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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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2024-Jun-20
Clarivate Analytics published the InCites Journal Citations Report for 2023. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.700 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.600.

2023-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2022. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.800 (0.700 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 1.000.

2023-Jun-05
SCOPUS published the CiteScore for 2022, computed by using an improved methodology, counting the citations received in 2019-2022 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2022 is 2.0. For "General Computer Science" we rank #134/233 and for "Electrical and Electronic Engineering" we rank #478/738.

2022-Jun-28
Clarivate Analytics published the InCites Journal Citations Report for 2021. The InCites JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.825 (0.722 without Journal self-cites), and the InCites JCR 5-Year Impact Factor is 0.752.

2022-Jun-16
SCOPUS published the CiteScore for 2021, computed by using an improved methodology, counting the citations received in 2018-2021 and dividing the sum by the number of papers published in the same time frame. The CiteScore of Advances in Electrical and Computer Engineering for 2021 is 2.5, the same as for 2020 but better than all our previous results.

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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: 969 | Views: 3,640

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 661]


[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.

[5] M. Fisz., "Probability theory and mathematical statistics," Warsaw: PWN. 1967.

[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 14] [SCOPUS Times Cited 15]


[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 14] [SCOPUS Times Cited 17]


[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 7] [SCOPUS Times Cited 9]


[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 6] [SCOPUS Times Cited 7]


[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 13] [SCOPUS Times Cited 15]


[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 89] [SCOPUS Times Cited 102]


[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 18]


[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 953] [SCOPUS Times Cited 1081]


[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 200] [SCOPUS Times Cited 232]


[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 10] [SCOPUS Times Cited 10]


[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 8] [SCOPUS Times Cited 8]


[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 24] [SCOPUS Times Cited 29]




References Weight

Web of Science® Citations for all references: 1,359 TCR
SCOPUS® Citations for all references: 2,211 TCR

Web of Science® Average Citations per reference: 59 ACR
SCOPUS® Average Citations per reference: 96 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 2024-12-16 11:03 in 113 seconds.




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


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