Model Order Reduction Applied to Replicate Blast Wave Interaction with Structure
This research explores the application of model order reduction (MOR) techniques for blast wave propagation and mitigation. Blast waves, with their rapid pressure changes and highly nonlinear behavior, pose significant challenges for predictive modeling. MOR, a mathematical dimensionality reduction...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-02-01
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| Series: | Engineering Proceedings |
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| Online Access: | https://www.mdpi.com/2673-4591/85/1/30 |
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| author | Edison Shehu Giovanni Marchesi Luca Lomazzi Marco Giglio Andrea Manes |
| author_facet | Edison Shehu Giovanni Marchesi Luca Lomazzi Marco Giglio Andrea Manes |
| author_sort | Edison Shehu |
| collection | DOAJ |
| description | This research explores the application of model order reduction (MOR) techniques for blast wave propagation and mitigation. Blast waves, with their rapid pressure changes and highly nonlinear behavior, pose significant challenges for predictive modeling. MOR, a mathematical dimensionality reduction technique, offers a solution by simplifying the complexity of large-scale dynamical systems described by differential equations. These systems can be computationally expensive to solve through conventional numerical schemes. MOR creates a reduced-order model (ROM) that retains the essential features and behavior of the original system but with fewer degrees of freedom. Unlike traditional high-fidelity simulations that are accurate but computationally expensive, MOR allows for multi-query scenarios. This approach significantly reduces computational demands without sacrificing accuracy, making it a valuable tool for engineers and professionals in safety engineering and defense planning. The study also enables the creation of reduced-order models based on high-fidelity simulations of blast wave interactions with structures, promoting their broader adoption in safety planning and structural assessments. |
| format | Article |
| id | doaj-art-a74ddafc4e6844d5a8f30748547036df |
| institution | OA Journals |
| issn | 2673-4591 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Engineering Proceedings |
| spelling | doaj-art-a74ddafc4e6844d5a8f30748547036df2025-08-20T02:24:34ZengMDPI AGEngineering Proceedings2673-45912025-02-018513010.3390/engproc2025085030Model Order Reduction Applied to Replicate Blast Wave Interaction with StructureEdison Shehu0Giovanni Marchesi1Luca Lomazzi2Marco Giglio3Andrea Manes4Departement of Mechanical Engineering, Politecnico di Milano, Via La Masa n.1, 20156 Milan, ItalyDepartement of Mechanical Engineering, Politecnico di Milano, Via La Masa n.1, 20156 Milan, ItalyDepartement of Mechanical Engineering, Politecnico di Milano, Via La Masa n.1, 20156 Milan, ItalyDepartement of Mechanical Engineering, Politecnico di Milano, Via La Masa n.1, 20156 Milan, ItalyDepartement of Mechanical Engineering, Politecnico di Milano, Via La Masa n.1, 20156 Milan, ItalyThis research explores the application of model order reduction (MOR) techniques for blast wave propagation and mitigation. Blast waves, with their rapid pressure changes and highly nonlinear behavior, pose significant challenges for predictive modeling. MOR, a mathematical dimensionality reduction technique, offers a solution by simplifying the complexity of large-scale dynamical systems described by differential equations. These systems can be computationally expensive to solve through conventional numerical schemes. MOR creates a reduced-order model (ROM) that retains the essential features and behavior of the original system but with fewer degrees of freedom. Unlike traditional high-fidelity simulations that are accurate but computationally expensive, MOR allows for multi-query scenarios. This approach significantly reduces computational demands without sacrificing accuracy, making it a valuable tool for engineers and professionals in safety engineering and defense planning. The study also enables the creation of reduced-order models based on high-fidelity simulations of blast wave interactions with structures, promoting their broader adoption in safety planning and structural assessments.https://www.mdpi.com/2673-4591/85/1/30blast waveextreme loading conditionmodel order reductionPODneural network |
| spellingShingle | Edison Shehu Giovanni Marchesi Luca Lomazzi Marco Giglio Andrea Manes Model Order Reduction Applied to Replicate Blast Wave Interaction with Structure Engineering Proceedings blast wave extreme loading condition model order reduction POD neural network |
| title | Model Order Reduction Applied to Replicate Blast Wave Interaction with Structure |
| title_full | Model Order Reduction Applied to Replicate Blast Wave Interaction with Structure |
| title_fullStr | Model Order Reduction Applied to Replicate Blast Wave Interaction with Structure |
| title_full_unstemmed | Model Order Reduction Applied to Replicate Blast Wave Interaction with Structure |
| title_short | Model Order Reduction Applied to Replicate Blast Wave Interaction with Structure |
| title_sort | model order reduction applied to replicate blast wave interaction with structure |
| topic | blast wave extreme loading condition model order reduction POD neural network |
| url | https://www.mdpi.com/2673-4591/85/1/30 |
| work_keys_str_mv | AT edisonshehu modelorderreductionappliedtoreplicateblastwaveinteractionwithstructure AT giovannimarchesi modelorderreductionappliedtoreplicateblastwaveinteractionwithstructure AT lucalomazzi modelorderreductionappliedtoreplicateblastwaveinteractionwithstructure AT marcogiglio modelorderreductionappliedtoreplicateblastwaveinteractionwithstructure AT andreamanes modelorderreductionappliedtoreplicateblastwaveinteractionwithstructure |