Civil Engineering / İnşaat Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/13
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Article Citation - WoS: 7Citation - Scopus: 7Investigating the Effects of Pa66 Electrospun Nanofibers Layered Within an Adhesive Composite Joint Fabricated Under Autoclave Curing(American Chemical Society, 2023) Esenoğlu, Gözde; Tanoğlu, Metin; Barışık, Murat; İplikçi, Hande; Yeke, Melisa; Nuhoğlu, Kaan; Türkdoğan, Ceren; Martin, Seçkin; Aktaş, Engin; Dehneliler, Serkan; Gürbüz, Ahmet Ayberk; İriş, Mehmet ErdemEnhancing the performance of adhesively joined composite components is crucial for various industrial applications. In this study, polyamide 66 (PA66) nanofibers produced by electrospinning were coated on unidirectional carbon/epoxy prepregs to increase the bond strength of the composites. Carbon/epoxy prepregs with/without PA66 nanofiber coating on the bonding region were fabricated using the autoclave, which is often used in the aerospace industry. The single lap shear Charpy impact energy and Mode-I fracture toughness tests were employed to examine the effects of PA66 nanofibers on the mechanical properties of the joint region. Scanning electron microscopy (SEM) was used to investigate the nanofiber morphology and fracture modes. The thermal characteristics of Polyamide 66 nanofibers were explored by using differential scanning calorimetry (DSC). We observed that the electrospun PA66 nanofiber coating on the prepreg surfaces substantially improves the joint strength. Results revealed that the single lap shear and Charpy impact strength values of the composite joint are increased by about 79 and 24%, respectively, by coating PA66 nanofibers onto the joining region. The results also showed that by coating PA66 nanofibers, the Mode-I fracture toughness value was improved by about 107% while the glass transition temperature remained constant.Article Citation - WoS: 9Citation - Scopus: 13Analysis of Adhesively Bonded Joints of Laser Surface Treated Composite Primary Components of Aircraft Structures(Elsevier, 2023) Martin, Seçkin; Nuhoğlu, Kaan; Aktaş, Engin; Tanoğlu, Metin; İplikçi, Hande; Barışık, Murat; Yeke, Melisa; Türkdoğan, Ceren; Esenoğlu, Gözde; Dehneliler, SerkanThe performance of the adhesively bonded aerospace structures highly depends on the adhesion strength between the adhesive and adherents, which is affected by, in particular, the condition of the bonding surface. Among the various surface treatment methods, as state of the art, laser surface treatment is a suitable option for the CFRP composite structures to enhance the adhesion performance, adjusting the roughness and surface free energy with relatively minimizing the damage to the fibers. The aim of this study is the validation and evaluation of the adhesive bonding behavior of the laser surface-treated CFRP composite structures, using the finite element technique to perform a conservative prediction of the failure load and damage growth. Such objectives were achieved by executing both experimental and numerical analyses of the secondary bonded CFRP parts using a structural adhesive. In this regard, to complement physical experiments by means of numerical simulation, macro-scale 3D FEA of adhesively bonded Single Lap Joint and Skin-Spar Joint specimens has been developed employing the Cohesive Zone Model (CZM) technique in order to simulate bonding behavior in composite structures especially skin-spar relation in the aircraft wing-box.Article Constitutive Equation Determination and Dynamic Numerical Modelling of the Compression Deformation of Concrete(Wiley, 2021) Seven, Semih Berk; Çankaya, M. Alper; Uysal, Çetin; Taşdemirci, Alper; Saatci, Selçuk; Güden, MustafaThe dynamic compression deformation of an in-house cast concrete (average aggregate size of 2-2.5 mm) was modelled using the finite element (FE), element-free Galerkin (EFG) and smooth particle Galerkin (SPG) methods to determine their capabilities of capturing the dynamic deformation. The numerical results were validated with those of the experimental split Hopkinson pressure bar tests. Both EFG and FE methods overestimated the failure stress and strain values, while the SPG method underestimated the peak stress. SPG showed similar load capacity profile with the experiment. At initial stages of the loading, all methods present similar behaviour. Nonetheless, as the loading continues, the SPG method predicts closer agreement of deformation profile and force histories. The increase in strength at high strain rate was due to both the rate sensitivity and lateral inertia caused by the confinement effect. The inertia effect of the material especially is effective at lower strain values and the strain rate sensitivity of the concrete becomes significant at higher strain values.Article Citation - WoS: 8Citation - Scopus: 9Dynamic Behavior Predictions of Fiber-Metal Laminate/Aluminum Foam Sandwiches Under Various Explosive Weights(SAGE Publications, 2016) Baştürk, Suat Bahar; Tanoğlu, Metin; Çankaya, Mehmet Alper; Eğilmez, Oğuz ÖzgürApplication of blast tests causes some problems to characterize the performance of panels due to the drastic conditions of explosive medium. Real test has high safety concerns and is not easily accessible because of its extra budget. Some approaches are needed for the preliminary predictions of dynamic characteristics of panels under blast loading conditions. In this study, the response of sandwiches under blast effect was evaluated by combining quasi-static experiments and computational blast test data. The primary aim is to relate the quasi-static panel analysis to dynamic blast load. Based on this idea, lightweight sandwich composites were subjected to quasi-static compression loading with a special test apparatus and the samples were assumed as single degree-of-freedom mass-spring systems to include dynamic effect. This approach provides a simpler way to simulate the blast loading over the surface of the panels and reveals the possible failure mechanisms without applying any explosives. Therefore the design of the panels can be revised by considering quasi-static test results. In this work, the peak deflections and survivabilities of sandwiches for various explosive weights were predicted based on the formulations reported in the literature. Major failure types were also identified and evaluated with respect to their thicknesses.Article Citation - WoS: 53Citation - Scopus: 63Artificial Neural Network (ann) Prediction of Compressive Strength of Vartm Processed Polymer Composites(Elsevier Ltd., 2005) Seyhan, Abdullah Tuğrul; Tayfur, Gökmen; Karakurt, Murat; Tanoğlu, MetinA three layer feed forward artificial neural network (ANN) model having three input neurons, one output neuron and two hidden neurons was developed to predict the ply-lay up compressive strength of VARTM processed E-glass/ polyester composites. The composites were manufactured using fabric preforms consolidated with 0, 3 and 6 wt.% of thermoplastic binder. The learning of ANN was accomplished by a backpropagation algorithm. A good agreement between the measured and the predicted values was obtained. Testing of the model was done within low average error levels of 3.28%. Furthermore, the predictions of ANN model were compared with those obtained from a multi-linear regression (MLR) model. It was found that ANN model has better predictions than MLR model for the experimental data. Also, the ANN model was subjected to a sensitivity analysis to obtain its response. As a result, the ANN model was found to have an ability to yield a desired level of ply-lay up compressive strength values for the composites processed with the addition of the thermoplastic binder.