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	acadia17_330
id	acadia17_330
authors	Krietemeyer, Bess; Bartosh, Amber; Covington, Lorne
year	2017
title	Shared Realities: A Method for Adaptive Design Incorporating Real-Time User Feedback using Virtual Reality and 3D Depth-Sensing Systems
doi	https://doi.org/10.52842/conf.acadia.2017.330
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 330- 339
summary	When designing interactive architectural systems and environments, the ability to gather user feedback in real time provides valuable insight into how the system is received and ultimately performs. However, physically testing or simulating user behavior with an interactive system outside of the actual context of use can be challenging due to time constraints and assumptions that do not reflect accurate social, behavioral, or environmental conditions. Employing evidence based, user-centered design practices from the field of human–computer interaction (HCI) coupled with emerging architectural design methodologies creates new opportunities for achieving optimal system performance and design usability for interactive architectural systems. This paper presents a methodology for developing a mixed reality computational workflow combining 3D depth sensing and virtual reality (VR) to enable iterative user-centered design. Using an interactive museum installation as a case study, user pointcloud data is observed via VR at full scale and in real time for a new design feedback experience. Through this method, the designer is able to virtually position him/herself among the museum installation visitors in order to observe their actual behaviors in context and iteratively make modifications instantaneously. In essence, the designer and user effectively share the same prototypical design space in different realities. Experimental deployment and preliminary results of the shared reality workflow are presented to demonstrate the viability of the method for the museum installation case study and for future interactive architectural design applications. Contributions to computational design, technical challenges, and ethical considerations are discussed for future work.
keywords	design methods; information processing; hci; VR; AR; mixed reality; computer vision
series	ACADIA
email
last changed	2022/06/07 07:52

_id	acadia17_366
id	acadia17_366
authors	Lin, Yuming; Huang, Weixin
year	2017
title	Behavior Analysis and Individual Labeling Using Data from Wi-Fi IPS
doi	https://doi.org/10.52842/conf.acadia.2017.366
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 366- 373
summary	It is fairly important for architects and urban designers to understand how different people interact with the environment. However, traditional investigation methods for studying environmental behavior are quite limited in their coverage of samples and regions, which are not sufficient to delve into the behavioral differences of people. Only recently, the development of indoor positioning systems (IPS) and data-mining techniques has made it possible to collect full-time, full-coverage data for behavioral difference research and individualized identification. In our research, the Wi-Fi IPS system is chosen among the various IPS systems as the data source due to its extensive applicability and acceptable cost. In this paper, we analyzed a 60-day anonymized dataset from a ski resort, collected by a Wi-Fi IPS system with 110 Wi-Fi access points. Combining this with mobile phone data and questionnaires, we revealed some interesting characteristics of tourists from different origins through spatial-temporal behavioral data, and further conducted individual labeling through supervised learning. Through this case study, temporal-spatial behavioral data from an IPS system exhibited great potential in revealing individual characteristics besides exploring group differences, shedding light on the prospect of architectural space personalization.
keywords	design methods; information processing; data mining; big data
series	ACADIA
email
last changed	2022/06/07 07:59

_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	caadria2018_210
id	caadria2018_210
authors	Lin, Yuqiong, Zheng, Jingyun, Yao, Jiawei and Yuan, Philip F.
year	2018
title	Research on Physical Wind Tunnel and Dynamic Model Based Building Morphology Generation Method
doi	https://doi.org/10.52842/conf.caadria.2018.2.165
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. 165-174
summary	The change of the building morphology directly affects the surrounding environment, while the evaluation of these environment data becomes the main basis for the genetic iterations of the building morphology. Indeed, due to the complexity of the outdoor natural ventilation, multiple factors in the site could be the main reasons for the change of air flow. Thus, the architect is suggested to take the wind environment as the main morphology generation factor in the early stage of the building design. Based on the research results of 2017 DigitalFUTURE Wind Tunnel Visualization Workshop, a novel self-form-finding method in design infancy has been proposed. This method uses Arduino to carry out the dynamic design of the building model, which can not only connect the sensor to monitor the wind environment data, but also contribute the building model to correlate with the wind environment data in real time. The integration of the Arduino platform and the physical wind tunnel can create the possibility of continuous and real-time physical changes, data collection and wind environment simulation, using quantitative environmental factors to control building morphology, and finally achieve the harmony among the building, environment and human.
keywords	Physical wind tunnel; dynamic model; building morphology generation; environmental performance design; wind environment visualization
series	CAADRIA
email
last changed	2022/06/07 07:59

