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 775

_id caadria2023_403
id caadria2023_403
authors Kim, Jong Bum, Kim, Seongchan and Aman, Jayedi
year 2023
title An Urban Building Energy Simulation Method Integrating Parametric BIM and Machine Learning
source Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 665–674
doi https://doi.org/10.52842/conf.caadria.2023.1.665
summary This research investigates a method of urban building energy simulation (UBES) by integrating Building Information Modeling (BIM), building simulation, and algorithm-based prediction to forecast the impact of surrounding conditions. In the urban context, building energy performances are determined not only by the individual building design but also by the building's surrounding context. Many energy performances are sensitive to outdoor and surrounding building conditions, such as neighbouring building volumes, heights, and spaces between buildings. However, such surrounding conditions were overlooked because they can exponentially increase the complexity of urban modeling and simulation. In that regard, the research sought to investigate a novel framework to take advantage of accurate performance simulations and algorithm-based fast predictions. This paper presents our UBES method implemented from three research phases: (i) building a parametric urban model in BIM to provide simulation inputs, (ii) creating a parametric simulation interface to produce training and validation data, and (iii) creating a prediction interface using a Support Vector Machine (SVR) algorithm. Lastly, the paper elaborates on the findings from the prediction results.
keywords Urban Energy Simulation, Solar Accessibility, Surrounding Conditions, Parametric BIM, Machine Learning, Support Vector Machine, Sustainable Cities and Communities
series CAADRIA
email
last changed 2023/06/15 23:14

_id caadria2023_38
id caadria2023_38
authors Xu, Qingru Mirah, Garcia del Castillo Lopez, Jose Luis and Samuelson, Holly Wasilowski
year 2023
title Towards a Decision Framework Integrating Physics-Based Simulation and Machine Learning in Conceptual Design
source Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 371–380
doi https://doi.org/10.52842/conf.caadria.2023.2.371
summary Researchers have leveraged machine learning technologies and physics-based modelling and simulation techniques to generate fast predictions of factors relevant to building daylighting, energy use, and other performance metrics. However, in the current literature, there is no generalized method outlining the thought process behind whether to implement physics-based simulation, machine learning, or both methods. This paper first proposes a conceptual framework that identifies the considerations researchers might ask when developing their workflow. Second, it presents an example case study developed according to the framework. The case study used daylight simulation and parametric modelling software to generate synthetic data automatically to train a conditional generative adversarial framework. The model was hosted on an interactive web app allowing users to create their building designs and provide design performance metrics and improved design simultaneously.
keywords Physic-based Modelling and Simulation, Physics-based Machine Learning, Early Design, Architecture, Research Development
series CAADRIA
email
last changed 2023/06/15 23:14

