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PROCEEDINGS OF THE SEVENTH INTERNATIONAL CONFERENCE ON ENGINEERING COMPUTATIONAL TECHNOLOGY
Edited by: B.H.V. Topping, J.M. Adam, F.J. Pallarés, R. Bru and M.L. Romero
Spatial Enrichment by Applying Hierarchy to Built Infrastructure
V. Varduhn, J. Frisch, R.-P. Mundani and E. Rank
Computation in Engineering, Technische Universität München, Germany
V. Varduhn, J. Frisch, R.-P. Mundani, E. Rank, "Spatial Enrichment by Applying Hierarchy to Built Infrastructure", in B.H.V. Topping, J.M. Adam, F.J. Pallarés, R. Bru, M.L. Romero, (Editors), "Proceedings of the Seventh International Conference on Engineering Computational Technology", Civil-Comp Press, Stirlingshire, UK, Paper 78, 2010. doi:10.4203/ccp.94.78
Keywords: spatial augmentation, built infrastructure, industry foundation classes, hierarchical data structures, computational steering, parallel computing, visibility analysis, proximity analysis.
Today, the need for digital information from built infrastructure is dominating many tasks within civil engineering such as planning or maintenance and it is still growing rapidly. In many cases the entirety of this information is not (cross-)linked over domains or scales, and, thus, prevents a better insight and deeper understanding of the underlying data to be gained. To provide the advantage of hierarchical ordered information, the data has to be dealt with data existing at different scales and models respecting the amount of data and their structure, which requires the application of an appropriate hierarchy and use of elaborate techniques.
In this paper, we present an approach for the hierarchical organisation of varying information such as textured height maps for terrain visualisation  or built infrastructure using industry-foundation-classes (IFC)  providing geometric and auxiliary information at a fully detailed level. The objective is to enhance the gain of insight to the user by fusing and exploiting these diverse data. Such an aggregation is the basis for arbitrary queries, for example the embedding of graph theory to building information modelling, and enables the separation of certain information from an unnecessary overhead.
In our approach, we apply a hierarchical data structure by using octrees in order to bridge the gap between different models and varying scales of information. This hierarchy, once established, provides an efficient tool for handling varieties of information and evaluating global specific values necessary for the orchestration of the models such as neighbouring relations between objects or calculating characteristics such as the total amount of floor space in a whole borough. By doing so, we overcome the obstacle of (distributed) information being separated or only weakly associated and therefore to receive meta-information which in that form is not available within the single data sources.
As example, we show that the coupling of a thermal comfort assessment analysis using octrees for a zonal model approach or a computational fluid dynamics simulation. Thermal comfort is defined and the coupling procedures are described in detail as well as underlined by results of such a computation.
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