The Bayesian view of extreme events

The Bayesian perspective of designing for the consequences of hazard is discussed. Structural engineers should be educated in Bayesian theory and its underlying philosophy, and about the centrality to the prediction problem of the predictive distribution. The primary contribution that Bayesianism can make to the debate about extreme possibilities is its clarification of the language of and thinking about risk. Frequentist methodologies are the wrong approach to the decisions that engineers need to make, decisions that involve assessments of abstract future possibilities based on incomplete and abstract information.

Neural activity associated with the passive prediction of ambiguity and risk for aversive events.

In economic decision making, outcomes are described in terms of risk (uncertain outcomes with certain probabilities) and ambiguity (uncertain outcomes with uncertain probabilities). Humans are more averse to ambiguity than to risk, with a distinct neural system suggested as mediating this effect. However, there has been no clear disambiguation of activity related to decisions themselves from perceptual processing of ambiguity. In a functional magnetic resonance imaging (fMRI) experiment, we contrasted ambiguity, defined as a lack of information about outcome probabilities, to risk, where outcome probabilities are known, or ignorance, where outcomes are completely unknown and unknowable. We modified previously learned pavlovian CS+ stimuli such that they became an ambiguous cue and contrasted evoked brain activity both with an unmodified predictive CS+ (risky cue), and a cue that conveyed no information about outcome probabilities (ignorance cue). Compared with risk, ambiguous cues elicited activity in posterior inferior frontal gyrus and posterior parietal cortex during outcome anticipation. Furthermore, a similar set of regions was activated when ambiguous cues were compared with ignorance cues. Thus, regions previously shown to be engaged by decisions about ambiguous rewarding outcomes are also engaged by ambiguous outcome prediction in the context of aversive outcomes. Moreover, activation in these regions was seen even when no actual decision is made. Our findings suggest that these regions subserve a general function of contextual analysis when search for hidden information during outcome anticipation is both necessary and meaningful.

Sand column impact onto a Kolsky pressure bar

A laboratory-based methodology to launch cylindrical sand slugs at high velocities is developed. The methodology generates well-characterised soil ejecta without the need for detonation of an explosive; this laboratory-based tool thereby allows for the experimental investigation of the soil-structure events. The experimental set-up comprises a launcher with a cylindrical cavity and a piston to push out the sand slug. The apparatus is used to launch both dry and water-saturated sand slugs. High speed photography is used to characterise the evolution of the sand slugs after launch. We find that the diameter of the slugs remains unchanged, and the sand particles possess only an axial component of velocity. However, the sand particles have a uniform spatial gradient of axial velocity and this results in lengthening of the slugs as they travel towards their target. Thus, the density of the sand slugs remains spatially homogenous but decreases with increasing time. The velocity gradient is typically higher in the dry sand slugs than that of the water-saturated slugs. The pressure exerted by the slugs on a rigid-stationary target is measured by impacting the slugs against a direct impact Kolsky bar. After an initial high transient pressure, the pressure reduces to a value of approximately ρv 2 where ρ is the density of the impacting sand slug and v is the particle velocity. This indicates that loading due to the sand is primarily inertial in nature. The momentum transmitted to the Kolsky bar was approximately equal to the incident momentum of the sand slugs, regardless of whether they are dry or water-saturated. © 2013 Elsevier Ltd. All rights reserved.