Distillation | EPFL Graph Search

thumb|200px|Une colonne à distiller au musée Stella Matutina de Saint-Leu, à La Réunion. La distillation est un procédé de séparation de mélange de substances liquides dont les températures d'ébullition sont différentes. Elle permet de séparer les constituants d'un mélange homogène. Sous l'effet de la chaleur ou d'une faible pression (loi des gaz parfaits), les substances se vaporisent successivement, et la vapeur obtenue est liquéfiée pour donner le distillat. Dès le , des opérations de « distillation » sont réalisées dans l'industrie pour obtenir entre autres du coke à partir de la houille, ou des gaz manufacturés. Ces opérations doivent être plus justement appelées pyrolyse : le terme « pyrolyse » est apparu probablement au pour distinguer les opérations de décomposition ou thermolyse, d'un composé organique par la chaleur pour obtenir d'autres produits (gaz et matière) qu'il ne contenait pas : dans la pyrolyse, le matériau est détruit. On peut supposer que par analogie, la cornu

Unsupervised Learning for Information Distillation

Kamand Kamangar

Current document archives are enormously large and constantly increasing and that makes it practically impossible to make use of them efficiently. To analyze and interpret large volumes of speech and text of these archives in multiple languages and produce structured information of interest to its user, information distillation techniques are used. In order to access the key information in response to a request (query), special text processing techniques such as distillation are required. The task consists of filtering methods to extract the important portions of relevant documents, named as snippets, to a query, as concisely and as correctly as possible. In the context of GALE Project, the queries are matched into several predefined templates. Template 1, which is the main focus of this work, corresponds to listing of facts about an {EVENT}. Answering to template 1 questions is much similar to extraction of general passages from an IR engine. In this work, we are implementing an iterative unsupervised method to answer the queries of this template. The goal of unsupervised learning is to increase the performance of classifier in terms of error rate and f-measure without depending to prior annotated data. The approach consists of using only highly confident features such as word transcriptions extracted from query as well as their synonyms. After forming the bootstrap model using these features, the model is improved using self-training, and is iteratively trained during consecutive runs. Our results indicate that the performance of the system may be improved by more than 12.5% relative in terms of classification error and 31% relative in terms of F-measure, by using the proposed methods.

IDIAP2007

Evaluation of advanced technologies based on integration techniques - Application on dividing wall column

Seifeldine Ahmed Fathalla

In order to separate a mixture into high purity products, Dividing Wall Distillation Columns (DWCs) have shown to be, in most cases, more convenient than using conventional distillation column sequence. In fact in DWCs the entire separation task occurs in one thermally coupled column shell hence reducing investement and operationg cost up to 60%. The DWC is a one column shell with a condensor at the top and a reboiler at the bottom. A wall located inside the shell divides a particular region of the column in two. Size and position of the wall among other elements will have an important effect on product purities strongly dependent on the relative volatility of the components. The assembly of the wall inside the shell represents the most critical step of fabrication, two methods for assembling the wall inside the shell are used, by welding or using stacked wall elements. In order to evaluate DWC using pinch analysis, the DWC has to be separated from the rest of the process GCC, plotting the CGCC and mirroring it to the rest of the process GCC which helps then indentify possible heat recovery between the Column and the background process and hence identify the most efficient way of placing intermediate heat exchangers for heat recovery. Modelling a DWC has proven to be a very difficult task. Using sensitivity analysis we were able to identify the key parameters infulencing the composition of our product streams. In the case of our design, the required high purties in the two stream products meaning 99% Butanol purity and 99% 2-Ethyl- Butanol purity have been reached. Unfortunatly specification to reach low purities in some components for both streams presented to be challenging and were not quite reached (less than 0.5% 2-Ethyl-Butanol was required for the Butanol product stream and 0.68% was reached, less than 0.5% of Hexanol in the 2-Ethyl Butanol product was required and 0.76% was reached). Using pinch analysis tthe MER requirement of both the conventional sequence and the DWC was identified. The CGCC and Carnot CGCC was plotted. The MER for the conventional distillation sequence was found to be 2060 [Kw] while for the DWC model 1809 [Kw]. The DWC has hence an MER 12% lower than what is required for the conventional sequence. However exergy losses in DWC (195 [Kw]) have shown to be larger than for the sequential distillation column (192 [Kw]). This is contrary to the results found in the literature, further improvement of the DWC have to be made.

2013

An Atomistic Simulation Method for Oxygen Impurities in Aluminium Based on Variable Charge Molecular Dynamics

Andreas Elsener

Impurities are known to have a significant impact on materials properties. In particular, the presence of impurities can change mechanical properties and stabilize the microstructure by reducing grain growth and recrystallization processes. In the past atomistic simulations, in particular molecular dynamics, have contributed a lot to the understanding of deformation mechanisms in nanocrystalline metals. Especially, insights into details of dislocation/GB interactions have been gained. Additionally, simulations on coupled grain boundary migration in bicrystalline samples have played an important role in understanding stress assisted grain growth in nanocrystalline metals. However, all these simulations have been performed on monatomic systems. This means that the role of impurities has not yet been considered in these simulations. Some of the important difference between experiments and simulations could be removed by introducing dilute O distributions to computational Al samples. For this purpose, a simulation method is required which can deal with the oxidation of Al atoms around the O impurities and which can simulate the ionic and metallic nature of bonding simultaneously. Here, a method is suggested which fulfills the requirements by modifying the variable charge method of Streitz and Mintmire [Phys. Rev. B 50, 11996 (1994)]. A local chemical potential approach which optimizes the charge on only those atoms expected to be ionic is developed. Additionally the EAM potential for the non-electrostatic interaction given in the publication of Streitz and Mintmire is substituted by empirical potentials which treat the Al-Al interactions with a well-known Al potential. The Al-O and O-O interactions in these EAM potentials are fitted for the simulation of dilute O impurities in Al and additionally for the simulation of corundum in case of a second potential. The aforementioned developments are applied to study the effect of O impurities on the deformation of nc Al. A fully three-dimensional nc sample containing 15 grains of 12 nm grain-size is deformed with a dilute O content in the triple junction lines. The impact of O impurities on dislocation propagation is also considered in a sample which consists of a single grain extracted from a large molecular dynamics simulation. This simulation geometry contains a perfect dislocation, which is pinned at the surrounding grain boundary network. Therefore it allows the study of pinning strength and after unpinning the propagation behavior of the dislocation under various O impurity distributions. Additionally, the role of O impurities on coupled GB migration is investigated by studying two bicrystalline samples with different O distributions in both of them. In the discussion, the emphasis is on the simulation method. Especially, the significance of the samples, simulation conditions and the performance of the method in the different applications are discussed. Additionally, the different developments (local chemical potential approach and EAM potentials) are critically analyzed and improvements for future simulations of impurities are suggested.

EPFL2010