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JCR Impact Factor: 0.595
JCR 5-Year IF: 0.661
Issues per year: 4
Current issue: May 2017
Next issue: Aug 2017
Avg review time: 76 days


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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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LATEST NEWS

2017-Jun-14
Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

2017-Apr-04
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2017-Feb-16
With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

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2016-Dec-17
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  1/2014 - 4

Identification of Random Material Parameters in Eddy Current Problems

SLUZALEC, A. See more information about SLUZALEC, A. on SCOPUS See more information about SLUZALEC, A. on IEEExplore See more information about SLUZALEC, A. on Web of Science
 
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Download PDF pdficon (606 KB) | Citation | Downloads: 371 | Views: 1,674

Author keywords
eddy current, inverse problem, finite element method, Monte Carlo method

References keywords
stochastic(7), sluzalec(6), rigid(4), random(4), problems(4), optimization(4), inverse(4), heat(4), forming(4), design(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2014-02-28
Volume 14, Issue 1, Year 2014, On page(s): 25 - 28
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2014.01004
Web of Science Accession Number: 000332062300004
SCOPUS ID: 84894627983

Abstract
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Stochastic identification of material parameters in eddy current problems is presented. A method has been developed for computing eddy currents in materials with random magnetic properties. The electromagnetic field is formulated in terms of finite elements. The numerical solutions for deterministic as well as stochastic direct and inverse problems have been described. The proposed direct and inverse formulation describes probabilistic distributions of material data. As an example the stochastic identification of material data in an infinitely long conductor with a circular cross-section is presented. The stochastic solutions are obtained by application of the Monte Carlo method.


References | Cited By  «-- Click to see who has cited this paper

[1] S. Ang, W. H. Tang, "Probability Concepts in Engineering, Planning and Design," Vol. I, Basic Principles. New York: Wiley; 1975.

[2] H. Kesten, "Random difference equations and renewal theory for products of random matrices," Acta Mathematica, 131, pp. 207-248, 1973.
[CrossRef] [SCOPUS Times Cited 453]


[3] H. J. Larson," Probabilistic Models in Engineering Science," Vols. 1 and 2, New York: Wiley; 1979.

[4] E. Vanmarcke, "Random Fields, Analysis and Synthesis," (2nd edn.). Cambridge, Massachusetts: MIT Press, 1984.

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[6] H. T. Banks, K. Kunisch, "Estimation Techniques for Distributed Parameter Systems," Boston: Birkhauser; 1989.
[CrossRef]


[7] M. Grzywinski, A. Sluzalec, "Stochastic equations of rigid-thermo-viscoplasticity in metal forming process," Int. J. Eng. Sci. 40, pp. 367-383, 2002.
[CrossRef] [Web of Science Times Cited 13] [SCOPUS Times Cited 13]


[8] A. Sluzalec, "Simulation of stochastic metal forming process for rigid-viscoplastic material," Int. J. Mech. Sci. 42, pp. 1935-1946, 2000.
[CrossRef] [Web of Science Times Cited 12] [SCOPUS Times Cited 14]


[9] A. Sluzalec, "Stochastic shape sensitivity in powder metallurgy processing," Applied Mathematical Modelling, 36 (8), pp. 3743-3752, 2012.
[CrossRef] [Web of Science Times Cited 7] [SCOPUS Times Cited 7]


[10] A. Sluzalec, "Stochastic finite elements in optimization of powder metallurgy materials," Mechanics Based Design of Structures and Machines, 40 (1), pp. 33-41, 2012.
[CrossRef] [Web of Science Times Cited 6] [SCOPUS Times Cited 8]


[11] A. Sluzalec, "Stochastic sensitivity in metal forming of rigid-poroplastic materials," Structural and Multidisciplinary Optimization, 45 (1), pp. 139-145, 2012.
[CrossRef] [Web of Science Times Cited 5] [SCOPUS Times Cited 6]


[12] A. Sluzalec, "Temperature field in random conditions," Int. J. Heat Mass Transfer, 34 (1), pp. 55-58, 1991.
[CrossRef] [Web of Science Times Cited 10] [SCOPUS Times Cited 13]


[13] O. C. Zienkiewicz, The Finite Element Method. New York: McGraw-Hill; 1977.

[14] J. E. B. Cardoso, J. S. Arora, "Variational method for design sensitivity analysis in nonlinear structural mechanics," AIAA J., 26, pp. 595-603, 1988.
[CrossRef] [Web of Science Times Cited 82] [SCOPUS Times Cited 91]


[15] E. J. Haug, J. S. Arora, Applied optimal design. New York: Wiley, 1979.

[16] F. Ma, "Approximate analysis of a class of linear stochastic systems with colored noise," Int. J. Eng. Sci., 24, pp. 19-34, 1986.
[CrossRef] [Web of Science Times Cited 14] [SCOPUS Times Cited 16]


[17] K. Mosegaard, A. Tarantola, "Monte Carlo sampling of solutions to inverse problems," Journal of Geophysical Research, 100, pp. 431-447, 1995.
[CrossRef] [Web of Science Times Cited 413]


[18] J. Wang., N. Zabaras, "A Bayesian inference approach to the inverse heat conduction problem," Int. J. Heat Mass Transfer, 47, pp. 3927-3941, 2004.
[CrossRef] [Web of Science Times Cited 99] [SCOPUS Times Cited 116]


[19] M. Ebrahimi., "Monte Carlo Optimization to solve a Two- dimensional inverse heat conduction problem," Australian Journal of Basic and Applied Sciences, 5 (11), pp. 2097-2105, 2011.

[20] V. C. Mariani., L. S. Coelho, "Global optimization of thermal conductivity using stochastic algorithms," Inverse Problems in Science and Engineering, 17 (4), pp. 511-535, 2009.
[CrossRef] [Web of Science Times Cited 9] [SCOPUS Times Cited 9]


[21] I. Pokorska, Re-identification problems in forming of rigid-visco-poroplastic materials, International Journal for Numerical Methods in Engineering, 73, 8, 1077-1093, 2008.
[CrossRef] [Web of Science Times Cited 6] [SCOPUS Times Cited 6]


[22] W. M. Rucker, K. R. Richter, "Calculation of two-dimensional eddy current problems with the boundary element method," IEEE Trans.Mag., 6, pp. 2429-2431, 1983.
[CrossRef] [Web of Science Times Cited 22] [SCOPUS Times Cited 26]




References Weight

Web of Science® Citations for all references: 698 TCR
SCOPUS® Citations for all references: 778 TCR

Web of Science® Average Citations per reference: 30 ACR
SCOPUS® Average Citations per reference: 34 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2017-06-26 17:46 in 108 seconds.




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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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