Cumincad : CUMINCAD Papers : Search Results

CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

PDF papers
References

Hits 1 to 20 of 601

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

_id	acadia18_196
id	acadia18_196
authors	Zhang, Yan; Grignard; Aubuchon, Alexander; Lyons, Keven; Larson, Kent
year	2018
title	Machine Learning for Real-time Urban Metrics and Design Recommendations
doi	https://doi.org/10.52842/conf.acadia.2018.196
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. 196-205
summary	Cities are growing, becoming more complex, and changing rapidly. Currently, community engagement for urban decision-making is often ineffective, uninformed, and only occurs in projects’ later stages. To facilitate a more collaborative and evidence-based urban decision- making process for both experts and non-experts, real-time feedback and optimized suggestions are essential. However, most of the current tools for urban planning are neither capable of performing complex simulations in real time nor of providing guidance for better urban performance. CityMatrix was introduced to address these challenges. Machine learning techniques were applied to achieve real-time prediction of multiple urban simulations, and thousands of city configurations were simulated. The simulation results were used to train a convolutional neural network (CNN) to predict the traffic and solar performance of unseen city configurations. The prediction with the CNN is thousands of times faster than the original simulations and maintains a high-quality representation of the results. This machine learning approach was applied as a versatile, quick, accurate, and computationally efficient method not only for real-time feedback, but also for optimized design recommendations. Users involved in the evaluation of this project had a better understanding of the embodied trade-offs of the city and achieved their goals in an efficient manner.
keywords	full paper, optimization, collaboration, urban design & analysis, ai & machine learning
series	ACADIA
type	paper
email
last changed	2022/06/07 07:57

_id	caadria2018_046
id	caadria2018_046
authors	Lu, Siliang and Cochran Hameen, Erica
year	2018
title	Integrated IR Vision Sensor for Online Clothing Insulation Measurement
doi	https://doi.org/10.52842/conf.caadria.2018.1.565
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. 565-573
summary	As one of the most important building systems, HVAC plays a key role in creating a comfortable thermal environment. Predicted Mean Vote (PMV), an index that predicts the mean value of the votes of a large group of persons on the thermal sensation scale, has been adopted to evaluate the built environment. Compared to environmental factors, clothing insulation can be much harder to measure in the field. The existing research on real-time clothing insulation measurement mainly focuses on expensive infrared thermography (IR) cameras. Therefore, to ensure cost-effectiveness, the paper has proposed a solution consisting of a normal camera, IR and air temperature sensors and Arduino Nanos to measure clothing insulation in real-time. Moreover, the algorithm includes the initialization from clothing classification with pre-trained neural network and optimization of the clothing insulation calculation. A total of 8 tests have been conducted with garments for spring/fall, summer and winter. The current results have shown the accuracy of T-shirt classification can reach over 90%. Moreover, compared with the results with IR cameras and reference values, the accuracies of the proposed sensing system vary with different clothing types. Research shall be further conducted and be applied into the dynamic PMV-based HVAC control system.
keywords	clothing insulation; skin temperature; clothing classification; IR temperature sensor; Optimization
series	CAADRIA
email
last changed	2022/06/07 07:59

_id	caadria2018_290
id	caadria2018_290
authors	Wang, Zhenyu, Shi, Jia, Yu, Chuanfei and Gao, Guoyuan
year	2018
title	Automatic Design of Main Pedestrian Entrance of Building Site Based on Machine Learning - A Case Study of Museums in China's Urban Environment
doi	https://doi.org/10.52842/conf.caadria.2018.2.227
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. 227-235
summary	The main pedestrian entrance of the building site has a direct influence on the use of the buildings, so the selection of the main pedestrian entrance is very important in the process of architectural design. The correct selection of the main pedestrian entrance of building site depends on the experience of designers and environment data collected by designers, the process is time consuming and inefficient, especially when the building site located in complex urban environment. In order to improve the efficiency of design process, we used online map to collect museums information in China as training samples, and constructing artificial neural networks to predict the direction of the main pedestrian entrance. After the training, we get the prediction model with 79% prediction accuracy. Although the accuracy still need to be improved, it creates a new approach to analysis the main pedestrian entrance of the site and worth further researching.
keywords	Artificial Neural Network (ANN); Main Pedestrian Entrance of Building Site; Automatic Design
series	CAADRIA
email
last changed	2022/06/07 07:58

