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  Subjects -> ARCHITECTURE (Total: 219 journals)
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Spool
Number of Followers: 1  

  This is an Open Access Journal Open Access journal
ISSN (Print) 2215-0897 - ISSN (Online) 2215-0900
Published by TU Delft Homepage  [7 journals]
  • Interdisciplinary Data-integrated Approaches

    • Authors: Michael Hensel, Henriette Bier
      Pages: 3 - 4
      Abstract: Rapid urbanization with the associated land cover and land use change, as well as resource depletion, contribute to the degradation of ecosystems and biodiversity and have a negative impact on human health and well-being. Societal calls for responses and results pose a significant challenge for research and education in the various fields concerned with the environment. Alongside the current environmental crisis there is a pressing need for developing ‘green solutions’ for the built environment with the help of data-driven methods, workflows and tools. In view these developments, a shift from narrow disciplinary and domain-specific approaches towards broader interdisciplinary, multi-domain and multi-scalar strategies is required. This includes data-acquisition, data-sharing and data-integration, as well as data-driven modelling to enable the complexity of sustainability problems arising from rapid urbanization to be tackled. While there have been efforts to address the challenges of multi-domain approaches, for instance in the fields of sustainability, the urban and architectural sciences, as well as the interoperability of methods and tools, the actual problem goes deeper, requiring interdisciplinary knowledge exchange to develop adequate shared paradigms, concepts, methods and tools.  Cyber-physical Architecture (CpA) issue 5 addresses these challenges by engaging with experts from a range of disciplines involved in environmental concerns while utilizing data-acquisition, data-sharing and integration, and data-driven modelling in a discourse that identifies modalities for a broader interdisciplinary, multi-domain and multi-scalar approach.
      PubDate: 2022-05-28
      DOI: 10.47982/spool.2022.1.00
      Issue No: Vol. 9, No. 1 (2022)
       
  • ‘Greening’ the Cities

    • Authors: Sinéad Nicholson, Marika Tomasi, Daniele Belleri, Carlo Ratti, Marialena Nikolopoulou
      Pages: 5 - 18
      Abstract: We are facing an urgent global environmental crisis that requires a reframing of traditional professional and conceptual boundaries within the urban environment. Complex and multidisciplinary issues need complex and multidisciplinary solutions, which result from the collaboration of many different disciplines concerned with the urban environment. A more integrated ecological perspective that recognizes the complexity of urban environments and resituates our ‘artificial’ or human-made world within its natural ecosystem can facilitate this shift towards greater knowledge exchange. C40 Cities case studies provide a framework within which to understand the disciplines and scales encompassed by ecological solutions, while projects at MIT Senseable City Lab and CRA-Carlo Ratti Associati highlight how data is used as a tool in driving ecological solutions.  The artificial world of sensors, data and networks creates a bridge between the ‘artificial’ and ‘natural’ elements of our urban environments, allowing us to fully understand the present condition, connect city users and decision makers, and better integrate ecological solutions into the built environment.
      PubDate: 2022-05-27
      DOI: 10.47982/spool.2022.1.01
      Issue No: Vol. 9, No. 1 (2022)
       
  • Data-driven design for Architecture and Environment Integration

    • Authors: Defne Sunguroğlu Hensel, Jakub Tyc, Michael Hensel
      Pages: 19 - 34
      Abstract: Rapid urbanization and related land cover and land use changes are primary causes of climate change, and of environmental and ecosystem degradation. Sustainability problems are becoming increasingly complex due to these developments. At the same time vast amounts of data on urbanization, construction and resulting environmental conditions are being generated. Yet it is hardly possible to gain insights for sustainable plan-ning and design at the same rate as data is generated. Moreover, the complexity of compound sustainability problems requires interdisciplinary approaches that address multiple knowledge fields, multiple dynamics and multiple spatial, temporal and functional scales. This raises a question regarding methods and tools available to planners and architects for tackling these complex issues. To address this problem we are developing an interdisciplinary approach, computational framework and related workflows for multi-domain and trans-scalar modelling that integrate planning and design scales. For this article two lines of research were selected. The first focuses on understanding environments for the purpose of discovering, recovering and adapting land knowledge to different conditions and contexts. This entails an analytical data-integrated computational workflow. The second line of research focuses on designing environments and developing an approach and computational workflow for data-integrated planning and design. These two lines converge in a combined analytical and generative data-integrated computational workflow. This combined approach aims for an intense integration of architectures and environments that we call embedded architectures. In this article we discuss the two lines of research, their convergence, and further research questions.
      PubDate: 2022-05-27
      DOI: 10.47982/spool.2022.1.02
      Issue No: Vol. 9, No. 1 (2022)
       
