All Sky Camera for the CTA Atmospheric Calibration work package

The All Sky Camera (ASC) is a passive non-invasive imaging system for rapid night sky atmosphere monitoring. By design, the operation of the ASC will not affect the measurement procedure of the CTA observatory, for which we discuss its application in this report. The data collected should enable improved productivity and increased measurement time for the CTA observatory. The goal of ASC is to identify cloud position, atmosphere attenuation and time evolution of the sky condition, working within the CTA Central Calibration Facilities (CCF) group. Clouds and atmosphere monitoring may allow near-future prediction of the night-sky quality, helping scheduling. Also, in the case of partly cloudy night sky the cameras will identify the uncovered regions of the sky during the operation time, and define potential observable sources that can be measured. By doing so, a higher productivity of the CTA observatory measurements may be possible

FRAM telescopes and their measurements of aerosol content at the Pierre Auger Observatory and at future sites of the Cherenkov Telescope Array

A FRAM (F/(Ph)otometric Robotic Atmospheric Monitor) telescope is a system of a robotic mount, a large-format CCD camera and a fast telephoto lens that can be used for atmospheric monitoring at any site when information about the atmospheric transparency is required with high spatial or temporal resolution and where continuous use of laser-based methods for this purpose would interfere with other observations. The original FRAM has been operated at the Pierre Auger Observatory in Argentina for more than a decade, while three more FRAMs are foreseen to be used by the Cherenkov Telescope Array (CTA). The CTA FRAMs are being deployed ahead of time to characterize the properties of the sites prior to the operation of the CTA telescopes; one FRAM has been running on the planned future CTA site in Chile for a year while two others are expected to become operational before the end of 2018. We report on the hardware and current status of operation and/or deployment of all the FRAM instruments in question as well as on some of the preliminary results of integral aerosol measurements by the FRAMs in Argentina and ChileComment: Proceedings of AtmoHEAD 201

Visualization of the air flow behind the automotive benchmark vent

Passenger comfort in cars depends on appropriate function of the cabin HVAC system. A great attention is therefore paid to the effective function of automotive vents and proper formation of the flow behind the ventilation outlet. The article deals with the visualization of air flow from the automotive benchmark vent. The visualization was made for two different shapes of the inlet channel connected to the benchmark vent. The smoke visualization with the laser knife was used. The influence of the shape of the inlet channel to the airflow direction, its enlargement and position of air flow axis were investigated

Comparison of methods for flow border detection in images of smoke visualization

A separation of the flow region from the surroundings is an essential step in the analysis of smoke visualization images. The separation can be performed using several detection methods from the image segmentation group. This paper deals with the border detection of the air flow downstream of a benchmark automotive vent using different threshold-based detection methods. An assessment of the methods on the basis of the resulting image quality is also addressed. The quality level depends on the quantity and brightness of disturbances in the background area. The disturbance is usually an isolated region of smoke, which naturally cannot be a part of the flow. Three representative images of different quality levels were selected for the detection, and three methods were used for the evaluation. Each of the methods was used to determine the threshold differently (by the level, by the ratio, and by the change of brightness). It is demonstrated that the change-based method with an appropriately selected parameter is the most convenient for images with the worst quality level while level- and ratio-based methods are only applicable for images of good quality.A separation of the flow region from the surroundings is an essential step in the analysis of smoke visualization images. The separation can be performed using several detection methods from the image segmentation group. This paper deals with the border detection of the air flow downstream of a benchmark automotive vent using different threshold-based detection methods. An assessment of the methods on the basis of the resulting image quality is also addressed. The quality level depends on the quantity and brightness of disturbances in the background area. The disturbance is usually an isolated region of smoke, which naturally cannot be a part of the flow. Three representative images of different quality levels were selected for the detection, and three methods were used for the evaluation. Each of the methods was used to determine the threshold differently (by the level, by the ratio, and by the change of brightness). It is demonstrated that the change-based method with an appropriately selected parameter is the most convenient for images with the worst quality level while level- and ratio-based methods are only applicable for images of good quality