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	ecaade2023_99
id	ecaade2023_99
authors	Dervishaj, Arlind, Fonsati, Arianna, Hernández Vargas, José and Gudmundsson, Kjartan
year	2023
title	Modelling Precast Concrete for a Circular Economy in the Built Environment
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. 177–186
doi	https://doi.org/10.52842/conf.ecaade.2023.2.177
summary	In recent years, there has been a growing interest in adopting circular approaches in the built environment, specifically reusing existing buildings or their components in new projects. To achieve this, drawings, laser scanning, photogrammetry and other techniques are used to capture data on buildings and their materials. Although previous studies have explored scan-to-BIM workflows, automation of 2D drawings to 3D models, and machine learning for identifying building components and materials, a significant gap remains in refining this data into the right level of information required for digital twins, to share information and for digital collaboration in designing for reuse. To address this gap, this paper proposes digital guidelines for reusing precast concrete based on the level of information need (LOIN) standard EN 17412-1:2020 and examines several CAD and BIM modelling strategies. These guidelines can be used to prepare digital templates that become digital twins of existing elements, develop information requirements for use cases, and facilitate data integration and sharing for a circular built environment.
keywords	building information modelling (BIM), circular construction, reuse, concrete
series	eCAADe
email
last changed	2023/12/10 10:49

_id	acadia20_456
id	acadia20_456
authors	Alali, Jiries; Negar Kalantar, Dr.; Borhani, Alireza
year	2020
title	Casting on a Dump
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. 456-463.
doi	https://doi.org/10.52842/conf.acadia.2020.1.456
summary	“Casting on a dump” focuses on finding accessible, low-tech fabrication methodologies that allow for the construction of parametrically designed nonstandard modular cast panels. Such an approach adopts a computational design framework using a single low-tech and low-energy fabrication device to create nonrepetitive volumetric panels cast in situ. The design input for these panels is derived from design preferences and environmental control data. The technique expands upon easy to fabricate and cast methods, targeting less-developed logistical settings worldwide, and thus responding to imminent needs related to climate, available resources, and the economy.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	ecaade2020_190
id	ecaade2020_190
authors	Dounas, Theodoros, Jabi, Wassim and Lombardi, Davide
year	2020
title	Smart Contracts for Decentralised Building Information Modelling
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. 565-574
doi	https://doi.org/10.52842/conf.ecaade.2020.2.565
summary	The paper presents a model for decentralizing building information modelling, through implementing its infrastructure using the decentralized web. We discuss the shortcomings of BIM in terms of its infrastructure, with a focus on tracing identities of design authorship in this collective design tool. In parallel we examine the issues with BIM in the cloud and propose a decentralized infrastructure based on the Ethereum blockchain and the Interplanetary filesystem (IPFS). A series of computing nodes, that act as nodes on the Ethereum Blockchain, host disk storage with which they participate in a larger storage pool on the Interplanetary Filesystem. This storage is made available through an API is used by architects and designers creating and editing a building information model that resides on the IPFS decentralised storage. Through this infrastructure central servers are eliminated, and BIM libraries and models can be shared with others in an immutable and transparent manner. As such Architecture practices are able to exploit their intellectual property in novel ways, by making it public on the internet. The infrastructure also allows the decentralised creation of a resilient global pool of data that allows the participation of computation agents in the creation and simulation of BIM models.
keywords	Blockchain; decentralisation; immutability; resilience; Building Information Modelling
series	eCAADe
email
last changed	2022/06/07 07:55

