TY  - GEN
AU  - Villanueva, Lucas
AU  - Martinez Valero, Miguel
AU  - Šarkić Glumac, Anina
AU  - Meld, Marcello
PY  - 2023
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/3291
AB  - A data-driven investigation of the flow around a high-rise building is per- formed combining heterogeneous experimental samples and RANS CFD. The coupling is performed using techniques based on the Ensemble Kalman Filter (EnKF), including advanced manipulations such as localization and inflation. The augmented state estimation obtained via EnKF has also been employed to improve the predictive features of the model via an optimization of the five free global model constant of the K − ε turbulence model used to close the equations. The optimized values are very far from the classical values prescribed as general recommendations and implemented in codes, but also different from other data-driven analyses reported in the literature. The re- sults obtained with this new optimized parametric description show a global improvement for both the velocity field and the pressure field. In addition, some topological improvement for the flow organization are observed down- stream, far from the location of the sensors.
T2  - arXiv preprint arXiv:2301.11195
T1  - Augmented state estimation of urban settings using intrusive sequential Data Assimilation
VL  - 1/26
DO  - 10.48550/arXiv.2301.11195
ER  - 

@misc{
author = "Villanueva, Lucas and Martinez Valero, Miguel and Šarkić Glumac, Anina and Meld, Marcello",
year = "2023",
abstract = "A data-driven investigation of the flow around a high-rise building is per- formed combining heterogeneous experimental samples and RANS CFD. The coupling is performed using techniques based on the Ensemble Kalman Filter (EnKF), including advanced manipulations such as localization and inflation. The augmented state estimation obtained via EnKF has also been employed to improve the predictive features of the model via an optimization of the five free global model constant of the K − ε turbulence model used to close the equations. The optimized values are very far from the classical values prescribed as general recommendations and implemented in codes, but also different from other data-driven analyses reported in the literature. The re- sults obtained with this new optimized parametric description show a global improvement for both the velocity field and the pressure field. In addition, some topological improvement for the flow organization are observed down- stream, far from the location of the sensors.",
journal = "arXiv preprint arXiv:2301.11195",
title = "Augmented state estimation of urban settings using intrusive sequential Data Assimilation",
volume = "1/26",
doi = "10.48550/arXiv.2301.11195"
}

Villanueva, L., Martinez Valero, M., Šarkić Glumac, A.,& Meld, M.. (2023). Augmented state estimation of urban settings using intrusive sequential Data Assimilation. in arXiv preprint arXiv:2301.11195, 1/26.
https://doi.org/10.48550/arXiv.2301.11195

Villanueva L, Martinez Valero M, Šarkić Glumac A, Meld M. Augmented state estimation of urban settings using intrusive sequential Data Assimilation. in arXiv preprint arXiv:2301.11195. 2023;1/26.
doi:10.48550/arXiv.2301.11195 .

Villanueva, Lucas, Martinez Valero, Miguel, Šarkić Glumac, Anina, Meld, Marcello, "Augmented state estimation of urban settings using intrusive sequential Data Assimilation" in arXiv preprint arXiv:2301.11195, 1/26 (2023),
https://doi.org/10.48550/arXiv.2301.11195 . .