_id	ecaade2017_302
id	ecaade2017_302
authors	Saleh Tabari, Mohammad Hassan, Kalantari, Saleh and Ahmadi, Nooshin
year	2017
title	Biofilm-inspired Formation of Artificial Adaptive Structures
doi	https://doi.org/10.52842/conf.ecaade.2017.2.303
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 2, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 303-312
summary	Todays design researchers are beginning to develop a process-based approach to biomimicry. Instead of merely looking at static natural structures for inspiration, we are learning to draw from the underlying organic processes that lead to the creation of those structures. This paradigm shift points us in the direction of adaptive fabrication systems that can grow through processes of self-assembly and can reconfigure themselves to meet the contours of local environments. In this study we examined the structural growth patterns of bacterial biofilms as a basis for a new kind of artificial, self-assembling module. This demonstration of bio-inspired design shows how contemporary technology allows us to harness the lessons of evolution in new and innovative ways. By exploring the dynamic assembly of complex structural formations in nature, we are able to derive new resource-efficient approaches to adaptable designs that are suited to changing environments. Ultimately we aspire to produce fully synthetic analogues that follow similar patterns of self-assembly to those found in bacterial biofilm colonies. Designers have only just begun to explore the tremendous wealth of natural form-creation processes that can now be replicated with computer-aided design and fabrication; this project shows just one example of what the future might hold.
keywords	Biofilm; Adaptive Structure; Formation; Quorum Sensing; Parametric Condition
series	eCAADe
email
last changed	2022/06/07 07:56

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

_id	acadia17_238
id	acadia17_238
authors	El-Zanfaly, Dina
year	2017
title	A Multisensory Computational Model for Human-Machine Making and Learning
doi	https://doi.org/10.52842/conf.acadia.2017.238
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 238-247
summary	Despite the advancement of digital design and fabrication technologies, design practices still follow Alberti’s hylomorphic model of separating the design phase from the construction phase. This separation hinders creativity and flexibility in reacting to surprises that may arise during the construction phase. These surprises often come as a result of a mismatch between the sophistication allowed by the digital technologies and the designer’s experience using them. These technologies and expertise depend on one human sense, vision, ignoring other senses that could be shaped and used in design and learning. Moreover, pedagogical approaches in the design studio have not yet fully integrated digital technologies as design companions; rather, they have been used primarily as tools for representation and materialization. This research introduces a multisensory computational model for human-machine making and learning. The model is based on a recursive process of embodied, situated, multisensory interaction between the learner, the machines and the thing-in-the-making. This approach depends heavily on computational making, abstracting, and describing the making process. To demonstrate its effectiveness, I present a case study from a course I taught at MIT in which students built full-scale, lightweight structures with embedded electronics. This model creates a loop between design and construction that develops students’ sensory experience and spatial reasoning skills while at the same time enabling them to use digital technologies as design companions. The paper shows that making can be used to teach design while enabling the students to make judgments on their own and to improvise.
keywords	education, society & culture; fabrication
series	ACADIA
email
last changed	2022/06/07 07:55

