187,084 research outputs found

    Digital predictions of complex cylinder packed columns

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    A digital computational approach has been developed to simulate realistic structures of packed beds. The underlying principle of the method is digitisation of the particles and packing space, enabling the generation of realistic structures. Previous publications [Caulkin, R., Fairweather, M., Jia, X., Gopinathan, N., & Williams, R.A. (2006). An investigation of packed columns using a digital packing algorithm. Computers & Chemical Engineering, 30, 1178–1188; Caulkin, R., Ahmad, A., Fairweather, M., Jia, X., & Williams, R. A. (2007). An investigation of sphere packed shell-side columns using a digital packing algorithm. Computers & Chemical Engineering, 31, 1715–1724] have demonstrated the ability of the code in predicting the packing of spheres. For cylindrical particles, however, the original, random walk-based code proved less effective at predicting bed structure. In response to this, the algorithm has been modified to make use of collisions to guide particle movement in a way which does not sacrifice the advantage of simulation speed. Results of both the original and modified code are presented, with bulk and local voidage values compared with data derived by experimental methods. The results demonstrate that collisions and their impact on packing structure cannot be disregarded if realistic packing structures are to be obtained

    Perspectives on Design Considerations Inspired by Security and Quantum Technology in Cyberphysical Systems for Process Engineering

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    Advances in computer science have been a driving force for change in process systems engineering for decades. Faster computers, expanded computing resources, simulation software, and improved optimization algorithms have all changed chemical engineers’ abilities to predict, control, and optimize process systems. Two newer areas relevant to computer science that are impacting process systems engineering are cybersecurity and quantum computing. This work reviews some of our group’s recent work in control-theoretic approaches to control system cybersecurity and touches upon the use of quantum computers, with perspectives on the relationships between process design and control when cybersecurity and quantum technologies are of interest

    Performance limits and trade-offs in entropy-driven biochemical computers

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    The properties and fundamental limits of chemical computers have recently attracted significant interest as a model of computation, an unifying principle of cellular organisation and in the context of bio-engineering. As of yet, research in this topic is based on case-studies. There exists no generally accepted criterion to distinguish between chemical processes that compute and those that do not. Here, the concept of entropy driven computer (EDC) is proposed as a general model of chemical computation. It is found that entropy driven computation is subject to a trade-off between accuracy and entropy production, but unlike many biological systems, there are no trade-offs involving time. The latter only arise when it is taken into account that the observation of the state of the EDC is not energy neutral, but comes at a cost. The significance of this conclusion in relation to biological systems is discussed. Three examples of biological computers, including an implementation of a neural network as an EDC are given

    Modeling and simulation in engineering sciences

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    This book features state-of-the-art contributions in mathematical, experimental and numerical simulations in engineering sciences. The contributions in this book, which comprise twelve chapters, are organized in six sections spanning mechanical, aerospace, electrical, electronic, computer, materials, geotechnical and chemical engineering. Topics include metal micro-forming, compressible reactive flows, radio frequency circuits, barrier infrared detectors, fiber Bragg and long-period fiber gratings, semiconductor modelling, many-core architecture computers, laser processing of materials, alloy phase decomposition, nanofluids, geo-materials and rheo-kinetics. Contributors are from Europe, China, Mexico, Malaysia and Iran. The chapters feature many sophisticated approaches including Monte Carlo simulation, FLUENT and ABAQUS computational modelling, discrete element modelling and partitioned frequency-time methods. The book will be of interest to researchers and also consultants engaged in many areas of engineering simulation

    Micro-computer applications in environmental engineering

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    Micro-computers can have wide applications for simulating many processes in environmental engineering. Micro-computers can have potential applications in environmental engineering for (i) selection of the best optimized water distribution network models, (ii) selection of the best optimized sewerage network models, (iii) forecasting of chemical water quality variables in surface water and (iv) modeling of contaminant transport into groundwater.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/26900/1/0000466.pd

    Computational analysis of transitional airflow through packed columns of spheres using the finite volume technique

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    Copyright © 2010 Elsevier. NOTICE: this is the author’s version of a work that was accepted for publication in Computers and Chemical Engineering. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computers and Chemical Engineering, Volume 34 Issue 6 (2010), DOI: 10.1016/j.compchemeng.2009.10.013We compare computational simulations of the flow of air through a packed column containing spherical particles with experimental and theoretical results for equivalent beds. The column contained 160 spherical particles at an aspect ratio N=7.14N=7.14, and the experiments and simulations were carried out at particle Reynolds numbers of (RedP=700−5000)(RedP=700−5000). Experimental measurements were taken of the pressure drop across the column and compared with the correlation of Reichelt (1972) using the fitted coefficients of Eisfeld and Schnitzlein (2001). An equivalent computational domain was prepared using Monte Carlo packing, from which computational meshes were generated and analysed in detail. Computational fluid dynamics calculations of the air flow through the simulated bed was then performed using the finite volume technique. Results for pressure drop across the column were found to correlate strongly with the experimental data and the literature correlation. The flow structure through the bed was also analysed in detail

    A Chemical Engineering Laboratory over Distributed Control and Measurement Systems

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    Remote Control of Lab Apparatus Via the Internet Allows Flexible Scheduling of Experiments and Exercises. This Paper Presents a Novel Application of Computers and Internet Technology in Chemical Engineering Education that Highlights Interactive Learning for an Undergraduate Course in Online Measurement and Control. the Proposed Client-Server Architecture Can Be Adapted to Drive Different Kinds of Devices and Can Be Easily Expanded. the Developed Online Laboratory Has Been Tested by Many Students using Different Connections and Operating Conditions. This Internet-Based Solution Can Improve Undergraduate Engineering Education in a Conventional Unit Operation Laboratory. as an Example, the Application of Remote Experiments to Characterize a Plug Flow Reactor is Described. © 2007 Wiley Periodicals Inc

    AI and OR in management of operations: history and trends

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    The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested
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