusion/movement speeds, and deviation between the computer model and the physical object on the build platen. Physical models varied from their digital counterparts by several millimeters due to material deformation in the extrusion and cooling process. Real-time deviation verification studies will likely improve the workflow in future studies.
series	cdrf
email
last changed	2024/05/29 14:04

_id	acadia19_40
id	acadia19_40
authors	Garcia del Castillo y López, Jose Luis
year	2019
title	Robot Ex Machina
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. 40-49
doi	https://doi.org/10.52842/conf.acadia.2019.040
summary	Industrial robotic arms are increasingly present in digital fabrication workflows due to their robustness, degrees of freedom, and potentially large scale. However, the range of possibilities they provide is limited by their typical software control paradigms, specifically offline programming. This model requires all the robotic instructions to be pre-defined before execution, a possibility only affordable in highly predictable environments. But in the context of architecture, design and art, it can hardly accommodate more complex forms of control, such as responding to material feedback, adapting to changing conditions on a construction site, or on-the-fly decision-making. We present Robot Ex Machina, an open-source computational framework of software tools for real-time robot programming and control. The contribution of this framework is a paradigm shift in robot programming models, systematically providing a platform to enable real-time interaction and control of mechanical actuators. Furthermore, it fosters programming styles that are reactive to, rather than prescriptive about, the state of the robot. We argue that this model is, compared to traditional offline programming, beneficial for creative individuals, as its concurrent nature and immediate feedback provide a deeper and richer set of possibilities, facilitates experimentation, flow of thought, and creative inquiry. In this paper, we introduce the framework, and discuss the unifying model around which all its tools are designed. Three case studies are presented, showcasing how the framework provides richer interaction models and novel outcomes in digital making. We conclude by discussing current limitations of the model and future work.
series	ACADIA
type	normal paper
email
last changed	2022/06/07 07:51

_id	cf2019_039
id	cf2019_039
authors	Guo, Fei ; Eduardo Castro e Costa, Jose Duarte and Shadi Nazarian
year	2019
title	Computational Implementation of a Tool for Generative Design of High-rise Residential Building Facades
source	Ji-Hyun Lee (Eds.) "Hello, Culture!" [18th International Conference, CAAD Futures 2019, Proceedings / ISBN 978-89-89453-05-5] Daejeon, Korea, pp. 301-316
summary	We propose a computational design tool that aims to provide more variety to the design of high-rise residential building facades. In contemporary cities, the pressure to build many high-rise residential buildings leaves little time to focus on facade design, resulting in repetitive facades that impart a monotonous appearance to cities. We propose a computational tool that can help to improve facade variety, based on shape grammars and parametric modeling. Shape grammars are used to analyze facade composition and to structure design knowledge. Subsequently, the grammars are converted into parametric models, which are implemented using the Python programming language that can be used to generate designs in CAD software. The resulting tool encodes a general parametric model that manipulates the rules of formal composition of building facades. Without limitations from software, the program takes advantage of the high-processing power of the computer to provide many design solutions from which architects can choose.
keywords	Variety, Facades, Computational Design, Parametric Modeling, Shape Grammar
series	CAAD Futures
email
last changed	2019/07/29 14:15

_id	acadia19_16
id	acadia19_16
authors	Hosmer, Tyson; Tigas, Panagiotis
year	2019
title	Deep Reinforcement Learning for Autonomous Robotic Tensegrity (ART)
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. 16-29
doi	https://doi.org/10.52842/conf.acadia.2019.016
summary	The research presented in this paper is part of a larger body of emerging research into embedding autonomy in the built environment. We develop a framework for designing and implementing effective autonomous architecture defined by three key properties: situated and embodied agency, facilitated variation, and intelligence.We present a novel application of Deep Reinforcement Learning to learn adaptable behaviours related to autonomous mobility, self-structuring, self-balancing, and spatial reconfiguration. Architectural robotic prototypes are physically developed with principles of embodied agency and facilitated variation. Physical properties and degrees of freedom are applied as constraints in a simulated physics-based environment where our simulation models are trained to achieve multiple objectives in changing environments. This holistic and generalizable approach to aligning deep reinforcement learning with physically reconfigurable robotic assembly systems takes into account both computational design and physical fabrication. Autonomous Robotic Tensegrity (ART) is presented as an extended case study project for developing our methodology. Our computational design system is developed in Unity3D with simulated multi-physics and deep reinforcement learning using Unity’s ML-agents framework. Topological rules of tensegrity are applied to develop assemblies with actuated tensile members. Single units and assemblies are trained for a series of policies using reinforcement learning in single-agent and multi-agent setups. Physical robotic prototypes are built and actuated to test simulated results.
series	ACADIA
type	normal paper
email
last changed	2022/06/07 07:50

