Skip to main content
Log in

Automation of primal and sensitivity analysis of transient coupled problems

  • Original Paper
  • Published:
Computational Mechanics Aims and scope Submit manuscript

Abstract

The paper describes a hybrid symbolic–numeric approach to automation of primal and sensitivity analysis of computational models formulated and solved by finite element method. The necessary apparatus for the automation of steady-state, steady-state coupled, transient and transient coupled problems is introduced as combination of a symbolic system, an automatic differentiation (AD) technique and an automatic code generation. For this purpose the paper extends the classical formulation of AD by additional operators necessary for a high abstract description of primal and sensitivity analysis of the typical computational models. An appropriate abstract description for the fully implicit primal and sensitivity analysis of hyperelastic and elasto-plastic problems and a symbolic input for the generation of necessary user subroutines for the two-dimensional, hyperelastic finite element are presented at the end.

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

Access this article

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

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Amberg G, Tonhardt R, Winkler C (1999) Finite element simulations using symbolic computing. Math Comput Simul 49: 257–274

    Article  MathSciNet  Google Scholar 

  2. Bartholomew-Biggs M, Brown S, Christianson B, Dixon L (2000) Automatic differentiation of algorithms. J Comput Appl Math 124(1–2): 171–190

    Article  MATH  MathSciNet  Google Scholar 

  3. Beall MW, Shephard MS (1999) Object-oriented framework for reliable numerical simulations. Eng Comput 15(1): 61–72

    Article  Google Scholar 

  4. Bischof C, Hovland P, Norris B (2002) Implementation of automatic differentiation tools. In: Norris C, Fenwick JB Proceedings of the ACM SIGPLAN workshop on partial evaluation and semantics-based program manipulation. ACM Press, New York

  5. Bischof CH, Buecker HM, Lang B, Rasch A, Risch JW (2003) Extending the functionality of the general-purpose finite element package SEPRAN by automatic differentiation. Int J Numer Methods Eng 58: 2225–2238

    Article  MATH  Google Scholar 

  6. Choi KK, Kim NH (2005) Structural sensitivity analysis and optimization 1, Linear systems. Springer, New York, p 446

    Google Scholar 

  7. Eyheramendy D, Zimmermann Th (1999) Object-oriented symbolic derivation and automatic programming of finite elements in mechanics. Eng Comput 15(1): 12–36

    Article  Google Scholar 

  8. Fritzson P, Fritzson D (1992) The need for high-level programming support in scientific computing applied to mechanical analysis. Comput Struct 45: 387–395

    Article  Google Scholar 

  9. Gonnet G (1986) New results for random determination of equivalence of expression. In: Char BW (ed) Proceedings of 1986 ACM symposium on symbolic and algebraic computation, Waterloo, pp 127–131

  10. Griewank A (2000) Evaluating derivatives: principles and techniques of algorithmic differentiation. SIAM, Philadelphia

    MATH  Google Scholar 

  11. Keulen F, Haftka RT, Kim NH (2005) Review of options for structural design sensitivity analysis. Part 1: linear systems. Comput Methods Appl Mech Eng 194: 3213–3243

    Article  MATH  Google Scholar 

  12. Kleiber M, Antunez H, Hien TH, Kowalczyk P (1997) Parameter sensitivity in nonlinear mechanics. Wiley, New York

    Google Scholar 

  13. Kirby RC, Knepley M, Logg A, Scott LR (2005) Optimizing the evaluation of finite element matrices. SIAM J Sci Comput 27: 741–758

    Article  MATH  MathSciNet  Google Scholar 

  14. Korelc J (1997) Automatic generation of finite-element code by simultaneous optimization of expressions. Theor Comput Sci 187: 231–248

    Article  MATH  Google Scholar 

  15. Korelc J (2001) Hybrid system for multi-language and multi-environment generation of numerical codes. In: Proceedings of the ISSAC’2001 symposium on symbolic and algebraic computation. ACM Press, New York, pp 209–216

  16. Korelc J (2002) Multi-language and multi-environment generation of nonlinear finite element codes. Eng Comput 18: 312–327

    Article  Google Scholar 

  17. Korelc J (2007) AceGen user manual, http://www.fgg.uni-lj.si/symech/

  18. Michaleris P, Tortorelli DA, Vidal CA (1994) Tangent operators and design sensitivity formulations for transient non-linear coupled problems with applications to elastoplasticity. Int J Numer Methods Eng 37: 2471–2499

    Article  MATH  Google Scholar 

  19. Logg A (2007) Automating the finite element method. Arch Comput Methods Eng 14: 93–138

    Article  MATH  MathSciNet  Google Scholar 

  20. Mathematica 6.0, Wolfram Research Inc., http://www.wolfram.com

  21. Pironneau O, Hecht F, Hyaric A (2008) FreeFem++, ftp://www.freefem.org/

  22. Simo JC, Hughes TJR (1998) Computational inelasticity. Springer, New York

    MATH  Google Scholar 

  23. Wang PS (1986) Finger: a symbolic system for automatic generation of numerical programs in finite element analysis. J Symb Comput 2: 305–316

    Article  MATH  Google Scholar 

  24. Zienkiewicz OC, Taylor RL (1991) The finite element method, vols I, II. McGraw Hill, New York

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jože Korelc.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Korelc, J. Automation of primal and sensitivity analysis of transient coupled problems. Comput Mech 44, 631–649 (2009). https://doi.org/10.1007/s00466-009-0395-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00466-009-0395-2

Keywords

Navigation