miércoles, 7 de abril de 2021
Northrop Grumman's optionally-manned Firebird demonstrates operational flexibility
TEMACOM Artificial intelligence and Machine learning to predict defective Aerospace components - IDAERO
Recently Idaero Joint TEMACOM Project, as part of a consortium with Airbus and IMDEA.
Idaero is in charge of development the software including AI and ML core.
One of the goals of TEMACOM is reducing defects probability occurrence during manufacturing of aerospace parts by developing TEMACOM predictive software.
First Stage
First stage of the project just finished, consists of prediction of what conditions may lead to defects during RTM manufacturing process.
RTM (Resin Transfer Moulding) process consist of injecting epoxy resin in a mold with carbon fiber, so parts manufactured copy the geometry of the mould and are reinforced with carbon fibres.
RTM process are used widely to improve efficiency while manufacturing composite components for aerospace, automotive, wind power and other industries.
There are some possible defects that may appear in the parts during the process, that affect mechanical properties.
Second Stage
Second and current stage of the project is the prediction of manufacturing issues when drilling panels for assembling, based on detection of position of the tools on the outer shape of the manufactured panels, that can result in defects in the holes.
Idaero
Idaero is specialized in developing engineering software of any kind, including Machine Learning and Artificial intelligence solutions applied to improve manufacturing processes.
TEMACOM is a Project from Innovation Hub calls of the Regional Government of Madrid and receives funds from Community of Madrid.
TEMACOM is a Project from Innovation Hub calls of the Regional Government of Madrid and receives funds from Community of Madrid
Recently Idaero Joint TEMACOM Project, as part of a consortium with Airbus and IMDEA.
Idaero is in charge of development the software including AI and ML core.
One of the goals of TEMACOM is reducing defects probability occurrence during manufacturing of aerospace parts by developing TEMACOM predictive software.
First Stage
First stage of the project just finished, consists of prediction of what conditions may lead to defects during RTM manufacturing process.
RTM (Resin Transfer Moulding) process consist of injecting epoxy resin in a mold with carbon fiber, so parts manufactured copy the geometry of the mould and are reinforced with carbon fibres.
RTM process are used widely to improve efficiency while manufacturing composite components for aerospace, automotive, wind power and other industries.
There are some possible defects that may appear in the parts during the process, that affect mechanical properties.
Second Stage
Second and current stage of the project is the prediction of manufacturing issues when drilling panels for assembling, based on detection of position of the tools on the outer shape of the manufactured panels, that can result in defects in the holes.
Idaero
Idaero is specialized in developing engineering software of any kind, including Machine Learning and Artificial intelligence solutions applied to improve manufacturing processes.
TEMACOM is a Project from Innovation Hub calls of the Regional Government of Madrid and receives funds from Community of Madrid.
TEMACOM is a Project from Innovation Hub calls of the Regional Government of Madrid and receives funds from Community of Madrid
TsAGI Developed a Concept of Aircraft Wing Surface Micro-Relief
During unfavorable weather conditions or in case of crew errors, the flying aircraft risks reaching critical angles of attack, which can lead to a plane crash. To solve the problem of the drop in lift, scientists from the Central Aerohydrodynamic Institute named after Professor N.E. Zhukovsky (part of the Research Center "Institute named after N.E. Zhukovsky") investigate the possibility to control the detachable flow around the wing using the surface microrelief. The fundamental activity is being carried out within the framework of Micro-Relief, TsAGI R&D
At the first stage, TsAGI created a concept of the micro-relief which is a number of plastic-foil zig-zag vortex generators distributed above the streamlined surface.
After that, TsAGI used the subsonic T-129 WT to find the best relief position on the wing. The wing model tests were performed at 15-20 m/s flow rate, 0...35-degree angles of attack, and with different micro-relief positions.
'The testing revealed that wing leading edge area is the most effective position for the micro-relief. This does not only increase the maximum lift coefficient but also significantly slows the lift descent at post stall,' said Maksim Ustinov, Doctor of Sciences in Physics and Mathematics, TsAGI Deputy Head of Supersonic Aircraft Aerothermodynamics.
The next stage included tests of micro-relief influence on high-lift wing; they showed the efficiency of using it at the wing slat.
The concept developed may be applicable for different aircraft types; this year, it will be tested on a main rotor blade model. Tests will be carried out on the special facility in the Department for Rotorcraft Aerodynamics and Dynamics.
In the course of the work, the scientists will study the mechanism of the influence of the relief on the unsteady separation of the flow. This will improve the know-how parameters to be used on the rotor blade profile. It is expected that the use of microrelief will significantly increase the helicopter aerodynamic characteristics, in particular, its maximum velocity.