Riju De - Academia.edu (original) (raw)
Papers by Riju De
Biodiesel, a mixture of fatty acid methyl esters (FAME), can be produced through transesterificat... more Biodiesel, a mixture of fatty acid methyl esters (FAME), can be produced through transesterification of refined vegetable oils and is a potential alternate energy source. A higher concentration of FAME from a batch transesterification reactor can be obtained by maintaining a higher reactor temperature. This, however, increases the energy costs. Also, incomplete reactions influence the FAME separation during the downstream operations. Therefore, from an economical perspective, it is desirable to balance FAME yield, energy costs, and the cost of FAME separation. This study formulates and solves an energy cost minimization problem first, followed by a multi-objective optimization problem (MOOP) with objectives of- maximization of FAME concentration, minimization of reactor energy cost, and minimization of cost of methanol separation. The dynamic optimization problem is solved by utilizing orthogonal collocation on finite elements (OCFE) approach using the fmincon solver in MATLAB®. Opt...
Control Engineering Practice, 2020
Biodiesel are fatty acid methyl esters (FAME), which can be produced by the transesterification r... more Biodiesel are fatty acid methyl esters (FAME), which can be produced by the transesterification reaction of vegetable oils with methanol. A batch transesterification process is often associated with model uncertainties and unmeasured disturbances, which may create a detrimental effect on the batch end FAME yield due to plant-model mismatch. Therefore, batch-to-batch iterative learning control (ILC) is necessary to track the desired reference FAME profile under such process variations. This work demonstrates a constrained quadratic programming problem (QPP) based batch-to-batch ILC framework for optimizing the endpoint FAME concentration by controlling the hot water flow profile passing through the reactor jacket under uncertainty. Parametric uncertainties are modeled separately in two case studies, which involve different batch transesterification models differing in the state variables. Case study 1 considers uncertainty in the apparent activation energy and brings out a comparative study between a QPP based ILC and a heuristics based approach. The comparison is shown based on the tracking performance of the ILC in terms of reduction in the batch end tracking error and total root mean square error of the same. Batch-to-batch ILC is superior as it produces faster convergence of the tracking error by saving 6 batches as compared to the heuristics approach. Case study 2 involves the implementation of constrained QPP based ILC algorithm on a proposed 54-state detailed batch transesterification model of canola oil, where uncertainty is modeled as the change in the input triglyceride composition from the base case. The desired reference FAME concentration profile is tracked in 9 batches for fixed uncertainty whereas it takes 15 batches to achieve the stochastic convergence under stochastic disturbance.
Chemical Engineering Research and Design, 2020
This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Fuel, 2019
Biodiesel is a mixture of fatty acid methyl esters (FAME), which can be produced by the transeste... more Biodiesel is a mixture of fatty acid methyl esters (FAME), which can be produced by the transesterification reaction of vegetable oils with methanol. The production of biodiesel is comprised of a series of stages such as reaction, methanol separation, water washing, decantation, and unreacted oil separation followed by the biodiesel purification. Each of these stages involves certain performance measures which need to be optimized for making the overall process cost-effective and productive. Therefore, a commercial base catalyzed batch transesterification process is optimized first with an objective: maximization of the fatty acid methyl esters concentration in final batch time. Dynamic optimization is used with the hot water flow rate passing through the reactor jacket as the decision variable. Orthogonal collocation on finite elements (OCFE) method is employed to convert the dynamic optimization problem into a non-linear programming (NLP) problem. The integrated reaction-separation steps of the biodiesel production process is modeled and simulated in Aspen Plus. Total two multi-objective optimization (MOOP) problems are formulated and solved to capture the trade-offs among the performance indices of the reactor and separation units collectively. Compared to the dynamic optimization problem result, MOOP-1 produced an optimal biodiesel concentration of 0.97 kmol/m 3 at an optimal reactor energy cost of 0.12 $/l FAME produced. MOOP-2 determined that the energy expenditure in the reactor jacket is 1.064 times the total energy usage of all the reboilers of the distillation columns. In comparison to MOOP-1, the Pareto-fronts of MOOP-2 produced more cost-effective results in terms of comprehensive trade-offs among the objective functions used.
