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

_id	ecaadesigradi2019_605
id	ecaadesigradi2019_605
authors	Andrade Zandavali, Bárbara and Jiménez García, Manuel
year	2019
title	Automated Brick Pattern Generator for Robotic Assembly using Machine Learning and Images
doi	https://doi.org/10.52842/conf.ecaade.2019.3.217
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. 217-226
summary	Brickwork is the oldest construction method still in use. Digital technologies, in turn, enabled new methods of representation and automation for bricklaying. While automation explored different approaches, representation was limited to declarative methods, as parametric filling algorithms. Alternatively, this work proposes a framework for automated brickwork using a machine learning model based on image-to-image translation (Conditional Generative Adversarial Networks). The framework consists of creating a dataset, training a model for each bond, and converting the output images into vectorial data for robotic assembly. Criteria such as: reaching wall boundary accuracy, avoidance of unsupported bricks, and brick's position accuracy were individually evaluated for each bond. The results demonstrate that the proposed framework fulfils boundary filling and respects overall bonding structural rules. Size accuracy demonstrated inferior performance for the scale tested. The association of this method with 'self-calibrating' robots could overcome this problem and be easily implemented for on-site.
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:54

_id	caadria2019_266
id	caadria2019_266
authors	Indraprastha, Aswin and Dwi Pranata Putra, Bima
year	2019
title	Informed Walkable City Model - Developing A Multi-Objective Optimization Model for Evaluating Walkability Concept
doi	https://doi.org/10.52842/conf.caadria.2019.2.161
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 2, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 161-170
summary	This study presents an informed city analysis methodology as a tool for evaluating the concept of walkability for the existing urban area. The aim of this study was to propose an integrative approaches enable optimization of urban design element and walkability amenities under certain walkability performance criteria. The parametric methods are being developed in three stages of modeling: 1) City data modeling; 2) Walkability scores and indicators modeling; 3) Optimization model of the urban area. In the walk score algorithm, we modified three elements that determine walk score result: Walk Score Categories, Distance Decay Function and Pedestrian Friendliness Metric. We developed the customized algorithm based on the data gathered from field observation and sample interviews to normalize and define values in the walk score algorithm. The result is a parametric model to evaluate walkability concept in a certain urban area considering quantified factors that determine walkability scores. The model furthermore seeks to optimize walkability score by assessing new amenities on an existing urban area using multi-objective optimization method that produces an integrative method of urban analysis.
keywords	walkability; walk score; parametric models; multi-objective optimization; informed city analysis
series	CAADRIA
email
last changed	2022/06/07 07:50

_id	ijac201917103
id	ijac201917103
authors	Bejarano, Andres; and Christoph Hoffmann
year	2019
title	A generalized framework for designing topological interlocking configurations
source	International Journal of Architectural Computing vol. 17 - no. 1, 53-73
summary	A topological interlocking configuration is an arrangement of pieces shaped in such a way that the motion of any piece is blocked by its neighbors. A variety of interlocking configurations have been proposed for convex pieces that are arranged in a planar space. Published algorithms for creating a topological interlocking configuration start from a tessellation of the plane (e.g. squares colored as a checkerboard). For each square S of one color, a plane P through each edge E is considered, tilted by a given angle ? against the tessellated plane. This induces a face F supported by P and limited by other such planes nearby. Note that E is interior to the face. By adjacency, the squares of the other color have similarly delimiting faces. This algorithm generates a topological interlocking configuration of tetrahedra or antiprisms. When checked for correctness (i.e. for no overlap), it rests on the tessellation to be of squares. If the tessellation consists of rectangles, then the algorithm fails. If the tessellation is irregular, then the tilting angle is not uniform for each edge and must be determined, in the worst case, by trial and error. In this article, we propose a method for generating topological interlocking configurations in one single iteration over the tessellation or mesh using a height value and a center point type for each tile as parameters. The required angles are a function of the given height and selected center; therefore, angle choices are not required as an initial input. The configurations generated using our method are compared against the configurations generated using the angle-choice approach. The results show that the proposed method maintains the alignment of the pieces and preserves the co-planarity of the equatorial sections of the pieces. Furthermore, the proposed method opens a path of geometric analysis for topological interlocking configurations based on non-planar tessellations.
keywords	Topological interlocking, surface tessellation, irregular geometry, parametric design, convex assembly
series	journal
email
last changed	2019/08/07 14:04

