The paper proposes a novel process integration for biodiesel blend in the Membrane assisted React... more The paper proposes a novel process integration for biodiesel blend in the Membrane assisted Reactive Divided Wall Distillation (MRDW) column. Biodiesel is a green fuel and grade of biodiesel blend is B20 (%) which consist of 20% biodiesel and rest 80% commercial diesel. Instead of commercial diesel, Tertiary Amyl Ethyl Ether (TAEE) was used as an environment friendly fuel for blending biodiesel. Biodiesel and TAEE were synthesized in a pilot scale reactive distillation column. Dual reactive distillation and MRDW were simulated using aspen plus. B20 (%) limit calculation was performed using feed flow rates of both TAEE and biodiesel. MRDW was compared with dual reactive distillation column and it was observed that MRDW is comparatively cost effective and suitable in terms of improved heat integration and flow pattern.
In this research work, neural network based single loop and cascaded control strategies, based on... more In this research work, neural network based single loop and cascaded control strategies, based on Feed Forward Neural Network trained with Back Propagation (FBPNN) algorithm is carried out to control the product composition of reactive distillation. The FBPNN is modified using the steepest descent method. This modification is suggested for optimization of error function. The weights connecting the input and hidden layer, hidden and output layer is optimized using steepest descent method which causes minimization of mean square error and hence improves the response of the system. FBPNN, as the inferential soft sensor is used for composition estimation of reactive distillation using temperature as a secondary process variable. The optimized temperature profile of the reactive distillation is selected as input to the neural network. Reboiler heat duty is selected as a manipulating variable in case of single loop control strategy while the bottom stage temperature T9 is selected as a ma...
International Journal of Chemical Engineering and Applications, 2014
In this paper we have used the heuristic search algorithm for the process optimization of Reactiv... more In this paper we have used the heuristic search algorithm for the process optimization of Reactive Distillation column. Basically, Process optimization is the manipulation of process variables, so as to optimize some of the parameters without violating the constraints. Gravitational Search Algorithm (GSA) is a new heuristic optimization technique based on law of gravity and mass interactions. This technique is used for process optimization of Methyl-Tert-Butyl-Ether (MTBE) reactive distillation. This work highlights the potential of GSA for an optimization of MTBE reactive distillation that involves complex reaction system. The results obtained gives better performance of MTBE reactive distillation.
Fuzzy Counter Propagation Neural Network (FCPN) controller design is developed, for a class of no... more Fuzzy Counter Propagation Neural Network (FCPN) controller design is developed, for a class of nonlinear dynamical systems. In this process, the weight connecting between the instar and outstar, that is, input-hidden and hidden-output layer, respectively, is adjusted by using Fuzzy Competitive Learning (FCL). FCL paradigm adopts the principle of learning, which is used to calculate Best Matched Node (BMN) which is proposed. This strategy offers a robust control of nonlinear dynamical systems. FCPN is compared with the existing network like Dynamic Network (DN) and Back Propagation Network (BPN) on the basis of Mean Absolute Error (MAE), Mean Square Error (MSE), Best Fit Rate (BFR), and so forth. It envisages that the proposed FCPN gives better results than DN and BPN. The effectiveness of the proposed FCPN algorithms is demonstrated through simulations of four nonlinear dynamical systems and multiple input and single output (MISO) and a single input and single output (SISO) gas furn...
The paper proposes a novel process integration for biodiesel blend in the Membrane assisted React... more The paper proposes a novel process integration for biodiesel blend in the Membrane assisted Reactive Divided Wall Distillation (MRDW) column. Biodiesel is a green fuel and grade of biodiesel blend is B20 (%) which consist of 20% biodiesel and rest 80% commercial diesel. Instead of commercial diesel, Tertiary Amyl Ethyl Ether (TAEE) was used as an environment friendly fuel for blending biodiesel. Biodiesel and TAEE were synthesized in a pilot scale reactive distillation column. Dual reactive distillation and MRDW were simulated using aspen plus. B20 (%) limit calculation was performed using feed flow rates of both TAEE and biodiesel. MRDW was compared with dual reactive distillation column and it was observed that MRDW is comparatively cost effective and suitable in terms of improved heat integration and flow pattern.
In this research work, neural network based single loop and cascaded control strategies, based on... more In this research work, neural network based single loop and cascaded control strategies, based on Feed Forward Neural Network trained with Back Propagation (FBPNN) algorithm is carried out to control the product composition of reactive distillation. The FBPNN is modified using the steepest descent method. This modification is suggested for optimization of error function. The weights connecting the input and hidden layer, hidden and output layer is optimized using steepest descent method which causes minimization of mean square error and hence improves the response of the system. FBPNN, as the inferential soft sensor is used for composition estimation of reactive distillation using temperature as a secondary process variable. The optimized temperature profile of the reactive distillation is selected as input to the neural network. Reboiler heat duty is selected as a manipulating variable in case of single loop control strategy while the bottom stage temperature T9 is selected as a ma...
International Journal of Chemical Engineering and Applications, 2014
In this paper we have used the heuristic search algorithm for the process optimization of Reactiv... more In this paper we have used the heuristic search algorithm for the process optimization of Reactive Distillation column. Basically, Process optimization is the manipulation of process variables, so as to optimize some of the parameters without violating the constraints. Gravitational Search Algorithm (GSA) is a new heuristic optimization technique based on law of gravity and mass interactions. This technique is used for process optimization of Methyl-Tert-Butyl-Ether (MTBE) reactive distillation. This work highlights the potential of GSA for an optimization of MTBE reactive distillation that involves complex reaction system. The results obtained gives better performance of MTBE reactive distillation.
Fuzzy Counter Propagation Neural Network (FCPN) controller design is developed, for a class of no... more Fuzzy Counter Propagation Neural Network (FCPN) controller design is developed, for a class of nonlinear dynamical systems. In this process, the weight connecting between the instar and outstar, that is, input-hidden and hidden-output layer, respectively, is adjusted by using Fuzzy Competitive Learning (FCL). FCL paradigm adopts the principle of learning, which is used to calculate Best Matched Node (BMN) which is proposed. This strategy offers a robust control of nonlinear dynamical systems. FCPN is compared with the existing network like Dynamic Network (DN) and Back Propagation Network (BPN) on the basis of Mean Absolute Error (MAE), Mean Square Error (MSE), Best Fit Rate (BFR), and so forth. It envisages that the proposed FCPN gives better results than DN and BPN. The effectiveness of the proposed FCPN algorithms is demonstrated through simulations of four nonlinear dynamical systems and multiple input and single output (MISO) and a single input and single output (SISO) gas furn...
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Papers by Dev Agarwal