Determination of Parameters of Endurance Limit Distribution Law of Material by the Methods of Nonparametric Statistics and Kinetic Theory of High-Cycle Fatigue

Ksenia Syzrantseva; Vladimir Syzrantsev

doi:10.4028/www.scientific.net/KEM.736.52

Paper Titles

Radiation-Modification Impact on the Filled Polytetrafluoroethylene Structure and Mechanical Strength
p.29

Studying Temperature Effects on Internal Microstresses in Indexable Inserts Made of (Ti,W)C-Co Group Hard Alloys
p.35

Effect of Ageing Process on Properties of Tube Steel under Conditions of Tyumen Region
p.40

Tungsten Surface Erosion by Hydrogen Plasma Irradiation
p.46

Determination of Parameters of Endurance Limit Distribution Law of Material by the Methods of Nonparametric Statistics and Kinetic Theory of High-Cycle Fatigue
p.52

Thermal Properties and Phase Composition of Full-Scale Corium of Fast Energy Reactor
p.58

Influence of the Cobalt Additive on the Flux Cored Wire of System Fe-C-Si-Mn-Cr-Ni-Mo-V
p.63

Mathematical Models for Calculation of Crack Resistance of Composite Materials
p.68

The Formation of Surface Roughness of Piston Rings for the Purpose of Improving the Adhesion of Wear-Resistant Coatings
p.73

HomeKey Engineering MaterialsKey Engineering Materials Vol. 736Determination of Parameters of Endurance Limit...

Determination of Parameters of Endurance Limit Distribution Law of Material by the Methods of Nonparametric Statistics and Kinetic Theory of High-Cycle Fatigue

Abstract:

The paper considers the first developed algorithm of processing the data of specimen life tests based on the kinetic theory of mechanical fatigue and methods of nonparametric statistics. It makes it possible to determine the distribution density function of the material endurance limit. Implementation of the algorithm is illustrated on example of processing the data obtained in fatigue tests of steel 50 specimens.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Key Engineering Materials (Volume 736)

Pages:

52-57

DOI:

https://doi.org/10.4028/www.scientific.net/KEM.736.52

Citation:

Cite this paper

Online since:

June 2017

Authors:

Ksenia Syzrantseva*, Vladimir Syzrantsev

Keywords:

Distribution Density Function, Endurance Limit, High-Cycle Fatigue, Kinetic Theory of Fatigue, Nonparametric Statistics, Parzen-Rosenblatt Estimation, Specimen Life Tests

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] M.N. Saushkin, V.P. Sazanov, V.S. Vakulyuk, Method of determining endurance limit stress of cylindrical specimens made of structural steels by residual stresses of check test piece, PNRPU Mechanics Bulletin. 4 (2014) 178-196.

DOI: 10.15593/perm.mech/2014.4.07

Google Scholar

[2] O.O. Larin, O.I. Trubayev, O.O. Vodka, The fatigue life-time propagation of the connection elements of long-term operated hydro turbines considering material degradation, PNRPU Mechanics Bulletin. 1. (2013) 167-193.

DOI: 10.15593/2224-9893/2014.1.09

Google Scholar

[3] L. Susmel and P. Lazzarin, A bi-parametric Wohler curve for high cycle multiaxial fatigue assessment, Fatigue Fract. Eng. Mater. Struct., 25 (2002) 63-78.

DOI: 10.1046/j.1460-2695.2002.00462.x

Google Scholar

[4] J. Schijve, Fatigue of structures and materials in the 20th century and the state of the art, Int. J. of Fatigue. 25 (2003) 679-702.

DOI: 10.1016/s0142-1123(03)00051-3

Google Scholar

[5] S.V. Serensen, R.M. Shneiderovich, Deformations and rupture criteria under low-cycles fatigue, Experimental Mechanics. 6 (12) (1966) 587-592.

DOI: 10.1007/bf02326826

Google Scholar

[6] S. V. Serensen and N. A. Makhutov, Resistance of a low-carbon steel weld to low-cycle failure as a function of the properties of individual zones, Strength of Materials. 12 (1970) 1239–1247.

DOI: 10.1007/bf01528831

Google Scholar

[7] V.S. Bondar, V.V. Danshin, D.A. Makarov, Mathematical modelling of deformation and damage accumulation under cyclic loading, PNRPU Mechanics Bulletin. 2 (2014)125-152.

DOI: 10.15593/perm.mech/2014.2.06

Google Scholar

[8] N.G. Burago, A.B. Zhuravlev, I.S. Nikitin, Models of multiaxial fatigue fracture and service life estimation of structural elements, Mechanics of Solids. 46(6) (2011) 828-838.

DOI: 10.3103/s0025654411060033

Google Scholar

[9] Ye. K. Pochtenny, Accumulating of fatigue damages, Russ. Eng. Research. 1 (1982) 11-15.

Google Scholar

[10] M.S. Sonawane, C.A. Dhawale, Evaluation and analysis of few parametric and nonparametric classification methods, Proc. 2nd Int. Conf. on Computational Intelligence and Communication Technology (CICT 2016) Article number 7546567, 14-21.

DOI: 10.1109/cict.2016.13

Google Scholar

[11] V.L. Gorokhov, D.V. Kholodnyak, Nonparametric statistics in multivariate time series for cognitive anomaly detection, 19th Int. Conf. on Soft Computing and Measurements (SCM 2016) Article number 7519804, 435-436.

DOI: 10.1109/scm.2016.7519804

Google Scholar

[12] Z.I. Botev, J.F. Grotowski, D.P. Kroese, Kernel density estimation via diffusion, Ann. Stat. 38 (No. 5) (2010) 2916–2957.

DOI: 10.1214/10-aos799

Google Scholar

[13] V. Syzrantsev, K. Syzrantseva, V. Ilinykh, Algorithm for calculation of confidence intervals of low-cycle fatigue curve, Res. J. of Appl. Sci. 10(8) (2015) 334-337.

Google Scholar

[14] V. N. Syzrantsev, K.V. Syzrantseva, V. N. Il'inykh, L. A. Chernaya, Confidence limits for the low-cycle fatigue curve, Russ. Eng. Research. 36(1) (2016) 20-24.

DOI: 10.3103/s1068798x16010196

Google Scholar