Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Article Surface Integrity and Tool Wear in S2-GFRP Milling: Experimental and Statistical Evaluation of Cutting Parameters and DLC and TiAlN Tool Coatings(Springer London Ltd, 2026) Danisman, Sengul; Yilmaz, Cagatay; Ersoy, Emin; Kesriklioglu, SinanIn this study, the surface integrity of S2-glass fiber-reinforced polymer (S2-GFRP) composites during milling with carbide cutters was investigated using a two-phase experimental design, focusing on surface roughness (Ra), burr area, and tool wear (VB). In the first phase, using a Taguchi L9 design, the effects of coating type (uncoated, TiAlN, DLC), spindle speed (2000-6000 rpm), and feed rate (0,15-0,25 mm/rev) on Ra and burr area were evaluated. In this short machining range where tool wear was negligible, the optimal combination yielding the lowest Ra (approximate to 0.97 mu m) and the minimum burr area (approximate to 231 mm & sup2;) was determined to be 4000 rpm, 0,15 mm/rev, and the DLC-coated tool. Regarding the effect of tool material on Ra, the DLC-coated tool provided approximately 4 and 2 times better results than the uncoated and TiAlN-coated tools, respectively. In the second phase, experiments extended up to 130 passes with this optimal parameter set showed that Ra increased significantly with increasing VB, and the burr area exhibited threshold-like behavior. In particular, a sudden increase in Ra and the burr area was observed when the VB approximate to threshold of approximately 100 mu m was exceeded; partial regression analyses confirmed different burr-formation tendencies in the low- and high-wear regimes. The results reveal that DLC coating initially provides superior performance in S2-GFRP milling, but surface degradation accelerates after the critical VB threshold.Article Experimental Comparative Analysis of Hole-Making Strategies and Cutting Parameters on Flexural Properties and Induced Delamination in S2 Glass and Basalt Fiber-Reinforced Polymers(John Wiley and Sons Inc, 2026) Eltahir, Sara Saeed Abdulrahman; Yilmaz, Cagatay; Kesriklioglu, SinanOpen holes are often required in the applications of fiber-reinforced polymers (FRP). However, machining them leads to fiber and matrix damage, reducing the overall quality of composites. The novelty of this study lies in investigating the influence of multiple hole machining strategies under varying feed rates and cutting speeds on the flexural strength, chord modulus and hole quality for S2-Glass (S2-GFRP) and basalt fiber-reinforced polymers (BFRP), followed by three-point bending tests and statistical analysis to determine the optimum machining parameters in terms of flexural properties, delamination, and time efficiency. Findings indicate that conventional milling yields an increase in the flexural strength and chord modulus by 22.2 MPa and 1.9 GPa, respectively, for S2 GFRP. While climb milling performs best for BFRP, enhancing flexural performance by 7.6 MPa and 0.4 GPa. Direct drilling at high feed rate and cutting speed shows the poorest performance. Hole machining at low feed rate using climb milling minimizes delamination at the entrance by 14.8% for S2 GFRP and by 2.7% for BFRP using conventional milling. At the exit, helical milling at a low feed rate suppresses delamination damage by 58.5% and 10.7% for S2 GFRP and BFRP. The most time-efficient method is direct drilling at a feed rate of 0.075 mm/rev and cutting speed of 75 m/min or climb milling with same feed rate, but 25 m/min cutting speed. Within the tested ranges, the optimized drilling setup significantly improved structural performance of S2-GFRP and GFRP, confirming the effectiveness of the proposed experimental-statistical framework.Article Citation - WoS: 2Citation - Scopus: 1A Comprehensive Analysis of Acoustic Emission Signals To Distinguish the Different Damage Types for Fiber-Reinforced Polymers: A Review(Wiley, 2025-12-03) Yilmaz, CagatayFiber-reinforced polymers (FRP) attract the attention of key industries, such as aerospace, wind energy, and automotive, as they can reduce the weight of structural components without compromising their mechanical properties. Due to FRP's anisotropic and non-homogeneous structure, their failure under different loading conditions and the corresponding failure mechanisms must be investigated. One method that progressively monitors the failure of FRP underload is Acoustic Emission (AE). AE can register the elastic stress waves in the form of digitized waveforms, released by the discontinuous events that occur in the FRP under load. These discontinuities can be clustered and identified as transverse cracking, fiber/matrix interface debonding, delamination, and fiber failure by analyzing the AE waveforms. Recently, numerous clustering approaches using machine learning algorithms, along with the varying features of AE waveforms, have been developed and are being used. These algorithms include supervised and unsupervised clustering, deep learning algorithms, and neural network methods, among others. While supervised algorithms require a training dataset to classify AE signals, unsupervised algorithms can perform clustering without training datasets. Deep learning and neural network algorithms can train themselves to cluster data, but they may require a significant amount of computer power when the dataset is large. This review paper provides comprehensive information on the clustering algorithm, along with the AE wave features, the range of features for different damage types, and the type of reinforcer.Article Failure Analysis of Fused Deposition Modeling 3D Printed Poly Lactic Acid Polymer(Sage Publications Ltd, 2025-10-04) Yilmaz, Cagatay; Eltahir, Sara Saeed AbdulrahmanAdditive manufacturing, commonly known as 3D printing (AM), has emerged as one of the most transformative technological advances in the last few decades in global manufacturing, as it allows for the production of intricate components without the use of costly molds. Fused Deposition Modeling (FDM) is widely adopted among various AM techniques due to its accessibility and effectiveness. FDM 3D-printed PLA (Poly Lactic Acid) shows a transversely isotopic symmetry similar to laminated composite structures. Therefore, classical lamination theory can be applied to FDM 3D-printed PLA. This study attempts to expand the knowledge by relying on classical lamination theory and several imposed failure theories like maximum stress, Tsai-Hill, Tsai-Wu, and Hashin to determine how FDM 3D printing of PLA fails. We investigate eight different raster orientations (0 degrees, 10 degrees, 15 degrees, 30 degrees, 45 degrees, 60 degrees, 75 degrees, and 90 degrees) and compare the theoretical prediction of strength with experimental findings. With this comprehensive analysis, we are seeking to better understand the failure analysis of FDM 3D printed PLA. The maximum stress, Tsai-Wu, Tsai-Hill, and Hashin failure theories show good agreement with experimental findings for 0 degrees and 90 degrees raster orientations. As the raster orientation shifts from 0 degrees, the discrepancy between experimental results and theoretical predictions increases, peaks at mid-angles, and then decreases, becoming negligible at 90 degrees.