WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Article Minimization of Thermal Stresses in Instrumented Cutting Tools with Embedded Thin Film Thermocouples(Korean Society of Mechanical Engineers, 2026-04) Kesriklioglu, Sinan; Sivesoglu, AbdurrahmanThis study investigates the optimization of multilayer coatings on cutting tools to minimize thermal stress and temperature differences between the tool-chip interface and embedded thermocouples. The novelty of this study lies in directly linking coating architecture to temperature measurement accuracy, revealing that coatings not only affect heat dissipation and stress development but may also distort the apparent temperature recorded by embedded sensors. The types and thickness ranges of thin film layers in instrumented cutting tools were determined, and multi-physics finite element simulations were then used to evaluate coating configurations under thermal loading, assessing both stress distribution and temperature variance in the multilayer coating system. The Taguchi method, coupled with desirability analysis, identified optimal coating parameters that simultaneously minimize thermal stresses and temperature disparities, which are critical for accurate temperature measurements and extending the lifespan of cutting inserts. This framework enables a controllable trade-off between mechanical reliability and thermal measurement fidelity. The results reveal significant interactions among coating configurations (settings) and between thermal and mechanical properties of the materials used, demonstrating that careful selection of layer materials and thicknesses optimizes stress and temperature responses yielding thermal stress of 1628 MPa (second lowest and only 0.4 % higher than the minimum) and temperature difference of 12.1 degrees C (third lowest and 55 % lower than average). These findings underscore the potential of precise coating design to enhance tool performance and longevity in high temperature machining applications.Article Citation - WoS: 1Citation - Scopus: 1Prediction of the Diffusible Hydrogen Concentration After Electrochemical Charging Utilizing Artificial Intelligence(IOP Publishing Ltd, 2025-09-01) Sivesoglu, Abdurrahman; Li, Yang; Bal, BurakThe concentration of diffusible hydrogen in a material is of high importance as it helps to predict the hydrogen embrittlement effect in the material, and the amount of mechanical properties' degradation after reaching a critical concentration. Despite that, a simple experimental setup is not available to measure hydrogen concentration at service. In this paper, a multi-layer perceptron (MLP) model is developed using weight initialization, which can estimate the diffusible hydrogen concentration of Face-Centred-Cubic (FCC) metals after electrochemical charging. The input properties of the model include the electrochemical charging parameters of current density, temperature, and charging time as well as the grain size of the specimen. The MLP model with and without the weight initialization was validated and tested with unseen test dataset. The model in both cases showed an excellent predictive performance with a higher accuracy and faster convergence when using weight initialization. A linear correlation of 89% between the experimental and predicted hydrogen concentration was observed. This demonstrates that for the family of FCC metals under electrochemical charging, the estimation of diffusible hydrogen concentration is a feasible path for material safety design analysis.