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Öğe A parameter identifiability and estimation study in Yesilirmak River(2009) Berber, Rıdvan; Yüceer, Mehmet; Karadurmuş, ErdalWater quality models have relatively large number of parameters, which need to be estimated against observed data through a non-trivial task that is associated with substantial difficulties. This work involves a systematic model calibration and validation study for river water quality. The model considered was composed of dynamic mass balances for eleven pollution constituents, stemming from QUAL2E water quality model by considering a river segment as a series of continuous stirred-tank reactors (CSTRs). Parameter identifiability was analyzed from the perspective of sensitivity measure and collinearity index, which indicated that 8 parameters would fall within the identifiability range. The model parameters were then estimated by an integration based optimization algorithm coupled with sequential quadratic programming. Dynamic field data consisting of major pollutant concentrations were collected from sampling stations along Yesilirmak River around the city of Amasya in Turkey, and compared with model predictions. The calibrated model responses were in good agreement with the observed river water quality data, and this indicated that the suggested procedure provided an effective means for reliable estimation of model parameters and dynamic simulation for river streams.Öğe An artificial neural network model for the effects of chicken manure on ground water(2012) Karadurmuş, Erdal; Çeşmeci, Mustafa; Yüceer, Mehmet; Berber, RıdvanIn the areas where broiler industry is located, poultry manure from chicken farms could be a major source of ground water pollution, and this may have extensive effects particularly when the farms use nearby ground water as their fresh water supply. Therefore the prediction the extent of this pollution, either from rigorous mathematical diffusion modeling or from the perspective of experimental data evaluation bears importance. In this work, we have investigated modeling of the effects of chicken manure on ground water by artificial neural networks. An ANN model was developed to predict the total coliform in the ground water well in poultry farms. The back-propagation algorithm was employed for training and testing the network, and the Levenberg-Marquardt algorithm was utilized for optimization. The MATLAB 7.0 environment with Neural Network Toolbox was used for coding. Given the associated input parameters such as the number of chickens, type of manure pool management and depth of well, the model estimates the possible amount of total coliform in the wells to a satisfactory degree. Therefore it is expected to be of help in future for estimating the ground water pollution resulting from chicken farms. © 2011 Elsevier B.V. All rights reserved.Öğe An interactive gis-based software for dynamic monitoring of rivers(Scibulcom Ltd., 2014) Yetik, Mehmet Kazım; Yüceer, Mehmet; Karadurmuş, Erdal; Semizer, Eda; Çalımlı, Ayla; Berber, RıdvanWater quality research and development attempts have been the most valuable resources in the sense of model calibration and verification techniques. Due to the fact that current degree of pollution in rivers and importance of the sustainable water resources management, the interactive river monitoring becomes inevitable. Within the scope of river water quality monitoring, Geographical Information Systems (GIS) are gaining widespread acceptance besides this fast and reliable water quality models and parameter estimation techniques are becoming available. However, integrating water quality models with GIS is limited in literature. This study presents an integrated platform on which ArcMap as a GIS and a water quality model in MATLAB are brought together in an interactive and user friendly manner. The software provides a considerable developments in future real time river monitoring and environmental pollution assessment.Öğe Assessment of the sediment toxicity in Bulgarian and Turkish rivers using the biomarkers in chironomus riparius Mg. (Diptera: Chironomidae)(2012) Duran, Mustafa; Michailova, Paraskeva; Sarı, Adile; Ilkova, Julia; Şen, Alaatin; Karadurmuş, ErdalAs a model organism we used Chironomus riparius Mg. - a widely distributed species that can be reared in the laboratory conditions and has excellent salivary gland chromosomes. The study showed that the genome at cytogenetical and biochemical levels is a sensitive biomarker and can serve as early - warning indicators of environmental impact of chemicals. Analysis of trace metals in sediment of Chaya River (Asenovgrad, Bulgaria, 2010) and Derincay River (Turkey, 2010), indicated higher concentrations of trace metals (Pb, Cr, Cu, Cd) in comparison with reference