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Publisher Summary This chapter describes an industrial application of predictive functional control (PFC), which belongs to a family of Model Predictive Control (MBPC). The case presented in this chapter consists of controlling the bottom level and the reboiler temperature of a stripper distillation column, which belongs to the naphtha hydrotreater (Hydrobon) plant located at REPSOL-YPF Plaza Huincul refinery. The Hydrobon plant objective is to eliminate the downstream naphtha reforming (Platforming) plant catalyst. Level and temperature control by zone strategy is implemented; it involves keeping the level and temperature inside a specific allowable band with respect to the set point, and the corresponding controller tuning parameters are adjusted depending on that. The project consists of three main steps: process identification, off-line controller design, and on-line commissioning. The controllers were implemented in the control processor of the Distributed Control System (DCS). This chapter presents the details of the identification and off-line design as well as the results obtained after the control strategies commissioning.

Publisher Summary A new process to value a methanol + methyl acetate (MeOH + MeAc) azeotropic mixture by reactive extractive distillation with n-butanol (BuOH) using o-xylene as entrainer has been developed. High purity MeOH and butyl acetate (BuAc) were obtained as products. This chapter discusses how to synthesize (batch/continuous comparison, residue curve map analysis, and solvent selection), to size and rate the equipments (steady state simulation of the azeotropic separation, the reactive extractive distillation unit, and the solvent recovery system), and to perform the process dynamic modeling (control strategy, parameter tuning, and robustness analysis) of a reactive extractive distillation unit and solvent recovery system. Detailed analysis of the reactive and extractive distillation unit should be performed because of parameter coupling. The preliminary economic study carried out reveals that the process has no profitability. As expected, the process bottleneck is the reactive distillation unit and, in particular, the control strategy to achieve coupled targets.

Publisher Summary This chapter describes the synthesis of reactive and extractive distillation units, using distillation line diagrams. It gives detailed description of EXTRACTIVE DISTILLATION and REACTIVE DISTILLATION. For extractive distillation, solvents need to be chosen just on the basis of selectivity to emphasize the cost of the extraction column, whereas the cost in the solvent recovery system is sometimes significant and may control the cost of the global process. The in-situ removal of product form the reaction zone causes equilibrium-limited reactions to be shifted forward, thus allowing high conversion. Moreover, the chemical reaction can change the topology of the nonreactive residue curve maps (RCM). For extractive and reactive distillation, accurate analysis of the non-reactive RCM is needed. Moreover, to visualize the solution, transformed molar composition (Ung and Doherty) provides information on the feasibility and column sequencing. This is done by determining the stables and unstable nodes, detecting any reactive azeotrope and reactive distillation boundaries and targeting them as potential bottoms and distillate products respectively.

Publisher Summary This chapter describes the dynamic modeling of batch distillation by drawing a comparison between commercial software. Checking the accuracy of the physical properties' model is the key factor to succeed in process simulation, obtaining realistic results. To compare the results from different process simulators, the same physical property model and parameters were used. For the high tendency to avoid the use of any group contribution method for process simulation, universal quasichemical (UNIQUAC) method was selected. For this, UNIQUAC parameters have been modified to be temperature-dependent. Going further, the chapter discusses the process of Initialization with HYSYS®, initialization using BATCHFRAC®, and a pseudo-stationary model. However if the models are to be used as ad-hoc observer or estimator for control purposes, the temperature measurements have lower time lag (around 30 seconds) and are the best economic way to estimate the composition. In all cases, the essential factor is interface between process simulators and plant data. The experimental temperature data confronted with the prediction for each software are in a good correlation. Therefore, the chapter emphasizes the fact that additional considerations about commercial elements of available software and hardware should also be done.

