A novel hybrid simulation-optimization approach for the optimal design of multicomponent distillation columns

Póster presentado en Escape 22, European Symposium on Computer Aided Process Engineering, University College London, UK, 17-20 June 2012.

A hybrid simulation-optimization approach for the design of internally heat-integrated distillation columns

Paper submitted to AIChE 2012 Annual Meeting: Energy Efficiency by Process Intensification, Pittsburgh, PA, October 28-November 2, 2012.

Logic hybrid simulation-optimization algorithm for distillation design

In this paper, we propose a novel algorithm for the rigorous design of distillation columns that integrates a process simulator in a generalized disjunctive programming formulation. The optimal distillation column, or column sequence, is obtained by selecting, for each column section, among a set of column sections with different number of theoretical trays. The selection of thermodynamic models, properties estimation etc., are all in the simulation environment. All the numerical issues related to the convergence of distillation columns (or column sections) are also maintained in the simulation environment. The model is formulated as a Generalized Disjunctive Programming (GDP) problem and solved using the logic based outer approximation algorithm without MINLP reformulation. Some examples involving from a single column to thermally coupled sequence or extractive distillation shows the performance of the new algorithm.

Integration of different models in the design of chemical processes: Application to the design of a power plant

With advances in the synthesis and design of chemical processes there is an increasing need for more complex mathematical models with which to screen the alternatives that constitute accurate and reliable process models. Despite the wide availability of sophisticated tools for simulation, optimization and synthesis of chemical processes, the user is frequently interested in using the ‘best available model’. However, in practice, these models are usually little more than a black box with a rigid input–output structure. In this paper we propose to tackle all these models using generalized disjunctive programming to capture the numerical characteristics of each model (in equation form, modular, noisy, etc.) and to deal with each of them according to their individual characteristics. The result is a hybrid modular–equation based approach that allows synthesizing complex processes using different models in a robust and reliable way. The capabilities of the proposed approach are discussed with a case study: the design of a utility system power plant that has been decomposed into its constitutive elements, each treated differently numerically. And finally, numerical results and conclusions are presented.

Comparative analysis of the visual performance and aberrometric outcomes with a new hybrid and two silicone hydrogel multifocal contact lenses: a pilot study

Background: The aim was to evaluate the visual performance achieved with a new multifocal hybrid contact lens and to compare it with that obtained with two other currently available multifocal soft contact lenses. Methods: This pilot prospective comparative study comprised a total of 16 presbyopic eyes of eight patients ranging in age from 43 to 58 years. All patients were fitted with three different models of multifocal contact lens: Duette multifocal (SynergEyes), Air Optix AQUA multifocal (Alcon) and Biofinity multifocal (CooperVision). Fittings were performed randomly in each patient according to a random number sequence, with a wash-out period between fittings of seven days. At two weeks post-fitting, visual, photopic contrast sensitivity and ocular aberrometry were evaluated. Results: No statistically significant differences were found in distance and near visual acuity achieved with the three different types of multifocal contact lens (p ≥ 0.05). Likewise, no significant differences between lenses were found in the monocular and binocular defocus curve (p ≥ 0.10). Concerning contrast sensitivity, better monocular contrast sensitivities for 6, 12 and 18 cycles per degree were found with the Duette and Air Optix multifocal compared to Biofinity (p = 0.02). Binocularly, differences between lenses were not significant (p ≥ 0.27). Furthermore, trefoil aberration was significantly higher with Biofinity multifocal (p < 0.01) and Air Optix (p = 0.01) multifocal compared to Duette. Conclusions: The Duette multifocal hybrid contact lens seems to provide similar visual quality outcomes in presbyopic patients with low corneal astigmatism, when compared with other soft multifocal contact lenses. This preliminary result should be confirmed in studies with larger samples.

Large scale optimization of a sour water stripping plant using surrogate models

In this work, we propose a new methodology for the large scale optimization and process integration of complex chemical processes that have been simulated using modular chemical process simulators. Units with significant numerical noise or large CPU times are substituted by surrogate models based on Kriging interpolation. Using a degree of freedom analysis, some of those units can be aggregated into a single unit to reduce the complexity of the resulting model. As a result, we solve a hybrid simulation-optimization model formed by units in the original flowsheet, Kriging models, and explicit equations. We present a case study of the optimization of a sour water stripping plant in which we simultaneously consider economics, heat integration and environmental impact using the ReCiPe indicator, which incorporates the recent advances made in Life Cycle Assessment (LCA). The optimization strategy guarantees the convergence to a local optimum inside the tolerance of the numerical noise.