Architectural intelligence最新文献

Thermostatically controlled load (TCL) contributes a relatively higher proportion of energy consumption. Its mathematical models can be used for quantifying the real-time supply and demand balance between the power generations and load systems. The relevant studies have received great attention with the development of smart grids in recent years. This study mainly presented the development of TCL mathematical models from a single model to aggregated models. Finally, the advantages of these models were compared and analyzed based on the simulation results. This study could provide a theoretical basis for the applications of TCLs in the supply and demand balances.

Given the increasing interest in offsite construction and the prefabricated components it produces, this paper aims to establish a common matrix, the PreDI, for the offsite construction industry. The effort is to enhance the comparability of research and practices in offsite construction, making it more universally understood. Offsite construction involves manufacturing components in a factory and then assembling them on-site. It is considered a more sustainable approach due to less material usage, energy consumption, and waste generation during component fabrication. However, the lack of common terminology for offsite construction poses many challenges in the industry and its research, hindering communication and research.

The Prefabricated Dimensions and Integrations (PreDI) matrix, developed in the study, provides a solution for industry and research use. Thus, industry and academia can utilize the PreDI widely, accurately, and precisely in communication. This paper demonstrates the PreDI matrix’s application in life cycle assessment research on offsite construction, showcasing its utility and setting the stage for more robust research analyses in the future. Using the PreDI matrix in 24 U.S. Department of Energy Solar Decathlon houses further highlights its potential in the industry. Finally, the paper concludes with a broader outlook on its impacts on offsite construction.

This paper illustrates the design and fabrication processes of the Hypar Up pavilion, which served as a proof-of-concept to demonstrate the viability of a design-to-fabrication workflow for complex yet modular architectural geometries that utilise small and planar timber offcuts geometries discretised as Planar Quadrilateral (PQ) meshes. By integrating computational design and optimisation with efficient manufacturing processes, this research highlights the technical challenges of repurposing materials with unknown characteristics, notably detailing solutions, and evaluates the efficiency of design-to-manufacturing workflows with surplus timber products, using a quantitative cost analysis of the fabrication and assembly phases. While exploring the potential of repurposing scrap wood into hypar-shaped modular construction components, this work expands on existing research on segmented shells and investigates methods and means to move beyond the use of shell structures as monolithic and static artefacts. The pavilion is intended as a 1:1 modular prototype that can be resized to accommodate different dimensions of the timber panel offcuts and potential applications to be tested in future applications, such as load-bearing walls and facade retrofitting.

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.