Startseite A priori error estimates for finite element approximations to transient convection-diffusion-reaction equations in fluidized beds
Artikel
Lizenziert
Nicht lizenziert Erfordert eine Authentifizierung

A priori error estimates for finite element approximations to transient convection-diffusion-reaction equations in fluidized beds

  • V. Dhanya Varma und Suresh Kumar Nadupuri EMAIL logo
Veröffentlicht/Copyright: 30. November 2021
Veröffentlichen auch Sie bei De Gruyter Brill

Abstract

In this work, a priori error estimates for finite element approximations to the governing equations of heat and mass transfer in fluidized beds are derived. These equations are time dependent strongly coupled system of five semilinear convection-diffusion-reaction equations. The a priori error estimates for all the five variables are obtained for the error measured in L (L 2) and L 2 ( E ) , E is the energy norm.


Corresponding author: Suresh Kumar Nadupuri, Department of Mathematics, National Institute of Technology Calicut, Calicut, India, E-mail:

Funding source: Council of Scientific and Industrial Research (CSIR)

Award Identifier / Grant number: 09/874(0031)/2018/EMR-I

Acknowledgments

The authors would like to thank Council of Scientific and Industrial Research (CSIR), India (09/874(0031)/2018/EMR-I) for their support.

  1. Author contribution: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: This work was funded by Council of Scientific and Industrial Research (CSIR).

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

A Appendix

Theorem A.1

Let E be a triangle or parallelogram in two dimension or a tetrahedron or hexahedron in three dimension. Let vH s (E) for s ≥ 1. Let k ≥ 0 be an integer. There exist a constant C independent of v and h E and a function v ̃ P k ( E ) such that

0 q s , v v ̃ H q ( E ) Ch E min ( k + 1 , s ) q | v | H s ( E ) .

For details, see [16, 18].

Lemma A.2

(Gronwall’s inequality). Let f, g, h be piecewise continuous non-negative functions defined on (a, b). Assume that g is nondecreasing. Assume that there is a positive constant C independent of t such that

t ( a , b ) , f ( t ) + h ( t ) g ( t ) + C a t f ( s ) d s .

Then,

t ( a , b ) , f ( t ) + h ( t ) e C ( t a ) g ( t ) .

References

[1] S. Bruhns and J. Werther, “An investigation of the mechanism of liquid injection into fluidized beds,” AIChE J., vol. 51, no. 3, pp. 766–775, 2005. https://doi.org/10.1002/aic.10336.Suche in Google Scholar

[2] S. Heinrich, M. Peglow, M. Ihlow, M. Henneberg, and L. Mörl, “Analysis of the start-up process in continuous fluidized bed spray granulation by population balance modelling,” Chem. Eng. Sci., vol. 57, no. 20, pp. 4369–4390, 2002. https://doi.org/10.1016/s0009-2509(02)00352-4.Suche in Google Scholar

[3] K. Wintermantel, “Process and product engineering: achievements, present and future challenges,” Chem. Eng. Res. Des., vol. 77, no. 3, pp. 175–188, 1999. https://doi.org/10.1205/026387699526089.Suche in Google Scholar

[4] M. Henneberg, S. Heinrich, M. Ihlow, and L. Mörl, “Fluidized bed air drying: experimental study and model development,” Can. J. Chem. Eng., vol. 81, no. 2, pp. 176–184, 2003.10.1002/cjce.5450810202Suche in Google Scholar

[5] N. Chamakuri, N. Suresh Kumar, A. Bück, and G. Warnecke, “Parallel and high resolution numerical solution of concentration and temperature distributions in fluidized beds,” Comput. Chem. Eng., vol. 52, pp. 122–133, 2013.10.1016/j.compchemeng.2012.12.004Suche in Google Scholar

[6] N. Chamakuri, G. Warnecke, S. Heinrich, and M. Peglow, “Numerical simulation of temperature and concentration distributions in fluidized beds with liquid injection,” Chem. Eng. Sci., vol. 62, no. 6, pp. 1567–1590, 2007.10.1016/j.ces.2006.11.046Suche in Google Scholar

[7] F. Brezzi and M. Fortin, “Mixed and hybrid finite element methods,” in Springer Series in Computational Mathematics, vol. 15, New York, Springer-Verlag, 1991.10.1007/978-1-4612-3172-1Suche in Google Scholar

[8] P. G. Ciarlet, The Finite Element Method for Elliptic Problems, vol. 40, Philadelphia, SIAM, 2002.10.1137/1.9780898719208Suche in Google Scholar

[9] K. Eriksson, D. Estep, P. Hansbo, and C. Johnson, Computational Differential Equations, Cambridge, Cambridge University Press, 1996.Suche in Google Scholar