_id	cf2017_533
id	cf2017_533
authors	El-Zanfaly, Dina; Abdelmohsen, Sherif
year	2017
title	Imitation in Action: A Pedagogical Approach for Making Kinetic Structures
source	Gülen Çagdas, Mine Özkar, Leman F. Gül and Ethem Gürer (Eds.) Future Trajectories of Computation in Design [17th International Conference, CAAD Futures 2017, Proceedings / ISBN 978-975-561-482-3] Istanbul, Turkey, July 12-14, 2017, pp. 533-545.
summary	One of the problems in teaching students how to design kinetic architecture is the difficulty of helping them grasp concepts like motion, physical computing and fabrication, concepts not generally dealt with in conventional architectural projects. In this paper, we introduce a pedagogical method for better utilizing prototyping and explore the role prototyping plays in learning and conceptualizing design ideas. Our method is based on building the learner’s sensory experience through iteration and focusing on the process as well as the product. Specifically, our research attempts to address the following questions: How can architecture students anticipate and feel motion while they design kinetic prototypes? How do their prototypes enable them to explore design ideas? As a case study, we applied our methodology in an 8-week workshop in a fabrication laboratory in Cairo, Egypt. The workshop was open to young architects and students who had completed at least four semesters of study at the university. We describe the pedagogical approach we developed to build the sensory experience of making motion, and demonstrate the basic setting and stages of the workshop. We show how a cyclical learning process, based on perception and action -- copying and iteration -- contributed to the students’ learning experience and enabled them to create and improvise on their own.
keywords	Kinetic Architecture, Digital Fabrication, Sensory Experience, Computational Making, Imitation
series	CAAD Futures
email
last changed	2017/12/01 14:38

_id	acadia17_474
id	acadia17_474
authors	Peng, Wenzhe; Zhang, Fan; Nagakura, Takehiko
year	2017
title	Machines’ Perception of Space: Employing 3D Isovist Methods and a Convolutional Neural Network in Architectural Space Classification
doi	https://doi.org/10.52842/conf.acadia.2017.474
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 474- 481
summary	Simple and common architectural elements can be combined to create complex spaces. Different spatial compositions of elements define different spatial boundaries, and each produces a unique local spatial experience to observers inside the space. Therefore an architectural style brings about a distinct spatial experience. While multiple representation methods are practiced in the field of architecture, there lacks a compelling way to capture and identify spatial experiences. Describing an observer’s spatial experiences quantitatively and efficiently is a challenge. In this paper, we propose a method that employs 3D isovist methods and a convolutional neural network (CNN) to achieve recognition of local spatial compositions. The case studies conducted validate that this methodology works well in capturing and identifying local spatial conditions, illustrates the pattern and frequency of their appearance in designs, and indicates peculiar spatial experiences embedded in an architectural style. The case study used small designs by Mies van der Rohe and Aldo van Eyck. The contribution of this paper is threefold. First, it introduces a sampling method based on 3D Isovist that generates a 2D image that can be used to represent a 3D space from a specific observation point. Second, it employs a CNN model to extract features from the sampled images, then classifies their corresponding space. Third, it demonstrates a few case studies where this space classification method is applied to different architectural styles.
keywords	design methods; information processing; AI; machine learning; computer vision; representation
series	ACADIA
email
last changed	2022/06/07 08:00

