Assessing airflow rates of a naturally ventilated test facility using a fast and simple algorithm supported by local air velocity measurements

The high spatial and temporal variations of airflow patterns in ventilation openings of naturally ventilated animal houses make it difficult to accurately measure the airflow rate. This paper focuses on the development of a fast assessment technique for the airflow rate of a naturally ventilated test facility through the combination of a linear algorithm and local air velocity measurements. This assessment technique was validated against detailed measurement results obtained by the measuring method of Van Overbeke et al. (2015) as a reference. The total air velocity |u-|, the normal |Y-| and tangential velocity component |x-| and the velocity vector u- measured at the meteomast were chosen as input variables for the linear algorithms. The airflow rates were split in a group where only uni-directional flows occurred at vent level (no opposite directions of |Y-| present in the airflow pattern of the opening), and a group where bi-directional flows occurred (the air goes simultaneously in and out of the opening). For airflow rates with uni-directional flows the input variables u- and |Y-| yielded the most accurate results. For this reason, it was suggested to use the |Y-| instead of |u-| in ASHRAE’s formula of Q = E × A × |u-|. For bi-directional flows a multiple linear model was suggested where input variable u- gave the best results to assess the airflow rate

Methodology for airflow rate measurements in a naturally ventilated mock-up animal building with side and ridge vents

Currently there exists no generally accepted reference technique to measure the ventilation rate through naturally ventilated (NV) vents. This has an impact on the reliability of airflow rate control techniques and emission rate measurements in NV animal houses. As an attempt to address this issue a NV test facility was built to develop new airflow rate measurement techniques for both side wall and ridge vents. Three set-ups were used that differed in vent configuration, i.e. one cross ventilated set-up and two ridge ventilated set-ups with different vent sizes. The airflow through the side vents was measured with a technique based on an automatic traverse movement of a 3D ultrasonic anemometer. In the ridge, 7 static 2D ultrasonic anemometers were installed. The methods were validated by applying the air mass conservation principle, i.e. the inflow rates must equal the outflow rates. The calculated in - and outflow rates agreed within (5 ± 8)%, (8 ± 5)% and (−9 ± 7)% for the three different set-ups respectively, over a large range of wind incidence angles. It was found that the side vent configuration was of large importance for the distribution of the airflow rates through the vents. The ridge proved to be a constant outlet, whilst side vents could change from outlet to inlet depending on the wind incidence angle. The range of wind incidence angles in which this transition occurred could be clearly visualised

The state of peer-to-peer network simulators

Networking research often relies on simulation in order to test and evaluate new ideas. An important requirement of this process is that results must be reproducible so that other researchers can replicate, validate and extend existing work. We look at the landscape of simulators for research in peer-to-peer (P2P) networks by conducting a survey of a combined total of over 280 papers from before and after 2007 (the year of the last survey in this area), and comment on the large quantity of research using bespoke, closed-source simulators. We propose a set of criteria that P2P simulators should meet, and poll the P2P research community for their agreement. We aim to drive the community towards performing their experiments on simulators that allow for others to validate their results

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

The phase 0/A study of the ESA M3 mission candidate EChO

Stars and planetary system