Civil Engineering / İnşaat Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/13
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Article Citation - WoS: 3Citation - Scopus: 3Ensemble and Optimized Hybrid Algorithms Through Runge Kutta Optimizer for Sewer Sediment Transport Modeling Using a Data Pre-Processing Approach(Elsevier, 2023) Safari, Mir Jafar Sadegh; Gül, Enes; Dursun, Ömer Faruk; Tayfur, GökmenUncontrolled sediment deposition in drainage and sewer systems raises unexpected maintenance expenditures. To this end, implementation of an accurate model relying on effective parameters involved is a reliable benchmark. In this study, three machine learning techniques, namely extreme learning machine (ELM), multilayer perceptron neural network (MLPNN), and M5P model tree (M5PMT); and three optimization approaches of Runge Kutta (RUN), genetic algorithm (GA), and particle swarm optimization (PSO) are applied for modeling. The optimization and ensemble hybridization approaches are applied in the modeling procedure. For the case of hybrid optimized models, the ELM and MLPNN models are hybridized with RUN, GA, and PSO algorithms to develop six hybrid models of ELM-RUN, ELM-GA, ELM-PSO, MLPNN-RUN, MLPNN-GA, and MLPNN-PSO. Ensemble hybrid models are developed through coupling the ELM and MLPNN models with the M5PMT algorithm. The data pre-processing approach is applied to find the best randomness characteristic of the utilized data. Results illustrate that the RUN-based hybrid models outperform the GA- and PSO-based counterparts. Although the MLPNN-RUN and MLPNN-M5PMT hybrid models generate better results than their alternatives, MLPNN-M5PMT slightly outperforms MLPNN-RUN model with a coefficient of determination of 0.84 and a root mean square error of 0.88. The current study shows the superiority of the ensemble-based approach to the optimization techniques. Further investigation is needed by considering alternative optimization techniques to enhance sediment transport modeling. © 2023 International Research and Training Centre on Erosion and Sedimentation/the World Association for Sedimentation and Erosion ResearchArticle 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 Citation - WoS: 4Citation - Scopus: 4Destratification of Thermally Stratified Water Columns by Air Diffusers(Elsevier, 2023) Elçi, Şebnem; Hazar, Oğuz; Bahadıroğlu, Nisa; Karakaya, Derya; Bor, AslıThis study aims at improving the understanding in order to optimise an aeration system for artificial destratification to control cyanobacteria growth in the reservoirs. Previous applications for artificial destratification in reservoirs were based on installations based on computational methods, where neither the effect of air bubble size and configuration nor the effect of air density in the bubble plume could be investigated. This study seeks for an optimized design with the help of experimental and numerical analyses. In order to perform experimental studies, a novel water tank enabling the heating/cooling of the water column as desired and a diffuser system were manufactured. During the experimental studies, effect of bubble size, bubble slip velocity, and other parameters of air diffuser on destratification efficiency were investigated. Based on the nondimensional parameters, a new destratification efficiency formula is obtained by the Genetic Algorithm (GA) approach. Additionaly, the hydrodynamics of the water tank during the mixing process by air diffuser was simulated via 3D numerical model and validated with experimental results. The Eulerian multiphase model with the ‘degassing’ boundary condition and k-ω turbulence model are found to be suitable for the purposes of the study. Based on the error analysis of comparisons of the model and observations, the best configuration of air diffuser is proposed, and the numerical model is found to be successful in simulating the destratification of thermally stratified water columns by air diffuser.Article Citation - WoS: 1Citation - Scopus: 1Comparison of the Predicted and the Observed Wave Spectral Parameters During the Storms at Filyos Coasts, the Southwestern Black Sea(Elsevier, 2022) Öztunalı Özbahçeci, Bergüzar; Güler, MuzafferIn-situ wave measurement data are mainly used to validate the bulk wave parameters predicted by numerical models. Although the frequently used third-generation wave models are spectral models, determination of various spectral parameters and validation with the observed data are not common. This study covers the spectral analysis of selected storm records of a nearshore wave measurement campaign carried out at Filyos coasts with