[10] J. Cannon and Y. Lin, “A priori L2-error estimates for finite element methods for nonlinear diffusion equations with memory,” SIAM J. Numer. Anal., vol. 27, no. 3, pp. 595–607, 1990. https://doi.org/10.1137/0727036.Suche in Google Scholar

[11] P. Castillo, B. Cockburn, D. Schötzau, and C. Schwab, “Optimal a priori error estimates for the hp-version of the local discontinuous galerkin method for convection–diffusion problems,” Math. Comput., vol. 71, no. 238, pp. 455–478, 2002.10.1090/S0025-5718-01-01317-5Suche in Google Scholar

[12] B. Kiniger and B. Vexler, “A priori error estimates for finite element discretizations of a shape optimization problem,” ESAIM Math. Model. Numer. Anal., vol. 47, no. 6, pp. 1733–1763, 2013. https://doi.org/10.1051/m2an/2013086.Suche in Google Scholar

[13] R. Rannacher and B. Vexler, “A priori error estimates for the finite element discretization of elliptic parameter identification problems with pointwise measurements,” SIAM J. Control Optim., vol. 44, no. 5, pp. 1844–1863, 2005. https://doi.org/10.1137/040611100.Suche in Google Scholar

[14] M. F. Wheeler, “A priori L2-error estimates for Galerkin approximations to parabolic partial differential equations,” SIAM J. Numer. Anal., vol. 10, no. 4, pp. 723–759, 1973.10.1137/0710062Suche in Google Scholar

[15] Y. Sun, P. Sun, B. Zheng, and G. Lin, “Error analysis of finite element method for Poisson–nernst–planck equations,” J. Comput. Appl. Math., vol. 301, pp. 28–43, 2016. https://doi.org/10.1016/j.cam.2016.01.028.Suche in Google Scholar

[16] B. Riviere, Discontinuous Galerkin Methods for Solving Elliptic and Parabolic Equations: Theory and Implementation, Philadelphia, Society for Industrial and Applied Mathematics, 2008.10.1137/1.9780898717440Suche in Google Scholar

[17] C. Nagaiah and G. Warnecke, “Adaptive higher order numerical simulation of heat and mass transfer in fluidized beds,” Preprints-2008, Fakultät für Mathematik, Otto-Von-Guericke-Universität Magdeburg, no. 08-21, pp. 1–18, 2008.Suche in Google Scholar

[18] L. Babuška and M. Suri, “The optimal convergence rate of the p-version of the finite element method,” SIAM J. Numer. Anal., vol. 24, no. 4, pp. 750–776, 1987.10.1137/0724049Suche in Google Scholar

Received: 2020-03-23
Revised: 2021-02-19
Accepted: 2021-11-04
Published Online: 2021-11-30
Published in Print: 2022-12-16

© 2021 Walter de Gruyter GmbH, Berlin/Boston

Artikel in diesem Heft

  1. Frontmatter
  2. Original Research Articles
  3. Coordinated target tracking in sensor networks by maximizing mutual information
  4. Legendre wavelet residual approach for moving boundary problem with variable thermal physical properties
  5. Computational study of intravenous magnetic drug targeting using implanted magnetizable stent
  6. Extended logistic map for encryption of digital images
  7. Valuation of the American put option as a free boundary problem through a high-order difference scheme
  8. Power minimization of gas transmission network in fully transient state using metaheuristic methods
  9. A priori error estimates for finite element approximations to transient convection-diffusion-reaction equations in fluidized beds
  10. Higher order rogue waves for the(3 + 1)-dimensional Jimbo–Miwa equation
  11. Dynamic characteristics of supersonic turbulent free jets from four types of circular nozzles
  12. New insights into singularity analysis
  13. Chaos and bifurcations in a discretized fractional model of quasi-periodic plasma perturbations
  14. Wavelet collocation methods for solving neutral delay differential equations
  15. Numerical solution of highly non-linear fractional order reaction advection diffusion equation using the cubic B-spline collocation method
  16. Solving nonlinear third-order boundary value problems based-on boundary shape functions
  17. Positive radial solutions for Dirichlet problems involving the mean curvature operator in Minkowski space
  18. Effect of outlet impeller diameter on performance prediction of centrifugal pump under single-phase and cavitation flow conditions
  19. A fractional-order ship power system: chaos and its dynamical properties
  20. Graphical structure of extended b-metric spaces: an application to the transverse oscillations of a homogeneous bar
  21. Hypergeometric fractional derivatives formula of shifted Chebyshev polynomials: tau algorithm for a type of fractional delay differential equations
  22. Modelling and numerical synchronization of chaotic system with fractional-order operator
Heruntergeladen am 17.9.2025 von https://www.degruyterbrill.com/document/doi/10.1515/ijnsns-2020-0063/html
Button zum nach oben scrollen