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	ijac201816101
id	ijac201816101
authors	Nisztu, Maciejk and Pawe³ B. Myszkowsk
year	2018
title	Usability of contemporary tools for the computational design of architectural objects: Review, features evaluation and reflection
source	International Journal of Architectural Computing vol. 16 - no. 1, 58-84
summary	This article is an overview focused on functionality and usability of selected contemporary approaches for the computational floor plan generation of architectural objects. This article describes current solutions for generative architectural design and focuses on their usability from the point of view of architectural design practice. Recent research papers and prototypes, as well as the most important tools (selected computer-aided design and BIM software) for generative design from the architectural perspective, are described. The functionalities and level of usability of present-day software and prototypes are described. In addition, the descriptive review of the research prototypes architectural design outcomes is present. Furthermore, the survey among active architects regarding the usage of computational tools in the professional practice and possible guidelines for the development of such tools are present. This article summarises with the conclusion about the current state of generative floor plan design tools, the lack of fully functional and developed commercial tools of this type on the market and future directions for the development of generative floor plans tools.
keywords	Architectural design, case studies, computer-aided architectural design, optimisation in computer-aided architectural design, computer-aided architectural design applications
series	journal
email
last changed	2019/08/07 14:03

_id	ecaade2018_295
id	ecaade2018_295
authors	Dezen-Kempter, Eloisa, Cogima, Camila Kimi, Vieira de Paiva, Pedro Victor and Garcia de Carvalho, Marco Antonio
year	2018
title	BIM for Heritage Documentation - An ontology-based approach
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 213-222
doi	https://doi.org/10.52842/conf.ecaade.2018.1.213
summary	In the recent decades, the high-resolution remote sensing, through 3D laser scanning and photogrammetry benefited historic buildings maintenance, conservation, and restoration works. However, the dense surface models (DSM) generated from the data capture have nonstructured features as lack of topology and semantic discretization. The process to create a semantically oriented 3D model from the DSM, using the of Building Information Model technology, is a possibility to integrate historical information about the life cycle of the building to maintain and improving architectural valued building stock to its functional level and safeguarding its outstanding historical value. Our approach relies on an ontology-based system to represent the knowledge related to the building. Our work outlines a model-driven approach based on the hybrid data acquisition, its post-processing, the identification of the building' main features for the parametric modeling, and the development of an ontological map integrated with the BIM model. The methodology proposed was applied to a large-scale industrial historical building, located in Brazil. The DSM were compared, providing a qualitative assessment of the proposed method.
keywords	Reality-based Surveying; Ontology-based System; BIM; Built heritage management
series	eCAADe
email
last changed	2022/06/07 07:55

_id	caadria2018_303
id	caadria2018_303
authors	Song, Jae Yeol, Kim, Jin Sung, Kim, Hayan, Choi, Jungsik and Lee, Jin Kook
year	2018
title	Approach to Capturing Design Requirements from the Existing Architectural Documents Using Natural Language Processing Technique
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 2, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 247-254
doi	https://doi.org/10.52842/conf.caadria.2018.2.247
summary	This paper describes an approach to utilizing natural language processing (NLP) to capture design requirements from the natural language-based architectural documents. In various design stage of the architectural process, there are several different kinds of documents describing requirements for buildings. Capturing the design requirements from those documents is based on extracting information of objects, their properties, and relations. Until recently, interpreting and extracting that information from documents are almost done by a manual process. To intelligently automate the conventional process, the computer has to understand the semantics of natural languages. In this regards, this paper suggests an approach to utilizing NLP for semantic analysis which enables the computer to understand the semantics of the given text data. The proposed approach has following steps: 1) extract noun words which mostly represent objects and property data in Korean Building Act; 2) analyze the semantic relations between words, using NLP and deep learning; 3) Based on domain database, translate the noun words in objects and properties data and find out their relations.
keywords	NLP (Natural Language Processing); Deep learning; Design requirements; Korean Building Act; Semantic analysis
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	ecaade2018_265
id	ecaade2018_265
authors	Tauscher, Helga and Stouffs, Rudi
year	2018
title	An IFC-to-CityGML Triple Graph Grammar
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 517-524
doi	https://doi.org/10.52842/conf.ecaade.2018.1.517
summary	A triple graph grammar has been adopted as a formal framework for semantic and geometric conversion of IFC models into CityGML Level of Detail (LoD) 3/4 building models. The advantages of a triple graph grammar approach are threefold: firstly, it allows for the conversion rules to be graphically defined; secondly, the generation of the conversion routines corresponding to these rules can be automated; and, thirdly, a complete mapping can be achieved in an incremental way by adding rule by rule.The objective of this work is the development of a methodology and algorithms to automate the conversion of Building Information Models into CityGML building models, capturing both geometric and semantic information as available in the BIM models, in order to create semantically enriched 3D city models that include both exterior and interior structures such as corridors, rooms, internal doors, and stairs.
keywords	BIM; CityGML; Triple Graph Grammar; conversion
series	eCAADe
email
last changed	2022/06/07 07:58

