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Authors:F Peter Ortner, Jing Zhi Tay Abstract: International Journal of Architectural Computing, Ahead of Print. Embedding circular economy (CE) principles in early design requires iterative evaluation across multiple lifecycle phases, with trade-offs between objectives complicating the identification of best solutions. This paper puts forward methods to automatically discover diverse, yet well-performing solution types within complex multi-objective CE design optimisation models. Working with a parametric model derived from a furniture design for CE case study, a comparison is made between weighted-sum single objective optimisation and multi-objective optimisation augmented with clustered solution types targeted by the reference point-based NSGA-II optimisation algorithm. Efficiency of optimisation, quality of results and distinctiveness of solution types presented by each method is compared in an effort to understand which will best assist designers to manage complexity in CE design. The generalisability of the presented methods to larger scale CE design problems is discussed and future areas of work on computational design for CE are extrapolated from the presented results. Citation: International Journal of Architectural Computing PubDate: 2023-05-26T10:40:55Z DOI: 10.1177/14780771231177508
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Authors:Likai Wang, Ting Luo, Tong Shao, Guohua Ji Abstract: International Journal of Architectural Computing, Ahead of Print. In building massing design, using passive design strategies is a critical approach to reducing energy consumption while offering comfortable indoor environments. However, it is often impractical for architects to systematically explore passive design strategies at the outset of the building massing design and architectural form-finding processes, which may result in inefficient or ineffective utilization of the strategies. To address this issue, this study presents a reverse passive design strategy exploration approach that leverages the capability of computational optimization and parametric modeling to help architects identify feasible passive design strategies for building massing design. The approach is achieved using a building massing design generation and optimization tool, called EvoMass, and various building performance simulation tools in Rhino-Grasshopper. The optimization can produce site-specific design references that reflect rich performance implications associated with passive design strategies, such as atriums and self-shading. As such, architects can screen out promising passive design strategies corresponding to different performance factors from the optimization result. Two case studies related to daylighting, sky exposure, and solar heat utility are presented to demonstrate the approach, and the relevant utility and limitations are discussed. Citation: International Journal of Architectural Computing PubDate: 2023-05-18T10:21:22Z DOI: 10.1177/14780771231177514
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Authors:Patrick Bedarf, Anna Szabo, Enrico Scoccimarro, Benjamin Dillenburger Abstract: International Journal of Architectural Computing, Ahead of Print. This paper presents an innovative design and fabrication workflow for a lightweight composite slab prototype that combines mineral foam 3D printing (F3DP) and concrete casting. Non-standardized concrete elements that are geometrically optimized for resource efficiency often result in complex shapes that are difficult to manufacture. This paper extends the research in earlier studies, showing that F3DP can address this challenge. F3DP is used to construct 24 stay-in-place formwork elements for a lightweight, resource-efficient ribbed concrete element with a 2 × 1.3 m footprint. This advancement highlights the improved robotic F3DP setup, computational design techniques for geometry and print path generation, and strategies to achieve near-net-shape fabrication. The resulting prototype shows how complex geometries that were previously cost-prohibitive can be produced efficiently. Discussing the findings, challenges, and future improvements offers useful perspectives and supports the development of this resourceful and sustainable construction technique. Citation: International Journal of Architectural Computing PubDate: 2023-05-17T09:25:53Z DOI: 10.1177/14780771231174526
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Authors:Andrew Kudless Abstract: International Journal of Architectural Computing, Ahead of Print. This paper examines the prevalence of bias in artificial intelligence text-to-image models utilized in the architecture and design disciplines. The rapid pace of advancements in machine learning technologies, particularly in text-to-image generators, has significantly increased over the past year, making these tools more accessible to the design community. Accordingly, this paper aims to critically document and analyze the collective, computational, and cognitive biases that designers may encounter when working with these tools at this time. The paper delves into three hierarchical levels of operation and investigates the possible biases present at each level. Starting with the training data for large language models (LLM), the paper explores how these models may create biases privileging English-language users and perspectives. The paper subsequently investigates the digital materiality of models and how their weights generate specific aesthetic results. Finally, the report concludes by examining user biases through their prompt and image selections and the potential for platforms to perpetuate these biases through the application of user data during training. Citation: International Journal of Architectural Computing PubDate: 2023-05-12T11:13:28Z DOI: 10.1177/14780771231170272