2016 Indian Control Conference (ICC), 2016
With the advancement of studies in the field of renewable fuels, biodiesel production has receive... more With the advancement of studies in the field of renewable fuels, biodiesel production has received a lot of attention over the years. Biodiesel production is based on transesterification reaction between a vegetable oil containing triglycerides and a shorter chain alcohol e.g. methanol. A batch transesterification process needs tighter control on reaction temperature for achieving higher triglyceride conversion. Here, open loop control called optimal control has been employed on the transesterification kinetic model of a batch process. A multi-objective optimization problem is formulated with two objectives namely, maximization of methyl ester concentration at batch end time and minimization of final batch time. An e-constraint approach is adopted for solving the multi-objective optimization problem. Orthogonal collocation on finite elements scheme is employed to generate the optimal temperature trajectory. Under the framework of collocation method, state and control profiles have been discretized using piecewise linear Lagrange's polynomials and the control problem has got transformed into an NLP problem. fmincon solver is utilized in solving the NLP in MATLAB®. Maximum methyl ester concentration at final batch time and the minimum batch end time have been determined to be 0.8315 mol/l and 67.4 min, respectively. Optimal results have been found with two finite elements and five interior collocation points.
Journal of Chemical Technology & Biotechnology, 2013
BACKGROUND: Packed bed biofilm reactors (PBBR) are gaining interest for the bioremediation of was... more BACKGROUND: Packed bed biofilm reactors (PBBR) are gaining interest for the bioremediation of wastewater contaminated with heavy metals. The study of both hydrodynamics and microbial growth kinetics are equally important for assessment of the overall bioremediation efficiency of a PBBR. RESULTS: Hydrodynamics of a Bacillus cereus (JUBT1) based biofilm reactor of diameter 45 mm and length 460 mm undergoing removal of Hg 2+ ions up to a conversion efficiency of 90% have been determined using both actual and Ca-alginate based artificial biofilms. The Peclet numbers obtained using biotic and abiotic biofilms have been determined to be 9.74 and 8.8, respectively. The micrographs of the biofilm with the variation of aging period suggest its stability up to 150 days of operation. A mathematical model has been developed and validated incorporating both the dispersion parameter and microbial growth kinetics. CONCLUSION: This work demonstrates that in order to carry out hydrodynamic studies of a PBBR, the use of abiotic films rather than biotic films is much more beneficial and time efficient as it does not require strict biochemical precautions. Moreover, using lower inlet concentrations of Hg 2+ ions, the exit conversion of the PBBR is found to be maximum.
Computer Aided Chemical Engineering
Biodiesel, a mixture of fatty acid methyl esters (FAME), can be produced through transesterificat... more Biodiesel, a mixture of fatty acid methyl esters (FAME), can be produced through transesterification of refined vegetable oils and is a potential alternate energy source. A higher concentration of FAME from a batch transesterification reactor can be obtained by maintaining a higher reactor temperature. This, however, increases the energy costs. Also, incomplete reactions influence the FAME separation during the downstream operations. Therefore, from an economical perspective, it is desirable to balance FAME yield, energy costs, and the cost of FAME separation. This study formulates and solves an energy cost minimization problem first, followed by a multi-objective optimization problem (MOOP) with objectives of- maximization of FAME concentration, minimization of reactor energy cost, and minimization of cost of methanol separation. The dynamic optimization problem is solved by utilizing orthogonal collocation on finite elements (OCFE) approach using the fmincon solver in MATLAB®. Opt...
Control Engineering Practice, 2020
Biodiesel are fatty acid methyl esters (FAME), which can be produced by the transesterification r... more Biodiesel are fatty acid methyl esters (FAME), which can be produced by the transesterification reaction of vegetable oils with methanol. A batch transesterification process is often associated with model uncertainties and unmeasured disturbances, which may create a detrimental effect on the batch end FAME yield due to plant-model mismatch. Therefore, batch-to-batch iterative learning control (ILC) is necessary to track the desired reference FAME profile under such process variations. This work demonstrates a constrained quadratic programming problem (QPP) based batch-to-batch ILC framework for optimizing the endpoint FAME concentration by controlling the hot water flow profile passing through the reactor jacket under uncertainty. Parametric uncertainties are modeled separately in two case studies, which involve different batch transesterification models differing in the state variables. Case study 1 considers uncertainty in the apparent activation energy and brings out a comparative study between a QPP based ILC and a heuristics based approach. The comparison is shown based on the tracking performance of the ILC in terms of reduction in the batch end tracking error and total root mean square error of the same. Batch-to-batch ILC is superior as it produces faster convergence of the tracking error by saving 6 batches as compared to the heuristics approach. Case study 2 involves the implementation of constrained QPP based ILC algorithm on a proposed 54-state detailed batch transesterification model of canola oil, where uncertainty is modeled as the change in the input triglyceride composition from the base case. The desired reference FAME concentration profile is tracked in 9 batches for fixed uncertainty whereas it takes 15 batches to achieve the stochastic convergence under stochastic disturbance.
