APPLICATION OF THE MARKOV CHAIN MONTE CARLO METHOD TO ESTIMATION OF PARAMETERS IN A MODEL OF ADSORPTION-ENHANCED REACTION PROCESS FOR MERCURY REMOVAL FROM NATURAL GAS

• DOI: 10.22533/at.ed.31919010435

• Palavras-chave: Atena

• Keywords: Mercury removal, Natural gas, Markov Chain Monte Carlo Method.

• Abstract:

  A mathematical model proposed

  in the literature for the adsorption of mercury

  was solved numerically. This model involved the

  diffusion in the adsorbent particle, followed by

  a chemical reaction inside the solid matrix. The

  model was obtained based on the differential

  mass balance for the solute in a volume element

  bed with an equation involving diffusion and

  a first-order chemical reaction. For the direct

  solution of the problem, the Method of Lines

  (MOL) was applied to simplify the system of

  Partial Differential Equations (PDEs) into a

  system of time dependent Ordinary Differential

  Equations (ODEs). For the estimation of

  parameters, simulated measurements were

  generated with a normal distribution, with the

  direct solution as the mean and deviations of

  10% regarding the maximum value of the exact

  solution. The sensor is located at the exit of the

  bed. Lastly, based on the sensitivity analysis,

  two parameters were chosen and estimated

  by the Markov Chain Monte Carlo (MCMC)

  method regarding the Gaussian distribution as

  a prior distribution to unknown parameters. In

  the estimation, the mean equal to the reference

  value with a standard deviation of 10% of the

  reference values. The results showed that the

  method was able to reproduce the reference

  values with relative errors of less than 3% for

  both the parameters.

• Número de páginas: 15