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Authors:Benjamin Ennemoser, Ingrid Mayrhofer-Hufnagl Abstract: International Journal of Architectural Computing, Ahead of Print. The development of Generative Adversarial Networks (GANs) has accelerated the research of Artificial Intelligence (AI) in architecture as a generative tool. However, since their initial invention, many versions have been developed that only focus on 2D image datasets for training and images as output. The current state of 3DGAN research has yielded promising results. However, these contributions focus primarily on building mass, extrusion of 2D plans, or the overall shape of objects. In comparison, our newly developed 3DGAN approach, using fully spatial building datasets, demonstrates that unprecedented interconnections across different scales are possible resulting in unconventional spatial configurations. Unlike a traditional design process, based on analyzing only a few precedents (typology) according to the task, by collaborating with the machine we can draw on a significantly wider variety of buildings across multiple typologies. In addition, the dataset was extended beyond the scale of complete buildings and involved building components that define space. Thus, our results achieve a high spatial diversity. A detailed analysis of the results also revealed new hybrid architectural elements illustrating that the machine continued the interconnections of scale since elements were not explicitly part of the dataset, becoming a true design collaborator. Citation: International Journal of Architectural Computing PubDate: 2023-05-11T05:29:57Z DOI: 10.1177/14780771231168231
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Authors:Andrew John Wit, Dana Cupkova, Matias del Campo, Mollie Claypool Abstract: International Journal of Architectural Computing, Ahead of Print.
Citation: International Journal of Architectural Computing PubDate: 2023-05-10T12:16:14Z DOI: 10.1177/14780771231171939
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Authors:Melih Kamaoğlu Abstract: International Journal of Architectural Computing, Ahead of Print. Humans have always sought to grasp nature’s working principles and apply acquired intelligence to artefacts since nature has always been the source of inspiration, solution and creativity. For this reason, there is a comprehensive interrelationship between the philosophy of nature and architecture. After Charles Darwin’s revolutionary work, living beings have started to be comprehended as changing, evolving and developing dynamic entities. Evolution theory has been accepted as the interpretive power of biology after several discussions and objections among scientists. In time, the working principles of evolutionary mechanisms have begun to be explained from genetic code to organism and environmental level. Afterwards, simulating nature’s evolutionary logic in the digital interface has become achievable with computational systems’ advancements. Ultimately, architects have begun to utilise evolutionary understanding in design theories and methodologies through computational procedures since the 1990s. Although several studies about technical and pragmatic elements of evolutionary tools in design, there is still little research on the historical, theoretical and philosophical foundations of evolutionary understanding in digital architecture. This paper fills this literature gap by critically reviewing the evolutionary understanding embedded in digital architecture theories and designs since the beginning of the 1990s. The original contribution is the proposed intellectual framework seeking to understand and conceptualise how evolutionary processes were defined in biology and philosophy, then represented through computational procedures, to be finally utilised by architectural designers. The network of references and concepts is deeply connected with the communication between natural processes and their computational simulations. For this reason, another original contribution is the utilisation of theoretical limits and operative principles of computation procedures to shed light on the limitations, shortcomings and potentials of design theories regarding their speculations on the relationship between natural and computational ontologies. Citation: International Journal of Architectural Computing PubDate: 2023-05-03T05:48:08Z DOI: 10.1177/14780771231174890
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Authors:Panagiota Pouliou, Anca-Simona Horvath, George Palamas Abstract: International Journal of Architectural Computing, Ahead of Print. The process of architectural design aims at solving complex problems that have loosely defined formulations, no explicit basis for terminating the problem-solving activity, and where no ideal solution can be achieved. This means that design problems, as wicked problems, sit in a space between incompleteness and precision. Applying digital tools in general and artificial intelligence in particular to design problems will then mediate solution spaces between incompleteness and precision. In this paper, we present a study where we employed machine learning algorithms to generate conceptual architectural forms for site-specific regulations. We created an annotated dataset of single-family homes and used it to train a 3D Generative Adversarial Network that generated annotated point clouds complying with site constraints. Then, we presented the framework to 23 practitioners of architecture in an attempt to understand whether this framework could be a useful tool for early-stage design. We make a three-fold contribution: First, we share an annotated dataset of architecturally relevant 3D point clouds of single-family homes. Next, we present and share the code for a framework and the results from training the 3D generative neural network. Finally, we discuss machine learning and creative work, including how practitioners feel about the emergence of these tools as mediators between incompleteness and precision in architectural design. Citation: International Journal of Architectural Computing PubDate: 2023-04-27T01:03:35Z DOI: 10.1177/14780771231168229