Chemical Engineering Research and Design, 2020
This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Fuel, 2019
Biodiesel is a mixture of fatty acid methyl esters (FAME), which can be produced by the transeste... more Biodiesel is a mixture of fatty acid methyl esters (FAME), which can be produced by the transesterification reaction of vegetable oils with methanol. The production of biodiesel is comprised of a series of stages such as reaction, methanol separation, water washing, decantation, and unreacted oil separation followed by the biodiesel purification. Each of these stages involves certain performance measures which need to be optimized for making the overall process cost-effective and productive. Therefore, a commercial base catalyzed batch transesterification process is optimized first with an objective: maximization of the fatty acid methyl esters concentration in final batch time. Dynamic optimization is used with the hot water flow rate passing through the reactor jacket as the decision variable. Orthogonal collocation on finite elements (OCFE) method is employed to convert the dynamic optimization problem into a non-linear programming (NLP) problem. The integrated reaction-separation steps of the biodiesel production process is modeled and simulated in Aspen Plus. Total two multi-objective optimization (MOOP) problems are formulated and solved to capture the trade-offs among the performance indices of the reactor and separation units collectively. Compared to the dynamic optimization problem result, MOOP-1 produced an optimal biodiesel concentration of 0.97 kmol/m 3 at an optimal reactor energy cost of 0.12 $/l FAME produced. MOOP-2 determined that the energy expenditure in the reactor jacket is 1.064 times the total energy usage of all the reboilers of the distillation columns. In comparison to MOOP-1, the Pareto-fronts of MOOP-2 produced more cost-effective results in terms of comprehensive trade-offs among the objective functions used.
2016 Indian Control Conference (ICC), 2016
With the advancement of studies in the field of renewable fuels, biodiesel production has receive... more With the advancement of studies in the field of renewable fuels, biodiesel production has received a lot of attention over the years. Biodiesel production is based on transesterification reaction between a vegetable oil containing triglycerides and a shorter chain alcohol e.g. methanol. A batch transesterification process needs tighter control on reaction temperature for achieving higher triglyceride conversion. Here, open loop control called optimal control has been employed on the transesterification kinetic model of a batch process. A multi-objective optimization problem is formulated with two objectives namely, maximization of methyl ester concentration at batch end time and minimization of final batch time. An e-constraint approach is adopted for solving the multi-objective optimization problem. Orthogonal collocation on finite elements scheme is employed to generate the optimal temperature trajectory. Under the framework of collocation method, state and control profiles have been discretized using piecewise linear Lagrange's polynomials and the control problem has got transformed into an NLP problem. fmincon solver is utilized in solving the NLP in MATLAB®. Maximum methyl ester concentration at final batch time and the minimum batch end time have been determined to be 0.8315 mol/l and 67.4 min, respectively. Optimal results have been found with two finite elements and five interior collocation points.
Journal of Chemical Technology & Biotechnology, 2013
BACKGROUND: Packed bed biofilm reactors (PBBR) are gaining interest for the bioremediation of was... more BACKGROUND: Packed bed biofilm reactors (PBBR) are gaining interest for the bioremediation of wastewater contaminated with heavy metals. The study of both hydrodynamics and microbial growth kinetics are equally important for assessment of the overall bioremediation efficiency of a PBBR. RESULTS: Hydrodynamics of a Bacillus cereus (JUBT1) based biofilm reactor of diameter 45 mm and length 460 mm undergoing removal of Hg 2+ ions up to a conversion efficiency of 90% have been determined using both actual and Ca-alginate based artificial biofilms. The Peclet numbers obtained using biotic and abiotic biofilms have been determined to be 9.74 and 8.8, respectively. The micrographs of the biofilm with the variation of aging period suggest its stability up to 150 days of operation. A mathematical model has been developed and validated incorporating both the dispersion parameter and microbial growth kinetics. CONCLUSION: This work demonstrates that in order to carry out hydrodynamic studies of a PBBR, the use of abiotic films rather than biotic films is much more beneficial and time efficient as it does not require strict biochemical precautions. Moreover, using lower inlet concentrations of Hg 2+ ions, the exit conversion of the PBBR is found to be maximum.
Computer Aided Chemical Engineering