_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	acadia19_50
id	acadia19_50
authors	Ibrahim, Nazim; Joyce, Sam Conrad
year	2019
title	User Directed Parametric Design for Option Exploration
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. 50-59
doi	https://doi.org/10.52842/conf.acadia.2019.050
summary	The potential of parametric associative models to explore large ranges of different designs is limited by our ability to manually create and modify them. While computation has been successfully used to generate variations by optimizing input parameters, adding or changing ‘components’ and ‘links’ of these models has typically been manual and human driven. The intellectual overhead and challenges of manually creating and maintaining complex parametric models has limited their usefulness in early stages of design exploration, where a quicker and wider design search is preferred. Recent methods called Meta Parametric Design using Cartesian Genetic Programming (CGP) specifically tailored to operate on parametric models, allows computational generation and topological modification for parametric models. This paper proposes the refinement of Meta Parametric techniques to quickly generate and manipulate models with a higher level of control than existing; enabling a more natural human centric user-directed design exploration process. Opening new possibilities for the computer to act as a co-creator: able to generate its own novel solutions, steered at a high-level by user(s) and able to develop convergent or divergent solutions over an extended interaction session, replicating in a faster way a human design assistant.
series	ACADIA
type	normal paper
email
last changed	2022/06/07 07:50

_id	ecaadesigradi2019_073
id	ecaadesigradi2019_073
authors	Junk, Stefan, Niederhüfner, Michelle, Borkowska, Nina and Schrock, Steffen
year	2019
title	Direct Digital Manufacturing of Architectural Models using Binder Jetting and Polyjet Modeling
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 1, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 451-456
doi	https://doi.org/10.52842/conf.ecaade.2019.1.451
summary	Today, architectural models are an important tool for illustrating drawn-on plans or computer-generated virtual models and making them understandable. In addition to the conventional methods for the manufacturing of physical models, a wide range of processes for Direct Digital Manufacturing (DDM) has spread rapidly in recent years. In order to facilitate the application of these new methods for architects, this contribution examines which technical and economic results are possible using 3D printed architectural models. Within a case study, it will be shown on the basis of a multi-storey detached house, which kind of data preparation is necessary. The DDM of architectural models will be demonstrated using two widespread techniques and the resulting costs will be compared.
keywords	Architeetual model; CAAD; Direct Digital Manufacturing; Binder Jetting; Polyjet Modelling
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:52

_id	cf2019_042
id	cf2019_042
authors	Khan, Sumbul; Bige Tuncer, Ramanathan Subramanian and Lucienne Blessing
year	2019
title	3D CAD modeling using gestures and speech: Investigating CAD legacy and non-legacy procedures
source	Ji-Hyun Lee (Eds.) "Hello, Culture!" [18th International Conference, CAAD Futures 2019, Proceedings / ISBN 978-89-89453-05-5] Daejeon, Korea, pp. 347-366
summary	3D CAD modeling using natural interaction techniques necessitates greater research into the modeling procedures employed by users. In a previously conducted experiment, we elicited speech and gestures input for 3D CAD modeling tasks for conceptual design. In this paper, we examine the 3D modeling procedures articulated by the participants, using gestures and speech, for creating basic 3D models of increasing complexity. We identified 3D modeling procedures and characterized them as CAD legacy and non-legacy procedures. Results show that (1) non-legacy procedures were employed by a considerable number of participants who had fair and high proficiency in CAD and (2) Non-legacy procedures with fewer steps were rated favorably by participants. Based on the results, we provide recommendations on key aspects of non-legacy procedures that need to be incorporated in CAD modeling programs to facilitate speech and gestural input.
keywords	Gestures, 3D CAD modeling, Human Computer Interaction, computer aided design, natural interaction
series	CAAD Futures
email
last changed	2019/07/29 14:15

_id	ecaadesigradi2019_339
id	ecaadesigradi2019_339
authors	Kinugawa, Hina and Takizawa, Atsushi
year	2019
title	Deep Learning Model for Predicting Preference of Space by Estimating the Depth Information of Space using Omnidirectional Images
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 2, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 61-68
doi	https://doi.org/10.52842/conf.ecaade.2019.2.061
summary	In this study, we developed a method for generating omnidirectional depth images from corresponding omnidirectional RGB images of streetscapes by learning each pair of omnidirectional RGB and depth images created by computer graphics using pix2pix. Then, the models trained with different series of images shot under different site and weather conditions were applied to Google street view images to generate depth images. The validity of the generated depth images was then evaluated visually. In addition, we conducted experiments to evaluate Google street view images using multiple participants. We constructed a model that estimates the evaluation value of these images with and without the depth images using the learning-to-rank method with deep convolutional neural network. The results demonstrate the extent to which the generalization performance of the streetscape evaluation model changes depending on the presence or absence of depth images.
keywords	Omnidirectional image; depth image; Unity; Google street view; pix2pix; RankNet
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:52

