The Experts below are selected from a list of 7038 Experts worldwide ranked by ideXlab platform
Abdurrahman Tanyolac - One of the best experts on this subject based on the ideXlab platform.
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effects of phase vector and history extension on prediction power of adaptive network based fuzzy inference system anfis model for a real scale anaerobic wastewater treatment plant operating under unsteady state
Bioresource Technology, 2009Co-Authors: Altunay Perendeci, Abdurrahman Tanyolac, Sever Arslan, Serdar S CelebiAbstract:Abstract A conceptual neural fuzzy model based on adaptive-network based fuzzy inference system, ANFIS, was proposed using available input on-line and off-line operational variables for a Sugar Factory anaerobic wastewater treatment plant operating under unsteady state to estimate the effluent chemical oxygen demand, COD. The predictive power of the developed model was improved as a new approach by adding the phase vector and the recent values of COD up to 5–10 days, longer than overall retention time of wastewater in the system. History of last 10 days for COD effluent with two-valued phase vector in the input variable matrix including all parameters had more predictive power. History of 7 days with two-valued phase vector in the matrix comprised of only on-line variables yielded fairly well estimations. The developed ANFIS model with phase vector and history extension has been able to adequately represent the behavior of the treatment system.
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electrochemical treatment of simulated beet Sugar Factory wastewater
Chemical Engineering Journal, 2009Co-Authors: Guray Guven, Altunay Perendeci, Abdurrahman TanyolacAbstract:Abstract Electrochemical treatment of simulated beet Sugar Factory wastewater was studied as an alternative treatment method for the first time in literature. Through the preliminary batch runs, appropriate electrode material was determined as iron due to high removal efficiency of chemical oxygen demand, COD, and turbidity. The effect of operational conditions, applied voltage, electrolyte concentration and waste concentration on COD removal percent and initial COD removal rate were investigated through response surface methodology, RSM. In the set of runs, highest COD removal and COD initial removal rate were realized as 86.36% and 43.65 mg/L min, respectively, after 8 h at the applied voltage of 12 V, 100% waste concentration with 50 g/L NaCl. Treatment conditions were optimized by RSM where applied voltage was kept in the range, electrolyte concentration was minimized, waste concentration, COD removal percent and COD initial removal rate were maximized at 25 °C. Optimum conditions at 25 °C were estimated as 12 V applied voltage, 100% waste concentration and 33.05 g/L electrolyte concentration to achieve 79.66% and 33.69 mg/L min for COD removal and COD initial removal rate, respectively. Kinetic investigations denoted that reaction order of electrochemical treatment reaction was 1.2 with the activation energy of 5.17 kJ/mol. These results support the applicability of electrochemical treatment to the beet Sugar Factory wastewater as an alternative advanced wastewater treatment method with further research.
P B Gangavati - One of the best experts on this subject based on the ideXlab platform.
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exergy analysis of cogeneration power plants in Sugar industries
Applied Thermal Engineering, 2009Co-Authors: S C Kamate, P B GangavatiAbstract:Abstract In this paper, exergy analysis of a heat-matched bagasse-based cogeneration plant of a typical 2500 tcd Sugar Factory, using backpressure and extraction condensing steam turbine is presented. In the analysis, exergy methods in addition to the more conventional energy analyses, are employed to evaluate overall and component efficiencies and to identify and assess the thermodynamic losses. The analysis is carried out for a wide range of steam inlet conditions selected around the Sugar industry’s export cogeneration plant. The results show that, at optimal steam inlet conditions of 61 bar and 475 °C, the backpressure steam turbine cogeneration plant perform with energy and exergy efficiency of 0.863 and 0.307 and condensing steam turbine plant perform with energy and exergy efficiency of 0.682 and 0.260, respectively. Boiler is the least efficient component and turbine is the most efficient component of the plant.
Thomas Parisini - One of the best experts on this subject based on the ideXlab platform.
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identification of neural dynamic models for fault detection and isolation the case of a real Sugar evaporation process
Journal of Process Control, 2005Co-Authors: Krzysztof Patan, Thomas ParisiniAbstract:Abstract The paper deals with problems of fault detection of industrial processes using dynamic neural networks. The considered neural network has a feed-forward multi-layer structure and dynamic characteristics are obtained by using dynamic neuron models. Two optimisation problems are associated with neural networks. The first one is selection of a proper network structure which is solved by using information criteria such as the Akaike Information Criterion or the Final Prediction Error. In turn, the training of the network is performed by a stochastic approximation algorithm. The effectiveness of the proposed fault detection and isolation system is checked using real data recorded in Lublin Sugar Factory, Poland. Additionally, a comparison with alternative approaches is presented.
