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.

Building intuition of iron evolution during solar cell processing through analysis of different process models

An important aspect of Process Simulators for photovoltaics is prediction of defect evolution during device fabrication. Over the last twenty years, these tools have accelerated process optimization, and several Process Simulators for iron, a ubiquitous and deleterious impurity in silicon, have been developed. The diversity of these tools can make it difficult to build intuition about the physics governing iron behavior during processing. Thus, in one unified software environment and using self-consistent terminology, we combine and describe three of these Simulators. We vary structural defect distribution and iron precipitation equations to create eight distinct Models, which we then use to simulate different stages of processing. We find that the structural defect distribution influences the final interstitial iron concentration ([Fe-i]) more strongly than the iron precipitation equations. We identify two regimes of iron behavior: (1) diffusivity-limited, in which iron evolution is kinetically limited and bulk [Fe-i] predictions can vary by an order of magnitude or more, and (2) solubility-limited, in which iron evolution is near thermodynamic equilibrium and the Models yield similar results. This rigorous analysis provides new intuition that can inform Process Simulation, material, and process development, and it enables scientists and engineers to choose an appropriate level of Model complexity based on wafer type and quality, processing conditions, and available computation time.

Large scale optimization of a sour water stripping plant using surrogate models

In this work, we propose a new methodology for the large scale optimization and process integration of complex chemical processes that have been simulated using modular chemical process simulators. Units with significant numerical noise or large CPU times are substituted by surrogate models based on Kriging interpolation. Using a degree of freedom analysis, some of those units can be aggregated into a single unit to reduce the complexity of the resulting model. As a result, we solve a hybrid simulation-optimization model formed by units in the original flowsheet, Kriging models, and explicit equations. We present a case study of the optimization of a sour water stripping plant in which we simultaneously consider economics, heat integration and environmental impact using the ReCiPe indicator, which incorporates the recent advances made in Life Cycle Assessment (LCA). The optimization strategy guarantees the convergence to a local optimum inside the tolerance of the numerical noise.

Experiences on dynamic simulation software in chemical engineering education

Commercial process simulators are increasing interest in the chemical engineer education. In this paper, the use of commercial dynamic simulation software, D-SPICE® and K-Spice®, for three different chemical engineering courses is described and discussed. The courses cover the following topics: basic chemical engineering, operability and safety analysis and process control. User experiences from both teachers and students are presented. The benefits of dynamic simulation as an additional teaching tool are discussed and summarized. The experiences confirm that commercial dynamic simulators provide realistic training and can be successfully integrated into undergraduate and graduate teaching, laboratory courses and research. © 2012 The Institution of Chemical Engineers.

Análisis de las simulaciones del proceso de deshidratación del gas natural con Aspen Hysys y Aspen Plus

El gas natural ha tomado un rol estratégico importante en el suministro de energía a nivel mundial como consecuencia de la creciente demanda global de energía. El agua es probablemente el componente indeseable más común en el gas natural no tratado ya que su presencia puede ocasionar la formación de hidratos y problemas de corrosión. Debido a las potenciales consecuencias costosas, el gas debe ser sometido a procesos de acondicionamiento a fin de alcanzar las especificaciones requeridas para su venta, transporte hacia los centros de distribución y consumo final. En los últimos años, la simulación de procesos está jugando un papel muy importante en la industria del gas y petróleo como una herramienta adecuada y oportuna para el diseño, caracterización, optimización y monitoreo del funcionamiento de procesos industriales. En el presente trabajo se describe el desarrollo de dos simulaciones estacionarias del proceso de deshidratación de gas natural por absorción con trietilenglicol (TEG), empleando los simuladores comerciales de procesos Aspen HYSYS V8.3 y Aspen PLUS V8.2. La composición del gas natural, la configuración del proceso y las condiciones de operación empleadas en los cálculos y la simulación son típicas de los yacimientos y plantas de acondicionamiento de la provincia de Salta (Argentina).

Dynamic data reconciliation for sequential modular simulators: application to a mixing process

This paper describes a method for dynamic data reconciliation of nonlinear systems that are simulated using the sequential modular approach, and where individual modules are represented by a class of differential algebraic equations. The estimation technique consists of a bank of extended Kalman filters that are integrated with the modules. The paper reports a study based on experimental data obtained from a pilot scale mixing process.

USER'S GUIDE FOR ADVANCED PROCESS SIMULATION SOFTWARE APROS 5

Tässä diplomityössä tehtiin käyttäjän opas kehittyneelle prosessisimulointiohjelmistolle APROS 5. Opas on osa VTT Energialle tehtävää APROS 5 käyttäjän koulutuspakettia, joka julkaistaan myöhemmin CD-ROM -muotoisena. Prosessisimulointiohjelmistoa AAPROS 5 voidaan käyttää termohydraulisten prosessien, automaatiopiirien ja sähköjärjestelmien mallinnuksessa. Ohjelma sisältää myös neutroniikkamallin ydinreaktorin käyttäytymisen mallintamiseksi. APROS:in aikaisemmilla UNIX-ympäristössä toimivilla versioilla on toteutettu useita ydinvoimalaitosten turvallisuustutkimukseen liittyviä analyysejä ja sekä ydinvoimalaitosten että konventionaalisten voimalaitosten koulutussimulaattoreita. APROS 5 toimii Windows NT -ympäristössä ja on oleellisesti erilainen käyttää kuin aikaisemmat versiot. Tämän myötä syntyi tarve uudelle käyttäjän oppaalle. Käyttäjän oppaassa esitetään APROS 5:n tärkeimmät toiminnot, mallinnuksen periaatteet ja termohydraulisten ja neutroniikan ratkaisumallit. Lisäksi oppaassa esitetään esimerkki, jossa mallinnetaan yksinkertaistettu VVER-440 -tyyppisen ydinvoimalaitoksen primääripiiri. Yksityiskohtaisempaa tietoa ohjelmistosta on saatavilla APROS 5 -dokumentaatiosta.