_id	ecaade2020_290
id	ecaade2020_290
authors	Elesawy, Amr Alaaeldin, Signer, Mario, Seshadri, Bharath and Schlueter, Arno
year	2020
title	Aerial Photogrammetry in Remote Locations - A workflow for using 3D point cloud data in building energy modeling
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. 723-732
doi	https://doi.org/10.52842/conf.ecaade.2020.1.723
summary	Building energy modelling (BEM) results are highly affected by the surrounding environment, due to the impact of solar radiation on the site. Hence, modelling the context is a crucial step in the design process. This is challenging when access to the geometrical data of the built and natural environment is unavailable as in remote villages. The acquisition of accurate data through conventional surveying proves to be costly and time consuming, especially in areas with a steep and complex terrain. Photogrammetry using drone-captured aerial images has emerged as an innovative solution to facilitate surveying and modeling. Nevertheless, the workflow of translating the photogrammetry output from data points to surfaces readable by BEM tools proves to be tedious and unclear. This paper presents a streamlined and reproducible approach for constructing accurate building models from photogrammetric data points to use for architectural design and energy analysis in early design stage projects.
keywords	Building Energy Modeling; Photogrammetry; 3D Point Clouds; Low-energy architecture; Multidisciplinary design; Education
series	eCAADe
email
last changed	2022/06/07 07:55

_id	ijac202018304
id	ijac202018304
authors	Aagaard, Anders Kruse and Niels Martin Larsen
year	2020
title	Developing a fabrication workflow for irregular sawlogs
source	International Journal of Architectural Computing vol. 18 - no. 3, 270-283
summary	In this article, we suggest using contemporary manufacturing technologies to integrate material properties with architectural design tools, revealing new possibilities for the use of wood in architecture. Through an investigative approach, material capacities and fabrication methods are explored and combined towards establishing new workflows and architectural expressions, where material, fabrication and result are closely interlinked. The experimentation revolves around discarded, crooked oak logs, doomed to be used as firewood due to their irregularity. This project treats their diverging shapes differently by offering unique processing to each log informed by its particularities. We suggest here a way to use the natural forms and properties of sawlogs to generate new structures and spatial conditions. In this article, we discuss the scope of this approach and provide an example of a workflow for handling the discrete shapes of natural sawlogs in a system that involve the collection of material, scanning/digitisation, handling of a stockpile, computer analysis, design and robotic manufacturing. The creation of this specific method comes from a combination of investigation of wood as a material, review of existing research in the field, studies of the production lines in the current wood industry and experimentation through our in-house laboratory facilities. As such, the workflow features several solutions for handling the complex and different shapes and data of natural wood logs in a highly digitised machining and fabrication environment. This up-cycling of discarded wood supply establishes a non-standard workflow that utilises non-standard material stock and leads to a critical articulation of today’s linear material economy. The project becomes part of an ambition to reach sustainable development goals and technological innovation in global and resource-intensive architecture and building industry.
keywords	Natural wood, robotic fabrication, computation, fabrication, research by design
series	journal
email
last changed	2020/11/02 13:34

