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Authors:Abdulrahman Alymani, Wassim Jabi Abstract: International Journal of Architectural Computing, Ahead of Print. The use of neural networks to retrieve relevant images has become mainstream. However, retrieving images that contain specific spatial relationships remains a challenging task. Images alone are not sufficient to fully describe spatial and topological relationships, which are usually better represented as a graph made up of nodes and edges. This paper describes the development of a graph-based computational tool for retrieving architectural precedents that closely match the relationship between a building and its surrounding ground as detected in a designer’s project. The tool, titled Building Ground Relationship (BGR), stems from a research project into Graph Machine Learning (GML) that used Deep Graph Convolutional Neural Networks (DGCNNs) to classify building and ground relationships. The neural network was trained using a large synthetic dataset of graphs and optimized through the fine-tuning of its hyperparameters. To verify its performance, a second surrogate model was built using the Deep Graph Library (DGL). The results were nearly identical, thus giving confidence that the model is highly optimized. In the development of the BGR tool, two primary technologies were utilized. In the first instance, the synthetic database was built in Rhino Grasshopper by generating variations of a parametric model. The dual graphs of these models were then automatically generated and exported using the Toplogic software library. The second phase involved developing GML models used for predicting the class of the conceptual design, enabling the retrieval of the smaller case study. The results of this research point to the importance of topological representation and machine learning approaches in retrieving and classifying architectural precedents. Citation: International Journal of Architectural Computing PubDate: 2024-08-09T11:49:27Z DOI: 10.1177/14780771241260853
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Authors:Yujie Cao, Azhan Abdul Aziz, Wan Nur Rukiah Mohd Arshard Abstract: International Journal of Architectural Computing, Ahead of Print. This study explored integrating Stable Diffusion, a generative artificial intelligence (AI), into architectural design workflows, focusing on its impact on design process and students’ learning experiences. A comparative analysis revealed an optimized workflow incorporating Stable Diffusion, which enhanced design exploration, conceptualization and visualization in early design stages. Demonstrations showcased text/image-to-image capabilities generating architectural visuals. Employing a mixed-methods research design, which encompasses comparative analysis and a thorough questionnaire-based exploration, the research sheds light on the challenges and opportunities of integrating Stable Diffusion into architectural education and practice. While receptive, some concerns existed around AI automation risks. The paper contributes to a deeper understanding of the transformative potential of generative AI, particularly Stable Diffusion, in reshaping workflows and educational dimensions of architectural design. Findings advise integrating emerging AI like Stable Diffusion into architecture curricula to equip students for AI-driven industries, emphasizing judicious human-AI collaboration. Further research could continue optimizing hybrid human-AI design workflows. Citation: International Journal of Architectural Computing PubDate: 2024-08-07T09:17:05Z DOI: 10.1177/14780771241270257
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Authors:Deena EL-Mahdy Abstract: International Journal of Architectural Computing, Ahead of Print. The study presents unique teaching approach for generating a parametric modular facade fabrication for first-year students in visual design module using a computational visual coding method based on Truchet Tiles. The method followed four main phases: exploring tiling, testing connectivity, fabrication, and assembly. Shape grammar was considered during the design principles implementation to respond to climatic behavior. Space-filling shapes method known as the “Generalized Abeille Tiles” was followed to ensure tiling connectivity. The experimentation involves manual folding techniques without any software. A survey was conducted among first-year and fourth-year students post-introduction to computational software. The results showed a wide range of alternative geometries with different self-shading patterns generated. It highlighted that facade fabrication aided students in comprehending computational logic, easing the understanding of computational software complexity. This pilot study emphasizes the effectiveness of teaching computational concepts in early curricula. Citation: International Journal of Architectural Computing PubDate: 2024-08-07T09:11:41Z DOI: 10.1177/14780771241270265
