Simulation of segregation in a fluidized bed by CFD-DEM by using similarities

Segregation happens in a fluidized bed due to particles with different sizes and/or different densities. Segregation is important for a lot of processes such as gasification, combustion and drying, but there are still a lot of unknown features. CFD coupled with DEM (discrete element model) is a powerful tool to investigate segregation in fluidized beds, but the computational load by this approach is too heavy to perform simulations in large-scale. In this study, similarities are used to decrease computational load. A fluidized bed consisting of jetsam and flotsam particles is simulated, i.e. large particles with small density and small particles with large density, respectively (Table 1). The dimensions of the fluidized bed are 1m height, 1m length and 0.037m depth. The number of real particles in the bed exceeds 1 billion, which is too large to track in a numerical simulation by computer. Therefore, in the imaginary system which is simulated the number of particles is reduced as described below. The imaginary system contains imaginary gas and imaginary particles. Each imaginary particle with a diameter K times larger than that of the real particle replaces a group of real particles. It is deduced that the segregation behavior of the imaginary system is similar to that of the real system, if the physical properties of the imaginary system are adjusted such that Reynolds and Archimedes numbers equal those of the real system (Fig.2). Enlarging the imaginary particles by a factor K can decrease the number of particles and hence the computational load by a factor of K-4.5. Please click Additional Files below to see the full abstract

THE ROLE OF SOCIAL NETWORKS IN ONLINE REVIEWING

Online reviews are a dominant resource for consumer decisions but what leads users to write reviews remains largely unexamined. Extant research on user content generation has primarily focused on what motivates users to contribute content, and less on the effects of informational and social environment surrounding these users. The aim of this study is to examine how a user’s contribution to an online review platform is affected by reviews of his/her friends from both informational and social perspectives. We expect that information, reciprocity, and social comparison are primary drivers for contribution. Among friends who wrote reviews, we predict that those who carry redundant information have less effect on the focal user’ contribution, whereas those who are strong-tie friends of the focal user have a stronger effect. Furthermore, we expect that users’ status moderates these effects such that an elite user responds more positively to friends who carry redundant information, and more negatively to those who are strong-tie friends, compared to non-elite users. Our expected findings hold implications for online review platforms in terms of highlighting the most relevant reviews generated by one’s peer