_id	ecaade2023_259
id	ecaade2023_259
authors	Sonne-Frederiksen, Povl Filip, Larsen, Niels Martin and Buthke, Jan
year	2023
title	Point Cloud Segmentation for Building Reuse - Construction of digital twins in early phase building reuse projects
doi	https://doi.org/10.52842/conf.ecaade.2023.2.327
source	Dokonal, W, Hirschberg, U and Wurzer, G (eds.), Digital Design Reconsidered - Proceedings of the 41st Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2023) - Volume 2, Graz, 20-22 September 2023, pp. 327–336
summary	Point cloud processing has come a long way in the past years. Advances in computer vision (CV) and machine learning (ML) have enabled its automated recognition and processing. However, few of those developments have made it through to the Architecture, Engineering and Construction (AEC) industry. Here, optimizing those workflows can reduce time spent on early-phase projects, which otherwise could be spent on developing innovative design solutions. Simplifying the processing of building point cloud scans makes it more accessible and therefore, usable for design, planning and decision-making. Furthermore, automated processing can also ensure that point clouds are processed consistently and accurately, reducing the potential for human error. This work is part of a larger effort to optimize early-phase design processes to promote the reuse of vacant buildings. It focuses on technical solutions to automate the reconstruction of point clouds into a digital twin as a simplified solid 3D element model. In this paper, various ML approaches, among others KPConv Thomas et al. (2019), ShapeConv Cao et al. (2021) and Mask-RCNN He et al. (2017), are compared in their ability to apply semantic as well as instance segmentation to point clouds. Further it relies on the S3DIS Armeni et al. (2017), NYU v2 Silberman et al. (2012) and Matterport Ramakrishnan et al. (2021) data sets for training. Here, the authors aim to establish a workflow that reduces the effort for users to process their point clouds and obtain object-based models. The findings of this research show that although pure point cloud-based ML models enable a greater degree of flexibility, they incur a high computational cost. We found, that using RGB-D images for classifications and segmentation simplifies the complexity of the ML model but leads to additional requirements for the data set. These can be mitigated in the initial process of capturing the building or by extracting the depth data from the point cloud.
keywords	Point Clouds, Machine Learning, Segmentation, Reuse, Digital Twins
series	eCAADe
email
last changed	2023/12/10 10:49

_id	acadia17_590
id	acadia17_590
authors	Steinfeld, Kyle
year	2017
title	Dreams May Come
doi	https://doi.org/10.52842/conf.acadia.2017.590
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 590- 599
summary	This paper argues that prevailing approaches to CAD software have been fashioned to support modes of reasoning only of secondary importance to design activity, and that, due to some recent developments in computer vision, this state of affairs may be about to change. Surveying the current state of CAD tools, a critical position is developed based upon the best current understanding of the cognitive processes related to design. Following a high-level overview of some of the important developments in computer vision, and a curated set of examples of the applications these developments are finding in practices loosely related to architectural design, we draw out a number of parallels between machine learning (ML) and design thinking. We expect that this will serve as a guide to future research at the intersection of ML and architectural design tools.
keywords	education society & culture; computer vision; education
series	ACADIA
email
last changed	2022/06/07 07:56

_id	ecaade2017_027
id	ecaade2017_027
authors	Carl, Timo, Schein, Markus and Stepper, Frank
year	2017
title	Sun Shades - About Designing Adaptable Solar Facades
doi	https://doi.org/10.52842/conf.ecaade.2017.2.165
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 2, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 165-174
summary	External shading structures are a well-established typology for reducing solar heat loads. A major disadvantage is their inflexible nature, blocking views from inside and desired solar radiation for seasons with less sunshine hours. An adaptive approach on the other end can accommodate dynamic environmental exchange and user control. Furthermore, kinetic movement has great potential to create expressive spatial structures. However, such typologies are inherently complex. This paper presents the design process for two novel adaptive façade typologies, conducted on an experimental level in an educational context. Moreover, we will discuss the conception of a suitable methodological framework, which we applied to engage the complexity of this design task. Thereby we will highlight the importance of employing various methods, combining analogue and computational models not in a linear sequence, but rather in an overlapping, iterative way to create an innovation friendly design setting. The Sun Shades project offers insight into the relationships between design potentials inherent in adaptable structures and the advantages and limitation of computational methods employed to tackle them.
keywords	computational design methodology; performance-based design; associative geometry modelling; solar simulation; physical form-finding; design theory
series	eCAADe
email
last changed	2022/06/07 07:54

