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Papers by mehmet yüceer

An interpenetrated polymer network (IPN) poly(NIPAAm-co-AAc) hydrogel was synthesized by two poly... more An interpenetrated polymer network (IPN) poly(NIPAAm-co-AAc) hydrogel was synthesized by two polymeriza-tion method: emulsion and solution polymerization. The pH-and temperature-sensitive hydrogel was loaded by swelling with riboflavin drug, a B2 vitamin. The release of riboflavin as a function of time has been achieved under different pH and temperature environments. The determination of experimental conditions and the analysis of drug delivery results were achieved using response surface methodology (RSM). In this work, artificial neural networks (ANNs) in MATLAB were also used to model the release data. The predictions from the ANN model, which associated input variables, produced results showing good agreement with experimental data compared to the RSM results.

Chemical and Process Engineering - Inzynieria Chemiczna i Procesowa, 2013

Saccharamyces cerevisia known as baker's yeast is a product used in various food industries. Worl... more Saccharamyces cerevisia known as baker's yeast is a product used in various food industries. Worldwide economic competition makes it a necessity that industrial processes be operated in optimum conditions, thus maximisation of biomass in production of saccharamyces cerevisia in fedbatch reactors has gained importance. The facts that the dynamic fermentation model must be considered as a constraint in the optimisation problem, and dynamics involved are complicated, make optimisation of fed-batch processes more difficult.

Particulate Science and Technology, 2013

The present study aims to response surface methodology (RSM) for predicting magnetizing propertie... more The present study aims to response surface methodology (RSM) for predicting magnetizing properties of the matrix's elements of the magnetic filter that are constructed from the bi-mixture of the magnetic balls of various sizes, employed in the cleaning of the disperse mixture of water and corrosion particles (rust) of low concentrations. Based on a three-level central composite design (CCRD) involving

Water Resources Management, 2013

ABSTRACT Prediction of longitudinal dispersion coefficient (LDC) is still a novel topic for both ... more ABSTRACT Prediction of longitudinal dispersion coefficient (LDC) is still a novel topic for both environmental and water sciences due to its practical importance. In this study, the appraisal of LDC is considered as a spatial modelling problem and the analyses are carried out by regression kriging. Since LDC prediction includes some geometrical (spatial) parameters, the analyses have been performed such that it takes spatial variability of data into account. The modelling procedure consists of two stages. In the first stage, spatial variables are analyzed via multi-linear regression technique and deterministic relationships are identified. In the second stage, based on the spatial auto-correlations of the residuals, the regression-based kriging procedure is applied. The capacity and accuracy level of the method has been compared with former models. As a consequence, the applications revealed that analyzing hydraulic and geometrical parameters with spatially correlated errors is a convenient approach for evaluating LDC in a hydrological system.

Applied Soft Computing Journal, 2012

In the areas where broiler industry is located, poultry manure from chicken farms could be a majo... more In 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.

Chemical Engineering Research and Design, 2012

ABSTRACT To obtain the most suitable control algorithm for a wearable artificial pancreas, differ... more ABSTRACT To obtain the most suitable control algorithm for a wearable artificial pancreas, different control algorithms were compared and tested using a Hovorka model. Model predictive control (MPC), linear and nonlinear model forms, proportional integral derivative control (PID), neural-network-based model predictive control (NN-MPC), nonlinear autoregressive moving average (NARMA-L2) and sequential quadratic programming (SQP) were evaluated using the Hovorka model. Due to the fact that modeling of biomedical processes are very complex, to present the most effective control algorithm, various control strategies were needed to application. In the control algorithms, set point tracking and disturbance rejection were performed. With respect to the rise times of the control algorithms, SQP with optimal control had the shortest time, and NARMA-L2 had the longest time. Because the control algorithm connects the glucose meter and the insulin pump in an artificial pancreas, the rise time is the most important parameter. We propose that optimal control with SQP is the most suitable control algorithm to connect the glucose meter and the insulin pump.