_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
doi	https://doi.org/10.52842/conf.acadia.2018.166
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
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_298
id	ecaade2018_298
authors	Rossi, Gabriella and Nicholas, Paul
year	2018
title	Modelling A Complex Fabrication System - New design tools for doubly curved metal surfaces fabricated using the English Wheel
doi	https://doi.org/10.52842/conf.ecaade.2018.1.811
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. 811-820
summary	Standard industrialization and numeration models fail to translate the richness and complexity of traditional crafts into the making of the architectural elements, which excludes them from the industry. This paper introduces a new way of modelling a complex craft fabrication method, namely the English Wheel, that is based on the creation of a cyber-physical system. The cyber-physical system connects a robotic arm and an artificial neural network. The robot arm controls the movement of a metal sheet through the English wheel to achieve desired geometries according to toolpaths and predicted deformations specified by the neural network. The method is demonstrated through the making of 1:1 design probes of doubly curved metal surfaces.
keywords	Digital craft; metal forming; doubly curved surfaces; robotic fabrication; neural networks; cyber-physical system
series	eCAADe
email
last changed	2022/06/07 07:56

_id	acadia18_146
id	acadia18_146
authors	Rossi, Gabriella; Nicholas, Paul
year	2018
title	Re/Learning the Wheel. Methods to Utilize Neural Networks as Design Tools for Doubly Curved Metal Surfaces
doi	https://doi.org/10.52842/conf.acadia.2018.146
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. 146-155
summary	This paper introduces concepts and computational methodologies for utilizing neural networks as design tools for architecture and demonstrates their application in the making of doubly curved metal surfaces using a contemporary version of the English Wheel. The research adopts an interdisciplinary approach to develop a novel method to model complex geometric features using computational models that originate from the field of computer vision. The paper contextualizes the approach with respect to the current state of the art of the usage of artificial neural networks both in architecture and beyond. It illustrates the cyber physical system that is at the core of this research, with a focus on the employed neural network–based computational method. Finally, the paper discusses the repercussions of these design tools on the contemporary design paradigm.
keywords	full paper, ai & machine learning, digital craft, robotic production, computation
series	ACADIA
type	paper
email
last changed	2022/06/07 07:56

_id	acadia18_156
id	acadia18_156
authors	Huang, Weixin; Zheng, Hao
year	2018
title	Architectural Drawings Recognition and Generation through Machine Learning
doi	https://doi.org/10.52842/conf.acadia.2018.156
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
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	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
doi	https://doi.org/10.52842/conf.ecaade.2018.2.253
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
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	ijac201816203
id	ijac201816203
authors	Anderson, Carl; Carlo Bailey, Andrew Heumann and Daniel Davis
year	2018
title	Augmented space planning: Using procedural generation to automate desk layouts
source	International Journal of Architectural Computing vol. 16 - no. 2, 164-177
summary	We developed a suite of procedural algorithms for space planning in commercial offices. These algorithms were benchmarked against 13,000 actual offices designed by human architects. The algorithm performed as well as an architect on 77% of offices, and achieved a higher capacity in an additional 6%, all while following a set of space standards. If the algorithm used the space standards the same way as an architect (a more relaxed interpretation), the algorithm achieved a 97% match rate, which means that the algorithm completed this design task as well as a designer and in a shorter time. The benchmarking of a layout algorithm against thousands of existing designs is a novel contribution of this article, and we argue that it might be a first step toward a more comprehensive method to automate parts of the office layout process.
keywords	Office design, design augmentation, space planning, automation, office layout, desk layouts
series	journal
email
last changed	2019/08/07 14:03

