Efficient use of iterative solvers in nested topology optimization

By Oded Amir, Mathias Stolpe, Ole Sigmund. 2010

100 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Computational Theory and Mathematics, Mechanics of Materials

View Paper: https://www.semanticscholar.org/paper/4cfc881b6522b8f7994b589599862c4852c3303e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Civil and Structural Engineering

In Computational Theory and Mathematics

In Mechanics of Materials

Citations in the corpus

Efficient generation of large-scale pareto-optimal topologies (2013, methodology): “Finally, a nested approach was proposed in [17] where by choosing convergence criteria (for the iterative solver) that are better tuned to the optimization objective (and sensitivities), it was shown that one can reduce the computational cost by about 60% without losing on accuracy.”
A survey of structural and multidisciplinary continuum topology optimization: post 2000 (2014, methodology): “Amir et al. (2009, 2010), demonstrated more efficient use of iterative solvers in nested topology optimization in addition to an approximate reanalysis procedure where FEA is performed only at certain intervals of iteration and approximate reanalysis is used otherwise.”
Single-loop system reliability-based topology optimization considering statistical dependence between limit-states (2011, unknown): “For example, researchers make use of powerful computing resources such as parallel computing (Borrvall and Petersson 2001; Evgrafov et al. 2008), approximation procedure (Amir et al. 2009), or fast iterative solvers (Wang et al. 2007; Amir et al. 2010).”
Improving multiresolution topology optimization via multiple discretizations (2012, methodology): “These approaches [4–13] can be broadly divided into three groups: (1) employing powerful computing resources; (2) introducing efficient solution”
Improving the efficiency of large scale topology optimization through on‐the‐fly reduced order model construction (2015, methodology): “[14] proposed methods based on the use of Krylov subspaces.”
A multi-resolution method for 3D multi-material topology optimization (2015, unknown): “…cost of the finite element analysis can be done in a number of ways, by introducing parallel computing [28–31], by employing fast iterative solver [32,33], by performing FE analysis after certain intervals [34,35] or by reducing the number of degrees of freedom in the FE model [36–39].”