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Authors:Ultan Byrne Abstract: International Journal of Architectural Computing, Ahead of Print. This paper recommends that critical attention towards machine learning should be focused on the ordering procedures at work in these models. More precisely, it draws attention to the central role of ‘latent spaces.’ The paper first explores ‘latent space’ through a series of analogies, and then briefly situates the concept in relation to a genealogy reaching back to developments in mathematical statistics at the turn to the 20th century. Citation: International Journal of Architectural Computing PubDate: 2023-04-19T06:58:40Z DOI: 10.1177/14780771231170271
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Authors:Nemeh Rihani Abstract: International Journal of Architectural Computing, Ahead of Print. This paper investigates the potential of dense multi-image 3D photogrammetric reconstruction of destroyed cultural heritage monuments by employing public domain imagery for heritage site visitors. This work focuses on the digital reconstruction of the Temple of Bel, one of the heritage monuments in Palmyra, Syria, which was demolished in the summer of 2015 due to armed conflict. This temple is believed to be one of the most significant religious structures of the first century AD in the Middle East and North Africa (MENA) region with its unique design and condition before destruction actions. The process is carried out using solely one source of images; the freely available visitors’ images collected from the social media platforms and web search engines. This paper presents a digital 3D reconstruction workflow for the collected images using an advanced photogrammetry pipeline and dense image matching software. The virtually reconstructed outputs will be managed and implemented efficiently in Unity3D to create an entire 3D virtual interactive environment for the deconstructed temple to be visualised and experienced using the new Oculus Quest VR headset. The virtual Palmyra’s visitor will be offered an enhanced walk-through off-site interactive, immersive experience compared to the real-world one, which is non-existing and unobtainable at the site in the current time. Citation: International Journal of Architectural Computing PubDate: 2023-04-10T04:29:29Z DOI: 10.1177/14780771231168224
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Authors:Xinwei Zhuang, Yi Ju, Allen Yang, Luisa Caldas Abstract: International Journal of Architectural Computing, Ahead of Print. Generative design in architecture has long been studied, yet most algorithms are parameter-based and require explicit rules, and the design solutions are heavily experience-based. In the absence of a real understanding of the generation process of designing architecture and consensus evaluation matrices, empirical knowledge may be difficult to apply to similar projects or deliver to the next generation. We propose a workflow in the early design phase to synthesize and generate building morphology with artificial neural networks. Using 3D building models from the financial district of New York City as a case study, this research shows that neural networks can capture the implicit features and styles of the input dataset and create a population of design solutions that are coherent with the styles. We constructed our database using two different data representation formats, voxel matrix and signed distance function, to investigate the effect of shape representations on the performance of the generation of building shapes. A generative adversarial neural network and an auto decoder were used to generate the volume. Our study establishes the use of implicit learning to inform the design solution. Results show that both networks can grasp the implicit building forms and generate them with a similar style to the input data, between which the auto decoder with signed distance function representation provides the highest resolution results. Citation: International Journal of Architectural Computing PubDate: 2023-04-03T07:04:44Z DOI: 10.1177/14780771231168233
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Authors:Adam Sebestyen, Urs Hirschberg, Shervin Rasoulzadeh Abstract: International Journal of Architectural Computing, Ahead of Print. We present an early prototype of a design system that uses Deep Learning methodology—Conditional Variational Autoencoders (CVAE)—to arrive at custom design spaces that can be interactively explored using semantic labels. Our work is closely tied to principles of parametric design. We use parametric models to create the dataset needed to train the neural network, thus tackling the problem of lacking 3D datasets needed for deep learning. We propose that the CVAE functions as a parametric tool in itself: The solution space is larger and more diverse than the combined solution spaces of all parametric models used for training. We showcase multiple methods on how this solution space can be navigated and explored, supporting explorations such as object morphing, object addition, and rudimentary 3D style transfer. As a test case, we implemented some examples of the geometric taxonomy of “Operative Design” by Di Mari and Yoo. Citation: International Journal of Architectural Computing PubDate: 2023-03-31T08:08:17Z DOI: 10.1177/14780771231168232
