Cumincad : CUMINCAD Papers : Search Results

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

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

_id	ijac202018407
id	ijac202018407
authors	Marcelo Bernal, Victor Okhoya, Tyrone Marshall, Cheney Chen and John Haymaker
year	2020
title	Integrating expertise and parametric analysis for a data-driven decision-making practice
source	International Journal of Architectural Computing vol. 18 - no. 4, 424–440
summary	This study explores the integration of expert design intuition and parametric data analysis. While traditional professional design expertise helps to rapidly frame relevant aspects of the design problem and produce viable solutions, it has limitations in addressing multi-criteria design problems with conflicting objectives. On the other hand, parametric analysis, in combination with data analysis methods, helps to construct and analyze large design spaces of potential design solutions and tradeoffs, within a given frame. We explore a process whereby expert design teams propose a design using their current intuitive and analytical methods. That design is then further optimized using parametric analysis. This study specifically explores the specification of geometric and material properties of building envelopes for two typically conflicting objectives: daylight quality and energy consumption. We compare performance of the design after initial professional design exploration, and after parametric analysis, showing consistently significant performance improvement after the second process. The study explores synergies between intuitive and systematic design approaches, demonstrating how alignment can help expert teams efficiently and significantly improve project performance.
keywords	Performance analysis, parametric analysis, design space, design expertise, data analysis, optimization
series	journal
email
last changed	2021/06/03 23:29

_id	ecaade2020_015
id	ecaade2020_015
authors	Yazici, Sevil
year	2020
title	A machine-learning model driven by geometry, material and structural performance data in architectural design process
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 1, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 411-418
doi	https://doi.org/10.52842/conf.ecaade.2020.1.411
summary	Artificial Intelligence (AI), based on interpretation of data, influences various professions including architectural design today. Although research on integrating conceptual design with Machine Learning (ML) algorithms as a subset of the AI has been investigated previously, there is not a framework towards integration of architectural geometry with material properties and structural performance data towards decision making in the early-design phase. Undertaking performance simulations require significant amount of computation power and time. The aim of this research is to integrate ML algorithms into design process to achieve time efficiency and improve design results. The proposed workflow consists of three stages, including generation of the parametric model; running structural performance simulations to collect the data, and operating the ML algorithms, including Artificial Neural Network (ANN), Non-Linear Regression (NLR) and Gaussian Mixture (GM) for undertaking different tasks. The results underlined that the system generates relatively fast solutions with accuracy. Additionally, ML algorithms can assist generative design processes.
keywords	Machine-learning; performance simulation; data-driven design; early-design phase
series	eCAADe
email
last changed	2022/06/07 07:57

_id	caadria2020_423
id	caadria2020_423
authors	Erhan, Halil, Zarei, Maryam, Abuzuraiq, Ahmed M., Haas, Alyssa, Alsalman, Osama and Woodbury, Robert
year	2020
title	FlowUI: Combining Directly-Interactive Design Modeling with Design Analytics
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 475-484
doi	https://doi.org/10.52842/conf.caadria.2020.1.475
summary	In a systems building experiment, we explored how directly manipulating non-parametric geometries can be used together with a real-time parametric performance analytics for informed design decision-making in the early phases of design. This combination gives rise to a design process where considerations that would traditionally take place in the late phases of design can become part of the early phases. The paper presents FlowUI, a prototype tool for performance-driven design that is developed in a collaboration with our industry partner as part of our design analytics research program. The tool works with and responds to changes in the design modeling environment, processes the design data and presents the results in design (data) analytics interfaces. We discuss the system's design intent and its overall architecture, followed by a set of suggestions on the comparative analysis of design solutions and design reports generation as integral parts of design exploration tasks.
keywords	Non-Parametric Modeling; Performance-Driven Design; Design Analytics; Information Visualization
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	ecaade2020_479
id	ecaade2020_479
authors	Trento, Armando, Kieferle, Joachim B. and Wössner, Uwe
year	2020
title	A Decision Making Tool for Supporting Strategies of Archaeological Restoration - Case Study of Ostia, Maritime 'Portus' of the Imperial Rome
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 1, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 107-116
doi	https://doi.org/10.52842/conf.ecaade.2020.1.107
summary	Computer aided examination methods for remains of previous human societies support the study of past human behaviour, thus enriching the understanding of our culture. With mostly limited budgets, finding the most effective use for the limited resources for archaeological restoration is highly relevant for many existing sites all over the world. Sites, that need to allow visitors to safely experience archaeological heritage, even within natural landscapes. This paper illustrates an innovative method, technically using Building Information Modelling (BIM) and Virtual Reality (VR), for integrating the domain specific parameters - at all various scales - of the historical asset into one shared digital twin. To provide an effective platform for all project participants to share their knowledge, and to jointly develop the best design decision. The information is collected and displayed within the digital twin of the archaeological site, both for the communication between the specialists, and facilitating practice of the archaeological investigation, further analysis, conservative restoration and reconstruction. The case study aims at implementing this tool into the ongoing Portus project of Imperial Rome.
keywords	Archaeological Restoration; Digital Design Support System; BIM; VR
series	eCAADe
email
last changed	2022/06/07 07:57