_id ecaade2023_000
id ecaade2023_000
authors Dokonal, Wolfgang, Hirschberg, Urs and Wurzer, Gabriel
year 2023
title eCAADe 2023 Digital Design Reconsidered - Volume 1
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 1, Graz, 20-22 September 2023, 905 p.
doi https://doi.org/10.52842/conf.ecaade.2023.1.001
summary The conference logo is a bird’s eye view of spiral stairs that join and separate – an homage to the famous double spiral staircase in Graz, a tourist attraction of this city and a must-see for any architecturally minded visitor. Carved out of limestone, the medieval construction of the original is a daring feat of masonry as well as a symbolic gesture. The design speaks of separation and reconciliation: The paths of two people that climb the double spiral stairs separate and then meet again at each platform. The relationship between architectural design and the growing digital repertoire of tools and possibilities seems to undergo similar cycles of attraction and rejection: enthusiasm about digital innovations – whether in Virtual Reality, Augmented Reality, Energy Design, Robotic Fabrication, the many Dimensions of BIM or, as right now, in AI and Machine Learning – is typically followed by a certain disillusionment and a realization that the promises were somewhat overblown. But a turn away from these digital innovations can only be temporary. In our call for papers we refer to the first and second ‘digital turns’, a term Mario Carpo coined. Yes, it’s a bit of a pun, but you could indeed see these digital turns in our logo as well. Carpo would probably agree that design and the digital have become inseparably intertwined. While they may be circling in different directions, an innovative rejoinder is always just around the corner. The theme of the conference asked participants to re-consider the relationship between Design and the Digital. The notion of a cycle is already present in the syllable “re”. Indeed, 20 years earlier, in 2003, we held an ECAADE conference in Graz simply under the title “Digital Design” and our re-using – or is it re-cycling? – the theme can be seen as the completion of one of those cycles described above: One level up, we meet again, we’ve come full circle. The question of the relationship between Design and the Digital is still in flux, still worthy of renewed consideration. There is a historical notion implicit in the theme. To reconsider something, one needs to take a step back, to look into the past as well as into the future. Indeed, at this conference we wanted to take a longer view, something not done often enough in the fast-paced world of digital technology. Carefully considering one’s past can be a source of inspiration. In fact, the double spiral stair that inspired our conference logo also inspired many architects through the ages. Konrad Wachsmann, for example, is said to have come up with his famous Grapevine assembly system based on this double spiral stair and its intricate joinery. More recently, Rem Koolhaas deemed the double spiral staircase in Graz important enough to include a detailed model of it in his “elements of architecture” exhibition at the Venice Biennale in 2014. Our interpretation of the stair is a typically digital one, you might say. First of all: it’s a rendering of a virtual model; it only exists inside a computer. Secondly, this virtual model isn’t true to the original. Instead, it does what the digital has made so easy to do: it exaggerates. Where the original has just two spiral stairs that separate and join, our model consists of countless stairs that are joined in this way. We see only a part of the model, but the stairs appear to continue in all directions. The implication is of an endless field of spiral stairs. As the 3D model was generated with a parametric script, it would be very easy to change all parameters of it – including the number of stairs that make it up. Everyone at this conference is familiar with the concept of parametric design: it makes generating models of seemingly endless amounts of connected spiral stairs really easy. Although, of course, if we’re too literal about the term ‘endless’, generating our stair model will eventually crash even the most advanced computers. We know that, too. – That's another truth about the Digital: it makes a promise of infinity, which, in the end, it can’t keep. And even if it could: what’s the point of just adding more of the same: more variations, more options, more possible ways to get lost? Doesn’t the original double spiral staircase contain all those derivatives already? Don’t we know that ‘more’ isn’t necessarily better? In the original double spiral stair the happy end is guaranteed: the lovers’ paths meet at the top as well as when they exit the building. Therefore, the stair is also colloquially known as the Busserlstiege (the kissing stair) or the Versöhnungsstiege (reconciliation stair). In our digitally enhanced version, this outcome is no longer clear: we can choose between multiple directions at each level and we risk losing sight of the one we were with. This is also emblematic of our field of research. eCAADe was founded to promote “good practice and sharing information in relation to the use of computers in research and education in architecture and related professions” (see ecaade.org). That may have seemed a straightforward proposition forty years ago, when the association was founded. A look at the breadth and depth of research topics presented and discussed at this conference (and as a consequence in this book, for which you’re reading the editorial) shows how the field has developed over these forty years. There are sessions on Digital Design Education, on Digital Fabrication, on Virtual Reality, on Virtual Heritage, on Generative Design and Machine Learning, on Digital Cities, on Simulation and Digital Twins, on BIM, on Sustainability, on Circular Design, on Design Theory and on Digital Design Experimentations. We hope you will find what you’re looking for in this book and at the conference – and maybe even more than that: surprising turns and happy encounters between Design and the Digital.
series eCAADe
email
last changed 2023/12/10 10:49

