Civil Engineering / İnşaat Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/13
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Article Citation - WoS: 31Citation - Scopus: 32Development and Analysis of Composite Overwrapped Pressure Vessels for Hydrogen Storage(SAGE Publications, 2021) Kartav, Osman; Kangal, Serkan; Yücetürk, Kutay; Tanoğlu, Metin; Aktaş, Engin; Artem, Hatice SeçilIn this study, composite overwrapped pressure vessels (COPVs) for high-pressure hydrogen storage were designed, modeled by finite element (FE) method, manufactured by filament winding technique and tested for burst pressure. Aluminum 6061-T6 was selected as a metallic liner material. Epoxy impregnated carbon filaments were overwrapped over the liner with a winding angle of +/- 14 degrees to obtain fully overwrapped composite reinforced vessels with non-identical front and back dome layers. The COPVs were loaded with increasing internal pressure up to the burst pressure level. During loading, deformation of the vessels was measured locally with strain gauges. The mechanical performances of COPVs designed with various number of helical, hoop and doily layers were investigated by both experimental and numerical methods. In numerical method, FE analysis containing a simple progressive damage model available in ANSYS software package for the composite section was performed. The results revealed that the FE model provides a good correlation as compared to experimental strain results for the developed COPVs. The burst pressure test results showed that integration of doily layers to the filament winding process resulted with an improvement of the COPVs performance.Article Citation - WoS: 40Citation - Scopus: 37Investigation of Interlayer Hybridization Effect on Burst Pressure Performance of Composite Overwrapped Pressure Vessels With Load-Sharing Metallic Liner(SAGE Publications, 2020) Kangal, Serkan; Kartav, Osman; Tanoğlu, Metin; Aktaş, Engin; Artem, Hatice SeçilIn this study, multi-layered composite overwrapped pressure vessels for high-pressure gaseous storage were designed, modeled by finite element method and manufactured by filament winding technique. 34CrMo4 steel was selected as a load-sharing metallic liner. Glass and carbon filaments were overwrapped on the liner with a winding angle of [+/- 11 degrees/90 degrees(2)](3) to obtain fully overwrapped composite reinforced vessel with non-identical front and back dome endings. The vessels were loaded with increasing internal pressure up to the burst pressure level. The mechanical performances of pressure vessels, (i) fully overwrapped with glass fibers and (ii) with additional two carbon hoop layers on the cylindrical section, were investigated by both experimental and numerical approaches. In numerical approaches, finite element analysis was performed featuring a simple progressive damage model available in ANSYS software package for the composite section. The metal liner was modeled as elastic-plastic material. The results reveal that the finite element model provides a good correlation between experimental and numerical strain results for the vessels, together with the indication of the positive effect on radial deformation of the COPVs due to the composite interlayer hybridization. The constructed model was also able to predict experimental burst pressures within a range of 8%. However, the experimental and finite element analysis results showed that hybridization of hoop layers did not have any significant impact on the burst pressure performance of the vessels. This finding was attributed to the change of load-sharing capacity of composite layers due to the stiffness difference of carbon and glass fibers.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.