Modelling of Air Flow Analysis for Residential Homes Using Particle Image Velocimetry - Environmental Software Systems. Infrastructures, Services and Applications Access content directly
Conference Papers Year : 2015

Modelling of Air Flow Analysis for Residential Homes Using Particle Image Velocimetry

Rajiv Pratap
  • Function : Author
Ramesh Rayudu
  • Function : Author
  • PersonId : 983272

Abstract

The purpose of this paper is to simulate the designed physical Particle Image Velocimetry (PIV) system, as a simulation platform to physically build and implement a system for residential building and housing research. The focus is on the angle filter; the filter used to process the images of a laser progressively scanning through a space by adjusting its angle.An indicator of heat escape and ventilation in buildings is the airflow itself. Conventional airflow measurement techniques are typically intrusive, interfering with the data or the environment. For small flows such as that in residential housing, the error introduced can sometimes be large relative to the measured data. In contrast, PIV is a relatively a non-intrusive measurement tool that measures flows. However, there are a few problems with standard PIV techniques, for implementation in an attic space.The proposed solution is to use dust particles, already present in the air, as tracers for the PIV system. In conclusion, our PIV system with a non-diverging laser beam produces a velocity field of similar quality to a velocity field of a standard PIV system.
Fichier principal
Vignette du fichier
978-3-319-15994-2_29_Chapter.pdf (4 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01328562 , version 1 (08-06-2016)

Licence

Attribution

Identifiers

Cite

Rajiv Pratap, Ramesh Rayudu, Manfred Plagmann. Modelling of Air Flow Analysis for Residential Homes Using Particle Image Velocimetry. 11th International Symposium on Environmental Software Systems (ISESS), Mar 2015, Melbourne, Australia. pp.293-302, ⟨10.1007/978-3-319-15994-2_29⟩. ⟨hal-01328562⟩
57 View
77 Download

Altmetric

Share

Gmail Facebook X LinkedIn More