1,720,986 research outputs found
Robust optimisation of the streamlined shape of a high-speed train in crosswind conditions
No full textTraditional deterministic aerodynamic optimisation cannot consider environmental uncertainty, which may lead to sensitivity issues. The present study proposes a robust design framework for the aerodynamic optimisation of high-speed trains, which accounts for the uncertain wind and its impact on crosswind stability. In this framework, a variance analysis method based on the Non-Intrusive Polynomial Chaos is proposed to determine the deformation area, and a parametric model is subsequently established. The Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is used as the optimiser to minimise the mean and variance of the aerodynamic response. The mean and variance can be quickly predicted by an uncertainty analysis approach combining Monte Carlo simulation and Kriging model. The framework is then applied to the optimisation of a high-speed train under crosswind. The results of the robust optimisation are compared with those of the baseline geometry and deterministic optimisation. The mean and variance of the rolling moment under crosswind are reduced by 2.26% and 3.37% respectively after optimisation, indicating that the performance and robustness are both improved. The proposed framework is effective for the engineering design of high-speed trains and can also provide a reference for the robust design of other aerodynamic shapes
On the nature of the lightest scalar resonances
No full textWe briefly review the recent progresses in the new unitarization approach being developed by us. Especially we discuss the large N-c pi pi scatterings by making use of the partial wave S matrix parametrization form. We find that the a pole may move to the negative real axis on the second sheet of the complex s plane, therefore it raises the interesting question that this 'sigma' pole may be related to the sigma in the linear sigma model.Physics, NuclearCPCI-S(ISTP)
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
PARAMETRIZATION OF HIGH-SPEED TRAIN STREAMLINE SHAPE
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In the past decade, the high speed trains (HSTs) in China have experienced a booming development, with the design of CRH380A as a predominant example. A series of brand new HSTs have been developed with high aerodynamic performance, which includes the running resistance, the lift of the trailing car, pressure waves when trains pass by each other, aerodynamic noise in the far field, etc. In order to design HSTs with better aerodynamic performance, it is necessary to perform aerodynamic shape optimization, especially to optimize the streamline shape of HSTs. Parametrization is the basis for the whole optimization process, since good parametrization approach not only affects the optimization strategy, but also determines the design space and optimization efficiency. In the present paper, a series of work related to the streamline shape parametrization performed by the author in recent years have been introduced. Four different parametrization approaches have been exhibited, which are Local Shape Function method (LSF) and Free-Foam Deformation method (FFD), Modified Vehicle Modeling Function method (MVMF), Class function/Shape function Transformation method (CST). These methods could be categorized into two kinds: shape disturbance approach (LSF and FFD) and shape description approach (MVMF and CST). Among these four methods, some are developed by the authors while some are locally modified so as to meet the parametrization of the streamline shape. The detailed process of these four approaches are exhibited in the present paper and the characteristics of these four approaches are compared.</p
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Exploring hidden flow structures from sparse data through deep learning strengthened proper orthogonal decomposition
No full textProper orthogonal decomposition (POD) enables complex flow fields to be decomposed into linear modes according to their energy, allowing the key features of the flow to be extracted. However, traditional POD requires high quality inputs, namely, high resolution spatiotemporal data. To alleviate the dependence of traditional POD on the quality and quantity of data, this paper presents a POD method that is strengthened by a physics informed neural network (PINN) with an overlapping domain decomposition strategy. The loss function and convergence of modes are considered simultaneously to determine the convergence of the PINN POD model. The proposed framework is applied to the flow past a two dimensional circular cylinder at Reynolds numbers ranging from 100 to 10 000 and achieves accurate and robust extraction of flow structures from spatially sparse observation data. The spatial structures and dominant frequency can also be extracted under high level noise. These results demonstrate that the proposed PINN POD method is a reliable tool for extracting the key features from sparse observation data of flow fields, potentially shedding light on the data driven discovery of hidden fluid dynamics
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