2026-04-14T07:10:06Zhttps://recercat.cat/oai/request

oai:recercat.cat:2117/4461862026-01-09T09:42:09Zcom_2072_1033col_2072_452950

Adaptive reduced order modeling to assess peak stresses in heterogeneous arterial sections Gahima, Stephan Stefanati, Marco Rodríguez Matas, José Félix García González, Alberto Díez, Pedro Universitat Politècnica de Catalunya. Departament d'Enginyeria Civil i Ambiental Universitat Politècnica de Catalunya. LACÀN - Mètodes Numèrics en Ciències Aplicades i Enginyeria Àrees temàtiques de la UPC::Matemàtiques i estadística::Anàlisi numèrica::Mètodes numèrics Angiology Numerical analysis Vascular diseases Biomechanical analysis and modeling Cardiovascular models Vascular surgery We introduce an adaptive model reduction approach to compute peak Von Mises stress (pVMS) in heterogeneous arterial sections. The pipeline follows a standard two-phase process: first, we construct the training set of displacement snapshots obtained from the full order model offline, and then we compute pVMS in the online phase. We adaptively enrich the modal representation in critical regions (around the lumen and in calcified areas) using a level-set approach. Optimized for efficient pVMS computation, as a key plaque vulnerability indicator, this technique significantly reduces the computational cost of training machine learning models to classify plaque vulnerability based on pVMS. The authors acknowledge financial support provided by the Ministerio de Ciencia, Innovación y Universidades (MCIN/ AEI/10.13039/501100011033, MICIU/AEI/10.13039/501100011033/ FEDER, UE) through grants PID2022-141957OB-C21, PID2023-153082OB-I00 and CEX2018-000797-S; the Fondazione Regionale per la Ricerca Biomedica (Regione Lombardia), via project ID 3432721; and the Italian Ministry of University and Research (PRIN 2022, grant 2022ZKEP8S). The authors acknowledge Zhongzhao Teng of the University of Cambridge for providing the realistic 2D geometries used in this work. Funding Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. Peer Reviewed Postprint (published version) 2025-11-11 Article Gahima, S. [et al.]. Adaptive reduced order modeling to assess peak stresses in heterogeneous arterial sections. «Computational mechanics», 11 Novembre 2025, 1432-0924 https://hdl.handle.net/2117/446186 10.1007/s00466-025-02713-2 eng https://link.springer.com/article/10.1007/s00466-025-02713-2 info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2022-141957OB-C21/ES/INGENIERIA COMPUTACIONAL BASADA EN DATOS PARA ACTUACION FLEXIBLE/ info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2023-153082OB-I00/ES/HERRAMIENTAS DE INGENIERIA COMPUTACIONAL PARA PROSPECCION EN GEOTERMIA PROFUNDA/ CEX2018-000797-S http://creativecommons.org/licenses/by/4.0/ Open Access Attribution 4.0 International 14 p. application/pdf Springer