_id	acadia21_76
id	acadia21_76
authors	Smith, Rebecca
year	2021
title	Passive Listening and Evidence Collection
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. 76-81.
doi	https://doi.org/10.52842/conf.acadia.2021.076
summary	In this paper, I present the commercial, urban-scale gunshot detection system ShotSpotter in contrast with a range of ecological sensing examples which monitor animal vocalizations. Gunshot detection sensors are used to alert law enforcement that a gunshot has occurred and to collect evidence. They are intertwined with processes of criminalization, in which the individual, rather than the collective, is targeted for punishment. Ecological sensors are used as a “passive” practice of information gathering which seeks to understand the health of a given ecosystem through monitoring population demographics, and to document the collective harms of anthropogenic change (Stowell and Sueur 2020). In both examples, the ability of sensing infrastructures to “join up and speed up” (Gabrys 2019, 1) is increasing with the use of machine learning to identify patterns and objects: a new form of expertise through which the differential agendas of these systems are implemented and made visible. I trace the differential agendas of these systems as they manifest through varied components: the spatial distribution of hardware in the existing urban environment and / or landscape; the software and other informational processes that organize and translate the data; the visualization of acoustical sensing data; the commercial factors surrounding the production of material components; and the apps, platforms, and other forms of media through which information is made available to different stakeholders. I take an interpretive and qualitative approach to the analysis of these systems as cultural artifacts (Winner 1980), to demonstrate how the political and social stakes of the technology are embedded throughout them.
series	ACADIA
type	paper
email
last changed	2023/10/22 12:06

_id	ecaade2020_089
id	ecaade2020_089
authors	Ardic, Sabiha Irem, Kirdar, Gulce and Lima, Angela Barros
year	2020
title	An Exploratory Urban Analysis via Big Data Approach: Eindhoven Case - Measuring popularity based on POIs, accessibility and perceptual quality parameters
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 309-318
doi	https://doi.org/10.52842/conf.ecaade.2020.2.309
summary	The cities are equipped with the data as a result of the individuals' sharings and application usage. This significant amount of data has the potential to reveal relations and support user-centric decision making. The focus of the research is to examine the relational factors of the neighborhoods' popularity by implementing a big data approach to contribute to the problem of urban areas' degradation. This paper presents an exploratory urban analysis for Eindhoven at the neighborhood level by considering variables of popularity: density and diversity of points of interest (POI), accessibility, and perceptual qualities. The multi-sourced data are composed of geotagged photos, the location and types of POIs, travel time data, and survey data. These different datasets are evaluated using BBN (Bayesian Belief Network) to understand the relationships between the parameters. The results showed a positive and relatively high connection between popularity - population change, accessibility by walk - density of POIs, and the feeling of safety - social cohesion. For further studies, this approach can contribute to the decision-making process in urban development, specifically in real estate and tourism development decisions to evaluate the land prices or the hot-spot touristic places.
keywords	big data approach; neighborhood analysis; popularity; point of interest (POI); accessibility; perceptual quality
series	eCAADe
email
last changed	2022/06/07 07:54

