On the feasibility of affordable high-fidelity CFD simulations for indoor environment design and control

Morozova, Nina; Trias, F. X.; Capdevila, Roser; Segarra, Carlos David Pérez; Oliva, A.

doi:10.1016/j.buildenv.2020.107144

Cited by 33 publications

(23 citation statements)

References 47 publications

(60 reference statements)

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“…Chen et al (2018) used a grid of 4 × 10 6 control volumes for an accurate simulation of an office room with a ceiling fan. Hence, high computing cost prevents CFD from becoming the primary tool for indoor environmental simulations ( Morozova, Trias, Capdevila, Pérez-Segarra, & Oliva, 2020 ).…”

Section: Discussionmentioning

confidence: 99%

Assessing and controlling infection risk with Wells-Riley model and spatial flow impact factor (SFIF)

Guo

Qian

Sun

et al. 2021

Sustainable Cities and Society

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Section: Discussionmentioning

confidence: 99%

Assessing and controlling infection risk with Wells-Riley model and spatial flow impact factor (SFIF)

Guo

Qian

Sun

et al. 2021

Sustainable Cities and Society

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“…In our previous work [6], we studied the feasibility of affordable, fast, and high-fidelity CFD simulations for indoor environmental applications, considering two representative test cases and a wide range of numerical setups. We considered three possible building applications: conceptual design, detailed design, and MPC.…”

Section: Antecedentsmentioning

confidence: 99%

“…As the output parameters of the model, we use average Nusselt number on the hot wall -< Nu >, jet separation pointx sep , average kinetic energy -< E >, average enstrophy -< Ω >, and the average temperature of the cavity. The jet separation point is a point at the top cavity wall, where the wall-shear stress < τ W > is equal to zero, as shown in the equation (6). Other flow parameters are calculated using equations (4) - (5).…”

Section: Data Generationmentioning

confidence: 99%

“…Its high computational cost prevents CFD from becoming the primary design tool for building applications, and it is mostly used for research or particular high-end building design. To become a primary design tool, CFD is required to provide sufficient accuracy in capturing flow properties, be fast, and fit into an office computer [6]. Over the last decade, several attempts to reduce the computational cost of CFD for indoor environmental applications have been made.…”

Section: Introductionmentioning

confidence: 99%

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Investigating The Capabilities Of CFD-Based Data-Driven Models For Indoor Environmental Design And Control

Morozova¹,

Trias²,

Capdevila³

et al. 2021

14th WCCM-ECCOMAS Congress

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In this work, we study the accuracy of CFD-based data-driven models, which predict comfortrelated flow parameters in a ventilated cavity with a heated floor. We compare the computational cost and accuracy of three different models, namely artificial neural network, support vector regression, and gradient boosting regression. The tested scenarios include short and long cavities with different inlet velocities. Among the studied frameworks, the artificial neural network provides the most accurate predictions for most of the tested flow configurations. However, test configurations with jet separation and a secondary vortex are more difficult to predict correctly; thus more high-fidelity data is required in order to construct a more robust and reliable model.

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“…For some specific ambits, many of them have to be evaluated in order to find out the one that is best performing in terms of prefixed requirements fulfilling. The cost of such a procedure can easily become unaffordable, in particular when the dimension of the problem is big enough (see, e.g., [10]). Typical applications where such a difficulty is often arising are, for example, shape optimization problems, uncertainty quantification studies or optimal control frameworks.…”

Section: Introductionmentioning

confidence: 99%

A segregated reduced order model of a pressure-based solver for turbulent compressible flows

Zancanaro¹,

Stabile²,

Rozza³

2022

Preprint

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This article provides a reduced order modelling framework for turbulent compressible flows discretized by the use of finite volume approaches. The basic idea behind this work is the construction of reduced order models capable of providing fully consistent solutions with respect to the high fidelity flow fields. Full order solutions are often obtained through the use of segregated solvers, employing slightly modified conservation laws so that they can be decoupled and then solved one at a time. Classical reduction architectures, on the contrary, rely on the Galerkin projection of a complete Navier-Stokes system to be projected all at once, causing a mild discrepancy with the high order solutions. In this article we rely on segregated reduced order algorithms for the resolution of turbulent and compressible flows in the context of physical and geometrical parameters. At the full order level turbulence is modeled using an eddy viscosity approach. Since there are a variety of different turbulence models for the approximation of this supplementary viscosity, one of the aims of this work is to provide reduced order models which are independent on this selection. This goal is reached by the application of hybrid methods where Navier-Stokes equations are projected in a standard way while the viscosity field is approximated by the use of data-driven interpolation methods or by the evaluation of a properly trained neural network. By exploiting the aforementioned expedients it is possible to reduced the computational cost associated wit fluid flow problems characterized by high Reynolds numbers and elevated Mach numbers.

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On the feasibility of affordable high-fidelity CFD simulations for indoor environment design and control

Cited by 33 publications

References 47 publications

Assessing and controlling infection risk with Wells-Riley model and spatial flow impact factor (SFIF)

Assessing and controlling infection risk with Wells-Riley model and spatial flow impact factor (SFIF)

Investigating The Capabilities Of CFD-Based Data-Driven Models For Indoor Environmental Design And Control

A segregated reduced order model of a pressure-based solver for turbulent compressible flows

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