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model free actuator fault detection using a spectral estimation approach the case of the damadics benchmark problem
IFAC Proceedings Volumes, 2003Co-Authors: Fabio Previdi, Thomas ParisiniAbstract:This paper presents the application to the DAMADICS benchmark fault detection problem of a model-free fault detection technique based on the use of a specific spectral analysis tool, namely, the Squared Coherency Functions (SCFs). The detection of a fault is achieved by on-line monitoring the estimate of the squared coherency function, which is sensitive to the occurrence of significative changes in the plant dynamics. The alarm threshold are based on the estimates of the confidence intervals of the SCF. Results on both simulation and real data of the DAMADICS benchmark (which is developed to approximate the industrial process in a Sugar Factory located in Lublin, Poland) are outlined.
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neural approximators for fault detection of actuators in the presence of friction the case of the damadics benchmark problem
IFAC Proceedings Volumes, 2003Co-Authors: A A Papadimitropoulos, G A Rovithakls, Thomas ParisiniAbstract:Abstract The problem of actuator fault detection (FD) for mechanical systems with friction phenomena is addressed. A novel methodology based on an on-line neuralapproximation scheme is applied to the DAMADICS benchmark problem. The FD algorithm is based on the well known dynamic LuGre model characterizing mechanical friction effects. This friction model is suitable for use in the simulation model of the DAMADICS benchmark which is developed in order to approximate the industrial process in a Sugar Factory located in Lublin (Poland). The approximation scheme makes it possible to evaluate on line suitable thresholds for the detection of incipient or abrupt faults regarding the friction and the spring models of the (considered actuator
Altunay Perendeci - One of the best experts on this subject based on the ideXlab platform.
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effects of phase vector and history extension on prediction power of adaptive network based fuzzy inference system anfis model for a real scale anaerobic wastewater treatment plant operating under unsteady state
Bioresource Technology, 2009Co-Authors: Altunay Perendeci, Abdurrahman Tanyolac, Sever Arslan, Serdar S CelebiAbstract:Abstract A conceptual neural fuzzy model based on adaptive-network based fuzzy inference system, ANFIS, was proposed using available input on-line and off-line operational variables for a Sugar Factory anaerobic wastewater treatment plant operating under unsteady state to estimate the effluent chemical oxygen demand, COD. The predictive power of the developed model was improved as a new approach by adding the phase vector and the recent values of COD up to 5–10 days, longer than overall retention time of wastewater in the system. History of last 10 days for COD effluent with two-valued phase vector in the input variable matrix including all parameters had more predictive power. History of 7 days with two-valued phase vector in the matrix comprised of only on-line variables yielded fairly well estimations. The developed ANFIS model with phase vector and history extension has been able to adequately represent the behavior of the treatment system.
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electrochemical treatment of simulated beet Sugar Factory wastewater
Chemical Engineering Journal, 2009Co-Authors: Guray Guven, Altunay Perendeci, Abdurrahman TanyolacAbstract:Abstract Electrochemical treatment of simulated beet Sugar Factory wastewater was studied as an alternative treatment method for the first time in literature. Through the preliminary batch runs, appropriate electrode material was determined as iron due to high removal efficiency of chemical oxygen demand, COD, and turbidity. The effect of operational conditions, applied voltage, electrolyte concentration and waste concentration on COD removal percent and initial COD removal rate were investigated through response surface methodology, RSM. In the set of runs, highest COD removal and COD initial removal rate were realized as 86.36% and 43.65 mg/L min, respectively, after 8 h at the applied voltage of 12 V, 100% waste concentration with 50 g/L NaCl. Treatment conditions were optimized by RSM where applied voltage was kept in the range, electrolyte concentration was minimized, waste concentration, COD removal percent and COD initial removal rate were maximized at 25 °C. Optimum conditions at 25 °C were estimated as 12 V applied voltage, 100% waste concentration and 33.05 g/L electrolyte concentration to achieve 79.66% and 33.69 mg/L min for COD removal and COD initial removal rate, respectively. Kinetic investigations denoted that reaction order of electrochemical treatment reaction was 1.2 with the activation energy of 5.17 kJ/mol. These results support the applicability of electrochemical treatment to the beet Sugar Factory wastewater as an alternative advanced wastewater treatment method with further research.
S C Kamate - One of the best experts on this subject based on the ideXlab platform.
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exergy analysis of cogeneration power plants in Sugar industries
Applied Thermal Engineering, 2009Co-Authors: S C Kamate, P B GangavatiAbstract:Abstract In this paper, exergy analysis of a heat-matched bagasse-based cogeneration plant of a typical 2500 tcd Sugar Factory, using backpressure and extraction condensing steam turbine is presented. In the analysis, exergy methods in addition to the more conventional energy analyses, are employed to evaluate overall and component efficiencies and to identify and assess the thermodynamic losses. The analysis is carried out for a wide range of steam inlet conditions selected around the Sugar industry’s export cogeneration plant. The results show that, at optimal steam inlet conditions of 61 bar and 475 °C, the backpressure steam turbine cogeneration plant perform with energy and exergy efficiency of 0.863 and 0.307 and condensing steam turbine plant perform with energy and exergy efficiency of 0.682 and 0.260, respectively. Boiler is the least efficient component and turbine is the most efficient component of the plant.