  • Data-driven Urban Design

    • Authors: Jeroen van Ameijde
      Pages: 35 - 48
      Abstract: Nicholas Negroponte and MIT’s Architecture Machine Group speculated in the 1970s about computational processes that were open to participation, incorporating end-user preferences and democratizing urban design. Today’s ‘smart city’ technologies, using the monitoring of people’s movement and activity patterns to offer more effective and responsive services, might seem like contemporary interpretations of Negroponte’s vision, yet many of the collectors of user information are disconnected from urban policy making. This article presents a series of theoretical and procedural experiments conducted through academic research and teaching, developing user-driven generative design processes in the spirit of ‘The Architecture Machine’. It explores how new computational tools for site analysis and monitoring can enable data-driven urban place studies, and how these can be connected to generative strategies for public spaces and environments at various scales. By breaking down these processes into separate components of gathering, analysing, translating and implementing data, and conceptualizing them in relation to urban theory, it is shown how data-driven urban design processes can be conceived as an open-ended toolkit to achieve various types of user-driven outcomes. It is argued that architects and urban designers are uniquely situated to reflect on the benefits and value systems that control data-driven processes, and should deploy these to deliver more resilient, liveable and participatory urban spaces.
      PubDate: 2022-05-27
      DOI: 10.47982/spool.2022.1.03
      Issue No: Vol. 9, No. 1 (2022)
       
  • Bio-Cyber-Physical ‘Planetoids’ for Repopulating Residual
           Spaces

    • Authors: Pierre Oskam, Henriette Bier, Hamed Alavi
      Pages: 49 - 55
      Abstract: Minimal interventions that provide various microclimates can stimulate both biodiversity and social accessibility of leftover spaces. New habitats are often developed for different animal and plant species based on studies of the microclimates typical of such residual spaces. By introducing interventions of 0.5-1.0 m diameter ‘planetoids’ placed at various locations, existing and new life is supported. The ‘planetoid’ described in this paper is prototyped by means of Design-to-Robotic-Production and -Operation (D2RP&O). This implies that it is not only produced by robotic means, but that it contains sensor-actuator mechanisms that allow humans to interact with them by establishing a bio-cyber-physical feedback loop.
      PubDate: 2022-05-27
      DOI: 10.47982/spool.2022.1.04
      Issue No: Vol. 9, No. 1 (2022)
       
  • Indoor Air Quality Forecast in Shared Spaces– Predictive Models and
           Adaptive Design Proposals

    • Authors: Hamed Alavi, Sailin Zhong, Denis Lalanne
      Pages: 57 - 63
      Abstract: The high concentration of air pollutants in indoor environments can have a remarkable adverse impact on health and well-being, cognitive performance and productivity. Indoor air pollutants are especially problematic in naturally ventilated shared spaces such as classrooms and meeting rooms, where human-generated pollutants can rise rapidly. When the inhabitants are exposed to indoor air pollution, recovering from its ramifications takes time and harms their well-being in the long run. In our approach, we seek to predict and prevent such hazardous situations instead of rectifying them after they happen. The prediction and prevention are accomplished through algorithms that can learn from the evolution of air pollutants and other variables to indicate whether or not a high level of pollution is forecast. We present two AI-enabled methods, one providing the forecast for the concentration level of carbon dioxide in the next 5 and 20 minutes with 86% and 92% accuracy. The second algorithm provides predictive indicators about how the CO2 level will evolve during the upcoming session (meeting or a course) before the session starts. We will discuss design implications and present design proposals on how these methods can inform interactive solutions for preventing high concentrations of indoor air pollutants.
      PubDate: 2022-05-27
      DOI: 10.47982/spool.2022.1.05
      Issue No: Vol. 9, No. 1 (2022)
       
 
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