Multifidelity Topology Optimization with Runtime Verification and Acceptance Control: Benchmark Study in 2D and 3D.
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| Title: | Multifidelity Topology Optimization with Runtime Verification and Acceptance Control: Benchmark Study in 2D and 3D. |
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| Authors: | Tatke, Nikhil1 (AUTHOR) nikhil.tatke@polsl.pl, Kaczmarczyk, Jarosław1 (AUTHOR) |
| Source: | Materials (1996-1944). Feb2026, Vol. 19 Issue 4, p769. 17p. |
| Subjects: | Discretization methods, Computer performance |
| Abstract: | Topology optimization using density-based approaches often requires high-resolution meshes to achieve reliable compliance evaluation and robustness against mesh dependency. However, increasing the problem sizes—especially in 3D—results in prohibitively expensive computation times. Coarse-mesh approaches significantly accelerate runtimes; however, they also introduce discretization errors that can guide the optimizer towards incorrect topology families if left unregulated. To address this issue, a multifidelity framework with acceptance control was developed that enables runtime verification and explicitly manages the optimizer state. The main idea is to use coarse discretizations to generate new design proposals and transfer candidate designs to fine discretizations at periodic intervals for verification. Proposals are then accepted or rejected using a best-referenced criterion; if verification fails, the optimizer reverts to the best verified state. The proposed framework balances fine-discretization accountability with coarse-discretization efficiency through configurable verification schedules and a cleanup phase. The framework is evaluated on standard 2D and 3D structural benchmark problems with deterministic load perturbations, and performance is assessed in terms of final verified compliance, wall-clock runtime, acceptance rate, and gray fraction. [ABSTRACT FROM AUTHOR] |
| Copyright of Materials (1996-1944) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 191972910 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Multifidelity Topology Optimization with Runtime Verification and Acceptance Control: Benchmark Study in 2D and 3D. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Tatke%2C+Nikhil%22">Tatke, Nikhil</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> nikhil.tatke@polsl.pl</i><br /><searchLink fieldCode="AR" term="%22Kaczmarczyk%2C+Jarosław%22">Kaczmarczyk, Jarosław</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Materials+%281996-1944%29%22">Materials (1996-1944)</searchLink>. Feb2026, Vol. 19 Issue 4, p769. 17p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Discretization+methods%22">Discretization methods</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+performance%22">Computer performance</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Topology optimization using density-based approaches often requires high-resolution meshes to achieve reliable compliance evaluation and robustness against mesh dependency. However, increasing the problem sizes—especially in 3D—results in prohibitively expensive computation times. Coarse-mesh approaches significantly accelerate runtimes; however, they also introduce discretization errors that can guide the optimizer towards incorrect topology families if left unregulated. To address this issue, a multifidelity framework with acceptance control was developed that enables runtime verification and explicitly manages the optimizer state. The main idea is to use coarse discretizations to generate new design proposals and transfer candidate designs to fine discretizations at periodic intervals for verification. Proposals are then accepted or rejected using a best-referenced criterion; if verification fails, the optimizer reverts to the best verified state. The proposed framework balances fine-discretization accountability with coarse-discretization efficiency through configurable verification schedules and a cleanup phase. The framework is evaluated on standard 2D and 3D structural benchmark problems with deterministic load perturbations, and performance is assessed in terms of final verified compliance, wall-clock runtime, acceptance rate, and gray fraction. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Materials (1996-1944) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=191972910 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/ma19040769 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 17 StartPage: 769 Subjects: – SubjectFull: Discretization methods Type: general – SubjectFull: Computer performance Type: general Titles: – TitleFull: Multifidelity Topology Optimization with Runtime Verification and Acceptance Control: Benchmark Study in 2D and 3D. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Tatke, Nikhil – PersonEntity: Name: NameFull: Kaczmarczyk, Jarosław IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 02 Text: Feb2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 19961944 Numbering: – Type: volume Value: 19 – Type: issue Value: 4 Titles: – TitleFull: Materials (1996-1944) Type: main |
| ResultId | 1 |