_id	caadria2020_306
id	caadria2020_306
authors	Akizuki, Yuta, Bernhard, Mathias, Kakooee, Reza, Kladeftira, Marirena and Dillenburger, Benjamin
year	2020
title	Generative Modelling with Design Constraints - Reinforcement Learning for Object Generation
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. 445-454
doi	https://doi.org/10.52842/conf.caadria.2020.1.445
summary	Generative design has been explored to produce unprecedented geometries, nevertheless design constraints are, in most cases, second-graded in the computational process. In this paper, reinforcement learning is deployed in order to explore the potential of generative design satisfying design objectives. The aim is to overcome the three issues identified in the state of the art: topological inconsistency, less variations in style and unpredictability in design. The goal of this paper is to develop a machine learning framework, which works as an intellectual design interpreter capable of codifying an input geometry to form a new geometry. Experiments demonstrate that the proposed method can generate a family of tables of unique aesthetics, satisfying topological consistency under given constraints.
keywords	generative design; computational design; data-driven design; reinforcement learning; machine learning
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	acadia20_228
id	acadia20_228
authors	Alawadhi, Mohammad; Yan, Wei
year	2020
title	BIM Hyperreality
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.
doi	https://doi.org/10.52842/conf.acadia.2020.1.228
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	acadia20_226p
id	acadia20_226p
authors	Borhani, Alireza; Kalantar, Negar
year	2020
title	Interlocking Shell
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. 226-231
summary	With a specific focus on robotic stereotomy, two full-scale vault structures were designed to explore the potential of self-standing building structures made from interlocking components; these structures were fabricated with a track-mounted industrial-scale robot (ABB 4600). To respond to the economic affordances of robotic subtractive cutting, all uniquely shaped structural modules came from one block of material (48"" x96"" x36""). Through the discretization of curvilinear tessellated vault surfaces into a limited number of uniquely shaped modules with embedded form-fitting connectors, the project exhibited the potential for programming a robot to cut ruled surfaces to produce freeform shells of any kind. Representing nearly zero-waste construction, the developed technology can potentially be used for self-supporting emergency shelters and field medical clinics, facilitating easy shipping and speedy assembly. Without using any scaffolding, a few people can erect and dismantle an entire mortar-free structure at the construction site. The disassembled structure occupies minimal space in storage, and the structure’s pieces can be transported to the site in stacks. Robot milling is a common technique for removing material to transform a block into a sculptural shape. Unlike milling techniques that produce significant waste, we used a hotwire that sliced through a Geofoam block to create almost no waste pieces. Since the front side of every module was concurrent with the backside of the next one, such a decision allowed to operate just one cut per front side of each module. In this case, by having three cuts, two neighboring modules were fabricated. The form of the structure and its modules emerged from the constraints of the fabrication technique, aiming to establish a feedback loop between geometry, material, simulation, and tool. By cross-referencing geometric data across Grasshopper, a customized tessellation script was made to breakdown a vault into its modular ruled surface constructs.
series	ACADIA
type	project
email
last changed	2021/10/26 08:08

_id	caadria2020_141
id	caadria2020_141
authors	Dezen-Kempter, Eloisa, Mezencio, Davi Lopes, Miranda, Erica De Matos, De SÃ¡, Danilo Pico and Dias, Ulisses
year	2020
title	Towards a Digital Twin for Heritage Interpretation - from HBIM to AR visualization
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. 183-191
doi	https://doi.org/10.52842/conf.caadria.2020.2.183
summary	Data-driven Building Information Modelling (BIM) technology has brought new tools to efficiently deal with the tension between the real and the virtual environments in the field of Architecture, Engineering, Construction, and Operation (AECO). For historic assets, BIM represents a paradigm shift, enabling better decision-making about preventive maintenance, heritage management, and interpretation. The potential application of the Historic-BIM is creating a digital twin of the asset. This paper deals with the concept of a virtual environment for the consolidation and dissemination of heritage information. Here we show the process of creating interactive virtual environments for the Pampulha Modern Ensemble designed by Oscar Niemeyer in the 1940s, and the workflow to their dissemination in an AR visualization APP. Our results demonstrate the APP feasibility to the Pampulha's building interpretation.
keywords	Augmented Reality (AR); Historic Building Information Modelling (HBIM); Heritage Interpretation; Modern Architecture
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	sigradi2020_392
id	sigradi2020_392
authors	Fialho, Beatriz Campos; Codinhoto, Ricardo; Fabricio, Márcio Minto
year	2020
title	BIM and IoT for the AEC Industry: A systematic literature mapping
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. 392-399
summary	The AEC industry has been facing a digital transformation for improving services involved in buildings lifecycle, fostered by two disruptive technologies: Building Information Modelling (BIM) and Internet of Things (IoT). However, the literature lacks discussions regarding applications and challenges of BIM and IoT systems in the AEC. This Systematic Literature Mapping addresses this gap through search, analysis, and classification of 75 journal article abstracts published between 2015 and 2019. An increase of articles over the period is observed, predominantly with technical and processual solutions for Construction and Operation and Maintenance. The interoperability of data is a key challenge to organizations.
keywords	Building Information Modelling, Internet of Things, Integration, Network, Smart Cities
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
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
doi	https://doi.org/10.52842/conf.ecaade.2020.2.585
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	sigradi2020_968
id	sigradi2020_968
authors	Gongora, Nicolás; Chiarella, Mauro
year	2020
title	ATMOSPH (DAQ) + APP post-occupancy evaluation (POE). Energy efficiency building optimized in real time
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. 968-974
summary	Greenhouse issues in existing glass-enclosed buildings can be controlled by optimizing energy efficiency and thermal comfort using low cost, customizable, customizable, open source, transferable resources. For such objectives, it is necessary to strategically link algorithmic, heuristic and manufacturing processes. For the case study, the creation of a personalized data acquisition device (DAQ) and a post-occupational evaluation APP (POE) enabled us to advance on real-time building energy efficiency operating on the need for comfort in the rooms and users.
keywords	Data acquisition, Post-occupancy evaluation, Domotic, arduino, Architectural skin
series	SIGraDi
email
last changed	2021/07/16 11:53

