684 resultados para Extractive distillation


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The addition of oxygenated renewable fuels, such as ethanol or ethyl tert-butyl ether (ETBE) to standard gasoline may be necessary to comply with some environmental directives but could also prevent compliance with some fuel regulations and could also seriously change engine performance. From this point of view, the Reid Vapour Pressure (RVP), the distillation curve, the oxygen content and the density belong to the group of the most relevant parameters. This study evaluates the influence of the simultaneous addition of ethanol and ETBE on some physical properties of engine gasoline. The main conclusion is that the simultaneous addition of ETBE and ethanol changes the RVP, the distillation curve and the density in a way that can affect engine operation and the mandatory EN 228 and ASTM D4814 standards. Some opposite properties of both oxygenates could help to increase the renewable energy content without preventing compliance with these regulations.

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No presente trabalho foram avaliados processos alternativos de dessalinização visando a recuperação e reuso da água contida em salmouras concentradas, sendo o processo de cristalização assistida por destilação por membranas (MDC) investigado com profundidade. Foi desenvolvido um modelo diferencial para o processo de destilação por membranas por contato direto (DCMD), contemplando métodos termodinâmicos rigorosos para sistemas aquosos de eletrólitos fortes, bem como mecanismos de transferência de calor e massa e efeitos de polarização de temperatura e concentração característicos deste processo de separação. Com base em simulações realizadas a partir do modelo matemático assim desenvolvido, foram investigados os principais parâmetros que influenciam o projeto de um módulo de membranas para DCMD. O modelo foi posteriormente estendido com equações de balanço de massa e energia adicionais para incluir a operação de cristalização e desta forma representar o processo de MDC. De posse dos resultados das simulações e do modelo estendido, foi desenvolvido um método hierárquico para o projeto de processos de MDC, com o objetivo de conferir características de rastreabilidade e repetibilidade a esta atividade. Ainda a partir do modelo MDC foram discutidos aspectos importantes em MDC como a possibilidade de nucleação e crescimento de cristais sobre a superfície das membranas, bem como o comportamento do processo com sais com diferentes características de solubilidade e largura da zona metaestável. Verificou-se que para sais cuja solubilidade varia muito pouco com a temperatura e que possuem zona metaestável com pequena largura, caso do NaCl, a operação com resfriamento no cristalizador não é viável pois aumenta excessivamente o consumo energético do processo, sendo nesses casos preferível a operação \"isotérmica\" - sem resfriamento no cristalizador - e o convívio com a possibilidade de nucleação no interior do módulo. No extremo oposto, observou-se que para sais com grande variabilidade da solubilidade com a temperatura, um pequeno resfriamento no cristalizador é suficiente para garantir condições de subsaturação no interior do módulo, sem grande ônus energético para o processo. No caso de sais com pequena variabilidade da solubilidade com a temperatura, mas com largura da zona metaestável elevada, existe certo ônus energético para a operação com resfriamento do cristalizador, porém não tão acentuado como no caso de sais com zona metaestável estreita. Foi proposto um fluxograma alternativo para o processo de MDC, onde foi introduzido um circuito de pré-concentração da alimentação antes do circuito de cristalização, para o caso de alimentação com soluções muito diluídas. Este esquema proporcionou um aumento do fluxo permeado global do processo e consequentemente uma redução na área total de membrana requerida. Verificou-se que através do processo com préconcentração da alimentação de 5% até 10% em massa - no caso de dessalinização de uma solução de NaCl - foi possível reduzir-se a área total da membrana em 27,1% e o consumo energético específico do processo em 10,6%, quando comparado ao processo sem pré-concentração. Foram desenvolvidas ferramentas úteis para o projeto de processos de dessalinização por MDC em escala industrial.

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Com o objetivo de aumentar o lucro de plantas químicas, a Otimização em Tempo Real (RTO) é uma ferramenta que busca determinar as condições ótimas operacionais do processo em estado estacionário, respeitando as restrições operacionais estabelecidas. Neste trabalho foi realizada a implementação prática de um ciclo RTO em um processo de destilação por recompressão de vapor (VRD), propileno-propano, da Refinaria de Paulínia (Petrobras S.A.), a partir de dados históricos da planta. Foram consideradas as principais etapas de um ciclo clássico de RTO: identificação de estado estacionário, reconciliação de dados, estimação de parâmetros e otimização econômica. Essa unidade foi modelada, simulada e otimizada em EMSO (Environment for Modeling, Simulation and Optimization), um simulador de processos orientado a equações desenvolvido no Brasil. Foram analisados e comparados dois métodos de identificação de estado estacionário, um baseado no teste estatístico F e outro baseado em wavelets. Ambos os métodos tiveram resultados semelhantes e mostraram-se capazes de identificar os estados estacionários de forma satisfatória, embora seja necessário o ajuste de parâmetros na sua implementação. Foram identificados alguns pontos estacionários para serem submetidos ao ciclo RTO e foi possível verificar a importância de partir de um estado estacionário para a continuidade do ciclo, já que essa é uma premissa do método. A partir dos pontos analisados, os resultados deste estudo mostram que o RTO é capaz de aumentar o ganho econômico entre 2,5-24%, dependendo das condições iniciais consideradas, o que pode representar ganhos de até 18 milhões de dólares por ano. Além disso, para essa unidade, verificou-se que o compressor é um equipamento limitante no aumento de ganho econômico do processo.

