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However, their implementation remains a major challenge due to, among other things, the need to apply nontrivial stabilization schemes and generate custom quadrature rules. This article introduces the robust and computationally efficient algorithms and data structures comprising an immersed finite element preprocessing framework. The input to the preprocessor consists of a background mesh and one or more geometries defined on its domain. The output is structured into groups of elements with custom quadrature rules formatted such that common finite element assembly routines may be used without or with only minimal modifications. The key to the preprocessing framework is the construction of material topology information, concurrently with the generation of a quadrature rule, which is then used to perform enrichment and generate stabilization rules. While the algorithmic framework applies to a wide range of immersed finite element methods using different types of meshes, integration, and stabilization schemes, the preprocessor is presented within the context of the extended isogeometric analysis. This method utilizes a structured B-spline mesh, a generalized Heaviside enrichment strategy considering the material layout within individual basis functions\u2019 supports, and face-oriented ghost stabilization. Using a set of examples, the effectiveness of the enrichment and stabilization strategies is demonstrated alongside the preprocessor\u2019s robustness in geometric edge cases. Additionally, the performance and parallel scalability of the implementation are evaluated.<\/jats:p>","DOI":"10.1007\/s00366-025-02163-7","type":"journal-article","created":{"date-parts":[[2025,8,18]],"date-time":"2025-08-18T04:08:36Z","timestamp":1755490116000},"page":"3919-3957","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Enriched immersed finite element and isogeometric analysis: algorithms and data structures"],"prefix":"10.1007","volume":"41","author":[{"given":"Nils","family":"Wunsch","sequence":"first","affiliation":[]},{"given":"Keenan","family":"Doble","sequence":"additional","affiliation":[]},{"given":"Mathias R.","family":"Schmidt","sequence":"additional","affiliation":[]},{"given":"Lise","family":"No\u00ebl","sequence":"additional","affiliation":[]},{"given":"John A.","family":"Evans","sequence":"additional","affiliation":[]},{"given":"Kurt","family":"Maute","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,8,18]]},"reference":[{"key":"2163_CR1","unstructured":"(2024) Moris \u2013 multi-physics optimization research and innovation system. https:\/\/github.com\/kkmaute\/moris, accessed: 2024-10-25"},{"key":"2163_CR2","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1016\/j.cma.2012.03.008","volume":"225","author":"C Annavarapu","year":"2012","unstructured":"Annavarapu C, Hautefeuille M, Dolbow JE (2012) A robust Nitsche\u2019s formulation for interface problems. 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