_id	ecaadesigradi2019_414
id	ecaadesigradi2019_414
authors	Costa Lima, Mariana, Cardoso, Daniel and Freitas, Clarissa
year	2019
title	Informal Settlements and City Information Modeling - Producing data to inform land use regulation in Fortaleza-Brazil
doi	https://doi.org/10.52842/conf.ecaade.2019.3.323
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. 323-332
summary	In recent years, several advances have occurred concerning the legitimacy of precarious informal settlements in Brazil. In spite of this progress in the legal dimension, little has been made concerning standards to ensure urban space quality. The difficulties of reversing this exclusionary logic are due to several complex factors. A factor less discussed, especially in the national literature, but that has begun to draw the attention of scholars, is the invisibility of the informal city. This research assumes that it is necessary to regulate the urban form of precarious informal settlements, in order to prevent the deterioration of urban environmental quality. We highlight the importance to compile data about their urban form and their built environment, in order to contribute to a reality-based regulatory policy for these settlements, and this is the primary purpose of this study. To address this question, we propose a method of measuring the settlements' urban form, based on the City Information Modeling's theorical and practical framework, which is applied to a case study in Fortaleza, Brazil.
keywords	Informal settlements; City Information Modeling; Urban regulation; ZEIS Bom Jardim
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:56

_id	ecaadesigradi2019_288
id	ecaadesigradi2019_288
authors	da Silva Lopes Vieira, Thomaz and Schulz, Jens-Uwe
year	2019
title	Design Method Aided by MABS and Cloud Computing - Framework integrating: construction techniques, materials, and fabrication
doi	https://doi.org/10.52842/conf.ecaade.2019.1.195
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. 195-205
summary	This paper presents a novel method based in Multi-Agent Based Simulation (MABS), Cloud Computing, and the combination of big data analytics and IoT. The method performs in two layers: it assists designers with information coming from previews of projects and surroundings, and, it automates some procedures according to parameters and interactions between agents. The first part of this paper briefly describes the state of the art and challenges of the real estate market. The second chapter highlight gaps and future challenges in design practice, and in the third chapter, it introduces the method. To conclude, in the last part, this concept is analyzed through a pilot project under development in our institution.
keywords	Computational design; Multi-Agent-Based system; Robotic fabrication; Cyber-Physical Systems; Big Data; Internet of Things
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:56

_id	caadria2019_117
id	caadria2019_117
authors	Deniz Kiraz, Leyla and Kocaturk, Tuba
year	2019
title	Integrating User-Behaviour as Performance Criteria in Conceptual Parametric Design
doi	https://doi.org/10.52842/conf.caadria.2019.1.215
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. 215-224
summary	Prediction of user behaviour has always been problematic in architectural design. Several methods have already been developed and explored to model human behaviour in architecture. However, the majority of these methods are implemented during post-design evaluation where the insights obtained can only be implemented in a limited capacity. There is an apparent gap and opportunity, in current research and practice, to embed behaviour simulations directly into the conceptual design process. The proposed paper (research) aims to fill this gap. This paper will report on the results of a recently completed research exploring the integration process of Agent Based Modelling into the conceptual design process, using a parametric design approach. The research resulted in the development of a methodological framework for the integration of behavioural parameters into the explorative stages of the early design process. This paper also offers a categorisation and critical evaluation of existing Agent Based Modelling applications in current research and practice, which leads to the formulation of possible pathways for future implementation.
keywords	Performance Based Design; Generative Design; Behaviour Modelling; Agent Based Modelling; Parametric Design
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	ecaadesigradi2019_648
id	ecaadesigradi2019_648
authors	Eisenstadt, Viktor, Langenhan, Christoph and Althoff, Klaus-Dieter
year	2019
title	Generation of Floor Plan Variations with Convolutional Neural Networks and Case-based Reasoning - An approach for transformative adaptation of room configurations within a framework for support of early conceptual design phases
doi	https://doi.org/10.52842/conf.ecaade.2019.2.079
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. 79-84
summary	We present an approach for computer-aided generation of different variations of floor plans during the early phases of conceptual design in architecture. The early design phases are mostly characterized by the processes of inspiration gaining and search for contextual help in order to improve the building design at hand. The generation method described in this work uses the novel as well as established artificial intelligence methods, namely, generative adversarial nets and case-based reasoning, for creation of possible evolutions of the current design based on the most similar previous designs. The main goal of this approach is to provide the designer with information on how the current floor plan can evolve over time in order to influence the direction of the design process. The work described in this paper is part of the methodology FLEA (Find, Learn, Explain, Adapt) whose task is to provide a holistic structure for support of the early conceptual phases in architecture. The approach is implemented as the adaptation component of the framework MetisCBR that is based on FLEA.
keywords	room configuration; adaptation; case-based reasoning; convolutional neural networks; conceptual design
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:55

