Reducing dimensionality in topology optimization using adaptive design variable fields

By James K. Guest, Lindsey C. Smith Genut. 2010

138 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/81b6d6259449182255fe635028f0f380b8cf497b

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

Length scale and manufacturability in density-based topology optimization (2016, background): “The density field discretization can be decoupled from the discretization of the state problem [66] which might result in reduction of the optimization time.”
Adaptive topology optimization with independent error control for separated displacement and density fields (2014, methodology): “In the work of Guest and Genut [22], the design variables were adaptively activated and deactivated to reduce the number of design variables actually fed into the optimizer.”
Structural topology optimization based on non-local Shepard interpolation of density field (2011, methodology): “[36–38], in which a mesh-independent physical length scale is adopted for generating more clear topologies, but no additional relations are introduced between the design variables and the den-”
Eliminating beta-continuation from Heaviside projection and density filter algorithms (2011, methodology): “The authors have previously used the term projection method to describe these approaches so as to distinguish them from heuristic filters and to emphasize properties not typically associated with filters, including reduced and adaptable dimensionality of the φ space ( Guest and Smith Genut 2010 ) an”
Topology optimization of structures using meshless density variable approximants (2013, methodology): “It is noted that the problem formulation may be functionally similar to the filtering [9–11] or projection methods [20,24].”
Multiple-Material Topology Optimization of Compliant Mechanisms Created Via PolyJet Three-Dimensional Printing (2014, unknown): “[13–15] for enhancing computational efficiency.”
Improving the efficiency of large scale topology optimization through on‐the‐fly reduced order model construction (2015, background): “They have gained much interest in recent years in various domains, be it in analysis [4]-[7] or optimization [8]-[11].”
Integrated topology optimization with embedded movable holes based on combined description by material density and level sets (2013, background): “constraint approaches [17,18], the higher-order/non-conforming finiteelementmethods [19,20]and theprojectionmethods [21–24].”
Improving multiresolution topology optimization via multiple discretizations (2012, methodology): “Our proposed adaptive approach has some similarity with the adaptive approach of Reference [30] in that both approaches keep the same finite element mesh during the optimization process.”
A nodal variable method of structural topology optimization based on Shepard interpolant (2012, methodology): “It is noted that the idea of using different meshes for discretization of displacement field and design variables was also proposed in a recent paper of Guest and Smith Genut [24].”