Architectural intelligence最新文献

In the contemporary era of urban design, the advent of big data and digital technologies has ushered in innovative approaches to exploring urban spaces. This study focuses on the application of Augmented Reality (AR) and Extended Reality (XR) technologies in the metropolitan areas of Houston and Amsterdam. These technologies create immersive 'Phygital Installations' that blend physical and digital elements, effectively capturing people's perceptions and enhancing urban design proposals. By fostering human-centered planning, AR and XR technologies make urban design more interactive and accessible to the public. Houston, with its rapid industrial growth and diverse socio-economic landscape, provides a unique setting to examine the impacts of these technologies on urban form and socio-environmental dynamics. In contrast, Amsterdam, with its rich historical layers and socio-cultural diversity, offers insights into the integration of AR/XR technologies in urban planning, particularly in the realm of historical preservation and contemporary urban development. This research contributes to the emerging field of AR/XR in urban design by highlighting the transformative potential of these technologies in enhancing the understanding and engagement in urban design and spatial planning.

This article proposes using scaled fabrication models to assist the design research of 3D-printed discrete concrete structures where full-scale fabrication tests are costly and time-consuming. A scaled fabrication model (SFM) is a scaled model 3D-printed the same way as in actual construction to reflect its fabrication details and acquire alike layer line textures. The components of a 1:10 SFM can be easily produced by consumer-level desktop 3D printers with minimal modification. SFMs assist the design communication and make possible quick tests of distinct fabrication designs that are hard to assess in digital modeling during the conceptual design phase. A case study of a discrete compression-dominant funicular floor derived from graphic statics is presented to illustrate the contribution of SFM to the design research of force-informed toolpathing where the printing direction of a component is aligned to the principal stress line. The design iterations encompass a sequence of component, partial, and full model SFM printing tests to explore and optimize the fabrication schemes where parallel, non-parallel, and creased slicing methods to create toolpaths are compared and chosen to adapt different discrete components.

The energy consumption during the operation and maintenance phase of buildings is huge. As the built-up area in China increases, the demand for energy conservation in existing buildings has become a key focus of its dual carbon policy. Intelligent operation and maintenance based on digital twins is an emerging means to reduce carbon emissions from buildings, but it faces some problems in the process of promotion. Complete digital and intelligent transformation requires significant investment and has certain requirements for project parties and operation and maintenance teams. Small businesses or individual households have relatively simple requirements for intelligent operation and maintenance scenarios and do not require complete digital twins. To address the above issues, this article uses an affordable universal digital twin framework to provide a digital solution for intelligent operation and maintenance of existing buildings. This solution allows networking communication between devices and uses IoT modules to monitor and control the environment. This digital twinning model can reduce the measurement and control of energy-consuming end devices without on-site transformation and has rich scalability. This article uses the solution to deploy an office at a university in Henan Province and specifically measures the power consumption of displays, indoor environment, and air conditioning. According to the needs, it expands the space occupation, fans, air handlers, lights, and other end devices of the digital twin. The digital twin accurately presents the energy consumption of the office during extreme weather conditions, which has an auxiliary role in promoting digital twins in the region and optimizing energy consumption in existing buildings.

Thermal comfort of indoor occupants exposed to solar radiation is receiving widespread attention. Researchers have proposed many models to predict solar radiation and related indexes are used to evaluate thermal comfort. However, there are some limitations in the existing solar radiation models and evaluation indexes, such as only applying to sunny weather and requiring intensive modeling work. This study adopts a mathematical model called the improved HNU Solar Model and proposes a new evaluation index called the annual thermal discomfort time ratio by solar radiation (ratio_{td, solar}) to evaluate thermal comfort of indoor occupants exposed to solar radiation. The effects of different window parameters, i.e. window direction, window transmittance (T_sol) and window-to-wall ratio (WWR) on ratio_{td, solar} were also analyzed. The results show that the indoor area less than 2.0 m away from the window is easy to have solar discomfort. And for every 0.1 reduction in WWR, the average values of the four directions are reduced by 3% to 4%; and for every 0.1 reduction in T_sol, the ratio_{td, solar} values of four window directions are reduced by 4% to 6%. This study provides references for evaluating and optimizing the window design to create thermally comfortable environments for indoor occupants.

Recent development of powder-bed additive manufacturing promises to enable the production of architectural structures that combine high resolution and articulation with economies of scale. These capabilities can potentially be used for functionally graded metamaterials as part of the building envelope and structure, paving the way for new functionalities and performances. However, designing such multifunctional structures requires new design and modelling strategies to control, understand, and generate complex geometries and their transcalar interdependencies. The work presented here demonstrates a modeling framework that can unite multiple generative and organizational algorithms to create a unified, 3D printable building element that integrates a range of functional requirements. Our methods are based on an understanding of stigmergic principles for self-organization and developed to allow for a wide range of application scenarios and design intents. The framework is structured around a composite modeling environment based on a combination of volumetric modeling and particle-spring systems, and is developed to negotiate the large scalar range necessary for such applications. We present here a prototype demonstrator designed using this framework: Meristem Wall, a functionally integrated building envelope fabricated through a combination of powder bed 3D printing and CNC knitting.

