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

PDF papers
References

Hits 1 to 20 of 572

Reformat results as: short short into frame detailed detailed into frame

_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	ecaade2021_203
id	ecaade2021_203
authors	Arora, Hardik, Bielski, Jessica, Eisenstadt, Viktor, Langenhan, Christoph, Ziegler, Christoph, Althoff, Klaus-Dieter and Dengel, Andreas
year	2021
title	Consistency Checker - An automatic constraint-based evaluator for housing spatial configurations
source	Stojakovic, V and Tepavcevic, B (eds.), Towards a new, configurable architecture - Proceedings of the 39th eCAADe Conference - Volume 2, University of Novi Sad, Novi Sad, Serbia, 8-10 September 2021, pp. 351-358
doi	https://doi.org/10.52842/conf.ecaade.2021.2.351
summary	The gradual rise of artificial intelligence (AI) and its increasing visibility among many research disciplines affected Computer-Aided Architectural Design (CAAD). Architectural deep learning (DL) approaches are being developed and published on a regular basis, such as retrieval (Sharma et al. 2017) or design style manipulation (Newton 2019; Silvestre et al. 2016). However, there seems to be no method to evaluate highly constrained spatial configurations for specific architectural domains (such as housing or office buildings) based on basic architectural principles and everyday practices. This paper introduces an automatic constraint-based consistency checker to evaluate the coherency of semantic spatial configurations of housing construction using a small set of design principles to evaluate our DL approaches. The consistency checker informs about the overall performance of a spatial configuration followed by whether it is open/closed and the constraints it didn't satisfy. This paper deals with the relation of spaces processed as mathematically formalized graphs contrary to existing model checking software like Solibri.
keywords	model checking, building information modeling, deep learning, data quality
series	eCAADe
email
last changed	2022/06/07 07:54

_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	caadria2017_029
id	caadria2017_029
authors	Sun, Zheng and Cao, Yong Kang
year	2017
title	Applications of Integrated Digital Technologies for Surveying Tibetan Architectural Heritage:Three Years of Experiences
source	P. Janssen, P. Loh, A. Raonic, M. A. Schnabel (eds.), Protocols, Flows, and Glitches - Proceedings of the 22nd CAADRIA Conference, Xi'an Jiaotong-Liverpool University, Suzhou, China, 5-8 April 2017, pp. 663-672
doi	https://doi.org/10.52842/conf.caadria.2017.663
summary	Absence of reliable and accurate surveying of Tibetan architectural heritage has long been a major constraint for architects, architectural historians and archeologists working in that region. Due to distinctive geographical environment and architectural typology, unique surveying technologies are required in Tibet. In the last three years, integrated digital surveying technologies are applied to architectural heritage in Gyantse, a Tibetan city. The aim of the surveying is to document and analyze local architectural heritage for potential technical intervention such as consolidation, restoration and renovation. Key technical issues ranging from reliability of consumer-level UAV to BIM-based platform are presented in the article. The conclusions are that digital technologies greatly improve architectural heritage surveying in Tibet in terms of accuracy, efficiency and versatility. Future works will be addressed in more robust algorithms for points cloud semantic segmentation, change detection of large-scale architectural heritage based on remotely sensed imagery over time, and data exchange and coordination between BIM and GIS, etc.
keywords	Architectural heritage; Digital survey; Tibet; UAV; BIM
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	acadia17_138
id	acadia17_138
authors	Berry, Jaclyn; Park, Kat
year	2017
title	A Passive System for Quantifying Indoor Space Utilization
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 138-145
doi	https://doi.org/10.52842/conf.acadia.2017.138
summary	This paper presents the development of a prototype for a new sensing device for anonymously evaluating space utilization, which includes usage factors such as occupancy levels, congregation and circulation patterns. This work builds on existing methods and technology for measuring building performance, human comfort and occupant experience in post-occupancy evaluations as well as pre-design strategic planning. The ability to collect data related to utilization and occupant experience has increased significantly due to the greater accessibility of sensor systems in recent years. As a result, designers are exploring new methods to empirically verify spatial properties that have traditionally been considered more qualitative in nature. With this premise, this study challenges current strategies that rely heavily on manual data collection and survey reports. The proposed sensing device is designed to supplement the traditional manual method with a new layer of automated, unbiased data that is capable of capturing environmental and social qualities of a given space. In a controlled experiment, the authors found that the data collected from the sensing device can be extrapolated to show how layout, spatial interventions or other design factors affect circulation, congregation, productivity, and occupancy in an office setting. In the future, this sensing device could provide designers with real-time feedback about how their designs influence occupants’ experiences, and thus allow the designers to base what are currently intuition-based decisions on reliable data and evidence.
keywords	design methods; information processing; smart buildings; IoT
series	ACADIA
email
last changed	2022/06/07 07:52

