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  • 1
    Electronic Resource
    Electronic Resource
    s.l. : American Chemical Society
    Industrial & engineering chemistry research 31 (1992), S. 2805-2805 
    ISSN: 1520-5045
    Source: ACS Legacy Archives
    Topics: Chemistry and Pharmacology , Process Engineering, Biotechnology, Nutrition Technology
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    s.l. : American Chemical Society
    Industrial & engineering chemistry research 31 (1992), S. 1927-1936 
    ISSN: 1520-5045
    Source: ACS Legacy Archives
    Topics: Chemistry and Pharmacology , Process Engineering, Biotechnology, Nutrition Technology
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    s.l. : American Chemical Society
    Industrial & engineering chemistry research 33 (1994), S. 292-298 
    ISSN: 1520-5045
    Source: ACS Legacy Archives
    Topics: Chemistry and Pharmacology , Process Engineering, Biotechnology, Nutrition Technology
    Type of Medium: Electronic Resource
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  • 4
    Electronic Resource
    Electronic Resource
    s.l. : American Chemical Society
    Industrial & engineering chemistry research 30 (1991), S. 713-721 
    ISSN: 1520-5045
    Source: ACS Legacy Archives
    Topics: Chemistry and Pharmacology , Process Engineering, Biotechnology, Nutrition Technology
    Type of Medium: Electronic Resource
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  • 5
    Electronic Resource
    Electronic Resource
    s.l. : American Chemical Society
    Industrial & engineering chemistry research 33 (1994), S. 1878-1878 
    ISSN: 1520-5045
    Source: ACS Legacy Archives
    Topics: Chemistry and Pharmacology , Process Engineering, Biotechnology, Nutrition Technology
    Type of Medium: Electronic Resource
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  • 6
    Electronic Resource
    Electronic Resource
    Hoboken, NJ : Wiley-Blackwell
    AIChE Journal 42 (1996), S. 742-752 
    ISSN: 0001-1541
    Keywords: Chemistry ; Chemical Engineering
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology , Process Engineering, Biotechnology, Nutrition Technology
    Notes: With the growing environmental concern, it is necessary to improve process simulation and develop design tools to account for environmental factors in the synthesis of large-scale chemical processes. A major obstacle in tackling this problem is uncertainties in some of the technical and economic parameters, which lead to uncertainties in design, plant performance, and cost estimates. Further, a conceptual process design involves the identification of an optimal flowsheet structure from many alternatives stituting the “superstructure.” Synthesis and optimization of large-scale processes involving uncertainties often require considerable computational effort. A novel algorithm presented here is based on simulated annealing for the process synthesis of large-scale flowsheets having several configurations and considers uncertainties in the process design systematically. This new “stochastic annealing algorithm,” provides an efficient approach to stochastic synthesis problems by incorporating a penalty term in the objective function and balances the trade-off between accuracy and efficiency based on the annealing temperature. It has been used to study a benchmark synthesis problem in the HDA process. Savings of up to 80% in CPU time has been achieved without significant loss of solution precision with stochastic annealing, compared to simulated annealing with a fixed sample size. It can be applied to analyze efficiently any complex process flowsheet and provide valuable insights into process feasibility based on optimal design, plant performance, and uncertainty issues.
    Additional Material: 12 Ill.
    Type of Medium: Electronic Resource
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  • 7
    Electronic Resource
    Electronic Resource
    Hoboken, NJ : Wiley-Blackwell
    AIChE Journal 38 (1992), S. 1551-1563 
    ISSN: 0001-1541
    Keywords: Chemistry ; Chemical Engineering
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology , Process Engineering, Biotechnology, Nutrition Technology
    Notes: This article presents a unified approach to simultaneous solution of optimization and optimal control problems in batch distillation, operating under different modes of operation: variable, constant, or optimal reflux. The simplified, computationally efficient short-cut method and a novel algorithm to solve the optimal control problems in batch distillation is the basis of this unified approach. The short-cut method identifies the feasible region of operation essential for optimization and optimal control problems, and provides analytical partial derivatives of the model parameters crucial to the solution.The new algorithm for the solution of optimal combination of the maximum principle and NLP optimization techniques. It circumvents the problems associated with the maximum principle approach (iterative solution of a two-point boundary value problem, undounded control variables, and inability to handle the simultaneous optimization and optimal control problem), and the coupled ODE discretization-NLP optimization scheme for nonlinear models (higher system nonlinearities, multiplicity of solutions, sensitivity of convergence to initial guesses). This algorithm reduces the dimensionality of the problem, and the nature of the algorithm allows a common platform to optimal solutions of different operating conditions. This article also shows that different categories of the optimal control problems in batch distillation essentially involve the solution of the maximum distillate problem.
    Additional Material: 6 Ill.
    Type of Medium: Electronic Resource
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  • 8
    Electronic Resource
    Electronic Resource
    Hoboken, NJ : Wiley-Blackwell
    AIChE Journal 37 (1991), S. 1571-1578 
    ISSN: 0001-1541
    Keywords: Chemistry ; Chemical Engineering
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology , Process Engineering, Biotechnology, Nutrition Technology
    Notes: Using rigorous models to simulate batch distillation involves the solution of many stiff differential equations. The dimensionality of the problem also increases with an increase in the number of plates and components, which imposes limitations on the use of rigorous models. Furthermore, problems in design, optimization, synthesis, and control involve iterative procedures, and considerable computational efforts would be required to solve them rigorously. As an alternative, the short-cut method (Diwekar and Madhavan, 1991a) provided reasonably accurate solutions without much computational effort. This method in the present form, however, cannot be applied to azeotropic systems because of the impassable barrier of the azeotropic point and needs to be modified. The azeotropic approximation proposed by Anderson and Doherty (1984) was used to modify the short-cut method for binary azeotropic systems. The modified algorithm presented here was tested extensively with a number of binary azeotropic systems for both constant reflux and variable reflux modes of operation, and the results were shown to compare well with the rigorous models. The method requires significantly less computational efforts and is very useful in analyzing feasible region of operation.
    Additional Material: 6 Ill.
    Type of Medium: Electronic Resource
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  • 9
    Electronic Resource
    Electronic Resource
    Hoboken, NJ : Wiley-Blackwell
    AIChE Journal 42 (1996), S. 1500-1500 
    ISSN: 0001-1541
    Keywords: Chemistry ; Chemical Engineering
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology , Process Engineering, Biotechnology, Nutrition Technology
    Type of Medium: Electronic Resource
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  • 10
    Electronic Resource
    Electronic Resource
    Hoboken, NJ : Wiley-Blackwell
    AIChE Journal 43 (1997), S. 440-447 
    ISSN: 0001-1541
    Keywords: Chemistry ; Chemical Engineering
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology , Process Engineering, Biotechnology, Nutrition Technology
    Notes: The concept of robust design involves identification of design settings that make the product performance less sensitive to the effects of seasonal and environmental variations. This concept is discussed in this article in the context of batch distillation column design with feed stock variations, and internal and external uncertainties. Stochastic optimization methods provide a general approach to robust/parameter design as compared to conventional techniques. However, the computational burden of these approaches can be extreme and depends on the sample size used for characterizing the parametric variations and uncertainties. A novel sampling technique is presented that generates and inverts the Hammersley points (an optimal design for placing n points uniformly on a k-dimensional cube) to provide a representative sample for multivariate probability distributions. The example of robust batch-distillation column design illustrates that the new sampling technique offers significant computational savings and better accuracy.
    Additional Material: 8 Ill.
    Type of Medium: Electronic Resource
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