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41
A review of recent design procedures for water networks in refineries and process plants
 Comput. Chem. Eng
"... This paper presents a review of the procedures to design and retrofit water networks. Although the emphasis is in showing results for refineries, the methods are valid for any process plants. It is first shown that the problem has been decomposed into the design of two interacting subsystems. One pr ..."
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This paper presents a review of the procedures to design and retrofit water networks. Although the emphasis is in showing results for refineries, the methods are valid for any process plants. It is first shown that the problem has been decomposed into the design of two interacting subsystems. One problem is the freshwater and wastewater reuse allocation and the other is the wastewater treatment problem. It is also shown how the wastewater treatment problem was modeled as a distributed and decentralized treatment. The roadmap towards zero liquid discharge and energy integrated solutions is then discussed. Several solution approaches are briefly outlined emphasizing the main trend leaning towards the use of mathematical programming. The major claim made is that mathematical programming can produce globally optimal solutions and practically important suboptimal solutions when conceptual insights are employed to build the models. Although the paper intends to be comprehensive, it emphasizes the author’s recent work. Finally, a few of the existing challenges of the area are outlined. © 2000 Elsevier
High Level Optimization Model for the Retrofit Planning of Process Networks
 Ind. Eng. Chem. Res
, 2002
"... The retrofit design of a network of processes over several time periods is addressed in this paper. A strategy is proposed that consists of a high level to analyze the entire network, and a low level to analyze a specific process flowsheet in detail. A methodology is presented for the high level to ..."
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Cited by 6 (6 self)
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The retrofit design of a network of processes over several time periods is addressed in this paper. A strategy is proposed that consists of a high level to analyze the entire network, and a low level to analyze a specific process flowsheet in detail. A methodology is presented for the high level to model process flowsheets and retrofit modifications using a multiperiod generalized disjunctive programming (GDP) model. This problem is reformulated as a mixedinteger linear program (MILP) using the convex hull formulation. Two examples that illustrate the proposed model are presented. The results show that the proposed GDP model provides a significant benefit over the existing network without retrofit, and provides a clear advantage over intuitively choosing modifications based on heuristics. To illustrate the performance benefits of using the convex hull formulation, the problem is also modeled as an MILP with bigM constraints.
Design of GraphBased Evolutionary Algorithms: A Case Study for Chemical Process Networks
 EVOLUTIONARY COMPUTATION
, 2001
"... This paper describes the adaptation of evolutionary algorithms (EAs) to the structural optimization of chemical engineering plants, using rigorous process simulation combined with realistic costing procedures to calculate target function values. To represent ..."
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Cited by 4 (2 self)
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This paper describes the adaptation of evolutionary algorithms (EAs) to the structural optimization of chemical engineering plants, using rigorous process simulation combined with realistic costing procedures to calculate target function values. To represent
REPRO: Supporting Flowsheet Design by CaseBase Retrieval
 Proceedings of the Third European Workshop on CaseBased Reasoning (pp. 400412
, 1996
"... ion strategy during local components comparison. The localroot of the component x will be denoted: localroot(x). . function defines the role (the task) of a given component in a flowsheet aggregation. The function of the component x will be denoted: function(x). . quantity defines how many ident ..."
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Cited by 3 (1 self)
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ion strategy during local components comparison. The localroot of the component x will be denoted: localroot(x). . function defines the role (the task) of a given component in a flowsheet aggregation. The function of the component x will be denoted: function(x). . quantity defines how many identical components perform the function specified in the function slot. . weight is a real value Î <0;1> that indicates the importance of a given components in the whole assembly. The value of a component x weight will be denoted: weight(x). Additionally each subclass of the component class has domainspecific slots and methods for computing local similarity between two instance components. Thanks to polymorphism the proper domain specific formula is used. Pump Reactor Pump1  class  instance  isa relationship  apartof relationship Pump2 Hydrog. C3 Flowsheet1 Flowsheet2 Reactor1 Reactor2 Component Hydrog. C6C8 Process Pipe Pipe1 Pipe2 Fig.1. The objectoriented flowsheet repre...
Tool Support for the Management of Design Processes in Chemical Engineering
 Computers & Chemical Engineering
, 2003
"... Design processes in chemical engineering are hard to support. In particular, this applies to conceptual design and basic engineering, in which the fundamental decisions concerning the plant design are performed. The design process is highly creative, many design alternatives are explored, and both u ..."
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Cited by 3 (2 self)
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Design processes in chemical engineering are hard to support. In particular, this applies to conceptual design and basic engineering, in which the fundamental decisions concerning the plant design are performed. The design process is highly creative, many design alternatives are explored, and both unexpected and planned feedback occurs frequently. As a consequence, it is inherently difficult to manage design processes, i.e. to coordinate the effort of experts working on tasks such as creation of flow diagrams, steadystate and dynamic simulations, etc. On the other hand, proper management is crucial because of the large economic impact of the performed design decisions. We present a management system which takes the difficulties mentioned above into account by supporting the coordination of dynamic design processes. The management system equally covers products, activities, and resources, and their mutual relationships. With respect to coverage and integration, and with respect to the dynamics of design processes, the functionality of the management system goes considerably beyond commercial project, document, and workflow management systems.
