Skip to main content
SpringerLink
Log in

Determining silica solubility in bayer process liquor

  • Research Summary
  • Aluminum
  • Published:
JOM Aims and scope Submit manuscript

Abstract

The efficient precipitation of dissolved silica from Bayer process liquor is essential for the production of high-quality alumina and the reduction of excessive scaling in the heat exchangers in the evaporation building of Bayer processes. The accurate prediction of silica solubility in Bayer liquor is one of the key parameters in improving the design and operation of the desilication process. Previous findings, particularly with respect to the influence of temperature and concentrations of caustic soda and alumina on the solubility of silica, are inconclusive. In this article, experimental results are presented over a wide range of temperature and alumina and caustic soda concentrations. Attempts are made to utilize artificial neural networks for identifying the process variables and modeling. The radial basis function neural network architecture was used successfully to generate a nonlinear correlation for the prediction of the solubility of silica in Bayer process liquor. The resulting correlation can predict the present data and the control data of other investigators with good accuracy.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Abbreviations

B:

CB0/CA0

C:

CC0/CA0

CA0 :

Concentration of Na2SiO3 in the liquor (kg/m3)

CB0 :

Concentration of NaAlO2 in the liquor (kg/m3)

CC0 :

Concentration of H2O in the liquor (kg/m3)

CD0 :

Concentration of caustic soda in the liquor (kg/m3)

CAL :

Alumina concentration [kg (Al2O3)/m3]

Cb :

Bulk silica concentration [kg (SiO2)/m3]

C*:

Saturation concentration of silica [kg/m3]

C*:

Output vector

D:

CD0/CA0

G:

Green function

I:

Identity matrix

kDSP :

Reaction constant (m4/kg · min.)

KD :

Equilibrium constant of dissolution reaction

KP :

Equilibrium constant of the precipitation reaction

m:

Constant in Equation 12

M:

Stoichiometric constant

N:

Number of exemplar

n:

DSP deposition rate (kg/m2 · min.)

t:

Center of Gaussian activation function

T:

Temperature (K)

x:

Input vector

X*:

Equilibrium fractional conversion of Na2SiO3

w:

Weight vector

Φ:

Interpolation matrix

φ(·):

Activation function

λ:

Regularization parameter

σ:

Radius of Gaussian activation function

References

  1. P.G. Cousineau and G.D. Fulford, “Aspect of the Desilication of Bayer Liquor,” Light Metals 1987, ed. R. Zabreznik (Warrendale, PA: TMS, 1987), pp. 11–17.

    Google Scholar 

  2. H. Müller-Steinhagen, M. Jamialahmadi, and B. Robson, “Understanding and Mitigating Heat Exchanger Fouling in Bauxite Refineries,” JOM, 46 (11) (1994), pp. 36–41.

    Google Scholar 

  3. G.A. O’Neill, “Prediction of Heat Exchanger Heat Transfer Coefficient Decay Due to Fouling,” Light Metals 1986, ed. R.E. Miller (Warrendale, PA: TMS, 1986), pp. 133–140.

    Google Scholar 

  4. A. Duncan (Paper presented at the 1994 TMS Annual Meeting, San Francisco, CA, February 27–March 3, 1994).

  5. M. Jamialahmadi and H. Müller-Steinhagen, “Thermodynamic Relationships for the Solubility of Silica in Bayer Process Liquor,” Aluminum 68, Jahrgang (1992), pp. 230–233.

    CAS  Google Scholar 

  6. T. Oku and K. Yamada, “The Dissolution Rate of Quartz and the Rate of Desilication in Bayer Liquor,” Light Metals 1971, ed. T.G. Edgeworth (Warrendale, PA: TMS, 1971), pp. 31–45.

    Google Scholar 

  7. A.N. Adamson, E.J. Bloore, and A.R. Carr, “Basic Principles of Bayer Process Design,” J. Extr. Met. of Aluminum, 1 (1963), pp. 23–58.

    CAS  Google Scholar 

  8. M.G. Leiteizen, “Kinetics of Converting Bauxite Silica to Sodium Aluminosilicate,” TSV Met., 45 (1972), pp. 37–40.

    CAS  Google Scholar 

  9. P.J. Cresswell, “Factors Affecting Desilication of Bayer Process Liquors,” CHEMECA, 48 (1984), pp. 285–292.

    Google Scholar 

  10. K.J. Hewett, A.J. White, and G.I. Roach, “Silica Solubility in Plant Liquors,” AJW23/MDR (Confidential Report) (April 1987).

  11. A.M. Shaw, F.J. Doyle, and J.S. Schwaber, “A Dynamic Neural Network Approach to Nonlinear Process Modeling,” Computers Chem. Eng., 21 (1997), pp. 371–385.

    Article  CAS  Google Scholar 

  12. L.H. Unger, B.A. Powell, and S.N. Kamens, “Adaptive Neural Nets for Fault Diagnosis and Process Control,” Computers Chem. Eng., 14 (1990), pp. 561–572.

    Article  Google Scholar 

  13. M.J.D. Powell, “Radial Basis Functions for Multivariable Interpolation: A Review,” IMA Conference Proceedings on Algorithms for the Approximation of Functions and Data (Shirvenham, U.K.: RMCS, 1985), pp. 143–167.

    Google Scholar 

  14. M.J.D. Powell, “Radial Basis Function Approximations to Polynomials,” Numerical Analysis 1987 Proceedings (Dundee, U.K.: 1988), pp. 223–241.

  15. T. Poggio and F. Girosi, “Regularization Algorithms for Learning That Are Equivalent to Multilayer Networks,” Science, 247 (1990), pp. 978–982.

    Article  Google Scholar 

  16. D.R. Baughman and Y.A. Liu, Neural Networks in Bioprocessing and Chemical Engineering (New York: Academic Press, 1995).

    Google Scholar 

  17. J.J. Kotte, “Bayer Digestion and Pre-Digestion Desilication Reactor Design,” Light Metals 1989, ed. P.G. Campbell (Warrendale, PA: TMS, 1989), pp. 46–81.

    Google Scholar 

  18. I.Z. Pevzner et al., “Mathematical Description of the Alumina Solution Desiliconizing Process,” TSV Met., 16 (1975), pp. 53–57.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Engineering in the Environment, University of Surrey, GU2 5HX, Guilford, Surrey, England

    H. Müller-Steinhagen

Authors
  1. H. Müller-Steinhagen
    View author publications

    You can also search for this author in PubMed Google Scholar

Additional information

M. Jamialahmadi earned his Ph.D. in chemical engineering at Aston University in 1983. He is currently a professor and dean of the Petroleum Industry Research Center, Ahwar, Iran.

H. Müller-Steinhagen is currently a professor and head of the School of Engineering in the Environment, University of Surrey.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Müller-Steinhagen, H. Determining silica solubility in bayer process liquor. JOM 50, 44–49 (1998). https://doi.org/10.1007/s11837-998-0286-6

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11837-998-0286-6

Keywords

Search

Navigation