A Comparison of Different Quasi-Newton Acceleration Methods for Partitioned Multi-Physics Codes

  • Conference paper
  • First Online:
Transactions on Engineering Technologies (IMECS 2017)

Abstract

In many cases, different physical systems interact, which translates to coupled mathematical models. We only focus on methods to solve (strongly) coupled problems with a partitioned approach, i.e. where each of the physical problems is solved with a specialized code that we consider to be a black box solver. Running the black boxes one after another, until convergence is reached, is a standard but slow solution technique, known as non-linear Gauss-Seidel iteration. A recent interpretation of this approach as a root-finding problem has opened the door to acceleration techniques based on Quasi-Newton methods that can be “strapped onto” the original iteration loop without modification to the underlying code. In this paper, we analyze the performance of different acceleration techniques on different multi-physics problems.

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

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
EUR 29.95
Price includes VAT (Thailand)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
EUR 160.49
Price includes VAT (Thailand)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
EUR 199.99
Price excludes VAT (Thailand)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info
Hardcover Book
EUR 199.99
Price excludes VAT (Thailand)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. A.C. Aitken, On Bernouilli’s numerical solution of algebraic equations. Proc. Roy. Soc. Edinb. 46, 289–305 (1926)

    Article  MATH  Google Scholar 

  2. A.E.J. Bogaers, S. Kok, B.D. Reddy, T. Franz, Quasi-Newton methods for implicit black-box FSI coupling. Comput. Methods Appl. Mech. Eng. 279, 113–132 (2014)

    Article  MathSciNet  Google Scholar 

  3. A.E.J. Bogaers, S. Kok, B.D. Reddy, T. Franz, An evaluation of quasi-Newton methods for application to FSI problems involving free surface flow and solid body contact. Comput. Struct. 173, 71–83 (2016)

    Article  Google Scholar 

  4. C.G. Broyden, A class of methods for solving nonlinear simultaneous equations. Math. Comput. 19, 577–593 (1965)

    Article  MathSciNet  MATH  Google Scholar 

  5. C.G. Broyden, Quasi-Newton methods and their applications to function minimization. Math. Comput. 21, 368–381 (1967)

    Article  MATH  Google Scholar 

  6. J. Degroote, K.-J. Bathe, J. Vierendeels, Performance of a new partitioned procedure versus a monolithic procedure in fluid-structure interaction. Comput. Struct. 87(11), 793–801 (2009)

    Article  Google Scholar 

  7. J. Degroote, R. Haelterman, S. Annerel, P. Bruggeman, J. Vierendeels, Performance of partitioned procedures in fluid-structure interaction. Comput. Struct. 88(7), 446–457 (2010)

    Article  Google Scholar 

  8. J.E. Dennis, J.J. Moré, Quasi-Newton methods: motivation and theory. SIAM Rev. 19, 46–89 (1977)

    Article  MathSciNet  MATH  Google Scholar 

  9. J.E. Dennis, R.B. Schnabel, Least change secant updates for Quasi-Newton methods. SIAM Rev. 21, 443–459 (1979)

    Article  MathSciNet  MATH  Google Scholar 

  10. T. Eirola, O. Nevanlinna, Accelerating with rank-one updates. Linear Algebra Appl. 121, 511–520 (1989)

    Article  MathSciNet  MATH  Google Scholar 

  11. H.-R. Fang, Y. Saad, Two classes of multisecant methods for nonlinear acceleration. Numer. Linear Algebra Appl. 16(3), 197–221 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  12. A. Friedlander, M.A. Gomes-Ruggiero, D.N. Kozakevich, J.M. Martinez, S.A. dos Santos, Solving nonlinear systems of equations by means of Quasi-Newton methods with a nonmonotone strategy. Optim. Methods Softw. 8, 25–51 (1997)