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Authors:Ingrid Mayrhofer-Hufnagl, Benjamin Ennemoser Abstract: International Journal of Architectural Computing, Ahead of Print. Understanding the importance of data is crucial for realizing the full potential of AI in architectural design. Satellite images are extremely numerous, continuous, high resolution, and accessible, allowing nuanced experimentation through dataset curation. Combining deep learning with remote-sensing technologies, this study poses the following questions. Do newly available datasets uncover ideas about the city previously hidden because urban theory is predominantly Eurocentric' Do extensive and continuous datasets promise a more refined examination of datasets’ effects on outcomes' Generative adversarial networks can endlessly generate new designs based on a curated dataset, but architectural evaluation has been questionable. We employ quantitative and qualitative assessment metrics to investigate human collaboration with AI, producing results that contribute to understanding AI-based urban design models and the significance of dataset curation. Citation: International Journal of Architectural Computing PubDate: 2023-03-30T07:39:32Z DOI: 10.1177/14780771231168223
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Authors:Marcela Noronha Pinto de Oliveira e Sousa, Fabiano Rogerio Correa Abstract: International Journal of Architectural Computing, Ahead of Print. There has been a recent interest in the field of digital heritage to advance historic building information modeling (HBIM) towards digital twins (DT). This paper investigates the potential and limitations of HBIM use as DTs through a systematic mapping of literature (SML). The conclusions were applied in an incremental and low-code workflow to model historic buildings aiming at achieving a trade-off between a high degree of parametrization and a high degree of geometric accuracy. The proposed workflow is illustrated through a parametric script developed with visual programming in Grasshopper for Rhino 3D to model historic columns from profiles. VisualARQ for Rhino 3D is used to convert the script into a BIM object that uses profiles, automatically extracted from a point cloud acquired with 3D laser scanning, as an initial shape. This results in a simpler workflow to achieve more accurate HBIM models that could be leveraged in DT simulations. Citation: International Journal of Architectural Computing PubDate: 2023-03-29T01:38:20Z DOI: 10.1177/14780771231168226
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Authors:Dimitra Tsoumpri Abstract: International Journal of Architectural Computing, Ahead of Print. Flexible and adaptable spaces have been a field of interest in western architecture since the 1930s and Modernism’s “Open plan.” Even though it started as a design problem, as cybernetics became a more active part of the design process, adaptable space became dependent on technology and mechanical systems. A lot of methods tend to diminish the role of architectural design and offer deterministic implementations that limit the user’s creative freedom and interaction with the adaptable system. This study explores how adaptable space can be approached through design and how adaptability can be implemented in existing spaces through a computational approach. The paper is structured in two parts, the analysis, and the concept method. The first part includes the literacy review and known architectural examples of adaptability. The second part focuses on proposing a design method for approaching adaptable spaces with a high degree of user creative freedom. The method is tested through a case study regarding the implementation of a spatial adaptable system in a 1970s apartment. Citation: International Journal of Architectural Computing PubDate: 2023-03-24T08:44:38Z DOI: 10.1177/14780771231162382
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Authors:Nicholas Rawlings, Dimitris Papanikolaou Abstract: International Journal of Architectural Computing, Ahead of Print. The ability of architects to collaborate and work in parallel on digital assets is limited by pessimistic strategies for managing shared files. The software engineering community has worked around this problem by adopting optimistic version control techniques, which rely on the ability to diff, patch, and merge versions of the files they manage. Unfortunately, the diffing, patching, and merging algorithms in existing version control systems are designed to work with text, and not with the types of files, such as 3D models, most commonly used by architects. This paper presents a high-level design for a command line program capable of diffing, patching, and merging openNURBS models, an open source 3D model format that enjoys widespread use among architects and other designers. Key algorithms are illustrated through simple geometric examples, and future plans to integrate the program into an existing version control system are described. Citation: International Journal of Architectural Computing PubDate: 2023-02-28T05:13:23Z DOI: 10.1177/14780771231154485
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Authors:Gozde Damla Turhan, Guzden Varinlioglu, Murat Bengisu Abstract: International Journal of Architectural Computing, Ahead of Print. Recent studies in digital design and fabrication processes focus on the potentials of using biological systems in nature as mathematical models or more recently as bio-based materials and composites in various applications. The reciprocal integration between mechanical and digital media for designing and manufacturing bio-based products is still open to development. The current digital form-finding scripts involve an extensive material list, although bio-based materials have not been fully integrated yet. This paper explores a customized form-finding process by suggesting a framework through mechanically informed material-based computation. Bacterial cellulose, an unconventional yet potential material for design, was explored across its biological