_id	acadia19_16
id	acadia19_16
authors	Hosmer, Tyson; Tigas, Panagiotis
year	2019
title	Deep Reinforcement Learning for Autonomous Robotic Tensegrity (ART)
doi	https://doi.org/10.52842/conf.acadia.2019.016
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
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
doi	https://doi.org/10.52842/conf.acadia.2020.1.382
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.
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	caadria2020_431
id	caadria2020_431
authors	Kim, Jong Bum, Balakrishnan, Bimal and Aman, Jayedi
year	2020
title	Environmental Performance-based Community Development - A parametric simulation framework for Smart Growth development in the United States
doi	https://doi.org/10.52842/conf.caadria.2020.1.873
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. 873-882
summary	Smart Growth is an urban design movement initiated by Environmental Protection Agency (EPA) in the United States (Smart Growth America, 2019). The regulations of Smart Growth control urban morphologies such as building height, use, position, section configurations, faÃ§ade configurations, and materials, which have an explicit association with energy performances. This research aims to analyze and visualize the impact of Smart Growth developments on environmental performances. This paper presents a parametric modeling and simulation framework for Smart Growth developments that can model the potential community development scenarios, simulate the environmental footprints of each parcel, and visualize the results of modeling and simulation. We implemented and examined the proposed framework through a case study of two Smart Growth regulations: Columbia Unified Development Code (UDC) in Missouri (City of Columbia Missouri, 2017) and Overland Park Downtown Form-based Code (FBC) in Kansas City (City of Overland Park, 2017, 2019). Last, we discuss the implementation results, the limitations of the proposed framework, and the future work. We anticipate that the proposed method can improve stakeholders' understanding of how Smart Growth developments are associated with potential environmental footprints from an expeditious and thorough exploration of what-if scenarios of the multiple development schemes.
keywords	Smart Growth; Building Information Modeling (BIM); Parametric Simulation; Solar Radiation
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	acadia19_664
id	acadia19_664
authors	Koshelyuk, Daniil; Talaei, Ardeshir; Garivani, Soroush; Markopoulou, Areti; Chronis, Angelo; Leon, David Andres; Krenmuller, Raimund
year	2019
title	Alive
doi	https://doi.org/10.52842/conf.acadia.2019.664
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. 664-673
summary	In the context of data-driven culture, built space still maintains low responsiveness and adaptability. Part of this reality lies in the low resolution of live information we have about the behavior and condition of surfaces and materials. This research addresses this issue by exploring the development of a deformation-sensing composite membrane material system following a bottom-up approach and combining various technologies toward solving related technical issues—exploring conductivity properties of graphene and maximizing utilization within an architecture-related proof-of-concept scenario and a workflow including design, fabrication, and application methodology. Introduced simulation of intended deformation helps optimize the pattern of graphene nanoplatelets (GNP) to maximize membrane sensitivity to a specific deformation type while minimizing material usage. Research explores various substrate materials and graphene incorporation methods with initial geometric exploration. Finally, research introduces data collection and machine learning techniques to train recognition of certain types of deformation (single point touch) on resistance changes. The final prototype demonstrates stable and symmetric readings of resistance in a static state and, after training, exhibits an 88% prediction accuracy of membrane shape on a labeled sample data-set through a pre-trained neural network. The proposed framework consisting of a simulation based, graphene-capturing fabrication method on stretchable surfaces, and includes initial exploration in neural network training shape detection, which combined, demonstrate an advanced approach to embedding intelligence.
series	ACADIA
type	normal paper
email
last changed	2022/06/07 07:51