_id	sigradi2020_180
id	sigradi2020_180
authors	Cavalcanti, Isabella Eloy; Mendes, Leticia Teixeira
year	2020
title	Form and urban life in Christopher Alexander's work: translation of patterns for parametric code
source	SIGraDi 2020 [Proceedings of the 24th Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Online Conference 18 - 20 November 2020, pp. 180-187
summary	Computational design, specifically parametric modeling, has played important role in reaching complex forms, optimizations and automations of design processes. In addition to using parametric technology as a tool to generate form, this article aims to discuss the potential of parametric design as a connection between theory and design activity, both in practice and in the teaching activity. To illustrate that, this paper will present results of a bigger research that used the work of the architect Christopher Alexander as a basis for the development of decision-making instruments that deal with the complexity between form and urban life.
keywords	Urban design, Parametric modeling, Computational design, Christopher Alexander
series	SIGraDi
email
last changed	2021/07/16 11:48

_id	caadria2020_141
id	caadria2020_141
authors	Dezen-Kempter, Eloisa, Mezencio, Davi Lopes, Miranda, Erica De Matos, De SÃ¡, Danilo Pico and Dias, Ulisses
year	2020
title	Towards a Digital Twin for Heritage Interpretation - from HBIM to AR visualization
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 2, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 183-191
doi	https://doi.org/10.52842/conf.caadria.2020.2.183
summary	Data-driven Building Information Modelling (BIM) technology has brought new tools to efficiently deal with the tension between the real and the virtual environments in the field of Architecture, Engineering, Construction, and Operation (AECO). For historic assets, BIM represents a paradigm shift, enabling better decision-making about preventive maintenance, heritage management, and interpretation. The potential application of the Historic-BIM is creating a digital twin of the asset. This paper deals with the concept of a virtual environment for the consolidation and dissemination of heritage information. Here we show the process of creating interactive virtual environments for the Pampulha Modern Ensemble designed by Oscar Niemeyer in the 1940s, and the workflow to their dissemination in an AR visualization APP. Our results demonstrate the APP feasibility to the Pampulha's building interpretation.
keywords	Augmented Reality (AR); Historic Building Information Modelling (HBIM); Heritage Interpretation; Modern Architecture
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	caadria2020_272
id	caadria2020_272
authors	Erhan, Halil, Abuzuraiq, Ahmed M., Zarei, Maryam, AlSalman, Osama, Woodbury, Robert and Dill, John
year	2020
title	What do Design Data say About Your Model? - A Case Study on Reliability and Validity
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 557-567
doi	https://doi.org/10.52842/conf.caadria.2020.1.557
summary	Parametric modeling systems are widely used in architectural design. Their use for designing complex built environments raises important practical challenges when composed by multiple people with diverse interests and using mostly unverified computational modules. Through a case study, we investigate possible concerns identifiable from a real-world collaborative design setting and how such concerns can be revealed through interactive data visualizations of parametric models. We then present our approach for resolving these concerns using a design analytic workflow for examine their reliability and validity. We summarize the lessons learnt from the case study, such as the importance of an abundance of test cases, reproducible design instances, accessing and interacting with data during all phases of design, and seeking high cohesion and decoupling between design geometry and evaluation components. We suggest a systematic integration of design modeling and analytics for enhancing a reliable design decision-making.
keywords	Model Reliability; Model Validity; Parametric Modeling; Design Analytics; Design Visualization
series	CAADRIA
email
last changed	2022/06/07 07:55