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The increasing economic competition drives the industry to implement tools that improve their processes efficiencies. The process automation is one of these tools, and the Real Time Optimization (RTO) is an automation methodology that considers economic aspects to update the process control in accordance with market prices and disturbances. Basically, RTO uses a steady-state phenomenological model to predict the process behavior, and then, optimizes an economic objective function subject to this model. Although largely implemented in industry, there is not a general agreement about the benefits of implementing RTO due to some limitations discussed in the present work: structural plant/model mismatch, identifiability issues and low frequency of set points update. Some alternative RTO approaches have been proposed in literature to handle the problem of structural plant/model mismatch. However, there is not a sensible comparison evaluating the scope and limitations of these RTO approaches under different aspects. For this reason, the classical two-step method is compared to more recently derivative-based methods (Modifier Adaptation, Integrated System Optimization and Parameter estimation, and Sufficient Conditions of Feasibility and Optimality) using a Monte Carlo methodology. The results of this comparison show that the classical RTO method is consistent, providing a model flexible enough to represent the process topology, a parameter estimation method appropriate to handle measurement noise characteristics and a method to improve the sample information quality. At each iteration, the RTO methodology updates some key parameter of the model, where it is possible to observe identifiability issues caused by lack of measurements and measurement noise, resulting in bad prediction ability. Therefore, four different parameter estimation approaches (Rotational Discrimination, Automatic Selection and Parameter estimation, Reparametrization via Differential Geometry and classical nonlinear Least Square) are evaluated with respect to their prediction accuracy, robustness and speed. The results show that the Rotational Discrimination method is the most suitable to be implemented in a RTO framework, since it requires less a priori information, it is simple to be implemented and avoid the overfitting caused by the Least Square method. The third RTO drawback discussed in the present thesis is the low frequency of set points update, this problem increases the period in which the process operates at suboptimum conditions. An alternative to handle this problem is proposed in this thesis, by integrating the classic RTO and Self-Optimizing control (SOC) using a new Model Predictive Control strategy. The new approach demonstrates that it is possible to reduce the problem of low frequency of set points updates, improving the economic performance. Finally, the practical aspects of the RTO implementation are carried out in an industrial case study, a Vapor Recompression Distillation (VRD) process located in Paulínea refinery from Petrobras. The conclusions of this study suggest that the model parameters are successfully estimated by the Rotational Discrimination method; the RTO is able to improve the process profit in about 3%, equivalent to 2 million dollars per year; and the integration of SOC and RTO may be an interesting control alternative for the VRD process.

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The McCabe-Thiele method is a classical approximate graphical method for the conceptual design of binary distillation columns which is still widely used, mainly for didactical purposes, though it is also valuable for quick preliminary calculations. Nevertheless, no complete description of the method has been found and situations such as different thermal feed conditions, multiple feeds, possibilities to extract by-products or to add or remove heat, are not always considered. In the present work we provide a systematic analysis of such situations by developing the generalized equations for: a) the operating lines (OL) of each sector, and b) the changeover line that provides the connection between two consecutive trays of the corresponding sectors separated by a lateral stream of feed, product, or a heat removal or addition.

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Presentation submitted to PSE Seminar, Chemical Engineering Department, Center for Advanced Process Design-making (CAPD), Carnegie Mellon University, Pittsburgh (USA), October 2012.

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This article analyzes the appropriateness of a text summarization system, COMPENDIUM, for generating abstracts of biomedical papers. Two approaches are suggested: an extractive (COMPENDIUM E), which only selects and extracts the most relevant sentences of the documents, and an abstractive-oriented one (COMPENDIUM E–A), thus facing also the challenge of abstractive summarization. This novel strategy combines extractive information, with some pieces of information of the article that have been previously compressed or fused. Specifically, in this article, we want to study: i) whether COMPENDIUM produces good summaries in the biomedical domain; ii) which summarization approach is more suitable; and iii) the opinion of real users towards automatic summaries. Therefore, two types of evaluation were performed: quantitative and qualitative, for evaluating both the information contained in the summaries, as well as the user satisfaction. Results show that extractive and abstractive-oriented summaries perform similarly as far as the information they contain, so both approaches are able to keep the relevant information of the source documents, but the latter is more appropriate from a human perspective, when a user satisfaction assessment is carried out. This also confirms the suitability of our suggested approach for generating summaries following an abstractive-oriented paradigm.

