Architectural intelligence最新文献

Situated in the field of architectural biodesign, InterspeciesForms explores a closer relationship between the fungus Pleurotus ostreatus and the designer in the creation of form. The intention of hybridizing mycelia’s agency of growth with architectural design aesthetic, is to generate novel, non- indexical crossbred designed outcomes. The purpose of this research to advance architecture's existing relationship with the biological and evolve preconceived notions of form. In order to establish a direct dialogue between architectural and mycelia agencies, robotic feedback systems are implemented to extract data from the physical realm and feed it into the digital. Initiating this cyclic feedback system, mycelia growth is scanned in order to computationally visualize its entangled network and agency of growth. Utilizing mycelia’s physical data as impute, the architect then embeds design intention into this process through customized algorithms based on the logic of stigmergy. In order to bring this cross-bred computational outcome back into the physical realm, form is 3D printed with a customized mixture of mycelium and agricultural waste. Once the geometry has been extruded, the robot patiently waits for the mycelia to grow and react to the organic 3D- printed compound. The architect then responds with a countermove, by scanning this new growth and continuing the cyclic feedback system between nature-machine and the architect. This procedure demonstrates form emerging in real time according to the co-creational design process and dynamic dialogue between architectural and mycelia agencies.

Under the influence of globalization, the transformation of traditional architectural space is vital to the growth of local architecture. As an important spatial element of traditional gardens, Taihu stone has the image qualities of being “thin, wrinkled, leaky and transparent” The “transparency” and “ leaky” of Taihu stone reflect the connectivity and irregularity of Taihu stone’s holes, which are consistent with the contemporary architectural design concepts of fluid space and transparency. Nonetheless, relatively few theoretical studies have been conducted on the spatial analysis and design transformation of Taihu stone. Using machine learning, we attempt to extract the three-dimensional spatial variation pattern of Taihu stone in this paper. This study extracts 3D spatial features for experiments using artificial neural networks (ANN) and generative adversarial networks (GAN). In order to extract 3D spatial variation patterns, the machine learning model learns the variation patterns between adjacent sections. The trained machine learning model is capable of generating a series of spatial sections with the spatial variation pattern of the Taihu stone. The purpose of the experimental results is to compare the performance of various machine learning models for 3D space learning in order to identify a model with superior performance. This paper also presents a novel concept for machine learning to master continuous 3D spatial features.

This article introduces introduces a new prefabricated and assembled steel structure system and its key construction technologies for repeated switching scenes in existing stadiums. This steel structure system follows the DfD design method, minimizing the volume of each group of structural member units and separating the connection interfaces between members. In order to improve the construction and assembly efficiency of all the structural components, this study establishes an assembly-oriented BIM model data system by adding customized attributes in the family library in Autodesk REVIT. By associating model attributes with on-site monitoring data of the construction process, this research realizes real-time acquisition and display of construction data of all components during the whole life cycle. At the same time, aiming at the requirements of high-precision positioning and digital dynamic monitoring in future on-site construction, this research proposes an innovative construction positioning monitoring method which combines motion capture system with traditional construction monitoring technology. By correcting the positioning data of motion capture system with traditional construction monitoring data, real-time dynamic monitoring of several monitoring points in a 12*15 m large site is realized and the measurement error is controlled within ±1 mm. This study takes the construction project of “ice-water conversion” from the main swimming pool of the National Swimming Center in the Summer Olympic Games to the curling venue of the Winter Olympic Games as an example to show the important role of relevant technology to improve the construction efficiency in the construction application for the renovation of existing Olympic venues.

Operating with an abundance mindset – rather than from a place of “scarcity” – is a new paradigm, relevant to the practices of design and construction, which expands the definition of “resources” as well as where resources, both raw and non-raw materials, can be found and “mined”.

Within three scales of design and planning, the current research – developed at the Institute for Advanced Architecture of Catalonia (IAAC) – examines the applications of computational technologies and life cycle assessment with the goal of setting up protocols for enhancing processes of urban mining and material reuse in future circular construction. In the material scale (i), selected projects experiment with up-cycled waste for the creation of new engineered composites for construction. In the building scale (ii), robotic technologies and computer vision are used to scan and sort the materials from existing buildings or demolition sites. Finally, in the urban scale (iii), google images, satellite data and ML are used to index the existing material stock in building façades in cities.

The research calls for agents involved in design, planning and construction to shift their focus to the anthroposphere as a source of, rather than just a destination for, processed goods. The concept of “urban mining” is revisited to manage the material stock in urban systems and the use of anthropogenic resources in new production cycles.