_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	acadia18_166
id	acadia18_166
authors	Kvochick, Tyler
year	2018
title	Sneaky Spatial Segmentation. Reading Architectural Drawings with Deep Neural Networks and Without Labeling Data
source	ACADIA // 2018: Recalibration. On imprecisionand infidelity. [Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-17729-7] Mexico City, Mexico 18-20 October, 2018, pp. 166-175
doi	https://doi.org/10.52842/conf.acadia.2018.166
summary	Currently, it is nearly impossible for an artificial neural network to generalize a task from very few examples. Humans, however, excel at this. For instance, it is not necessary for a designer to see thousands or millions of unique examples of how to place a given drawing symbol in a way that meets the economic, aesthetic, and performative goals of the project. In fact, the goals can be (and usually are) communicated abstractly in natural language. Machine learning (ML) models, however, do need numerous examples. The methods that we explore here are an attempt to circumvent this in order to make ML models more immediately useful. In this work, we present progress on the application of contemporary ML techniques to the design process in the architecture, engineering, and construction (AEC) industry. We introduce a technique to partially circumvent the data hungriness of neural networks, which is a significant impediment to their application outside of the ML research community. We also show results on the applicability of this technique to real-world drawings and present research that addresses how some fundamental attributes of drawings as images affect the way they are interpreted in deep neural networks. Our primary contribution is a technique to train a neural network to segment real-world architectural drawings after using only generated pseudodrawings.
keywords	full paper, representation + perception, computation, ai & machine learning
series	ACADIA
type	paper
email
last changed	2022/06/07 07:51

_id	ecaade2018_329
id	ecaade2018_329
authors	De Luca, Francesco, Nejur, Andrei and Dogan, Timur
year	2018
title	Facade-Floor-Cluster - Methodology for Determining Optimal Building Clusters for Solar Access and Floor Plan Layout in Urban Environments
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 2, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 585-594
doi	https://doi.org/10.52842/conf.ecaade.2018.2.585
summary	Daylight standards are one of the main factors for the shape and image of cities. With urbanization and ongoing densification of cities, new planning regulations are emerging in order to manage access to sun light. In Estonia a daylight standard defines the rights of light for existing buildings and the direct solar access requirement for new premises. The solar envelope method and environmental simulations to compute direct sun light hours on building façades can be used to design buildings that respect both daylight requirements. However, no existing tool integrates both methods in an easy to use manner. Further, the assessment of façade performance needs to be related to the design of interior layouts and of building clusters to be meaningful to architects. Hence, the present work presents a computational design workflow for the evaluation and optimisation of high density building clusters in urban environments in relation to direct solar access requirements and selected types of floor plans.
keywords	Performance-driven Design; Urban Design; Direct Solar Access; Environmental Simulations and Evaluations; Parametric Modelling
series	eCAADe
email
last changed	2022/06/07 07:55

