Nonlinear stochastic model for bacterial disinfection: Analytical solution and Monte Carlo simulation

L. T. Fan, Andres Argoti, Ronaldo G. Maghirang, Song Tien Chou

Research output: Contribution to journalArticlepeer-review

Abstract

This contribution presents a sequel to our previously published nonlinear stochastic model for bacterial disinfection whose intensity function is explicitly proportional to the contact time of the bacteria with the disinfecting agent. In the current model, the intensity function is proportional to the square of the contact time to account for an accelerated rate of a disinfection process. The model gives rise to the process master equation whose solution renders it possible to obtain the analytical expressions of the process mean, variance (or standard deviation), and coefficient of variation. Moreover, the master equation has been simulated via the Monte Carlo method, thereby yielding the numerical estimates of these quantities. The estimates values are compared with those computed via the analytical expressions; they are in excellent accord. They are also compared with the available experimental data as well as with the results obtained from our earlier model.

Original languageEnglish (US)
Pages (from-to)1697-1702
Number of pages6
JournalIndustrial and Engineering Chemistry Research
Volume51
Issue number4
DOIs
StatePublished - Feb 1 2012
Externally publishedYes

ASJC Scopus subject areas

  • Chemistry(all)
  • Chemical Engineering(all)
  • Industrial and Manufacturing Engineering

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