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: 14Citation - Scopus: 15Investigation of the Effect of Gel Properties on Supercritical Drying Kinetics of Ionotropic Alginate Gel Particles(Elsevier, 2019) Şahin, İbrahim; Uzunlar, Erdal; Erkey, CanA series of spherical ionotropic alginate gel particles with different diameters ranging from 2.8mm to 5.0mm and porosities ranging from 0.899 to 0.976 were prepared by dripping a Na-alginate solution into a solution of salts of divalent cations (Ca2+, Mn2+, Ni2+, Co2+, Cu2+ and Zn2+). After solvent exchange with ethanol, kinetics of supercritical drying of these ionotropic alginate gel particles in a packed bed was investigated at 308-338 K and 100-120 bar. Experimental data were compared with predictions of a model which considers diffusive transport inside the pores and convection in the flowing fluid stream. The model predicted drying profiles by taking into account only the changes in porosity and diameter of the gel particles. A convective mass transfer coefficient correlation that was originally developed for supercritical drying of Ca-alginate gel particles was found to be suitable for M-alginate gel particles. (C) 2019 Elsevier B.V. All rights reserved.Article Citation - WoS: 23Citation - Scopus: 24Investigation of Kinetics of Supercritical Drying of Alginate Alcogel Particles(Elsevier Ltd., 2019) Şahin, İbrahim; Uzunlar, Erdal; Erkey, CanSpherical calcium alginate gel particles were synthesized by dripping method. The effects of temperature, pressure, particle size and CO2 flow rate on kinetics of supercritical drying of alginate gel particles in a packed bed were investigated. Increase in CO2 flow rate, increase in temperature and decrease in particle size increased the drying rate and decreased the drying time. A mathematical model based on (i) the diffusion of the solvent inside the pores of gel particles, (ii) external mass transfer of the solvent from the surface of the gel particles into the flowing fluid stream, and (iii) convection and axial dispersion of the solvent in the flowing fluid stream was developed. A correlation for predicting external mass transfer coefficients for supercritical drying of alcogel particles was developed by fitting the model to experimental data. A good agreement between the experimental data and model results was achieved using the developed correlation.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.