Login / Signup

On the SCD semismooth* Newton method for generalized equations with application to a class of static contact problems with Coulomb friction.

Helmut GfrererMichael MandlmayrJiří V OutrataJan Valdman
Published in: Computational optimization and applications (2022)
In the paper, a variant of the semismooth ∗ Newton method is developed for the numerical solution of generalized equations, in which the multi-valued part is a so-called SCD (subspace containing derivative) mapping. Under a rather mild regularity requirement, the method exhibits (locally) superlinear convergence behavior. From the main conceptual algorithm, two implementable variants are derived whose efficiency is tested via a generalized equation modeling a discretized static contact problem with Coulomb friction.
Keyphrases
  • mental health
  • machine learning
  • deep learning
  • gene expression
  • copy number
  • dna methylation
  • high density