PERMAS is an internationally established FE analysis system with users in many countries. It offers powerful capabilities, ultimate computing power and high software reliability. PERMAS enables the engineer to perform comprehensive analyses and simulations in many fields of applications like stiffness analysis, stress analysis, determination of natural modes, dynamic simulations in the time and frequency domain, determination of temperature fields and electromagnetic fields, analysis of anisotropic material like fibre-reinforced composites.

References in zbMATH (referenced in 13 articles )

Showing results 1 to 13 of 13.
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  1. Arregui-Mena, José David; Margetts, Lee; Mummery, Paul M.: Practical application of the stochastic finite element method (2016)
  2. Ferretti, Gianni; Leva, Alberto; Scaglioni, Bruno: Object-oriented modelling of general flexible multibody systems (2014)
  3. Klebanov, Yakov Mordukhovich; Adeyanov, Igor’ Evgen’evich: Solution parallelization of softening plasticity problems (2011)
  4. Tobias, Christoph; Eberhard, Peter: Stress recovery with Krylov-subspaces in reduced elastic multibody systems (2011)
  5. Herrero, José R.; Navarro, Juan J.: Hypermatrix oriented supernode amalgamation (2008)
  6. Herrero, José R.; Navarro, Juan J.: Analysis of a sparse hypermatrix Cholesky with fixed-sized blocking (2007)
  7. Herrero, José R.; Navarro, Juan J.: Sparse hypermatrix Cholesky: customization for high performance (2007)
  8. Meske, R.; Lauber, B.; Schnack, Eckart: A new optimality criteria method for shape optimization of natural frequency problems (2006)
  9. Meske, R.; Sauter, Joachim; Schnack, Eckart: Nonparametric gradient-less shape optimization for real-world applications (2005)
  10. Heitzer, M.: Statical shakedown analysis with temperature-dependent yield condition (2004)
  11. Larrazábal, Germán: A parallel iterative method for the Schur complement system (2004)
  12. Klebanov, I. M.; Davydov, A. N.: A parallel computational method in steady power-law creep (2001)
  13. Challacombe, Matt: A general parallel sparse-blocked matrix multiply for linear scaling SCF theory (2000)