A methodology for quantifying flow patterns in a water-table apparatus for naturally ventilated buildings
- 29 February 2020
- journal article
- research article
- Published by Taylor & Francis in Architectural Science Review
- Vol. 64 (1-2) , 98-108
Abstract
Wind-driven ventilation in buildings is an effective way of diluting the indoor air for maintaining thermal comfort and acceptable indoor air quality. Visualization of the wind-induced flow patterns in a building using a water-table apparatus is a relatively convenient method that produces instantaneous results. The present study focused on the quantification of the flow patterns generated in and around buildings using water-table experiments. The flow patterns were analyzed photographically to derive different ventilation metrics, such as dead spots, ventilation efficiency, etc., which would reveal quantitative information regarding the flow in the different zones of the building. Experiments were conducted using different configurations in order to verify the results obtained with the photographic method. The method used in the present study could be useful in the prediction of flow patterns for complex geometries, which would assist in undertaking early decisions for the proper orientation of a building and its openings. Abbreviations: ACH: Air Changes per Hour (h−1); AS: Room with windows on adjacent walls configuration; AVE: Absolute Ventilation Efficiency; BHK: Bedroom, Hall, Kitchen; C: dye concentration at a point after t, s (g/l); CFD: Computational Fluid Dynamics; Ci: average inside concentration(g/l); Cmax: maximum dye concentration at a point (g/l); Co: initial concentration at a point (g/l); Cs: concentration in the outdoor supply air (g/l); d: characteristic length (mm or m); D: Dining room; dC: change in concentration (g/l); DS: Dead Spots; Ea: Absolute Ventilation Efficiency; fps: Frames per seconds; IAQ: Indoor Air Quality; k reactivity rate (h−1); K: Kitchen; L: Living Room; MATLAB: Matrix Laboratory; OS: Room with windows on opposite walls configuration; P: Dimensionless penetration factor; P1: Passage 1; P2: Passage 2; P3: Passage 3; Pix: Pixel value (px); PNG Portable network graphics; R1: Room 1; R2: Room 2; R3: Room 3; Re: Reynolds Number; RGB: Red, Green, Blue; S: indoor source emission rate (μg/h); SS: Room with single-sided window configuration; T1: Toilet 1; T2: Toilet 2; T3: Toilet 3; U: Utility room; V: Room volume, m3; v: velocity (m/s); VLC: VideoLAN ClientKeywords
This publication has 16 references indexed in Scilit:
- nullPhilosophy Study, 2016
- Towards sustainable, energy-efficient and healthy ventilation strategies in buildings: A reviewRenewable and Sustainable Energy Reviews, 2016
- Field measurement of ventilation ratesIndoor Air, 2015
- Air Change Rate Measurements using Tracer Gas Carbon Dioxide from Dry IceInternational Journal of Ventilation, 2014
- A review of the performance of different ventilation and airflow distribution systems in buildingsBuilding and Environment, 2014
- Ventilation performance prediction for buildings: A method overview and recent applicationsBuilding and Environment, 2009
- Indoor Air Quality Engineering2003
- VENTILATION OF BUILDINGS2002
- Indoor air quality and healthAtmospheric Environment, 1999
- Indoor-outdoor relationships of respirable sulfates and particlesAtmospheric Environment (1967), 1981