_id ecaade2023_001
id ecaade2023_001
authors Dokonal, Wolfgang, Hirschberg, Urs and Wurzer, Gabriel
year 2023
title eCAADe 2023 Digital Design Reconsidered - Volume 2
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, 899 p.
doi https://doi.org/10.52842/conf.ecaade.2023.2.001
summary The conference logo is a bird’s eye view of spiral stairs that join and separate – an homage to the famous double spiral staircase in Graz, a tourist attraction of this city and a must-see for any architecturally minded visitor. Carved out of limestone, the medieval construction of the original is a daring feat of masonry as well as a symbolic gesture. The design speaks of separation and reconciliation: The paths of two people that climb the double spiral stairs separate and then meet again at each platform. The relationship between architectural design and the growing digital repertoire of tools and possibilities seems to undergo similar cycles of attraction and rejection: enthusiasm about digital innovations – whether in Virtual Reality, Augmented Reality, Energy Design, Robotic Fabrication, the many Dimensions of BIM or, as right now, in AI and Machine Learning – is typically followed by a certain disillusionment and a realization that the promises were somewhat overblown. But a turn away from these digital innovations can only be temporary. In our call for papers we refer to the first and second ‘digital turns’, a term Mario Carpo coined. Yes, it’s a bit of a pun, but you could indeed see these digital turns in our logo as well. Carpo would probably agree that design and the digital have become inseparably intertwined. While they may be circling in different directions, an innovative rejoinder is always just around the corner. The theme of the conference asked participants to re-consider the relationship between Design and the Digital. The notion of a cycle is already present in the syllable “re”. Indeed, 20 years earlier, in 2003, we held an ECAADE conference in Graz simply under the title “Digital Design” and our re-using – or is it re-cycling? – the theme can be seen as the completion of one of those cycles described above: One level up, we meet again, we’ve come full circle. The question of the relationship between Design and the Digital is still in flux, still worthy of renewed consideration. There is a historical notion implicit in the theme. To reconsider something, one needs to take a step back, to look into the past as well as into the future. Indeed, at this conference we wanted to take a longer view, something not done often enough in the fast-paced world of digital technology. Carefully considering one’s past can be a source of inspiration. In fact, the double spiral stair that inspired our conference logo also inspired many architects through the ages. Konrad Wachsmann, for example, is said to have come up with his famous Grapevine assembly system based on this double spiral stair and its intricate joinery. More recently, Rem Koolhaas deemed the double spiral staircase in Graz important enough to include a detailed model of it in his “elements of architecture” exhibition at the Venice Biennale in 2014. Our interpretation of the stair is a typically digital one, you might say. First of all: it’s a rendering of a virtual model; it only exists inside a computer. Secondly, this virtual model isn’t true to the original. Instead, it does what the digital has made so easy to do: it exaggerates. Where the original has just two spiral stairs that separate and join, our model consists of countless stairs that are joined in this way. We see only a part of the model, but the stairs appear to continue in all directions. The implication is of an endless field of spiral stairs. As the 3D model was generated with a parametric script, it would be very easy to change all parameters of it – including the number of stairs that make it up. Everyone at this conference is familiar with the concept of parametric design: it makes generating models of seemingly endless amounts of connected spiral stairs really easy. Although, of course, if we’re too literal about the term ‘endless’, generating our stair model will eventually crash even the most advanced computers. We know that, too. – That's another truth about the Digital: it makes a promise of infinity, which, in the end, it can’t keep. And even if it could: what’s the point of just adding more of the same: more variations, more options, more possible ways to get lost? Doesn’t the original double spiral staircase contain all those derivatives already? Don’t we know that ‘more’ isn’t necessarily better? In the original double spiral stair the happy end is guaranteed: the lovers’ paths meet at the top as well as when they exit the building. Therefore, the stair is also colloquially known as the Busserlstiege (the kissing stair) or the Versöhnungsstiege (reconciliation stair). In our digitally enhanced version, this outcome is no longer clear: we can choose between multiple directions at each level and we risk losing sight of the one we were with. This is also emblematic of our field of research. eCAADe was founded to promote “good practice and sharing information in relation to the use of computers in research and education in architecture and related professions” (see ecaade.org). That may have seemed a straightforward proposition forty years ago, when the association was founded. A look at the breadth and depth of research topics presented and discussed at this conference (and as a consequence in this book, for which you’re reading the editorial) shows how the field has developed over these forty years. There are sessions on Digital Design Education, on Digital Fabrication, on Virtual Reality, on Virtual Heritage, on Generative Design and Machine Learning, on Digital Cities, on Simulation and Digital Twins, on BIM, on Sustainability, on Circular Design, on Design Theory and on Digital Design Experimentations. We hope you will find what you’re looking for in this book and at the conference – and maybe even more than that: surprising turns and happy encounters between Design and the Digital.
series eCAADe
type normal paper
email
last changed 2024/08/29 08:36

_id ecaade2023_31
id ecaade2023_31
authors Canli, Ilkim, Gursel Dino, Ipek and Kalkan, Sinan
year 2023
title Useful Daylight Illuminance Prediction Under Data Imbalance in an Urban Context
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. 599–608
doi https://doi.org/10.52842/conf.ecaade.2023.2.599
summary Optimal daylight illumination can aid sustainable design by improving occupants’ psychological and physical health, visual and thermal comfort and decreasing electrical lighting energy usage in buildings. However, dense urban areas can result in restricted daylight access in buildings. Therefore, daylight analysis considering surrounding buildings is important for implementing daylighting strategies. Useful Daylight Illuminance (UDI) is a performance metric that can quantify the annual illuminance levels within certain illumination classes (UDIfell-short, UDIsupplementary, UDIautonomous, and UDIexceeded). UDI can be predicted using machine-learning (ML) methods. However, the calculated data is typically unevenly distributed, generally following a power-law distribution, which causes ML models to underperform for UDI classes with less data. Simulations can be utilized to increase the less dispersed data in the dataset; however, at the urban scale, the computational cost of collecting simulation data for daylighting analysis makes it difficult to augment data with simulations. To undertake this challenge, in this study, SMOTE (Synthetic Minority Oversampling Technique) was applied to augment data to increase the prediction performance of the ML model. The results showed that augmenting the data in the classes which are unevenly distributed leads to an increase in ML model prediction performance. This method shows that SMOTE can be used to increase the performance of ML models during UDI estimation at the urban scale.
keywords Daylight Illumination, Machine Learning Prediction, Useful Daylight Illuminance, Data Imbalance
series eCAADe
email
last changed 2023/12/10 10:49