Optimal Control Applications and Methods, 2009

Determination of the optimal aeration profile for an activated sludge system in which nitrificati... more Determination of the optimal aeration profile for an activated sludge system in which nitrification and denitrification take place sequentially in a single reactor (alternating aerobic-anoxic) is an attractive optimization problem because of complexities involved in, and high computational times required for solution. The rigorous dynamic modeling and start-up simulation of such a system, together with aeration profile optimization by an evolutionary algorithm (EA), were tackled in a previous study. In this paper an easy-to-implement dynamic optimization technique based on sequential quadratic programming method and control vector parameterization approach is provided. In comparison with EA, the proposed algorithm gives better results in shorter computation times. main operational cost. Determining the optimum durations of consecutive aeration and non-aeration periods in order to minimize the energy consumption is a nontrivial dynamic optimization problem. The dynamical character comes from the complicated dynamic model Figure 1. Schematic diagram of an activated sludge system.

Chemical Engineering and Technology, 2009

This study involves real-time monitoring and fault diagnosis in batch baker's yeast fermentation.... more This study involves real-time monitoring and fault diagnosis in batch baker's yeast fermentation. A specific Real Time Statistical Process Analysis and Control (RT-SPAC) program was developed to monitor instantaneous reaction conditions. The air flow rate fed to the reactor, temperature, pH, and dissolved oxygen concentration in a laboratory-size fermenter were monitored and recorded by means of on-line sensors. Under control of the RT-SPAC program, 22 batch baker's yeast fermentation operations were carried out. In the first 20 operations, an ordinary process was followed under previously defined nominal operating conditions. Historical data collected from these batches were then used for online Dynamic Principal Component Analysis (DPCA) in the course of the following two batches. The last two batches were implemented such that some deliberate faults (in temperature and pH) were introduced during the operation. The results indicated that the software was capable of capturing the process faults, and furthermore the possible causes of these faults were identified by contribution plots.

Mathematical and Computer Modelling, 2007

This work considers optimal scheduling of a set of orders in a multi-product batch plant with non... more This work considers optimal scheduling of a set of orders in a multi-product batch plant with non-identical parallel processing units where the process is single stage. The allocation of orders to the production units was formulated as an MILP problem in continuous time. Starting from the basic model proposed earlier, and adding a new constraint that was missing in previous literature, the new formulation solves the problem with a different objective function which considers the total production time or total production cost of the set of orders, without resorting to the application of any heuristic rules. A special MATLAB program has been developed for automatic creation of the optimization model, which otherwise may be a very time consuming task prone to errors. The formulation has been tested with extensive numerical, as well as one industrial, problems. The results indicate importance of the proposed modifications and effectiveness of the automated generation of the model, and present better solutions for the industrial example considered.

Chemical Engineering and Technology, 2007

Acrylic fiber is commercially produced by free radical polymerization, initiated by a redox syste... more Acrylic fiber is commercially produced by free radical polymerization, initiated by a redox system. Industrial production of polyacrylonitrile is a variant of aqueous dispersion polymerization, which takes place in a homogenous phase under isothermal conditions with perfect mixing. The fact that the kinetics are a lot more complicated than those of ordinary polymerization systems makes it difficult to control the molecular weight. On the other hand, abundant data is being gathered in industrial polymerization systems, and this information makes the neural network based controllers a good candidate for managing such a difficult control problem. Multilayer neural networks have been applied successfully in the identification and control of dynamic systems. In this work, the neural network based control of continuous acrylonitrile (ACN) polymerization is studied, based on a previously developed new rigorous dynamic model for the polymerization of acrylonitrile. Two typical neural network controllers are investigated, i.e., model predictive control and NARMA-L2 (Nonlinear Auto Regressive Moving Average) control. These controllers are representative of the variety of common ways in which multilayer networks are used in control systems. The results present a comparison of the two common neural network controllers, and indicate that the model predictive controller requires a larger computational time.