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Authors:Gulbin Ozcan-Deniz, Beliz Ozorhon, Osman Can Kaya Abstract: International Journal of Architectural Computing, Ahead of Print. Over the past decade, the construction industry has undergone significant change due to technological advancements. Among these, Building Information Modeling (BIM) has been one of the pioneer technologies to impact this transformation. Projects using BIM reported increased productivity with expedited work of project stakeholders while maximizing their collaboration. While BIM has achieved remarkable success in developed countries, its adoption in developing countries remains limited. Studies showed that the acceptance of BIM technology is still very low in some countries. This study examines the status of BIM adoption including exploring the barriers as well as the factors that contribute to overcoming these barriers in adopting BIM in developing countries. BIM enablers in construction projects from the perspective of public clients were examined via a systematic review performed through the literature to identify these factors. Interviews were conducted with public clients to examine these factors. The average severity of each factor was ranked by clients. Notably, the study reveals that unfavorable economic conditions, high costs, and unclear project benefits as the significant barriers to BIM adoption. Clear advantages of BIM were reported as the ease of use, high analysis ability, positive attitude of the company, and demand/satisfaction of the clients. Citation: International Journal of Architectural Computing PubDate: 2024-08-02T08:13:45Z DOI: 10.1177/14780771241270196
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Authors:Elien Vissers-Similon, Theodoros Dounas, Johan De Walsche Abstract: International Journal of Architectural Computing, Ahead of Print. This paper provides a strategic classification of artificial intelligence (AI) techniques based on a systematic literature review and four levels of potential: the levels of input, output, collaboration and creativity. The classification demonstrates the potential and challenges of the AI techniques when used in early stages of architectural design. We aspire to help architects, researchers and developers to choose which AI techniques might be worth pursuing for specific tasks, optimising the use of today’s computational power in architectural design workflows. The results of the classification strongly indicate that Evolutionary Computing, Transformer Models and Graph Machine Learning hold the greatest potential for impact in early architectural design, and thus merit the attention to achieve that potential. Moreover, the classification assists with building multi-technique applications and helps to identify the most suitable AI technique for different circumstances such as the architect’s programming skills, the availability of training data or the nature of the design problem. Citation: International Journal of Architectural Computing PubDate: 2024-07-26T01:33:53Z DOI: 10.1177/14780771241260857
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Authors:Masaaki Matsuoka, Kunihiko Fujiwara Abstract: International Journal of Architectural Computing, Ahead of Print. Designing architectural and urban spaces based on continuous human spatial experience throughout a sequence may lead to architectural and urban forms not bound to conventional concepts. These forms would be made possible through the combination of a quantitative sequential landscape evaluation and morphological optimization utilizing algorithmic processes. In this study, we introduce a method for evaluating sequential landscapes, in which the configuration of buildings, trees, etc., in view changes as pedestrians move along a particular path, using a genetic algorithm optimization of architectural forms to bring them closer to the designer’s ideals. The method’s validity was tested using two case studies, assuming the design of a sequential landscape in an actual city and park. The results present a more efficient, objective, and reproducible method for designing sequences in buildings, cities, and landscapes, compared to traditional methods. Citation: International Journal of Architectural Computing PubDate: 2024-07-22T04:12:41Z DOI: 10.1177/14780771241260851
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Authors:Goncalo Castro Henriques, Andres Martin Passaro, Rodrigo Garcia Alvarado, Luis Felipe González Böhme, Francisco Javier Quitral Zapata, Sergio Araya Abstract: International Journal of Architectural Computing, Ahead of Print. Scientific knowledge, ideally neutral and impartial, is inevitably shaped by geographical, economic, and cultural contexts. This research contends that overcoming the constraints of human and economic scarcity, inertia, and limited funding access demands development of collaborative research networks. To this end, four university laboratories from Brazil and Chile - UFRJ, UBB, UTFSM and UAI - have united to advance robotics applied to architecture. The methodology begins with an analysis of Industry 4.0, Fab Lab implementations, and robotics in architecture in the region. They identify key research aspects by mapping each laboratory’s activities and technologies to pinpoint expertise and potential collaborative areas. The authors propose a summary