growth, tensile properties, and the integration of datasets into digital form finding. The initial results of the comparison between digital form finding with conventional materials versus mechanically informed digital form finding revealed a huge difference in terms of both the resulting optimum geometry and the maximum axial forces that the geometry could actually handle. Although this integration is relatively novel in the literature, the proposed methodology has proven effective for enhancing the structural optimization process within digital design and fabrication and for bringing us closer to real-life applications. This approach allows conventional and limited material lists in various digital form finding and structural optimization scripts to cover novel materials once the quantitative mechanical properties are obtained. This method has the potential to develop into a commercial algorithm for a large number of bio-based and customized prototypes within the context of digital form finding of complex geometries. Citation: International Journal of Architectural Computing PubDate: 2023-02-25T07:54:29Z DOI: 10.1177/14780771231159239
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Authors:Yifan Zhou, Hyoung-June Park Abstract: International Journal of Architectural Computing, Ahead of Print. The goal of this paper is to develop an interactive web-based machine learning application to assist architects with multimodal inputs (sketches and textual information) for conceptual design. With different textual inputs, the application generates the architectural stylistic variations of a user’s initial sketch input as a design inspiration. A novel machine learning model for the multimodal input application is introduced and compared to others. The machine learning model is performed through procedural training with the content curation of training data (1) to control the fidelity of generated designs from the input and (2) to manage their diversity. The web-based interface is at its work in progress as a frontend of the proposed application for better user experience and future data collection. In this paper, the framework of the proposed interactive application is explained. Furthermore, the implementation of its prototype is demonstrated with various examples. Citation: International Journal of Architectural Computing PubDate: 2023-01-05T04:34:23Z DOI: 10.1177/14780771221147605
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Authors:Ruwan Fernando, Ruby Michael Abstract: International Journal of Architectural Computing, Ahead of Print. Evolutionary design (ED) is a strategy that makes use of computational power to couple generative techniques with evaluation methods, to put forward designs that are better with each iteration. In this research, we present a representation scheme for solving spatial layout problems that is simple to implement as well as extend. The mechanisms for evaluation and mutation are defined and also shown to be extendable. Ultimately, the topic explored here is the ways in which ED and computation can enhance our design thinking and how computers can provide the background to new design processes and workflows. Citation: International Journal of Architectural Computing PubDate: 2023-01-04T06:38:35Z DOI: 10.1177/14780771221148778
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Authors:Andre Brown First page: 3 Abstract: International Journal of Architectural Computing, Ahead of Print.
Citation: International Journal of Architectural Computing PubDate: 2023-01-14T10:12:29Z DOI: 10.1177/14780771231153022
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Abstract: International Journal of Architectural Computing, Ahead of Print.
Citation: International Journal of Architectural Computing PubDate: 2022-08-08T04:53:38Z DOI: 10.1177/14780771221093272
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Authors:Sverre Magnus Haakonsen, Anders Rønnquist, Nathalie Labonnote First page: 5 Abstract: International Journal of Architectural Computing, Ahead of Print. Shape grammars allow a designer to explore a diverse and broad design space. Especially among architects and engineers, the opportunity to evaluate numerous alternatives in the conceptual phase facilitates creativity. Since the introduction of shape grammars 50 years ago, significant research and development have been performed: new applications, combinations with optimisation and integration in digital environments, among others. Consequently, there is a need to map the existing literature to encourage further progress in the field and a lower threshold for those interested in learning more about shape grammars. This study, therefore, presents a systematic mapping of shape grammars in architecture and engineering. Mapping is performed by identifying a query of relevant keywords used in five databases, with the results forming the basis of the mapping. Each of the included articles is then screened to filter out those that do not fit the content criteria. The remaining publications are then evaluated and organised based on the attributes’ application, research type, implementation, engineering and optimisation. The outcome is organised in explanatory illustrations and tables. The final discussion highlights the extensive work performed with shape grammars in the generation of two-dimensional floor plans, an increase in digital development in recent years and the need for further research. The findings indicate a gap between the state of the art and the necessary level of applicability for shape grammars to be an attractive design tool, especially for non-experts. Citation: International Journal of Architectural Computing PubDate: 2022-05-20T01:17:17Z DOI: 10.1177/14780771221089882