data. The response at cytogenetical level is determined by changes of gene expression of key structures (BRs and NOR) and increased in structural chromosome somatic aberrations. Changes of gene expression are indicated by decreasing the transcriptional activity of BRs and NOR: very often they occurred in the intermediate state of activity or BRs are in collapse. The cells with somatic rearrangements of C. riparius from polluted Derincay and Chaya River were in 16.94% and 36.36% respectively, which were significantly higher than those of the control (Derincay River: G = 125.53, P<0.001; Chaya River: G = 73.81, P<0.001). Somatic index was the highest in the sample from Chaya River - 3.25, following by Derincay River -1.58, while it was 0.13 in the control sample. The response of the C. riparus at biochemical level is characterized by increaseing amount of metallothionein (MT) higher in Chaya River in comparison of Derincay River. Similarly, the other studied enzyme activities, GST and EROD, showed on the average 20% and 24% higher activities respectively, in Derincay than in Chaya. In addition, in accordance with above enzyme activities, the level of AChE inhibition is about 10% higher in Derincay River than in Chaya River. As a result, alterations in these biochemical parameters could be regarded as valid reflections of the increased trace metals in Derincay and Chaya Rivers. It could be concluded that the environmental diagnose quality by multilevel approach (cytogenetical and biochemical) will enable better understanding of the impact of pollutants on organisms and should be successful implemented in environmental monitoring procedures.Öğe Genome response of model invertebrates and vertebrates species to stress agents in the environment(2010) Michailova, Paraskeva; Atanasov, Nasko; Ilkova, Julia; Chassovnikarova, Tsenka G.; Duran, Mustafa; Karadurmuş, ErdalThe genome response of model invertebrate and vertebrate species to stress agent in the environment was studied. The both group of species were collected from contaminated water stations along Marisa (Kemera) and Chaya (Asenovgrad) Rivers and terrestrial areas near Asenovgrad. The structural and functional alterations of the salivary gland chromosomes of Chironomus riparius as well as the aberrations of mitotic chromosomes of Apodemus flavicollis and Microtus arvalis were analyzed. In the polytene chromosomes of C. riparius a high spectrum of somatic aberrations were detected, which appeared in significantly higher frequency in comparison of the control (Kemera: G=37.99, df=1, P<0.001; Asenovgrad, G = 42.82, df = 1, P<0.001). Also, the key structure of the polytene chromosomes: Balbiani rings and Nucleolar Organizer decreased their normal function activity which indicates that they are direct target for the stress of contaminants in the environment. The frequency of aberrant cells of small rodents (Apodemus flavicollis and Microtus arvalis) was significantly higher than the control, well expressed in M. arvalis (G = 4.54, df =1, P <0.05). In both groups of studied species genome instability were found, realized by many structure chromosome rearrangements which can be used as a cost-effective indicator of genotoxicity, and hence suitable markers of potential environmental stress. However, the studied species show differences in their response which might be depended on their biology. © 2010 Taylor and Francis Group, LLC.Öğe Modeling of blending of mineral base oils via artificial neural networks(Czech Society of Chemical Engineering, 2014) Karadurmuş, Erdal; Akyazı, Habib; Yüceer, Mehmet[No abstract available]Öğe Physical properties of LLDPE and PP filled with wood flours(American Society of Mechanical Engineers (ASME), 2015) Baş, Gamze Sultan; Sancaktar, Erol; Karadurmuş, ErdalIn this study, composites of polypropylene (PP), as well as linear low density polyethylene (LLDPE) thermoplastics filled with wood flour have been investigated to study the effect of size and amount of wood flour on their mechanical, thermal and aging properties. PP and LLDPE were mixed with five different types of wood flour, i.e., cedar, maple, oak, poplar, and select pine, by adding different percentages of wood flour at 30, 40 and 50 weight percentages. Mixing was done using a mini compounder at 180-210ºC and dog-bone shape samples were produced by using a mini-injection molding machine. Two different sizes of wood flour labeled as thin (425 – 500 µm) and thick (600 – 710 µm) were compared for PP-wood and LLDPE-wood composites. Mechanical properties of blends were investigated by tensile testing and thermal behaviors of blends were characterized by using DSC analyses. Poplar and maple show better tensile results among other wood types with 543.7 MPa and 600.5 MPa Young’s modulus and 21.05 MPa and 24.53 MPa tensile