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.

Optimization of Chemical Processes Using Surrogate Models Based on a Kriging Interpolation

Superstructure approaches are the solution to the difficult problem which involves the rigorous economic design of a distillation column. These methods require complex initialization procedures and they are hard to solve. For this reason, these methods have not been extensively used. In this work, we present a methodology for the rigorous optimization of chemical processes implemented on a commercial simulator using surrogate models based on a kriging interpolation. Several examples were studied, but in this paper, we perform the optimization of a superstructure for a non-sharp separation to show the efficiency and effectiveness of the method. Noteworthy that it is possible to get surrogate models accurate enough with up to seven degrees of freedom.

Phrase-based statistical machine translation: explanation of its processes and statistical models and evaluation of the English to Spanish translations produced

Statistical machine translation (SMT) is an approach to Machine Translation (MT) that uses statistical models whose parameter estimation is based on the analysis of existing human translations (contained in bilingual corpora). From a translation student’s standpoint, this dissertation aims to explain how a phrase-based SMT system works, to determine the role of the statistical models it uses in the translation process and to assess the quality of the translations provided that system is trained with in-domain goodquality corpora. To that end, a phrase-based SMT system based on Moses has been trained and subsequently used for the English to Spanish translation of two texts related in topic to the training data. Finally, the quality of this output texts produced by the system has been assessed through a quantitative evaluation carried out with three different automatic evaluation measures and a qualitative evaluation based on the Multidimensional Quality Metrics (MQM).

Multimodal analysis of a sample of political posters in Ireland during and after the Celtic Tiger

The aim of this research paper is to analyse the key political posters made for the campaigns of Irish political party Fianna Fáil framed in the Celtic Tiger (1997-2008) and post-Celtic Tiger years (2009-2012). I will then focus on the four posters of the candidate in the elections that took place in 1997, 2002, 2007 and 2011 with the intention of observing first how the leader is represented, and later on pinpointing the similarities and possible differences between each. This is important in order to observe the main linguistic and visual strategies used to persuade the audience to vote that party and to highlight the power of the politician. Critical discourse analysis tools will be helpful to identify the main discursive strategies employed to persuade the Irish population to vote in a certain direction. Van Leeuwen’s (2008) social actor theory will facilitate the understanding of how participants are represented in the corpus under analysis. Finally, the main tools of Kress and van Leeuwen’s visual grammar (2006) will be applied for the analysis of the images. The study reveals that politicians are represented in a consistently positive way, with status and formal appearance so that people are persuaded to vote for the party they represent because they trust them as political leaders. The study, thus, points out that the poster is a powerful tool used in election campaigns to highlight the power of political parties.