_id	ecaade2017_244
id	ecaade2017_244
authors	Chaltiel, Stephanie, Bravo, Maite and Chronis, Angelos
year	2017
title	Digital fabrication with Virtual and Augmented Reality for Monolithic Shells
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 2, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 211-218
doi	https://doi.org/10.52842/conf.ecaade.2017.2.211
summary	The digital fabrication of monolithic shell structures is presenting some challenges related to the interface between computational design and fabrication techniques, such as the methods chosen for the suitable parametrization of the geometry based on materiality characteristics and construction constrains, the digital optimization criteria of variables, and the translation of the relevant code used for digital fabrication. Specifically, the translation from the digital to the physical when a definite materiality appears during the digital fabrication process proves to be a crucial step, which is typically approached as a linear and predetermined sequence. This often-difficult step offers the potential of embedding a certain level of interactivity between the fabricator and the materialized model during the fabrication process in order to allow for real time adjustments or corrections. This paper features monolithic shell construction processes that promote a simple interface of live interaction between the fabricator and the tool control during the digital fabrication process. The implementation of novel digital and physical methods will be explored, offering the possibility of being combined with automated fabrication actions controlled by real time inputs with virtual reality [VR] influenced by 3d scanning and 3d CAD programs, and the possibility of incorporating augmented reality [AR].
keywords	virtual reality; augmented reality; monolithic shells
series	eCAADe
email
last changed	2022/06/07 07:55

_id	ecaade2017_041
id	ecaade2017_041
authors	Fukuda, Tomohiro, Kuwamuro, Yasuyuki and Yabuki, Nobuyoshi
year	2017
title	Optical Integrity of Diminished Reality Using Deep Learning
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 1, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 241-250
doi	https://doi.org/10.52842/conf.ecaade.2017.1.241
summary	A new method is proposed to improve diminished reality (DR) simulations to allow the demolition and removal of entire buildings in large-scale spaces. Our research goal was to obtain optical integrity by using a scientific and reliable simulation approach. Further, we tackled presumption of the texture of the background sky by applying deep learning. Our approach extracted the background sky using information from the actual sky obtained from a photographed image. This method comprised two steps: (1) detection of the sky area from the image through image segmentation and (2) creation of an image of the sky through image inpainting. The deep convolutional neural networks developed by us to train and predict images were evaluated to be feasible and effective.
keywords	Diminished Reality; Optical Integrity; Deep Learning; Augmented Reality; Landscape assessment
series	eCAADe
email
last changed	2022/06/07 07:50

_id	ecaade2023_44
id	ecaade2023_44
authors	Mayrhofer-Hufnagl, Ingrid and Ennemoser, Benjamin
year	2023
title	From Linear to Manifold Interpolation: Exemplifying the paradigm shift through interpolation
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. 419–429
doi	https://doi.org/10.52842/conf.ecaade.2023.2.419
summary	The advent of artificial intelligence, specifically neural networks, has marked a significant turning point in the field of computation. During such transformative times, we are often faced with a dearth of appropriate vocabulary, which forces us to rely on existing terms, regardless of their inadequacy. This paper argues that the term “interpolation,” typically used in deep learning (DL), is a prime example of this phenomenon. It is not uncommon for beginners to misunderstand its meaning, as DL pioneer Francois Chollet (2017) has noted. This misreading is especially true in the discipline of architecture, and this study aims to demonstrate how the meaning of “interpolation” has evolved in the second digital turn. We begin by illustrating, using 2D data, the difference between linear interpolation in the context of topological figures and its use in DL algorithms. We then demonstrate how 3DGANs can be employed to interpolate across different topologies in complex 3D space, highlighting the distinction between linear and manifold interpolation. In both 2D and 3D examples, our results indicate that the process does not involve continuous morphing but instead resembles the piecing together of a jigsaw puzzle to form many parts of a larger ambient space. Our study reveals how previous architectural research on DL has employed the term “interpolation” without clarifying the crucial differences from its use in the first digital turn. We demonstrate the new possibilities that manifold interpolation offers for architecture, which extend well beyond parametric variations of the same topology.
keywords	Interpolation, 3D Generative Adversarial Networks, Deep Learning, Hybrid Space
series	eCAADe
email
last changed	2023/12/10 10:49