_id	ascaad2021_065
id	ascaad2021_065
authors	Fraschini, Matteo; Julian Raxworthy
year	2021
title	Territories Made by Measure: The Parametric as a Way of Teaching Urban Design Theory
source	Abdelmohsen, S, El-Khouly, T, Mallasi, Z and Bennadji, A (eds.), Architecture in the Age of Disruptive Technologies: Transformations and Challenges [9th ASCAAD Conference Proceedings ISBN 978-1-907349-20-1] Cairo (Egypt) [Virtual Conference] 2-4 March 2021, pp. 494-506
summary	Design tools like Grasshopper are often used to either generate novel forms, to automate certain design processes or to incorporate scientific factors. However, any Grasshopper definition has certain assumptions about design and space built into it from its earliest genesis, when the initial algorithm is set out. Correspondingly, implicit theoretical positions are built into definitions, and therefore its results. Approaching parametric design as a question of architectural, landscape architectural or urban design theory allows the breaking down of traditional boundaries between the technical and the historical or theoretical, and the way parametric design, and urban design history & theory, can be conveyed in the teaching environment. Once the boundaries between software and history & theory are transgressed, Grasshopper can be a way of testing the principles embedded in historical designs and thus these two disciplines can be joined. In urban design, there is an inherent clash between an ideal model and existing urban geography or morphology, and also between formal (qualitative) and numerical (quantitative) aspects. If a model provides a necessary vision for future development, an existing topography then results from the continuous human and natural modifications of a territory. To explore this hypothesis, the “Urban Design Representation” subject in the Master of Urban Design program at the University of Cape Town taught in 2017 & 2018 was approached “parametrically” from these two opposite, albeit convergent, starting points: the conceptual/rational versus the physical/empiric representations of a territory. In this framework, Grasshopper was used to represent typical standards and parameters of modern urban planning (for example, Floor/Area Ratio, height and distance between buildings, site coverage, etc), and a typological approach was adopted to study and “decode” the relationship between public and private space, between the street, the block and topography, between solids and voids. This methodology permits a cross-comparison of different urban design models and the immediate evaluation of their formal outputs derived from parametric data.
series	ASCAAD
email
last changed	2021/08/09 13:13

_id	acadia18_156
id	acadia18_156
authors	Huang, Weixin; Zheng, Hao
year	2018
title	Architectural Drawings Recognition and Generation through Machine Learning
source	ACADIA // 2018: Recalibration. On imprecisionand infidelity. [Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-17729-7] Mexico City, Mexico 18-20 October, 2018, pp. 156-165
doi	https://doi.org/10.52842/conf.acadia.2018.156
summary	With the development of information technology, the ideas of programming and mass calculation were introduced into the design field, resulting in the growth of computer- aided design. With the idea of designing by data, we began to manipulate data directly, and interpret data through design works. Machine Learning as a decision making tool has been widely used in many fields. It can be used to analyze large amounts of data and predict future changes. Generative Adversarial Network (GAN) is a model framework in machine learning. It’s specially designed to learn and generate output data with similar or identical characteristics. Pix2pixHD is a modified version of GAN that learns image data in pairs and generates new images based on the input. The author applied pix2pixHD in recognizing and generating architectural drawings, marking rooms with different colors and then generating apartment plans through two convolutional neural networks. Next, in order to understand how these networks work, the author analyzed their framework, and provided an explanation of the three working principles of the networks, convolution layer, residual network layer and deconvolution layer. Lastly, in order to visualize the networks in architectural drawings, the author derived data from different layer and different training epochs, and visualized the findings as gray scale images. It was found that the features of the architectural plan drawings have been gradually learned and stored as parameters in the networks. As the networks get deeper and the training epoch increases, the features in the graph become more concise and clearer. This phenomenon may be inspiring in understanding the designing behavior of humans.
keywords	full paper, design study, generative design, ai + machine learning, ai & machine learning
series	ACADIA
type	paper
email
last changed	2022/06/07 07:49

_id	acadia21_70
id	acadia21_70
authors	McAndrew, Claire; Jaschke, Clara; Retsin, Gilles; Saey, Kevin; Claypool, Mollie; Parissi, Danaë
year	2021
title	House Block
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 B. Bogosian, K. Dörfler, B. Farahi, J. Garcia del Castillo y López, J. Grant, V. Noel, S. Parascho, and J. Scott. 70-75.
doi	https://doi.org/10.52842/conf.acadia.2021.070
summary	House Block was a temporary housing prototype in East London, UK from April to May 2021. The project constituted the most recent in a series of experiments developing Automated Architecture (AUAR) Labs’ discrete framework for housing production, one which repositions the architect as curator of a system and enables participants to engage with active agency. Recognizing that there is a knowledge gap to be addressed for this reconfiguration of practices to take form, this project centred on making automation and its potential for local communities tangible. This sits within broader calls advocating for a more material alignment of inclusive design with makers and 21st Century making in practice (see, for example, Luck 2018). House Block was designed and built using AUAR’s discrete housing system consisting of a kit of parts, known as Block Type A. Each block was CNC milled from a single sheet of plywood, assembled by hand, and then post-tensioned on site. Constructed from 270 identical blocks, there are no predefined geometric types or hierarchy between parts. The discrete enables an open-ended, adaptive system where each block can be used as a column, floor slab, wall, or stair—allowing for disconnection, reconfiguration, and reassembly (Retsin 2019). The democratisation of design and production that defines the discrete creates points for alternative value systems to enter, for critical realignments in architectural production.
series	ACADIA
type	project
email
last changed	2023/10/22 12:06

