Evaluation of mean velocity and mean speed for test ventilated room from RANS and LES CFD modeling

Ivanov, Nikolay; Zasimova, Marina; Смирнов, Е. М.; Markov, Detelin

doi:10.1051/e3sconf/20198502004

Cited by 6 publications

(4 citation statements)

References 16 publications

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“…However, for multi-jet configuration considered in the study, it is not possible to use less-empirical scale-resolving simulation due to enormous computational resources required. From the literature data [39,40], it is evident that a k-ε turbulence model and the baseline SST k-ω model accurately predict jet flows and qualitatively reproduce separation zones behavior that gave a basis for the turbulence model choice in the current computations.…”

Section: Computational Aspectsmentioning

confidence: 83%

“…To evaluate the thermal comfort indices (and DR in particular), the time-averaged velocity magnitude, <V>, called the mean "speed" distributions, must be used [42]. It is known that in case of large velocity fluctuations that is detected for the test classroom, both in the experiments and in the unsteady computations, the "speed" values could be much higher than the "velocity" values [40].…”

Section: Rans-based Draught Rate (Dr) Evaluationmentioning

confidence: 99%

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On the Procedure of Draught Rate Assessment in Indoor Spaces

et al. 2020

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The objective of the paper is to demonstrate the importance of the unsteady Computational Fluid Dynamics (CFD) simulations and long-term measurements for the reliable assessment of thermal comfort indoors, for proper categorization of the indoor thermal environment and for identifying the reasons for complaints due to draught discomfort. Numerical simulations and experimental measurements were applied in combination to study ventilation in a field laboratory, a university classroom with a controlled indoor environment. Strong unsteadiness of the airflow was registered both in the unsteady RANS results and the real-scale long-term velocity data measured with thermo anemometer. Low-frequency high-amplitude velocity fluctuations observed lead to substantial time variation of the draught rate. In case of categorization of a thermal environment, the point measurements or steady-state RANS computations would lead to wrong conclusions as well as they cannot be used for identification of the reasons for people’s complaints due to draught discomfort if strong unsteadiness of the airflow exists. It is demonstrated that the length of the time interval for draught rate (DR) assessment may not be universal if low-frequency high-amplitude pulsations are present in the room airflow.

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Section: Computational Aspectsmentioning

confidence: 83%

Section: Rans-based Draught Rate (Dr) Evaluationmentioning

confidence: 99%

On the Procedure of Draught Rate Assessment in Indoor Spaces

et al. 2020

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“…With a few exceptions, the studies under consideration share many characteristics. The Wall-Adapting Local Eddy-viscosity Model LES (WALE-LES) was used in most cases, except one research group that preferred the Wall Modelled LES (WM-LES) [21,[35][36][37][38].…”

Section: Sub-grid Quality Indicatorsmentioning

confidence: 99%

A Review of Large-Eddy Simulation Cell Size Requirements for Indoor Flows

Szodrai

2023

Buildings

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Nowadays computational fluid dynamics now assists ventilation system designers and architects in understanding the induced flow behaviour in the indoor environment. The use of large-eddy simulation is a novel methodology for these types of assessments. The method requires that the computational domain be adequately discretized in order to resolve the majority of the flow. The last five years of publications of Elsevier, SAGE, and Multidisciplinary Digital Publishing Institute were screened. Indoor flow categories were utilized to assess the differences. Based on the papers reviewed, the cell size requirement was considered as a key factor of computational demand. Specifications were made for each type of indoor flow simulation.

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“…Most of the contributions presented RANS simulation results, and among others, PhD theses by Bennetsen [18] and Voight [19] provided the most complete sets of RANS data under conditions of the test [17]. Recent contributions [20,21] presented accurate RANS and wall-modeled LES (WMLES) data on mixing ventilation in the test room [17].…”

Section: Introductionmentioning

confidence: 99%

Unsteady RANS Simulation of Air Distribution in a Ventilated Classroom with Numerous Jets

et al. 2019

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The study is devoted to the Unsteady Reynolds-Averaged Navies-Stokes (URANS) simulation of ventilation in an isothermal room with numerous jets supplied from ceiling diffusers. The computations of the airflow under the test conditions considered were carried out in the classroom of the Technical University of Sofia with no occupants. The room floor has a simple rectangular form, but several columns, beams, window sills, and four radiators are located inside the room that makes the geometry more complex. Air is supplied to the room through four ceiling fan coils, the Reynolds number is 2×104. Calculations were carried out using the ANSYS Fluent 18.2 software with the standard k-ε turbulence model chosen. Computational meshes of up to 33 million hexahedral cells clustered to the inlet and outlet sections were used. The main aim of the study presented is to analyze and discuss the complicated 3D flow structure in the room and to give foundation for future measurements of air velocity field in the room.

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Evaluation of mean velocity and mean speed for test ventilated room from RANS and LES CFD modeling

Cited by 6 publications

References 16 publications

On the Procedure of Draught Rate Assessment in Indoor Spaces

On the Procedure of Draught Rate Assessment in Indoor Spaces

A Review of Large-Eddy Simulation Cell Size Requirements for Indoor Flows

Unsteady RANS Simulation of Air Distribution in a Ventilated Classroom with Numerous Jets

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