Issue 45

L. Zou et alii, Frattura ed Integrità Strutturale, 45 (2018) 53-66; DOI: 10.3221/IGF-ESIS.45.05 65 R EFERENCES [1] Dong, P., Hong J. K., Osage D. et al. (2013). Assessment of Asme’s Fsrf Rules for Vessel and Piping Welds using a New Structural Stress Method, Welding in the World, 47, pp. 31-43.DOI:10.1007/BF03266376. [2] Dong, P. (2001). A structural stress definition and numerical implementation for fatigue analysis of welded joints, International Journal of Fatigue, 23 865-876. DOI:10.1016/S0142-1123(01)00055-X. [3] Dong, P. and Hong J. K. (2013). The Master S-N Curve Approach to Fatigue of Piping and Vessel Welds, Welding in the World, 48, pp. 28-36. DOI:10.1007/BF03266411. [4] Guo, H. G., Zhang, J., Zhang, Y. et al. (2013). Structural Stress Based Fatigue Analysis Method for Plane Steel Gate, Advanced Materials Research, 838-841, pp. 314-318. DOI:10.4028/ www.scientific.net/AMR.838-841.314. [5] Hong, J. K. and Cox, A. (2017). Application of Weld Fatigue Evaluation Procedure for Considering Multi-Axial Stress States Using the Battelle Structural Stress Method, proceedings of the SAE World Congress Experience, WCX™ 17: SAE World Congress Experience. DOI:10.4271/2017-01-0338. [6] Yaghoubshahi, M., Alinia, M. M. and Milani, A. S. (2017). Master S-N curve approach to fatigue prediction of breathing web panels, Journal of Constructional Steel Research, 128, pp.789-799. DOI: 10.1016/j.jcsr.2016.10.015. [7] Jain, A., Paepegem, W. V., Verpoest, I. and Lomov, S. V. (2016). A feasibility study of the Master SN curve approach for short fiber reinforced composites, International Journal of Fatigue, 91, pp. 264-274. DOI:10.1016/j.ijfatigue.2016.06.015. [8] Dong, P., Prager, M. and Osage, D. (2013). The Design Master S-N Curve in ASME Div 2 Rewrite and its Validations, Welding in the World, 51, pp. 53-63. DOI: 10.1007/BF03266573. [9] Pawlak, Z. (1984). Rough classification, International Journal of Man-Machine Studies, 51, pp. 469-483. DOI:10.1006/ijhc.1983.0315. [10]Wen, L. Y., Min, F. and Wang, S. Y. (2017). A two-stage discretization algorithm based on information entropy, Applied Intelligence, 47, pp. 1-17. DOI:10.1007/s10489-017-0941-0. [11] Luo, J., Xue, Q. and Tang, Z. W. (2013). Research on Attribute Discretization for Combat Simulation Data, Computer Simulation, 30, pp. 26-13. (in Chinese) [12] Feng, T., Fan, H. T. and Mi, J. S. (2017). Uncertainty and reduction of variable precision multigranulation fuzzy rough sets based on three-way decisions, International Journal of Approximate Reasoning, 85, pp. 36-58. DOI: 10.1016/j.ijar.2017.03.002. [13] Feng, T. and Mi, J. S. (2016). Variable precision multigranulation decision-theoretic fuzzy rough sets, Knowledge- Based Systems, 91, pp. 93-101. DOI:10.1016/j.knosys.2015.10.007. [14] Rahimi, A., Benini, L. and Gupta, R. K. (2017). From Variability Tolerance to Approximate Computing in Parallel Integrated Architectures and Accelerators, Springer, Switzerland. [15]Kiapour, A., Naghizadeh and Qomi M. (2017), An Approximate Tolerance Interval for the Size-Biased Poisson- Lindley Random Variable, 10, pp. 299-316. DOI:10.18869/acadpub.jss.10.2.299. [16] Tripathy, B. K. and Parida, S. K. (2017). Covering Based Pessimistic Multigranular Approximate Rough Equivalences and Approximate Reasoning, First International Conference on SCI 2016. DOI: 10.1007/978-981-10-5544-7_30. [17] Lin, G. and Li, J. (2011). A Covering-Based Pessimistic Multigranulation Rough Set. 7th international conference on intelligent computing, pp. 673-680. DOI: 10.1007/978-3-642-24553-4_89. [18] Zhang, J., Li T., Da R. and Liu D. (2012). Neighborhood rough sets for dynamic data mining, International Journal of Intelligent Systems, 27, pp. 317-342. DOI:10.1002/int.21523. [19] Shakiba, A. and Hooshmandasl, M. R. (2015). Neighborhood system S -approximation spaces and applications, Knowledge & Information Systems, 49, pp. 749-794. DOI:10.1007/s10115-015-0913-9. [20]Hu, Q., Yu D., Liu J. and Wu C. (2008). Neighborhood rough set based heterogeneous feature subset selection, Information Sciences, 178(18), pp. 3577-3594. DOI:10.1016/j.ins.2008.05.024. [21]Dong, P., Osage, D. A., Prager, M. (2002). Master S-N curve method for fatigue evaluation of welded components, Welding Research Council Bulletin, 47, pp. 41-44. [22] Cruz, J. A. M. P. D., Costa, J. D. M., Borrego, L. F. P. and Ferreira J. A. M. (2000). Fatigue life prediction in AlMgSi1 lap joint weldments, International Journal of Fatigue, 22, pp. 601-610. DOI:10.1016/S0142- 1123(00)00023-2. [23] Beretta, S. and Sala, G. (2004). A model for fatigue strength of welded lap joints, Fatigue & Fracture of Engineering Materials & Structures, 28, pp. 257-264. DOI:10.1111/j.1460-2695.2004.00849.