_id	ecaade2017_271
id	ecaade2017_271
authors	Narahara, Taro
year	2017
title	Collective Construction Modeling and Machine Learning: Potential for Architectural Design
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 2, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 341-348
doi	https://doi.org/10.52842/conf.ecaade.2017.2.341
summary	Recently, there are significant developments in artificial intelligence using advanced machine learning algorithms such as deep neural networks. These new methods can defeat human expert players in strategy-based board games such as Go and video games such as Breakout. This paper suggests a way to incorporate such advanced computing methods into architectural design through introducing a simple conceptual design project inspired by computational interpretations of wasps' collective constructions. At this stage, the paper's intent is not to introduce a practical and fully finished tool directly useful for architectural design. Instead, the paper proposes an example of a program that can potentially become a conceptual framework for incorporating such advanced methods into architectural design.
keywords	Design tools; Stigmergy; Machine learning
series	eCAADe
email
last changed	2022/06/07 07:58

_id	ecaade2017_009
id	ecaade2017_009
authors	Takizawa, Atsushi and Furuta, Airi
year	2017
title	3D Spatial Analysis Method with First-Person Viewpoint by Deep Convolutional Neural Network with Omnidirectional RGB and Depth Images
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 2, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 693-702
doi	https://doi.org/10.52842/conf.ecaade.2017.2.693
summary	The fields of architecture and urban planning widely apply spatial analysis based on images. However, many features can influence the spatial conditions, not all of which can be explicitly defined. In this research, we propose a new deep learning framework for extracting spatial features without explicitly specifying them and use these features for spatial analysis and prediction. As a first step, we establish a deep convolution neural network (DCNN) learning problem with omnidirectional images that include depth images as well as ordinary RGB images. We then use these images as explanatory variables in a game engine to predict a subjects' preference regarding a virtual urban space. DCNNs learn the relationship between the evaluation result and the omnidirectional camera images and we confirm the prediction accuracy of the verification data.
keywords	Space evaluation; deep convolutional neural network; omnidirectional image; depth image; Unity; virtual reality
series	eCAADe
email
last changed	2022/06/07 07:56

_id	cf2017_051
id	cf2017_051
authors	Chen, Kian Wee; Janssen, Patrick; Norford, Leslie
year	2017
title	Automatic Parameterisation of Semantic 3D City Models for Urban Design Optimisation
source	Gülen Çagdas, Mine Özkar, Leman F. Gül and Ethem Gürer (Eds.) Future Trajectories of Computation in Design [17th International Conference, CAAD Futures 2017, Proceedings / ISBN 978-975-561-482-3] Istanbul, Turkey, July 12-14, 2017, pp. 51-65.
summary	We present an auto-parameterisation tool, implemented in Python, that takes in a semantic model, in CityGML format, and outputs a parametric model. The parametric model is then used for design optimisation of solar availability and urban ventilation potential. We demonstrate the tool by parameterising a CityGML model regarding building height, orientation and position and then integrate the parametric model into an optimisation process. For example, the tool parameterises the orientation of a design by assigning each building an orientation parameter. The parameter takes in a normalised value from an optimisation algorithm, maps the normalised value to a rotation value and rotates the buildings. The solar and ventilation performances of the rotated design is then evaluated. Based on the evaluation results, the optimisation algorithm then searches through the parameter values to achieve the optimal performances. The demonstrations show that the tool eliminates the need to set up a parametric model manually, thus making optimisation more accessible to designers.
keywords	City Information Modelling, Conceptual Urban Design, Parametric Modelling, Performance-Based Urban Design
series	CAAD Futures
email
last changed	2017/12/01 14:37