Mathematical and Computer Modelling, 2007

Predictions and quality management issues for environmental protection in river basins rely on wa... more Predictions and quality management issues for environmental protection in river basins rely on water-quality models. These models can be used to simulate conditions in or near the range of the calibrated or verified conditions. In this respect, estimation of parameters, which is still practiced by heuristic approaches (i.e. manually), seems to be the point where the attention needs to be focused. The authors' research group has developed a systematic approach for dynamic simulation and parameter estimation in river water quality models, which has eliminated the cumbersome trial-end-error method. This study reports a user-interactive software named as RSDS (River Stream Dynamics and Simulation) for the implementation of the suggested technique, and provides a comparative investigation of the suggested modelling approach against a well established and worldwide known water quality software, QUAL2E. Experimental data collected in field observations along the Yesilirmak river basin in Turkey were checked against the predictions from both software programs. The results indicated that much better agreement with the experimental data could be obtained from RSDS compared with QUAL2E. Thus, the systematic procedure suggested in the present work provides an effective means for reliable estimation of the model parameters and dynamic simulation for river basins, and therefore, contributes to the efforts toward predicting the extent of the effect of possible pollutant discharges in river basins.

Computer Aided Chemical Engineering, 2006

Acrylic fiber is commercially produced by free radical polymerization, initiated by a redox syste... more Acrylic fiber is commercially produced by free radical polymerization, initiated by a redox system. The fact that the kinetics is a great deal more complicated than that of ordinary polymerization systems makes the problem of controlling molecular weight a difficult one. In this study, dynamics and control of continuous acrylonitrile polymerization are studied based on a previously described kinetics by Peebles (Applied Polymer Science, 1973, 17, 113–128). As the conventional feedback controller was found to be unsuccessful, a model state feedback (MSFB) control strategy was implemented. The performances of linear and nonlinear controllers have been compared via simulation, and it was concluded that the nonlinear form would be effectively employed for set point tracking as well as disturbance rejection.

Chemical Engineering and Processing: Process Intensification, 2005

Chemical engineering problems formulated as mixed integer nonlinear programming (MINLP) model are... more Chemical engineering problems formulated as mixed integer nonlinear programming (MINLP) model are difficult to solve when the model is non-convex. In order to overcome this difficulty, a semi-heuristic algorithm for production scheduling was developed in this work. Using this approach, the non-convex MINLP problem is first considered as an MILP problem without dividing the orders into units. The order causing prolonged delivery time is thus identified, constraints for this order are then relaxed and MILP problem is re-solved using the new constraints. Having reached the new schedule, the quantitative distribution of the specific order to different units is determined by solving the LP problem that does not contain integer variables since allocation of orders to the units, and processing order are known. The results obtained with three example problems indicate improvements over previously reported schedules and therefore, give promise that the suggested strategy may be used in moderately sized industrial applications.

Computer Aided Chemical Engineering, 2005

A common problem in model verification is to determine the values of model parameters that provid... more A common problem in model verification is to determine the values of model parameters that provide the best fit to measured data, based on some type of least squares or maximum likelihood criterion. In the most general case, this requires the solution of a nonlinear and frequently nonconvex optimization problem. Some of the available software lack in generality, while others do not provide ease of use. As the need for a user-interactive parameter estimation software, especially for identifying kinetic parameters, was needed; in this work we developed an integration based optimization approach to provide a solution to such problems. For easy implementation of the technique, a parameter estimation software (PARES) has been developed in MATLAB environment. When tested with extensive example problems from literature, the suggested approach is proven to provide good agreement between predicted and observed data within relatively less computing time and iterations.

