2010 Annual Meeting

(383d) An Integrated Framework for Model-Based Solids Process Engineering

Authors

Mark Pinto - Presenter, Procter & Gamble
Sean Bermingham - Presenter, Process Systems Enterprise Ltd
John Hecht - Presenter, Procter & Gamble


Solids
processes are estimated to rarely reach more than 60% of design capacity and
require 10 times longer to start-up than those involving only liquid-gas
streams.  The business costs associated with these staggering statistics are
exacerbated by the capital and energy-intensive nature of solids processes.

This
contribution therefore focuses on the development of a model-based engineering
tool that can help address these problems through a better understanding of the
process and associated risks.

The
first part of this contribution describes a new modelling framework for solids
process aimed at providing a step change in the facilities available to engineers
responsible for the design and operation of industrial solids processes.  This
framework has the following characteristics:

  • Use of fully discretised population balances (particle
    size distributions and composition distributions).
  • Ability to address true dynamics.
  • Robust handling of large numbers of recycles.
  • Support for model validation (parameter estimation and
    experiment design).
  • Optimisation capability for design and operation of
    processes.
  • Interfacing to standard CFD packages.
  • Phenomenological approach to model development that
    facilitates rapid and consistent development of models.
  • An intuitive user interface.

    • The
    second part of this paper covers a number of typical case studies investigated
    with this new framework:

    1. Model discrimination and parameter estimation using
      experimental data from a fed-batch agglomeration process.
    2. Analysing the impact of uncertainty in model and
      design parameters on process performance in order to quantify risk associated
      with capital expenditure decisions.
    3. Determining the optimal trade-off between on the one
      hand low capital cost and reduced start-up times of the process and on the other
      hand the robustness of the process with respect to downstream disturbances
      (e.g. blockages).
    4. How does the operation of upstream units, in this case
      a crystalliser, impact the capacity of downstream solids handling?
    5. How can information from lab-scale studies coupled
      with CFD simulations of plant-scale equipment be coupled to aid plant scale
      equipment design and optimisation?