_id	ecaade2017_031
id	ecaade2017_031
authors	Castelo Branco, Renata and Leit?o, António
year	2017
title	Integrated Algorithmic Design - A single-script approach for multiple design tasks
doi	https://doi.org/10.52842/conf.ecaade.2017.1.729
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 1, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 729-738
summary	Many great architectural endeavors today engage in a multi software approach, as each specialty involved needs a different software, and different task required from the architect, such as 3D modeling, analysis or rendering, also benefit from the use of different tools. Combining them in the same process is not always a successful endeavor. A more effective portability mechanism is needed, and Algorithmic Design (AD) has the potential to become one. This paper explores the advantages of the algorithmic approach to the design process, and proposes a methodology capable of integrating the different tools and paradigms currently used in architecture. The methodology is based on the development of a computer program that describes not only the intended model, but also additional tasks, such as the required analysis and rendering. It takes advantage of CAD, BIM and analysis tools, with little effort when it comes to the transition between them.
keywords	Algorithmic Design; CAD; BIM; Analysis tools
series	eCAADe
email
last changed	2022/06/07 07:55

_id	ecaade2017_210
id	ecaade2017_210
authors	Jimenez Garcia, Manuel, Soler, Vicente and Retsin, Gilles
year	2017
title	Robotic Spatial Printing
doi	https://doi.org/10.52842/conf.ecaade.2017.2.143
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 2, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 143-150
summary	There has been significant research into large-scale 3D printing processes with industrial robots. These were initially used to extrude in a layered manner. In recent years, research has aimed to make use of six degrees of freedom instead of three. These so called "spatial extrusion" methods are based on a toolhead, mounted on a robot arm, that extrudes a material along a non horizontal spatial vector. This method is more time efficient but up to now has suffered from a number of limiting geometrical and structural constraints. This limited the formal possibilities to highly repetitive truss-like patterns. This paper presents a generalised approach to spatial extrusion based on the notion of discreteness. It explores how discrete computational design methods offer increased control over the organisation of toolpaths, without compromising design intent while maintaining structural integrity. The research argues that, compared to continuous methods, discrete methods are easier to prototype, compute and manufacture. A discrete approach to spatial printing uses a single toolpath fragment as basic unit for computation. This paper will describe a method based on a voxel space. The voxel contains geometrical information, toolpath fragments, that is subsequently assembled into a continuous, kilometers long path. The path can be designed in response to different criteria, such as structural performance, material behaviour or aesthetics. This approach is similar to the design of meta-materials - synthetic composite materials with a programmed performance that is not found in natural materials. Formal differentiation and structural performance is achieved, not through continuous variation, but through the recombination of discrete toolpath fragments. Combining voxel-based modelling with notions of meta-materials and discrete design opens this domain to large-scale 3D printing. Please write your abstract here by clicking this paragraph.
keywords	discrete; architecture; robotic fabrication; large scale printing; software; plastic extrusion
series	eCAADe
email
last changed	2022/06/07 07:52

_id	acadia17_308
id	acadia17_308
authors	Joyce, Sam Conrad; Ibrahim, Nazim
year	2017
title	Exploring the Evolution of Meta Parametric Models
doi	https://doi.org/10.52842/conf.acadia.2017.308
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 308- 317
summary	Parametric associative logic can describe complex design scenarios but are typically non-trivial and time consuming to develop. Optimization is being widely applied in many fields to find high-performing solutions to objective design needs, and this is being extended further to include user input to satisfy subjective preferences. However, whilst conventional optimization approaches can set good parameters for a model, they cannot currently improve the underlying logic defined by the associative topology of the model, leaving it limited to predefined domain of designs. This work looks at the application of Cartesian Genetic Programming (CGP) as a method for allowing the automatic generation, combination and modification of valid parametric models, including topology. This has value as it allows for a much greater range of solutions, and potentially computational "creativity," as it can develop unique and surprising solutions. However, the application of a genome-based definition and evolutionary optimization, respectively, to describe parametric models and develop better models for a problem, introduce many unknowns into the model generation process. This paper explains CGP as applied to parametric design and investigates the difference between using mating, mutating and both strategies together as a way of combining aspects of parent models, under selection by a genetic algorithm under random, objective and user (Interactive GA) preferences. We look into how this effects the resultant overiterated interaction in relation to both the geometry and the parametric model.
keywords	design methods; information processing; generative system; data visualization; computational / artistic cultures
series	ACADIA
email
last changed	2022/06/07 07:52