_id	acadia18_136
id	acadia18_136
authors	Austern, Guy; Capeluto, Isaac Guedi; Grobman, Yasha Jacob
year	2018
title	Fabrication-Aware Design of Concrete Façade Panels. A Computational Method For Evaluating the Fabrication of Large- Scale Molds in Complex Geometries
doi	https://doi.org/10.52842/conf.acadia.2018.136
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. 136-145
summary	This paper presents a design methodology for concrete façade panels that takes into consideration constraints related to digital fabrication machinery. A computational method for the real-time evaluation of industrial mold-making techniques, such as milling and hot wire cutting, was developed. The method rapidly evaluates the feasibility, material use, and machining time of complex geometry molds for architectural façade elements. Calculation speed is achieved by mathematically approximating CAM-machining operations. As results are obtained in nearly real time, the method can be easily incorporated into the architectural design process during its initial stages, when changes to the design are more effective. In the paper, we describe the algorithms of the computational evaluation method. We also show how it can be used to introduce fabrication considerations into the design process by using it to rationalize several types of panels. Additionally, we demonstrate how the method can be used in complex, large-scale architectural projects to save machining time and materials by evaluating and altering the paneling subdivision.
keywords	full paper, fabrication & robotics, digital fabrication, performance + simulation, geometry
series	ACADIA
type	paper
email
last changed	2022/06/07 07:54

_id	ecaade2018_219
id	ecaade2018_219
authors	Bai, Nan, Ye, Wenqia, Li, Jianan, Ding, Huichao, Pienaru, Meram-Irina and Bunschoten, Raoul
year	2018
title	Customised Collaborative Urban Design - A Collective User-based Urban Information System through Gaming
doi	https://doi.org/10.52842/conf.ecaade.2018.1.419
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. 419-428
summary	As we step into a new data-based information age, it is important to get citizens involved in the whole design process. Our research tries to build up a user-based urban information system by collecting the data of neighborhood land use preference from all the residents through gaming. The result of each individual decision will be displayed in real time using Augmented Reality technology, while the collective decision dataset will be stored, analyzed and learnt by computer, forming an optimal layout that meets the highest demand of the community. A pre-experiment has been conducted in a. an abstract virtual site and b. an existing site by collecting opinions from 122 participants, which shows that the system works well as a new method for collaborative design. This system has the potential to be applied both in realistic planning processes, as a negotiation toolkit, and in virtual urban forming, in the case of computer games or space colonization.
keywords	Collaborative Design; Customization; Urban Design; Gaming; Information System
series	eCAADe
email
last changed	2022/06/07 07:54

_id	sigradi2018_1580
id	sigradi2018_1580
authors	Bomfim de Araujo, Alana; Groetelaars , Natalie Johanna; Leão de Amorim, Arivaldo
year	2018
title	Use of Dense Stereo Matching for Existing Building Documentation: Comparative Analysis of Tools
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. 874-879
summary	This paper presents a comparative study of Dense Stereo Matching (DSM) tools to generate point cloud from digital photogrammetric restitution. The capability of four different state-of-the-art software systems as Photoscan (Agisoft), 3DF Zephyr Free (3Dflow), Remake (Autodesk) and Recap 360 (Autodesk) is examined to document a historical object. The main aspects compared are: processing time, export file formats, file size, quality and density of point clouds obtained from tools standard parameters. From the literature review, the analysis and the experiments, it is possible to evaluate the potential of DSM technique for the existing building documentation.
keywords	Dense Stereo Matching (DSM); Digital photogrammetry; DSM tools; Point cloud; Triangular irregular network (TIN)
series	SIGRADI
email
last changed	2021/03/28 19:58

