RESUMO
Micro-abrasion remains a test configuration hugely used, mainly for thin coatings. Several studies have been carried out investigating the parameters around this configuration. Recently, a new study was launched studying the behavior of different ball materials in abrasive particles' dynamics in the contact area. This study intends to extend that study, investigating new ball materials never used so far in this test configuration. Thus, commercial balls of American Iron and Steel Institute (AISI) 52100 steel, Stainless Steel (SS) (AISI) 304 steel and Polytetrafluoroethylene (PTFE) were used under different test conditions and abrasive particles, using always the same coating for reference. Craters generated on the coated samples' surface and tracks on the balls' surface were carefully observed by Scanning Electron Microscopy (SEM) and 3D microscopy in order to understand the abrasive particles' dynamics. As a softer material, more abrasive particles were entrapped on the PTFE ball's surface, generating grooving wear on the samples. SS AISI 304 balls, being softer than the abrasive particles (diamond), also allowed particle entrapment, originating from grooving wear. AISI 52100 steel balls presented particle dynamics that are already known. Thus, this study extends the knowledge already existing, allowing to better select the ball material to be used in ball-cratering tests.
RESUMO
This work introduces the use of machine vision in the massive bubble recognition process, which supports the validation of boiling models involving bubble dynamics, as well as nucleation frequency, active site density and size of the bubbles. The two algorithms presented are meant to be run employing quite standard images of the bubbling process, recorded in general-purpose boiling facilities. The recognition routines are easily adaptable to other facilities if a minimum number of precautions are taken in the setup and in the treatment of the information. Both the side and front projections of subcooled flow-boiling phenomenon over a plain plate are covered. Once all of the intended bubbles have been located in space and time, the proper post-process of the recorded data become capable of tracking each of the recognized bubbles, sketching their trajectories and size evolution, locating the nucleation sites, computing their diameters, and so on. After validating the algorithm's output against the human eye and data from other researchers, machine vision systems have been demonstrated to be a very valuable option to successfully perform the recognition process, even though the optical analysis of bubbles has not been set as the main goal of the experimental facility.
RESUMO
Advantages, such as thermal storage improvement, are found when using PCMs (Phase Change Materials) in storage tanks. The inclusion of three different types of materials in a 60 l test tank is studied. Two test methodologies were developed, and four tests were performed following each methodology. A thermal analysis is performed to check the thermal properties of each PCM. The distributions of the water temperatures inside the test tanks are evaluated by installing four Pt-100 sensors at different heights. A temperature recovery is observed after exposing the test tank to an energy demand. An energetic analysis that takes into account the energy due to the water temperature, the energy due to the PCM and the thermal loss to the ambient environment is also presented. The percentage of each PCM that remains in the liquid state after the energy demand is obtained.
RESUMO
This paper describes a prototype instrumentation system for photogrammetric measuring of bed and ash layers, as well as for flying particle detection and pursuit using a single device (CCD) web camera. The system was designed to obtain images of the combustion process in the interior of a domestic boiler. It includes a cooling system, needed because of the high temperatures in the combustion chamber of the boiler. The cooling system was designed using CFD simulations to ensure effectiveness. This method allows more complete and real-time monitoring of the combustion process taking place inside a boiler. The information gained from this system may facilitate the optimisation of boiler processes.