_id	acadia17_426
id	acadia17_426
authors	Moorman, Andrew
year	2017
title	Pattern Making and Learning: Non-Routine Practices in Generative Design
doi	https://doi.org/10.52842/conf.acadia.2017.426
source	ACADIA 2017: DISCIPLINES & DISRUPTION [Proceedings of the 37th Annual Conference of the Association for Computer Aided Design in Architecture (ACADIA) ISBN 978-0-692-96506-1] Cambridge, MA 2-4 November, 2017), pp. 426- 435
summary	We now witness an upsurge in mainstream generative design tools fortified by simulation that speed up the concealed linear synthesis of optimized design alternatives. In pursuit of optimality, these tools saturate local machines or cloud servers with analysis and design iteration data, only to discard it once the procedure has concluded. Largely absent, however, are tools for an active, adaptive relationship with design exploration and the reuse of corresponding design data and metadata. In Pattern Making and Pattern Learning, we propose that these characteristics are mutually beneficial. This paper presents a series of revisions to the optimization framework for routine design synthesis that examine a potential symbiosis between the production of large datasets (big data) and non-routine practices of making in design. Our engagement with iterative design exercises is twofold: as a supply of computer-generated design information to foster user intuition and explore the design space on non-objective terms, and as a supply of human-generated design information to learn artifacts of user preference in the interest of design software personalization. These concepts are applied to the generation of functionally graded patterning in chair design, combining methods of physical production with programmable sheet material behavior through a custom interactive synthesis framework.
keywords	design methods; information processing; ai & machine learning; simulation & optimization; generative system
series	ACADIA
email
last changed	2022/06/07 07:58

_id	sigradi2017_074
id	sigradi2017_074
authors	Nisenbaum, Marcio; José Ripper Kós
year	2017
title	Paisagens Sonoras Digitais: metodologia de representação dos sons urbanos por meio de motor de jogo. [Digital soundscapes: urban sound representation methodology based on game engine.]
source	SIGraDi 2017 [Proceedings of the 21th Conference of the Iberoamerican Society of Digital Graphics - ISBN: 978-956-227-439-5] Chile, Concepción 22 - 24 November 2017, pp.505-512
summary	This paper discusses about soundscape notation possibilities and structures a methodology for representing urban sounds based on game engine technology. Recently, new forms of sound visualization and auralization techniques have emerged within the research fields of Soundscape and Noise Pollution studies. The development of digital media, such as game engines, introduced new forms of audiovisual 3d representations, combining geometry and sound in a structured interactive computational space. This paper addresses these novel methods of representation and reflects upon their contribution for soundscape studies through an ongoing study case.
keywords	Soundscapes; Simulation; Game engine; Digital medium.
series	SIGRADI
email
last changed	2021/03/28 19:59

_id	sigradi2022_51
id	sigradi2022_51
authors	Varsami, Constantina; Tsamis, Alexandros; Logan, Timothy
year	2022
title	Gaming Engine as a Tool for Designing Smart, Interactive, Light-Sculpting Systems
source	Herrera, PC, Dreifuss-Serrano, C, Gómez, P, Arris-Calderon, LF, Critical Appropriations - Proceedings of the XXVI Conference of the Iberoamerican Society of Digital Graphics (SIGraDi 2022), Universidad Peruana de Ciencias Aplicadas, Lima, 7-11 November 2022 , pp. 617–628
summary	Even though interactive (Offermans et.al., 2013), adaptive (Viani et.al., 2017), and self-optimizable (Sun et.al., 2020) lighting systems are becoming readily available, designing system automations, and evaluating their impact on user experience significantly challenges designers. In this paper we demonstrate the use of a gaming engine as a platform for designing, simulating, and evaluating autonomous smart lighting behaviors. We establish the Human - Lighting System Interaction Framework, a computational framework for developing a Light Sculpting Engine and for designing occupant-system interactions. Our results include a. a method for combining in real-time lighting IES profiles into a single ‘combined’ profile - b. algorithms that optimize in real-time, lighting configurations - c. direct glare elimination algorithms, and d. system energy use optimization algorithms. Overall, the evolution from designing static building components to designing interactive systems necessitates the reconsideration of methods and tools that allow user experience and system performance to be tuned by design.
keywords	User Experience, Human-Building Interaction, Smart Lighting, Lighting Simulation, Gaming Engine
series	SIGraDi
email
last changed	2023/05/16 16:56

