scholarly journals CFD Simulation Analysis on Make-up Air Supply by Distance from Cookstove for Cooking-Generated Particle

2020 ◽  
Vol 17 (21) ◽  
pp. 7799
Author(s):  
Hyungkeun Kim ◽  
Kyungmo Kang ◽  
Taeyeon Kim
Keyword(s):  
Fluid Dynamics ◽  
Cfd Simulation ◽  
Simulation Analysis ◽  
Dynamics Simulation ◽  
Living Room ◽  
Computational Fluid Dynamics Simulation ◽  
Apartment House ◽  
Indoor Airflow ◽  
Contaminant Source ◽  
Air Supply

Indoor cooking is the main cause of particulate matter (PM) within residential houses along with smoking. Even with the range hood turned on, cooking-generated PM can spread quickly into the living room due to the heat generated by the cookstove. In order to improve the PM spread prevention performance of the range hood, a supply of make-up air is needed. Generally, make-up air is supplied through a linear diffuser between the kitchen and living room. In such cases, it is necessary to determine the appropriate location of the supply diffuser. This study evaluates the spread of PM according to different locations of the supply diffuser, which feeds in make-up air. For this purpose, indoor airflow and PM spread were analyzed through CFD (Computational Fluid Dynamics) simulation analysis. By changing the location of the supply diffuser from the contaminant source, PM concentration was analyzed in the kitchen and living room of an apartment house in Korea. Based on the results, the optimal installation location was determined. In this study, 1.5 m from the source was the most effective location of make-up air supply to prevent the spread of cooking-generated particles.

scholarly journals Computational Fluid Dynamics Simulation of Airflow and Air Pattern in the Living Room for Reducing Coronavirus Exposure

2021 ◽  
Author(s):  
Majid Bayatian ◽  
Khosro Ashrafi ◽  
Zahra Amiri ◽  
Elahe Jafari
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Indoor Air ◽  
Cfd Simulation ◽  
Fluid Dynamic ◽  
Dynamics Simulation ◽  
Living Room ◽  
Air Velocity ◽  
Cfd Validation ◽  
Airflow Pattern

Abstract Viruses can be transmitted in indoor environments. Important factors in Indoor Air Quality (IAQ) are air velocity, relative humidity, temperature, and airflow pattern and Computational fluid dynamics (CFD) can use for IAQ assessment. The objective of this study is to CFD simulation in the living room to the prediction of the air pattern and air velocity. A computational fluid dynamic model was applied for airflow pattern and air velocity simulation. For simulation, GAMBIT, FLUENT, and CFD post software were used as preprocessing, processing, and post-processing, respectively. CFD validation was carried out by comparing the computed data with the experimental measurements. The final mesh number was set to 1,416,884 elementary cells and SIMPLEC algorithm was used for pressure-velocity coupling. PERSTO, and QUIK schemes have been used for the pressure terms, and the other variables, respectively. Simulations were carried out in ACH equals 3, 6 and 8 in four lateral walls. The maximum error and root mean square error from the air velocity were 14% and 0.10, respectively. Terminal settling velocity and relaxation time were equal to 0.302 ×10− 2 m/s and 0.0308 ×10− 2 s for 10 µm diameter particles, respectively. The stopping distance was 0.0089m and 0.011m for breathing and talking, respectively. The maximum of mean air velocity is in scenario 4 with ACH = 8 that mean air velocity is equal to 0.31 in 1.1m height, respectively. The results of this study showed that avoiding family gatherings is necessary for exposure control and suitable airflow and pattern can be improving indoor air conditions.

scholarly journals High-speed prediction of computational fluid dynamics simulation in crystal growth

CrystEngComm ◽  
2018 ◽  
Vol 20 (41) ◽  
pp. 6546-6550 ◽  
Author(s):  
Yosuke Tsunooka ◽  
Nobuhiko Kokubo ◽  
Goki Hatasa ◽  
Shunta Harada ◽  
Miho Tagawa ◽  
...  
Keyword(s):  
Machine Learning ◽  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
High Speed ◽  
Cfd Simulation ◽  
Large Diameter ◽  
Dynamics Simulation ◽  
Computational Fluid Dynamics Simulation ◽  
High Quality ◽  
Speed Prediction

The combination of the CFD simulation and machine learning thus makes it possible to determine optimized parameters for high-quality and large-diameter crystals.

Computational Fluid Dynamics Simulation of Steel Bars Cooling by Free Convection and Thermal Radiation

2015 ◽  
Vol 798 ◽  
pp. 170-174
Author(s):  
Paulo Henrique Terenzi Seixas ◽  
Paul Campos Santana Silva ◽  
Rudolf Huebner
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Thermal Radiation ◽  
Cfd Simulation ◽  
Dynamics Simulation ◽  
Cfd Model ◽  
Computational Fluid Dynamics Simulation ◽  
Slow Cooling ◽  
Steel Bars ◽  
Computational Fluid Dynamics Cfd

In this article, the pilling process of hot steel bars is analyzed. During the loading three bars are placed over a wood surface, after those other three are placed over the previous for two times with 5 minutes intervals between them.They are all subject to a slow cooling by thermal radiation and free convection.A Computational Fluid Dynamics (CFD) model to predict the temperature profile of them is developed. Comparison between the CFD simulation results and experimental data yielded an average difference in the bars temperature between -0.3oC and 3.5oC.

scholarly journals Influence of Air Supply Height on Sleep Comfort Through Computational Fluid Dynamics Simulation

2021 ◽  
Vol 39 (4) ◽  
pp. 1173-1179
Author(s):  
Xiling Gao ◽  
Libin Shang ◽  
Rujie Xia ◽  
Xiaodong Zhang ◽  
Wei Yao
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Energy Use ◽  
Dynamics Simulation ◽  
Computational Fluid Dynamics Simulation ◽  
Air Conditioning System ◽  
Air Supply ◽  
Aeration Efficiency ◽  
Computational Fluid Dynamics Cfd ◽  
Air Speed

Taking the bed in the bedroom as an air-conditioning system (ACS), this paper attempts to disclose the influence of air supply height (ASH) on sleep comfort. Specifically, a computational fluid dynamics (CFD) model was established to simulate the air temperature distribution, air speed, and carbon dioxide content (CDC) indoor at five ASHs of the ACS. The simulation results were compared with lab data. On this basis, the aeration efficiency (AE), temperature regulation risk (TRR), and energy-use factor (EUF) of the ACS were analyzed under different working conditions, and the overall efficacy of the ACS was assessed comprehensively by the technique for order of preference by similarity to ideal solution (TOPSIS).

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