_id	ecaade2020_156
id	ecaade2020_156
authors	Hemmerling, Marco and Maris, Simon
year	2020
title	INTERCOM - A platform for collaborative design processes
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 173-180
doi	https://doi.org/10.52842/conf.ecaade.2020.2.173
summary	The INTERCOM project propounds a cloud-based collaboration platform for digital planning processes in architecture. The concept is based on an openBIM approach and ensures open access for all partners involved. At its core it provides IFC-based and model-related online tools for planning, communication and collaboration. The interaction with the model and the exchange with other project partners takes place in real-time via a model-related chat and BCF exports. In addition, the integration of e-learning modules (e.g. video tutorials, wikis, project documents) encourages problem solving through further education. Especially the integration of communication and collaboration tools is supposed to enhance the decision making throughout the design process and become a key factor for a successful and coordinated BIM process. Primarily INTERCOM has been developed as a prototype for teaching BIM in interdisciplinary teams. Subsequently, the application can also be adopted for professional practice. The paper evaluates previous experiences from BIM cloud teaching and discusses the conception and development of the proposed collaborative platform.
keywords	architecture curriculum; didactics; building information modeling (BIM); collaborative design process; common data environment (CDE)
series	eCAADe
email
last changed	2022/06/07 07:49

_id	caadria2020_119
id	caadria2020_119
authors	Hsiao, Yuan Sung (Kris)
year	2020
title	A Comparison of Design Impact and Creativity in the Early Stage of Complex Building Design Processes
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 345-354
doi	https://doi.org/10.52842/conf.caadria.2020.1.345
summary	This paper applied empirical research, the evidence-based method, on the correlation between creativity and computing tools (parametric and nonparametric tools) for the design ideation stage of complex buildings like hospitals. The computer-based protocol analysis was set at observing two different groups of CAD architects worked in a small design task. Then the statistical tool, SPSS, was applied to explore the relationships of the different activities and the impact of design creativity on the design process. The research discovered that the numbers of idea generation had significant connecting to the parametric design process. Also, the users showed well-organised design decision making and better design cognition performance, such as strategical thought during the ideation stage. On the other hand, the nonparametric design users made fewer design ideas and did not appear clear ideation process in terms of some critical design decision making.
keywords	Algorithmic design; Design creativity; Complex building design; Hospital; Design cognition
series	CAADRIA
email
last changed	2022/06/07 07:51

_id	ecaade2024_4
id	ecaade2024_4
authors	Irodotou, Louiza; Gkatzogiannis, Stefanos; Phocas, Marios C.; Tryfonos, George; Christoforou, Eftychios G.
year	2024
title	Application of a Vertical Effective Crank–Slider Approach in Reconfigurable Buildings through Computer-Aided Algorithmic Modelling
source	Kontovourkis, O, Phocas, MC and Wurzer, G (eds.), Data-Driven Intelligence - Proceedings of the 42nd Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2024), Nicosia, 11-13 September 2024, Volume 1, pp. 421–430
doi	https://doi.org/10.52842/conf.ecaade.2024.1.421
summary	Elementary robotics mechanisms based on the effective crank–slider and four–bar kinematics methods have been applied in the past to develop architectural concepts of reconfigurable structures of planar rigid-bar linkages (Phocas et al., 2020; Phocas et al., 2019). The applications referred to planar structural systems interconnected in parallel to provide reconfigurable buildings with rectangular plan section. In enabling structural reconfigurability attributes within the spatial circular section buildings domain, a vertical setup of the basic crank–slider mechanism is proposed in the current paper. The kinematics mechanism is integrated on a column placed at the middle of an axisymmetric circular shaped spatial linkage structure. The definition of target case shapes of the structure is based on a series of numerical geometric analyses that consider certain architectural and construction criteria (i.e., number of structural members, length, system height, span, erectability etc.), as well as structural objectives (i.e., structural behavior improvement against predominant environmental actions) aiming to meet diverse operational requirements and lightweight construction. Computer-aided algorithmic modelling is used to analyze the system's kinematics, in order to provide a solid foundation and enable rapid adaptation for mechanisms that exhibit controlled reconfigurations. The analysis demonstrates the implementation of digital parametric design tools for the investigation of the kinematics of the system at a preliminary design stage, in avoiding thus time-demanding numerical analysis processes. The design process may further provide enhanced interdisciplinary performance-based design outcomes.
keywords	Reconfigurable Structures, Spatial Linkage Structures, Kinematics, Parametric Associative Design
series	eCAADe
email
last changed	2024/11/17 22:05

