Description:
In this study, the effects of Plasticity Index (PI) variation on the seismic response of mid-rise building frames resting on soft soil deposits are investigated. To achieve this goal, three structural models including 5, 10, and 15 storey buildings are simulated in conjunction with a clayey soil representing soil class Ee according to the classification of AS1170.4-2007 (Earthquake actions in Australia) and then varying the Plasticity Index. Structural sections of the selected frames were designed according to AS3600-2009 (Australian Standard for Concrete Structures) after undertaking dynamic analysis under the influence of four different earthquake ground motions. The frame sections are modelled and analysed, employing finite difference method adopting FLAC 2D software under two different boundary conditions: (i) fixed base (no Soil-Structure Interaction), and (ii) flexible base considering soil-structure interaction. Fully nonlinear dynamic analyses under the influence of different earthquake records are conducted and the results in terms of maximum lateral displacements and inter-storey drifts for the above mentioned boundary conditions are obtained, compared, and discussed. Base on the results of the numerical investigations, it becomes apparent that as the Plasticity Index of the subsoil increases, the base shears of mid-rise building frames resting on soft soil deposits increase, while the lateral deflections and corresponding inter-storey drifts decrease. It is concluded that reduction of the Plasticity Index could noticeably amplify the effects of soil-structure interaction on the seismic response of mid-rise building frames.
Description:
Effective building detection and roof reconstruction has an influential demand over the remote sensing research community. In this paper, we present a new automatic LiDAR point cloud segmentation method using suitable seed points for building detection and roof plane extraction. Firstly, the LiDAR point cloud is separated into "ground" and "non-ground" points based on the analysis of DEM with a height threshold. Each of the non-ground point is marked as coplanar or non-coplanar based on a coplanarity analysis. Commencing from the maximum LiDAR point height towards the minimum, all the LiDAR points on each height level are extracted and separated into several groups based on 2D distance. From each group, lines are extracted and a coplanar point which is the nearest to the midpoint of each line is considered as a seed point. This seed point and its neighbouring points are utilised to generate the plane equation. The plane is grown in a region growing fashion until no new points can be added. A robust rule-based tree removal method is applied subsequently to remove planar segments on trees. Four different rules are applied in this method. Finally, the boundary of each object is extracted from the segmented LiDAR point cloud. The method is evaluated with six different data sets consisting hilly and densely vegetated areas. The experimental results indicate that the proposed method offers a high building detection and roof plane extraction rates while compared to a recently proposed method.
Description:
A large group of men, women and children are posed in front of two small buildings. The scene may be at Grant. Another source locates this scene at Budgeree, and another in the Bairnsdale area.
Description:
Item held by Centre for Gippsland Studies, Federation University Australia.
Description:
Record generated from title list.
Description:
Grant and its neighbours - POT 60|Photograph : also at AB0337
Description:
A large group of men, women and children are posed in front of two small buildings. The scene may be at Grant. Another source locates this scene at Budgeree, and another in the Bairnsdale area.
Description:
Item held by Centre for Gippsland Studies, Federation University Australia.
Description:
Record generated from title list.
Description:
Grant and its neighbours - POT 60|Photograph : also at AB0337