1,720,994 research outputs found
Highly efficient fe simulations by means of simplified corotational formulation
Full text linkFinite Element Method (FEM) has deservedly gained the reputation of the most powerful numerical method in the field of structural analysis. It offers tools to perform various kinds of simulations in this field, ranging from static linear to nonlinear dynamic analyses. In recent years, a particular challenge is development of FE formulations that enable highly efficient simulations, aiming at real-time dynamic simulations as a final objective while keeping high simulation fidelity such as nonlinear effects. The authors of this paper propose a simplified corotational FE formulation as a possible solution to this challenge. The basic idea is to keep the linear behavior of each element in the FE assemblage, but to extract the rigid-body motion on the element level and include it in the formulation to cover geometric nonlinearities. This paper elaborates the idea and demonstrates it on static cases with three different finite element types. The objective is to check the achievable accuracy based on such a simplified geometrically nonlinear FE formulation. In the considered examples, the difference between the results obtained with the present formulation and those by rigorous formulations is less than 3% although fairly large deformations are induced
A new method for complexity determination by using fractals and its applications in material surface characteristics
Full text linkIn this article, a new method for complexity determination by using fractals in combination with an artificial intelligent approach is proposed and its application in laser hardening technology is detailed. In particular, nanoindentation tests were applied as a way to investigate the hardness properties of tool steel alloys with respect to both marginal and relevant changes in laser hardening parameters. Specifically, process duration and temperature were considered, together with nanoindentation, later related to surface characteristics by image analysis and Hurst exponent determination. Three different Machine Learning algorithms (Random Forest, Support Vector Machine and k-Nearest Neighbors) were used and predictions compared with measures in terms of mean, variability and linear correlation. Evidences confirmed the general applicability of this method, based on integrating fractals for microstructure analysis and machine learning for their deep understanding, in material science and process engineering
Modelling the Surface Roughness of Steel after Laser hardening by using 2D Visibility Network, Convolutional neural Networks and Genetic Programming
Full text linkThe surface characterization of materials after Robot Laser Hardening (RLH) is a technically demanding procedure. RLH is commonly used to harden parts, especially when subject to wear. By changing their surface properties, this treatment can offer several benefits such as lower costs for additional machining, no use of cooling agents or chemicals, high flexibility, local hardening, minimal deformation, high accuracy, and automated and integrated process in the production process. However, the surface roughness strongly depends on the heat treatment and parameters used in the process. This article used a network theory approach (i.e., the visibility network in 2D space) to analyze the surface roughness of tool steel EN100083-1 upon RLH. Specifically, two intelligent methods were merged in this investigation. Firstly, a genetic algorithm was applied to derive a relationship between the parameters of the robot laser cell and topological surface properties. Furthermore, convolutional neural networks allowed the assessment of surface roughness based on 2D photographic image
A practical guideline in the design and use of woodworking tools
Full text linkCircular saw blades, either with carbide or diamond inserts, are customarily embedded in wood working machines once they permit a precise and efficient manufacturing of wooden products starting from rawshaped solid wood chunks or laminate panels, allowing efficient processes and improving the overall industrial quality and competiveness of the final product. However, the parameters associated with blade design must be defined with caution, aiming to avoid undesirable cutting performance and consequent relevant detrimental impacts on both processes and equipment. Thus, based on the literature, the present investigation intends to collect and gather a consistent information set regarding the effect of changes in tool design parameters on manufacturing, particularly in the case of wood machining by circular saw blades with reinforced tips. The general outlook provided aims at pointing out essential frameworks and practical guidelines for a better comprehension of the most adequate criteria to be used in the design and choice of tools for each specific manufacturing condition
MACHINE LEARNING TOOLS IN THE ANALYZE OF A BIKE SHARING SYSTEM
Full text linkAdvanced models, based on artificial intelligence and machine learning, are used here to analyze a bike-sharing system. The specific target was to predict the number of rented bikes in the Nova Mesto (Slovenia) public bike share scheme. For this purpose, the topological properties of the transport network were determined and related to the weather conditions. Pajek software was used and the system behavior during a 30-week period was investigated. Open questions were, for instance: how many bikes are shared in different weather conditions? How the network topology impacts the bike sharing system? By providing a reasonable answer to these and similar questions, several accurate ways of modeling the bike sharing system which account for both topological properties and weather conditions, were developed and used for its optimization
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe 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
Full text link“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
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe 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
Full text linkWe 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
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