964 resultados para Computational Simulation


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Process modelling is an integral part of any process industry. Several sugar factory models have been developed over the years to simulate the unit operations. An enhanced and comprehensive milling process simulation model has been developed to analyse the performance of the milling train and to assess the impact of changes and advanced control options for improved operational efficiency. The developed model is incorporated in a proprietary software package ‘SysCAD’. As an example, the milling process model has been used to predict a significant loss of extraction by returning the cush from the juice screen before #3 mill instead of before #2 mill as is more commonly done. Further work is being undertaken to more accurately model extraction processes in a milling train, to examine extraction issues dynamically and to integrate the model into a whole factory model.

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This paper proposes a simulation-based density estimation technique for time series that exploits information found in covariate data. The method can be paired with a large range of parametric models used in time series estimation. We derive asymptotic properties of the estimator and illustrate attractive finite sample properties for a range of well-known econometric and financial applications.

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This experiment examined whether trait regulatory focus moderates the effects of task control on stress reactions during a demanding work simulation. Regulatory focus describes two ways in which individuals self-regulate toward desired goals: promotion and prevention. As highly promotion-focused individuals are oriented toward growth and challenge, it was expected that they would show better adaptation to demanding work under high task control. In contrast, as highly prevention-focused individuals are oriented toward safety and responsibility they were expected to show better adaptation under low task control. Participants (N = 110) completed a measure of trait regulatory focus and then three trials of a demanding inbox activity under either low, neutral, or high task control. Heart rate variability (HRV), affective reactions (anxiety & task dissatisfaction), and task performance were measured at each trial. As predicted, highly promotion-focused individuals found high (compared to neutral) task control stress-buffering for performance. Moreover, highly prevention-focused individuals found high (compared to low) task control stress-exacerbating for dissatisfaction. In addition, highly prevention-focused individuals found low task control stress-buffering for dissatisfaction, performance, and HRV. However, these effects of low task control for highly prevention-focused individuals depended on their promotion focus.

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Designed for undergraduate and postgraduate students, academic researchers and industrial practitioners, this book provides comprehensive case studies on numerical computing of industrial processes and step-by-step procedures for conducting industrial computing. It assumes minimal knowledge in numerical computing and computer programming, making it easy to read, understand and follow. Topics discussed include fundamentals of industrial computing, finite difference methods, the Wavelet-Collocation Method, the Wavelet-Galerkin Method, High Resolution Methods, and comparative studies of various methods. These are discussed using examples of carefully selected models from real processes of industrial significance. The step-by-step procedures in all these case studies can be easily applied to other industrial processes without a need for major changes and thus provide readers with useful frameworks for the applications of engineering computing in fundamental research problems and practical development scenarios.

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Carbon nanoscrolls (CNSs) are one of the carbon-based nanomaterials similar to carbon nanotubes (CNTs) but are not widely studied in spite of their great potential applications. Their practical applications are hindered by the challenging fabrication of the CNSs. A physical approach has been proposed recently to fabricate the CNS by rolling up a monolayer graphene nanoribbon (GNR) around a CNT driven by the interaction energy between them. In this study, we perform extensive molecular dynamics (MD) simulations to investigate the various factors that impact the formation of the CNS from GNR. Our simulation results show that the formation of the CNS is sensitive to the length of the CNT and temperature. When the GNR is functionalized with hydrogen, the formation of the CNS is determined by the density and distribution of the hydrogen atoms. Graphyne, the allotrope of graphene, is inferior to graphene in the formation of the CNS due to the weaker bonds and the associated smaller atom density. The mechanism behind the rolling of GNR into CNS lies in the balance between the GNR–CNT van der Waals (vdW) interactions and the strain energy of GNR. The present work reveals new important insights and provides useful guidelines for the fabrication of the CNS.

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The impact of simulation methods for social research in the Information Systems (IS) research field remains low. A concern is our field is inadequately leveraging the unique strengths of simulation methods. Although this low impact is frequently attributed to methodological complexity, we offer an alternative explanation – the poor construction of research value. We argue a more intuitive value construction, better connected to the knowledge base, will facilitate increased value and broader appreciation. Meta-analysis of studies published in IS journals over the last decade evidences the low impact. To facilitate value construction, we synthesize four common types of simulation research contribution: Analyzer, Tester, Descriptor, and Theorizer. To illustrate, we employ the proposed typology to describe how each type of value is structured in simulation research and connect each type to instances from IS literature, thereby making these value types and their construction visible and readily accessible to the general IS community.

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In this chapter, we draw out the relevant themes from a range of critical scholarship from the small body of digital media and software studies work that has focused on the politics of Twitter data and the sociotechnical means by which access is regulated. We highlight in particular the contested relationships between social media research (in both academic and non-academic contexts) and the data wholesale, retail, and analytics industries that feed on them. In the second major section of the chapter we discuss in detail the pragmatic edge of these politics in terms of what kinds of scientific research is and is not possible in the current political economy of Twitter data access. Finally, at the end of the chapter we return to the much broader implications of these issues for the politics of knowledge, demonstrating how the apparently microscopic level of how the Twitter API mediates access to Twitter data actually inscribes and influences the macro level of the global political economy of science itself, through re-inscribing institutional and traditional disciplinary privilege We conclude with some speculations about future developments in data rights and data philanthropy that may at least mitigate some of these negative impacts.