_id	ecaade2024_4
id	ecaade2024_4
authors	Irodotou, Louiza; Gkatzogiannis, Stefanos; Phocas, Marios C.; Tryfonos, George; Christoforou, Eftychios G.
year	2024
title	Application of a Vertical Effective Crank–Slider Approach in Reconfigurable Buildings through Computer-Aided Algorithmic Modelling
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 1, pp. 421–430
doi	https://doi.org/10.52842/conf.ecaade.2024.1.421
summary	Elementary robotics mechanisms based on the effective crank–slider and four–bar kinematics methods have been applied in the past to develop architectural concepts of reconfigurable structures of planar rigid-bar linkages (Phocas et al., 2020; Phocas et al., 2019). The applications referred to planar structural systems interconnected in parallel to provide reconfigurable buildings with rectangular plan section. In enabling structural reconfigurability attributes within the spatial circular section buildings domain, a vertical setup of the basic crank–slider mechanism is proposed in the current paper. The kinematics mechanism is integrated on a column placed at the middle of an axisymmetric circular shaped spatial linkage structure. The definition of target case shapes of the structure is based on a series of numerical geometric analyses that consider certain architectural and construction criteria (i.e., number of structural members, length, system height, span, erectability etc.), as well as structural objectives (i.e., structural behavior improvement against predominant environmental actions) aiming to meet diverse operational requirements and lightweight construction. Computer-aided algorithmic modelling is used to analyze the system's kinematics, in order to provide a solid foundation and enable rapid adaptation for mechanisms that exhibit controlled reconfigurations. The analysis demonstrates the implementation of digital parametric design tools for the investigation of the kinematics of the system at a preliminary design stage, in avoiding thus time-demanding numerical analysis processes. The design process may further provide enhanced interdisciplinary performance-based design outcomes.
keywords	Reconfigurable Structures, Spatial Linkage Structures, Kinematics, Parametric Associative Design
series	eCAADe
email
last changed	2024/11/17 22:05

_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	ijac202018103
id	ijac202018103
authors	Kimm, Geoff
year	2020
title	Actual and experiential shadow origin tagging: A 2.5D algorithm for efficient precinct-scale modelling
source	International Journal of Architectural Computing vol. 18 - no. 1, 41-52
summary	This article describes a novel algorithm for built environment 2.5D digital model shadow generation that allows identities of shadowing sources to be efficiently precalculated. For any point on the ground, all sources of shadowing can be identified and are classified as actual or experiential obstructions to sunlight. The article justifies a 2.5D raster approach in the context of modelling of architectural and urban environments that has in recent times shifted from 2D to 3D, and describes in detail the algorithm which builds on precedents for 2.5D raster calculation of shadows. The algorithm is efficient and is applicable at even precinct scale in low-end computing environments. The simplicity of this new technique, and its independence of GPU coding, facilitates its easy use in research, prototyping and civic engagement contexts. Two research software applications are presented with technical details to demonstrate the algorithm’s use for participatory built environment simulation and generative modelling applications. The algorithm and its shadow origin tagging can be applied to many digital workflows in architectural and urban design, including those using big data, artificial intelligence or community participative processes.
keywords	2.5D raster, actual and experiential shadow origins, generative techniques, participatory built environment simulation, reactive scripting for design
series	journal
email
last changed	2020/11/02 13:34