An Experimental Multimedia Process Control Room

The centralised control rooms of large industrial plants have separated people from the processes they should control. Perception is restricted mainly to the visual sense. Only telephone or radio links provide narrow-band voice communication with maintenance personnel down in the plant. Multimedia equipment can perceptionally bring back the operator into the plant while bodily keeping him the comfortable and safe control room. This involves video and audio transmission from process components as well as sights and sounds artificially generated from measurements. Groupware systems support inter-action between operators, engineers, and managers in different plants. With support from the German government, the state of Hessen, and industrial companies the Laboratory for Systems Engineering and Human-Machine Systems at the University of Kassel establishes an Experimental Multimedia Process Control Room. Core of this set-up are two high-performance graphics workstations linked to one of several process or vehicle simulators. Multimedia periphery includes video and teleconferencing equipment and a vibration and sound generation system.

Dynamic data reconciliation for sequential modular simulators

In this paper the implementation of dynamic data reconciliation techniques for sequential modular models is described. The paper is organised as follows. First, an introduction to dynamic data reconciliation is given. Then, the online use of rigorous process models is introduced. The sequential modular approach to dynamic simulation is briefly discussed followed by a short review of the extended Kalman filter. The second section describes how the modules are implemented. A simulation case study and its results are also presented.

Interactive Graphic Simulation: An Advanced Methodology to Improve the Teaching-Learning Process in Nuclear Engineering Education and Training

Nowadays, computer simulators are becoming basic tools for education and training in many engineering fields. In the nuclear industry, the role of simulation for training of operators of nuclear power plants is also recognized of the utmost relevance. As an example, the International Atomic Energy Agency sponsors the development of nuclear reactor simulators for education, and arranges the supply of such simulation programs. Aware of this, in 2008 Gas Natural Fenosa, a Spanish gas and electric utility that owns and operate nuclear power plants and promotes university education in the nuclear technology field, provided the Department of Nuclear Engineering of Universidad Politécnica de Madrid with the Interactive Graphic Simulator (IGS) of “José Cabrera” (Zorita) nuclear power plant, an industrial facility whose commercial operation ceased definitively in April 2006. It is a state-of-the-art full-scope real-time simulator that was used for training and qualification of the operators of the plant control room, as well as to understand and analyses the plant dynamics, and to develop, qualify and validate its emergency operating procedures.

Emulation of random output simulators

Computer models, or simulators, are widely used in a range of scientific fields to aid understanding of the processes involved and make predictions. Such simulators are often computationally demanding and are thus not amenable to statistical analysis. Emulators provide a statistical approximation, or surrogate, for the simulators accounting for the additional approximation uncertainty. This thesis develops a novel sequential screening method to reduce the set of simulator variables considered during emulation. This screening method is shown to require fewer simulator evaluations than existing approaches. Utilising the lower dimensional active variable set simplifies subsequent emulation analysis. For random output, or stochastic, simulators the output dispersion, and thus variance, is typically a function of the inputs. This work extends the emulator framework to account for such heteroscedasticity by constructing two new heteroscedastic Gaussian process representations and proposes an experimental design technique to optimally learn the model parameters. The design criterion is an extension of Fisher information to heteroscedastic variance models. Replicated observations are efficiently handled in both the design and model inference stages. Through a series of simulation experiments on both synthetic and real world simulators, the emulators inferred on optimal designs with replicated observations are shown to outperform equivalent models inferred on space-filling replicate-free designs in terms of both model parameter uncertainty and predictive variance.

[meanings Of The Sickening Process For Patients With Systemic Lupus Erythematosus: A Review Of The Literature.]

Systemic lupus erythematosus is an autoimmune disease that causes many psychological repercussions that have been studied through qualitative research. These are considered relevant, since they reveal the amplitude experienced by patients. Given this importance, this study aims to map the qualitative production in this theme, derived from studies of experiences of adult patients of both genders and that had used as a tool a semi-structured interview and/or field observations, and had made use of a sampling by a saturation criterion to determine the number of participants in each study. The survey was conducted in Pubmed, Lilacs, Psycinfo e Cochrane databases, searching productions in English and Portuguese idioms published between January 2005 and June 2012. The 19 revised papers that have dealt with patients in the acute phase of the disease showed themes that were categorized into eight topics that contemplated the experienced process at various stages, from the onset of the disease, extending through the knowledge of the diagnosis and the understanding of the manifestations of the disease, drug treatment and general care, evolution and prognosis. The collected papers also point to the difficulty of understanding, of the patients, on what consists the remission phase, revealing also that this is a clinical stage underexplored by psychological studies.

[in Process Citation].

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O aluno com deficiência visual nas aulas de educação física : análise do processo inclusivo = The student with visual impairments : analysis of inclusive process

Universidade Estadual de Campinas . Faculdade de Educação Física