_id caadria2023_300
id caadria2023_300
authors Okhoya, Victor and Bernal, Marcelo
year 2023
title Variability in Machine Learning for Multi-Criteria Performance Analysis
source Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 149–158
doi https://doi.org/10.52842/conf.caadria.2023.1.149
summary Parametric analysis is emerging as an important approach to building performance evaluation in architectural practice. Since architectural performance has many competing metrics multi-criteria analysis is required to deal effectively with the complexity. However, multi-criteria parametric analysis involves large design spaces that are expensive to compute. Machine learning is emerging as an important design space reduction method for multi-criteria analysis. However, there are many types of machine learning algorithms and architects can benefit from understanding which algorithms perform well on which tasks. Using a mid-rise commercial residential tower project this paper investigates three common machine learning algorithms for performance against three common performance metrics. The algorithms are multi-layer perceptrons, support vector machines, and random forests, while the metrics are site energy, illuminance, and a value function that combines them both. In addition, we seek to understand what factors are most impactful in improving algorithm performance. We investigate four impact factors namely sample size, sensitivity analysis, feature selection, and hyperparameters. We find that multi-layer perceptrons perform best for all three performance metrics. We also find that hyperparameter tuning is the most impactful factor affecting multi-layer perceptron performance.
keywords parametric analysis, machine learning, design space
series CAADRIA
email
last changed 2023/06/15 23:14

_id acadia23_v2_44
id acadia23_v2_44
authors Pei, Wanyu; Stouffs, Rudi
year 2023
title Parametric Archetype: A Synthetic Digital Method of Buildings Material Stock Representation Based on Distance Measurement
source ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 2: Proceedings of the 43rd Annual Conference for the Association for Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9860805-9-8]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 44-52.
summary Building material stock (BMS) is a crucial inventory of secondary resources which contain comprehensive information for analyzing the potential of material reuse and urban harvesting. Due to the complexity of urban building systems and the large number of buildings, obtaining building information one by one is impractical. Existing methods for stock representation mainly start from data collection, and utilize techniques such as clustering, machine learning, computer vision, et cetera, to process and analyze large and complete datasets. However, it is noticed that data on urban buildings, especially for building materials, is very limited or rather inaccessible. Existing methods cannot be applied in data-scarce cities and are also challenging to update over time. Therefore, this study proposes a synthetic approach named parametric archetype for the digital repre- sentation of BMS. This approach combines distance measurement, which is a distance within dimensions describing building features, to match instance buildings dynamically to a parametric archetype with the highest similarity. The weight and types of different building features, which may influence building material (composition and properties) in distance measurement, can be determined by supervised, semi-supervised, or unsuper- vised learning, whether relying on ample available data or domain rules/expert knowledge when data is scarce. This way, the parametric archetype model can use data more effi- ciently to form a synthetic and extensible representation for urban-level BMS (Figure 1). The parametric archetype is anticipated to offer an approach for describing, quantifying, and modeling the real building material stock system incrementally and transparently.
series ACADIA
type paper
email
last changed 2024/04/17 13:58

_id caadria2023_282
id caadria2023_282
authors Qin, Bowen and Zheng, Hao
year 2023
title An Image-Based Machine Learning Method for Urban Features Prediction With Three-Dimensional Building Information
source Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 109–118
doi https://doi.org/10.52842/conf.caadria.2023.1.109
summary Machine learning has been proven to be a very efficient tool in urban analysis, using models trained with big data. We have seen research that applies a generative adversarial network (GAN) to train models, feeding the street map and visualized urban characteristics to predict certain urban features. However, in most cases, the input map is a two-dimensional (2D) map that only stores the land type data (e.g., building, street, green space), hence reducing building information to only the ground-floor area. The identities of buildings with similar floor areas can be hugely different, which may contribute to the prediction errors in previous machine-learning models. In this research, we emphasize the importance of the use of an image-based neural network to analyze the relationship between urban features and the constructed environment. We compare the model that uses traditional street color maps as the input set, against a new input set with more detailed building data. Once trained, the model with the enhanced input set yields output at a higher level of accuracy in certain areas. We apply the new model framework to three selected urban features predictions: rental price, building energy cost, and food sanitary ratio. A broad range of new research could be conduct with our new framework.
keywords Artificial Intelligence, Generative adversarial network, Urban features, Building elevation, Open-source data, Prediction
series CAADRIA
email
last changed 2023/06/15 23:14

_id ijac202321308
id ijac202321308
authors Xu, Hang; Tsung-Hsien Wang
year 2023
title A generative computational workflow to develop actionable renovation strategies for renewable built environments: A case study of Sheffield
source International Journal of Architectural Computing 2023, Vol. 21 - no. 3, 516–535
summary Urban building energy modelling (UBEM) is a prevalent research method to examine the multi-scale building to urban renovation in mitigating global energy-related carbon emissions. However, only a few studies delineate a complete workflow from generation to application using UBEM. In particular, to facilitate the designing of sustainable built environments, existing research needs to emphasize the integration of multiscale energy performance evaluation within the design development process for architects and urban planners. The key challenges lie in the need for integrated datasets and incompatibility between software tools required for designing, modelling, and evaluation. This paper presents a comprehensive methodological framework to investigate applicable urban decarbonization strategies. A case study of Sheffield in the UK demonstrates the development of an automated and standardized computational workflow. This data-driven workflow aims to evaluate energy demand and supply scenarios at an urban scale to access the potential of decarbonizing built environments. The workflow is designed to be adaptable to various scales of urban regions, given a suitable geographic information system (GIS) dataset.
keywords Parametric design, urban sustainability, urban building energy modelling, building performance simulation, decarbonization
series journal
last changed 2024/04/17 14:30