table comparing the labs and a chronological overview to track regional robotics advancement. To raise awareness among peers, the initiative involves joint actions such as courses, workshops and technical visits. Recognising the scarcity of robotic units and the inapplicability of procedures from wealthier contexts, the authors draw on their lab experience to propose guidelines for implementing robotics research units in academia within the region. This includes technological alternatives, installation considerations, and detailed configuration reviews. The deployment of additional robotic units is a means to foster collaboration and bolster the network. Anticipated outcomes encompass increased critical mass, collaborative research initiatives, faculty and student exchange across institutions, higher publication rates, knowledge acquisition, and improved access to global funding agencies. In summary, the Southern Creative Robotics network initiative aims to catalyse the creative integration of digital manufacturing and robotics technology within design in the Ibero-American context. Citation: International Journal of Architectural Computing PubDate: 2024-07-21T06:27:02Z DOI: 10.1177/14780771241260855
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Authors:Pedro Veloso Abstract: International Journal of Architectural Computing, Ahead of Print. This pedagogical study delves into integrating established and emerging computational methods into architectural education, with a specific focus on building envelope design within a B.Arch. course. Students employ parametric modeling (PM), design optimization (DO), and multimodal large language models (MLLMs) to analyze and reinterpret building envelope precedents. Parametric design and optimization are utilized to explore envelope variations based on parametric logic and performance evaluation. In the case of MLLMs, students leverage visual patterns from precedents as a form-giving construct for new 3D envelope proposals. While students adeptly integrate MLLMs into their design process, generating successful 3D models, challenges arise in control and translation across representations, leading to unclear scale and tectonics in some design proposals. Survey results reveal that students perceive MLLMs as a valuable, uncomplicated method for rapid design ideation and refinement, but challenges persist in addressing real architectural constraints. Parametric modeling is viewed as a tool for structuring design and DO is seen as a later stage for refining designs based on metrics. The study underscores the importance of evolving user interfaces for MLLMs in specific design tasks, addressing challenges in precision and design scale through prompts and guiding images. It also discusses the potential to combine MLLMs with various generative methods and modeling software during transitions between design media to support future initiatives integrating computational methods into the design process. Citation: International Journal of Architectural Computing PubDate: 2024-07-19T11:33:11Z DOI: 10.1177/14780771241254634
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Authors:Umberto Luigi Roncoroni, Veronica Crousse de Vallongue, Octavio Centurion Bolaños Abstract: International Journal of Architectural Computing, Ahead of Print. This article describes generative algorithms and Digital Fabrication techniques with organic materials to create complex 3D objects for industrial design, sculpture, and architecture. Experimental artistic production using these algorithms concluded with a solution based on programmable meshes, which use identifiers to control the topological characteristics of vertices during the modeling process. On the other hand, the hybridization of analog and digital techniques was explored through fabrication. Comparing artistic production and hybrid techniques with generative AI, we will discuss topics of Computational Creativity in art, industrial design, and architecture. The programmable meshes solution, combined with hybrid fabrication processes, enables an incredible variety of complex forms, stimulates artistic creativity, and provides flexible feedback to bypass some Digital Fabrication issues. Our findings also elucidate the importance of original technology development and cultural identity in fostering creative and culturally inclusive technologies for art and education. Citation: International Journal of Architectural Computing PubDate: 2024-06-15T09:18:17Z DOI: 10.1177/14780771241260850
