Showing 9 results for Optimization
Alireza Chackoshian Khorasani, Mansour Mashreghi, Soheila Yaghmaei,
Volume 6, Issue 4 (3-2014)
Abstract
Background and Objectives: Optimization of mazut biocracking with different variables is one of the bioengineering applications in petroleum industry. The purpose of this study was to optimize biocracking of mazut by native microorganisms. Materials and Methods: To optimize mazut cracking, using Taguchi method we run 32 experiments using seven factors including amount of microbial inoculation, initial pH, surfactant, glucose, phosphor source, nitrogen source and sea salt each of them with four levels and factor of microorganism type with two levels for design of experiment using that 32 experiments were designed by them. Results: Results showed that microbial mixture, 0.016 OD600 microbial inoculations, pH 8.3, Tween80 concentration of 2 g/L, glucose concentration of 4 g/L, phosphate concentration of 5 g/L, ammonium concentration of 9 g/L and sea salt concentration of 0.5 g/L were optimized conditions for biocracking of mazut process. Conclusion: Optimized level for each factor was not essentially inevitably the highest or the lowest level. Based on the analysis of variance, phosphor source with 15.8% and pH with 14.8% had the highest effect among other factors however overally, error factor with 31.6% had the highest influence. Amount of microbial inoculation with 0.63% had the lowest effect on optimizing biocracking of mazut.
Samaneh Ghodrati, Gholamreza Moussavi,
Volume 7, Issue 2 (10-2014)
Abstract
Background and objectives: Electrocoagulation (EC) as an electrochemical method was developed to overcome the drawbacks of conventional decolorization technologies and is an attractive alternative for the treatment of textile dyes. This study was aimed at the optimization of the EC process for decolorization and COD removal of a real textile wastewater using response surface methodology (RSM). RSM is an important branch of experimental design and a critical technology in developing new processes, optimizing their performance, and improving design and formulation of a new products. Materials and Methods: In this study, a bench scale EC reactor was designed, constructed, and studied for treatment of a textile wastewater. The main operational variables were current intensity, residence time, initial pH, and electrode materials as independent variables color and COD removal were considered as dependent variables. The experimental runs were designed using selected variables using Design Expert 7.0 software and the process was optimized for decolorization and COD removal using the response surface method. Results: The optimal operational conditions in the EC process for attaining the maximum decolorization and COD removal were current density of 0.97 A, initial pH of 4.04, residence time of 48 min, and Fe electrode. The desirability factor for Fe electrode was 1, while decolorization and COD removal were predicted 76.3 and 75.6% respectively, which was confirmed by the experimental results. Conclusion: The experimental results indicated that the EC process is an efficient and promising process for the decolorization and COD removal of textile effluents. Under the optimized conditions, the experimental values had a good correlation with the predicted ones, indicating suitability of the model and the success of the RSM in optimizing the conditions of EC process in treating the textile wastewater with maximum removals of color and COD under selected conditions of independent variables.
A Moghaddam, M Mokhtari, R Peirovi,
Volume 10, Issue 3 (12-2017)
Abstract
Background and Objective: one of the steps in water treatment to protect microbial quality of water network is disinfection. Chlorine is one of disinfectants. It is necessary to maintain Free Residual Chlorine (FRC) between minimum and maximum throughout the distribution system in accordance to health standards. This study was aimed to optimize Chlorine dosage in water distribution networks using GANetXL model.
Materials and Methods: In this paper for the first time using an add-in called GANetXL optimization that uses a genetic algorithm, the Chlorine injection was optimized in a reference network based on dynamic connection to EPANET2 hydraulic and qualitative analysis in Excel software. The objective function is formulated such that the squared difference between computed chlorine concentrations and the minimum residual concentration at all monitoring nodes at all times is minimum. The decision variables were the optimized injection dose at boosters’ locations.
Results: The injection rate was obtained (minimum: 0, average: 183.87, maximum: 776.57 and total 4412.84 mg/min per a day) at the station as the number of generation was reduced to 200. Critical nodes formed 20% of the total nodes of network.
Conclusion: Based on the results, minimization of Chlorine whilst comply with FRC standard has both health and economical effects. The results can help the water distribution system management in terms of water quality (by maintaining FRC), health promotion and monetary.
M Sabonian, Ma Behnajady,
Volume 11, Issue 2 (9-2018)
Abstract
Background and Objective: Chromium is present in two oxidation forms of Cr(III) and Cr(VI). Cr(III) is less toxic than Cr(VI). The aim of this article was to optimize an artificial neural network structure in modeling the photocatalytic reduction of Cr(VI) by TiO2-P25 nanoparticles.
