A NONPROBABILISTIC SET MODEL OF STRUCTURAL RELIABILITY BASED ON SATISFACTION DEGREE OF INTERVAL

In engineering structural systems, two types of uncertainty exist in systems widely. Epistemic uncertainty comes from incomplete information or ignorance while aleatory uncertainty derives from inherent variations. Due to the influence of many uncertainties and vagueness in the available information, all probabilities or probability distributions of random variables are precise known or perfect determination is impossible. For many structural reliability problems lacking information of the uncertain parameters, interval variable is a convenient and effective selection for the uncertainty description. According to this method, this paper suggests a new nonprobabilistic set model of structural reliability based on interval analysis and the satisfaction degree of the interval. The nonprobabilistic reliability of a structure is defined as the satisfaction degree between the stress-interval and the strength-interval. With the nonprobabilistic reliability model presented in this paper, a practical engineering example of the contact fatigue reliability analysis for the gear transmission is calculated and the result is reasonable and reliable. http://dx.doi.org/10.5755/j01.mech.17.1.208

[1]  I. Elishakoff Essay on uncertainties in elastic and viscoelastic structures: From A. M. Freudenthal's criticisms to modern convex modeling , 1995 .

[2]  Dan M. Frangopol Progress in probabilistic mechanics and structural reliability , 2002 .

[3]  Sarp Adali,et al.  Non-probabilistic modelling and design of sandwich plates subject to uncertain loads and initial deflections , 1995 .

[4]  Joseph Edward Shigley,et al.  Mechanical engineering design , 1972 .

[5]  Ramon E. Moore Methods and applications of interval analysis , 1979, SIAM studies in applied mathematics.

[6]  Dan Givoli,et al.  Stress Concentration at a Nearly Circular Hole With Uncertain Irregularities , 1992 .

[7]  V. Kreinovich,et al.  Experimental uncertainty estimation and statistics for data having interval uncertainty. , 2007 .

[8]  Hong-Zhong Huang,et al.  Optimal Design Accounting for Reliability, Maintenance, and Warranty , 2010 .

[9]  Y. Ben-Haim Robust reliability in the mechanical sciences , 1996 .

[10]  Y. Ben-Haim Convex Models of Uncertainty in Radial Pulse Buckling of Shells , 1993 .

[11]  Palle Thoft-Christensen,et al.  Structural Reliability Theory and Its Applications , 1982 .

[12]  Yakov Ben-Haim,et al.  Discussion on: A non-probabilistic concept of reliability , 1995 .

[13]  Y. Ben-Haim A non-probabilistic measure of reliability of linear systems based on expansion of convex models , 1995 .

[14]  Yi Ding,et al.  Fuzzy universal generating functions for multi-state system reliability assessment , 2008, Fuzzy Sets Syst..

[15]  Hong-Zhong Huang,et al.  Reliability assessment for fuzzy multi-state systems , 2010, Int. J. Syst. Sci..

[16]  Guo Shu,et al.  A non-probabilistic model of structural reliability based on interval analysis , 2001 .

[17]  C. Jiang,et al.  Optimization of structures with uncertain constraints based on convex model and satisfaction degree of interval , 2007 .

[18]  Yakov Ben-Haim,et al.  A non-probabilistic concept of reliability , 1994 .

[19]  A. Bargelis,et al.  Structural optimization in product design process , 2010 .

[20]  Kai-Yuan Cai,et al.  Introduction to Fuzzy Reliability , 1996 .

[21]  Alfred Sir Pugsley,et al.  The safety of structures , 1966 .

[22]  Yakov Ben-Haim,et al.  Dynamics of a thin cylindrical shell under impact with limited deterministic information on its initial imperfections , 1990 .