Shunjiang Ni

MODELING THE DYNAMICS OF DISASTER SPREADING FROM KEY NODES IN COMPLEX NETWORKS

In this paper, we present the dynamics of disaster spreading from key nodes in complex networks. The key nodes have maximum and minimum out-degree nodes, which show important in spreading disaster. This paper considers directed Erdos–Renyi, scale-free and small-world networks. Using the model considering the common characteristics of infrastructure and lifeline networks, i.e., self-healing function and disaster spreading mechanism, we carry out simulations for the effects of the recovery time parameter and the time delay on the recovery rate and the number of damaged nodes. Simulation results show some typical disaster spreading characteristics, e.g., a non-equilibrium phase transition in the parameter space, disturbance from the maximum out-degree nodes resulting in more damaged effect, etc.

A Preliminary Study of Mobility Patterns in Urban Subway

Understanding human mobility patterns is of great importance to traffic forecasting, urban planning, epidemic spread and many other socioeconomic dynamics covering spatiality and human travel. Based on the records of Beijing subway, we presented a preliminary study of human mobility patterns at urban scale, including return ratio and trip distance. Especially, both linear distance and actual route distance are considered. We found that for a single mode of transportation, the displacement distribution not only decays exponentially, but also has a peak, which represents the characteristics of travel radius (CTR). The CTR of actual route distance is significantly greater than that of linear distance, which indicates that quite of the passengers make detours relative to the linear path when traveling by subway.

Numerical investigation of airflow, heat transfer and particle deposition for oral breathing in a realistic human upper airway model

Inhalation injury from exposure to fire smoke is one of the causes of burn-related death. In this study, a realistic three-dimensional human upper airway model was built from magnetic resonance imaging (MRI) scanned images, including the nasal, oral, pharynx, larynx, trachea and part of the first generation of the tracheobronchial tree, as well as a tissue region from the pharynx to the upper bronchi. The Transition Shear Stress Transport (SST-transition) turbulence model, Pennes bioheat transfer equation, convective boundary conditions and a Lagrangian frame were applied and verified with experimental measurements to simulate the airflow fields, temperature distributions and particle deposition in the human airway model. The effects of flow rate, inhalation temperature and particle diameter were studied. It showed that the oral cavity is more likely to be affected by the inlet air conditions. The mucosa in the oral, pharynx and larynx are more likely to cause the thermal injury. The inspiration flow rate significantly influences the airflow fields, temperature distributions and particle deposition fraction interior of the human upper airway model, especially in the pharynx-larynx region. The rising flow rate, inhalation air temperature and particle diameter all contribute to boosting the total deposition fraction in the model. The heated particles with a higher temperature are more likely to be deposited in the oral cavity and the influence of the inlet temperature has a minor influence in the case of a bigger particle diameter.