Natural disasters such as earthquakes and tsunamis foster the creation of effective evacuation strategies to prevent the loss of human lives. This article proposes a simulation model to find out optimum evacuation routes, during a tsunami using Ant Colony Optimization (ACO) algorithms. ACO is a discrete optimization algorithm inspired by the ability of ants to establish the shortest path from their nest to a food source, and vice versa, using pheromones. The validation of the model was carried out through two drills, which were conducted in the coastal town of Penco, Chile. This town was strongly affected by an 8.8 Mw earthquake and tsunami over February 2010. The first drill was held with minimum information, leaving the population to act randomly and intuitively. The second drill was carried out with information provided by the model, inducing people to use the optimized routes generated by the ACO algorithm. The results showed that, in case of an emergency, conventional evacuation routes showed longer escape times compared to those produced by the model developed in this research.
Hysteresis in the field emission (FE) data of a chemical vapor synthesized carbon nanotube fiber cathode is analyzed in the regime where self-heating effects are negligible. In both the forward and reverse applied field sweeps, various FE modes of operation are identified: including Fowler-Nordheim (FN) tunneling and space-charge limited emission from the fiber tip and FN emission from the fiber sidewall. Hysteresis in the FE data is linked to the difference in the field enhancement factors in the different FE modes of operation in the forward and reverse sweeps and related to changes in the fiber morphology.
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