Augmented state estimation of urban settings using on-the-fly sequential Data Assimilation

Villanueva, L.; Valero, M.M.; Glumac, A. Šarkić; Meldi, M.

doi:10.1016/j.compfluid.2023.106118

Computers & Fluids

2024

DOI: 10.1016/j.compfluid.2023.106118

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Augmented state estimation of urban settings using on-the-fly sequential Data Assimilation

L. Villanueva,

M.M. Valero,

A. Šarkić Glumac

et al.

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2024

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Cited by 3 publications

References 49 publications

(80 reference statements)

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Statistical Inference of Upstream Turbulence Intensity for the Flow Around a Bluff Body with Massive Separation

Moussie,

Errante,

Meldi

2024

Flow Turbulence Combust

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The Benchmarck on the Aerodynamics of a Rectangular 5:1 Cylinder is studied using a data-driven technique which bridges numerical simulation and available experimental results. Because of intrinsic features of the tools used for investigation, in particular in terms of set-up and boundary conditions, significant discrepancies have been observed in the literature when comparing experimental and numerical results. An approach based on the Ensemble Kalman Filter is here used to optimize a synthetic turbulent inlet used as boundary condition in the numerical calculation, in order to reduce the discrepancy with the available experiments. The data-driven method successfully optimizes the boundary condition features, which produce a significant improvement of the accuracy in the prediction of the flow. These findings open perspectives of application towards the analysis of realistic cases, where boundary conditions are complex and usually unknown.

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Statistical Inference of Upstream Turbulence Intensity for the Flow Around a Bluff Body with Massive Separation

Moussie,

Errante,

Meldi

2024

Flow Turbulence Combust

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show abstract

Review of OpenFOAM applications in the computational wind engineering: from wind environment to wind structural engineering

Ricci

2024

Meccanica

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The use of computational fluid dynamics (CFD) in the wind engineering (WE) is generally defined as computational wind engineering (CWE). Since its foundation in 2004, the use of OpenFOAM in CWE has been increasing progressively and covers nowadays a wide range of topics, from wind environment to wind structural engineering. This paper was drafted in response to the invitation from the organizers of the 18th OpenFOAM workshop held in Genoa (Italy) on 11–14 July 2023, when a technical session on Civil Engineering and Wind Engineering was organized. In this paper the author briefly reviews the history of WE and surveys the evolution, methods, and future challenges of OpenFOAM in the CWE. Topics are here regrouped into three main research areas and discussed from a physical, engineering and purely computational perspective. The study does not cover the Wind Energy and related topics, since this can be considered nowadays as a stand-alone subfield of the WE. This review confirms that OpenFOAM is a versatile tool widely used for WE applications that often require new models to be developed ad hoc by CFD users. It can be coupled easily with numerical weather prediction models for mesoscale-microscale wind and thermal studies, with building energy simulation models to determine the energy demand, with finite element method for structural engineering design. OpenFOAM represents an extraordinary opportunity for all CFD users worldwide to share codes and case studies, to explore the potential of new functionalities and strengthen the network within the CFD community.

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Multigrid sequential data assimilation for the Large Eddy Simulation of a massively separated bluff-body flow

Moldovan,

Mariotti,

Cordier

et al. 2024

Computers & Fluids

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Augmented state estimation of urban settings using on-the-fly sequential Data Assimilation

Cited by 3 publications

References 49 publications

Statistical Inference of Upstream Turbulence Intensity for the Flow Around a Bluff Body with Massive Separation

Statistical Inference of Upstream Turbulence Intensity for the Flow Around a Bluff Body with Massive Separation

Review of OpenFOAM applications in the computational wind engineering: from wind environment to wind structural engineering

Multigrid sequential data assimilation for the Large Eddy Simulation of a massively separated bluff-body flow

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