On the construction and use of linear low-dimensional ventilation models

Cao, Shi-Jie; Meyers, Johan

doi:10.1111/j.1600-0668.2012.00771.x

Cited by 50 publications

(31 citation statements)

References 21 publications

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“…There are two main circumstances that need to be considered in a densely populated city. First, during mild seasons, people may adopt natural ventilation as their main ventilation strategy [5][6][7][8], which may increase the incursion of outdoor pollutants to indoor areas through windows [9]. Second, outbreaks of acutely infectious diseases or even the ordinary flu season [10] may result in airborne viruses or biological aerosols in the airflow, which poses a great threat to public health.…”

Section: Introductionmentioning

confidence: 99%

Investigation of interunit dispersion in 2D street canyons: A scaled outdoor experiment

Dai

Mak

Zhang

et al. 2020

Building and Environment

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A B S T R A C TInterunit dispersion problems have been studied previously mainly through on-site measurements, wind tunnel tests, and CFD simulations. In this study, a scaled outdoor experiment was conducted to examine the interunit dispersion characteristics in consecutive two-dimensional street canyons. Tracer gas (CO 2 ) was continuously released to simulate the pollutant dispersion routes between the rooms in street canyons. The wind velocity, wind direction, air temperature, and tracer gas concentrations were monitored simultaneously. Two important parameters, the air exchange rate and reentry ratio, were analyzed to reveal the ventilation performance and interunit dispersion of the rooms in the street canyons. Based on the real-time weather conditions, it was found that the ventilation performance of the source room varied according to the room location. The air exchange rate distribution of the leeward-side room was more stable than that of the windward side. The tracer gas was mainly transported in the vortex direction inside the street canyon, and the highest reentry ratio was observed at the room nearest to the source room along the transportation route. In addition, under real weather conditions, the rooms in the street canyon have a high probability of experiencing a high reentry ratio based on the maximum reentry ratio of each room. This study provides authentic airflow and pollutant dispersion information in the street canyons in an urban environment. The dataset of this experiment can be used to validate further numerical simulations.

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Section: Introductionmentioning

confidence: 99%

Investigation of interunit dispersion in 2D street canyons: A scaled outdoor experiment

Dai

Mak

Zhang

et al. 2020

Building and Environment

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“…Since the early work of Nielsen (1973) in the 1970s, a lot of work has been published on the numerical pre-diction of room airflow, which is governed by recirculation cells, flow separation, and flow attachment (e.g., Awbi, 1989;Jones and Whittle, 1992;Kato et al, 1992;Gan and Awbi, 1994;Nielsen, 1998;van Hooff and Blocken, 2010;Cao and Meyers, 2012;Ramponi and Blocken, 2012). The majority of these studies consisted of CFD simulations of mixing or displacement ventilation, either with or without buoyancy effects.…”

Section: Introductionmentioning

confidence: 99%

On the suitability of steady RANS CFD for forced mixing ventilation at transitional slot Reynolds numbers

2012

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This article presents a detailed numerical study of isothermal forced mixing ventilation driven by a low-velocity (transitional) wall jet using steady computational fluid dynamics (CFD) simulations. It is shown that the numerically obtained room airflow patterns are highly dependent on the chosen turbulence model and large differences with experimentally obtained velocity fields can be present. The renormalization group (RNG) k-ε model, which is commonly used for room airflow modeling, shows the largest deviations from the measured velocities, indicating the care that must be taken when selecting a turbulence model for room airflow prediction. As a result of the different predictions of the flow pattern in the room, large differences are present between the predicted air exchange efficiency obtained with the four tested turbulence models, which can be as high as 44%.

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“…In comparison with 2D modelling, 3D urban flow modelling provides better understanding and much more information about local flow structure, vertical inertia, unsteady dynamics and pollution fluctuations. However, the majority of existing 3D Computational Fluid Dynamics (CFD) urban flow models suffer from an extremely high computational cost and cannot respond rapidly enough for real-time forecasting [17,18]. Model reduction technology is therefore being developed to mitigate the computational cost, since it offers the potential to simulate complex systems with substantially reduced computational requirements.…”

Section: Introductionmentioning

confidence: 99%

“…For example, Wu et al [42] proposed a fast and accurate method to model turbulent flows in a square duct with high Reynolds numbers using improved wall-modelled LES. Cao et al [17] used a discrete Green's function method to derive a low dimensional indoor ventilation model. Liu et al [18] used a fast fluid dynamics and a local searching method to derive a fast model for indoor airflow simulation.…”

Section: Introductionmentioning

confidence: 99%

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A reduced order model for turbulent flows in the urban environment using machine learning

Xiao

Heaney

Mottet

et al. 2019

Building and Environment

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To help create a comfortable and healthy indoor and outdoor environment in which to live, there is a need to understand turbulent air flows within the urban environment. To this end, building on a previously reported method [1], we develop a fast-running Non-Intrusive Reduced Order Model (NIROM) for predicting the turbulent air flows found within an urban environment. To resolve larger scale turbulent fluctuations, we employ a Large Eddy Simulation (LES) model and solve the resulting computational model on unstructured meshes. The objective is to construct a rapid-running NIROM from these results that will have 'similar' dynamics to the original LES model. Based on Proper Orthogonal Decomposition (POD) and machine learning techniques, this Reduced Order Model (ROM) is six orders of magnitude faster than the high-fidelity LES model and we demonstrate how 'similar' it can be to the high-fidelity model by comparing statistical quantities such as the mean flows, Reynolds stresses and probability densities of the velocities. We also include validation of the high-fidelity model against data from wind tunnel experiments. This paper represents a key step towards the use of reduced order modelling for operational purposes with the tantalising possibility of it being used in place of Gaussian plume models, and the potential for greatly improved model fidelity and confidence.

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On the construction and use of linear low-dimensional ventilation models

Cited by 50 publications

References 21 publications

Investigation of interunit dispersion in 2D street canyons: A scaled outdoor experiment

Investigation of interunit dispersion in 2D street canyons: A scaled outdoor experiment

On the suitability of steady RANS CFD for forced mixing ventilation at transitional slot Reynolds numbers

A reduced order model for turbulent flows in the urban environment using machine learning

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