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Computational epigenetics is a new area of research focused on exploring how DNA methylation patterns affect transcription factor binding that affect gene expression patterns. The aim of this study was to produce a new protocol for the detection of DNA methylation patterns using computational analysis which can be further confirmed by bisulfite PCR with serial pyrosequencing. The upstream regulatory element and pre-initiation complex relative to CpG islets within the methylenetetrahydrofolate reductase gene were determined via computational analysis and online databases. The 1,104 bp long CpG island located near to or at the alternative promoter site of methylenetetrahydrofolate reductase gene was identified. The CpG plot indicated that CpG islets A and B, within the island, contained 62 and 75 % GC content CpG ratios of 0.70 and 0.80–0.95, respectively. Further exploration of the CpG islets A and B indicates that the transcription start sites were GGC which were absent from the TATA boxes. In addition, although six PROSITE motifs were identified in CpG B, no motifs were detected in CpG A. A number of cis-regulatory elements were found in different regions within the CpGs A and B. Transcription factors were predicted to bind to CpGs A and B with varying affinities depending on the DNA methylation status. In addition, transcription factor binding may influence the expression patterns of the methylenetetrahydrofolate reductase gene by recruiting chromatin condensation inducing factors. These results have significant implications for the understanding of the architecture of transcription factor binding at CpG islets as well as DNA methylation patterns that affect chromatin structure.

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Red blood cells (RBCs) are the most common type of cells in human blood and they exhibit different types of motions and deformed shapes in capillary flows. The behaviour of the RBCs should be studied in order to explain the RBC motion and deformation mechanism. This article presents a numerical simulation method for RBC deformation in microvessels. A two dimensional spring network model is used to represent the RBC membrane, where the elastic stretch/compression energy and the bending energy are considered with the constraint of constant RBC surface area. The forces acting on the RBC membrane are obtained from the principle of virtual work. The whole fluid domain is discretized into a finite number of particles using smoothed particle hydrodynamics concepts and the motions of all the particles are solved using Navier--Stokes equations. Minimum energy concepts are used to simulate the deformed shape of the RBC model. To verify the model, the motion of a single RBC is simulated in a Poiseuille flow and the characteristic parachute shape of the RBC is observed. Further simulations reveal that the RBC shows a tank treading motion when it flows in a linear shear flow.

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Carbon fibre reinforced polymer (CFRP) strengthening of metallic structures under static loading has shown great potential in the recent years. However, steel structures are often experienced natural (e.g. earthquake, wind) as well as man-made (e.g. vehicular impact, blast) dynamic loading. Therefore, there is a growing interest among the researchers to investigate the capability of CFRP strengthened members under such dynamic conditions. This study focuses on the finite element (FE) numerical modelling and simulation of CFRP strengthened steel column under transverse impact loading to predict the behaviour and failure modes. Impact simulation process and the CFRP strengthened steel column are validated with the existing experimental results in literature. The validated FE model of CFRP strengthened steel column is then further used to investigate the effects of transverse impact loading on its structural performance. The results are presented in terms of transvers e impact force, lateral and axial displacement, and deformed shape to evaluate the effectiveness of CFRP strengthening technique. Comparisons between the bare steel and CFRP strengthened steel columns clearly indicate the performance enhancement of strengthened column under transverse impact loading.

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Electric distribution networks are now in the era of transition from passive to active distribution networks with the integration of energy storage devices. Optimal usage of batteries and voltage control devices along with other upgrades in network needs a distribution expansion planning (DEP) considering inter-temporal dependencies of stages. This paper presents an efficient approach for solving multi-stage distribution expansion planning problems (MSDEPP) based on a forward-backward approach considering energy storage devices such as batteries and voltage control devices such as voltage regulators and capacitors. The proposed algorithm is compared with three other techniques including full dynamic, forward fill-in, backward pull-out from the point of view of their precision and their computational efficiency. The simulation results for the IEEE 13 bus network show the proposed pseudo-dynamic forward-backward approach presents good efficiency in precision and time of optimization.

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A virtual power system can be interfaced with a physical system to form a power hardware-in-the-loop (PHIL) simulation. In this scheme, the virtual system can be simulated in a fast parallel processor to provide near real-time outputs, which then can be interfaced to a physical hardware that is called the hardware under test (HuT). Stable operation of the entire system, while maintaining acceptable accuracy, is the main challenge of a PHIL simulation. In this paper, after an extended stability analysis for voltage and current type interfaces, some guidelines are provided to have a stable PHIL simulation. The presented analysis have been evaluated by performing several experimental tests using a Real Time Digital Simulator (RTDS™) and a voltage source converter (VSC). The practical test results are consistent with the proposed analysis.