Developmental Approach for Topology Optimization via Multifidelity Analyses and Topological Derivative

A recent tractable gradient-based approach that exploits a new two-point topological derivative is extended here to encompass multifidelity modeling. Handling multidisciplinary responses during structural topology optimization is important to a field that has grown rapidly in the last decade, spurred by additive manufacturing. The cellular division method for topological design is more general than conventional optimality criterion methods used most often in industrial structural topology design; however, it is a discrete approach that is daunting without topological derivatives, due to the curse of dimensionality. Results are presented to address that issue for benchmark test cases using the multifidelity approach with two-point topological derivatives to drive cellular development.

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Publication Details

Journal
AIAA Journal
Published
2026-05-18
DOI
https://doi.org/10.2514/1.j065659
Primary Topic
Topology Optimization in Engineering
Type
article
Field-Weighted Citation Impact
0.00

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article

Developmental Approach for Topology Optimization via Multifidelity Analyses and Topological Derivative

Raymond M. Kolonay, Robert A. Canfield, Marcelo H. Kobayashi
AIAA Journal
Topology Optimization in Engineering
article

Developmental Approach for Topology Optimization via Multifidelity Analyses and Topological Derivative

Raymond M. Kolonay, Robert A. Canfield, Marcelo H. Kobayashi
article en

Abstract

A recent tractable gradient-based approach that exploits a new two-point topological derivative is extended here to encompass multifidelity modeling. Handling multidisciplinary responses during structural topology optimization is important to a field that has grown rapidly in the last decade, spurred by additive manufacturing. The cellular division method for topological design is more general than conventional optimality criterion methods used most often in industrial structural topology design; however, it is a discrete approach that is daunting without topological derivatives, due to the curse of dimensionality. Results are presented to address that issue for benchmark test cases using the multifidelity approach with two-point topological derivatives to drive cellular development.

AIAA Journal
University of Hawaiʻi at Mānoa (US), United States Air Force Research Laboratory (US), Virginia Tech (US)
University of Dayton Research Institute
Industry, innovation and infrastructure
Openalex Percentile: Top 9%
Topology Optimization in Engineering
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