_id	ecaade2018_398
id	ecaade2018_398
authors	Papavasiliou, Mattheos
year	2018
title	The Didactic Aspect of Ars Combinatoria in Architectural Design - Employing syntactic ("space syntax") formulations to communicate architectural design to students of Architecture.
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 2, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 525-530
doi	https://doi.org/10.52842/conf.ecaade.2018.2.525
summary	This paper presents educative aspects of visualization techniques based on an idea by B. Hillier to illustrate architectural forms with the space syntax theory. It explores and renders the technique of transformation and implementation of syntactic analysis in order to convey to students of Architecture spatial concepts and to differentiate spatial arrangements that present understandably similarities and differences. The technique is applied to plans of well-known examples from the history of Architecture and illustrates to a sufficient extent the theoretical interpretations taught in the architectural design studio.
keywords	architectural configuration; design strategy; design analysis; shape evaluation
series	eCAADe
email
last changed	2022/06/07 08:00

_id	ecaade2023_10
id	ecaade2023_10
authors	Sepúlveda, Abel, Eslamirad, Nasim and De Luca, Francesco
year	2023
title	Machine Learning Approach versus Prediction Formulas to Design Healthy Dwellings in a Cold Climate
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. 359–368
doi	https://doi.org/10.52842/conf.ecaade.2023.2.359
summary	This paper presents a study about the prediction accuracy of daylight provision and overheating levels in dwellings when considering different methods (machine learning vs prediction formulas), training, and validation data sets. An existing high-rise building located in Tallinn, Estonia was considered to compare the best ML predictive method with novel prediction formulas. The quantification of daylight provision was conducted according to the European daylight standard EN 17037:2018 (based on minimum Daylight Factor (minDF)) and overheating level in terms of the degree-hour (DH) metric included in local regulations. The features included in the dataset are the minDF and DH values related to different combinations of design parameters: window-to-floor ratio, level of obstruction, g-value, and visible transmittance of the glazing system. Different training and validation data sets were obtained from a main data set of 5120 minDF values and 40960 DH values obtained through simulation with Radiance and EnergyPlus, respectively. For each combination of training and validation dataset, the accuracy of the ML model was quantified and compared with the accuracy of the prediction formulas. According to our results, the ML model could provide more accurate minDF/DH predictions than by using the prediction formulas for the same design parameters. However, the amount of room combinations needed to train the machine-learning model is larger than for the calibration of the prediction formulas. The paper discuss in detail the method to use in practice, depending on time and accuracy concerns.
keywords	Optimization, Daylight, Thermal Comfort, Overheating, Machine Learning, Predictive Model, Dwellings, Cold Climates
series	eCAADe
email
last changed	2023/12/10 10:49

_id	sigradi2018_1417
id	sigradi2018_1417
authors	Bambozzi, Lucas
year	2018
title	The Invisible Around: Art And Informational Space [The Unstable Place]
source	SIGraDi 2018 [Proceedings of the 22nd Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Brazil, São Carlos 7 - 9 November 2018, pp. 1128-1133
summary	The paper discusses variants of informational spaces, permeated by connectivity and communication flow. The approach considers the 'place' as a field of semantic migrations, it seeks to investigate an architectural space that tends to include invisible aspects in its constitution, affected by a set of recent communication technologies. It comments on creative processes and artistic experiments investigating ways to "see" or visualize electromagnetic fields, radio waves, wi-fi and cellular signals generated by media in circulation spaces, in convergences of crossing signs and systems.
keywords	Informational space; Electromagnetic fields; Obsolescence; Mobility; Context specificity
series	SIGRADI
email
last changed	2021/03/28 19:58

