A high-speed imaging facility for Queen's University

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The ability to observe and measure rapid changes in behaviour is the key to understanding many of the most significant problems in both civil engineering and human interaction. In Canada the civil engineering community faces pressing challenges in how to assess the risk associated with (i) climate change driven landslides, (ii) aging reinforced concrete infrastructure and (iii) deteriorated railway foundation systems. As recent events across Canada and around the world have illustrated, landslides can have a devastating effect on surrounding populations and transportation networks. And yet there is little understanding of the key drivers of these rapid events including the effect of increasingly severe weather events associated with climate change. Many reinforced concrete structures that were built in the mid-twentieth century are approaching the end of their design lives but cannot all be replaced. Instead a better understanding of their performance is required so that they are repaired or replaced only when necessary without compromising the safety of the Canadian public. Similar issues exist on Canadian railways where a wholesale replacement of tracks is impossible and so localized repairs must be used. However detecting which areas of track require repair and ensuring that these repairs are effective is difficult to do. What links each of these areas is the need for robust dynamic data sets that will allow engineers to better understand and predict behaviour. A similar need exists in psychology where dynamic and subtle changes in facial expressions are the key to understanding this aspect of human interaction.