The paper seeks to investigate novel potentials for building design and structure generation that arise at the intersection of computational design and AI-generated 3D geometries. Although the use of AI technologies is exponentially increasing inside the architectural discipline, the design of spatial building configurations using AI-generated 3D geometries is still limited in its applications and represents an ongoing field of investigation in advanced architectural research. In this regard, several questions still need to be answered: how can we design new building typologies from AI-generated 3D geometries? And how can we use these typologies to shape both the real and the virtual world?

The paper proposes a new approach to architectural design where artificial intelligence is used as the starting point for design exploration, while computational design procedures are employed to convert AI-generated 3D geometries into building elements – such as columns, beams, horizontal and vertical surfaces. The paper starts with a general overview of the current use of artificial intelligence inside the architectural discipline, and then it moves towards the explanation of specific AI generative models for 3D geometry reconstruction and representation. Subsequently, the proposed working pipeline is analysed in more detail – from the creation of 3D geometries using generative AI models to the conversion of such geometries into building elements that can be further designed and optimised using computational design tools and methods. The results shown in the paper are achieved using Shap-E as the main AI model, though the proposed pipeline can be implemented with multiple AI models. The paper ends by showing some of the generated results, finally adding some considerations to the relationship between human and artificial creativity inside the architectural discipline.

The work presented in the paper suggests that the use of computational design tools and methods combined with the tectonics of the latent space opens new opportunities for topological and typological explorations. In a time where traditional architectural typologies are moving towards stagnation due to their inability to satisfy new human needs and ways of living, exploring AI-based working pipelines related to architectural design allows the definition of new design solutions for the generation of new architectural spaces. In doing so, the serendipitous aspect of AI biases is used as an auxiliary force to inform design decisions, promoting the discovery of a new inbuilt dynamism between human and artificial creativity. In a time where AI is everywhere, understanding the measure of such dynamism represents a key aspect for the future of the architectural discipline.

Accurately predicting homeowners’ aesthetic preferences is crucial in interior design. This study develops a fine-tuning model (LORA) for interior design styles corresponding to different MBTI personality types, leveraging the Stable Diffusion Web UI platform and integrating it into a generative artificial intelligence framework. Subsequently, personalized aesthetic preference architectural interior renderings are recommended based on homeowners’ personality traits, aiming to achieve an adaptive interior design approach. To achieve more precise adaptive solutions, this research surveys the style and color tendencies of respondents with different MBTI personality types and adds style description prompts to assist in image generation. The study finds that this method can better predict the interior design styles favored by certain MBTI personality types. This research contributes to addressing aesthetic biases between designers and homeowners, bringing innovative ideas and methods to interior design, and is expected to enhance homeowners’ satisfaction.

The research investigates the topological optimisation of the metal brackets that connect curtain wall panelling to the floor slabs of a building. As is typically the case with standard building components, the brackets are overdesigned with higher load margins than real applied loads. Optimising them results in reduced mass and a more evenly spread stress distribution. Correspondingly, the question that the project asks is whether the optimised designs have a comparable structural performance to the standard bracketry used in construction, and a lower embodied carbon. To answer this, several optimisations of a standard facade bracket are performed, resulting in a total of six converged design options, with three of them progressed for fabrication. The manufactured designs are then horizontal and vertical load and residual stress tested to assess their performance, and an embodied carbon analysis is performed to calculate the corresponding emissions for raw material extraction, processing, and component fabrication. The results indicate the presence of compressive yield magnitude residual stresses, and that structural performance is comparable to a standard bracket, but embodied carbon is in most cases higher. The paper concludes with a discussion of the findings, and possible next steps in the optimisation, structural testing, and embodied carbon analysis workflow.

Ruffled surfaces that appear in biological forms, such as coral and lettuce, are a great source of inspiration for architectural and furniture design. This paper proposes a mechanism based on a bending-active scissors grid that effectively reproduces the process of differential growth. The structure can deploy from a linearly folded state with rotational symmetry to a complex ruffled surface without rotational symmetry. The deployed shape further exhibits a wave-like motion similar to the swimming gait of flatworms or cuttlefish. First, we propose a design method for the mechanism computed from the surface of constant negative Gaussian curvature. We then numerically analyze the symmetry-breaking process of deployment and zero-stiffness wave-like motion after deployment. We built two demonstrators to verify the deployment and the transformation. The first demonstrator with 1.5m diameter was fabricated to verify the symmetry-breaking deployment motion. The second demonstrator with 0.9m diameter was fabricated to demonstrate the wave-like motion by controlled pulling of the group of threads.