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Mechanical Testing of Selective-Laser-Sintered Polyamide PA2200 Details: Analysis of Tensile Properties via Finite Element Method and Machine Learning Approaches.

Ivan Pavlovich MalashinDmitriy MartysyukVadim Sergeevich TynchenkoVladimir NelyubAleksei BorodulinAndrey Galinovsky
Published in: Polymers (2024)
This study delves into the mechanical characteristics of polyamide PA2200 components crafted using selective laser sintering (SLS) technology. Our primary objective is to analyze the tensile behavior of the components printed at various orientations, showing its response to diverse loading conditions. Finite element method (FEM) modeling was employed to analyze the tensile behavior of these details. The time determined for breaking the detail is 9 s. In addition we forecast key properties, such as tensile behavior and strength, using machine learning (ML) techniques, and the best models are for predicting relative elongation are KNeighborsRegressor and SVR.
Keyphrases
  • finite element
  • machine learning
  • high speed
  • artificial intelligence
  • mass spectrometry
  • deep learning
  • high resolution