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Authors:Gizem Özerol, Semra Arslan Selçuk First page: 23 Abstract: International Journal of Architectural Computing, Ahead of Print. 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. Citation: International Journal of Architectural Computing PubDate: 2022-05-17T05:34:11Z DOI: 10.1177/14780771221100102
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Authors:Hossein Soltan Rahmati, Mohammad Hossein Ayatollahi First page: 42 Abstract: International Journal of Architectural Computing, Ahead of Print. Morphological theories in architecture are more popular than ever partly due to the rapid developments in computational techniques. This rapid development, however, is more fruitful when it is informed of the philosophical and ethical bases of such techniques. The neglected historical case of Benjamin W. Betts, an architect of the late Victorian Britain, is an early example of the effects of philosophical presuppositions on computable theories of morphogenesis in arts and architecture. The aims of this study are to shed light on his motivations and sources of inspiration, and also to present an algorithm for his procedure. We used the only book available on the Betts' works in addition to archival materials to conduct the research. Betts was under heavy influence of Idealism and Oriental thought in his symbology and the morphogenetic procedure he designed. The Python/Grasshopper algorithm for Rhino presented in this paper produces two dimensional Betts' diagrams that can be used as an educational tool or an opportunity of enjoying the beauty of mathematical forms, and the immense variety they offer thanks to parameterization. Citation: International Journal of Architectural Computing PubDate: 2022-06-05T04:00:10Z DOI: 10.1177/14780771221106152
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Authors:Bhoomika Umashankar First page: 67 Abstract: International Journal of Architectural Computing, Ahead of Print. Architects aspire to build iconic buildings and focus on experimenting with non-standard forms. The construction of non-standard forms is challenging. This has led many researchers and facade designers to develop and resolve the complexity of forms to simpler, buildable elements. In this progress, the tessellation of non-standard surfaces has experimented considerably with different approaches using computational tools. All the approaches from researchers or facade engineers have limited access for every designer. As they develop patented software or use any coding languages which are not accessed by any open-source platform. Hence in academia, it is difficult to experiment in this domain. This paper analyzes the existing panalization computational tools and different approaches used by researchers worldwide in developing complex curved surfaces. Analyzing the relevant cases led to identifying the gap in current research. This has led to investigate and explore a new algorithmic process using an existing computational tool: Agent-based modeling on an open-source tool (Grasshopper-Visual programming language), which is phase -1 of the Master’s thesis. Citation: International Journal of Architectural Computing PubDate: 2022-08-16T07:03:04Z DOI: 10.1177/14780771221120693
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Authors:Seyed Hossein Zargar, Jaleh Sadeghi, Nathan C. Brown First page: 84 Abstract: International Journal of Architectural Computing, Ahead of Print. Agent-based modelling (ABM) is a complex problem-solving approach that can be employed in early-stage parametric design, and certain design applications may benefit from such a bottom-up strategy. This research investigates the potential of ABM for structural design optimization. A case study of a form-found cantilevered truss is presented that has a doubly curved shape over a regular grid, resulting in individual members with different lengths across the structure. It is hypothesized that an agent-based approach might generate an irregular grid of similar or better structural performance, but with more uniform length of individual elements. This approach could be useful when designing a global structural form from a kit of parts or adaptively reusing a disassembled existing structure with regular member lengths. A series of ABM simulations are conducted with different hyperparameters, and the generated designs are compared to the original form-found shape in terms of structural performance. Citation: International Journal of Architectural Computing PubDate: 2022-11-30T03:12:43Z DOI: 10.1177/14780771221143493
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Authors:Djordje Stojanovic, Milica Vujovic, Yi Ding, Milan Katic First page: 100 Abstract: International Journal of Architectural Computing, Ahead of Print. This paper introduces modular and context-aware evaporative cooling for the outdoor urban environment as a physical structure that could be implemented at various scales and physical contexts. We propose a technique for collecting occupancy and climatic data to create a computational context and optimise its operation. We then outline a concept for developing a predictive algorithm that would further enhance its performance. The research focuses on the interaction between the proposed system and the environment and establishes an evidence-based technique to balance the temperature drop and the humidity it generates. The study combines architectural design, mechanical engineering and computer science to enable the upscaled application of evaporative cooling to help reduce local heat accumulation in cities. Citation: International Journal of Architectural Computing PubDate: 2022-05-20T09:36:31Z DOI: 10.1177/14780771221095307
