Standard

Assessing natural ventilation rates using a combined measuring and modelling approach. / De Vogeleer, Gerlinde; Van Overbeke, Philippe; Pieters, Jan G.; Demeyer, Peter.

International Conference of Agricultural Engineering - AgEng 2014 Zurich - Engineering for Improving Resource Efficiency. The European Society of Agricultural Engineers (EurAgEng), 2014.

Research output: Chapter in Book/Report/Conference proceedingC1: Articles in proceedingsResearchpeer-review

Harvard

De Vogeleer, G, Van Overbeke, P, Pieters, JG & Demeyer, P 2014, Assessing natural ventilation rates using a combined measuring and modelling approach. in International Conference of Agricultural Engineering - AgEng 2014 Zurich - Engineering for Improving Resource Efficiency. The European Society of Agricultural Engineers (EurAgEng), Zurich, Switzerland, 7/07/14.

APA

De Vogeleer, G., Van Overbeke, P., Pieters, J. G., & Demeyer, P. (2014). Assessing natural ventilation rates using a combined measuring and modelling approach. In International Conference of Agricultural Engineering - AgEng 2014 Zurich - Engineering for Improving Resource Efficiency The European Society of Agricultural Engineers (EurAgEng).

Vancouver

De Vogeleer G, Van Overbeke P, Pieters JG, Demeyer P. Assessing natural ventilation rates using a combined measuring and modelling approach. In International Conference of Agricultural Engineering - AgEng 2014 Zurich - Engineering for Improving Resource Efficiency. The European Society of Agricultural Engineers (EurAgEng). 2014

Author

De Vogeleer, Gerlinde ; Van Overbeke, Philippe ; Pieters, Jan G. ; Demeyer, Peter. / Assessing natural ventilation rates using a combined measuring and modelling approach. International Conference of Agricultural Engineering - AgEng 2014 Zurich - Engineering for Improving Resource Efficiency. The European Society of Agricultural Engineers (EurAgEng), 2014.

Bibtex

@inbook{52a9fdbb37294c1f8db14ec3854d180b,
title = "Assessing natural ventilation rates using a combined measuring and modelling approach",
abstract = "Natural ventilation of animal houses clearly has advantages as for instance its low power consumption. However its application is often limited due to the lack of a reliable measuring and control system of the ventilation rate and so of emissions, as required for legislation.Although a lot of models exist to determine natural ventilation rates in buildings, it is still a challenge to know the ventilation rate accurately with few measurements. The objective of this work was to develop a model for the prediction of the natural ventilation rate in a pig house with as few measuring points as possible. Neural networks were used to investigate the reliability and accuracy of using as limited input as possible, taken from data collected from measurements with sonic anemometers in a real scale test building under outside weather conditions.",
author = "{De Vogeleer}, Gerlinde and {Van Overbeke}, Philippe and Pieters, {Jan G.} and Peter Demeyer",
year = "2014",
month = "7",
day = "7",
language = "English",
booktitle = "International Conference of Agricultural Engineering - AgEng 2014 Zurich - Engineering for Improving Resource Efficiency",
publisher = "The European Society of Agricultural Engineers (EurAgEng)",
address = "United Kingdom",

}

RIS

TY - CHAP

T1 - Assessing natural ventilation rates using a combined measuring and modelling approach

AU - De Vogeleer, Gerlinde

AU - Van Overbeke, Philippe

AU - Pieters, Jan G.

AU - Demeyer, Peter

PY - 2014/7/7

Y1 - 2014/7/7

N2 - Natural ventilation of animal houses clearly has advantages as for instance its low power consumption. However its application is often limited due to the lack of a reliable measuring and control system of the ventilation rate and so of emissions, as required for legislation.Although a lot of models exist to determine natural ventilation rates in buildings, it is still a challenge to know the ventilation rate accurately with few measurements. The objective of this work was to develop a model for the prediction of the natural ventilation rate in a pig house with as few measuring points as possible. Neural networks were used to investigate the reliability and accuracy of using as limited input as possible, taken from data collected from measurements with sonic anemometers in a real scale test building under outside weather conditions.

AB - Natural ventilation of animal houses clearly has advantages as for instance its low power consumption. However its application is often limited due to the lack of a reliable measuring and control system of the ventilation rate and so of emissions, as required for legislation.Although a lot of models exist to determine natural ventilation rates in buildings, it is still a challenge to know the ventilation rate accurately with few measurements. The objective of this work was to develop a model for the prediction of the natural ventilation rate in a pig house with as few measuring points as possible. Neural networks were used to investigate the reliability and accuracy of using as limited input as possible, taken from data collected from measurements with sonic anemometers in a real scale test building under outside weather conditions.

M3 - C1: Articles in proceedings

BT - International Conference of Agricultural Engineering - AgEng 2014 Zurich - Engineering for Improving Resource Efficiency

PB - The European Society of Agricultural Engineers (EurAgEng)

ER -