Computer Aided Chemical Engineering, 2003

... A Semi Heuristic MINLP Algorithm for Production Scheduling Mehmet Yuceer, Ilknur Atasoy andRi... more ... A Semi Heuristic MINLP Algorithm for Production Scheduling Mehmet Yuceer, Ilknur Atasoy andRidvan Berber Department of Chemical Engineering ... In a most recent work, Berber and Ozdemir (2003) identified one deficiency and two misconception about the formulation of ...

Journal of Food Processing and Preservation, 2012

ABSTRACT Effects of microwave power output and sample mass on drying behavior, color parameters, ... more ABSTRACT Effects of microwave power output and sample mass on drying behavior, color parameters, rehydration characteristics and some sensory scores of thyme leaves were investigated. Within the range of the microwave power outputs, 180-900W, and sample amounts, 25-100g, moisture content of the leaves were reduced to 0.1±(0.01) from 4.05kg water/kg dry base value. Drying times of the leaves were found to be varying between 3.5 and 15.5min for constant sample amount, and 6.5 and 20.5min for constant power output. Experimental drying data obtained were successfully modeled using artificial neural networks methodology. Statistical values of the test data were found to be 0.9999, 4.0937 and 0.025 for R-square, MAPE (%) and RMSE, respectively. Some changes were recorded in the quality parameters, and acceptable sensory scores for the dried leaves were observed in all of the experimental conditions (P<0.05). © 2012 Wiley Periodicals, Inc.

Journal of Dispersion Science and Technology, 2011

ABSTRACT In this study, we aimed at optimizing the parameters that govern the separation efficien... more ABSTRACT In this study, we aimed at optimizing the parameters that govern the separation efficiency in the electromagnetic filtration (EMF) of magnetizable dispersed particles from a water medium. Thus, we employed a Nelder-Mead modified simplex algorithm to maximize EMF efficiency choosing the external magnetic field strength, size of the filter matrix elements, filter length, and filtration velocity as variables to be optimized. It has been found that EMF efficiency decreased with increasing the filtration velocity and the size of the filter matrix elements. On the other hand, EMF efficiency increased when the filter length and the external magnetic strength was increased. Four variables were successfully optimized and a maximum level of EMF efficiency percentage of 77.05 was achieved by performing only 26 experiments. The results are expected to be useful in the future to predict the operating conditions of similar EMF systems.

Neural Computing and Applications, 2010

ABSTRACT This work presents an approach to the modeling of a real industrial isomerization reacto... more ABSTRACT This work presents an approach to the modeling of a real industrial isomerization reactor by using artificial neural networks (ANN) pre-processed with principal component analysis (PCA). The initial model considered the output fructose concentration as the output variable, while the flow rate of substrate to the reactor as the principal input variable. Then, the ANN model was restructured and inversely trained by assuming the exit fructose concentration as the input variable and the feed flow rate as the output variable. Results indicate good performance by the application of the developed strategy to an extensive industrial data set. The results are expected to be useful in future, controlling the fructose concentration in the HFCS isomerization reactor.

Water Science and Technology, 2009

Water quality models have relatively large number of parameters, which need to be estimated again... more Water 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.

Computer Aided Chemical Engineering, 2009

ABSTRACT Six control strategies; PID control, Model Predictive Control (MPC) with linear model, M... more ABSTRACT Six control strategies; PID control, Model Predictive Control (MPC) with linear model, MPC with non-linear model, Nonlinear Autoregressive-Moving Average (NARMA-L2) control, Neural Network Model Predictive Control (NN-MPC) and optimal control with sequential quadratic programming (SQP) algorithm were evaluated via simulation of activated sludge wastewater treatment process. Controller performance assessment was based on rise time, overshoot, Integral Absolute Error (IAE) and Integral Square Error (ISE) performance criteria. As dissolved oxygen level in the aeration tank plays an important role in obtaining the effluent water quality, and in operating cost, it was chosen as the controlled variable. It was concluded consequently that NARMA-L2 controller and optimal control with SQP would outperform the others in achieving the specified objective.