_id	ecaade2020_497
id	ecaade2020_497
authors	Kim, Eunsu, Rosenwasser, David and Garcia del Castillo Lopez, Jose Luis
year	2020
title	Urban Emotion - The interrogation of social media and its implications within urban context
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 475-482
doi	https://doi.org/10.52842/conf.ecaade.2020.2.475
summary	This paper presents social media as an analytical tool, helping to transform public policy-making, alongside urban needs by dissecting and evaluating human perception. Using emotion analysis on data gathered from a social media platform, experiments are developed to bring new value to architectural and civic narratives. Emotions from texts collected within social media platforms are extracted and mapped alongside tagged locations to gain a greater understanding of how public spaces are utilized. This project develops a new analytical layer within our built environment, working alongside the urban fabric, mechanical systems, and digital infrastructure. It is offered as an interactive tool for policymakers and designers to glean feedback, creating an informed conversation between citizens and decision-makers. Whereas social media platforms such as Twitter and Yelp have been referenced in past academic contexts, this project moves further by producing quantified emotions, painting a differentiated result from what purely semantic data could deliver.
keywords	Social Media; Mapping; Natural Language Processing
series	eCAADe
email
last changed	2022/06/07 07:52

_id	caadria2020_023
id	caadria2020_023
authors	Liu, Chenjun
year	2020
title	Double Loops Parametric Design of Surface Steel Structure Based on Performance and Fabrication
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 1, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 23-33
doi	https://doi.org/10.52842/conf.caadria.2020.1.023
summary	In intelligent epoch, automatic parameter design systems reduce the requirements of the skills needed to create objects. The creator only needs to select the most perceptual primitive form to automatically generate the data system that iterates to the most efficient solution. In this paper, a method of combining performance driven optimization with parametric design is proposed. The iterative evolution is under the control of performance loop and fabrication loop, which makes all the data provided by parametric design in a practical project available for exploring structural analysis and digital prefabrication. Related to the case of surface steel structure, parametric optimization is not limited to a set of shape types or design problems, it would be based on the generality and built-in characteristics of parametric modelling environment in the most convenient and flexible way. (Rolvink et al. 2010)And the given parameters would be fed back on geometric structure, performance indicators, and design variables, so that designers can easily and effectively coordinate and try different solutions. The system transforms the generated data into machine language so that the process including design, analysis, manufacturing, and construction can maintain the orthogonal persistence of the data.
keywords	parametric design; component prefabrication; curved steel structure; performance driven
series	CAADRIA
email
last changed	2022/06/07 07:59

_id	caadria2020_054
id	caadria2020_054
authors	Shen, Jiaqi, Liu, Chuan, Ren, Yue and Zheng, Hao
year	2020
title	Machine Learning Assisted Urban Filling
source	D. Holzer, W. Nakapan, A. Globa, I. Koh (eds.), RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference - Volume 2, Chulalongkorn University, Bangkok, Thailand, 5-6 August 2020, pp. 679-688
doi	https://doi.org/10.52842/conf.caadria.2020.2.679
summary	When drawing urban scale plans, designers should always define the position and the shape of each building. This process usually costs much time in the early design stage when the condition of a city has not been finally determined. Thus the designers spend a lot of time working forward and backward drawing sketches for different characteristics of cities. Meanwhile, machine learning, as a decision-making tool, has been widely used in many fields. Generative Adversarial Network (GAN) is a model frame in machine learning, specially designed to learn and generate image data. Therefore, this research aims to apply GAN in creating urban design plans, helping designers automatically generate the predicted details of buildings configuration with a given condition of cities. Through the machine learning of image pairs, the result shows the relationship between the site conditions (roads, green lands, and rivers) and the configuration of buildings. This automatic design tool can help release the heavy load of urban designers in the early design stage, quickly providing a preview of design solutions for urban design tasks. The analysis of different machine learning models trained by the data from different cities inspires urban designers with design strategies and features in distinct conditions.
keywords	Artificial Intelligence; Urban Design; Generative Adversarial Networks; Machine Learning
series	CAADRIA
email
last changed	2022/06/07 07:56