_id	caadria2019_326
id	caadria2019_326
authors	Lai, Po Yan, Kim, Meereh, Choi, Minkyu, Lee, Chae-Seok, Porcellini, Valentin, Yi, Taeha and Lee, Ji-Hyun
year	2019
title	Framework of Judgment System for Smart Home Assistant Utilizing Collective Intelligence Case-Based Reasoning
doi	https://doi.org/10.52842/conf.caadria.2019.1.695
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. 695-704
summary	This paper proposes a framework of judgment system for smart home assistant that utilizes Collective Intelligence Case Based Reasoning (CI-CBR). CBR is suitable for the smart home environment with its system adaptability to the changeful user scenarios. However, existing CBR solutions have shown relatively low accuracy in service recommendation. This research therefore aims at enhancing the accuracy by introducing collective intelligence into the recommendation system. Assuming that multiple agents will make better decision than single agent, we adopted a multi-agent approach to generate the most similar case, which represents the optimal recommendation from the case base. This paper describes how our system enables agents adopting different similarity measures come to an agreement about the most similar case by the means of majority voting in the judging process. Our framework of a collective judgment system demonstrates its potentials to improve recommendation accuracy, and further enhance the performance of existing smart home assistants.
keywords	Collective Intelligence; Case Based Reasoning; Smart home; Service recommendation; Multi-agent system
series	CAADRIA
email
last changed	2022/06/07 07:52

_id	ecaade2024_92
id	ecaade2024_92
authors	Mayor Luque, Ricardo; Beguin, Nestor; Rizvi Riaz, Sheikh; Dias, Jessica; Pandey, Sneham
year	2024
title	Multi-material Gradient Additive Manufacturing: A data-driven performative design approach to multi-materiality through robotic fabrication
doi	https://doi.org/10.52842/conf.ecaade.2024.1.381
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. 381–390
summary	Buildings are responsible for 39% of global energy-related carbon emissions, with operational activities contributing 28% and materials and construction accounting for 11%(World Green Building Council, 2019) It is therefore vital to reconsider our reliance on fossil fuels for building materials and to develop new advanced manufacturing techniques that enable an integrated approach to material-controlled conception and production. The emergence of Multi-material Additive Manufacturing (MM-AM) technology represents a paradigm shift in producing elements with hybrid properties derived from novel and optimized solutions. Through robotic fabrication, MM-AM offers streamlined operations, reduced material usage, and innovative fabrication methods. It encompasses a plethora of methods to address diverse construction needs and integrates material gradients through data-driven analyses, challenging traditional prefabrication practices and emphasizing the current growth of machine learning algorithms in design processes. The research outlined in this paper presents an innovative approach to MM-AM gradient 3D printing through robotic fabrication, employing data-driven performative analyses enabling control over print paths for sustainable applications in both the AM industry and our built environment. The article highlights several designed prototypes from two distinct phases, demonstrating the framework's viability, implications, and constraints: a workshop dedicated to data-driven analyses in facade systems for MM-AM 3D-printed brick components, and a 3D-printed brick facade system utilizing two renewable and bio-materials—Cork sourced from recycled stoppers and Charcoal, with the potential for carbon sequestration.
keywords	Data-driven Performative design, Multi-material 3d Printing, Material Research, Fabrication-informed Material Design, Robotic Fabrication
series	eCAADe
email
last changed	2024/11/17 22:05

_id	ecaadesigradi2019_233
id	ecaadesigradi2019_233
authors	Noronha Pinto de Oliveira e Sousa, Marcela, Duarte, Jose and Celani, Gabriela
year	2019
title	Urban Street Retrofitting - An Application Study on Bottom-Up Design
doi	https://doi.org/10.52842/conf.ecaade.2019.3.287
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. 287-296
summary	Urban streets will have to be retrofitted to improve walkability and to provide space for a diversity of transport modes. This paper introduces a framework which combines space syntax and shape grammars in a design support method for generating scenarios for urban street retrofitting. A procedure to hierarchize streets and select priority locations for urban street retrofitting is presented. Four different angular choice analyses with decreasing radii are used to derive the hierarchical structure of target urban areas with the aim of triggering shape grammar rules and generating bottom-up intervention designs. The same measure using a local radius to represent walking modal is then used to determine which streets should be retrofitted to improve pedestrian safety and walkability for the largest number of people. An application study using this procedure is presented and results are compared to street hierarchies from two different sources. This study is the first step towards automating the generation of design scenarios for urban street retrofitting.
keywords	Space Syntax; Street Hierarchy; Parametric Urbanism; Scenario Modeling; Travel Behavior
series	eCAADeSIGraDi
email
last changed	2022/06/07 08:00