An interpenetrated polymer network (IPN) poly(NIPAAm-co-AAc) hydrogel was synthesized by two poly... more An interpenetrated polymer network (IPN) poly(NIPAAm-co-AAc) hydrogel was synthesized by two polymeriza-tion method: emulsion and solution polymerization. The pH-and temperature-sensitive hydrogel was loaded by swelling with riboflavin drug, a B2 vitamin. The release of riboflavin as a function of time has been achieved under different pH and temperature environments. The determination of experimental conditions and the analysis of drug delivery results were achieved using response surface methodology (RSM). In this work, artificial neural networks (ANNs) in MATLAB were also used to model the release data. The predictions from the ANN model, which associated input variables, produced results showing good agreement with experimental data compared to the RSM results.

Chemical and Process Engineering - Inzynieria Chemiczna i Procesowa, 2013

Saccharamyces cerevisia known as baker's yeast is a product used in various food industries. Worl... more Saccharamyces cerevisia known as baker's yeast is a product used in various food industries. Worldwide economic competition makes it a necessity that industrial processes be operated in optimum conditions, thus maximisation of biomass in production of saccharamyces cerevisia in fedbatch reactors has gained importance. The facts that the dynamic fermentation model must be considered as a constraint in the optimisation problem, and dynamics involved are complicated, make optimisation of fed-batch processes more difficult.

Particulate Science and Technology, 2013

The present study aims to response surface methodology (RSM) for predicting magnetizing propertie... more The present study aims to response surface methodology (RSM) for predicting magnetizing properties of the matrix's elements of the magnetic filter that are constructed from the bi-mixture of the magnetic balls of various sizes, employed in the cleaning of the disperse mixture of water and corrosion particles (rust) of low concentrations. Based on a three-level central composite design (CCRD) involving

Water Resources Management, 2013

ABSTRACT Prediction of longitudinal dispersion coefficient (LDC) is still a novel topic for both ... more ABSTRACT Prediction of longitudinal dispersion coefficient (LDC) is still a novel topic for both environmental and water sciences due to its practical importance. In this study, the appraisal of LDC is considered as a spatial modelling problem and the analyses are carried out by regression kriging. Since LDC prediction includes some geometrical (spatial) parameters, the analyses have been performed such that it takes spatial variability of data into account. The modelling procedure consists of two stages. In the first stage, spatial variables are analyzed via multi-linear regression technique and deterministic relationships are identified. In the second stage, based on the spatial auto-correlations of the residuals, the regression-based kriging procedure is applied. The capacity and accuracy level of the method has been compared with former models. As a consequence, the applications revealed that analyzing hydraulic and geometrical parameters with spatially correlated errors is a convenient approach for evaluating LDC in a hydrological system.

Applied Soft Computing Journal, 2012

In the areas where broiler industry is located, poultry manure from chicken farms could be a majo... more In 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.

Chemical Engineering Research and Design, 2012

ABSTRACT To obtain the most suitable control algorithm for a wearable artificial pancreas, differ... more ABSTRACT To obtain the most suitable control algorithm for a wearable artificial pancreas, different control algorithms were compared and tested using a Hovorka model. Model predictive control (MPC), linear and nonlinear model forms, proportional integral derivative control (PID), neural-network-based model predictive control (NN-MPC), nonlinear autoregressive moving average (NARMA-L2) and sequential quadratic programming (SQP) were evaluated using the Hovorka model. Due to the fact that modeling of biomedical processes are very complex, to present the most effective control algorithm, various control strategies were needed to application. In the control algorithms, set point tracking and disturbance rejection were performed. With respect to the rise times of the control algorithms, SQP with optimal control had the shortest time, and NARMA-L2 had the longest time. Because the control algorithm connects the glucose meter and the insulin pump in an artificial pancreas, the rise time is the most important parameter. We propose that optimal control with SQP is the most suitable control algorithm to connect the glucose meter and the insulin pump.