_id	caadria2017_057
id	caadria2017_057
authors	Buš, Peter, Treyer, Lukas and Schmitt, Gerhard
year	2017
title	Urban Autopoiesis - Towards Adaptive Future Cities
doi	https://doi.org/10.52842/conf.caadria.2017.695
source	P. Janssen, P. Loh, A. Raonic, M. A. Schnabel (eds.), Protocols, Flows, and Glitches - Proceedings of the 22nd CAADRIA Conference, Xi'an Jiaotong-Liverpool University, Suzhou, China, 5-8 April 2017, pp. 695-704
summary	A city, defined as a unity of inhabitants with their environment and showing self-creating and self-maintaining properties, can be considered as an autopoietic system if we take into account its bottom-up processes with unpredictable behaviour of its components. Such a property can lead to self-creation of urban patterns. These processes are studied in well-known vernacular architectures and informal settlements around the world and they are able to adapt according to various conditions and forces. The main research objective is to establish a computational design-modelling framework for modelling autopoietic intricate characteristics of a city based on an adaptability, self-maintenance and self-generation of urban patterns with adequate visual representation.The paper introduces a modelling methodology that allows to combine planning tasks with inhabitants' interaction and data sources by using an interchange framework to model more complex urban dynamics. The research yields preliminary results tested in a simulation model of a redevelopment of Tanjong Pagar Waterfront, the container terminal in the city of Singapore being transformed into a new future centre as a conducted case study.
keywords	Urban Metabolism; Urban Autopoiesis; Computational Interchange; Emergent Urban Strategies; Adaptive City
series	CAADRIA
email
last changed	2022/06/07 07:54

_id	ecaade2017_140
id	ecaade2017_140
authors	Eversmann, Philipp
year	2017
title	Digital Fabrication in Education - Strategies and Concepts for Large-Scale Projects
doi	https://doi.org/10.52842/conf.ecaade.2017.1.333
source	Fioravanti, A, Cursi, S, Elahmar, S, Gargaro, S, Loffreda, G, Novembri, G, Trento, A (eds.), ShoCK! - Sharing Computational Knowledge! - Proceedings of the 35th eCAADe Conference - Volume 1, Sapienza University of Rome, Rome, Italy, 20-22 September 2017, pp. 333-342
summary	The consequences of automation technology on industry are currently widely discussed in terms of future tasks, work organisation and working environments. Even though various novel education programmes specialise in digital fabrication, relatively little has been written on concepts for a deeper integration of digital technologies in the architectural curriculum. This paper gives an overview of interdisciplinary educational approaches and digital project development techniques and describes a teaching method featuring intensive collaboration with research and industry, an iterative teaching method employing digital production of large-scale prototypes and a moderated self-learning process. We describe two examples of teaching initiatives in particular that were undertaken at TU Munich and ETH Zurich and analyse their results in terms of physical outcomes, teaching accomplishments, resource efficiency and connection to research. We discuss the relationship between necessary teaching intensity, project size and complexity of digital fabrication equipment and conclude by giving an outlook for future initiatives.
keywords	interdisciplinary collaboration; iterative process; self-learning
series	eCAADe
email
last changed	2022/06/07 07:55

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