_id	caadria2019_464
id	caadria2019_464
authors	Scott, Sophie, Doherty, Ben, Fabbri, Alessandra, Gardner, Nicole and Haeusler, M. Hank
year	2019
title	Discoverable Desks - Finding location and orientation in a mobile workplace
doi	https://doi.org/10.52842/conf.caadria.2019.2.653
source	M. Haeusler, M. A. Schnabel, T. Fukuda (eds.), Intelligent & Informed - Proceedings of the 24th CAADRIA Conference - Volume 2, Victoria University of Wellington, Wellington, New Zealand, 15-18 April 2019, pp. 653-662
summary	The drive towards increasing productivity through collaborative ways of working has spurred a parallel trend in flexible and adaptable workplace environments. Mobile desks are one feasible solution to this but workplaces that adopt mobile desks risk creating spatial inefficiencies. These range from overcrowding or underutilization, to potential compliance issues in terms of fire egress requirements and health and safety regulations. While there is a need to understand mobile desking configurations there are currently no well-established ways to track the location and orientation of mobile desks within workplaces. Consequently, this paper describes a research project that adopts an action research methodology as an iterative and participatory framework to investigate and develop a unique method for capturing the location and orientation of freely moveable desks in an open workplace environment. This uses an ensemble of Bluetooth location beacons and computer vision techniques to provide a finer resolution than either method alone can currently provide. The demonstration of this ensemble method is the main contribution of this work. This paper demonstrates that combining these methods can enhance the advantages of each; computer vision gives higher resolution and beacons reduce the scope of the image search task
keywords	Indoor Positioning Systems; Office Space Planning; Location Data; Computer vision; activity-based working
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	ecaadesigradi2019_663
id	ecaadesigradi2019_663
authors	Sha, Yin
year	2019
title	The Emerging of Spontaneous Materiality under Limited Digital Control
doi	https://doi.org/10.52842/conf.ecaade.2019.2.553
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. 553-558
summary	This paper focuses on a new form making method of spontaneous materiality under limited digital control, as a supplement to the trending method of digital materiality. A specific emphasis is placed on the connection between material selection and sensational expression in the contemporary information and digital technologies era. Spontaneous materiality refers to the alteration of material attributes by natural forces. The current techniques of digital materiality rely on accurate digital control and inhibit from the intervention of any unpredictable material variable, which shows excessive scientific calculations and a loss of artistic articulation in design. In the new form making method proposed here, intentional yet limited digital control sets the material framework where the combination of soft and hard materials takes place. With the influence of gravity and spatiotemporal accumulation of selected materials, the fusion of softness and hardness brings a coexistence of different material states and qualities in one object. Thus an integration of shape and matter produces a blurring boundary between physical material and digital form, and more importantly, a sensational experience with expectational slippages of vision and touch. Additional to the ongoing discussion of computation, this design research expands the potential of computation by restricting its influence.
keywords	Spontaneous materiality; limited digital control; sensational expression; sensuous quality; illusion
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:57

_id	ecaadesigradi2019_409
id	ecaadesigradi2019_409
authors	Ulkucu, Yigitcan and Alacam, Sema
year	2019
title	A Decision Support Framework for FLP in the Context of Industrial Facilities by the Use of BIM
doi	https://doi.org/10.52842/conf.ecaade.2019.2.269
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. 269-278
summary	In today's industrial production environment, an effective solution to the FLP (Facility Layout Problem) plays a significant role in deciding whether a facility will hold a competitive advantage against others by its improved workflow. This advantage comes from an efficient placement of facilities, which mostly contributes to the overall business performance. In addition to that, regarding the need to answer the demands of the dynamic market, facilities need to adapt their processes and adapt their production line as quickly as possible. Therefore, a continuous search for a solution to the FLP is present. Although there are many space allocation programs available both as academic and commercial products, present approaches' availability in the BIM environment is not common yet. This paper introduces a decision support system framework which uses Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) to generate the most appropriate solution in Revit Dynamo environment both in the earlier phases of design and through the life-cycle of the facility. The proposed framework will specifically be responsible for generating solutions for equipment location in serial production facilities. As NSGA-II is a Multi-Objective Evolutionary Algorithm (MOEA), a second optimization criterion is defined as the optimization of the foreman's locations distributed on the shop floor. A Dynamo package named Refinery will hold the optimization and evaluation procedures.
keywords	Facility Layout Problems; NSGA-II; Automated Space Layout
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:57

