WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/394
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Article Citation - WoS: 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 Citation - WoS: 12Citation - Scopus: 14The Effect of Different Tabbing Methods on the Damage Progression and Failure of Carbon Fiber Reinforced Composite Material Under Tensile Loading(Elsevier Sci Ltd, 2022-07) Ali, Hafiz Qasim; Yilmaz, Cagatay; Yildiz, MehmetComposites are well-known and widely used materials due to their anisotropic nature and high strength-to-weight ratio; therefore, the mechanical performance of these materials is crucial. Precise tensile testing is essential to obtain material properties that are crucial for the design stage of composite structures. This study is an effort to investigate the effect of adhesive materials used for tabbing process, which is necessary for the tensile testing procedure. Araldite and AF 163-2k film are used as the adhesive film, whereas in the case of AF 163-2k, tabbing is done through two different procedures (Jig and corner holes method). Apart from the tensile per-formance, strain distribution and damage progression are monitored simultaneously using digital image corre-lation (DIC) and acoustic emission (AE) analysis. It is observed that there is no significant difference in the ultimate tensile strength of these composites tabbed with different adhesives and procedures. Nevertheless, the first major failure strength is much higher in Araldite tabbed specimens compared to AF 163-2k film (the first major failure activity is defined as a point at which material loses its integrity, especially when considering structural or aerospace applications). Also, strain distribution throughout the gauge length recorded via DIC is appreciably different, which is attributed to damage accumulation and progression monitored by AE analysis. The frequency-based analysis of AE data is performed to classify the damage, and cumulative energy is correlated with the DIC to navigate the failure activity at different times and stress levels.Article Citation - WoS: 11Citation - Scopus: 11Monitoring and Verification of Micro-Strain Generated Inside the Laminate Subjected to Thermal Loading Through Fiber Bragg Grating Sensors and Classical Laminate Theory(Wiley, 2023-03-23) Yilmaz, Cagatay; Ali, Hafiz Qasim; Yildiz, MehmetFiber Bragg Grating (FBG) sensors possess enormous potential for the cure monitoring and integrity assessment of Carbon Fiber Reinforced Polymer (CFRP) composites. These sensors can be embedded inside the structure to monitor the strain in the desired region of interest. The strain on an FBG sensor can be calculated by measuring the change in the center wavelength of the sensor. This change in center wavelength is a function of temperature and mechanical strain. Therefore, temperature compensation is necessary for a precise mechanical strain measurement with an FBG sensor. In this study, FBG sensors are embedded in different layers of the CFRP laminate to record the mechanical strain caused by the thermal expansion, which happens under the influence of temperature. Classical laminate theory (CLT) is implemented to assess the accuracy of FBG sensor measurements and the strain data acquired from both FBG sensor and CLT correlates. Furthermore, a resistive strain gauge is deployed to measure the strain under the influence of temperature. It is depicted that strain values recorded by the strain gauge under the influence of the temperature do not agree with the strain measured by CLT, and an error of 150% occurs among their values.Article Citation - WoS: 6Citation - Scopus: 6Experimental and Statistical Damage Analysis in Milling of S2-Glass Fiber/Epoxy and Basalt Fiber/Epoxy Composites(Wiley, 2024-07-30) Sayin, Ahmed Cagri; Danisman, Sengul; Ersoy, Emin; Yilmaz, Cagatay; Kesriklioglu, SinanS2-glass fiber reinforced plastics (S2-GFRP) and basalt fiber reinforced plastics (BFRP) have emerged as crucial materials due to their exceptional mechanical properties, and milling of composite materials plays an important role in achieving desired properties. However, they have proven challenges due to relative inhomogeneity compared with metals, resulting unpredictability in quality of milling operations. The objective of this work is to investigate the effect of cutting parameters, tool geometry and tool surface materials on the surface quality of composites using burrs as a metric. S2-GFRP and BFRP composites were produced by the vacuum infusion method. Helical and straight flute end mills were manufactured from high-speed steel (HSS) and carbide rounds, and half of them were coated with titanium nitride using reactive magnetron sputtering technique. Taguchi L18 orthogonal array is used to determine the effect of tool material, tool angle, coating, cutting direction, spindle speed, and feed rate on the machining quality of S2-GFRPs and BFRPs with respect to burr formations. Milling experiments were conducted under dry conditions and then the burrs were imaged to calculate the total area and length. Statistical analysis was also performed to optimize the machining parameters and tool type for ensuring the structural integrity and performance of the final composite parts. The results showed that the selection of tool material has the most significant impact on the burr area and length of the machined surface. The novel image analysis allows to analyze the extent of the burr size with a desirable operation speed for industrial applications.