_id	ijac201816407
id	ijac201816407
authors	Mahankali, Ranjeeth; Brian R. Johnson and Alex T. Anderson
year	2018
title	Deep learning in design workflows: The elusive design pixel
source	International Journal of Architectural Computing vol. 16 - no. 4, 328-340
summary	The recent wave of developments and research in the field of deep learning and artificial intelligence is causing the border between the intuitive and deterministic domains to be redrawn, especially in computer vision and natural language processing. As designers frequently invoke vision and language in the context of design, this article takes a step back to ask if deep learning’s capabilities might be applied to design workflows, especially in architecture. In addition to addressing this general question, the article discusses one of several prototypes, BIMToVec, developed to examine the use of deep learning in design. It employs techniques like those used in natural language processing to interpret building information models. The article also proposes a homogeneous data format, provisionally called a design pixel, which can store design information as spatial-semantic maps. This would make designers’ intuitive thoughts more accessible to deep learning algorithms while also allowing designers to communicate abstractly with design software.
keywords	Associative logic, creative processes, deep learning, embedding vectors, BIMToVec, homogeneous design data format, design pixel, idea persistence
series	journal
email
last changed	2019/08/07 14:04

_id	caadria2018_062
id	caadria2018_062
authors	Narengerel, Amartuvshin, Hong, Sukjoo, Lee, Chae-Seok and Lee, Ji-Hyun
year	2018
title	FBSMAP: The Spatial Representation Method for Intelligent Semantic Service in Indoor Environment
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 2, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 587-596
doi	https://doi.org/10.52842/conf.caadria.2018.2.587
summary	In order to provide intelligent services in complex and diverse indoor environments, it is necessary to understand spatial features of indoor objects: furniture and items. Function-Behavior-Structure Map (FBSMAP), which is a novel indoor representation method that focuses on space functionality for intelligent semantic services, is introduced in this study. The three steps of FBSMAP are defining spatial components, constructing semantic map for indoor environment, and securing spatial features. This novel implementation method is implemented and examined on 3D house models.
keywords	Indoor Representation Method; Semantic Space; Spatial Subdivision; IndoorGML; Furniture Semantics
series	CAADRIA
email
last changed	2022/06/07 07:58

_id	caadria2018_173
id	caadria2018_173
authors	Stouffs, Rudi
year	2018
title	A Triple Graph Grammar Approach to Mapping IFC Models into CityGML Building Models
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 2, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 41-50
doi	https://doi.org/10.52842/conf.caadria.2018.2.041
summary	A triple graph grammar approach is adopted as a formal framework for semantic and geometric conversion of IFC models into CityGML Level of Detail 3/4 building models. The triple graph grammar approach supports a semantic mapping from IFC to CityGML, the generation of conversion routines from this mapping, and an incremental approach to achieving a "complete and near-lossless" mapping. The objective of this approach is the development of a methodology and algorithms to automate the conversion of Building Information Models into CityGML building models, capturing both geometric and semantic information as available in the BIM models, in order to create semantically enriched 3D city models that include both exterior and interior structures.
keywords	BIM; CityGML; conversion; semantic; automated
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	ecaade2018_331
id	ecaade2018_331
authors	Trento, Armando and Fioravanti, Antonio
year	2018
title	Contextual Capabilities Meet Human Behaviour - Round the peg and square the hole
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 1, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 613-620
doi	https://doi.org/10.52842/conf.ecaade.2018.1.613
summary	To improve environmental wellbeing and productivity, design innovation focuses on human's use-process, evolving individual space to flexible and specialized ones, according to the users' tasks - activity-based. BIM models supports sophisticated behaviours' simulation such as energy, acoustics, although it is not able to manage space use-processes. The present paper rather than a report of a case study or the presentation of a new methodology wants to contribute, together with previous works, in sketching a theroretical framework within which it is possible to compute the interaction between users and spaces (and vice versa). The quest is to reflect on possible paths for engineering knowledge and understanding, providing a BIM system the semantic information required to operate adaptively and achieve robust and innovative goal-directed behavior. Compared to current research on simulation systems, this research approach links Context, intended as spaces capabilities to Actor's Behavioural Knowledge including formalization of personality typologies and profiled behavioural patterns. By means of a classical problem solving metaphor, the "squared peg in a round hole" one, multiple categories for goal achievement are sketched, based on reciprocal Actors and Context behaviour adaptation.
keywords	Use-process Knowledge; Behavioural Knowledge; Use Simulation; Cognitive Computing
series	eCAADe
email
last changed	2022/06/07 07:57

