Continuous flow nanocatalysis: reaction pathways in the conversion of levulinic acid to valuable chemicals

The selective production of 2-methyltetrahydrofuran from levulinic acid has been effectively conducted using designed Cu based catalysts and compared with a commercial Pd/C system under microwave irradiation. Optimised conditions for the most active catalysts Cu-MINT (>90% conversion, 75% selectivity to MTHF) and Pd/C (78% conversion, 92% selectivity to MTHF) were further translated into a continuous flow process using the proposed catalysts to find out the deactivation of Cu-MINT under flow conditions (79 vs. 13% conversion with a switch in selectivity to products after 30 min in flow), the high stability of Pd/C (73 vs. 70% conversion at stable selectivity under analogous conditions to those of Cu-MINT) but, most importantly, different relevant pathways to valuable products from levulinic acid depending on the type of catalyst employed.

Integration of modular process simulators under the Generalized Disjunctive Programming framework for the structural flowsheet optimization

The optimization of chemical processes where the flowsheet topology is not kept fixed is a challenging discrete-continuous optimization problem. Usually, this task has been performed through equation based models. This approach presents several problems, as tedious and complicated component properties estimation or the handling of huge problems (with thousands of equations and variables). We propose a GDP approach as an alternative to the MINLP models coupled with a flowsheet program. The novelty of this approach relies on using a commercial modular process simulator where the superstructure is drawn directly on the graphical use interface of the simulator. This methodology takes advantage of modular process simulators (specially tailored numerical methods, reliability, and robustness) and the flexibility of the GDP formulation for the modeling and solution. The optimization tool proposed is successfully applied to the synthesis of a methanol plant where different alternatives are available for the streams, equipment and process conditions.

Rigorous Design of Complex Distillation Columns Using Process Simulators and the Particle Swarm Optimization Algorithm

We present a derivative-free optimization algorithm coupled with a chemical process simulator for the optimal design of individual and complex distillation processes using a rigorous tray-by-tray model. The proposed approach serves as an alternative tool to the various models based on nonlinear programming (NLP) or mixed-integer nonlinear programming (MINLP) . This is accomplished by combining the advantages of using a commercial process simulator (Aspen Hysys), including especially suited numerical methods developed for the convergence of distillation columns, with the benefits of the particle swarm optimization (PSO) metaheuristic algorithm, which does not require gradient information and has the ability to escape from local optima. Our method inherits the superstructure developed in Yeomans, H.; Grossmann, I. E.Optimal design of complex distillation columns using rigorous tray-by-tray disjunctive programming models. Ind. Eng. Chem. Res.2000, 39 (11), 4326–4335, in which the nonexisting trays are considered as simple bypasses of liquid and vapor flows. The implemented tool provides the optimal configuration of distillation column systems, which includes continuous and discrete variables, through the minimization of the total annual cost (TAC). The robustness and flexibility of the method is proven through the successful design and synthesis of three distillation systems of increasing complexity.

Factors that determine the level of commitment of our teaching staff when the implementation of continuous evaluation system takes place

Comunicación presentada en CIDUI 2010, Congreso Internacional Docencia Universitaria e Innovación, Barcelona, 30 junio-2 julio 2010.

Logic-Based Outer-Approximation Algorithm for Solving Discrete-Continuous Dynamic Optimization Problems

We present an extension of the logic outer-approximation algorithm for dealing with disjunctive discrete-continuous optimal control problems whose dynamic behavior is modeled in terms of differential-algebraic equations. Although the proposed algorithm can be applied to a wide variety of discrete-continuous optimal control problems, we are mainly interested in problems where disjunctions are also present. Disjunctions are included to take into account only certain parts of the underlying model which become relevant under some processing conditions. By doing so the numerical robustness of the optimization algorithm improves since those parts of the model that are not active are discarded leading to a reduced size problem and avoiding potential model singularities. We test the proposed algorithm using three examples of different complex dynamic behavior. In all the case studies the number of iterations and the computational effort required to obtain the optimal solutions is modest and the solutions are relatively easy to find.

Willingness Towards Continuous Assessment

Among the factors that affect the convergence towards the European Higher Education Area, university teaching staff's motivation is fundamental, and consequently, it is crucial to empirically know what this motivation depends on. In this context, one of the most relevant changes in the teacher-student relationship is assessment. In fact, the transition from a static assessment -focused on only one temporal point (final exam)- to a dynamic assessment, will require changes in thought and action, both on the part of teachers and students. In this line, the objective of this paper is to analyze the determinants of teaching staff's predisposition to the continuous assessment method. Specifically, we consider the following explanatory dimensions: teaching method used (which measures their degree of involvement with the ongoing adaptation process), type of subject (core, compulsory and optional), and teacher's personal characteristics (professional status and gender). The empirical application carried out at the University of Alicante uses Logit Models with Random Coefficients to capture heterogeneity, and shows that "cooperative learning" is a clear-cut determinant of "continuous assessment" as well as "continuous assessment plus final examination". Also, a conspicuous result, which in turn becomes a thought-provoking finding, is that professional status is highly relevant as a teacher's engagement is closely related to prospects of stability. Consequently, the most relevant implications from the results revolve around the way academic institutions can propose and implement inducement for their teaching staff.

Fostering Teaching Staff's Engagement in Continuous Assessment

Among the factors that affect the convergence towards the European Higher Education Area, university teaching staff's motivation is fundamental, and consequently, it is crucial to empirically know what this motivation depends on. In this context, one of the most relevant changes in the teacher-student relationship is assessment. In fact, the transition from a static assessment -focused on only one temporal point (final exam)- to a dynamic assessment, will require changes in thought and action, both on the part of teachers and students. In this line, the objective of this paper is to analyze the determinants of teaching staff's predisposition to the continuous assessment method. Specifically, we consider the following explanatory dimensions: teaching method used (which measures their degree of involvement with the ongoing adaptation process), type of subject (core, compulsory and optional), and teacher's personal characteristics (professional status and gender). The empirical application carried out at the University of Alicante uses Logit Models with Random Coefficients to capture heterogeneity, and shows that "cooperative learning" is a clear-cut determinant of "continuous assessment" as well as "continuous assessment plus final examination". Also, a conspicuous result, which in turn becomes a thought-provoking finding, is that professional status is highly relevant as a teacher's engagement is closely related to prospects of stability. Consequently, the most relevant implications from the results revolve around the way academic institutions can propose and implement inducement for their teaching staff.