Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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Access Right: Open AccessSubject: search.filters.subject.Numerical models

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  • Article
    Citation - WoS: 12
    Citation - Scopus: 14
    A Molecular Communication Perspective on Airborne Pathogen Transmission and Reception Via Droplets Generated by Coughing and Sneezing
    (IEEE, 2021) Güleç, Fatih; Atakan, Barış; Güleç, Fatih; 01.01. Units Affiliated to the Rectorate; 03.05. Department of Electrical and Electronics Engineering; 01. Izmir Institute of Technology; 03. Faculty of Engineering
    Infectious diseases spread via pathogens such as viruses and bacteria. Airborne pathogen transmission via droplets is an important mode for infectious diseases. In this paper, the spreading mechanism of infectious diseases by airborne pathogen transmission between two humans is modeled with a molecular communication perspective. An end-to-end system model which considers the pathogen-laden cough/sneeze droplets as the input and the infection state of the human as the output is proposed. This model uses the gravity, initial velocity and buoyancy for the propagation of droplets and a receiver model which considers the central part of the human face as the reception interface is proposed. Furthermore, the probability of infection for an uninfected human is derived by modeling the number of propagating droplets as a random process. The numerical results reveal that exposure time affects the probability of infection. In addition, the social distance for a horizontal cough should be at least 1.7 m and the safe coughing angle of a coughing human to infect less people should be less than -25 degrees.
  • Article
    Citation - WoS: 75
    Citation - Scopus: 99
    Case Study: Finite Element Method and Artificial Neural Network Models for Flow Through Jeziorsko Earthfill Dam in Poland
    (American Society of Civil Engineers (ASCE), 2005) Gökmen, Tayfur; Swiatek, Dorota; Wita, Andrew; Singh, Vijay Pratap Ratap; 01. Izmir Institute of Technology
    A finite element method (FEM) and an artificial neural network (ANN) model were developed to simulate flow through Jeziorsko earthfill dam in Poland. The developed FEM is capable of simulating two-dimensional unsteady and nonuniform flow through a nonhomogenous and anisotropic saturated and unsaturated porous body of an earthfill dam. For Jeziorsko dam, the FEM model had 5,497 triangular elements and 3,010 nodes, with the FEM network being made denser in the dam body and in the neighborhood of the drainage ditches. The ANN model developed for Jeziorsko dam was a feedforward three layer network employing the sigmoid function as an activator and the back-propagation algorithm for the network learning. The water levels on the upstream and downstream sides of the dam were input variables and the water levels in the piezometers were the target outputs in the ANN model. The two models were calibrated and verified using the piezometer data collected on a section of the Jeziorsko dam. The water levels computed by the models satisfactorily compared with those measured by the piezometers. The model results also revealed that the ANN model performed as good as and in some cases better than the FEM model. This case study offers insight into the adequacy of ANN as well as its competitiveness against FEM for predicting seepage through an earthfill dam body.