_id	caadria2018_044
id	caadria2018_044
authors	Inoue, Kazuya, Fukuda, Tomohiro, Cao, Rui and Yabuki, Nobuyoshi
year	2018
title	Tracking Robustness and Green View Index Estimation of Augmented and Diminished Reality for Environmental Design - PhotoAR+DR2017 project
source	T. Fukuda, W. Huang, P. Janssen, K. Crolla, S. Alhadidi (eds.), Learning, Adapting and Prototyping - Proceedings of the 23rd CAADRIA Conference - Volume 1, Tsinghua University, Beijing, China, 17-19 May 2018, pp. 339-348
doi	https://doi.org/10.52842/conf.caadria.2018.1.339
summary	To assess an environmental design, augmented and diminished reality (AR/DR) have a potential to build a consensus more smoothly through the landscape simulation of new design visualization of the items to be assessed, such as the green view index. However, the current system is still considered to be impractical because it does not provide complete user experience. Thus, we aim to improve the robustness of the AR/DR system and to integrate the estimation of the green view index into the AR/DR system on a game engine. Further, we achieve an improved stable tracking by eliminating the outliers of the tracking reference points using the random sample consensus (RANSAC) method and by defining the tracking reference points over an extensive area of the AR/DR display. Additionally, two modules were implemented, among which one module is used to solve the occlusion problem while the other is used to estimate the green view index. The novel integrated AR/DR system with all modules was developed on the game engine. A mock design project was developed in an outdoor environment for simulation purposes, thereby verifying the applicability of the developed system.
keywords	Environmental Design; Augmented Reality (AR); Diminished Reality (DR); Green View Index; Segmentation
series	CAADRIA
email
last changed	2022/06/07 07:50

_id	ecaade2018_370
id	ecaade2018_370
authors	Abdelmohsen, Sherif, Massoud, Passaint, El-Dabaa, Rana, Ibrahim, Aly and Mokbel, Tasbeh
year	2018
title	A Computational Method for Tracking the Hygroscopic Motion of Wood to develop Adaptive Architectural Skins
source	Kepczynska-Walczak, A, Bialkowski, S (eds.), Computing for a better tomorrow - Proceedings of the 36th eCAADe Conference - Volume 2, Lodz University of Technology, Lodz, Poland, 19-21 September 2018, pp. 253-262
doi	https://doi.org/10.52842/conf.ecaade.2018.2.253
summary	Low-cost programmable materials such as wood have been utilized to replace mechanical actuators of adaptive architectural skins. Although research investigated ways to understand the hygroscopic response of wood to variations in humidity levels, there are still no clear methods developed to track and analyze such response. This paper introduces a computational method to analyze, track and store the hygroscopic response of wood through image analysis and continuous tracking of angular measurements in relation to time. This is done through a computational closed loop that links the smart material interface (SMI) representing hygroscopic response with a digital and tangible interface comprising a Flex sensor, Arduino kit, and FireFly plugin. Results show no significant difference between the proposed sensing mechanism and conventional image analysis tracking systems. Using the described method, acquiring real-time data can be utilized to develop learning mechanisms and predict the controlled motion of programmable material for adaptive architectural skins.
keywords	Hygroscopic properties of wood; Adaptive architecture; Programmable materials; Real-time tracking
series	eCAADe
email
last changed	2022/06/07 07:54

_id	acadia18_394
id	acadia18_394
authors	Adel, Arash; Thoma, Andreas; Helmreich, Matthias; Gramazio, Fabio; Kohler, Matthias
year	2018
title	Design of Robotically Fabricated Timber Frame Structures
source	ACADIA // 2018: Recalibration. On imprecisionand infidelity. [Proceedings of the 38th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-17729-7] Mexico City, Mexico 18-20 October, 2018, pp. 394-403
doi	https://doi.org/10.52842/conf.acadia.2018.394
summary	This paper presents methods for designing nonstandard timber frame structures, which are enabled by cooperative multi-robotic fabrication at building-scale. In comparison to the current use of automated systems in the timber industry for the fabrication of plate-like timber frame components, this research relies on the ability of robotic arms to spatially assemble timber beams into bespoke timber frame modules. This paper investigates the following topics: 1) A suitable constructive system facilitating a just-in-time robotic fabrication process. 2) A set of assembly techniques enabling cooperative multi-robotic spatial assembly of bespoke timber frame modules, which rely on a man-machine collaborative scenario. 3) A computational design process, which integrates architectural requirements, fabrication constraints, and assembly logic. 4) Implementation of the research in the design and construction of a multi-story building, which validates the developed methods and highlights the architectural implications of this approach.
keywords	full paper, fabrication & robotics, generative design, computation, timber architecture
series	ACADIA
type	paper
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last changed	2022/06/07 07:54

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