Full Content is available to subscribers

Subscribe/Learn More  >

Estimating Parameters of a Packed Bed by Least Squares and Markov Chain Monte Carlo

[+] Author Affiliations
A. F. Emery, E. Valenti

University of Washington

Paper No. IMECE2005-82086, pp. 643-650; 8 pages
  • ASME 2005 International Mechanical Engineering Congress and Exposition
  • Heat Transfer, Part B
  • Orlando, Florida, USA, November 5 – 11, 2005
  • Conference Sponsors: Heat Transfer Division
  • ISBN: 0-7918-4222-3 | eISBN: 0-7918-3769-6
  • Copyright © 2005 by ASME


Most parameter estimation is based upon the assumption of normally distributed errors using least squares and the confidence intervals are computed from the sensitivities and the statistics of the residuals. For nonlinear problems, the assumption of a normal distribution of the parameters may not be valid. Determining the probability density distribution can be difficult, particularly when there is more than one parameter to be estimated or there is uncertainty about other parameters. An alternative approach is Bayesian inference, but the numerical computations can be expensive. Markov Chain Monte Carlo (MCMC) may alleviate some of the expense. The paper describes the application of MCMC to estimate the mass flow rate, the heat transfer coefficient, and the specific heat of a packed bed regenerator.

Copyright © 2005 by ASME



Interactive Graphics


Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In