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23 European Symposium On Computer Aided Process Engineering

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23rd European Symposium on Computer Aided Process Engineering

23rd European Symposium on Computer Aided Process Engineering Book
Author : Anonim
Publisher : Elsevier
Release : 2013-06-10
ISBN : 0444632417
File Size : 39,5 Mb
Language : En, Es, Fr and De

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Book Summary :

Computer-aided process engineering (CAPE) plays a key design and operations role in the process industries, from the molecular scale through managing complex manufacturing sites. The research interests cover a wide range of interdisciplinary problems related to the current needs of society and industry. ESCAPE 23 brings together researchers and practitioners of computer-aided process engineering interested in modeling, simulation and optimization, synthesis and design, automation and control, and education. The proceedings present and evaluate emerging as well as established research methods and concepts, as well as industrial case studies. Contributions from the international community using computer-based methods in process engineering Reviews the latest developments in process systems engineering Emphasis on industrial and societal challenges

23 European Symposium on Computer Aided Process Engineering

23 European Symposium on Computer Aided Process Engineering Book
Author : N. Meneghetti,E. Tomba,P. Facco,F. Lince,D.L. Marchisio,A.A. Barresi,F. Bezzo,M. Barolo
Publisher : Elsevier Inc. Chapters
Release : 2013-06-10
ISBN : 0128085843
File Size : 45,8 Mb
Language : En, Es, Fr and De

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Book Summary :

Product transfer is a problem commonly encountered in industry when a production has to be transferred from a source plant to a target plant. In this paper a strategy to assist product transfer is proposed. The strategy is based on latent variable models (LVMs) to relate the data available from one or more source plants with the (usually scarce) data available from the target plant, and on LVM inversion to estimate the target plant operating conditions. The inversion is performed within an optimization framework, which can handle constraints for both product quality variables and input variables. An experimental nanoparticle production process is used as a test bed to illustrate the benefits of the proposed strategy.

23 European Symposium on Computer Aided Process Engineering

23 European Symposium on Computer Aided Process Engineering Book
Author : Franco M. Novara,Juan M. Novas,Gabriela P. Henning
Publisher : Elsevier Inc. Chapters
Release : 2013-06-10
ISBN : 0128085975
File Size : 53,6 Mb
Language : En, Es, Fr and De

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Book Summary :

This work presents a novel, efficient and expressive Constraint Programming (CP) approach to the short-term scheduling problem of multistage batch plants. The CP model accounts for many features found in industrial settings and allows modeling operational policies that group batches of the same product into campaigns. Product campaigns simplify the plant operation and allow reducing scrap and changeover times. The formulation has been extensively tested with various examples, including large-scale ones, and different objective functions. Comparisons with results reported in recent contributions are also presented and discussed.

23 European Symposium on Computer Aided Process Engineering

23 European Symposium on Computer Aided Process Engineering Book
Author : Laurence Tock,François Maréchal
Publisher : Elsevier Inc. Chapters
Release : 2013-06-10
ISBN : 0128085606
File Size : 41,5 Mb
Language : En, Es, Fr and De

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Book Summary :

In the context of greenhouse gas emissions mitigation, CO2 capture and storage is regarded as a promising alternative for fossil fuel fed power plants. In order to design and evaluate the competitiveness of such complex integrated energy conversion systems, a systematic comparison including thermodynamic, economic and environmental considerations is necessary. From a process engineering perspective, it is important to evaluate the impact of CO2 capture not only on the efficiency but also on the costs and on the environmental impacts, and to assess the trade-offs. This paper presents the development of a systematic thermo-environomic optimisation strategy for the consistent modelling, comparison and optimisation of fuel decarbonisation options. In particular, it is highlighted how the economic scenario influences the competitiveness and hence the optimal process design.

