WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7150
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Article Citation - WoS: 8Citation - Scopus: 9Optimization of the Algal Species Chlorella Miniata Growth: Mathematical Modelling and Evaluation of Temperature and Light Intensity Effects(Elsevier, 2022) Sözmen, Alper Baran; Ata, Ayça; Övez, BikemGrowth of Chlorella miniata, a green microalga was investigated during this study under various temperature and light intensity values with the purpose of determining growth rate changes of the microalgae with cultivation parameters, experiments were carried out using airlift photobioreactors with a study volume of 6 L. Culturing conditions were between 66 and 385 μmol photon m−2 s−1 and between 14 and 30 °C for light intensity and ambient temperature, respectively. Acquired data were then used to test various mathematical models for coherency with experimental results. Aiba Model for light intensity and Skewed Normal Distribution Model for temperature parameters performed superior compared to the rest of the mathematical models used during the study. Utilizing both mathematical models a novel model was deduced to express effects of both light intensity and temperature parameters in combination on algal growth. Then the developed model was used to calculate the optimum growth condition of the species. The proposed mathematical model showed good coherency with experimental data and an average relative error of 1.97% for both temperature and light intensity effects on algal growth. The theoretical optimum temperature and light intensity for the maximum specific growth rate were calculated to be 22.43 °C and 291.5 μmol photon m−2 s−1 respectively.Article Citation - WoS: 24Citation - Scopus: 24GA-optimized model predicts dispersion coefficient in natural channels(IWA Publishing, 2009) Tayfur, GökmenModels whose parameters were optimized by genetic algorithm (GA) were developed to predict the longitudinal dispersion coefficient in natural channels. Following the existing equations in the literature, ten different linear and nonlinear models were first constructed. The models relate the dispersion coefficient to flow and channel characteristics. The GA model was then employed to find the optimal values of the constructed model parameters by minimizing the mean absolute error function (objective function). The GA model utilized an 80% cross-over rate and 4% mutation rate. It started each computation with a population of 100 chromosomes in the gene pool. For each model, while minimizing the objective function, the values of the model parameters were constrained between [-10, +10] at each iteration. The optimal values of the model parameters were obtained using a calibration set of 54 out of 80 sets of measured data. The minimum error was obtained for the case where the model was a linear equation relating dispersion coefficient to flow discharge. The model performance was then satisfactorily tested against the remaining 26 measured validation datasets. It performed better than the existing equations. it yielded minimum errors of MAE = 21.4m2/s (mean absolute error) and RMSE = 28.5m2/s (root mean-squares error) and a maximum accuracy rate of 81%. © IWA Publishing 2009.Article Citation - WoS: 9Citation - Scopus: 11Modeling of Hemodialysis Operation(Springer Verlag, 2010) Abacı, Hasan Erbil; Alsoy Altınkaya, SacideIn this study, a theoretical model was developed to predict the solute concentrations in patients' blood and optimize the efficiency of the hemodialysis operation. The model takes into account simultaneous mass and momentum transfer on the blood side both in radial and axial directions. A key component of the model is the incorporation of the protein adsorption on the inner surface of the membrane. The validity of the model was confirmed with the experimental data available in the literature for two different types of hemodiafilter. To illustrate the importance of including the radial concentration gradients and protein adsorption kinetics in the model, the experimental data were predicted with and without consideration of these effects. The results have shown that assuming uniform concentration in the radial direction or neglecting protein adsorption on the inner surface of the membrane leads to higher error in predicting the experimental data. In addition, significant error can be introduced in the calculation of the dialysis time if protein adsorption is not considered. © 2010 Biomedical Engineering Society.