_id	acadia19_522
id	acadia19_522
authors	Kohler, Daniel; Galika, Anna; Pu, Qiuru; Bai, Junyi
year	2019
title	Blockerties
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. 522-531
doi	https://doi.org/10.52842/conf.acadia.2019.522
summary	The paper aims for new urban forms of property enabled by computation models of distributed ledgers as they are currently being deployed with technologies like Blockchain. Distributed ledgers promise to constitute whole environments by chaining and sharing blocks of data. Upscaling this prospective, the paper describes objects with unique and strong compositional characteristics that act as closed black boxes and are able through distribution to create large scale effects. The final result of the nesting is the Interchain, a chain of chains that initiate with the characteristics of the contributing chains, and due to the distribution, unprecedented patterns arise. The resulting Interchain, observed with spatial and architectural characteristics, can project a new building form and a new urban model based on blockchain theory.
series	ACADIA
type	normal paper
email
last changed	2022/06/07 07:51

_id	ecaadesigradi2019_412
id	ecaadesigradi2019_412
authors	Leit?o de Souza, Thiago, Fialho, Valéria, Bicalho, Giovany, Schelk, Vinicius and Mendes, Isabella
year	2019
title	An Immersive 360° Experience in Rio de Janeiro in the Late 19th Century - The panorama of Victor Meirelles and Henri Langerock
source	Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 3, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 107-114
doi	https://doi.org/10.52842/conf.ecaade.2019.3.107
summary	This essay is related to the research project "The immersive experience in 360°: investigation, representation and digital immersion in the city of Rio de Janeiro in the 19th and 20th centuries", developed at PROURB in FAU-UFRJ, Rio de Janeiro/Brazil. This work will investigate the Panorama of Rio de Janeiro looking for memories and historical truths in its context: Which part represents a historical point of view? Which part is invention? How were the city and its landscape represented on the canvas? As the most well-known Rio de Janeiro's panorama, which project was idealized by the Brazilian painter Victor Meirelles de Lima (1832-1903) and the Belgian photo-painter Henri Charles Langerock (1830-1915), it was exhibited in Brussels 1888, Paris 1889, and Rio de Janeiro 1891-1896, with great recognition in all these cities. This paper will explore this Panorama, its initial studies, its landscape and the architecture depicted, newspapers descriptions of its exhibitions, and mainly, distinguishing among memories, historical truths and verisimilitudes. In order to achieve these objectives, digital and analogical systems of representations, sketches and computer graphics techniques, specially, tridimensional models will be developed and applied.
keywords	Panorama of Rio de Janeiro; Immersive experience in 360°; Geolocation; Virtual Reality; Digital Technologies; Cultural Heritage
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:52

_id	caadria2019_081
id	caadria2019_081
authors	Sheldon, Aron, Dobbs, Tiara, Fabbri, Alessandra, Gardner, Nicole, Haeusler, M. Hank, Ramos, Cristina and Zavoleas, Yannis
year	2019
title	Putting the AR in (AR)chitecture - Integrating voice recognition and gesture control for Augmented Reality interaction to enhance design practice
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 1, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 475-484
doi	https://doi.org/10.52842/conf.caadria.2019.1.475
summary	The architectural design process involves the development of spatial explorable 3D models, but the computer screen is main medium to communicate information to clients. Yet, Augmented Reality (AR) and Virtual Reality (VR) are the closest way to replicate our world, create new ones and interact within them. AR and VR headsets offer different ways to allow multiple stakeholders to effectively immerse themselves in 3D representations of design projects. But, to interact within these spaces and to perform design modifications, the development of new workflows is required. This research presents a new method where AR is used to visualize and edit project models using both voice recognition and hand-gestures software. While numerous projects are addressing software interoperability issues, user-interaction in an AR space remains a developing area of crucial relevance in research. Although hand-gestures are the usual form of model-state control employed in such systems, voice-control is emerging as a highly desirable and everyday form of human-computer interaction. This paper presents a plugin for the Hololens that allows the user to use voice and hand gestures to enhance the ability to work with 3D models and discusses and evaluates the project.
keywords	Augmented Reality; Design Workflows; Interaction Design; Voice Recogition; Gesture Recognition
series	CAADRIA
email
last changed	2022/06/07 07:56

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