    Article  MathSciNet  MATH  Google Scholar 

  13. J.-F. Gerbeau, M. Vidrascu et al., A Quasi-Newton algorithm based on a reduced model for Fluid-structure interaction problems in blood flows. ESAIM: Math. Model. Numer. Anal. 37(4), 631–647 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  14. R. Haelterman, J. Degroote, D. Van Heule, J. Vierendeels, The Quasi-Newton least squares method: a new and fast secant method analyzed for linear systems. SIAM J. Numer. Anal. 47(3), 2347–2368 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  15. R. Haelterman, J. Degroote, D. Van Heule, J. Vierendeels, On the similarities between the Quasi-Newton inverse least squares method and GMRes. SIAM J. Numer. Anal. 47(6), 4660–4679 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  16. R. Haelterman, J. Petit, H. Bruyninckx, J. Vierendeels, On the non-singularity of the Quasi-Newton-least squares method. J. Comput. Appl. Math. 257, 129–131 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  17. R. Haelterman, B. Lauwens, F. Van Utterbeeck, H. Bruyninckx, J. Vierendeels, On the similarities between the Quasi-Newton least squares method and GMRes. J. Comput. Appl. Math. 273, 25–28 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  18. R. Haelterman, B. Lauwens, H. Bruyninckx, J. Petit, Equivalence of QNLS and BQNLS for affine problems. J. Comput. Appl. Math. 278, 48–51 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  19. R. Haelterman, D. Van Eester, D. Verleyen, Accelerating the solution of a physics model inside a Tokamak using the (Inverse) Column Updating Method. J. Comput. Appl. Math. 279, 133–144 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  20. R. Haelterman, D. Van Eester, S. Cracana, Does anderson always accelerate picard? in 14th Copper Mountain Conference on Iterative Methods (Copper Mountain, USA, 2016)

    Google Scholar 

  21. R. Haelterman, A. Bogaers, J. Degroote, S. Cracana, Coupling of partitioned physics codes with Quasi-Newton methods, in Lecture Notes in Engineering and Computer Science: Proceedings of The International MultiConference of Engineers and Computer Scientists 2017, 15–17 Mar 2017, Hong Kong, pp. 750–755, 2017

    Google Scholar 

  22. C.T. Kelley, Iterative methods for linear and nonlinear equations (Frontiers in Applied Mathematics, SIAM, Philadelphia, 1995)

    Book  MATH  Google Scholar 

  23. V.L.R. Lopes, J.M. Martinez, Convergence properties of the Inverse Column-Updating Method. Optim. Methods Softw. 6, 127–144 (1995)

    Article  Google Scholar 

  24. J.M. Martinez, L.S. Ochi, Sobre dois metodos de broyden. Mathemática Aplicada e Comput. 1(2), 135–143 (1982)

    Google Scholar 

  25. J.M. Martinez, A Quasi-Newton method with modification of one column per iteration. Computing 33, 353–362 (1984)

    Article  MathSciNet  MATH  Google Scholar 

  26. J.M. Martinez, M.C. Zambaldi, An Inverse Column-Updating Method for solving large-scale nonlinear systems of equations. Optim. Methods Softw. 1, 129–140 (1992)

    Article  Google Scholar 

  27. J.M. Martinez, On the convergence of the column-updating method. Comput. Appl. Math. 12(2), 83–94 (1993)

    MathSciNet  MATH  Google Scholar 

  28. J.M. Martinez, Practical Quasi-Newton method for solving nonlinear systems. J. Comput. Appl. Math. 124, 97–122 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  29. S. Turek, J. Hron, Proposal for numerical Benchmarking of Fluid-structure interaction between an elastic object and laminar incompressible flow, in Fluid-Structure Interaction, ed. by H.-J. Bungartz, M. Schäfer, Michael, Series “Modelling, Simulation, Optimisation” Vol. 53 (Springer, Berlin, 2006), pp. 371–385. ISSN:1439-7358

    Google Scholar 

  30. J. Vierendeels, Implicit coupling of partitioned fluid-structure interaction solvers using reduced-order models, in Fluid-Structure Interaction, Modelling, Simulation, Optimization, ed. by H.-J. Bungartz, M. Sch äfer, Lecture Notes in Computer Science Engineering, vol. 53 (Springer, Berlin, 2006), pp. 1–18

    Google Scholar 

  31. J. Vierendeels, L. Lanoye, J. Degroote, P. Verdonck, Implicit coupling of partitioned fluid-structure interaction problems with reduced order models. Comput. Struct. 85, 970–976 (2007)

    Article  Google Scholar 

  32. E. Walhorn, A. Kölke, B. Hübner, D. Dinkler, Fluid-structure coupling within a monolithic model involving free surface flows. Comput. Struct. 83(25), 2100–2111 (2005)

    Article  Google Scholar 

  33. U.M. Yang, A family of preconditioned iterative solvers for sparse linear systems. Ph.D. thesis, Department of Computer Science, University of Illinois, Urbana-Champaign, 1995

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Rob Haelterman .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Haelterman, R., Bogaers, A., Degroote, J. (2018). A Comparison of Different Quasi-Newton Acceleration Methods for Partitioned Multi-Physics Codes. In: Ao, SI., Kim, H., Castillo, O., Chan, AS., Katagiri, H. (eds) Transactions on Engineering Technologies. IMECS 2017. Springer, Singapore. https://doi.org/10.1007/978-981-10-7488-2_11

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-7488-2_11

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-7487-5

  • Online ISBN: 978-981-10-7488-2

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Navigation