Materials and Methods: In this work, an artificial neural network (ANN) for the modeling photocatalytic reduction Cr(VI) by TiO2-P25 nanoparticles were used and its structure was optimized. The operating parameters were initial concentration of chromium, amount of photocatalyst, ultraviolet light irradiation time and pH. All the experiments were conducted in a batch photoreactor. The Cr(VI) concentration was measured with a UV/Vis spectrophotometer. ANN calculations were performed using Matlab 7 software and the ANN toolbox.
Results: The results show that the optimization of the ANN structure and the use of an appropriate algorithm and transfer function could significantly improve performance. The proposed neural network in modeling the photoactivity of TiO2-P25 nanoparticles in reducing Cr(VI) was acceptable, based on a good correlation coefficient (0.9886) and a small mean square error (0.00018). All the input variables affected the reduction of Cr(VI), however the effect of pH with an impact factor of 34.15 % was more significant than the others. The results indicated that pH = 2 was the best pH for photocatalytic reduction of Cr(VI). Increasing photocatalyst dosage and irradiation time in the investigated range increased Cr(VI) photocatalytic reduction.
Conclusion: Optimized structure of the ANN includes a three-layer feed-forward back propagation network with 4:10:1 topology and the most appropriate algorithm is a scaled conjugate gradient backpropagation algorithm.
M Hadi, M Solaimany Aminabad, M Amiri, M Arjipour,
Volume 11, Issue 3 (12-2018)
Abstract
Background and Objective: Treatment of hospital wastewaters has an important role in reducing the discharge of organics and pharmaceutical compounds into aquatic environments. Nowadays, advanced oxidation processes were extensively used for the removal of organic compounds from treated effluents. The study aimed to examine organic compounds removal from real treated effluent of a hospital treatment plant using a lab scale UV/H2O2/TiO2 process by optimizing the process.
Materials and Methods: The effluent characteristics including COD, TOC and DOC were measured and recorded. A hybrid advanced oxidation process (UV/H2O2/TiO2) was used for the removal of organic compounds. The experiments were designed using surface response methodology (RSM). The effects of the independent factors including pH, duration of UV irradiation, H2O2 and TiO2 concentrations on COD, TOC, DOC and the approximate cost of treatment were assessed by analysis of variance (ANOVA).
Results: The optimal condition was 7.2 for pH, 50 mg/L for H2O2, 100 mg/L for TiO2 and 19.65 min for irradiation time. This condition provided the maximum removal percentage for organic compounds with a minimum cost. The removal efficiency for TOC, DOC and COD were 63.9, 52.9, and 64.7%, respectively. The treatment cost was approximated to be $ 0.71 per one liter of the effluent.
Conclusion: Irradiation and H2O2 concentration had the greatest impact on the cost of the treatment. UV/H2O2/TiO2 process seems to be an expensive process for tertiary treatment of wastewater. However, further investigations are required to evaluate the cost effectiveness of the process for a full scale operation.
Maryam Razavi Mehr, Mohammad Hossein Fekri, Fatemeh Mohammadi Shad ,
Volume 14, Issue 2 (9-2021)
Abstract
Background and Objective: Due to the water shortages and the presence of industrial pollutants in water resources, wastewater treatment, especially colored wastewater, is essential. The aim of this study was to treat wastewater containing Methylene Blue dye using activated carbon nanocomposite/zinc oxide nanoparticles (ZnO/AC) obtained from canola oil waste by green method.
Materials and Methods: In the present study, the effect of different parameters (pH, Methylene Blue concentration, adsorbent amount, temperature and contact time) on the adsorption of Methylene Blue was investigated. Design of Experiment 7 software (Response Surface Method (RSM)) was used to evaluate the influence of various parameters on Methylene Blue removal.
Results: The results of the predicted experiments showed that the highest adsorption of Methylene Blue is at pH = 10, temperature 70 °C, contact time of 50 min, initial adsorption concentration of 10 mg/ L and adsorbent amount of 0.05 g. Under optimal conditions, ZnO/AC adsorbent was able to remove 98.22% of Methylene Blue from the aqueous medium.
Conclusion: Appropriate to the high potential of ZnO/AC nanocomposite in the removal of Methylene Blue pigment, it can be a good candidate for the removal of dye contaminants and wastewater treatment of textile factories.
Mohamad Javad Zoqi,
Volume 14, Issue 3 (12-2021)
Abstract
Background and Objective: The most used dyes in textile industries are Azo Group dyes. Azo dyes have complex aromatic compounds, low chemical and biodegradable stability. Due to these properties, treatment of this type of wastewater by conventional methods will not meet environmental standards. The advanced oxidation process has been widely used to treat organic matter from wastewater. In this study, dye purification of azo dye Reactive Red 195 by UV/H2O2 process was investigated. Moreover, the parameters affecting this process have also been determined.
