Dynamic Virtual Infrastructure Benchmarking (DynaVIBe)

Funding:FWF - Der Wissenschaftsfonds

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Project partners: -
Project staff: Robert SITZENFREI, Michael MAIR
Project duration: 04/2011 – 08/2014

Scientific topics:

70% 201 Construction Engineering
20% 102 Computer Sciences
10% 211 Other Technical Sciences



The analyses of case studies are a well-known instrument to identify problems and interactions of processes. In the field of urban water management the methodology is suited to evaluate new technologies, strategies or measures. However, data availability is limited and hence, new technologies, strategies or measures can only be tested on a limited number of case studies. The expenditure of time to build a detailed model of the water infrastructure of a midsize city can be quantified with several man-months. Moreover the results determined by the case studies are limited to specific boundary conditions and system properties and can hardly be generalized or transferred onto other boundary conditions. In line with the project “DynaVIBe” the Unit of Environmental Engineering (IUT) at the University of Innsbruck developed a tool for an algorithmic generation of virtual case studies for water supply and urban drainage systems including whole urban structures. Beside the generation and simulation of infrastructure systems on a spatial scale, also the temporal dimension within all simulations was established. Thus, it is possible to map the dynamics of urban water infrastructures into computing models and simulations. The implementation of the developed methods and algorithms is realized within the open source software “DynaMind”. The strength of the algorithms is the flexibility to use input data at different level of details. Virtual case studies can be generated by using only few input parameters up to using detailed data sets (generating semi-virtual case studies). The usage of input data sets with different levels of detail can explicitly control the validity of model simulation results so that various research questions in the field of urban water management can be investigated. Due to the high flexibility of the generation algorithms also surrogate data can be used as input. This approach was applied on street network data sets which are of good quality and free accessible (e.g. OpenStreetMap). Further, the history of an urban infrastructure network can be recreated by extracting street network data out of historical orthophotos. It was proved that the DynaVIBe approach is also capable to be applied on real case studies for finding optimal mechanisms for developing and controlling urban water infrastructure systems.


Publications and conferences:


  • Cities of the Future - Sustainable Urban Planning and Water Management, Stockholm, 2011 
    Modelling Adaptation Strategies for Urban Drainage Systems in the context of Dynamic Urban Environments.


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