_id ecaade2023_51
id ecaade2023_51
authors Aman, Jayedi, Kim, Jong Bum and Verniz, Debora
year 2023
title AI-Integrated Urban Building Energy Simulation: A framework to forecast the morphological impact on daylight availability
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. 369–378
doi https://doi.org/10.52842/conf.ecaade.2023.2.369
summary The research presents a computational framework to investigate the relationship between urban morphology and environmental performance metrics of buildings. Understanding how buildings interact with their surroundings is crucial in optimizing environmental performance. Current urban building energy simulation methods (UBES) often overlook the complex interaction between urban morphology and environmental performance across a diverse set of attributes, resulting in inaccuracies. The proposed framework integrates machine learning (ML) with physics-based simulations and includes Parametric Building Information Modeling, iterative physics-based simulations, Multi-Objective Optimization, and a graph neural network. The framework leverages the detailed analysis capabilities of physics-based simulations and the data processing strengths of ML to analyze urban morphological attributes. Evaluations indicate that the framework enhances prediction accuracy while considering the influence of urban morphology on environmental performance.
keywords Urban Morphology, Urban Building Energy Modeling, Graph Neural Networks, Sustainable Urban Development, Environmental Performance, Multi-objective Optimization
series eCAADe
email
last changed 2023/12/10 10:49

_id ascaad2023_065
id ascaad2023_065
authors Akbiyik, Selen; Güler, ªeyma; Selçuk, Semra
year 2023
title A Critical Review on Research Themes and Trends in Green BIM for AEC Sector
source C+++: Computation, Culture, and Context – Proceedings of the 11th International Conference of the Arab Society for Computation in Architecture, Art and Design (ASCAAD), University of Petra, Amman, Jordan [Hybrid Conference] 7-9 November 2023, pp. 899-916.
summary Green BIM is an emerging concept in the architecture, engineering, and construction industry that combines Building Information Modeling (BIM) technology with sustainable design principles. This approach emphasizes the importance of integrating green strategies into the design and construction process to improve the environmental performance of buildings. It enables designers, architects, engineers, and contractors to analyze the environmental impact of building materials and systems, simulate energy performance, and optimize the use of resources. The aim of the study is to conduct a bibliometric research and systematic analysis on the concept of 'green BIM'. Web of Science database was used to search for publications containing the term 'green BIM'. 252 relevant publications from the fields of construction building technology, architecture, and urban studies were analyzed. It evaluates research themes and trends in Green BIM in terms of publication and citation numbers, research areas, document types, journals, conferences, and books where publications were published, numbers of publications by country, author and co-authorship analysis, and keyword analysis. The keywords were divided into 9 clusters in the VOSviewer and each cluster was examined under a separate title. These titles are urban design, visual programming, design & construction, sustainability, energy efficiency, life cycle assessment, green BIM, project management and green building assessment. The results show that the most current keywords are being evaluated under the heading of urban studies. This situation highlights that, unlike other academic studies, priority is given to urban-scale applications of green BIM Moreover, apart from urban-scale studies, possible topics for academic research involve Life Cycle Assessment (LCA) and the integration of BIM in the LEED certification process. Currently, the industry and prominent publications prefer technical studies due to the extensive coverage of general inquiries.
series ASCAAD
email
last changed 2024/02/13 14:40

_id caadria2023_70
id caadria2023_70
authors Al-Douri, Firas, Yan, Wei and Jahic, Edin
year 2023
title Campusim: An Integrated Parametric BIM for Campus Design Simulation and Optimization
source Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 471–480
doi https://doi.org/10.52842/conf.caadria.2023.2.471
summary Although simulation models have been recently employed to model and examine pedestrian behavior in urban areas, comparable research has not been pursued in campus environments despite their importance as a critical area of inquiry. Those models' paucity and methodological limitations suggest investigating new research and design strategies to objectively assess and describe how the qualities of campus spaces and zones influence human behavior and, hence, predict the patterns of users' interaction and space usage. Those patterns and their impact on health have been pointed out as critical to the relationship among public space and quality of life due to Covid-19. There is an urgent need to develop decision support tools that would support interactive design processes and enhance the quality of open space design in terms of sense of space, place-making, and user interaction. To that goal, this study has proposed the integrated parametric BIM-based campus life simulation "CampuSIM" as a method for parametrization of the qualities of pedestrian campus zones and spaces. The study proposed the use of multi-objective optimization methods to fulfill various campus quantifiable and non-quantifiable design objectives. The significance of the proposed tool will result from its potential application in a wide range of complex, dynamic pedestrian behavior scenarios such as flows, social simulations, and design.
keywords Campus Modelling, Campus Master Planning, Campus Design, Parametric Modelling, BIM, Design Optimization
series CAADRIA
email
last changed 2023/06/15 23:14