the complex bottom topography in Turkey, Southwestern Black Sea. The bulk wave and the spectral parameters are also calculated by a third-generation nearshore wave model, SWAN (Simulating Waves Nearshore), forced by the ERA5 offshore wave data, which is the newest re-analysis of the European Centre for Medium-Range Weather Forecasts (ECMWF) for the selected storms. Before using ERA5 offshore wave data, they are calibrated by the wave data of the satellite radar altimeter. In-situ measured bathymetry data are used in the SWAN model. Observed and predicted bulk wave and spectral parameters are compared, and the statistical error measures are calculated not only for the significant wave height, the peak period, and the peak wave direction but also for the three different spectral periods, three different frequency width parameters, a directional width and, a spectral peakedness parameter for the first time. Low values of statistical error measures show that the current wave predictions have a good agreement with the observed ones in terms of the significant wave height, Hs, and the peak period, Tp. However, the SWAN model predicts a slightly narrower frequency and directional spectrum with higher peaks, although the error measures are low. Moreover, SWAN can not predict the wide range of spectral shape occurrences that the observed spectra have. The development of the various spectral parameters during the storms is also investigated for the first time. It is found that the frequency and directional spreading of the observed spectra become wider and unsharpened in the late stages of the storm compared to the early stages. However, the same tendency is not observed clearly in the predicted directional spreadingArticle Citation - WoS: 6Citation - Scopus: 9Investigation of Car Park Preference by Intelligent System Guidance(Elsevier, 2020) Doğaroğlu, Bora; Çalışkanelli, S. PelinIn recent years, especially in developing countries, the number of vehicles has rapidly increased, leading to an increase in the demand for parking spaces. The most effective method to overcome this is to efficiently manage existing car parks. For this purpose, intelligent transportation system (ITS) applications have been used for facilities. In this study, the effect of guidance according to parking preferences on the utilisation of car parks with the support of an intelligent parking guidance system is examined. The preference and choice of car parks were modelled based on the observed data by developing a simulation program and testing the validity of the model. Subsequently, the effects of various parameters (e.g., parking fees, walking distance, and driving distance) on the selection of car parks, which have been ignored in the existing ITS, were included in the examination of the model. The results indicate that the driving distance and carbon dioxide emission, walking distance, and parking fees are reduced by 17, 14, and 1%, respectively. This study shows that system efficiency can be enhanced by considering additional car park preference parameters in intelligent parking system designs and management. © 2020 Elsevier LtdArticle Citation - WoS: 32Citation - Scopus: 34Spatial and Temporal of Variation of Meteorological Drought and Precipitation Trend Analysis Over Whole Mauritania(Elsevier, 2020) Yacoub, Ely; Tayfur, GökmenUsing monthly precipitation data from 15 stations, well spread over whole Mauritania, and recorded for a long period of time (1919-2016) of almost 100 years, a classification of drought is performed, based on its intensity and duration. For this purpose, the gamma-Standardized Precipitation Index (gamma-SPI) is used to detect drought events (drought frequency, duration and intensity). The Mann-Kendall Test (MK test) is employed for the trend analysis of the precipitation data at all stations and the Thiel-Sen Approach is used to calculate the magnitude of the slopes of the trends. The drought analysis results show that there were severe and extreme drought conditions seen all over the country, especially in 1970s and 1980s. This serious case seems to be emerging in early 2010s. The drought conditions in recent years seems to be more pronounced in the central and southern regions of the country. The trend analysis results reveal that there is no depletion observed in precipitation at the northern region. The total deficit in precipitation is about 100 mm or less during almost 100 year period at the western region. However, the results show that there is pronounced decrease in precipitation at the southern region, reaching to almost a total of 300 mm deficit in nearly 100-year period.