_id	caadria2019_204
id	caadria2019_204
authors	Calixto, Victor, Gu, Ning and Celani, Gabriela
year	2019
title	A Critical Framework of Smart Cities Development
doi	https://doi.org/10.52842/conf.caadria.2019.2.685
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. 685-694
summary	This paper investigates through a review of the current literature on smart cities, reflecting different concepts across different political-social contexts, seeking to contribute to the establishment of a critical framework for smart cities development. The present work provides a review of the literature of 250 selected publications from four databases (Scielo, ScienceDirect, worldwide science, and Cumincad), covering the years from 2012 to 2018. Publications were categorised by the following steps: 3RC framework proposed by Kummitha and Crutzen (2017), the main political sectors of city planning, implementation strategies, computational techniques, and organisation rules. The information was analised graphically trying to identify tendencies along the time, and also, seeking to explore future possibilities for implementations in different political-social contexts. As a case of study, Australia and Brazil were compared using the proposed framework.
keywords	smart city; smart cities; literature review
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	ecaade2018_164
id	ecaade2018_164
authors	Chang, Mei-Chih, Buš, Peter, Tartar, Ayça, Chirkin, Artem and Schmitt, Gerhard
year	2018
title	Big-Data Informed Citizen Participatory Urban Identity Design
doi	https://doi.org/10.52842/conf.ecaade.2018.2.669
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. 669-678
summary	The identity of an urban environment is important because it contributes to self-identity, a sense of community, and a sense of place. However, under present-day conditions, the identities of expanding cities are rapidly deteriorating and vanishing, especially in the case of Asian cities. Therefore, cities need to build their urban identity, which includes the past and points to the future. At the same time, cities need to add new features to improve their livability, sustainability, and resilience. In this paper, using data mining technologies for various types of geo-referenced big data and combine them with the space syntax analysis for observing and learning about the socioeconomic behavior and the quality of space. The observed and learned features are identified as the urban identity. The numeric features obtained from data mining are transformed into catalogued levels for designers to understand, which will allow them to propose proper designs that will complement or improve the local traditional features. A workshop in Taiwan, which focuses on a traditional area, demonstrates the result of the proposed methodology and how to transform a traditional area into a livable area. At the same time, we introduce a website platform, Quick Urban Analysis Kit (qua-kit), as a tool for citizens to participate in designs. After the workshop, citizens can view, comment, and vote on different design proposals to provide city authorities and stakeholders with their ideas in a more convenient and responsive way. Therefore, the citizens may deliver their opinions, knowledge, and suggestions for improvements to the investigated neighborhood from their own design perspective.
keywords	Urban identity; unsupervised machine learning; Principal Component Analysis (PCA); citizen participated design; space syntax
series	eCAADe
email
last changed	2022/06/07 07:56

_id	caadria2018_056
id	caadria2018_056
authors	Chirkin, Artem, Pishniy, Maxim and Sender, Arina
year	2018
title	Generilized Visibility-Based Design Evaluation Using GPU
doi	https://doi.org/10.52842/conf.caadria.2018.2.483
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. 483-492
summary	Visibility plays an important role in perception and use of an urban design, and thus often becomes a target of design analysis. This work presents a fast method of evaluating various visibility-based design characteristics, such as isovists or insolation exploiting the GPU rendering pipeline and compute shaders. The proposed method employs a two-stage algorithm on each point of interest. First, it projects the visible space around a vantage point onto an equirectangular map. Second, it folds the map using a flexibly defined function into a single value that is associated with the vantage point. Being executed on a grid of points in a 3D scene, it can be visualized as a heat map or utilized by another algorithm for further design analysis. The developed system provides nearly real-time analysis tools for an early-stage design process to a broad audience via web services.
keywords	design analysis; design evaluation; GPU; isovist; insolation
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	acadia18_286
id	acadia18_286
authors	Claire Im, Hyeonji; AlOthman, Sulaiman; García del Castillo, Jose Luis
year	2018
title	Responsive Spatial Print. Clay 3D printing of spatial lattices using real-time model recalibration
doi	https://doi.org/10.52842/conf.acadia.2018.286
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. 286-293
summary	Additive manufacturing processes are typically based on a horizontal discretization of solid geometry and layered deposition of materials, the speed and the rate of which are constant and determined by the stability criteria. New methods are being developed to enable three-dimensional printing of complex self-supporting lattices, expanding the range of possible outcomes in additive manufacturing. However, these processes introduce an increased degree of formal and material uncertainty, which require the development of solutions specific to each medium. This paper describes a development to the 3D printing methodology for clay, incorporating a closed-loop feedback system of material surveying and self-correction to recompute new depositions based on scanned local deviations from the digital model. This Responsive Spatial Print (RSP) method provides several improvements over the Spatial Print Trajectory (SPT) methodology for clay 3D printing of spatial lattices previously developed by the authors. This process compensates for the uncertain material behavior of clay due to its viscosity, malleability, and deflection through constant model recalibration, and it increases the predictability and the possible scale of spatial 3D prints through real-time material-informed toolpath generation. The RSP methodology and early successful results are presented along with new challenges to be addressed due to the increased scale of the possible outcomes.
keywords	work in progress, closed loop system, spatial clay printing, self-supporting lattice, in-situ printking, extrusion rate, material behavior
series	ACADIA
type	paper
email
last changed	2022/06/07 07:52

