Flow visualization and analysis of thermal distribution for the nanofluid by the integration of fuzzy c-means clustering ANFIS structure and CFD methods

Journal of Visualization - A nanofluid containing copper (Cu) nanoparticles was simulated in a rectangular cavity using computational fluid dynamic (CFD). The upper and lower walls of the cavity...     

Stability and Rheological Properties of Model Low-Fat Salad Dressing Stabilized by Salep

A model low-fat salad dressing including salep as thickening agent was prepared. In order to obtain an stable salad dressing, different variables each one at three levels like salep content (0.5, 2.0, and 3.5% w/w), oil volume fraction (7.50, 16.25, and 25.00% w/w), pH (3, 5, and 7), salt concentration (0.3, 0.9, and 1.5% w/w), and egg yolk content (2, 4, and 6% w/w) were chosen and their effect on the creaming index of salad dressing was studied. It was observed that samples with highest salep content at pH 3 were the most stable during storage time (15 days). The microstructure of some samples was considered. Rheological measurements were performed for stable samples. Oil fraction and salt content increased zero shear viscosity and G′ modulus of samples.      

Server allocation for zero buffer tandem queues

In this paper we consider the problem of allocating servers to maximize throughput for tandem queues with no buffers. We propose an allocation method that assigns servers to stations based on the mean service times and the current number of servers assigned to each station. A number of simulations are run on different configurations to refine and verify the algorithm. The algorithm is proposed for stations with exponentially distributed service times, but where the service rate at each station may be different. We also provide some initial thoughts on the impact on the proposed allocation method of including service time distributions with different coefficients of variation.     

Optimal two-phase vaccine allocation to geographically different regions under uncertainty

In this article, we consider a decision process in which vaccination is performed in two phases to contain the outbreak of an infectious disease in a set of geographic regions. In the first phase, a limited number of vaccine doses are allocated to each region; in the second phase, additional doses may be allocated to regions in which the epidemic has not been contained. We develop a simulation model to capture the epidemic dynamics in each region for different vaccination levels. We formulate the vaccine allocation problem as a two-stage stochastic linear program (2-SLP) and use the special problem structure to reduce it to a linear program with a similar size to that of the first stage problem. We also present a Newsvendor model formulation of the problem which provides a closed form solution for the optimal allocation. We construct test cases motivated by vaccine planning for seasonal influenza in the state of North Carolina. Using the 2-SLP formulation, we estimate the value of the stochastic solution and the expected value of perfect information. We also propose and test an easy to implement heuristic for vaccine allocation. We show that our proposed two-phase vaccination policy potentially results in a lower attack rate and a considerable saving in vaccine production and administration cost.