International Journal of Heat and Mass Transfer 201 (2023)
2023/02
10.1016/j.ijheatmasstransfer.2022.123639
Sensor integration is one of the drivers in modern industry for obtaining real-time data and enabling transition to Industry 4.0. Sensor integration on production systems and tooling is one of the key points for data acquisition. Although several techniques can be applied for sensor integration, Laser Directed En- ergy Deposition (L-DED) is becoming one of the most relevant, since the sensor can be placed into the manufactured layer-by-layer structure. However, the thermal nature of the L-DED poses a challenge when heat-sensitive parts, such as thermocouples, are to be embedded. In order to ease parametrization and anticipate the behavior of the L-DED process, modeling is an interesting tool that has attracted the atten- tion of academia in the last years. Nevertheless, most models are highly complex and focused on a very local scale or include symmetry assumptions that restrict their use for real applications. In view of this need, in the present research work a thermal model that considers material addition and determines the clad geometry is developed. The model includes an automatic meshing algorithm that adapts the element size by refining the mesh where required. Besides, the model enables 5 axis L-DED, in-process variation of the machine feed rate, and allows to switch on and offthe laser to simulate not only the material deposition, but also the idle movements. The model is validated in two steps: single clad deposition on a flat surface and single clads on a 0.3 mm thick thermocouple sheath. Finally, the validated model is used for defining the maximum laser power for embedding virtually a 3 mm diameter K-type thermocouple with a 0.3 mm thick sheath. The results of the simulation are also corroborated by experimental integra- tion of the same thermocouple, which functionality is tested afterwards. Therefore, the L-DED modeling is proven to be an effective tool for manufacturing complex parts on the first try.
Jon Iñaki Arrizubieta (UPV/EHU), Marta Ostolaza (UPV/EHU), Maider Muro, Hegoi Andonegi, Aitzol Lamikiz (UPV/EHU)
L-DED, Model, Thermocouple, Sensor embedding, Adaptive mesh
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