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Incremental sampling methods for multi-fidelity surrogate modeling: Application on a furnace operating in MILD combustion conditions

Title: Incremental sampling methods for multi-fidelity surrogate modeling: Application on a furnace operating in MILD combustion conditions
Authors: Özden, Aysu; Procacci, Alberto; Galassi, Riccardo Malpica; Contino, Francesco; Parente, Alessandro
Source: Applied thermal engineering, 246
Publication Year: 2024
Collection: DI-fusion : dépôt institutionnel de l'Université libre de Bruxelles (ULB)
Subject Terms: Sciences de l'ingénieur; Technologie des autres industries; Co-Kriging; Digital twin; Manifold alignment; Multi-fidelity ROM; Proper orthogonal decomposition
Description: This study introduces a framework for developing a multi-fidelity reduced order model (MF-ROM) of a combustion furnace operating under Moderate and Intense Low-oxygen Dilution (MILD) conditions. It integrates Proper Orthogonal Decomposition for data compression, Procrustes manifold alignment for fidelity transfer, and CoKriging for interpolation. Design parameters such as air injector diameter, fuel composition, and equivalence ratio were used to generate two- and three-dimensional simulations and build the MF-ROM. Additionally, the key question concerning the optimal number of high-fidelity simulations to balance accuracy and training cost is addressed when building the MF-ROM. Through incremental sampling strategies, it is demonstrated that around half of the training cost can be conserved while maintaining comparable error values. ; SCOPUS: ar.j ; info:eu-repo/semantics/published
Document Type: article in journal/newspaper
File Description: 1 full-text file(s): application/pdf
Language: English
Relation: uri/info:doi/10.1016/j.applthermaleng.2024.122902; uri/info:pii/S1359431124005702; uri/info:scp/85188626221; https://dipot.ulb.ac.be/dspace/bitstream/2013/373857/3/Ozdenetal_ATE_2024.pdf
Availability: https://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/373857; https://dipot.ulb.ac.be/dspace/bitstream/2013/373857/3/Ozdenetal_ATE_2024.pdf
Accession Number: edsbas.50A83B34
Database: BASE