_id ecaade2023_71
id ecaade2023_71
authors Austern, Guy, Yosifof, Roei and Fisher-Gewirtzman, Dafna
year 2023
title A Dataset for Training Machine Learning Models to Analyze Urban Visual Spatial Experience
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. 781–790
doi https://doi.org/10.52842/conf.ecaade.2023.2.781
summary Previous studies have described the effects of urban attributes such as the Spatial Openness Index (SOI) on pedestrians’ experience. SOI uses 3-dimensional ray casting to quantify the volume of visible space from a single viewpoint. The higher the SOI value, the higher the perceived openness and the lower the perceived density. However, the ray casting simulation on an urban-sized sampling grid is computationally intensive, making this method difficult to use in real-time design tools. Convolutional Neural Networks (CNN), have excellent performance in computer vision in image processing applications. They can be trained to predict the SOI analysis for large urban fabrics in real-time. However, these supervised learning models need a substantial amount of labeled data to train on. For this purpose, we developed a method to generate a large series of height maps and SOI maps of urban fabrics in New York City and encoded them as images using colour information. These height map - SOI analysis image pairs can be used as training data for a CNN to provide rapid, precise visibility simulations on an urban scale.
keywords Visibility Analysis, Machine Learning, CNN, Perceived Density
series eCAADe
email
last changed 2023/12/10 10:49

_id ecaade2023_144
id ecaade2023_144
authors Irsyad, Naufal Andi, Alkadri, Miktha Farid, De Luca, Francesco, Arif, Muhammad and Heinzelmann, Florian
year 2023
title Tropical Responsive Envelopes for Urban Heat Island mitigation in tropical countries
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. 249–258
doi https://doi.org/10.52842/conf.ecaade.2023.2.249
summary Since tropical countries present wet and dry seasons all year round, the objective of solar envelopes significantly shifts and aims to minimize the penetration of direct sun access to the buildings, due to high temperatures. As a consequence, the air conditioner (AC) frequently becomes a short-term solution to mitigate a building’s temperature, which unfortunately contributes to an annual increase in energy consumption. Accordingly, shading conditions become considerably relevant for urban form generation in tropical contexts, especially to reduce the UHI effect for tropical high-rise building areas. The concept of tropical responsive envelopes is then proposed not only to create shading for adjacent buildings but also to perform self-building protection that refers to self-shading envelopes. This concept specifically deals with solar-radiation reduction in order to achieve appropriate daylight in both the proposed building and the surrounding context. To do so, a solar protection plane and ray tracing analysis are performed based on shading performance criteria. In parallel, solar radiation simulation is applied to identify potential solar collectors on the building surfaces. This provides architects with a comprehensive method of tackling passive solar design strategy for urban equatorial climates
keywords Solar Envelopes, Shading Envelopes, Self-shading Envelopes, Tropical Responsive Envelopes
series eCAADe
email
last changed 2023/12/10 10:49

_id acadia23_v3_179
id acadia23_v3_179
authors Jabi, Wassim; Leon, David Andres; Alymani, Abdulrahman; Behzad, Selda Pourali; Salamoun, Michelle
year 2023
title Exploring Building Topology Through Graph Machine Learning
source ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 3: Proceedings of the 43rd Annual Conference for the Association for Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9891764-1-0]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 24-32.
summary Graph theory offers a powerful method for analyzing complex networks and relationships. When combined with machine learning, graph theory can provide valuable insights into the data generated by 3D models. This workshop integrated advanced spatial modeling and analysis with artificial intelligence, highlighting the importance of technological advancements in shaping the future of architecture and design. It introduced participants to novel workflows that link parametric 3D modeling with concepts of topology, graph theory, and graph machine learning. We used Topologicpy, an advanced spatial modeling and analysis software library designed for Architecture, Engineering, and Construction, paired with DGL, a powerful machine learning library that provides tools for implementing and optimizing graph neural networks (Figure 1). In essence, this process blends cutting-edge technologies and architectural principles that will shape the future of design. Participants learned how to use these workflows to convert 3D models into graphs, analyze their properties, and perform classification and regression tasks. Participants also explored how to create synthetic datasets based on generative and parametric workflows, and build and optimize graph neural networks for specific tasks.
series ACADIA
type workshop
last changed 2024/04/17 14:00