Optimal Control Applications and Methods, 2009

Determination of the optimal aeration profile for an activated sludge system in which nitrificati... more Determination of the optimal aeration profile for an activated sludge system in which nitrification and denitrification take place sequentially in a single reactor (alternating aerobic-anoxic) is an attractive optimization problem because of complexities involved in, and high computational times required for solution. The rigorous dynamic modeling and start-up simulation of such a system, together with aeration profile optimization by an evolutionary algorithm (EA), were tackled in a previous study. In this paper an easy-to-implement dynamic optimization technique based on sequential quadratic programming method and control vector parameterization approach is provided. In comparison with EA, the proposed algorithm gives better results in shorter computation times. main operational cost. Determining the optimum durations of consecutive aeration and non-aeration periods in order to minimize the energy consumption is a nontrivial dynamic optimization problem. The dynamical character comes from the complicated dynamic model Figure 1. Schematic diagram of an activated sludge system.

Chemical Engineering and Technology, 2009

This study involves real-time monitoring and fault diagnosis in batch baker's yeast fermentation.... more This study involves real-time monitoring and fault diagnosis in batch baker's yeast fermentation. A specific Real Time Statistical Process Analysis and Control (RT-SPAC) program was developed to monitor instantaneous reaction conditions. The air flow rate fed to the reactor, temperature, pH, and dissolved oxygen concentration in a laboratory-size fermenter were monitored and recorded by means of on-line sensors. Under control of the RT-SPAC program, 22 batch baker's yeast fermentation operations were carried out. In the first 20 operations, an ordinary process was followed under previously defined nominal operating conditions. Historical data collected from these batches were then used for online Dynamic Principal Component Analysis (DPCA) in the course of the following two batches. The last two batches were implemented such that some deliberate faults (in temperature and pH) were introduced during the operation. The results indicated that the software was capable of capturing the process faults, and furthermore the possible causes of these faults were identified by contribution plots.

Mathematical and Computer Modelling, 2007

This work considers optimal scheduling of a set of orders in a multi-product batch plant with non... more This work considers optimal scheduling of a set of orders in a multi-product batch plant with non-identical parallel processing units where the process is single stage. The allocation of orders to the production units was formulated as an MILP problem in continuous time. Starting from the basic model proposed earlier, and adding a new constraint that was missing in previous literature, the new formulation solves the problem with a different objective function which considers the total production time or total production cost of the set of orders, without resorting to the application of any heuristic rules. A special MATLAB program has been developed for automatic creation of the optimization model, which otherwise may be a very time consuming task prone to errors. The formulation has been tested with extensive numerical, as well as one industrial, problems. The results indicate importance of the proposed modifications and effectiveness of the automated generation of the model, and present better solutions for the industrial example considered.

Chemical Engineering and Technology, 2007

Acrylic fiber is commercially produced by free radical polymerization, initiated by a redox syste... more Acrylic fiber is commercially produced by free radical polymerization, initiated by a redox system. Industrial production of polyacrylonitrile is a variant of aqueous dispersion polymerization, which takes place in a homogenous phase under isothermal conditions with perfect mixing. The fact that the kinetics are a lot more complicated than those of ordinary polymerization systems makes it difficult to control the molecular weight. On the other hand, abundant data is being gathered in industrial polymerization systems, and this information makes the neural network based controllers a good candidate for managing such a difficult control problem. Multilayer neural networks have been applied successfully in the identification and control of dynamic systems. In this work, the neural network based control of continuous acrylonitrile (ACN) polymerization is studied, based on a previously developed new rigorous dynamic model for the polymerization of acrylonitrile. Two typical neural network controllers are investigated, i.e., model predictive control and NARMA-L2 (Nonlinear Auto Regressive Moving Average) control. These controllers are representative of the variety of common ways in which multilayer networks are used in control systems. The results present a comparison of the two common neural network controllers, and indicate that the model predictive controller requires a larger computational time.