Arising the Nearly Zero Energy Buildings (NZEB) concept in Europe, the solar district heating systems (SDHS) present a potential solution to meet the buildings sector's European energy performance directive. Nevertheless, current practices face several technological and economical barriers to ensure service quality. In this context, our work presents a sustainability analysis (technical, economic, environmental, and social) for SDHS integration in the residential sector to meet the NZEB and positive energy building goals. This paper proposes an application of a machine learning model incorporating multi-objective optimization and multi-criteria decision making to facilitate a sustainability index for the decision-making stakeholders and policymakers. The proposed analysis application is illustrated through retrofitted residential communities with building energy rating (D) at different sizes (10, 25, 50, 100, and 500 houses) located in Emmen (Netherlands) and compared to a standard decentralized heat pump. The optimization results show the ability of SDHS to provide a solar fraction up to 95% in the community of 500 houses. Furthermore, achieving a NZEB status is only approved economically from a community size of 100 houses with a life cycle cost of 41 €/m2 and a payback period of 25 years. These results align with a substantial environmental and social improvement of 78.2% and 29.7%, respectively, compared to the decentralized heat pump. Overall, this study provides policy decision making with an evaluation for positive energy communities and suggests the SDHS integration to meet the global sustainability goals.

One of the most important drawbacks of life cycle assessment (LCA)-related analysis is the generation of reliable data. In the proposed methodology, this drawback is addressed using data from process simulations, based on first-principles models in the LCA calculations. Furthermore, uncertainty that arises from industrial data and a simulation hypothesis are explicitly incorporated, using Monte Carlo sampling, which allows statistical information to be translated into a set of representative scenarios for which the LCA calculations are performed. The combined use of LCA, process simulation, and sampling techniques results in a powerful environmentally conscious quantitative tool whose objective is to guide decision-makers toward the adoption of more-sustainable process alternatives. The main objective of the methodology is to show the main differences between production options. This novel methodology is applied to the specific case of phosphoric acid (PA) production.

The main objective of this paper is to present the application of selected multivariable statistical techniques in plant-wide wastewater treatment plant (WWTP) control strategies analysis. In this study, cluster analysis (CA), principal component analysis/factor analysis (PCA/FA) and discriminant analysis (DA) are applied to the evaluation matrix data set obtained by simulation of several control strategies applied to the plant-wide IWA Benchmark Simulation Model No 2 (BSM2). These techniques allow i) to determine natural groups or clusters of control strategies with a similar behaviour, ii) to find and interpret hidden, complex and casual relation features in the data set and iii) to identify important discriminant variables within the groups found by the cluster analysis. This study illustrates the usefulness of multivariable statistical techniques for both analysis and interpretation of the complex multicriteria data sets and allows an improved use of information for effective evaluation of control strategies.

Multi-objective optimization (MOO) is increasingly being used in a wide variety of applications to identify alternatives that balance several criteria. The energy sector is not an exception to this trend. Unfortunately, the complexity of MOO grows with the number of environmental objectives. This limitation is critical in energy systems, in which several environmental criteria are typically used to assess the merits of a given technology. In this paper, we investigate the use of a rigorous dimensionality reduction method for reducing the complexity of MOO as applied to an energy system (i.e., a solar Rankine cycle coupled with reverse osmosis and thermal storage). Instead of using an aggregated environmental metric, a common approach for reducing the number of environmental objectives in MOO, we propose to optimize the system in a reduced search space of objectives that fully describe its performance and which results from eliminating redundant criteria from the analysis. Numerical results show that it is possible to reduce the problem complexity by omitting redundant environmental indicators from the optimization. The authors would like to acknowledge financial support from the Spanish GovernmentENE2011-28269-C03-03, ENE2011-22722, DPI2012-37154-C02-02, CTQ2012-37039-C02) and to thank the Catalan Government for the quality accreditation given to their research groups SUSCAPE and GREA (2009 SGR 545, 2009 SGR 534).

In the framework of Knowledge Management, the Internet can be a valuable source of information to produce new Knowledge. Here, an ontology-based web search system to ease the enterprise managers in the process of discovering new knowledge from the documents in the Internet is introduced. By means of a graphical user interface, the user of the system supplies an ontology in RDF to describe the domain of interest, and sets up some predefined parameters in order to constrain the search corpus. A distributed intelligent process works to achieve the levels of quality and quantity about the results that the user established. Several ideas about how to use this system and its application to seven real domains are also supplied.