_id ecaade2023_272
id ecaade2023_272
authors Jorge, Leonardo, Eyesen, Carolina and Beirao, José Nuno
year 2023
title Design Cost Analysis in a BIM/VPI Framework
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. 217–226
doi https://doi.org/10.52842/conf.ecaade.2023.2.217
summary This paper aims to investigate the relations between architectural quality and financial feasibility of the design for constructing a sustainable environment. how is it possible to make the architect a protagonist of the design decision-making process, in which the financial impact on the final result is often most valued? The design process is often the stage of conflicting processes, and in particular, most requirements aiming at design sustainability usually collide with the financial plan and investment feasibility. How can the architect manage these conflicting requirements at early stages of the design process and keep track of their impacts as the design progresses in detail? During the design process, the architect is responsible to generate options seeking to meet the objectives of the stakeholders, while balancing multiple criteria such as sustainability requirements, cost, aesthetics and other. The set of design objectives must not impair the other qualities of the building or subjugate them to the final cost. In this way, we propose a digital tool to assist the architect, based on customer feedback, in different stages of the architectural project. Considering that financial feasibility is an essential design objective, the architect can operate a central role in this process, by balancing design decisions. The method consisted of (1) definition of the calculation models, (2) computational implementation of the tool (composed of a BIM modeling tool and an evaluation module), and (3) carrying out the case study. Initially, we present the framework, with an approach to the different stages of the project, systematized in LOD. Then, the different calculation models were implemented in a BIM/VPI environment, following a modular structure. We show a case study based on a housing project. Finally, we implemented the tool in a professional environment. Once a design program and a maximum investment value is defined for that program, the tool allows to confront construction cost and sustainability objectives (e.g.: designing a nZEB - netZero Energy Building) along the design process at different levels of detail. The flowchart for our BIM/VPI algorithm is presented and discussed in regard to its possible contributions to the production of more sustainable environments.
keywords Performance-based Design, Collaborative/Multi-disciplinary Design, Building Information Modelling, LOD, Algorithmic and Parametric Design, Decision-making
series eCAADe
email
last changed 2023/12/10 10:49

_id acadia23_v2_616
id acadia23_v2_616
authors Kuang, Zheyuan; Zhang, Jiaxin; Huang, Yiying; Li, Yunqin
year 2023
title Advancing Urban Renewal: An Automated Approach to Generating Historical Arcade Facades with Stable Diffusion Models
source ACADIA 2023: Habits of the Anthropocene: Scarcity and Abundance in a Post-Material Economy [Volume 2: Proceedings of the 43rd Annual Conference for the Association for Computer Aided Design in Architecture (ACADIA) ISBN 979-8-9860805-9-8]. Denver. 26-28 October 2023. edited by A. Crawford, N. Diniz, R. Beckett, J. Vanucchi, M. Swackhamer 616-625.
summary Urban renewal and transformation processes necessitate the preservation of the histor- ical urban fabric, particularly in districts known for their architectural and historical significance. These regions, with their diverse architectural styles, have traditionally required extensive preliminary research, often leading to subjective results. However, the advent of machine learning models has opened up new avenues for generating building facade images. Despite this, creating high-quality images for historical district renovations remains challenging, due to the complexity and diversity inherent in such districts. In response to these challenges, our study introduces a new methodology for automatically generating images of historical arcade facades, utilizing Stable Diffusion models conditioned on textual descriptions. By classifying and tagging a variety of arcade styles, we have constructed several realistic arcade facade image datasets. We trained multiple low-rank adaptation (LoRA) models to control the stylistic aspects of the gener- ated images, supplemented by ControlNet models for improved precision and authenticity. Our approach has demonstrated high levels of precision, authenticity, and diversity in the generated images, showing promising potential for real-world urban renewal projects. This new methodology offers a more efficient and accurate alternative to conventional design processes in urban renewal, bypassing issues of unconvincing image details, lack of precision, and limited stylistic variety. Future research could focus on integrating this two-dimensional image generation with three-dimensional modeling techniques, providing a more comprehensive solution for renovating architectural facades in historical districts.
series ACADIA
type paper
email
last changed 2024/04/17 13:59