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Authors:Ahmad A Fouad, Ahmed El Antably First page: 120 Abstract: International Journal of Architectural Computing, Ahead of Print. Spatial behavior is a principal aspect for architects to consider. Unfortunately, it is sometimes hard to predict, as users of space seldom follow a standard routine. However, predicting user behavior in a space can potentially illuminate the entire design process. Moreover, it is a key factor in fighting the recent COVID-19 pandemic. Until most of the public gets their vaccine, health officials recommend social distancing as the primary means of fighting the pandemic. This paper uses an agent-based modeling and simulation (ABMS) approach to reproduce, analyze, and predict spatial behavior during the pandemic in a school environment and its impact on disease propagation. The simulation reproduces the behavior of teachers and students at a sample elementary school. By manipulating parameters that simulate the school officials' response to the pandemic, stakeholders can assess the most effective preventive measures. As a result of running multiple scenarios, the study demonstrates how varying starting conditions and alternate spatial behaviors could lead to different results, providing insight to stakeholders on how to handle disease spread in school environments. Citation: International Journal of Architectural Computing PubDate: 2022-05-05T03:08:03Z DOI: 10.1177/14780771221089886
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Authors:David William Newton First page: 136 Abstract: International Journal of Architectural Computing, Ahead of Print. Mental health disorders, such as depression, have been estimated to account for the largest proportion of global disease burden. Existing research has established significant correlations between the built environment and mental health. This research, however, has relied on traditional statistical methods that are not amenable to working with large remote sensing image-based datasets. This research addresses this challenge and contributes new knowledge and a novel method for using generative deep learning for urban analysis and synthesis tasks involving mental health. The research specifically investigates three mental state measures: depression, anxiety, and the perception of safety. The experimental results demonstrate the efficacy of the process—providing a new method to find correlational signals, while providing insights on the correlation between specific urban design features and the incidence of depression. Citation: International Journal of Architectural Computing PubDate: 2022-05-18T12:55:05Z DOI: 10.1177/14780771221089885
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Authors:Sara Dotta Correa, Carlos Eduardo Verzola Vaz First page: 158 Abstract: International Journal of Architectural Computing, Ahead of Print. This work presents the second stage of a larger study which conducted the elaboration of a shape grammar based on the analysis of the remaining fishing villages in the Santa Catarina State, Southern Brazil. The architectural and formal structure of the villages provide a perspective of the constructive methods and features embedded in the spatial arrangements and represent a local cultural heritage site. The aim of the present work relies on unraveling its spatial resources using a shape grammar approach, in order to contribute to the preservation of a distinct culture, and is intended to be used to safeguard its formal language planning. Also, through the analytical grammar, it would be possible to contribute in framing design guidelines regarding the remaining villages, to keep it steady on the traditional context, safeguarding its peculiar character. As such, the method in this body of work considered the analysis resulting from the first stage, in order to develop an analytical shape grammar using Garopaba village as a case of study. This stage involved the establishment of a formal language for the analytical grammar, consisting of initial form, vocabulary, families, and spatial relations, and thus, a series of rules emerged, decoding the composition arrangements. The results involved the verification of the considered parameters, confirming the existence of spatial patterns. Thus, it was possible to conclude that the grammar contributes to identifying the occupation process occupation and the spatial patterns which underlies an artisanal fishing village. Also, the grammar allowed the creation of urban compositions similar to the structure of traditional fishing communities in Santa Catarina, generating different discussions regarding the analytical approach towards fishing villages arrangements, compared to the examples studied, specifically, in Garopaba city. Citation: International Journal of Architectural Computing PubDate: 2022-09-27T09:51:25Z DOI: 10.1177/14780771221124698
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Authors:Fadime Diker, Mesut Arslan, İlker Erkan First page: 188 Abstract: International Journal of Architectural Computing, Ahead of Print. In this study, it is aimed to develop an adaptive network-based fuzzy inference system (ANFIS) model that can estimate tread width values based on the physical characteristics of people and suitable for comfort and safety needs. The input values were obtained by measuring the height, step, and shoe sole lengths of the sample group of 200 people. For the tread width value to be used as output value, a prototype stair model in which different step sizes can be experienced was used. The tread width value obtained by using the test data in the developed ANFIS model was compared with the tread width value obtained from the experimental study. It has been concluded that the ANFIS model developed as a result of the comparison can be used as an efficient tool in estimating the value of stair tread width, which can meet people’s physical comfort needs. Citation: International Journal of Architectural Computing PubDate: 2022-04-15T03:57:15Z DOI: 10.1177/14780771221082252
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