Nonlinear computation in DIVA — methods and applications

Mangold, Michael; Kienle, Achim; Gilles, Ernst Dieter; Mohl, K. D.

doi:10.1016/s0009-2509(99)00341-3

Cited by 102 publications

(53 citation statements)

References 39 publications

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“…The dynamic simulation of the SMB systems are performed using the simulation environment with DIVA [23,24]. For the periodic switching a Petri net routine is implemented.…”

Section: Mathematical Model and Optimizationmentioning

confidence: 99%

Integrated Simulated Moving Bed Processes for Production of Single Enantiomers

2011

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Based on the assumption of true moving bed processes it was demonstrated that integration of a racemization reaction into a continuous chromatographic process can improve the production of single enantiomers. In view of possible practical implementations, the analysis is extended to more realistic simulated moving bed (SMB) processes. Superstructures of SMB-based systems are defined that reflect the three general concepts of flow sheet, partial, and total process integration. Process candidates are generated by simultaneously optimizing process structure and operating conditions. Optimal process setups are determined under idealized conditions as a function of the purity requirement. The best performance is achieved by fully integrated processes. These are compared under more realistic conditions to units with side reactors. The results indicate that a simple fully integrated SMB system with three zones is a particularly promising new process option. The new concept is investigated in detail to identify relevant practical aspects.

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“…The dynamic simulation of the SMB systems are performed using the simulation environment with DIVA [23,24]. For the periodic switching a Petri net routine is implemented.…”

Section: Mathematical Model and Optimizationmentioning

confidence: 99%

Integrated Simulated Moving Bed Processes for Production of Single Enantiomers

2011

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“…1. Numerical investigation of the open loop and closed loop dynamics was performed using the simulation environment DIVA [28].…”

Section: Modeling Approachmentioning

confidence: 99%

Dynamics and Control of Coupled Continuous Chromatography and Crystallization Processes for the Production of Pure Enantiomers

Swernath¹,

Kaspereit²,

Kienle³

2013

Chem Eng & Technol

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The combination of continuous chromatographic processes and subsequent crystallization with a recycle of the mother liquor can improve significantly the efficiency of separation processes for the production of enantiomers if compared to the stand-alone chromatographic process. For the first time, dynamic operability and plantwide control of such a process combination is investigated. In the first step, the effect of disturbances on the open loop dynamics is evaluated. In a second step, a simple plantwide control strategy is proposed in order to ensure a robust process operation. It is demonstrated that the direct control of the simulated moving bed (SMB) unit is not required to stabilize the process combination while maintaining the desired product specifications. Instead, this can be achieved easily by controlling the amount of solvent removed or added to the system.

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“…For the solution of such a MIDO problem, we consider the sequential approach in which the MIDO problem is decomposed into a series of dynamic NLP subproblems where binary variables are fixed and MILP master problems which determine a new binary configuration for the next NLP subproblem. The dynamic NLP problem is solved with the dynamic flow sheet simulator DIVA [16] using the DAE integrator DDASAC [17] and the SQP algorithm E04UCF from the NAG library [18]. The NLP subproblem gives an upper bound (UBD) on the final solution.…”

Section: Solution Approach For the Mido Problemmentioning

confidence: 99%

Inferential Control of Reactive Destillation Columns – An Algorithmic Approach

Paramasivan

Kienle

2011

Chem Eng & Technol

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Decentralized control system design comprises the selection of a suitable control structure and controller parameters. Here, mixed integer optimization is used to determine the optimal control structure and the optimal controller parameters simultaneously. The process dynamics is included explicitly into the constraints using a rigorous nonlinear dynamic process model. Depending on the objective function, which is used for the evaluation of competing control systems, two different formulations are proposed which lead to mixed-integer dynamic optimization (MIDO) problems. A MIDO solution strategy based on the sequential approach is adopted in the present paper. Here, the MIDO problem is decomposed into a series of nonlinear programming (NLP) subproblems (dynamic optimization) where the binary variables are fixed, and mixed-integer linear programming (MILP) master problems which determine a new binary configuration for the next NLP subproblem. The proposed methodology is applied to inferential control of reactive distillation columns as a challenging benchmark problem for chemical process control.

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Nonlinear computation in DIVA — methods and applications

Cited by 102 publications

References 39 publications

Integrated Simulated Moving Bed Processes for Production of Single Enantiomers

Integrated Simulated Moving Bed Processes for Production of Single Enantiomers

Dynamics and Control of Coupled Continuous Chromatography and Crystallization Processes for the Production of Pure Enantiomers

Inferential Control of Reactive Destillation Columns – An Algorithmic Approach

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