Optimising Pedestrian Flow Around Large Stadiums

This study proposes a method that combines the cellular automaton model and the differential evolution algorithm for optimising pedestrian flow around large stadiums. A miniature version of a large stadium and its surrounding areas is constructed via the cellular automaton model. Special mechanisms are applied to influence the behaviour of an agent that leaves from a certain stadium gate. The agent may be attracted to a nearby business facility and/or guided to uncongested areas. The differential evolution algorithm is then used to determine the optimal probabilities of the influencing agents for each stadium gate. The main goal is to reduce the evacuation time, and other goals such as reducing the costs for the influencing agents’ behaviours and the individual evacuation time are also considered. We found that, although they worked differently in different scenarios, the attraction and guidance of agents significantly reduced the evacuation time. The optimal evacuation time was achieved with moderate attraction to the business facilities and strong guidance to the detouring route. The results demonstrate that the proposed method can provide a goal-dependent, exit-specific strategy that is otherwise hard to acquire for optimising pedestrian flow.

Step Bunches, Nanowires and Other Vicinal “Creatures”—Ehrlich–Schwoebel Effect by Cellular Automata

Different patterns can be created on the surface of growing crystals, among which the step bunches and/or step meanders are two of the most studied. The Ehrlich–Schwoebel effect at the surface steps is considered one of the “usual suspects” of such patterning. A direct step barrier is when it is easier to attach a particle to the step from the lower terrace than from the upper terrace. Thus, during the process of crystal growth leads to the formation of meanders, while an inverse barrier leads to step bunching. Based on our vicinal Cellular Automaton model, but this time in (2 + 1)D, we show that the combination of a direct and inverse step barrier and the proper selection of the potential of the well between them leads to the formation of bunched step structures. Following this is the formation of anti-bands. In addition, changing the height of the direct step barrier leads to the growth of nanocolumns, nanowires, and nanopyramids or meanders, in the same system.

Microstructure and Elements Concentration of Inconel 713LC during Laser Powder Bed Fusion through a Modified Cellular Automaton Model

In this study, a hybrid finite element (FE) and cellular automaton (CA) model is developed to explore crystallization behavior and alloying of Inconel713LC during Laser powder bed fusion. A cellular automaton model is considering the surface nucleation, equiaxed bulk nucleation, and grain growth kinetics. In addition, the equation for solute diffusion is coupled with a cellular automaton model to simulate the IN713LC elements segregation. During the phase change, the non-equilibrium segregation model is applied to insert the effect of ultra-fast solidification happening during LPBF. It is found that, during LPBF processing of IN713LC, the micro segregation of Nb, Ti, and C is accrued at the grain boundaries. It is further shown that the micro segregation intensity depends on the solidification speed, which is determined in turn by the laser heat input. In particular, a lower laser heat input increases the solidification speed and results in a more uniform solid phase, thereby reducing the risk of crack formation. Finally, using a comparison between simulation results and experimental observation, it was shown that the proposed model successfully predicts the bulk element concentration of IN713LC after laser melting.