Multi-criteria optimization for parametrizing excess Gibbs energy models

Forte, Esther; Kulkarni, Aditya; Burger, Jakob; Bortz, Michael; Küfer, Karl‐Heinz; Hasse, Hans

doi:10.1016/j.fluid.2020.112676

Cited by 12 publications

(6 citation statements)

References 48 publications

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“…Professor Richard E. Smallley, Rice University [1], said, "Among the 10 major challenges facing human beings, there is no doubt that energy issues are in the first place." If there is no energy that can be used reasonably, then other problems cannot be solved.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Zero-Energy Buildings Based on Multicriteria Optimization Method

Chen

Dai

Cai

2022

Adsorption Science & Technology

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This paper uses SketchUp and OpenStudio to design and optimize the multiperformance parameters of the near-zero energy consumption residential building scheme stage. By establishing a basic model, the performance parameters such as insulation thickness, typical outer window, window-to-wall ratio, and their contribution rates within the threshold range are optimized for energy conservation; simulate the energy consumption of the determined multiperformance parameter combination scheme, select the most energy-saving scheme, and calculate its energy-saving contribution rate; calculate the life cycle cost of the above schemes, select the scheme with the lowest cost, and analyze its economic benefits; select energy-saving cost and economic benefit, and calculate energy-saving contribution rate and economic benefit. Finally, through the comparative analysis of the design and test data, this paper concludes that EnergyPlus will optimize the multiperformance parameters of the near-zero energy consumption residential building scheme stage. At the same time, the multiobjective optimization method and process of the passive energy-saving technology of the near-zero energy consumption building proposed in this paper, as well as the technology combination template under different needs, provide a reference for the selection of the technology path.

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Section: Introductionmentioning

confidence: 99%

Optimization of Zero-Energy Buildings Based on Multicriteria Optimization Method

Chen

Dai

Cai

2022

Adsorption Science & Technology

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“…Independent of this finding, we want to stress that even if there is only one solution in the fit, the fit is not very likely to describe several data well at the same time. Insights about the trade‐offs between the description qualities of the different data sets can be obtained by considering the fitting problem as multi‐objective problem 19, 20. And of course, one would introduce temperature‐dependent parameters in many cases to improve the simultaneous description of multiple data sets.…”

Section: Occurrence and Avoidance Of Multiple Solutions When Fitting mentioning

confidence: 99%

Multiple Solutions When Fitting Excess Gibbs Energy Models and Implications for Process Simulation

Vasiliu

Göttl

Bröcker

et al. 2020

Chemie Ingenieur Technik

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Excess Gibbs energy models are often fitted to binary experimental data of phase equilibria. Even in the case of two binary parameters fitted to two binary infinite‐dilution activity coefficients, multiple solutions for the parameters may occur. The present work shows that this is also true, if more data – like vapor‐liquid equilibrium data sets – is used. Chemical systems and conditions are identified that lead to multiple solutions. It is shown that the multiple solutions may lead to significantly different results when the models are used in simulation of separation processes.

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“…Using MCO for the development of thermodynamic models is highly attractive, as it gives an overview of what can be achieved with a given model class regarding the representation of a given data set. ,− Furthermore, MCO provides not only a single “best model” where the question what is “best” depends on arbitrary choices (namely, the weights assigned to the objectives), but provides a whole set of models representing the best compromises.…”

Section: Introductionmentioning

confidence: 99%

“…This is extremely costly when the objective function has to be evaluated by molecular simulations. Therefore, most of the previous works on MCO of molecular models − considered only model classes for which the dependence of the thermodynamic properties of interest from the model parameters had been explored before. Hence, in these cases, the MCO could be based on corresponding empirical correlations.…”

Section: Introductionmentioning

confidence: 99%

Hierarchical Multicriteria Optimization of Molecular Models of Water

Kulkarni,

Bortz,

Küfer

et al. 2024

J. Chem. Inf. Model.

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Many widely used molecular models of water are built from a single Lennard-Jones site on which three point charges are positioned, one negative and two positive ones. Models from that class, denoted LJ3PC here, are computationally efficient, but it is well known that they cannot represent all relevant properties of water simultaneously with good accuracy. Despite the importance of the LJ3PC water model class, its inherent limitations in simultaneously describing different properties of water have never been studied systematically. This task can only be solved by multicriteria optimization (MCO). However, due to its computational cost, applying MCO to molecular models is a formidable task. We have recently introduced the reduced units method (RUM) to cope with this problem. In the present work, we apply the RUM in a hierarchical scheme to optimize LJ3PC water models taking into account five objectives: the representation of vapor pressure, saturated liquid density, self-diffusion coefficient, shear viscosity, and relative permittivity. Of the six parameters of the LJ3PC models, five were varied; only the H–O–H bond angle, which is usually chosen based on physical arguments, was kept constant. Our hierarchical RUM-based approach yields a Pareto set that contains attractive new water models. Furthermore, the results give an idea of what can be achieved by molecular modeling of water with models from the LJ3PC class.

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Multi-criteria optimization for parametrizing excess Gibbs energy models

Cited by 12 publications

References 48 publications

Optimization of Zero-Energy Buildings Based on Multicriteria Optimization Method

Optimization of Zero-Energy Buildings Based on Multicriteria Optimization Method

Multiple Solutions When Fitting Excess Gibbs Energy Models and Implications for Process Simulation

Hierarchical Multicriteria Optimization of Molecular Models of Water

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