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Modeling and Simulation Research on Public’s Emergency Knowledge Diffusion Based on Weighted Small-World Network

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Abstract Although the significance of public emergency participation is beyond doubt, the public’s emergency knowledge in China and the present societal demands have a considerable gap. Therefore, this study constructed a theoretical model of public’s emergency knowledge diffusion based on the weighted small-world network model, and explored the diffusion patterns and influencing factors of public’s emergency knowledge under the different selection strategies of emergency knowledge senders and different network intensities by MATLAB simulation. The results show that regardless of the intensity of the relationship in the public’s emergency knowledge diffusion network, determining the sender with the knowledge priority strategy can bring a higher emergency knowledge growth rate in the short term. In addition, public participation policies, protection laws, and information technology play a positive role on the diffusion efficiency of public’s emergency knowledge, while the diffusion cost has a negative impact. Compared with weak relation networks, the diffusion efficiency is higher in strong relation networks, and the diffusion process of public’s emergency knowledge in weak relation networks is more susceptible to the influence of external factors. This study not only fills the gap in the study of public’s emergency knowledge diffusion, but also provides a theoretical reference for the improvement of public’s emergency knowledge.

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Discrete element method simulations are conducted to investigate the effects of applied uniaxial compressive load, and bidisperse particle size distributions on force networks within jammed granular media. The differences between the strong and weak networks are examined through investigating the spatial correlation and distribution of contact angles, and emergence of chainlike structures. The simulation results show that the chainlike structures are more prevalent in the strong network due to the larger cumulative probabilities of contact angles, but not all the contacts belonging to the strong or weak networks are able to constitute the chainlike structures. Although the contacts of coarse-fine particles are dominant for the bidisperse systems, the contacts of coarse–coarse particles dominate the strong network, as well as the linear chainlike structures. Upon increasing the pressure from very low to high, the probability of contact orientations with respect to the compression direction in the strong network increases for contact orientation less than \(60^{\circ }\) and decreases for contact orientation greater than \(60^{\circ }\), while the opposite trends are observed in the weak network. The tails of normalized normal contact forces distributions are quantified by \(\hbox {P}(\hbox {f}) = \hbox {exp}(-\hbox {cf}^{\mathrm{n}})\), and it is found that the value of n depends on the applied pressure and particle size distribution. Statistical analysis shows that the degree of homogeneity of contact force increases with increasing pressure, which is also validated by participation number.

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Experimental study of some properties of the strong and weak force networks in a jammed granular medium
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We are experimentally investigating the force network of a monolayer of grains through the jamming transition. Once the packing has been compressed beyond the volume fraction of jamming $$\phi _J$$, we use particle tracking and photoelastic techniques to determine the network of forces in the grains. We experimentally quantify the pressure inside each grain and highlight the two networks of forces existing in jammed granular materials: the load bearing network (force chains strong network) and the dissipative network (weak network). For the strong network, we study the statistical properties of the stress state of the grains and in particular the exponential tails of the probability density function of pressure and shear stress. As the distance to jamming increases, the probability density function of local shear in the system evolves and tends to look like a normal distribution while the probability density function of pressure does not evolve. For the weak network, we study the contact cycles in the granular packing. By calculating their numbers, we determine some statistical properties of these cycles. The number of cycles of order $$n=3$$ which carries the dissipative network increases linearly with the number of contacts.

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Reply to Mikesell and Birskyte, and to Cyr and Swanson

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