Mathematical and Computer Modelling, 2007

Predictions and quality management issues for environmental protection in river basins rely on wa... more Predictions and quality management issues for environmental protection in river basins rely on water-quality models. These models can be used to simulate conditions in or near the range of the calibrated or verified conditions. In this respect, estimation of parameters, which is still practiced by heuristic approaches (i.e. manually), seems to be the point where the attention needs to be focused. The authors' research group has developed a systematic approach for dynamic simulation and parameter estimation in river water quality models, which has eliminated the cumbersome trial-end-error method. This study reports a user-interactive software named as RSDS (River Stream Dynamics and Simulation) for the implementation of the suggested technique, and provides a comparative investigation of the suggested modelling approach against a well established and worldwide known water quality software, QUAL2E. Experimental data collected in field observations along the Yesilirmak river basin in Turkey were checked against the predictions from both software programs. The results indicated that much better agreement with the experimental data could be obtained from RSDS compared with QUAL2E. Thus, the systematic procedure suggested in the present work provides an effective means for reliable estimation of the model parameters and dynamic simulation for river basins, and therefore, contributes to the efforts toward predicting the extent of the effect of possible pollutant discharges in river basins.

Computer Aided Chemical Engineering, 2006

Acrylic fiber is commercially produced by free radical polymerization, initiated by a redox syste... more Acrylic fiber is commercially produced by free radical polymerization, initiated by a redox system. The fact that the kinetics is a great deal more complicated than that of ordinary polymerization systems makes the problem of controlling molecular weight a difficult one. In this study, dynamics and control of continuous acrylonitrile polymerization are studied based on a previously described kinetics by Peebles (Applied Polymer Science, 1973, 17, 113–128). As the conventional feedback controller was found to be unsuccessful, a model state feedback (MSFB) control strategy was implemented. The performances of linear and nonlinear controllers have been compared via simulation, and it was concluded that the nonlinear form would be effectively employed for set point tracking as well as disturbance rejection.

Chemical Engineering and Processing: Process Intensification, 2005

Chemical engineering problems formulated as mixed integer nonlinear programming (MINLP) model are... more Chemical engineering problems formulated as mixed integer nonlinear programming (MINLP) model are difficult to solve when the model is non-convex. In order to overcome this difficulty, a semi-heuristic algorithm for production scheduling was developed in this work. Using this approach, the non-convex MINLP problem is first considered as an MILP problem without dividing the orders into units. The order causing prolonged delivery time is thus identified, constraints for this order are then relaxed and MILP problem is re-solved using the new constraints. Having reached the new schedule, the quantitative distribution of the specific order to different units is determined by solving the LP problem that does not contain integer variables since allocation of orders to the units, and processing order are known. The results obtained with three example problems indicate improvements over previously reported schedules and therefore, give promise that the suggested strategy may be used in moderately sized industrial applications.

Computer Aided Chemical Engineering, 2005

A common problem in model verification is to determine the values of model parameters that provid... more A common problem in model verification is to determine the values of model parameters that provide the best fit to measured data, based on some type of least squares or maximum likelihood criterion. In the most general case, this requires the solution of a nonlinear and frequently nonconvex optimization problem. Some of the available software lack in generality, while others do not provide ease of use. As the need for a user-interactive parameter estimation software, especially for identifying kinetic parameters, was needed; in this work we developed an integration based optimization approach to provide a solution to such problems. For easy implementation of the technique, a parameter estimation software (PARES) has been developed in MATLAB environment. When tested with extensive example problems from literature, the suggested approach is proven to provide good agreement between predicted and observed data within relatively less computing time and iterations.