Through a multi-scalar approach, the outcome challenges the foundation of our material practices, presenting the potential to disrupt linear patterns of design and making in the built environment.

The chapter addresses the topic of architectural intelligence whose sole purpose is to create affordances and make experience ‘stand on its own’, apart from architecture and distinct from the architect. The principles of sensation constitute the principles of composition of an existential niche whose structure reveals the genetic conditions of real experience. The argument is unpacked across three sections by reference to the Simondonian concept of allagmatics defined as the theory of operations. The first section ‘Ticks and Cats’ argues in favour of inserting an interval between the input and output, with the aim of debunking the mechanicist allegiance to linearity and promoting the concept of quasi-causality. In the second section ‘Ducks and Rabbits’ the affordance theory meets contemporary neurosciences to revamp the concept of metastability and plasticity. Its goal is to reframe the subject as the effect of (architectural) affect. The concluding radical empiricist section ‘Zebras and Flies’ revisits the lesson of the Leibnizian Monadology to tie sense to sensibility and matter to manner. The overall ambition of the chapter is to contest the philosophy of representation through the concept of difference and multiplicity.

The formation of urban districts and the appeal of densely populated areas reflect a spatial equilibrium in which workers migrate to locations with greater urban vitality but diminished environmental qualities. However, the pandemic and associated health concerns have accelerated remote and hybrid work modes, altered people's sense of place and appreciation of urban density, and transformed perceptions of desirable places to live and work. This study presents a systematic method for evaluating the trade-offs between perceived urban environmental qualities and urban amenities by analysing post-pandemic urban residence preferences. By evaluating neighbourhood Street View Imagery (SVI) and urban amenity data, such as park sizes, the study collects subjective opinions from surveys on two working conditions (work-from-office or from-home). On this basis, several Machine Learning (ML) models were trained to predict the preference scores for both work modes. In light of the complexity of work-from-home preferences, the results demonstrate that the method predicts work-from-office scores with greater precision. In the post-pandemic era, the research aims to shed light on the development of a valuable instrument for driving and evaluating urban design strategies based on the potential self-organisation of work-life patterns and social profiles in designated neighbourhoods.

Porous urban spaces not only improve interactions, but also increase natural ventilation. Weathered rocks are where porous spaces exist in nature. This paper investigates the biomimicry of tafoni, a type of weathered rock that contains pores of varying sizes. The formation of tafoni inspires architectural design, but its complex shape makes manual modeling challenging. The objective of studying the biomimetics of tafoni is to apply its benefits to design applications. Using biomimetic techniques, computation algorithms for tafoni morphogenesis are developed. This paper investigates the inherent characteristics of tafoni and reclassifies them based on architectural geometric elements. It then describes the reclassified tafoni and explains the formation process. This paper develops a 3D evolutionary algorithm and a 2.5D descriptive algorithm based on diagrams. After a comparison, the 2.5D algorithm is chosen because it is more controllable and operable for computational design. This paper also conducts experiments on the results obtained by the 2.5D algorithm to demonstrate its adaptability and architectural design application potential, as well as its application schemes in various design disciplines, including urban planning, architectural design, and landscape design. This paper proposes an algorithm that can be utilized in various fields of computational design. It is computationally efficient while retaining its biological form.

In the field of digital design, a recent hot topic is the study of the interaction between spatial environment design and human factors. Electroencephalogram (EEG) and eye tracking can be used as quantitative analysis methods for architectural space evaluation; however, conclusions from existing studies on improving the quality of spatial environments based on human factors tend to remain qualitative. In order to realise the quantitative optimisation design of spatial elements from human physiological data, this research used the digital space optimisation method and perceptual evaluation research. In this way, it established an optimisation method for built space elements in real-time using human psychological indicators. Firstly, this method used the specific indicators of the Meditation value and Attention value in the human EEG signal, taking the ThinkGear AM (TGAM) module as the optimisation objective, the architectural space colour and the window size as the optimisation object, and the multi-objective genetic algorithm as the optimisation tool. Secondly, this research combined virtual reality scenarios and parametric linkage models to realise this optimisation method to establish a tool platform and workflow. Thirdly, this study took the optimisation of a typical living space as an example and recruited 50 volunteers to participate in an optimisation experiment. The results indicated that with the iterative optimisation of the multi-objective genetic algorithm, the specific EEG index decreases significantly and the standard deviation of the in-dex fluctuates and decreases during the iterative process, which further indicates that the optimisation method established in this study with the specific EEG index as the optimisation objective is effective and feasible. In addition, this study laid the foundation for more EEG indicators and more complex spatial element opti-misation research in the future.