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Authors:İremnur Tokaç, Anne Heimes, Michael Vorländer, Sigrid Brell-Çokcan Abstract: International Journal of Architectural Computing, Ahead of Print. In urban acoustics, the design of built environment substantially impacts the environmental noise of our everyday lives, as the built environment constantly reflects the sounds of human or non-human actors in its vicinity. The effects produced by these reflected sounds significantly depend on the geometric characteristics of the surrounding building façades. Despite their impact, the façade characteristics are often excluded from urban acoustic simulation models. As a result, sound reflection and scattering that are specifically related to building façades remain largely unexplored in noise control at the urban scale. Inspired by computational design tools used for exploring room acoustics, we investigate how a computational approach enables the analysis of geometric characteristics of façades to simulate urban acoustics during early design processes. This paper introduces a rule-based characterisation framework that enables the representation of geometric façade characteristics and their relationships with acoustic constraints in the form of rules. Our first results showed how these rules allowed for capturing and reconstructing façade geometries based on the given acoustic constraints. We believe that this novel approach empowers designers to describe their initial design ideas in a formalism that can be dynamically adapted to various dimensions, such as urban acoustics, and to reconstruct the form throughout the design process. Citation: International Journal of Architectural Computing PubDate: 2024-06-11T03:56:18Z DOI: 10.1177/14780771241260852
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Authors:Eymen Çağatay Bilge, Hakan Yaman Abstract: International Journal of Architectural Computing, Ahead of Print. The aim of this study is to find a building form and plan layout that can be used in the early stages of architectural design, where criteria such as daylight, view, sun-hour, sales area, and cost are optimized according to the different expectations of different housing type users. This study proposes a multi-objective early-stage design optimization for a real estate development project based on the NSGA2 genetic algorithm, considering weighted user preferences for different housing types. The framework is implemented using the platforms Rhino and Grasshopper; Wallacei is used for NSGA2, and Viktor.ai is used to deploy the app. Tested on six sample plots, the model was able to find architecturally optimized results that respond to different user expectations. While the model successfully demonstrated responsiveness to parameters, its focus on Pareto-optimal solutions limited the diversity of unit mixes generated. The model has been tested by professionals on a sample plot and is found to be important for architects and investors to generate ideas at an early stage of architectural design. Citation: International Journal of Architectural Computing PubDate: 2024-06-10T06:49:32Z DOI: 10.1177/14780771241260856
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Authors:Ahmed M. Abuzuraiq, Halil Erhan Abstract: International Journal of Architectural Computing, Ahead of Print. Designers in the built-environment disciplines increasingly solve problems using generative design methods, which promise novel and performant solutions to design problems but produce large design spaces that are challenging to explore. Design Space Exploration (DSE) interfaces have been used to understand, refine and narrow design spaces. Still, a critical analysis of current DSE interfaces shows a gap between their features and how designers explore and make decisions. We conducted a design study with domain experts to develop a DSE interface (DesignSense) that tightly integrates and adds to several features found separately in current DSE systems. We present a formative focus group evaluation, which suggested more areas for improvement and highlighted the need to distinguish designers from scientists as two user groups of DSE systems with varying needs, amongst other findings. Citation: International Journal of Architectural Computing PubDate: 2024-06-10T01:22:02Z DOI: 10.1177/14780771241260854
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Authors:Niloufar Emami Abstract: International Journal of Architectural Computing, Ahead of Print. This paper argues that computational design coupled with additive manufacturing (AM) holds the potential to transform precast façade design and construction. Computational design empowers the creation of intricate façade forms, while AM facilitates their fabrication. In two distinct ways, AM is poised to disrupt precast construction: firstly, through 3D printed formworks (3DPF), and secondly, by employing AM to produce the positive reference pieces for mold making. This paper’s focus lies on the latter method, particularly within an educational context. It reviews a novel pedagogical approach that was implemented in a design studio at Illinois School of Architecture. This pedagogy bridges the past and the future by reinterpreting historical projects and reimagining them using today’s advanced technologies. The incorporation of historic precedents into education implies a practical approach to design thinking, especially in mold design and fabrication. The outcomes highlight the intersection of established construction knowledge with emerging digital fabrication techniques. Citation: International Journal of Architectural Computing PubDate: 2024-06-08T10:03:42Z DOI: 10.1177/14780771241254638
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Authors:Burak Pak Abstract: International Journal of Architectural Computing, Ahead of Print.
