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Metal matrix composites (MMCs) exhibit superior characteristics such as low weight, high stiffness, and high mechanical and physical properties. Inheriting such an outstanding combination of specifications, they are nowadays considered as the promising materials in the aerospace and biomedical industries. However, the presence of high abrasive reinforcing particles in MMCs leads to severe manufacturing issues. Due to the tool-particle interactions which occur during the machining of MMCs, high tool wear and poor surface finish are induced and those elements are considered as the main drawbacks of cutting MMCs. In this study, dry turning experiments were conducted for two different inserts and coated carbide on a bar of titanium metal matrix composite (Ti-MMC). Semi-finishing machining is operated with cutting parameters based on the tool supplier's recommendations which were not fully optimized. The maximum flank wear length (VBBmax) was selected as the tool wear criteria.

Statistical process control (SPC) has been extensively used in many different industries including automotive, electronics, and aerospace, among others. SPC tools such as control charts, process capability analysis, sampling inspection, etc., have definitive and powerful impact on quality control and improvement for mass production and similar production systems. In aerospace manufacturing, however, applications of SPC tools are more challenging, especially when these tools are implemented in processes producing products of large sizes with slower production rates. For instance, following a widely accepted rule-of-thumb, about 100 units of products are required in the first phase of implementing a Shewhart type control chart. Once established, it then can be used for process control in the second phase for actual production process monitoring and control.

This paper presents CHT2D, a 2D hot air anti-icing simulation tool developed by the Advanced Aerodynamics group of Bombardier Aerospace. The tool has been developed from two main modules: the ice prediction code CANICE and the Navier-Stokes solver NSU2D, which is used to solve the hot air internal flow. A “weak” coupling beween the two modules based on function calls and information exchange has been priviledged. Three validation test cases are presented: for dry air conditions. Predictions from CHT2D agree quite well with the experiments. Preliminary results are also presented for a test case in icing conditions for different heat loads from the anti-icing system, to study the effect on the accumulated ice.

3D ice accretion codes have been available for a few decades but, depending on the specific application, their use may be cumbersome, time consuming and requiring a great deal of expertise in using the code. In particular, simulations of large 3D glaze ice accretions using multiple layers of ice is a very challenging and time consuming task. There are several reasons why 2D icing simulations tools are still widely used in the aircraft industry to produce realistic glaze ice shapes. 2D codes are very fast and robust, with a very short turn-around time. They produce adequate results in areas of the aircraft where 3D effects on airflow or droplets concentration can be neglected. Their use can be extended to other areas of the aircraft if relevant 3D effects can be taken into account. This paper proposes a simulation methodology that includes three levels of corrections to extend the use of 2D icing codes to most of the aircraft surfaces.

This paper summarizes the techniques used during a microphone array test campaign performed at Pierre-Elliott-Trudeau Airport in Montréal, Québec (Canada) during the summer of 2012. Emphasis is put on the actual measurement campaign as only a limited amount of analysis has been performed at this stage. An aircraft position tracking tool is presented along with the beamforming algorithms that were used. Over 500 aircraft were recorded during this test. A comparison of known tonal sources associated to a specific aircraft type is made between different airlines in order to evaluate the repeatability of the method.