EPIFLOW: Adaptive Analytical Design Framework for Resilient Urban Water Systems

Modelling Behaviour(2015)

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摘要
In a time when digital tools outpace design methods, we see an increasing obligation to provide empirical support for a historically qualitatively-oriented design profession. This condition necessitates a research framework that facilitates a more comprehensive assessment of both context condition and design effect; one that integrates a comprehensive predictive system that allows us to test various scenarios against systemic performance criteria. Motivated by extensive discourse on health and environmental stability surrounding urban hydrologic systems, and the implication of uninformed design in the propagation of health and environmental stability, EpiFlow tooling proposes a new way of incorporating consequences of hydrological processes into the early stages of design process. By utilizing computation and visual scripting as a means of embedding information into the modeling environment, EpiFlow integrates storm water runoff and water management models directly into the 3d modeling test-bed. The intention is to assimilate direct visual and quantitative feedback on water flow behavior within a single interface, and to provide rapid design feedback that would enable integration of natural systems into holistic design thinking while engaging larger systemic issues of the site. Currently, the algorithms utilized within EpiFlow mainly address urban storm water runoff and household waste water systems. These two systems, already addressed within the architectural discipline by standardized metrics, are essential for such analysis, and historically have been central to issues of pollution, health dangers, resource waste, and environmental degradation. This paper explains the EpiFlow tool and workflow, as well as explores its implications on design process within an academic setting.
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关键词
Water flow,Design methods,Design process,Workflow,Green infrastructure,Conceptual framework,Environmental degradation,Empirical research,Risk analysis (engineering),Environmental resource management,Computer science
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