The research presented in this paper addresses the problem of fitting a mathematical model to epidemic data. We propose an implementation of the Landweber iteration to solve locally the arising parameter estimation problem. The epidemic models considered consist of suitable systems of ordinary differential equations. The results presented suggest that the inverse problem approach is a reliable method to solve the fitting problem. The predictive capabilities of this approach are demonstrated by comparing simulations based on estimation of parameters against real data sets for the case of recurrent epidemics caused by the respiratory syncytial virus in children.
The steady state heat transfer equations associated to two fluids in counter flow, hot and cold, in a spiral heat exchanger are considered in this study. A numerical method for solution was proposed to approximate the temperature distribution and overall heat transfer coefficients using the flow rates and the temperatures at inlets and outlets. In particular the effectiveness and correction factor were computed as performance parameters and develop a tool for design. The method is tested and validated on two actual spiral heat exchangers that were reported in the literature.
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