_id	ecaade2020_498
id	ecaade2020_498
authors	Sousa, Megg and Paio, Alexandra
year	2020
title	Pattern-driven Design for Small Public Spaces - An analysis of pattern books and toolboxes
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 2, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 491-498
doi	https://doi.org/10.52842/conf.ecaade.2020.2.491
summary	Urban spatial patterns that can enhance the city's cultural, social, environmental, material and structural performance advance beyond the old notions of design patterns by incorporating the digital design. Pattern books such as "A Pattern Language" are revisited and toolboxes /toolkits are used in contemporary urban designs by laboratories and offices. The aim of this paper is to analyze the particularities and congruencies between some systems of patterns, pattern books, toolboxes and toolkits aimed at small public spaces, also considering the context of digital culture. The methodology proposed is the construction of a taxonomy that relates and classifies these selected patterns, by these following steps: a) selecting of patterns applicable to small public spaces; b) classification of patterns by "type" (location, behavior, processes and design components) and by "driven designs" approach (data-driven design, performance-driven design, and material- driven design) and relation to the recurrences of patterns between the systems; c) making and inserting in the taxonomy platform a table of elements and connections; d) filtering by classes for analysis. From the results obtained in the visualizations, it is possible to consider a larger volume of "location" type patterns and a smaller volume in "processes" indicating a field that can be developed.
keywords	Urban patterns; urban toolbox; small public spaces; data-driven design; pattern language
series	eCAADe
email
last changed	2022/06/07 07:56

_id	ecaade2020_284
id	ecaade2020_284
authors	Tan, Rachel, Patt, Trevor, Koh, Seow Jin and Chen, Edmund
year	2020
title	Exploration & Validation - Making sense of generated data in large option sets
source	Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 1, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 653-662
doi	https://doi.org/10.52842/conf.ecaade.2020.1.653
summary	The project is a real-world case study where we advised our client in the selection of a viable and well-performing design from a set of computationally generated options. This process was undertaken while validating the algorithmic generative process and user-defined evaluation criteria through scrutinizing the other alternative options to ensure ample variability was considered. Optimisation algorithms were not ideal as low performing options were not visible to validate variability. We established variability by extracting the different groups of options, proving to the client that various operational behaviours were present and accounted for. In order to sieve through the noise and derive meaningful results, we employed methods to filter through thousands of options, including: k-means clustering, archetypal labelling and analysis, pareto front analysis and visualisation overlays. We present a sense-making and decision-making process that utilizes principles of genetic algorithms and analysis of multi-dimensional user-derived evaluation scores. To enable the client's confidence in the computational model, we proved the effectiveness of the generative model through communicating and visualizing the impact of different criterias. This ensured that operational needs were considered. The visualization methods we employed, including pareto front extraction and analysis eventually helped our clients to arrive at a decision.
keywords	generative design; validation; multi-objective optimisation; k-means; pareto front; decision-making
series	eCAADe
email
last changed	2022/06/07 07:56