Citation: International Journal of Architectural Computing PubDate: 2024-05-24T01:40:43Z DOI: 10.1177/14780771241257717
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Authors:Tilanka Chandrasekera, Zahrasadat Hosseini, Ubhaya Perera Abstract: International Journal of Architectural Computing, Ahead of Print. This study focuses on Generative Artificial Intelligence (AI) and its transformative impact on design ideation. Generative AI, recognized for its ability to produce a wide array of design alternatives, has become an important tool in design, reshaping traditional methodologies. It facilitates the generation of novel and diverse design forms, acting as a co-creator in the design process. This technology, through machine learning and pattern recognition, analyzes extensive design datasets, enabling the production of innovative solutions. The utilization of generative AI extends beyond replicating AI-provided solutions; it aids in developing and influencing novel concepts, thus fostering original design solutions. This aligns with the concept of ‘reflective practice’ in design, where designers iteratively refine concepts through a dialogue between thought and action. The study employed a quasi-experimental design with 40 design students, randomly assigned to two groups of 20 each. Conducted in two phases, each phase involved a distinct urban furniture design task. In Phase 1, Group A was provided with a text-to-image generating AI tool, while Group B was not. In Phase 2, both groups undertook a similar task without AI assistance. This design exercise allowed for examining the influence of AI on creativity and cognitive load. Design outcomes from both tasks were anonymized and evaluated by experienced professionals using the Creative Product Semantic Scale (CPSS), which measures Novelty, Resolution, and Elaboration and Synthesis. Additionally, the NASA Task Load Index (NASA TLX) questionnaire assessed cognitive load aspects such as mental demand and effort. Findings suggest that generative AI significantly influences the creative design process, enhancing the quality of design outcomes and reducing cognitive load. The AI group demonstrated better performance in both tasks, indicating the impact of AI tools on design skills. This study underscores the potential of AI tools in design education, balancing cognitive load management with creativity enhancement. Citation: International Journal of Architectural Computing PubDate: 2024-05-22T09:38:34Z DOI: 10.1177/14780771241254637
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Authors:Arnott Ferels, Aswin Indraprastha Abstract: International Journal of Architectural Computing, Ahead of Print. This paper presents a novel approach to optimizing movement in urban areas through a dynamic multi-layer walkability model. This research uncovers new facets of walkability modeling within transit-oriented movement, aligning pedestrian pathways (Routes) with urban architecture, public spaces, and green spaces (Nodes). The dynamic multi-layer (DML) approach involves optimizing both the Nodes and Routes of the transit system using a multi-objective optimization method. This method improves accessibility and connectivity by aggregating the results of agent-based modeling for route simulations and considers multiple criteria, including greenness, distance to transit, and destination accessibility. Experimentation with a case study produced several findings that underscore the value of multi-layered models for transit movement and the power of computational methods in optimizing both Nodes and Routes. This discovery offers valuable insights into the DML process and its potential applications in the field of urban design and architecture. Citation: International Journal of Architectural Computing PubDate: 2024-05-18T11:29:28Z DOI: 10.1177/14780771241254639
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Authors:Khanh Hoa Thi Vo Abstract: International Journal of Architectural Computing, Ahead of Print. This research offers a pragmatic view on the adoption of Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR) in designing the built environment. Participants from 20 U.S. states and beyond formed a non-probability sample representing small to mid-sized Architecture, Engineering, and Construction (AEC) firms. The author engaged 59 professional participants through a 26-question online questionnaire, informed by existing literature and reviewed by two industry experts. Three additional expert participants provided comprehensive insights via semi-structured interviews. Results highlight design visualization and client presentations as top AR, VR, and MR applications. Key benefits include improved design assessment, early error detection, and heightened client satisfaction. Design collaboration was less prominent than suggested by the literature. Notable challenges persist in first-time user adoption and cost factors of equipment and training. Thus, the cost-benefit balance drives the dominance of older, lower-end devices found in this study despite the availability of advanced, high-fidelity infrastructure. Citation: International Journal of Architectural Computing PubDate: 2024-05-14T03:31:24Z DOI: 10.1177/14780771241254632
