ABSTRACT
Automated quantity take-off from digital models in road projects has many benefits. In real project settings, however, it seems rarely to take place. This paper investigates automated quantity take-off in a real-life road project and the experiences from this automation. A literature and a document study were performed. 48 domain models serialized in IFC 2 × 3 were then analyzed before 10 project members were interviewed. The quantity take-off was automated to harvest classified quantities to a specification of work. The automated quantity take-off was reproducible at revisions for 40% of the cost items. However, the transferability of the procedures to other use cases than the specification of work is questionable because of the applied cost breakdown structure. The findings suggest three practical improvements for automated quantity take-off in road projects. The three include (1) using unambiguous classes assembled in an ontology, (2) avoiding hard coding of cost breakdown structures in authoring tools, and (3) implementing the Level of Information Need (LOIN) to improve reusability across project phases and use cases. The quantity take-off and experiences are assessed from the designer's perspective. The client's and contractor's perspectives were out of this paper's scope.
ABSTRACT
Climate change is expected to lead to higher precipitation amounts and intensities causing an increase of the risk for flooding and combined sewer overflows in urban areas. To cope with these changes, water managers are requesting practical tools that can facilitate adaptive planning. This study was carried out to investigate how recent developments in downscaling techniques can be used to assess the effects of adaptive measures. A combined spatial-temporal downscaling methodology using the Statistical DownScaling Model-Decision Centric (SDSM-DC) and the Generalized Extreme Value distribution was applied to project future precipitation in the city of Bergen, Norway. A raingarden was considered a potential adaptive measure, and its performance was assessed using the RECARGA simulation tool. The benefits and limitations of using the proposed method have been demonstrated and compared to current design practices in Norway. Large differences in the raingarden's performance with respect to percentage overflow and lag-time reduction were found for varying projections. This highlights the need for working with a range of possible futures. Further, it was found that Ksat was the determining factor for peak-flow reduction and that different values of Ksat had different benefits. Engineering flexible solutions by combining measures holding different characteristics will induce robust adaptation.