23 European Symposium on Computer Aided Process Engineering

23 European Symposium on Computer Aided Process Engineering Book
Author : Jian-Guo Wang,Jia-Lin Kang,Shyan-Shu Shieh,Shi-Shang Jang,David Shan-Hill Wong
Publisher : Elsevier Inc. Chapters
Release : 2013-06-10
ISBN : 0128085436
File Size : 36,9 Mb
Language : En, Es, Fr and De

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Book Summary :

The plant input variables are transformed into the derived variables, which are physically and statistically meaningful for modeling. Then, this study proposed an adaptive modeling approach by employing nonnegative garrote variable selection and auto-regression integrated moving average correction. The high accuracy of the proposed modeling approaches makes the implementation of the model-based control of ratio of air to fuel for improving boiler's efficiency readily practicable.

23 European Symposium on Computer Aided Process Engineering

23 European Symposium on Computer Aided Process Engineering Book
Author : Marina Fedorova,Gurkan Sin,Rafiqul Gani
Publisher : Elsevier Inc. Chapters
Release : 2013-06-10
ISBN : 0128086289
File Size : 30,5 Mb
Language : En, Es, Fr and De

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Book Summary :

This work focuses on the development of a computer-aided modeling framework. The framework is a knowledge-based system that is built on a generic modeling language and structured on workflows for different modeling tasks. The overall objective of this work is to support model developers and users to generate and test models systematically, efficiently and reliably. In this way, development of products and processes can be made faster, cheaper and more efficient. In this contribution, as part of the framework a generic modeling template for the systematic derivation of problem specific catalytic membrane fixed bed reactor models is presented. The application of the modeling template is highlighted with a case study related to the modeling of a catalytic membrane reactor coupling dehydrogenation of ethylbenzene with hydrogenation of nitrobenzene.

23 European Symposium on Computer Aided Process Engineering

23 European Symposium on Computer Aided Process Engineering Book
Author : Yuan-Jui Liu,Tao Chen,Yuan Yao
Publisher : Elsevier Inc. Chapters
Release : 2013-06-10
ISBN : 012808667X
File Size : 53,5 Mb
Language : En, Es, Fr and De

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Book Summary :

In order to monitor nonlinear processes, kernel principal component analysis (KPCA) has become a popular technique. Nevertheless, KPCA suffers from two major disadvantages. First, the underlying manifold structure of data is not considered in process modeling. Second, the selection of kernel function and kernel parameters is always problematic. To avoid such deficiencies, an integrating method of manifolding learning and Gaussian process is proposed in this paper, which extends the utilization of maximum variance unfolding (MVU) to online process monitoring and fault isolation. The proposed method is named as extendable MVU (EMVU), whose effectiveness is verified by the case studies on the benchmark Tennessee Eastman (TE) process.

23 European Symposium on Computer Aided Process Engineering

23 European Symposium on Computer Aided Process Engineering Book
Author : Jialin Liu,Shu Jie Liu,David Shan Hill Wong
Publisher : Elsevier Inc. Chapters
Release : 2013-06-10
ISBN : 0128086246
File Size : 44,9 Mb
Language : En, Es, Fr and De

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Book Summary :

Isolating faulty variables is a crucial step during the determination of the root causes of a process fault. Contribution plots, with their corresponding control limits, are the most popular tools used for isolating faulty variables. However, the isolation results may be misled by the smearing effect. In addition, the control limits of the contributions cannot be used to isolate faulty variables, since the control limits are obtained from the normal operating data, which lack any information about the faults. In chemical processes, process faults rarely show a random behavior; on the contrary, they will be propagated to varying variables due to the actions of the process controllers. During the evolution of a fault, the task of isolating faulty variables needs to be concerned with the faulty variables decided in the previous data; in addition, the current decisions should influence the isolation results for the next sample when the fault is constantly occurring. In the presented work, an unsupervised data-driven fault isolation method was developed based on Bayesian decision theory. The Tennessee Eastman (TE) process was used as a benchmark example to demonstrate how the different faulty variables were isolated when the fault was evolving.