strength for LLDPE when comparing thick and thin wood flour blends, respectively. In the case of PP; poplar and select pine gave higher Young’s modulus and tensile strength results. Samples were also aged in acid and water solution for 3 days, and their weight and dimensional changes were recorded and compared with neat polymer samples to show physical stabilityÖğe Prediction of bromate removal in drinking water using artificial neural networks(Taylor and Francis Inc., 2018) Karadurmuş, Erdal; Taşkın, Nur; Göz, Eda; Yüceer, MehmetIn treatment of natural water resources, bromide transforms into carcinogenic bromate, especially during the ozonation process. Adsorption was used in the experimental part of this study to remove this harmful compound from drinking water. For this purpose, technically, HCl-, NaOH-, and NH3-modified activated carbons were used. Scanning Electron Microscopy (SEM) and Brunauer–Emmett–Teller (BET) analyses were carried out within the characterization study. Moreover, the effects of diameters and heights of adsorption columns, flowrate, and particle size of adsorbent were investigated on the removal amounts of bromate. Optimum conditions were obtained from the experiments, and regional/real samples were collected and analyzed. After the experiments, an artificial neural network (ANN) was used to predict bromate removal percentage by using the observed data. Within this context, a feed-forward back-propagation ANN was chosen in this study. Additionally, the transfer function was selected as tangent sigmoid and 3 neurons were used in the hidden layer. Particle size and amount of the activated carbon, height and diameter of the column, volumetric flowrate, and initial concentration were selected as the input variables. Bromate removal percentage was selected as the output. It was found that the model an R value of 0.988, RMSE value of 3.47 and mean absolute percentage error (MAPE) of 5.19% in the test phase. © 2018, © 2018 International Ozone Association.Öğe Prediction of characteristic properties of crude oil blending with ANN(Taylor and Francis Inc., 2018) Karadurmuş, Erdal; Akyazı, Habib; Göz, Eda; Yüceer, MehmetMineral oil is one of the most important materials on earth and it is used widely for its several features. Mineral oils derived from petroleum products are commonly used to decrease the friction effects in machine parts and, thus, they both prevent wear/overheating and facilitate power transmission. In this study, various binary mixtures of various base oils (SN-80, SN-100, SN-150, SN-50, SN-500) were prepared at different volumetric ratios. Kinematic viscosity (at 40°C and 100°C), viscosity index, flash point, pour point, and density (at 20°C) measurements were performed for characterization of the prepared mixtures. These values were modeled by an artificial neural network (ANN) and the model was tested with root mean squared error (RMSE), mean absolute percentage error (MAPE, %), and regression coefficient (R) values. A higher value of correlation coefficient and smaller values of MAPE and RMSE indicate that the model performs better. For predicting kinematic viscosity at 40°C, correlation coefficients were calculated for training and testing the network as 0.9999 and 0.9995, respectively. Respective MAPE values were determined as 1.011% and 1.8771%. © 2017, © 2017 Taylor & Francis.Öğe River water quality model verification through a GIS based software(2009) Yetik, Mehmet Kazım; Yüceer, Mehmet; Berber, Rıdvan; Karadurmuş, ErdalResearch and development attempts on water quality models created valuable resources in the sense of model calibration and verification techniques. Recognizing the current degree of pollution in rivers and the importance of the sustainable water resources management, the interactive river monitoring appears to be at the center of recent focus. However the available information in this area is still far from expectations. On one side, the Geographical Information Systems (GIS) are gaining widespread acceptance and on the other side fast and reliable water quality models and parameter estimation techniques are becoming available. However, previous work on integrating water quality models and GIS is very limited. This work brings an integrated platform on which ArcMap as a GIS and a water quality model in Matlab™ are brought together in an interactive and user-friendly manner. The software developed allows the user to enter the data collected from the river, runs the dynamic model in the Matlab™ environment, predicts the values of pollution constituents along the river, extracts the results and displays the water quality on the map in different forms. The software thus provides a considerable ease in future real time application for on site river monitoring and environmental pollution assessment.
