A Property Based Approach for Simultaneous Process and Molecular Design

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

doi:10.1016/s1004-9541(08)60100-7

Cited by 21 publications

(13 citation statements)

References 15 publications

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“…A good understanding of molecular phenomena can aid the consideration of the properties in process design, for example, deciding the best location for stream recycling not only based on mineral concentrations, but also considering the final result in properties (such as pH, chemical potential, dissolved oxygen). A technique for property integration based on property clustering can be used for this purpose [176][177][178]. To achieve these objectives, more research and development efforts in this area are necessary.…”

Section: Discussionmentioning

confidence: 99%

Trends in Modeling, Design, and Optimization of Multiphase Systems in Minerals Processing

2019

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Multiphase systems are important in minerals processing, and usually include solid–solid and solid–fluid systems, such as in wet grinding, flotation, dewatering, and magnetic separation, among several other unit operations. In this paper, the current trends in the process system engineering tasks of modeling, design, and optimization in multiphase systems, are analyzed. Different scales of size and time are included, and therefore, the analysis includes modeling at the molecular level (molecular dynamic modeling) and unit operation level (e.g., computational fluid dynamic, CFD), and the application of optimization for the design of a plant. New strategies for the modeling, design, and optimization of multiphase systems are also included, with a strong focus on the application of artificial intelligence (AI) and the combination of experimentation and modeling with response surface methodology (RSM). The integration of different modeling techniques such as CFD with discrete element simulation (DEM) and response surface methodology (RSM) with artificial neural networks (ANN) is included. The paper finishes with tools to study the uncertainty, both epistemic and stochastic, based on uncertainty and global sensitivity analyses, which is present in all mineral processing operations. It is shown that all of these areas are very active and can help in the understanding, operation, design, and optimization of mineral processing that involves multiphase systems. Future needs, such as meso-scale modeling, are highlighted.

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Section: Discussionmentioning

confidence: 99%

Trends in Modeling, Design, and Optimization of Multiphase Systems in Minerals Processing

2019

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“…Within the computer-aided molecular design (CAMD) framework (Harper and Gani, 1999;Eljack et al, 2008;McLeese et al, 2010), a characterization based method was combined with chemometric (Solvason, 2011;Hada et al, 2011) and property clustering techniques (Shelley and El-Halwagi, 2000) in a reverse problem formulation (Eden et al, 2004) to develop a logical and systematic approach of selectively choosing a given ionic pair that matches a set of desired physical property targets. The following sections describe these techniques and frameworks in detail and demonstrate how they relieve the challenges and limitations mentioned earlier.…”

Section: Methodsmentioning

confidence: 99%

Characterization Based Reverse Design of Ionic Liquids

Davis

Hada

Herring

et al. 2014

Proceedings of the 8th International Conference on Foundations of Computer-Aided Process Design

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“…Screening-based methods, and that reduce the molecular search space, based on a generate-and-test strategy, that employ physical property targets have been used in several studies (Hostrup et al, 1999;Karunanithi et al, 2005;Eljack et al, 2008). The determination of targets by using property "clusters" has been investigated (Eljack et al, 2008). Buxton et al (1999) proposed a screening approach embedded in an MINLP optimizer and applied it to the design of a solvent for a separation unit with fixed operating conditions.…”

Section: Introductionmentioning

confidence: 99%

“…Hierarchical optimization has been used to generate initial guesses for the solution of the full CAMPD problem (Burger et al, 2015). Screening-based methods, and that reduce the molecular search space, based on a generate-and-test strategy, that employ physical property targets have been used in several studies (Hostrup et al, 1999;Karunanithi et al, 2005;Eljack et al, 2008). The determination of targets by using property "clusters" has been investigated (Eljack et al, 2008).…”

Section: Introductionmentioning

confidence: 99%