A novel algorithm for molecular synthesis using enhanced property operators

Chemmangattuvalappil, Nishanth G.; Eljack, Fadwa; Solvason, Charles C.; Eden, Mario R.

doi:10.1016/j.compchemeng.2008.07.016

Cited by 32 publications

(13 citation statements)

References 8 publications

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“…CAMD is the reverse use the group contribution method. Different solution strategies are implemented to solve CAMD techniques: heuristic numeration (Hostrup et al 1999, Li et al, 2002, knowledge based technique Gani, 2000, Yamamoto andTochigi, 2008), molecular property clusters with algebraic equations (Chemmangattuvalappil et al 2009, Eljack and Eden, 2008, Kazantzi et al, 2007 and optimization-based methods (Diwekar and Shastri 2011, Karunanithi et al, 2005, Samudra and Sahinidis, 2005, Ostrovsky et al, 2002.…”

Section: Computer Added Molecular Designmentioning

confidence: 99%

Homogenous multi-agent optimization for process systems engineering problems with a case study of computer aided molecular design

Gebreslassie

Diwekar

2017

Chemical Engineering Science

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In this paper, we propose a novel homogenous multi-agent optimization (HMAO) framework for optimal design of large scale process system engineering problems. The platform is validated using a benchmark problems and a computer-aided molecular design (CAMD) problem. The molecular design problem is a solvent selection problem and it is formulated as a mixed integer nonlinear programming (MINLP) in which solute distribution coefficient of a candidate solvent is maximized subject to structural feasibility, thermodynamic property and process constraints. The model simultaneously determines the optimal decisions that include the size and the functional groups of the candidate solvents. In developing the HMAO framework, multiple efficient ant colony optimization (EACO) algorithms are considered as distinct algorithmic agents. We illustrate this approach through a real world case study of the optimal design of solvent for extraction of acetic acid from waste process stream using liquid-liquid extraction. The UNIFAC model based on the infinite dilution activity coefficient is used to estimate the mixture properties. The results show that quality of the objective function and the computational efficiencies are improved by a factor ranged from 1.475 to 4.137. The new solvents proposed in this work are with much better targeted thermodynamic properties compared to the solvents proposed so far in previous studies.

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Section: Computer Added Molecular Designmentioning

confidence: 99%

Homogenous multi-agent optimization for process systems engineering problems with a case study of computer aided molecular design

Gebreslassie

Diwekar

2017

Chemical Engineering Science

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“…Molecular structures that can match the property targets are then identified from solving a separate CAMD problem. The corresponding algorithm has been developed and used to design blanket wash solvents in Chemmangattuvalappil et al (2009). Bardow et al (2010) and Oyarzún et al (2011) proposed a two-stage method for integrated molecular and process design where continuous parameters characterizing molecules are optimized together with process variables in the first stage.…”

Section: Introductionmentioning

confidence: 99%

A hybrid stochastic–deterministic optimization approach for integrated solvent and process design

Zhou

Sundmacher

2017

Chemical Engineering Science

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The best solution to computer-aided solvent and process design problems can be only achieved by the simultaneous optimization of solvent molecules and process operating conditions. In this contribution, a hybrid stochastic-deterministic optimization approach is proposed for integrated solvent and process design. It is a combination of a genetic algorithm (GA) that optimizes the discrete molecular variables and a gradient-based deterministic algorithm that solves the continuous nonlinear optimization problem of the process at fixed molecular variables as proposed by the GA. The method is demonstrated on a coupled absorption-desorption process where solvent molecular structures as well as the operating conditions of the absorption and desorption columns are optimized simultaneously. While deterministic mixed-integer nonlinear programming (MINLP) algorithms rely on well-selected initial estimates, the proposed hybrid approach can reliably and steadily solve the problem under random initializations. The combination of the advantages of stochastic and deterministic algorithms makes the approach a promising alternative to conventional MINLP algorithms for solving integrated solvent and process design problems.

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“…The property for molecule i can now be estimated as (Chemmangattuvalappil et al, 2009): Since all the combinations of all first order groups, whose maximum occurrence is taken as the limit, are considered, no potential molecule is left out. Introduction of the higher order groups prior to this stage in the molecular design model would lead to a non-linear model and does not increase the accuracy of the model significantly.…”

Section: Rulementioning

confidence: 99%

“…Also, scaling down data to fit into a graphical representation may prevent it from capturing data at the right level of detail (Qin et al, 2004). An algebraic molecular design approach using higher order groups has been developed (Chemmangattuvalappil et al, 2009), but its application range could be improved if the accuracy of the property prediction is enhanced by better techniques for enumerating higher order groups. The technique incorporated in this work aims at reducing the number of combinations of groups that should be checked for forming a molecule with the required properties.…”

Section: Simultaneous Process and Molecular Designmentioning

confidence: 99%

“…Employing systematic algebraic techniques to design molecules based on GCM decreases the permutations of groups that need to be checked if they have a valid molecule hidden in them. Algorithms to identify the molecules that meet the process targets have been developed by many research groups, including Marcoulaki and Kokossis (1998), Harper et al (1999), Harper and Gani (2000), Eljack et al (2007) and Chemmangattuvalappil et al (2009). In this contribution, the focus is to introduce methods that improve the efficiency of solving the molecular design problem as part of the simultaneous solution of process and product design problems.…”

Section: Introductionmentioning

confidence: 99%

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An algebraic approach for simultaneous solution of process and molecular design problems

Bommareddy

Chemmangattuvalappil

Solvason

et al. 2010

Braz. J. Chem. Eng.

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-The property integration framework has allowed for simultaneous representation of processes and products from a properties perspective and thereby established a link between molecular and process design problems. The simultaneous approach involves solving two reverse problems. The first reverse problem identifies the property targets corresponding to the desired process performance. The second reverse problem is the reverse of a property prediction problem, which identifies the molecular structures that match the targets identified in the first problem. Group Contribution Methods (GCM) are used to form molecular property operators that will be used to track properties. Earlier contributions in this area have worked to include higher order estimation of GCM for solving the molecular design problem. In this work, the accuracy of the property prediction is further enhanced by improving the techniques to enumerate higher order groups. Incorporation of these higher order enumeration techniques increases the efficiency of property prediction and thus the application range of the group contribution methods in molecular design problems. Successful tracking of properties is the key in applying the reverse problem formulation for integrated process and product design problems. An algebraic technique has been developed for solving process and molecular design problems simultaneously. Since both process and molecular property operators target the same optimum process performance, the set of inequality expressions can be solved simultaneously to identify the molecules that meet the desired process performance. Since this approach is based on an algebraic algorithm, any number of properties can be tracked simultaneously.

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A novel algorithm for molecular synthesis using enhanced property operators

Cited by 32 publications

References 8 publications

Homogenous multi-agent optimization for process systems engineering problems with a case study of computer aided molecular design

Homogenous multi-agent optimization for process systems engineering problems with a case study of computer aided molecular design

A hybrid stochastic–deterministic optimization approach for integrated solvent and process design

An algebraic approach for simultaneous solution of process and molecular design problems

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