Material distribution topology optimization for boundary-effect-dominated problems: a reviewVisa övriga samt affilieringar
2026 (Engelska)Ingår i: Structural and multidisciplinary optimization (Print), ISSN 1615-147X, E-ISSN 1615-1488, Vol. 69, nr 4, artikel-id 102Artikel, forskningsöversikt (Refereegranskat) Published
Abstract [en]
This review focuses on material distribution-based topology optimization methods for boundary-effect-dominated problems. More precisely, it addresses problems where the behavior at or near the boundaries of the domain significantly influences the physics, such as problems involving boundary layers or the skin effect. While traditional topology optimization techniques have been highly successful in idealized settings, boundary-sensitive problems introduce unique challenges. We survey the historical development of relevant ideas, including fictitious-domain methods and filtering techniques, and provide a detailed account of modern approaches for handling boundary effects. Key topics include cascades of filters, multi-field representations, and methods for controlling length scale and interface sharpness. We also review specialized strategies for pressure and thermal loads, as well as recent advances in the design of coated structures and impedance-based modeling of boundary layers. This article aims to provide a comprehensive and structured overview of the field.
Ort, förlag, år, upplaga, sidor
Springer Nature, 2026. Vol. 69, nr 4, artikel-id 102
Nyckelord [en]
Boundary-effect-dominated problems, Coated structures, Design-dependent loads, Implicit boundary representation, Material distribution, Problems with layers, Topology optimization
Nationell ämneskategori
Datavetenskap (datalogi)
Identifikatorer
URN: urn:nbn:se:umu:diva-252210DOI: 10.1007/s00158-026-04287-wISI: 001731491500001Scopus ID: 2-s2.0-105035547296OAI: oai:DiVA.org:umu-252210DiVA, id: diva2:2055967
Forskningsfinansiär
Vetenskapsrådet, 2022-03783eSSENCE - An eScience Collaboration2026-04-272026-04-272026-04-27Bibliografiskt granskad