How Well Do We Understand Earthquake Induced Liquefaction?

Soil liquefaction following large earthquakes is a major contributor to damage to infrastructure and economic loss, as borne out by the earthquakes in Japan and New Zealand in 2011. While extensive research has been conducted on soil liquefaction and our understanding of liquefaction has been advancing, several uncertainties remain. In this paper the basic premise that liquefaction is an 'undrained' event will be challenged. Evidence will be offered based on dynamic centrifuge tests to show that rapid settlements occur both in level ground and for shallow foundations. It will also be shown that the definition of liquefaction based on excess pore pressure generation and the subsequent classification of sites as liquefiable and non-liquefiable is not satisfactory, as centrifuge test data shows that both loose and dense sand sites produce significant excess pore pressure. Experimental evidence will be presented that shows that the permeability of sands increases rapidly at very low effective stresses to allow for rapid drainage to take place from liquefied soil. Based on these observations a micro-mechanical view of soil liquefaction that brings together the Critical State view of soil liquefaction and the importance of dynamic loading will be presented. © 2012 Indian Geotechnical Society.

Machine Vision Enhanced Post-Earthquake Inspection and Rapid Loss Estimation

Manual inspection is required to determine the condition of damaged buildings after an earthquake. The lack of available inspectors, when combined with the large volume of inspection work, makes such inspection subjective and time-consuming. Completing the required inspection takes weeks to complete, which has adverse economic and societal impacts on the affected population. This paper proposes an automated framework for rapid post-earthquake building evaluation. Under the framework, the visible damage (cracks and buckling) inflicted on concrete columns is first detected. The damage properties are then measured in relation to the column's dimensions and orientation, so that the column's load bearing capacity can be approximated as a damage index. The column damage index supplemented with other building information (e.g. structural type and columns arrangement) is then used to query fragility curves of similar buildings, constructed from the analyses of existing and on-going experimental data. The query estimates the probability of the building being in different damage states. The framework is expected to automate the collection of building damage data, to provide a quantitative assessment of the building damage state, and to estimate the vulnerability of the building to collapse in the event of an aftershock. Videos and manual assessments of structures after the 2009 earthquake in Haiti are used to test the parts of the framework.