Materials and Methods: In this study, dye treatment was conducted in the presence of different concentrations of hydrogen peroxide, and at different retention time, temperature and pH values in a continuous photoreactor equipped with UV lamps. Using central composite design and response surface methodology (RSM), effects of various concentrations of hydrogen peroxide, retention time, temperature, and pH on the color and COD removal were studied in the range of 0–2%, 60-240 min, 25-80 oC, and 3-10, respectively.
Results: The results showed that the concentration of hydrogen peroxide and retention time were the most influential parameters on color and COD removal. Color removal significantly enhanced by increasing retention time and H2O2 concentration to 200 min and 1.2%, respectively. pH increase had positive effect on color removal. There were increases in the rate of color and COD removal as the temperature went up to 50 oC. However, temperature of 80 oC negatively impacted AOP process. According to RSM, the optimum factor levels were achieved at 1.28%, 240 min, 49 oC and 10 for concentrations of hydrogen peroxide, reaction time, temperature, and pH, respectively.
Conclusion: According to the result, UV/H2O2 proved to be capable of degrading Reactive Red 195. Almost all the azo dye color destroyed after 209 min while 87.52 % of the COD was removed after 240 min of irradiation.
Mehrab Aghazadeh, Amirhesam Hasani, Mehdi Borghei,
Volume 15, Issue 3 (12-2022)
Abstract
Background and Objective: Based on its unique characteristics, oil industry wastewater must be treated before discharging into the environment. The study aimed to optimize the catalytic sonopraxone process in the treatment of petroleum wastewater using a statistical method.
Materials and Methods: The synthesis of Iron Oxide-Zinc Oxide was carried out by air oxidation and layer-by-layer self-assembly method. XRD, SEM, EDAX, FT-IR, BET, DRS, VSM and TGA techniques were used to investigate the structure. In this study, applied CCD method optimization of pH parameters, reaction time, ozone gas concentration, hydrogen peroxide concentration and catalyst amount in the process. In optimal conditions, BOD5 and TPH removal values, reaction kinetics and synergistic effect of mechanisms were studied. COD, TPH and BOD5 were measured by spectrophotometer (DR6000), GC-FID and incubator, respectively.
Results: The results indicated that the Fe3O4@ZnO structure is well formed. A quadratic model was proposed to model the process based on the correlation coefficient. Based on ANOVA analysis and p and f indices, the proposed model was reported to be significant. Optimum conditions include pH 6.4, ozone concentration 1.3 mg/L.min, hydrogen peroxide concentration 2.5 mL/L, reaction time 51 min and catalyst amount equal to 0.64 g/L. In these conditions, the amount of COD reduction was 82.3 and 70% theoretically and experimentally, respectively. Also, in optimal conditions, BOD5 and TPH removal rates were 90.5% and 85.8%, respectively. The kinetics of the process follows the kinetics of the first order (R2=0.98) and the presence of different mechanisms together causes a synergistic effect and increases the efficiency of the process.
Conclusion: This process can improve the quality of oil effluent based on COD, BOD5, and TPH removal.
Mohammad Hossein Fekri, Samaneh Soleymani, Maryam Razavi Mehr, Fatemeh Saki,
Volume 16, Issue 2 (9-2023)
Abstract
Background and Objective: Due to the presence of industrial pollutants in water sources, it is necessary to treat wastewater, especially colored wastewater. This study aims to treat wastewater containing methyl orange dye using nano mesopore SBA-16.
Materials and Methods: In this study, the effect of different parameters (pH, concentration of methyl orange, amount of adsorbent, temperature, and contact time) on the absorption of methyl orange by nanocomposite prepared with the help of Design of Experiment 7 software and Response Surface Method (RSM) was investigated.
Results: The maximum amount of pollutant removal by the adsorbent was obtained under optimal conditions of pH = 4.07, temperature 50 °C, contact time 35 minutes, initial concentration of adsorbent 10 mg/L, and amount of adsorbent 0.04 g. Also, the findings showed that the absorption behavior is most consistent with the Langmuir isotherm and the absorption process is exothermic and spontaneous at low temperatures.
Conclusion: In optimal conditions, the SBA-16 adsorbent was able to remove 98.60 % of methyl orange from the aqueous solution and the maximum adsorption capacity (qmax) for the removal of methyl orange pollutant was 37.73 mg/g. Considering the high potential of nano mesopore SBA-16 in removing methyl orange pigment, it can be considered a suitable candidate for removing colored pollutants and treating wastewater from textile factories.