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In this paper, we present a Text Summarisation tool, compendium, capable of generating the most common types of summaries. Regarding the input, single- and multi-document summaries can be produced; as the output, the summaries can be extractive or abstractive-oriented; and finally, concerning their purpose, the summaries can be generic, query-focused, or sentiment-based. The proposed architecture for compendium is divided in various stages, making a distinction between core and additional stages. The former constitute the backbone of the tool and are common for the generation of any type of summary, whereas the latter are used for enhancing the capabilities of the tool. The main contributions of compendium with respect to the state-of-the-art summarisation systems are that (i) it specifically deals with the problem of redundancy, by means of textual entailment; (ii) it combines statistical and cognitive-based techniques for determining relevant content; and (iii) it proposes an abstractive-oriented approach for facing the challenge of abstractive summarisation. The evaluation performed in different domains and textual genres, comprising traditional texts, as well as texts extracted from the Web 2.0, shows that compendium is very competitive and appropriate to be used as a tool for generating summaries.

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A graphical and systematic analysis of particular cases where the compositions of the streams developed in the rectification column coincide with one of the vapor (yGFk) or liquid (xGFk) portions generated from the GFk can be found in this material (i.e.: yGFk=yk+1,1 or xGFk=xk,NTk).

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ESAT 2014. 27th European Symposium on Applied Thermodynamics, Eindhoven University of Technology, July 6-9, 2014.

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Chiral L-prolinamides 2 containing the (R,R)- and (S,S)-trans-cyclohexane-1,2-diamine scaffold and a 2-pyrimidinyl unit are synthesized and used as general organocatalysts for intermolecular and intramolecular aldol reactions with 1,6-hexanedioic acid as a co-catalyst under solvent-free conditions. The intermolecular reaction between ketone–aldehyde and aldehyde–aldehyde must be performed under wet conditions with catalyst (S,S)-2b at 10 °C, which affords anti-aldols with high regio-, diastereo-, and enantioselectivities. For the Hajos–Parrish–Eder–Sauer–Wiechert reaction, both diastereomers of catalyst 2 give similar results at room temperature in the absence of water to give the corresponding Wieland–Miescher ketone and derivatives. Both types of reactions were scaled up to 1 g, and the organocatalysts were recovered by extractive workup and reused without any appreciable loss in activity. DFT calculations support the stereochemical results of the intermolecular process and the bifunctional role played by the organocatalyst by providing a computational comparison of the H-bonding networks occurring with catalysts 2a and 2b.

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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.

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From climate change over peak oil to the geopolitical scramble for the Arctic, there are ample signs that a global energy crisis is unfolding. The sheer scale and urgency of this looming crisis calls for international coordination. Yet, even a cursory look at the existing international energy institutions leads to a sobering conclusion: the global energy governance architecture is weak, fragmented and incomplete. This policy brief discusses both the flaws in the multilateral energy architecture and some emerging ideas to strengthen it, such as the proposal for a Sustainable Energy Trade Agreement and the new American disclosure rules for the extractive sector.

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The research team reviewed numerous several multi- sectoral entities and identified nine GGNs that became the subject of our case studies. The research team conducted semi-structured interviews with executives and staff from each of these GNNs and prepared a profile, including a description of the unique evolution of the organization, goals and objectives, organizational structure and governance arrangements for each GGN. The following list provides an overview of the nine GGNs profiled: 1. Every Woman Every Child is an unprecedented global effort that mobilizes and amplifies action by governments, multilaterals, the private sector, research centers, academia and civil society to address life-threatening health challenges facing women and children globally. 2. HERproject catalyzes global partnerships and local Networks to improve female workers’ general and reproductive health in eight emerging economies. 3. R4 Rural Resilience Initiative is a cutting-edge, strategic, large-scale partnership between the public and private sectors to innovate and develop better tools to help the world’s most vulnerable people build resilient livelihoods. 4. Extractive Industry Transparency Initiative is a coalition of governments, companies, civil society groups, investors and international organizations that aims to improve transparency and accountability in the extractives sector. 5. Global Network for Neglected Tropical Diseases works with international partners at the highest level of government, business and society to break down the logistical and financial barriers to delivering existing treatments for the seven most common neglected tropical diseases. 6. Global Alliance for Improved Nutrition is an alliance that supports public-private partnerships to increase access to the missing nutrients in diets necessary for people, communities and economies to be stronger and healthier. 7. Inter-Agency Network For Education in Emergencies is a global Network of individuals and representatives from NGOs, United Nations and donor agencies, governments, academic institutions, schools and affected populations working to ensure all persons have the right to a quality and safe education in emergencies and post- crisis recovery. 8. mHealth Alliance works with diverse partners to advance mobile-based or mobile-enhanced solutions that deliver health through research, advocacy, support for the development of interoperable solutions and sustainable deployment models. 9. The Rainforest Alliance is a global non-profit that focuses on environmental conservation and sustainable development and works through collaborative partnerships with various stakeholders.