Responsible research and innovation (RRI), as an integrated concept, is being promoted by the European Union since 2010 and forms part of the Horizon 2020 in the area of science with and for society. RRI is formed by five strategic dimension: public engagement, gender equality, science education, open science and ethics, to which the transversal dimension of governance is added to develop harmonious governance models and institutional strategies. RRIL developed learning courses for three of these dimensions: public engagement, gender equality and ethics, to which we add an introductory course to ReSI. The course introduces the students how gender is conceived in conventional and gender economic approach and to the linkage between gender and ecological economics. It enables the practitioner to apply broader multi-disciplinary approach to evaluate the sustainable impact of their research and innovation activities based on the three pillar model: ecological, economic and social sustainability, but also to assess policy impact. The course introduces the learners in the topic of gender equality as a guiding principle of responsible and sustainable research enabling them to apply the gender perspective in the processes of social and technological innovation, taking here the fields of economy, energy and artificial intelligence, especially in urban planning as pivotal points. It underpins the linkage of the gender perspective with public engagement and innovation ethics to achieve sustainable impact of science based innovation enabling the students to apply holistic innovation approach using the three-pillar model of sustainability. The course is accessible and open for download and importation to other learning platform (previous registration as teacher) at canvas.instructure.com: English version: https://lor.instructure.com/resources/0aa23b741bac4f6a855057d12c8e17c1 Spanish version: https://lor.instructure.com/resources/d4d02abecfaa4b6a9c48db55d1630827 publishedVersion

A new process to exploit a methanol + methyl acetate mixture by reactive and extractive distillation with n-butanol using o-xylene as the entrainer has been developed. The aim of this work is to synthesize, design, and study the dynamic behavior for the azeotropic separation, the reactive and extractive distillation unit, and the solvent recovery system. The process was modeled using rate-based and equilibrium-stage approaches with the kinetic expression developed for the transesterification reaction and reported in part I of this paper (Ind. Eng. Chem. Res. 2002, 41, 6663). High-purity methanol and butyl acetate were obtained as products, and yields approaching 100% of n-butanol were achieved. A parametric study elucidated the effects of the key operating variables. As expected, the process bottleneck is the reactive and extractive distillation unit and, in particular, the control strategy for achieving the coupled targets. A preliminary economic study reveals that the process has no profitability.

Multi-objective optimization (MOO) has emerged recently as a useful technique in the design andplanning of engineering systems because it allows identifying alternatives leading to significant envi-ronmental savings. MOO models typically contain an infinite number of Pareto solutions, from whichdecision-makers should choose the best one according to their preferences. An approach is here pre-sented that identifies and retains for further inspection a reduced set of Pareto solutions showing betteroverall performance. The capabilities of our approach are illustrated through its application to the designof reverse osmosis desalination plants considering simultaneously the unitary production cost and a setof environmental impacts in several damage categories. Our method reduces significantly the number ofPareto points, thereby facilitating the decision-making process in MOO. The authors would like to acknowledge financial support from the Spanish Government(ENE2011-28269-C03-03, ENE2011-22722, DPI2012-37154-C02-02, CTQ2012-37039-C02) and the Catalan Government for the quality accreditation given to their research groups SUSCAPE and GREA (2009 SGR 545, 2009 SGR 534)

Responsible Research & Innovation is a genius concept developed by the European Commission for the governance of research and innovation processes with a view on the (ethical) acceptability, sustainability and societal desirability of the innovation process and its marketable products. It aims to shape, maintain, develop, coordinate and align existing and novel research and innovation-related processes, actors and responsibilities with a view to ensuring desirable and acceptable research outcomes. In the Horizon 2020 programmes, there were and are some projects focusing on related training needs. But there is no substantial attempt observable to develop continuous higher education programmes supporting the implementation of this concept and the respective reorganisation processes in universities, research centres, research and innovation oriented enterprises and public authorities like cities or regional governments. This project pretends to fulfil this gap through the co-creation of higher education modules between different research and innovation actors. RRIL especially focus on public engagement, gender equality and ethics (in the knowledge fields Energy and Economy) testing the learning modules in innovative environments based on interactive real-problem approaches. The modules developed are offered to research and innovation actors supporting the implementation of RRI principles in the organisations capacitating the learners to develop jointly innovative solution for societal problems. RRIL is based on co-creation and open innovation processes giving a prominent role to the learners. The co-creation is conceived as multidisciplinary and transversal among different kinds of actors as HEI, research centres, NGO’s and cities paving the way for knowledge exchange between them. It consists in informed learning among practitioners considering learners as a knowledgeable and critical partners in designing and implementation of the learning means. Under this perspective, the potential learners – programme coordinators and tutors - are considered peers working collaboratively on the project outputs publishedVersion