_id	sigradi2021_300
id	sigradi2021_300
authors	Leiro, Manoela, Darzé, Júlia, Rios, Matheus and Lemos, Paulo
year	2021
title	An Experience with the Use of a BIM Tool in the Thermal Environmental Comfort Discipline
source	Gomez, P and Braida, F (eds.), Designing Possibilities - Proceedings of the XXV International Conference of the Ibero-American Society of Digital Graphics (SIGraDi 2021), Online, 8 - 12 November 2021, pp. 889–900
summary	This article presents a didactic experience carried out with the use of a BIM tool in the Thermal Environmental Comfort discipline of the graduate course in Architecture and Urbanism of a private Higher Education Institution in the city of Salvador-Bahia. Starting in 2020, students began designing solar protection devices using a geometric model in Revit. The method described in Annex I of the Technical Regulation on the Quality of Energy Efficiency Level in Residential Buildings (RTQ-R) was applied. The results obtained showed a better understanding by the students about the importance of correctly sizing solar protection devices for different orientations.
keywords	BIM, Ensino, Conforto Ambiental Térmico
series	SIGraDi
email
last changed	2022/05/23 12:11

_id	acadia20_170
id	acadia20_170
authors	Li, Peiwen; Zhu, Wenbo
year	2020
title	Clustering and Morphological Analysis of Campus Context
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.
doi	https://doi.org/10.52842/conf.acadia.2020.2.170
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	caadria2020_023
id	caadria2020_023
authors	Liu, Chenjun
year	2020
title	Double Loops Parametric Design of Surface Steel Structure Based on Performance and Fabrication
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. 23-33
doi	https://doi.org/10.52842/conf.caadria.2020.1.023
summary	In intelligent epoch, automatic parameter design systems reduce the requirements of the skills needed to create objects. The creator only needs to select the most perceptual primitive form to automatically generate the data system that iterates to the most efficient solution. In this paper, a method of combining performance driven optimization with parametric design is proposed. The iterative evolution is under the control of performance loop and fabrication loop, which makes all the data provided by parametric design in a practical project available for exploring structural analysis and digital prefabrication. Related to the case of surface steel structure, parametric optimization is not limited to a set of shape types or design problems, it would be based on the generality and built-in characteristics of parametric modelling environment in the most convenient and flexible way. (Rolvink et al. 2010)And the given parameters would be fed back on geometric structure, performance indicators, and design variables, so that designers can easily and effectively coordinate and try different solutions. The system transforms the generated data into machine language so that the process including design, analysis, manufacturing, and construction can maintain the orthogonal persistence of the data.
keywords	parametric design; component prefabrication; curved steel structure; performance driven
series	CAADRIA
email
last changed	2022/06/07 07:59

_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	caadria2020_107
id	caadria2020_107
authors	Meng, Leo Lin, Graham, Jeremy and Haeusler, M. Hank
year	2020
title	t-SNE: A Dimensionality Reduction Tool for Design Data Visualisation
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. 629-638
doi	https://doi.org/10.52842/conf.caadria.2020.2.629
summary	One can argue that data is the 'new oil'. Yet more important than the sheer quantity of data is the question, in the context of architecture and design, how data is represented in design, as this is becoming a more relevant question to the architecture profession. We argue that data, in particular n-dimensional, is often hidden even in BIM models. Hence we propose a new way of understanding the space by (1) generate and integrate space analytics data using space syntax method as well as space usage data and (2) visualise the data using t-Distributed Stochastic Neighbour Embedding (t-SNE), an unsupervised learning and dimensionality reduction tool to help intuitively display high dimensions of data. This approach may help to discover the 'hidden layers' of the building information that may be otherwise omitted. This investigation, its proposed hypothesis, methodology, implications, significance and evaluation are presented in the paper.
keywords	Data-Driven Design; t-SNE; Machine Learning; Space Syntax
series	CAADRIA
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last changed	2022/06/07 07:58

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