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Authors:Stylianos Dritsas, Cheryl Lee Teng Teng, Khystelle Yeo Zi Yi Abstract: International Journal of Architectural Computing, Ahead of Print. This article presents a method for constructing circulatory networks that intrinsically combine geometric, topological, and semantic spatial attributes. The objective of this work is to generate concise graph representations extracted from spatial geometry that may be used for wayfinding and code compliance analyses to inform architectural design and urban planning. Our approach is based on shape analysis using the Medial Axis Transform skeletonization method. We present a process for the semantic classification of its nodes and edges by constructing an analytical rational piece-wise 3D surface representation. This overcomes the problem of identifying salient or otherwise graph features. Furthermore, we augment the networks with peripheral pathways. This addresses the fundamental limitation of skeletal graphs forcing paths exclusively through the middle of space and thus producing unreasonable detours. We demonstrate that our approach encompasses subtle circulatory features and generates concise graphs for open and free-form spaces that do not exhibit corridor-like structures. Citation: International Journal of Architectural Computing PubDate: 2024-05-13T10:24:19Z DOI: 10.1177/14780771241254636
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Authors:Gaëlle Baudoux Abstract: International Journal of Architectural Computing, Ahead of Print. This paper deals with creative co-design between human and machine. It presents an alternative design method based on an emerging technology of sketch interpretation to support co-creation and collaborative creativity in architecture. This technology embraces spontaneity in design by generating inspirational images linked to the architect’s sketches. Our research aims to determine the benefits and challenges of this alternative instrumentation. We are developing a Wizard of Oz test method by immersing several designers in a studio instrumented by this human-machine co-creation technology. We analyze quantitatively and qualitatively the single-designer ideation activity of these subjects. We then investigate the integration of this co-creation instrumentation within the framework of a team design involving several architects. This confirms known benefits such as speeding-up and freeing-up of ideation and highlights the need for designers to evaluate sketched ideas by means of images simulating their real-life rendering, as well as the need for inspiration to materialize the premises of ideas that are still vague. Citation: International Journal of Architectural Computing PubDate: 2024-05-13T07:14:25Z DOI: 10.1177/14780771241253438
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Authors:Alexander Grasser-Parger Abstract: International Journal of Architectural Computing, Ahead of Print. This article explores the intersection of digital architecture, collaborative creativity, and community engagement through our conceptual framework of Collaborative Objects. By enabling a shift from user-generated content to community-generated content in architecture, this new approach promotes democratic design processes. Practical illustrations are provided through a series of public case studies—H = N Co-Doodle, H = N BLOCK, and Meta Block Linz—highlighting the versatility of the Collaborative Objects framework embedded within expanded software applications. These studies address the formal and informal consequences, opportunities, and challenges of transforming static design elements into dynamic, community driven narratives. While recognizing the challenges inherent in this paradigm shift, the article concludes by emphasizing the compelling potential for more shared, inclusive, and community-oriented design processes in the architectural field. Citation: International Journal of Architectural Computing PubDate: 2024-03-05T10:33:56Z DOI: 10.1177/14780771241234450
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Authors:Sverre M Haakonsen, Artur Tomczak, Bunji Izumi, Marcin Luczkowski Abstract: International Journal of Architectural Computing, Ahead of Print. As we strive to improve efficiency and minimise environmental impact in the construction industry, it is important to consider how these objectives impact the work and productivity of designers. This article presents a tool to assist designers in matching reclaimed building products with design intent. The demonstration is based on an actual design project of a two-storey public building made of reclaimed timber from disassembled barns. The algorithm’s objective is to propose optimal matching in terms of a structure’s environmental impact without overloading the user with additional work or excess information. The impact includes emissions embodied in material and related to the transportation from the donor site. The algorithm is integrated into the Grasshopper interface for easier use. All the inputs and objectives are quantitative and fully customisable. The user can still assess qualitative characteristics thanks to a graphical representation of the result. The demonstration shows how automation can simplify the design process with reclaimed elements, support traditional design workflows and enable improvements towards a more sustainable construction industry. Citation: International Journal of Architectural Computing PubDate: 2024-02-27T10:57:02Z DOI: 10.1177/14780771241234447
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Authors:Busra Dilaveroglu Abstract: International Journal of Architectural Computing, Ahead of Print. Architecture has always been a means of communicating stories through its design, with its structures and spaces serving as visual narratives. However, recent advancements in technology have created opportunities for architects to enhance their storytelling capabilities through the use of text-to-image algorithms. These algorithms have the potential to improve visual narratives by enabling architects to translate written descriptions into tangible visual representations. This article explores the architecture of visual narrative and how text-to-image algorithms can enhance it in diverse styles. This inquiry aims to help architectural epistemology understand and foresee the potential impact of this technology on the field of architecture. To understand the limits of AI in generating styles to