_id	cf2017_084
id	cf2017_084
authors	Chen, Kian Wee; Janssen, Patrick; Norford, Leslie
year	2017
title	Automatic Generation of Semantic 3D City Models from Conceptual Massing Models
source	Gülen Çagdas, Mine Özkar, Leman F. Gül and Ethem Gürer (Eds.) Future Trajectories of Computation in Design [17th International Conference, CAAD Futures 2017, Proceedings / ISBN 978-975-561-482-3] Istanbul, Turkey, July 12-14, 2017, pp. 84-100.
summary	We present a workflow to automatically generate semantic 3D city models from conceptual massing models. In the workflow, the massing design is exported as a Collada file. The auto-conversion method, implemented as a Python library, identifies city objects by analysing the relationships between the geometries in the Collada file. For example, if the analysis shows that a closed poly surface satisfies certain geometrical relationships, it is automatically converted to a building. The advantage of this workflow is that no extra modelling effort is required, provided the designers are consistent in the geometrical relationships while modelling their massing design. We will demonstrate the feasibility of the workflow using three examples of increasing complexity. With the success of the demonstrations, we envision the utoconversion of massing models into semantic models will facilitate the sharing of city models between domain-specific experts and enhance communications in the urban design process.
keywords	Interoperability, GIS, City Information Modelling, Conceptual Urban Design, Collaborative Urban Design Process
series	CAAD Futures
email
last changed	2017/12/01 14:37

_id	ecaade2017_050
id	ecaade2017_050
authors	Cursi, Stefano, Simeone, Davide and Coraglia, Ugo Maria
year	2017
title	An ontology-based platform for BIM semantic enrichment
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 2, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 649-656
doi	https://doi.org/10.52842/conf.ecaade.2017.2.649
summary	In its application to design phases, BIM has progressively shown limits in terms of semantic representation and efficiency of supporting collaboration. This paper investigates the possibilities related to BIM representation enrichment through semantic web approaches, in order to represent knowledge rather than information and presents a prototypal application oriented to the integration of the informative model of the building with a knowledge base developed by means of ontologies, providing a more structured system of interconnected information.
keywords	BIM; Semantic enrichment; Knowledge Management; Ontologies
series	eCAADe
email
last changed	2022/06/07 07:56

_id	cf2017_112
id	cf2017_112
authors	de Klerk, Rui; Beirao, Jose Nuno
year	2017
title	CIM-St: A Parametric Design System for Street Cross Sections
source	Gülen Çagdas, Mine Özkar, Leman F. Gül and Ethem Gürer (Eds.) Future Trajectories of Computation in Design [17th International Conference, CAAD Futures 2017, Proceedings / ISBN 978-975-561-482-3] Istanbul, Turkey, July 12-14, 2017, p. 112.
summary	City environment is very much determined by the design of its streets and in particular by the design of its cross section. This paper shows a street cross section design interface where designs are controlled by an ontology and a parametric design system. The system keeps its semantic structure through the ontology and provides a design interface that understands the computer interaction needed by the urban designer. Real time visual analytics are used to support the design decision process, allowing designers to objectively compare designs and measure the differences between them, in order to make informed decisions.
keywords	Parametric design, Ontologies, Compound grammars, Street cross section, Urban design systems
series	CAAD Futures
email
last changed	2017/12/01 14:37