Computer Aided Chemical Engineering, 2003

... A Semi Heuristic MINLP Algorithm for Production Scheduling Mehmet Yuceer, Ilknur Atasoy andRi... more ... A Semi Heuristic MINLP Algorithm for Production Scheduling Mehmet Yuceer, Ilknur Atasoy andRidvan Berber Department of Chemical Engineering ... In a most recent work, Berber and Ozdemir (2003) identified one deficiency and two misconception about the formulation of ...

Journal of Food Processing and Preservation, 2012

ABSTRACT Effects of microwave power output and sample mass on drying behavior, color parameters, ... more ABSTRACT Effects of microwave power output and sample mass on drying behavior, color parameters, rehydration characteristics and some sensory scores of thyme leaves were investigated. Within the range of the microwave power outputs, 180-900W, and sample amounts, 25-100g, moisture content of the leaves were reduced to 0.1±(0.01) from 4.05kg water/kg dry base value. Drying times of the leaves were found to be varying between 3.5 and 15.5min for constant sample amount, and 6.5 and 20.5min for constant power output. Experimental drying data obtained were successfully modeled using artificial neural networks methodology. Statistical values of the test data were found to be 0.9999, 4.0937 and 0.025 for R-square, MAPE (%) and RMSE, respectively. Some changes were recorded in the quality parameters, and acceptable sensory scores for the dried leaves were observed in all of the experimental conditions (P<0.05). © 2012 Wiley Periodicals, Inc.

Journal of Dispersion Science and Technology, 2011

ABSTRACT In this study, we aimed at optimizing the parameters that govern the separation efficien... more ABSTRACT In this study, we aimed at optimizing the parameters that govern the separation efficiency in the electromagnetic filtration (EMF) of magnetizable dispersed particles from a water medium. Thus, we employed a Nelder-Mead modified simplex algorithm to maximize EMF efficiency choosing the external magnetic field strength, size of the filter matrix elements, filter length, and filtration velocity as variables to be optimized. It has been found that EMF efficiency decreased with increasing the filtration velocity and the size of the filter matrix elements. On the other hand, EMF efficiency increased when the filter length and the external magnetic strength was increased. Four variables were successfully optimized and a maximum level of EMF efficiency percentage of 77.05 was achieved by performing only 26 experiments. The results are expected to be useful in the future to predict the operating conditions of similar EMF systems.

Neural Computing and Applications, 2010

ABSTRACT This work presents an approach to the modeling of a real industrial isomerization reacto... more ABSTRACT This work presents an approach to the modeling of a real industrial isomerization reactor by using artificial neural networks (ANN) pre-processed with principal component analysis (PCA). The initial model considered the output fructose concentration as the output variable, while the flow rate of substrate to the reactor as the principal input variable. Then, the ANN model was restructured and inversely trained by assuming the exit fructose concentration as the input variable and the feed flow rate as the output variable. Results indicate good performance by the application of the developed strategy to an extensive industrial data set. The results are expected to be useful in future, controlling the fructose concentration in the HFCS isomerization reactor.

Water Science and Technology, 2009

Water quality models have relatively large number of parameters, which need to be estimated again... more Water 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.

Computer Aided Chemical Engineering, 2009

ABSTRACT Six control strategies; PID control, Model Predictive Control (MPC) with linear model, M... more ABSTRACT Six control strategies; PID control, Model Predictive Control (MPC) with linear model, MPC with non-linear model, Nonlinear Autoregressive-Moving Average (NARMA-L2) control, Neural Network Model Predictive Control (NN-MPC) and optimal control with sequential quadratic programming (SQP) algorithm were evaluated via simulation of activated sludge wastewater treatment process. Controller performance assessment was based on rise time, overshoot, Integral Absolute Error (IAE) and Integral Square Error (ISE) performance criteria. As dissolved oxygen level in the aeration tank plays an important role in obtaining the effluent water quality, and in operating cost, it was chosen as the controlled variable. It was concluded consequently that NARMA-L2 controller and optimal control with SQP would outperform the others in achieving the specified objective.