enhance architectural narrative, six distinct styles were chosen for experimentation. The styles were selected based on their unique features, including an architect’s style, movement, or era. These styles include Zaha Hadid, Brutalist, modern-minimalistic, Peter Zumthor, Gothic, and Gaudi. The narrative was kept the same for each style while observing the changes in AI-generated visuals. The results were evaluated by comparing AI’s interpretations in terms of stylistic, environmental, material, form-based, and atmospheric features. While the results showed promise in terms of variations in each category, AI was not successful in implementing all stylistic features while keeping the narrative stable. In particular, after the second environment layer, the modern-minimalistic, Zumthor, and Brutalist styles lost their distinct features, while Gothic and Gaudi-inspired visuals were hardly generated even in the second environment layer. As a result, AI performed well in generating detailed environmental features without any given narrative and creating an atmospheric environment with enlightening the environment for the last layer. Citation: International Journal of Architectural Computing PubDate: 2024-02-17T04:05:22Z DOI: 10.1177/14780771241234449
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Authors:Carmela Cucuzzella, Morteza Hazbei, Mohammad Hossein Asgari Abstract: International Journal of Architectural Computing, Ahead of Print. Parametric design and gamification rely on quantitative factors that can be easily translated into computer language. However, measuring and quantifying the complex urban qualities poses a challenge. This leads to the question of how to incorporate complex spatial quality into parametric design. This research, therefore, proposes a method to parametrize and quantify urban qualities by extracting main spatial qualities from three main sources, developing a comprehensive list of qualities that can be effectively parametrized, breaking them down into more tangible parameters, and assessing their interrelations within a system model. The results reveal that although urban qualities are complex, they are better defined and parametrized when their relations and originating factors are fully investigated. Furthermore, qualities are classified according to their degree of connection to other qualities within the system model and the nature of these connections. This classification results in six categories: Main Instigator, Mediating and Consequential qualities, as well as Minimally, Moderately, and Highly connected qualities. This research contributes to urban parametric design by providing a method to parametrize urban qualities and gamification fields, allowing developers to implement city complex qualities into the games. Citation: International Journal of Architectural Computing PubDate: 2024-01-22T10:32:02Z DOI: 10.1177/14780771241228095
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Authors:Theodora Vardouli, Maxime Leblanc, Eliza Pertigkiozoglou Abstract: International Journal of Architectural Computing, Ahead of Print. This article elaborates a computationally enabled approach to the study of design methods in 1960s North America. This entails the construction, visualization, and analysis of a digital database built from entries of the Design Methods Group Newsletter, a periodical published monthly between 1966-71. The article proposes a workflow that combines methods such as topic modeling and network visualization to activate the Newsletter as a source of anecdotal and informal knowledge, and to enable histories of connectivity and transaction that may elude archival investigations on singular actors or institutions. In doing so, the article contributes arguments and techniques for the study of design methods as a complex social, technical, and intellectual meshwork. The meshwork brings discursive themes, techniques, actors, and institutions at the same level of investigation and allows for layered cartographies of the field that advanced the systematic study of design and ushered in the development of early computer applications. Citation: International Journal of Architectural Computing PubDate: 2024-01-13T03:01:23Z DOI: 10.1177/14780771231220903
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Authors:Hamidreza Malekian Abstract: International Journal of Architectural Computing, Ahead of Print. This article presents a design proposal for a socially engaging, architecturally dynamic, and adaptable pavilion that fosters interaction among individuals. The pavilion aims to bridge the gap between open and enclosed spaces in university campuses or other cultural settings, maximizing their vibrancy. To achieve this objective, the design incorporates principles of robotics and data-driven analysis to examine the mechanics, form, and modes of interaction of mobile elements, expressed through computer-coded language. The article delves into the design process and highlights key features of the pavilion, emphasizing its adaptability to variable conditions and its capacity to guide and facilitate people’s movements and interactions. Furthermore, it explores the potential of motion within architecture by utilizing mechanics and programmability inspired by the Rubik’s Cube system. The article also provides the technical design of all components and focuses on the Multipurpose Path Planning (MTP) approach as a guiding principle for the RO-BIK project. Citation: International Journal of Architectural Computing PubDate: 2024-01-05T07:25:00Z DOI: 10.1177/14780771231225700