_id	caadria2018_333
id	caadria2018_333
authors	Cupkova, Dana, Byrne, Daragh and Cascaval, Dan
year	2018
title	Sentient Concrete - Developing Embedded Thermal and Thermochromic Interactions for Architecture and Built Environment
doi	https://doi.org/10.52842/conf.caadria.2018.2.545
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. 545-554
summary	Historically, architectural design focused on adaptation of built environment to serve human needs. Recently embedded computation and digital fabrication have advanced means to actuate physical infrastructure in real-time. These 'reactive spaces' have typically explored movement and media as a means to achieve reactivity and physical deformation (Chatting et al. 2017). However, here we recontextualize 'reactive' as finding new mechanisms for permanent and non-deformable everyday materials and environments. In this paper, we describe our ongoing work to create a series of complex forms - modular concrete panels - using thermal, tactile and thermochromic responses controlled by embedded networked system. We create individualized pathways to thermally actuate these surfaces and explore expressive methods to respond to the conditions around these forms - the environment, the systems that support them, their interaction and relationships to human occupants. We outline the design processes to achieve thermally adaptive concrete panels, illustrate interactive scenarios that our system enables, and discuss opportunities for new forms of interactivity within the built environment.
keywords	Responsive environments; Geometrically induced thermodynamics; Ambient devices; Internet of things; Modular electronic systems
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	ecaade2018_121
id	ecaade2018_121
authors	Dimopoulos, Georgios
year	2018
title	Museum and Cultural Heritage in the World of Digital Technology
doi	https://doi.org/10.52842/conf.ecaade.2018.2.199
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. 199-204
summary	Museum as a cultural epiphenomenon reflects all changes occurring in cultural, political, economic and technological fields. Nowadays, as new technologies bring upon significant changes in the way we perceive space and time and open up new ways in understanding the world and all things, the museum is perceived as a network of potential things, a kind of web intersection that connects objective with digital reality. New technologies within the museum's space form a new relationship between the public and the cultural heritage objects, and offers new approach perspectives by reinforcing revisionist trends as far as the role and importance of the museum.
keywords	metanarratives; digital museum; visual reality
series	eCAADe
email
last changed	2022/06/07 07:55

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

_id	ijac201816205
id	ijac201816205
authors	Faircloth,Billie; Ryan Welch, Martin Tamke, Paul Nicholas, Phil Ayres, Yulia Sinke, Brandon Cuffy and Mette Ramsgaard Thomsen
year	2018
title	Multiscale modeling frameworks for architecture: Designing the unseen and invisible with phase change materials
source	International Journal of Architectural Computing vol. 16 - no. 2, 104-122
summary	Multiscale design and analysis models promise a robust, multimethod, multidisciplinary approach, but at present have limited application during the architectural design process. To explore the use of multiscale models in architecture, we develop a calibrated modeling and simulation platform for the design and analysis of a prototypical envelope made of phase change materials. The model is mechanistic in nature, incorporates material-scale and precinct scale-attributes, and supports the design of two- and three-dimensional phase change material geometries informed by heat transfer phenomena. Phase change material behavior, in solid and liquid states, dominates the visual and numerical evaluation of the multiscale model. Model calibration is demonstrated using real-time data gathered from the prototype. Model extensibility is demonstrated when it is used by designers to predict the behavior of alternate envelope options. Given the challenges of modeling phase change material behavior in this multiscale model, an additional multiple linear regression model is applied to data collected from the physical prototype in order to demonstrate an alternate method for predicting the melting and solidification of phase change materials.
keywords	Multiscale modeling, mechanistic modeling, heat transfer modeling, phase change materials, model validation
series	journal
email
last changed	2019/08/07 14:03

For more results click below: