Matteo Lo Verso , Stefano Riva , Carolina Introini , Eric Cervi , Luciana Barucca , Marco Caramello , Matteo Di Prinzio , Francesca Giacobbo , Laura Savoldi , Antonio Cammi
{"title":"Enhancing computational efficiency in nuclear fusion through reduced order modelling: Applications in magnetohydrodynamics","authors":"Matteo Lo Verso , Stefano Riva , Carolina Introini , Eric Cervi , Luciana Barucca , Marco Caramello , Matteo Di Prinzio , Francesca Giacobbo , Laura Savoldi , Antonio Cammi","doi":"10.1016/j.fusengdes.2025.115080","DOIUrl":null,"url":null,"abstract":"<div><div>Magnetohydrodynamics (MHD) studies the dynamics of electrically conducting fluids under the influence of a magnetic field and it is relevant in several nuclear applications. However, the high computational cost of multi-physics MHD simulations poses a challenge. Reduced Order Modelling (ROM) offers a promising alternative, enabling lower-dimensional approximations while preserving accuracy. This allows for a reduction in the computational time and, at the same time, accurate approximations of the intricate physics involved in fusion reactors. However, ROM techniques are relatively new within the MHD framework, and benchmark test cases should be considered in this first stage for verification and validation. Therefore, this study applies the ROM methodology to a MHD scenario to study their potentialities (and eventual criticalities) for this class of problems. The benchmark test case considered in this work is the Backward-Facing Step. The obtained results contribute to assessing the capabilities of ROM methodologies in MHD scenarios, demonstrating their potential to enhance computational efficiency in this field and representing a critical step towards advancing the computational modelling of complex systems in nuclear fusion.</div></div>","PeriodicalId":55133,"journal":{"name":"Fusion Engineering and Design","volume":"216 ","pages":"Article 115080"},"PeriodicalIF":1.9000,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fusion Engineering and Design","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0920379625002777","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NUCLEAR SCIENCE & TECHNOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Magnetohydrodynamics (MHD) studies the dynamics of electrically conducting fluids under the influence of a magnetic field and it is relevant in several nuclear applications. However, the high computational cost of multi-physics MHD simulations poses a challenge. Reduced Order Modelling (ROM) offers a promising alternative, enabling lower-dimensional approximations while preserving accuracy. This allows for a reduction in the computational time and, at the same time, accurate approximations of the intricate physics involved in fusion reactors. However, ROM techniques are relatively new within the MHD framework, and benchmark test cases should be considered in this first stage for verification and validation. Therefore, this study applies the ROM methodology to a MHD scenario to study their potentialities (and eventual criticalities) for this class of problems. The benchmark test case considered in this work is the Backward-Facing Step. The obtained results contribute to assessing the capabilities of ROM methodologies in MHD scenarios, demonstrating their potential to enhance computational efficiency in this field and representing a critical step towards advancing the computational modelling of complex systems in nuclear fusion.
期刊介绍:
The journal accepts papers about experiments (both plasma and technology), theory, models, methods, and designs in areas relating to technology, engineering, and applied science aspects of magnetic and inertial fusion energy. Specific areas of interest include: MFE and IFE design studies for experiments and reactors; fusion nuclear technologies and materials, including blankets and shields; analysis of reactor plasmas; plasma heating, fuelling, and vacuum systems; drivers, targets, and special technologies for IFE, controls and diagnostics; fuel cycle analysis and tritium reprocessing and handling; operations and remote maintenance of reactors; safety, decommissioning, and waste management; economic and environmental analysis of components and systems.