Snaiki, Reda et Mirfakhar, Seyedeh Fatemeh.
2024.
« Multiresolution dynamic mode decomposition approach for wind pressure analysis and reconstruction around buildings ».
Computer-Aided Civil and Infrastructure Engineering.
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Résumé
Accurate wind pressure analysis on high-rise buildings is critical for wind load prediction. However, traditional methods struggle with the inherent com- plexity and multiscale nature of these data. Furthermore, the high cost and practical limitations of deploying extensive sensor networks restrict the data col- lection capabilities. This study addresses these limitations by introducing a novel framework for optimal sensor placement on high-rise buildings. The frame- work leverages the strengths of multiresolution dynamic mode decomposition (mrDMD) for feature extraction and incorporates a novel regularization term within an existing sensor placement algorithm under constraints. This innova- tive term enables the algorithm to consider real-world system constraints during sensor selection, leading to a more practical and efficient solution for wind pressure analysis. mrDMD effectively analyzes the multiscale features of wind pressure data. The extracted mrDMD modes, combined with the enhanced con- strained QR decomposition technique, guide the selection of informative sensor locations. This approach minimizes the required number of sensors while ensur- ing accurate pressure field reconstruction and adhering to real-world placement constraints. The effectiveness of this method is validated using data from a scaled building model tested in a wind tunnel. This approach has the potential to rev- olutionize wind pressure analysis for high-rise buildings, paving the way for advancements in digital twins, real-time monitoring, and risk assessment of wind loads.
| Type de document: | Article publié dans une revue, révisé par les pairs |
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| Professeur: | Professeur Snaiki, Reda |
| Affiliation: | Génie de la construction |
| Date de dépôt: | 30 juill. 2024 18:56 |
| Dernière modification: | 08 août 2024 15:51 |
| URI: | https://espace2.etsmtl.ca/id/eprint/29033 |
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