_id	ecaade2024_409
id	ecaade2024_409
authors	Zarzycki, Andrzej
year	2024
title	BIM-Driven Curriculum for Integrated Design Studios: Maintaining data interoperability and design flexibility
source	Kontovourkis, O, Phocas, MC and Wurzer, G (eds.), Data-Driven Intelligence - Proceedings of the 42nd Conference on Education and Research in Computer Aided Architectural Design in Europe (eCAADe 2024), Nicosia, 11-13 September 2024, Volume 2, pp. 27–36
doi	https://doi.org/10.52842/conf.ecaade.2024.2.027
summary	This paper presents a curricular model for an integrated design studio focused on BIM-driven processes, satisfying the NAAB 2020's student performance criteria SC.5 and SC6. These criteria emphasize quantifiable, evidence-based design thinking by requiring the provision of "measurable environmental impacts" and "measurable outcomes of building performance." The studio, serving as a capstone project, integrates accessible design, user and regulatory requirements into building assemblies, structural and environmental systems, and life safety, underscoring the importance of measurable building performance outcomes. The adoption of computational design tools, particularly Building Information Modeling (BIM), facilitates engagement in environmental and user-focused simulations and ensures data interoperability throughout the design and post-occupancy phases. Utilizing a comprehensive set of tools, including life-cycle assessment (LCA) and energy modeling, the curriculum advances beyond simple simulations to support decision-making and multi-objective optimizations. This approach enables a new form of design thinking that incorporates a broader set of variables and considerations, encouraging students to meet various environmental impact and performance benchmarks, including LEED v.5 Certification points and Architecture 2030 energy standards. The integration of scenario simulation tools empowers students to autonomously advance their projects within a framework of constraints, marking a pedagogical shift towards faculty acting as learning facilitators and promoting student autonomy in design evaluation.
keywords	building information modeling, BIM, building performance simulations, design education
series	eCAADe
email
last changed	2024/11/17 22:05

_id	sigradi2020_120
id	sigradi2020_120
authors	Álvarez, Natalia; Bernal, Marcelo; Cáceres, Katherine
year	2020
title	Evolution and Projection of Computational Design Theories: Generation, Analysis, Selection and Fabrication
source	SIGraDi 2020 [Proceedings of the 24th Conference of the Iberoamerican Society of Digital Graphics - ISSN: 2318-6968] Online Conference 18 - 20 November 2020, pp. 120-127
summary	We can identify a milestone in computational design theories in the intersection between paradigms derived from theories of complexity and technological developments in the early 90’s. These theories provided the l foundation to build interpretation of the potential of the technology by adopting a language based on complexity to frame processes of generation, analysis, selection and manufacturing. To better understand the roots and direction of computational design theories, this study makes an in-depth literature review of four vectors involved in the formation of current dominant theoretical and technical approaches: theories of complexity, technological developments, professional practice and academia. The information collected is organized in chronological order in parallel timelines to facilitate readings exposing the intersections and synergies. The results show the emergence of theoretical approaches based on the convergence of theories and technologies, proof of concept in professional practice and consolidation in academia.
keywords	Generative Design, Performance Analysis, Data Analysis, Decision Making & Fabrication
series	SIGraDi
email
last changed	2021/07/16 11:48

_id	ijac202321102
id	ijac202321102
authors	Özerol, Gizem; Semra Arslan Selçuk
year	2023
title	Machine learning in the discipline of architecture: A review on the research trends between 2014 and 2020
source	International Journal of Architectural Computing 2023, Vol. 21 - no. 1, pp. 23–41
summary	Abstract Through the recent technological developments within the fourth industrial revolution, artificial intelligence (AI) studies have had a huge impact on various disciplines such as social sciences, information communication technologies (ICTs), architecture, engineering, and construction (AEC). Regarding decision-making and forecasting systems in particular, AI and machine learning (ML) technologies have provided an opportunity to improve the mutual relationships between machines and humans. When the connection between ML and architecture is considered, it is possible to claim that there is no parallel acceleration as in other disciplines. In this study, and considering the latest breakthroughs, we focus on revealing what ML and architecture have in common. Our focal point is to reveal common points by classifying and analyzing current literature through describing the potential of ML in architecture. Studies conducted using ML techniques and subsets of AI technologies were used in this paper, and the resulting data were interpreted using the bibliometric analysis method. In order to discuss the state-of-the-art research articles which have been published between 2014 and 2020, main subjects, subsets, and keywords were refined through the search engines. The statistical figures were demonstrated as huge datasets, and the results were clearly delineated through Sankey diagrams. Thanks to bibliometric analyses of the current literature of WOS (Web of Science), CUMINCAD (Cumulative Index about publications in Computer Aided Architectural Design supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD, and CAAD futures), predictable data have been presented allowing recommendations for possible future studies for researchers.
keywords	Artificial intelligence, machine learning, deep learning, architectural research, bibliometric analysis
series	journal
last changed	2024/04/17 14:30

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