Optimization of reactive distillation processes with simulated annealing
, 1999
"... A simulated annealingbased algorithm (MSIMPSA) suitable for the optimization of mixed integer nonlinear programming (MINLP) problems was applied to the synthesis of a nonequilibrium reactive distillation column. A simulation model based on an extension of conventional distillation is proposed for ..."
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A simulated annealingbased algorithm (MSIMPSA) suitable for the optimization of mixed integer nonlinear programming (MINLP) problems was applied to the synthesis of a nonequilibrium reactive distillation column. A simulation model based on an extension of conventional distillation is proposed for the simulation step of the optimization problem. In the case of ideal vapor}liquid equilibrium, the simulation results are similar to those obtained by Ciric and Gu (1994, AIChE Journal, 40(9), 1479) using the GAMS environment and to those obtained with the AspenPlus modular simulator. The optimization results are also similar to those previously reported and similar to those using an adaptive random search algorithm (MSGA). The optimizations were also performed with nonideal vapor}liquid equilibrium, considering either distributed feed and reaction trays or single feed and reaction tray. The results show that the optimized objective function values are very similar, and mostly independent of the number of trays and of the reaction distribution. It is shown that the proposed simulation/optimization equationoriented environments are capable of providing optimized solutions which are close to the global optimum, and reveal its adequacy for the optimization of reactive distillation
Superstructure Optimization of the Olefin Separation Process
 PROCEEDINGS ESCAPE13 (EDS. A. KRASLAWSKI AND I. TURUNEN
, 2003
"... The olefin separation process involves handling a feed stream with a number of hydrocarbon components. The objective of this process is to separate each of these components at minimum cost. We consider a superstructure optimization for the olefin separation system that consists of several technologi ..."
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Cited by 2 (2 self)
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The olefin separation process involves handling a feed stream with a number of hydrocarbon components. The objective of this process is to separate each of these components at minimum cost. We consider a superstructure optimization for the olefin separation system that consists of several technologies for the separation task units and compressors, pumps, valves, heaters, coolers, heat exchangers. We model the major discrete decisions for the separation system as a generalized disjunctive programming (GDP) problem. The objective function is to minimize the annualized investment cost of the separation units and the utility cost. The GDP problem is reformulated as an MINLP problem, which is solved with the Outer Approximation (OA) algorithm that is available in DICOPT++/GAMS. The solution approach for the superstructure optimization is discussed and numerical results of an example are presented.
A ProcessIntegrated Conceptual Design Environment for Chemical Engineering
 Proc. 18th Intl. Conf. on Conceptual Modeling (ER '99
, 1999
"... . The process industries (chemicals, food, oil, ...) are characterized by   continuous or batch  processes of material transformation. The design of such processes, and their mapping to the available equipment (plants composed of production units in which reactions take place), is a complex p ..."
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. The process industries (chemicals, food, oil, ...) are characterized by   continuous or batch  processes of material transformation. The design of such processes, and their mapping to the available equipment (plants composed of production units in which reactions take place), is a complex process that determines the competitiveness of these industries, as well as their environmental impact. In cooperation with researchers and industry from chemical engineering, we have developed the idea to capture and evaluate the experiences gained about process designs in socalled process data warehouses. The data sources for such process data warehouses are highly heterogeneous tools, e.g. for conceptual design (termed flowsheeting in chemical engineering), for mathematical simulations of large nonlinear differential equation systems, for measurements gained with experimental usage of equipment at small scale or in original size, or even from molecular modeling. The clients of a...
Integrated technique assessment based on the pinch analysis approach for the design
"... of production networks ..."
Evolutionary Approaches to Solve Three Challenging Engineering Tasks
, 1999
"... Three applications of evolutionary algorithms, namely the optimization of the nuclear core reload design, the synthesis of multilayer optical coatings, and the synthesis of chemical engineering plants, are presented in this paper. The examples demonstrate the applicability of the evolutionary appro ..."
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Three applications of evolutionary algorithms, namely the optimization of the nuclear core reload design, the synthesis of multilayer optical coatings, and the synthesis of chemical engineering plants, are presented in this paper. The examples demonstrate the applicability of the evolutionary approach to solve complex realworld problems. These problems are often mixedinteger, variabledimensional and multicriteria optimization problems. Additionally, instead of an objective function, given in a closed form, complex simulation models are used as an objective function, thus prohibiting success by means of classical analysis. Although standard evolutionary algorithms are not able to solve the three complex tasks presented here, enhanced evolutionary algorithms (EAs) clearly demonstrate their potential to do so. Through the three examples, we show the necessary ingredients for tackling realworld optimization problems. In addition to adequate representations and appropriate evolutionar...