_id	ecaade2017_023
id	ecaade2017_023
authors	Pankiewicz, Mateusz
year	2017
title	Causes and effects - Methodologies used in digitalization of architectural-urban heritage
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 2, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 25-30
doi	https://doi.org/10.52842/conf.ecaade.2017.2.025
summary	Since some time already, digital reconstructions in architecture, urbanism and archaeology are gradually switching from describing built heritage as a collection of static and unchangeable entities towards more compound and explicit presentation and knowledge management techniques. This includes for instance data management and multimedia systems, immersive environments or semantic information modelling such as GIS (Geospatial Information Systems), BIM (Building Information Modeling) or HBIM (Historic Building Information Modeling). Graphical user interfaces, interaction and usability have become an essential part of produced reconstructions. This shift in terms of dissemination of an architectural and urban heritage that is supposed to increase the social awareness and participation should be structured in a way that enables recipients originating from different backgrounds to grasp information pertaining to almost any knowledge domain, allowing for self-exploration and interpretation of presented knowledge. This paper discusses important nodes of the reconstruction process in the spirit of informative modelling that are characteristic for any possible approach towards conscious heritage representations.
keywords	Informative modelling; Spatio-temporal modelling; Cultural heritage
series	eCAADe
email
last changed	2022/06/07 08:00

_id	acadia17_446
id	acadia17_446
authors	Nejur, Andrei; Steinfeld, Kyle
year	2017
title	Ivy: Progress in Developing Practical Applications for a Weighted-Mesh Representation for Use in Generative Architectural Design
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 446- 455
doi	https://doi.org/10.52842/conf.acadia.2017.446
summary	This paper presents progress in the development of practical applications for graph representations of meshes for a variety of problems relevant to generative architectural design (GAD). In previous work (Nejur and Steinfeld 2016), the authors demonstrated that while approaches to marrying mesh and graph representations drawn from computer graphics (CG) can be effective within the domains of applications for which they have been developed, they have not adequately addressed wider classes of problems in GAD. There, the authors asserted that a generalized framework for working with graph representations of meshes can effectively bring recent advances in mesh segmentation to bear on GAD problems, a utility demonstrated through the development of a plug-in for the visual programming environment Grasshopper. Here, we describe a number of implemented solutions to mesh segmentation and transformation problems, articulated as a series of additional features developed as a part of this same software. Included are problems of mesh segmentation approached through the creation of acyclic connected graphs (trees); problems of mesh transformations, such as those that unfold a segmented mesh in anticipation of fabrication; and problems of geometry generation in relation to a segmented mesh, as demonstrated through a generalized approach to mesh weaving. We present these features in the context of their potential applications in GAD and provide a limited set of examples for their use.
keywords	design methods; information processing
series	ACADIA
email
last changed	2022/06/07 07:58

_id	acadia21_530
id	acadia21_530
authors	Adel, Arash; Augustynowicz, Edyta; Wehrle, Thomas
year	2021
title	Robotic Timber Construction
source	ACADIA 2021: Realignments: Toward Critical Computation [Proceedings of the 41st Annual Conference of the Association of Computer Aided Design in Architecture (ACADIA) ISBN 979-8-986-08056-7]. Online and Global. 3-6 November 2021. edited by S. Parascho, J. Scott, and K. Dörfler. 530-537.
doi	https://doi.org/10.52842/conf.acadia.2021.530
summary	Several research projects (Gramazio et al. 2014; Willmann et al. 2015; Helm et al. 2017; Adel et al. 2018; Adel Ahmadian 2020) have investigated the use of automated assembly technologies (e.g., industrial robotic arms) for the fabrication of nonstandard timber structures. Building on these projects, we present a novel and transferable process for the robotic fabrication of bespoke timber subassemblies made of off-the-shelf standard timber elements. A nonstandard timber structure (Figure 2), consisting of four bespoke subassemblies: three vertical supports and a Zollinger (Allen 1999) roof structure, acts as the case study for the research and validates the feasibility of the proposed process.
series	ACADIA
type	project
email
last changed	2023/10/22 12:06

_id	ijac201715301
id	ijac201715301
authors	Afsari, Kereshmeh; Charles Eastman and Dennis Shelden
year	2017
title	Building Information Modeling data interoperability for Cloud-based collaboration: Limitations and opportunities
source	International Journal of Architectural Computing vol. 15 - no. 3, 187-202
summary	Collaboration within Building Information Modeling process is mainly based on the manual transfer of document files in either vendor-specific formats or neutral format using Industry Foundation Classes. However, since the web enables Cloud-based Building Information Modeling services, it provides an opportunity to exchange data with web technologies. Alternative data sharing solutions include the federation of Building Information Modeling models and an interchange hub for data exchange in real time. These solutions face several challenges, are vendor locked, and integrate Building Information Modeling applications to a third new system. The main objective of this article is to investigate current limitations as well as opportunities of Cloud interoperability to outline a framework for a loosely coupled network-based Building Information Modeling data interoperability. This study explains that Cloud-Building Information Modeling data exchange needs to deploy major components of Cloud interoperability such as Cloud application programming interfaces, data transfer protocols, data formats, and standardization to redefine Building Information Modeling data flow in Cloud-based applications and to reshape collaboration process.
keywords	Building Information Modeling, Cloud, data exchange, interoperability, Industry Foundation Classes
series	journal
email
last changed	2019/08/07 14:03

