Achievements and Challenges in Recognizing and Reconstructing Civil Infrastructure

The US National Academy of Engineering recently identified restoring and improving urban infrastructure as one of the grand challenges of engineering. Part of this challenge stems from the lack of viable methods to map/label existing infrastructure. For computer vision, this challenge becomes “How can we automate the process of extracting geometric, object oriented models of infrastructure from visual data?” Object recognition and reconstruction methods have been successfully devised and/or adapted to answer this question for small or linear objects (e.g. columns). However, many infrastructure objects are large and/or planar without significant and distinctive features, such as walls, floor slabs, and bridge decks. How can we recognize and reconstruct them in a 3D model? In this paper, strategies for infrastructure object recognition and reconstruction are presented, to set the stage for posing the question above and discuss future research in featureless, large/planar object recognition and modeling.

Lateral spreading-induced abutment rotation in the 2011 Christchurch earthquake: Observations and analysis

A series of strong earthquakes near Christchurch, New Zealand, occurred between September 2010 and December 2011, causing widespread liquefaction throughout the city's suburbs. Lateral spreading developed along the city's Avon River, damaging many of the bridges east of the city centre. The short-to medium-span bridges exhibited a similar pattern of deformation, involving back-rotation of their abutments and compression of their decks. By explicitly considering the rotational equilibrium of the abutments about their point of contact with the rigid bridge decks, it is shown that relatively small kinematic demands from the laterally spreading backfill soil are needed to initiate pile yielding, and that this mode of deformation should be taken into account in the design of the abutments and abutment piles.