Responsible research and innovation (RRI), as an integrated concept, is being promoted by the European Union since 2010 and forms part of the Horizon 2020 in the area of science with and for society. RRI is formed by five strategic dimension: public engagement, gender equality, science education, open science and ethics, to which the transversal dimension of governance is added to develop harmonious governance models and institutional strategies. RRIL developed learning courses for three of these dimensions: public engagement, gender equality and ethics, to which we add an introductory course to ReSI. The main objective of the course Ethics in Responsible & Sustainable Innovation. is raising awareness on ethical dimension of conducting research and innovation development, as well as providing inspiration, knowledge and learning tools related to ethical considerations in research and innovation processes. The course introduces the students to various approached applied to ensure societal relevance and ethical acceptability of R&D+I outcomes in the context of business activity, energy research, and urban development. In this understanding, an ethical reflection is closely related to other concepts, such as sustainability, transparency, the precautionary principle, social responsibility of science, impact assessment, or design for values. The course is based on the premise that to ensure social relevance and acceptability of any innovation, its impact should be evaluated at the early stages of the research process, including its possible unintended and unexpected consequences. Monitoring the innovation process could be enabled by sharing authorship and responsibility for the results with relevant social groups (citizens, policymakers, entrepreneurs, educators, etc.) who should be involved in all stages of the process while respecting the principles of gender balance. Therefore, the course stresses the connections between ethical dimension of R&D+I with public engagement and gender perspective, and present them as complementary concepts The course is accessible and open for download and importation to other learning platform (previous registration as teacher) at canvas.instructure.com at: English version: https://lor.instructure.com/resources/eec37eb0a22d49a1bd5139b105f4194b Spanish version: https://lor.instructure.com/resources/a49f57278c9d466baec185c5d5a07348 publishedVersion

La formación permanente desempeña un papel fundamental en las políticas del mercado de trabajo en la UE. En el contexto de la creciente tasa de personas con estudios superiores y de cambios en los mercados de trabajo cualificados, las universidades han empezado a involucrarse en la educación para adultos y en las políticas activas del mercado de trabajo. El artículo presenta los resultados de estudios de casos no representativos de programas universitarios de educación para adultos realizados en siete países europeos con especial atención a las personas de mediana edad, quienes son cada vez más vulnerables socialmente. Uno de los rasgos más destacados de los estudios de casos fue la eficacia social de los programas universitarios de educación para adultos desde el punto de vista del acceso a empleos y de la calidad de trabajo/vida. Los resultados de los estudios de casos junto con el análisis de los resultados de otros proyectos europeos de formación permanente permitieron elaborar un esquema de las dimensiones esenciales de las universidades de educación para adultos socialmente eficaces.