_id	acadia17_38
id	acadia17_38
authors	Ahlquist, Sean; McGee, Wes; Sharmin, Shahida
year	2017
title	PneumaKnit: Actuated Architectures Through Wale- and Course-Wise Tubular Knit-Constrained Pneumatic Systems
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 38-51
doi	https://doi.org/10.52842/conf.acadia.2017.038
summary	This research explores the development of seamless pneumatically actuated systems whose motion is controlled by the combination of differentially knitted textiles and standardized thin-walled silicone tubing. This work proposes a fundamental material strategy that addresses challenges ranging from soft robotics to pneumatic architecture. Research in soft robotics seeks to achieve complex motions through non-mechanical monolithic systems, comprised of highly articulated shapes molded with a combination of elastic and inelastic materials. Inflatables in architecture focus largely on the active structuring of static forms, as facade systems or as structured envelopes. An emerging use of pneumatic architecture proposes morphable, adaptive systems accomplished through differentiated mechanically interconnected components. In the research described in this paper, a wide array of capabilities in motion and geometric articulation are accomplished through the design of knitted sleeves that generate a series of actuated “elbows.” As opposed to molding silicone bladders, differentiation in motion is generated through the more facile ability of changing stitch structure, and shaping of the knitted textile sleeve, which constrains the standard silicone tubing. The relationship between knit differentiation, pneumatic pressure, and the resultant motion profile is studied initially with individual actuators, and ultimately in propositions for larger seamless assemblies. As opposed to a cellular study of individual components, this research proposes structures with multi-scalar articulation, from fiber and stitch to overall form, composed into seamless, massively deformable architectures.
keywords	material and construction; fabrication; construction/robotics
series	ACADIA
email
last changed	2022/06/07 07:54

_id	acadia17_52
id	acadia17_52
authors	Ajlouni, Rima
year	2017
title	Simulation of Sound Diffusion Patterns of Fractal-Based Surface Profiles
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 52-61
doi	https://doi.org/10.52842/conf.acadia.2017.052
summary	Acoustical design is one of the most challenging aspects of architecture. A complex system of competing influences (e.g., space geometry, size, proportion, material properties, surface detail, etc.) contribute to shaping the quality of the auditory experience. In particular, architectural surfaces affect the way that sound reflections propagate through space. By diffusing the reflected sound energy, surface designs can promote a more homogeneous auditory atmosphere by mitigating sharp and focused reflections. One of the challenges with designing an effective diffuser is the need to respond to a wide band of sound wavelengths, which requires the surface profile to precisely encode a range of detail sizes, depths and angles. Most of the available sound diffusers are designed to respond to a narrow band of frequencies. In this context, fractal-based surface designs can provide a unique opportunity for mitigating such limitations. A key principle of fractal geometry is its multilevel hierarchical order, which enables the same pattern to occur at different scales. This characteristic makes it a potential candidate for diffusing a wider band of sound wavelengths. However, predicting the reflection patterns of complicated fractal-based surface designs can be challenging using available acoustical software. These tools are often costly, complicated and are not designed for predicting early sound propagation paths. This research argues that writing customized algorithms provides a valuable, free and efficient alternative for addressing targeted acoustical design problems. The paper presents a methodology for designing and testing a customized algorithm for predicting sound diffusion patterns of fractal-based surfaces. Both quantitative and qualitative approaches were used to develop the code and evaluate the results.
keywords	design methods; information processing; simulation & optimization; data visualization
series	ACADIA
email
last changed	2022/06/07 07:54

For more results click below: