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Model Order Reduction for Thermo-Elastic Assembly Group Models

Part of the Lecture Notes in Production Engineering book series (LNPE)


We present two model order reduction approaches based on different modelling strategies for a thermo-elastic assembly group model. Here, we consider the machine stand example given in Chap. 7. The focus is on capturing the structural variability. Therefore, we compare a switched linear systems (SLS) approach based on reduced order models determined by the Balanced Truncation (BT) method and a parametric model order reduction (PMOR) scheme based on an interpolatory projection method via the iterative rational Krylov algorithm (IRKA). In order to avoid the high dimensional coupled thermo-elastic system, additionally a Schur complement representation is applied to exploit the special structure of the one-sided coupling property of the system. The results show that both methods generate relative errors in the range of one per thousand.


  • Iterative Rational Krylov Algorithm (IRKA)
  • Parametric Model Order Reduction (PMOR)
  • Switched Linear Systems (SLS)
  • Balanced Truncation (BT)
  • Tool Slide

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Fig. 8.1
Fig. 8.2


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Correspondence to Norman Lang .

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Lang, N., Saak, J., Benner, P. (2015). Model Order Reduction for Thermo-Elastic Assembly Group Models. In: Großmann, K. (eds) Thermo-energetic Design of Machine Tools. Lecture Notes in Production Engineering. Springer, Cham.

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