The outcome of the Erasmus+ project Responsible Research and Innovation Learning are learning modules to anchor the concept of Responsible Research and Innovation (RRI). This required to develop a coherent concept of what sustainability and sustainable development is and which is the linkage to RRI. This discussion paper is not a result of an empirical research, but a revision of selected works consulted as policy documents, technical reports, articles and books on sustainability, sustainable development, social sustainability, economic sustainability and environmental and ecological economics. The purpose of this paper was not to provide new evidences, but to clarify basic concepts for the development of a learning programme. Despite the critics, we advocate for the three-pillar model of sustainable development. We take for grounded the validity of ecological sustainability as the main goal to mitigate the Anthropocene Crisis. We focus on the pillars of social and economic sustainability, underpinning that the social pillar, despite the recent efforts, is the less developed. In the area of economic sustainability, there is an important debate which concerns not only sustainability but also basic assumption of conventional economic approaches. In the background stands the question if the focus lies on economy as an integrated part of the system earth or as a system by its own. In the first case, the question is how economic activities contribute to maintain the earth as an ecosystem in which humanity can live. In the second case, the question is how to maintain economy as a value generation system considering the scarcity of natural resources in the frame of sustainable development. In both fields, social and economic sustainability, we observe a distinction between weak and strong sustainability, as two extremes of the societal implications of sustainability policies. The weak social sustainability approach support strategies without substantial change in society as a social system and the lowest political intervention as possible. The strong social sustainability approach assumed that ‘real’ sustainability strategies to contribute to solve the Anthropocene crisis will imply a fundamental transformation of society. Our starting point was that sustainability must be the reference point of RRI due to the Anthropocene crisis. In the conclusion, we argue that RRI should be an integrated part of sustainability as goals reinforcing the social pillar, but also as means to promote a high participation of society in the transformation to a sustainable world, to achieve a high degree of fairness of the transformation and to provide a sustainable ethical framework for science-based social and technological innovations. publishedVersion

Orientador: Prof. Dr. Marcelino Luiz Gimenes Coorientador: Prof. Dr. Sérgio Henrique Bernardo de Faria Dissertação (mestrado em Engenharia Química)--Universidade Estadual de Maringá, Centro de Tecnologia, Dep. de Engenharia Química, 2015 Resumo: Entre todos os processos de separação industriais, a destilação é um dos maiores consumidores de energia. Assim se justifica a busca de métodos de otimização de energia para colunas de destilação. A otimização dos parâmetros tais como estágio de alimentação, razão de refluxo, número de estágios, pode ser obtida da análise do perfil de perdas de exergia da coluna, que por sua vez depende da determinação das propriedades termodinâmicas do conjunto de correntes no interior da coluna. Este trabalho tem por objetivo realizar a otimização exergoeconômica um sistema industrial de colunas de destilação capaz de produzir etanol hidratado, utilizando-se o software Aspen Plus para simulação do sistema em estudo com o método rigoroso Radfrac para resolução das equações MESH das colunas aplicando-se os modelos termodinâmicos apropriados. Os parâmetros de projeto e operação da coluna, já otimizada do ponto de vista energético, são então avaliados e capazes de possibilitar uma otimização econômica para novas condições de operação. Os resultados mostram que foi possível realizar a otimização termodinâmica das colunas de destilação, de forma que as especificações críticas do processo não foram violadas. O processo otimizado perde menos energia que o processo original, porém requer um maior investimento. Tal resultado nos direcionou a investigar se o processo é válido do ponto econômico. A avaliação termoeconômica do processo nos levou a concluir que neste trabalho, mesmo com o aumento do investimento para implantação de um processo de maior eficiência, este é reposto em tempo viável e proporciona uma continua economia de gastos por requerer menos energia Abstract: Among all industrial separation processes, distillation is one of the largest energy consumers. Hence the search for energy optimization methods for distillation columns is justified. The optimization of parameters such as feed stage, reflux ratio, number of stages, can be obtained from analysing the exergy losses profile of the column, which in turn depends on the determination of the thermodynamic properties of the set of streams inside the column. This study aims to realize the exergoeconomic optimization of an industrial system of distillation columns capable of producing hydrated ethanol, using the Aspen Plus software for simulation of the system under study with Radfrac as a rigorous method for solving the MESH equations of the columns applying the appropriate thermodynamic models. The design and operational parameters of the column, already optimized from an energy point of view, are then evaluated and able to allow an economic optimization to new operating conditions. The results show that it was possible to achieve the thermodinamyc optimization of the distillation columns without violating the critical specifications of the process. The optimized process loses less energy than the original process, but requires greater investment. This result directed us to investigate if the process is valid economically. The thermoeconomic evaluation of the process led us to conclude that in this work, even with increased investment to implement a process of greater efficiency, it resets viable in time and provides a continuous cost savings by requiring less energy