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Authors:Carlos Medel-Vera, Pelayo Vidal-Estévez, Thomas Mädler Abstract: International Journal of Architectural Computing, Ahead of Print. This article discusses an application for classifying urban spaces using convolutional neural networks (CNNs). A seed dataset was initially generated composed of 630 photographs of urban spaces from the Adobe Stock repository. This dataset was topped up with images produced by two generative artificial intelligence (AI) engines, namely, Deep Dream Generator and Midjourney, making two additional augmented datasets, each composed of 2200 images. The training process was carried out using four well-known CNNs, namely, GoogLeNet, ResNet-18, ShuffleNet, and MobileNet-v2. The results show an increase of roughly 30% in the predicting capabilities in both augmented datasets when compared to the seed dataset. Furthermore, performance metrics are generally higher when using ResNet-18 which may suggest that this CNN architecture is more applicable to urban classification projects. Finally, although both generative AI engines have similar performance, Midjourney seems to slightly outperform Deep Dream Generator as a data augmentation engine for urban spaces. Citation: International Journal of Architectural Computing PubDate: 2024-01-03T11:42:54Z DOI: 10.1177/14780771231225697
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Authors:Muhammet ali Heyik, Derya Gulec OZER, Francisco Javier Abarca-Alvarez, José María Romero-Martínez Abstract: International Journal of Architectural Computing, Ahead of Print. This study introduces a collective cartography strategy for analyzing complex urban spaces. It was applied during a 7-day Erasmus + workshop with 46 participants from universities in Spain, Turkey, Portugal, and Poland, representing various backgrounds such as urban planning, architecture, heritage, information technologies, and tourism. The workshop's objective was to identify critical urban issues and generate sustainable and multisensory urban space concepts. The impact of this strategy, from co-sensing to co-ideation, was evaluated by its influence on collaboration and the development of self-generated tactics during the process. Within this context, we explored various group tactics, including multisensor data collection, multi-criteria-based analysis, crowdsourcing for site diagnosis, and distributed collaboration to enhance diverse perspectives and narratives. The findings, outputs, and reflections from participants indicate highly interactive, productive, and inclusive co-creation settings. These were facilitated through a web-based virtual collective space (Doyoucity) and a crowdsourcing mobile app for on-site data collection and analysis (Fulcrum). Citation: International Journal of Architectural Computing PubDate: 2024-01-03T06:19:48Z DOI: 10.1177/14780771231225699
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Authors:Tuba Kocaturk, Stefan Greuter, Thuong Hoang, Rui Wang Abstract: International Journal of Architectural Computing, Ahead of Print. In the realm of architectural evolution, the paradigm of static built environments has progressively shifted towards adaptive, responsive, and intelligent spaces. This paper presents a pioneering government-funded applied research project, the ‘Spatially Intelligent Arts Centre’, which exemplifies the convergence of multiple disciplines in the pursuit of redefining the traditional notion of a static arts centre. This endeavour sought to transform an existing arts centre building into a dynamic and intelligent space, thereby redefining its agency to foster novel user experiences and optimize operational efficiency. The project transcended conventional boundaries by merging the expertise of architects, computer scientists, user experience designers, spatial computing specialists, technology developers, and interface designers. Through transdisciplinary collaboration and adopting a design-thinking methodology, the project not only challenges the conventional limitations of architectural design but also offers a tangible illustration of the burgeoning field of human-building interaction research and practice. This paper details the conceptual underpinnings, technical implementations, and experiential outcomes of the Spatially Intelligent Arts Centre project, underscoring its significance as a model for implementation of human-building interaction in the context of a cultural building. Citation: International Journal of Architectural Computing PubDate: 2024-01-03T05:54:26Z DOI: 10.1177/14780771231225702
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Authors:Stephen Yang, Jonathan Dortheimer, Aaron Sprecher, Qian Yang First page: 216 Abstract: International Journal of Architectural Computing, Ahead of Print. This paper explores the potential of chatbots, powered by large language models, as a tool for fostering community participation in architectural and urban design. By taking a hybrid approach to community participation in a real-world mixed-use building project, in which we integrated remote chatbot engagements with face-to-face workshops, we explored the potential for a hybrid approach to scaling up the reach of participation while ensuring that such participation is meaningful, genuine, and empowering. Our findings suggest that a hybrid approach amplified the strengths and mitigated the shortcomings of the two methods. The chatbot was effective in sustaining the length of participation, broadening the reach of participation, and creating a personalized environment for introspection. Meanwhile, the face-to-face workshops still played a crucial role in bolstering community ties and trust. This research contributes to understanding chatbots’ strengths and weaknesses in participatory processes, both within spatial design and beyond. In addition, it informs future explorations of participatory processes that span different spatial-temporal configurations. Citation: International Journal of Architectural Computing PubDate: 2024-05-30T01:31:27Z DOI: 10.1177/14780771241253440
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