_id	ecaadesigradi2019_360
id	ecaadesigradi2019_360
authors	Wei, Likai, Ta, La, Li, Liang, Han, Yang, Feng, Yingying, Wang, Xin and Xu, Zhen
year	2019
title	RAF: Robot Aware Fabrication - Hand-motion Augmented Robotic Fabrication Workflow and Case Study
doi	https://doi.org/10.52842/conf.ecaade.2019.2.241
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. 241-250
summary	Fabricating process with robotic awareness and creativity makes architect able to explore the new boundary between digital and material world. Although parametric and generative design method make diverse processing of materials possible for robots, it's still necessary to establish a new design-fabrication framework, where we could simultaneously deal with designers, robots, data, sensor technology and material natural characters. In order to develop a softer system without gap between preset program and robot's varying environments, this paper attempts to establish an environment-computer-robot workflow and transform traditional robotic fabrication from linear to more tangible and suitable for architects' and designers' intuitive motion and gesture. RAF (Robotic Aware Fabrication), a concept of real-time external enhancement fabrication is proposed, and a new workflow of HARF (Hand-motion Augmented Robotic Fabrication) is developed, where motion sensor captures designer's hand-motion, filter algorithm recognizes the intention and update the preset program, robotic controller and RSI (Robotic Sensor Interface) adjusts robot's TCP (Tool Center Point) path in real time. With HARF workflow, two case studies of Hand-motion robotic dance and Free-form concrete wall are made.
keywords	RAF; HARF; Hand-motion Sensor; Styrofoam Mold; Concrete Wall; RSI
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:58

_id	ecaadesigradi2019_024
id	ecaadesigradi2019_024
authors	Wit, Andrew John and Ng, Rashida
year	2019
title	cloudMAGNET - A prototype for climatically active light-weight skins
doi	https://doi.org/10.52842/conf.ecaade.2019.2.627
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. 627-636
summary	This paper describes a potential for the integration of micro-encapsulated phase change material (mircoPCM) into lightweight skins as a means of regulating internal climatic conditions of volumetric objects. Viewed through the lens of the recently completed series of quarter-scale cloudMAGNET prototypes tested in the cloud forests of Monteverde, Costa Rica, this research utilized a wound, flexible carbon fiber framework and a lightweight fabric skin coated with varying densities of microPCM. The prototypes were monitored using real-time collection of climate data throughout the testing. In this paper we will demonstrate how climatic variables such as temperature, humidity, and pressure can be passively manipulated by varying the form and energy storage properties of materials without the use of active mechanical systems. Produced to bring awareness to the rising cloud levels within the Monteverde cloud forest, this research is intended to explore the fundamental relationships of material, energy and form. Beyond these objectives, the paper will also illustrate how these methods can be more broadly applied to the development of thermal-regulating lightweight tensile structures. Such innovations could be utilized as a method for the reimagining the architectural design and production processes allowing for the emergence of new typologies of environmentally self-mediating architecture.
keywords	material performance; phase change material; carbon fiber reinforced polymers; computation
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:57

_id	ecaadesigradi2019_308
id	ecaadesigradi2019_308
authors	Yetkin, Ozan and Gönenç Sorguç, Arzu
year	2019
title	Design Space Exploration of Initial Structural Design Alternatives via Artificial Neural Networks
doi	https://doi.org/10.52842/conf.ecaade.2019.1.055
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. 55-60
summary	Increasing implementation of digital tools within a design process generates exponentially growing data in each phase, and inevitably, decision making within a design space with increasing complexity will be a great challenge for the designers in the future. Hence, this research aimed to seek potentials of captured data within a design space and solution space of a truss design problem for proposing an initial novel approach to augment capabilities of digital tools by artificial intelligence where designers are allowed to make a wise guess within the initial design space via performance feedbacks from the objective space. Initial structural design and modelling phase of a truss section was selected as a material of this study since decisions within this stage affect the whole process and performance of the end product. As a method, a generic framework was proposed that can help designers to understand the trade-offs between initial structural design alternatives to make informed decisions and optimizations during the initial stage. Finally, the proposed framework was presented in a case study, and future potentials of the research were discussed.
keywords	design space; objective space; structural design; artificial intelligence; machine learning; optimization
series	eCAADeSIGraDi
email
last changed	2022/06/07 07:57

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