_id caadria2023_192
id caadria2023_192
authors Lin, Zhichao, Yin, Shi, Liao, Wei and Xiao, Yiqiang
year 2023
title Genetic Algorithm-Based Building Geometric Opening Configurations Optimization for Enhancing Ventilation Performance in the High-Density Urban District
source Immanuel Koh, Dagmar Reinhardt, Mohammed Makki, Mona Khakhar, Nic Bao (eds.), HUMAN-CENTRIC - Proceedings of the 28th CAADRIA Conference, Ahmedabad, 18-24 March 2023, pp. 251–260
doi https://doi.org/10.52842/conf.caadria.2023.1.251
summary The quality of the outdoor environment relates to urban ventilation performance. Poor wind conditions in high-density urban districts may lead to severe air pollution and deteriorate outdoor thermal comfort. The increase of openings in building geometry is one of the effective passive design strategies for enhancing the porosity of urban morphology and benefitting urban ventilation. However, the outdoor wind environment correlates with the opening configurations of building geometry complicatedly. For seeking the optimal opening configurations, a decision support tool is urgently needed. Our study proposes a genetic algorithm-based optimization workflow for the opening configurations of building geometry design by integrating Computational Fluid Dynamics simulation and parametric design. A residential block in Shenzhen, China is chosen as an example to show this workflow. The results demonstrate that when the porosity is 15%, the pedestrian-level mean wind speed, the wind speed dispersion, and the pressure difference between the front and rear of the downstream building can be optimized by 20.00%, 19.35%, and 183.33% on maximum. When the porosity is increased to 30%, these values are 42.22%, 16.13%, and 483.33%. The resultant opening distribution probability maps can support building design at an early stage to achieve a comfortable urban environment.
keywords Urban Ventilation, Building Openings, Building Porosity, Genetic Algorithm Optimization, Computational Fluid Dynamics
series CAADRIA
email
last changed 2023/06/15 23:14

_id ecaade2023_205
id ecaade2023_205
authors Meeran, Ahmed and Joyce, Sam
year 2023
title Rethinking Airport Spatial Analysis and Design: A GAN based data driven approach using latent space exploration on aerial imagery for adaptive airport planning
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. 501–510
doi https://doi.org/10.52842/conf.ecaade.2023.2.501
summary Airports require long term planning, balancing estimations of future demand against available airfield land and site constraints. This is becoming more critical with climate change and the transition to sustainable aviation fuelling infrastructure. This paper demonstrates a novel procedure using Satellite Imagery and Generative Learning to aid in the comparative analysis and early-stage airfield design. Our workflow uses a GAN trained on 2000 images of airports transforming them into a high-dimensional latent space capturing the typologies’ large-scale features. Using a process of projection and dimensional-reduction methods we can locate real-world airport images in the generative latent space and vice-versa. With this capability we can perform comparative “neighbour” analysis at scale based on spatial similarity of features like airfield configuration, and surrounding context. Using this low-dimensional 3D ‘airport designs space’ with meaningful markers provided by existing airports allows for ‘what if’ modelling, such as visualizing an airport on a site without one, modifying an existing airport towards another target airport, or exploring changes in terrain, such as due to climate change or urban development. We present this method a new way to undertake case study, site identification and analysis, as well as undertake speculative design powered by typology informed ML generation, which can be applied to any typologies which could use aerial images to categorize them.
keywords Airport Development, Machine Learning, GAN, High Dimensional Analysis, Parametric Space Exploration, tSNE, Latent Space Exploration, Data Driven Planning
series eCAADe
email
last changed 2023/12/10 10:49

_id cdrf2023_273
id cdrf2023_273
authors Pixin Gong, Xiaoran Huang, Chenyu Huang, Shiliang Wang
year 2023
title Modeling on Outdoor Thermal Comfort in Traditional Residential Neighborhoods in Beijing Based on GAN
source Proceedings of the 2023 DigitalFUTURES The 5st International Conference on Computational Design and Robotic Fabrication (CDRF 2023)
doi https://doi.org/https://doi.org/10.1007/978-981-99-8405-3_23
summary With the support of new urban science and technology, the bottom-up and human-centered space quality research has become the key to delicacy urban governance, of which the Universal Thermal Climate Index (UTCI) have a severe influence. However, in the studies of actual UTCI, datasets are mostly obtained from on-site measurement data or simulation data, which is costly and ineffective. So, how to efficiently and rapidly conduct a large-scale and fine-grained outdoor environmental comfort evaluation based on the outdoor environment is the problem to be solved in this study. Compared to the conventional qualitative analysis methods, the rapidly developing algorithm-supported data acquisition and machine learning modelling are more efficient and accurate. Goodfellow proposed Generative Adversarial Nets (GANs) in 2014, which can successfully be applied to image generation with insufficient training data. In this paper, we propose an approach based on a generative adversarial network (GAN) to predict UTCI in traditional blocks. 36000 data samples were obtained from the simulations, to train a pix2pix model based on the TensorFlow framework. After more than 300 thousand iterations, the model gradually converges, where the loss of the function gradually decreases with the increase of the number of iterations. Overall, the model has been able to understand the overall semantic information behind the UTCI graphs to a high degree. Study in this paper deeply integrates the method of data augmentation based on GAN and machine learning modeling, which can be integrated into the workflow of detailed urban design and sustainable construction in the future.
series cdrf
email
last changed 2024/05/29 14:04

For more results click below:

this is page 0show page 1show page 2show page 3show page 4show page 5... show page 38HOMELOGIN (you are user _anon_670552 from group guest) CUMINCAD Papers Powered by SciX Open Publishing Services 1.002